© 2019
BETHANIE CAVALIER
ALL RIGHTS RESERVED
ATTACHMENT THEORY: COMPARING THE RELATIONSHIP BETWEEN
ATTACHMENT HIERARCHIES AND LIFE SATISFACTION AMONG YOUNG-
OLD AND MID-OLD ADULTS
A Dissertation
Presented to
The Graduate Faculty at The University of Akron
In Partial Fulfillment
of the Requirements for the Degree
Doctor of Philosophy
Bethanie A. Cavalier
December, 2019
ATTACHMENT THEORY: COMPARING THE RELATIONSHIP BETWEEN
ATTACHMENT HIERARCHIES AND LIFE SATISFACTION AMONG YOUNG-
OLD AND MID-OLD ADULTS
Bethanie A. Cavalier
Dissertation
Approved: Accepted:
Advisor Department Chair Charles A. Waehler, Ph.D. Paul E. Levy, Ph.D.
Committee Member Interim Dean of the College Jennifer T. Stanley, Ph.D. Linda M. Subich, Ph.D.
Committee Member Dean of the Graduate School Harvey L. Sterns, Ph.D. Chand Midha, Ph.D.
Committee Member Date Ingrid K. Weigold, Ph.D. _
Committee Member Varunee Faii Sangganjanavanich, Ph.D.
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ABSTRACT
Bowlby (1982) postulated that the attachment hierarchy, or the rank-order of attachment figures used to fulfill attachment needs, was vital for adaptation from “the cradle to the grave” (p. 208). Subsequent empirical literature suggested the presence of predictable developmental trends in the size (number of attachment figures) and types of attachment figures (i.e., sibling, friend) included in the attachment hierarchy across the lifespan.
Investigations of the presence of shifts across the lifespan in preferences for different attachment figures has been accomplished through the identification of the primary attachment figure. Studies commonly identified the primary attachment figure by calculating a mean composite score. Copious research suggests that both the size of the attachment hierarchy and the primary attachment figure correlate with emotional well- being in younger adulthood. However, less attention has been paid to the relationships between the attachment hierarchy and cognitive aspects of well-being (i.e., life satisfaction). The current study focused on four attachment figure types (i.e., family, peers, romantic partners, and “other”), and expanded upon attachment theory research by investigating the relationships between age, the size of the attachment hierarchy, the primary attachment figure, and life satisfaction between the young-old (ages 65-74) and mid-old (ages 75-84). Support was found for a relationship between the size of the attachment hierarchy and life satisfaction in the young-old. The primary attachment figure was not found to relate with the size of the attachment hierarchy or levels of life
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satisfaction. Results indicated that the distributions of the primary attachment figure did not change from the young-old to the mid-old.
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TABLE OF CONTENTS Page LIST OF TABLES ...... ix
CHAPTER
I. INTRODUCTION ...... 1
Bowlby’s Attachment Theory ...... 2
Developmental Trends in the Attachment Hierarchy Across the Lifespan ...... 3
The Attachment Hierarchy and Well-Being ...... 6
Calls for Research and Implications ...... 10
Epochs in Older Adulthood ...... 15
Well-Being ...... 16
Conclusions and Research Questions ...... 19
II. A REVIEW OF THE LITERATURE ...... 20
An Introduction to Research on Aging ...... 21
Epochs in Older Adulthood ...... 24
Counseling Psychology and the Attachment Hierarchy ...... 30
Calls for Research on the Attachment Hierarchy ...... 37
Attachment Theory ...... 41
The Origins and Development of Attachment Theory ...... 41
Contemporary Attachment Theory ...... 47
The Attachment Hierarchy ...... 54
v The Size of the Attachment Hierarchy ...... 62
Types of Attachment Figures in the Attachment Hierarchy ...... 69
Measuring Attachment Type and its Hierarchy ...... 77
Life Satisfaction ...... 86
Conceptualization of Life Satisfaction ...... 86
Life Satisfaction and Older Adults ...... 90
The SWLS and the LSI-A ...... 93
Conclusion and the Present Study ...... 100
Hypotheses ...... 101
III. METHODS ...... 106
Participants ...... 106
Measures ...... 111
Demographic Questionnaire ...... 111
Attachment Network Questionnaire ...... 115
Satisfaction with Life Scale (SWLS) ...... 119
The Life Satisfaction Index-A (LSI-A) ...... 122
Procedures ...... 126
Hypotheses ...... 126
IV. RESULTS ...... 132
Data Cleaning ...... 132
Data Preparation for Hypotheses ...... 134
Descriptive Statistics: The Attachment Hierarchy and Life Satisfaction ...... 136
Main Statistical Analyses ...... 141
vi Hypothesis 1 – How does the size of the attachment hierarchy relate to levels of life satisfaction? ...... 141
Hypothesis 2 – Does the size of the attachment hierarchy differ between the young-old and mid-old? ...... 145
Hypothesis 3– Does the primary attachment figure impact the size of the attachment hierarchy? ...... 146
Hypothesis 4– Does the primary attachment figure on has impact levels of life satisfaction? ...... 150
Hypothesis 5 – Do distributions of each primary attachment figure type differ between the young-old and the mid-old? ...... 154
Summary of Results ...... 155
V. DISCUSSION ...... 157
Review of the Study ...... 158
A Review of the Research Questions, Hypotheses, and Results ...... 161
Hypothesis 1 - How does the size of the attachment hierarchy relate to levels of life satisfaction? ...... 161
Hypothesis 2 – Does the size of the attachment hierarchy differ between the young-old and mid-old? ...... 166
Hypothesis 3 – Does the primary attachment figure impact the size of the attachment hierarchy? ...... 171
Hypothesis 4 – Does the primary attachment figure on has impact levels of life satisfaction? ...... 176
Hypothesis 5 – Do distributions of each primary attachment figure type differ between the young-old and the mid-old? ...... 179
Implications for Research ...... 181
Implications for Clinical Practice ...... 186
Study Limitations and Strengths ...... 191
Conclusion ...... 194
vii REFERENCES ...... 196
APPENDICES ...... 230
Appendix A: Demographics Questionnaire ...... 231
Appendix B: Attachment Network Questionnaire ...... 235
Appendix C: Satisfaction with Life Scale= ...... 238
Appendix D: Life Satisfaction Index A ...... 239
Appendix E: IRB Approval ...... 242
Appendix F: Cover Letter ...... 243
Appendix G: Debriefing Statement ...... 244
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LIST OF TABLES
Table Page
2.1. List of Studies Which Investigated Epochs in Older Adulthood ...... 29
2.2. A Summary of the Primary Attachment Figures in Adulthood ...... 59
3.1. Age and Subjective Age Distribution Statistics for the Total Sample ...... 113
3.2. Demographic Variables for Total Sample and by Age Group ...... 114
4.1. Chi-Square Analyses with Marital Status in the Young-Old and Mid-Old Groups ...... 135
4.2 Chi-Square Analyses with Employment in the Young-Old, Mid-Old, and Total-Sample ...... 135
4.3. Partial Correlations between Age, Attachment Hierarchy Size, and Life Satisfaction for the Total Sample ...... 137
4.4 Average Attachment Hierarchy Size in the Young-Old, Mid-Old, and Total Sample ...... 137
4.5. Attachment Figure Distribution for the 1st Attachment Figure Listed on Each ANQ Question ...... 138
4.6. Primary Attachment Figure Distributions Assessed Through Mean Composite Scores ...... 139
4.7. Life Satisfaction Measure Scores ...... 141
4.8. Tests of Hypothesis 1: Correlations and Partial Correlations between Age, Attachment Hierarchy Size, and Life Satisfaction for the Total Sample ...... 143
4.9. Tests of Hypothesis 1: Correlations between Age, Attachment Hierarchy Size, and Life Satisfaction for the Young-Old and Mid-Old ...... 143
4.10 Tests of Hypothesis 1: Partial Correlations between Age, Attachment Hierarchy Size, and Life Satisfaction in the Young-Old and Mid-Old ...... 144
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4.11. Tests of Hypothesis 2: Independent T-test for Attachment Hierarchy Size Between the Young-Old and Mid-Old Groups ...... 146
4.12. Average Size of the Attachment Hierarchy based on Primary Attachment Figure Type (N = 170) ...... 147
4.13. Tests of Hypothesis 3: Levene’s Statistics Tests for Homogeneity of Variance .... 148
4.14. Tests of Hypothesis 3: ANOVA’s for Primary Attachment Figure Type and Size in the Young-Old and Mid-Old Groups ...... 148
4.15. Tests of Hypothesis 3: ANCOVA’s Between Primary Attachment Figure Type and Attachment Hierarchy Size in the Young-Old, Mid-Old, and Total Sample ...... 149
4.16. Tests of Hypothesis 4: MANOVA’s Between Primary Attachment Figure Type And Life Satisfaction in the Young-Old, Mid-Old, and Total Sample ...... 152
4.17. Tests of Hypothesis 4: MANCOVA’s Between Primary Attachment Figure Type and Life Satisfaction in the Young-Old, Mid-Old, and Total Sample ...... 154
4.18. Tests of Hypothesis 5: Final Chi-Square Analysis Testing Primary Attachment Figure Distributions between the Young-Old and Mid-Old Groups ...... 155
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CHAPTER I
INTRODUCTION
No variables, it can be held, have more far-reaching effects on personality development than have a child’s experiences within his family: for, starting during the first months in his relation with his mother figure, and extending through the years of childhood and adolescence in his relations with both parents, he builds up working models of how attachment figures are likely to behave towards him in any of a variety of situations; and on those models are based all his life expectations and therefore all his plans, for the rest of his life (Bowlby, 1973, p. 418).
The current chapter introduces a rationale for examination of Bowlby’s (1969,
1982) attachment hierarchy as it relates to life satisfaction between two epochs of older adulthood. The current chapter begins with an overview of Bowlby’s attachment theory, with a subsection on the developmental trends across the lifespan, and a subsection on the attachment hierarchy as it relates to well-being. The next section provides a summary of calls for research on the attachment hierarchy and potential implications that such a study could have, with a subsection to review the epochs in older adulthood and a subsection that outlines the concept of well-being. The final section provides a brief summary of the needs for future research and the aims of the current study.
1 Bowlby’s Attachment Theory
John Bowlby contributed profoundly to psychology’s conceptualization of people and attachment bonds (Merz & Consedine, 2012; Mikulincer & Shaver, 2007; Pitman &
Sharfe, 2010). In fact, Bowlby’s attachment theory has been the most commonly cited theory of attachment since Freud’s (1926) conceptualization of attachment as an instinctual drive came into question in the 1930’s (Bretherton, 1992). Bowlby’s work laid a foundation upon which the works of numerous researchers (Cicirelli, 2010; Doherty &
Feeney, 2004; Litwin & Shiovitz-Ezra, 2010; Trinke & Bartholomew, 1997; Yildiz,
2016) have established substantial contributions to theories of human development.
At the core of Bowlby’s attachment theory is the assertion that individuals develop relationships with attachment figures to maximize the fulfillment of three primary attachment needs (i.e., safety, security, proximity; Mikulincer & Shaver, 2007).
Bowlby (1988) explained that attachment needs can also be thought of as needs “for protection, comfort, and support” (p. 121). Humans are naturally inclined to seek proximity to familiar, comforting attachment figures in times of threat, pain, or need
(Mikulincer & Shaver). Attachment needs ultimately provide the driving force which motivates an individual to seek support from others.
Over time, the pattern of availability and sensitivity of attachment figures to one’s needs forms into an internalized schema which assists in the streamlining of information, allowing quick judgments about the probability of others meeting attachment needs
(Merz & Consedine, 2012; Mikulincer & Shaver, 2007). Notably, access to open and responsive significant others affects well-being across the lifespan.
2 Bowlby (1960, 1982) theorized that individuals develop relationships with multiple attachment figures, and termed the presence of multiple attachment figures an
“attachment hierarchy”—a collection of individuals which are sought in times of need or distress (Bowlby, 1982, p. 34). Bowlby claimed that the unconscious process of rank- ordering multiple attachment figures relies upon preferences for whom to seek.
Developmental Trends in the Attachment Hierarchy across the Life Span
Bowlby claimed that attachment theory applies to individuals from “the cradle to the grave” (Bowlby, 1969, p. 208). The lack of research on attachment hierarchies in older adulthood leaves much to be learned about the unique developmental trends of the attachment hierarchy in, and across, older adulthood. Because Bowlby did not address the specific ways that old age would impact the size of the attachment hierarchy or the types of attachment figures which would be included (Cicirelli, 2010; Mikulincer & Shaver,
2007), numerous researchers have insisted that more research is needed before attachment theory can be said to be truly applicable across the entire lifespan (Cicirelli,
2010; Fiori, Consedine, & Magai, 2008; Doherty & Feeney, 2004; Trinke &
Bartholomew, 1997).
Developmental trends are present in the attachment hierarchy across younger periods of life. More specifically, the size and types of attachment figures included in the attachment hierarchy undergo predictable transitions as one ages. The number and types
(i.e., brother, mother) of figures in the attachment hierarchy change throughout life.
Researchers often measure this by identifying whom an individual seeks first or which attachment figure meets the most attachment needs (i.e., the primary attachment figure).
3 The developmental trends found in research are in line with tenants of attachment theory. Bowlby (1979) theorized that attachment behaviors and bonds were “present and active throughout the life cycle” (p. 39). Soon after, Bowlby (1982) purported that attachment figures influence one’s ability to adapt to the environment. The fulfillment of attachment needs provides a secure base for individuals to explore and adapt to the environment: the size and types of figures included in the attachment hierarchy influence the fulfillment of attachment needs, which impact well-being. Secure relationships with positive attachment figures can also soothe feelings of anxiety and fear (Joeng et al.,
2017), which are critical to well-being.
Individuals unconsciously regulate the instinct to meet attachment needs through primitive, reflex-like behavior and the creation of complex attachment hierarchies
(Bowlby, 1980b; Bretherton, 1992; Doherty & Feeney, 2004). When something distressing occurs, or an attachment figure is unavailable, adjustment is needed to continue to meet attachment needs. The stage of development and life circumstances also influence change in the attachment hierarchy—individuals include new and eliminate old attachment figures for maximum adaptation to the environments (Cicirelli, 2010). The ultimate function of attachment processes is to maximize survival and procreation
(Bretherton, 1992) in a complex world. Thus, changes in attachment figures, or transferals of attachment functions to different figures, is inevitable and dynamic throughout the lifespan (Bowlby, 1980b; Cicirelli, 2010; Trinke & Bartholomew, 1997).
The ability to construct schema about the environment and one’s own actions in it are what make such complex attachment hierarchies possible.
4 Attachment theory initially focused on the period of infancy and toddlerhood and on the bond between a mother and her infant. It was not until the 1970’s that researchers began to focus on attachment hierarchies across adulthood (Bretherton, 1992; Doherty &
Feeney, 2004). At that time, research began focusing on identifying the attachment types that best fulfilled attachment needs. Since then, research has begun to explore developmental patterns across the lifespan.
Pitman and Sharfe (2010) found that infants initially seek the fulfillment of needs through one primary attachment figure; commonly the mother. Toddlers and children
(approximately ages 6 months to 12 years) develop multiple attachment bonds: including parents, grandparents, siblings, neighbors, and/or daycare staff (Mikulincer & Shaver,
2007). Adolescents and young adults show affinity for peers and romantic partners over parents (approximately ages 13-17 and 18-35; Fraley & Davis, 1997; Freeman & Simons,
2018; Hazan & Zeifman, 1994, 1999; Trinke & Bartholomew, 1997). The number of attachment figures appears to grow steadily until middle adulthood, when it peaks
(approximately ages 36-64; Doherty & Feeney, 2004; Trinke & Bartholomew, 1997) and eventually declines in older adulthood (approximately age 65 and above). Cicirelli (2010) reported that primary attachment figures in older adulthood included spouses, children,
God, and deceased spouses. It would be natural for the developmental shifts that have been found in the younger years to continue throughout older adulthood: what was needed was a study investigating any changes in the size and types of attachment figures included in the attachment hierarchy between different periods of older adulthood.
In summary, research on the size and types of attachment figures in the attachment hierarchy in older adulthood is pivotal because of Bowlby’s claim that
5 attachment theory applies to all individuals, regardless of age. To date, there is some support for the presence of developmental trends in the attachment hierarchy in older adulthood: older adults include attachment figures such as spouses, children, and intangible figures (i.e., God, a deceased spouse; Cicirelli, 2010). More research was needed on the manifestation of developmental trends of the size and types of attachment figures in, and across, older adulthood.
The Attachment Hierarchy and Well-Being
This section provides an outline of literature which supports the relationship between the attachment hierarchy and well-being. A few studies have investigated the impact of the attachment hierarchy on well-being in childhood and adulthood. However, the main goal of this section is to review research that has explored this relationship in older adulthood. There are four influential studies which included older adults that the current study expanded upon that are reviewed in detail at the end of this section.
Attachment theory would interpret the relationship between the size of the attachment hierarchy and well-being as a survival technique to the better adapt to complications in meeting attachment needs. In line with attachment theory, the size of the attachment hierarchy positively correlates with general well-being in childhood
(Melkman, 2017) and negatively correlates with depression in young adulthood (Iyer,
Jetten, Tsivrikos, Postmes, & Haslam, 2009). In older adulthood, size positively correlates with spiritual well-being (Fukui, Starnino, & Nelson-Becker, 2012), general well-being (Jurkuvėnas, Zamalijeva, Pakalniškienė, Kairys, & Bagdonas, 2017), and life satisfaction (Wang, 2016). Spiritual well-being has been found to associate with one’s ability to find meaning in life, which is vital in the later stages of life, and could have a
6 crucial impact on life satisfaction. What this study aimed at assessing was the identification of the primary attachment figure and its impact on the life satisfaction in older adulthood.
The types of attachment figures in the attachment hierarchy also impact well- being throughout the life span. There are few studies on the types of attachment figures or the primary attachment figure and well-being. In adolescence, the inclusion of the mother, father, and peers in the attachment hierarchies is associated with higher levels of life satisfaction (Yildiz, 2016). In older adulthood the inclusion of friends correlated negatively with mortality (Litwin, 2007), and anxiety (Litwin & Shiovitz-Ezra, 2010).
Older adults with a large variety of attachment figure types (i.e., romantic partner, friend) had less loneliness (Litwin & Shiovitz-Ezra, 2010). Further investigation could provide guidance on how to improve the attachment hierarchy and/or increase life satisfaction for older adults, or how to improve the attachment hierarchy to better fulfill attachment needs.
With evidence of developmental trends in the younger years, it becomes logical to wonder how developmental trends manifest in older adulthood, as well as be curious about any changes that occur within older adulthood. The later stages of life, or older adulthood, can last 35 or more years. Theoretical speculation is more prevalent than empirical evidence at this point (Ainsworth et al., 1978; Antonucci, Akiyama, &
Takahashi, 2004; Bowlby, 1969, 1977; Doherty & Feeney, 2004; Pitman & Sharfe, 2010;
Trinke & Bartholomew, 1997), and a study was needed to explore the extant attachment hierarchies in older adulthood, and the relationship between the attachment hierarchies and life satisfaction.
7 There are four influential studies which focused on both older adulthood and the attachment hierarchy. These studies were influential due to their focus on the attachment hierarchy in relation to well-being, and the size and types of people included in the attachment hierarchy. Litwin and Shiovitz-Ezra (2010) found that persons aged 65 and older (N = 1,462) had five categories of attachment hierarchies: diverse, friend, congregant, family, and restricted based on the types of attachment figures listed. Well- being was measured through questions about loneliness, anxiety, and happiness and concluded that individuals with more diversity of attachment figure types reported lower levels of loneliness and higher levels of social opportunities. One limitation of this study was that Litwin and Shiovitz-Ezra (2010) failed to identify the primary attachment figure.
To improve upon Litwin and Shiovitz-Ezra’s (2010) methodology, the present study proposes to focus instead on the identification of the primary attachment figure and assess well-being through the cognitive construct of life satisfaction.
Cicirelli (2010) completed the second influential study with a sample of older adults aged 60-99 (N = 80; Mage = 77.8 years). He reported that spouses and adult children were the most common attachment figures to be named, followed by intangible attachment figures (i.e., God, deceased spouse). One limitation of Cicirelli (2010) was the use of an author-created measurement of the attachment hierarchy. The current study will improve upon this work by using the Attachment Network Questionnaire (ANQ; Trinke
& Bartholomew, 1997), which is a standardized, peer-reviewed methodology with good psychometrics. The ANQ measures the size, order of preference, and the primary attachment figures in the attachment hierarchy. More information about the ANQ is provided in a future section.
8 The third influential study was completed by Wang (2016). Individuals aged 61-
71 (N = 314) with larger numbers of attachment hierarchies had higher levels of life satisfaction. Wang used author-created questions about the number of people in the attachment hierarchy, a multidimensional scale of perceived support, and the Satisfaction with Life Scale (SWLS; Diener, Emmons, & Larson, 1985). A mediating variable of perceived support was found. The current study aims at expanding upon the work of
Wang (2016) by investigating the influence the types of primary attachment figures reported in older adulthood, and the relationship these have with life satisfaction.
A fourth influential study analyzed the attachment hierarchy (a.k.a. social network) according to the convoy model (Antonucci, 2001; Kahn & Antonucci, 1980).
The convoy model captures the lifespan and life course nature of social relations with an emphasis on emotional closeness. Similar to attachment theory, the convoy model pays special attention to the characteristics of attachment figures (i.e., relationship type, age, sex, frequency of contact, proximity). Fiori, Smith, and Antonucci (2007) completed their study with a sample of individuals aged 70-103 (N = 516). An interview consisted of author-created questions about the social network and affective/physical aspects of well- being, as well as a consecutive circle network-mapping procedure (Antonucci, 1986).
Epochs of older adulthood were compared: results indicated that satisfaction with attachment figures depended on the number and types of attachment figures, the amounts
(and types) of support provided, and the age group one was in, which was consistent with the convoy model. What was needed was a study that used peer-reviewed, standardized measures with good psychometric properties, consideration of the primary attachment figure, and the use of life satisfaction to assess the cognitive aspects of well-being.
9 This section reviewed research that explored the relationship between the attachment hierarchy and well-being. Additional review and critique of Litwin and
Shiovitz-Ezra (2015), Cicirelli (2010), Wang (2016), and Fiori et al. (2007) will be provided in chapter two. The next section will introduce calls for research and outline the implications of the current study.
Calls for Research and Implications
Respectable research expands upon previous research, and the present study is not unique in this aspect. The previous sections outlined the need for future research that examines attachment theory and well-being in older adulthood. Fiori and colleagues
(2008) credit the ideas of Baltes (1996) when he stated that “understanding the complex nature of preferences for interpersonal dependency and autonomy in old age, as well as their implications for health and well-being, may enable practitioners to aid older adults in negotiating the tasks of balancing these seemingly conflicting needs” (p. 710).
Furthermore, Trinke and Bartholomew (1997) explained that a major limitation of attachment theory thus far was its inability to be generalized to older adults. This is especially true for the attachment hierarchy, and research on older adults could help to expand research generalizability.
Numerous studies have made calls for research on the attachment hierarchy in older adulthood (Doherty & Feeney, 2004; Fiori et al., 2008; Trinke, 1995; Trinke &
Bartholomew, 1997). Trinke and Bartholomew (1997), for instance, suggested that the importance placed on different types of “attachment figures may be, at least in part, a function of the age of the participants. In the future it would be fascinating to look at the
10 evolution of attachment hierarchies…throughout the life cycle” (p. 623). The need for research on the attachment hierarchy in older adulthood is well-established.
In addition to exploration of the attachment hierarchy in older adulthood, Cicirelli
(2010) made a specific recommendation for the inclusion of a measure of well-being.
Cicirelli also made the recommendation for the exploration of differences between groups of different ages within older adulthood. A more detailed review of the concept of epochs within older adulthood will be presented in a future section. Cicirelli (2010) speculated that research with older adults ages 65 and above could help psychologists to better understand both the reduction in size and the dynamic process of including new attachment figures and eliminating some of the old as one attempts to maximize adaptation in old age.
Trinke (1995) made the specific recommendation of the use of the ANQ (Trinke
& Bartholomew, 1997) with a wider variety of ages and life cycle stages. The ANQ is a
14-item questionnaire assessing traits of the attachment hierarchy. The ANQ identifies up to 15 attachment figures, captures the preferred order of the hierarchy, and allows for the identification of the primary attachment figure. Characteristics about attachment figures are gathered. The ANQ has been used in previous psychological research on the attachment hierarchy in young adulthood (Freeman & Simons, 2018; Pitman & Sharfe,
2010; Rowe & Carnelley, 2005; Trinke & Bartholomew, 1997), adulthood, (Doherty &
Feeney, 2004), and older adulthood (Doherty & Feeney, 2004). This section will now transition to a review of the benefits that could be provided from future research on the attachment hierarchy across different epochs of older adulthood.
11 First and foremost, the current study could increase awareness for scientists, practitioners, and the general public regarding the impact of the attachment hierarchy on well-being and emphasize the presence of gains in the later stages of life. Evidence for gains have been found in multiple studies on healthy aging, including areas of emotional well-being and social functioning (English & Cartensen, 2014). The present study could also aid in the identification of any special concerns—especially patterns in which older adults relate to others (Consedine & Magai 2003; Fiori et al., 2008; Kafetsios &
Sideridis, 2006). In addition, research that compares and contrasts multiple age ranges in older adulthood could help to increase awareness that later periods of older adulthood are not simply continuations of the patterns found in the young-old.
Likewise, Kirchmann and colleagues (2013) and Litwin and Shiovitz-Ezra (2010) suggested that future studies on the attachment hierarchy and well-being in older adulthood could provide further guidance for the development of interventions to improve well-being and/or relationships. Kirchmann and colleagues (2013) supported the notion of research aiding the development of intervention, and suggested that research uncovering the processes by which the attachment hierarchy relates to well-being has the potential for providing valuable insight into the development of effective intervention strategies for maintaining or enhancing the well-being of older adults. There is currently a dearth of information about effective interventions for the improvement of the attachment hierarchy. Such research could eventually influence the implementation of effective interventions with older clients who could benefit from adjusting the attachment hierarchy or improving well-being.
12 Notably, research suggests that improvements in the security of an individual’s schema about relationships can result from residential therapy in adolescence (Gur, 2006) and time-limited dynamic psychotherapy in adulthood (Travis, Bliwise, Binder, & Horne-
Moyer, 2001). Gur and Travis and colleagues concluded that improvements resulted from the interpersonal nature of the theory-driven techniques and the experience of successful interpersonal problem-solving in the therapy setting. Gur emphasized the therapist’s ability to act as a secure base. Such interventions would perhaps impact the attachment hierarchy as well or assist with a reassessment of the benefits of current and potential relationships. Investigation of these possibilities are needed. If the present study finds a connection between the attachment hierarchy and life satisfaction, research should test current interventions and/or guide the development of new techniques to maximize the benefits older adults receive from the number and/or types of attachment figures in the attachment hierarchy.
Another possibility for future research is the development of a cost-effective measurement of the attachment hierarchy to assess for risk-factors such as low numbers of attachment figures or low diversity of attachment figures, allowing clinicians to assist in goal-setting for the expansion of social activities, increased exposure to different types of people, or reconnections with family. At this point, the development of interventions continue to require further exploration for better guidance.
Moreover, a focus on gains in older adulthood is consistent with the goals of positive psychology, which focuses on core strengths, positive cognitions, and positive emotions to treat pathology. Positive psychology asserts that intervention can and should increase both well-being and life satisfaction (Gelfin, Zohar, & Lev-Ari, 2018; Layous &
13 Lyubomirsky, 2012). In a meta-analysis conducted by Sin (2009), studies with samples anywhere from childhood to age 60 indicated that intentional techniques that cultivate positive feelings, positive behaviors, and positive cognitions significantly enhanced well- being. Sin explained that the benefits of positive psychology interventions increased with age, and suggested that clinicians working with older adults should consider positive psychology interventions. Similarly, Ranzijn (2002) argued that positive psychology views the older adult as a resource rather than a burden to society, and that clinicians who maximize the person-environment fit and focus on strengths can effectively assist older adults with increasing both emotional and cognitive well-being.
Finally, future studies on the attachment hierarchy and life satisfaction in older adulthood could extend research on the convoy model (Kahn & Antonucci, 1980), and/or socioemotional selectivity theory (SST; Carstensen, 2006). Both are multidisciplinary approaches that offer conceptualizations of the attachment hierarchy that could augment those of attachment theory. The convoy model sees well-being as the result of the functionality of the social network. Well-being is a reflection of the network’s ability to provide support and reduce stress. SST, on the other hand, conceptualizes the reduction in numbers of attachment figures as one ages as the result of selective pruning of the social network in the service of emotion-regulation (Carstensen, Gross, & Fung, 1998; English
& Carstensen, 2014). Older adults are motivated to focus on emotionally meaningful and satisfying experiences (and significant others) due to limited time left in life: one intentionally spends more time with emotionally satisfying partners (Carstensen et al.,
1998). There is overwhelming empirical evidence supporting the affective components of
SST, yet one could argue that satisfaction with the social network could also be captured
14 with cognitive measures of life satisfaction. The convoy model and SST both offer explanations that could aid in the interpretation of the current study’s results.
In summary, this section provided a review of pertinent calls for research that were made by researchers of attachment theory. Work with older adults was needed, especially with the attachment hierarchy. Specific recommendations were made for research on the attachment hierarchy as measured by the ANQ, between different epochs in older adulthood, and as related to well-being. Finally, benefits of a future study on the attachment hierarchy and well-being were reviewed. The next section outlines the concept of epochs within older adulthood, as this was one of the recommendations for future research that the current study investigates.
Epochs in Older Adulthood
The goal of identifying developmental shifts across older adulthood is a new frontier of research on aging, yet few studies have used such an approach. This section briefly reviews empirical and theoretical literature that explored the concept of epochs within older adulthood.
Comparisons between unique age ranges of older adulthood are arguably as important as they are in early childhood (Johnson & Barer, 1997). Trinke (1995) reasoned that the exploration of the different epochs of older adulthood may yield age differences in the primary attachment figures that fulfill attachment needs. Psychological literature on aging indicated that this could be accomplished by distinguishing between discrete, but coherent, older adult lifespan groups (Cicirelli, 2006; Johnson & Barer,
1997; Orlinsky & Ronnestad, 2015), yet there is a lack of consensus on age-ranges that provide meaningful epochs within older adulthood.
15 The idea of comparing and contrasting epochs of older adulthood originated with
Neugarten’s (1974) seminal work which challenged the belief that age directly correlated with decreased functionality. She delineated between two age ranges: the young-old (ages
55-74) and the old-old (ages 75 and above), which Cicirelli (2006) replicated. Other research on epochs in older adulthood vary widely in the number and age ranges of epochs used.
Theoretical speculation suggests the following age ranges: the young-old (ages
65-74) and mid-old (ages 75-84). Some researchers include an epoch for the old-old as well. To reduce the risk of confounding variables and focus on an initial demonstration of age differences across two different epochs in older adulthood, the present study will test for differences between the young-old and mid-old as was done in Neugarten (1974) and
Cicirelli (2006).
In summary, the current study will use previous research on epochs of older adulthood, as well as theoretical speculation, as a methodological model. Age-ranges for the young-old (65-74) and mid-old (75-84) were used. The next section reviews the concept of well-being and proposes the use of a cognitive measure of well-being.
Well-Being
One’s individual attachment hierarchy has the potential to influence the fulfillment of attachment needs, which impact well-being. Historically, there have been different approaches to measuring well-being. This section will provide a brief overview of theory and empirical research of well-being and outline the measurements this study proposes to use.
16 Early attempts to examine well-being occurred in the 1950s and 1960s and took two approaches: the first considered well-being a function of social participation
(Neugarten, Havighurst, & Tobin, 1961). The second defined well-being in terms of subjective perceptions about the past and/or present. The second approach led to a variety of scales measuring subjective well-being. Today, consideration is required for the distinction between affective, or emotional, and cognitive, or judgmental, aspects of well- being (Diener, 1984; Veenhoven, 1996, 2013). Each is equally important and impactful, but cognitive aspects have been neglected within attachment theory research, and the cognitive aspect of well-being is more in line with healthy aging.
Affective measures are popular in attachment theory research (i.e., depression, anxiety, loneliness; Iyer et al., 2009; Litwin, 2007; Litwin & Shiovitz-Ezra, 2010;
Melkman, 2017). The cognitive aspect, on the other hand, has been less widely studied, especially with the attachment hierarchy. The cognitive component of well-being was conceptualized by Andrews and Withey (1976) as life satisfaction. Life satisfaction compares expectations and perceptions of outcomes for salient components of life such as social situations, relationships, and self-worth (Kane & Kane, 2000); making it a sensible choice for the current study’s empirical question. Life satisfaction is a similar, yet unique aspect of well-being (McKnight, Huebner, & Suldo, 2002), and is in line with quests to identify healthy aspects of aging.
Life satisfaction is a concept that demonstrates both stability and variability across time. About 50% of life satisfaction’s stability can be attributed to stable personality traits (Lykken & Tellegen, 1996; Lucas, 2008). Long term changes are attributed to changes in personal values and/or priorities, and behavioral choices: reported
17 that across periods as long as 10-25 years, 10% of people made large personality changes
(50% of the percentile ranks or more); 20% made moderate personality changes (33.3% or more); and approximately 33% made small personality changes (25% or more; Headey et al., 2010, 2013; Headey & Muffels, 2017). Lastly, individual differences exist in the volatility of life satisfaction over time. The biggest impact on volatility included narcissism and perceived health (Headey & Muffels, 2017).
The Satisfaction with Life Scale (SWLS: Diener et al., 1985) is one of the most popular scales of life satisfaction within psychological research (Oishi, 2006). Of more importance, it has good psychometric properties. The SWLS is a Likert scale with five questions ranked on a seven-point scale. The SWLS has been used in studies on the attachment hierarchy in adolescence (Yildiz, 2016), young adulthood (Diener et al.,
1985), and older adulthood (Diener et al., 1985; Litwin & Shiovitz-Ezra, 2010).
Another measure that has been widely used in studies of aging is the Life
Satisfaction Index A (LSI-A; Neugarten et al., 1961). The LSI-A has good psychometric properties and assesses five components of life satisfaction (zest, resolution and fortitude, congruence, self-concept, and mood tone). The LSI-A has 20 items which focus on the past, present, and future; answered on an agree/disagree format. The LSI-A was generated specifically for use with older adults and has been validated in subsequent research (Faegerstroem, Lindwall, Berg, & Rennemark, 2012; Wallace & Wheeler,
2002).
This section outlined the difference between affective and cognitive components of well-being. The concept of life satisfaction would be helpful in expanding attachment theory, especially in regard to the attachment hierarchy. The SWLS and the LSI-A were
18 used in the current study based on their good psychometric properties. The next section will review the research questions that are pertinent to the present study’s empirical question.
Conclusion and Research Questions
The present study expanded attachment theory research by examining the impact of both the size and types of attachment figures in the attachment hierarchy on life satisfaction between the young-old and the mid-old. Particular attention was paid to the influence of the primary attachment figure on life satisfaction. As recommended, this was accomplished through the utilization of ANQ (Trinke & Bartholomew, 1997) which is a measure that’s utility has been shown in older adulthood (Doherty & Feeney, 2004). The concept of life satisfaction is a cognitive component of well-being that is consistent with both positive psychology and studies on aging that wish to highlight healthy and successful aging and the SWLS and the LSI-A (Neugarten et al., 1961). The goal of the present study was to extend the investigation on Bowlby’s (1969, 1982) assertion that aspects of the attachment hierarchy impact well-being across the entire lifespan. The current study explored the impact of the attachment hierarchy on life satisfaction between the young-old (ages 65-74), and the mid-old (ages 75-84).
19
CHAPTER II
A REVIEW OF THE LITERATURE
People are much greater and much stronger than we imagine, and when unexpected tragedy comes…we see them so often grow to a stature that is far beyond anything we imagined. We must remember that people are capable of greatness, of courage, but not in isolation…They need the conditions of a solidly linked human unit in which everyone is prepared to bear the burden of others (Bowlby, 1988, p. 322).
Chapter two elaborates upon the important components underlying the empirical questions investigated in the current study. Specifically, this chapter provides a rationale for the present study examining the relationship between Bowlby’s (1969, 1982) attachment hierarchy and life satisfaction in older adulthood. This chapter begins with a section outlining the importance of research on older adulthood. In this first section, the evolution of research on aging is reviewed. Subsections cover the topics of the different epochs of older adulthood and recommendations made by researchers for future research on attachment hierarchies in older adulthood. The second section provides information pivotal to the present study: attachment theory. In the second section I provide an explication of attachment theory as an historic forbear of the field of psychology, followed by subsections which address the following: 1) the concepts of contemporary attachment theory; 2) the attachment style across the lifespan; 3) the attachment hierarchy
20 across the lifespan; 4) the primary attachment figure; 5) the size of the attachment hierarchy, 6) the types of people in the attachment hierarchy; and; 7) the measurements being proposed for use in the present study. The third section addresses the concept of life satisfaction. Three subsections in section three review the conceptualization of life satisfaction, life satisfaction in older adulthood, and the measures that the present study proposes to use. The fourth and final section concludes this chapter with a summary of the research questions and hypotheses of the current study.
An Introduction to Research on Aging
The increased interest in aging that is occurring within psychological research coincides with an opportunistic time in history: life expectancies are longer, and the population of older adults is expanding rapidly. In 2009, the world had 767 million individuals over age 60 (von Humboldt, & Leal, 2017). The population of older adults in the United States aged 65 and above increased from roughly three million in 1900 to nearly 35 million in 2000, and it is projected to triple to approximately 60 million by
2060 (Fishman, 2010; Wilmoth & Longino, 2007). Between 2010 and 2030, the proportion of older adults will increase by approximately 3% per year (DESA, 2010).
Psychologists interested in aging are increasingly attending to the roles of older adults in society (Himes & Fang, 2007; Walston et al., 2006). Of particular interest to the present study are the social aspects of aging and their impact on life satisfaction. The literature suggests that social aspects of aging are of particular interest to researchers, and that guidance is offered through multidisciplinary conceptual frameworks with goals of examining the impact of social influences on the life course (Achenbaum, 1995; Wilmoth
& Ferraro, 2007). Researchers often report the intention of identifying aspects of healthy
21 and/or successful aging in order to conceptualize the ways one can maximize the quality of life throughout the later stages of life. Notably, older adults are not always on the receiving end of social exchanges (Eggebeen, 1992; Wilmoth & Longino, 2007) and variables interacting with the social lives of older adults need to be investigated in order for psychologists to develop interventions that could improve well-being in older adulthood. With that in mind, research was needed to investigate the social lives of older adults: the present study aided in this aspect by exploring the attachment hierarchy’s impact on life satisfaction. Additionally, psychology needs to continue examining older adulthood to determine if the exciting findings on the plasticity and adaptivity of the young-old can apply to individuals who are living beyond this age-range (Baltes &
Smith, 2003).
For a long time, aging was viewed pessimistically as a time of decline and detachment from others (Himes & Fang, 2007). These opinions continue to color people’s views on aging today. However, preliminary work was done by Metvhnikoff
(1903) who spurred staunch questioning of the inevitability of old age as a period of decline and instigated research focusing on the process of healthy aging. Since then, research has shown that older adults continue to make meaningful contributions to society. Support has been found for the high cognitive and physical functioning that occurs well into later life (Cole, 1993; Neath & Surprenant, 2007; Shock et al., 1984).
The stability of cognitive and physical functioning into older adulthood enables psychologists to conceptualize a life course based on an individual’s needs and interests, and not age in and of itself (Himes & Fang, 2007; Riley & Riley, 1994).
22 There has been a recent influx of psychological literature on the needs of older adults and how those needs are met (Himes & Fang, 2007), as well as how well society is meeting the needs of the older adult population (Cherlin, 2004). Further research was needed to assist in the exploration of the social needs and interests of older adults in order to better understand how these processes impact older adults’ well-being, the functioning of society (Himes & Fang, 2007; Riley & Riley, 1994), and the efficacy of interventions aiming to improve quality of life in older adulthood. Older adults continue to play roles in their families and communities, and interest in social processes as they play out across the lifespan has guided much of the recent research on the social lives of older adults
(Himes & Fang, 2007).
Applied researchers interested in aging often work out of a scientist-practitioner model, believing that interventions most likely to be useful are well grounded in theory and lab-based research findings (Sterns & Camp, 1998). The scientist-practitioner model is in line with the values of counseling psychology, and provides guidance for the current study. Additionally, much of the research on healthy aging consists of cross-sectional designs, where a group of individuals from one age range is compared to another group of individuals from another age range (Freund & Isaacowitz, 2013; Wilmoth & Longino,
2007). Cross-sectional designs have been informative when identifying areas of difference between older and younger adults, and could potentially be used for comparing different epochs of older adulthood to examine for any inter-group differences. Freund and Isaacowitz (2013) suggested the use of cross-sectional designs may be more beneficial for those interested in age-related differences which occur within one developmental period, because extreme age comparisons are often confounded with
23 cohort differences. Notably, the present study’s goal is to examine the attachment hierarchy across two different age-groupings within older adulthood. It is important to also note the methodological limitations of cross-sectional designs: selective sample attrition, confounding of age, cohort, and historical time influences on development
(Baltes, Cornelius, & Nesselroade, 1977; Freund & Isaacowitz, 2013; Schaie, 1965).
Epochs of Older Adulthood
The current section reviews the history of, and current best practices of studies on differences between epochs of older adulthood. There is currently a lack of consensus for meaningful groupings within older adulthood, which is understandable because there are an uncountable number of variables which can impact both the physical and mental aging processes. The present study measured both chronological and subjective age in order to compare and contrast age ranges for similarities and changes in the attachment hierarchy and life satisfaction.
According to Johnson and Barer (1997) comparisons between the unique age ranges within a life stage are as important in older adulthood as they are in early childhood when development is paramount. To explore age-related changes across older adulthood, it is useful to distinguish between a set of discrete, but coherent, epochs within older adulthood (Baltes & Smith, 2003). Baltes and Smith considered research on the division of older adulthood into groups which can be compared as one of the new frontier topics of psychological research. Indeed, such studies have shown that later periods of older adulthood are not simply continuations of the patterns identified in the early stages
(Baltes, 1997; Baltes & Smith, 2003; Freund & Isaacowitz, 2013). Unfortunately, there is currently no overarching developmental theory which provides age criteria for dividing
24 older adulthood into meaningful age groups. Many researchers use ill-defined delineations of young, middle, and old within older adulthood (Freund & Isaacowitz,
2013). Yet the problem remains: for consistency and reproducibility, identifying set end points for different segments of older adulthood is important.
Identifying a chronological age at which older adulthood begins is challenging because age-ranges are dynamic and moving targets which can evolve and vary (Baltes &
Smith, 2003; Freund & Isaacowitz, 2013). Debate about the age at which older adulthood begins initially postulated the beginning of older adulthood to begin around age 55-60
(Cameron, 1969; Drevenstedt, 1976; MIDMAC, 1999; Neugarten, 1974). Soon after, research identified that this age cutoff was considered too young when retirement and subjective experiences of aging were considered, and that individuals classified old age as beginning around the age of 65 (Cameron, 1969; Drevenstedt, 1976). Use of the chronological age of 65 years is currently the most common age supported in the literature for the beginning of older adulthood (Anstey, Hofer, & Luszcz, 2003; Cicirelli,
2006, 2010; Dixon et al., 2004; Zizza, Ellison, & Wernette, 2009). Remarkably, if older adulthood begins around the age of 65, the periods of older adulthood could last up to 35 years or more, making older adulthood lengthy enough to explore transitions which occur within this life stage.
Lifespan developmental researchers are committed to the exploration of both continuity and change (Antonucci, Akiyama, & Merline, 2001; Baltes & Smith, 2003), and the goals of the current study are in line with this commitment. Changes that occur in the attachment hierarchy between the ages of 65-74 and 75-84 could assist psychologists with better understanding how attachment figures, and the preference one has for whom
25 to seek when distressed, impact the quality of life across older adulthood. Moreover, comparisons based on one’s subjective age could yield insight into meaningful ways to establish age-ranges for which to compare attachment across older adulthood.
Research on aging has established that the ages confining older adulthood are somewhat vague and flexible. Changes found between chronological age groups can be contingent on the cohort to which one belongs (Freund & Isaacowitz, 2013; Staudinger &
Bluck, 2001). Defining the confines of older adulthood becomes even more complex when considering research suggesting testing for within-period differences. Freund and
Isaacowitz (2013) articulated this problem well: college student samples usually span around seven years, while older adult samples can span around 25-30 years. There is much heterogeneity to be explored, as there is much variability within older adulthood
(Dannefer, 2003).
Exploration of older adulthood for discrete but coherent age ranges to be used to test for within-group differences in older adulthood is underway. The trend of delineating between the different epochs of older adulthood originated with the work of Bernice
Neugarten (1974), who published an article which introduced the distinctions between young-old (ages 55-74) and the old-old (ages 75 and above) in an attempt to demonstrate that age does not directly correlate with decreasing functionality in older adults.
Comparing the young-old with the old-old then became normative methodology for initial studies exploring the aging process (Baltes & Smith, 2003; Neugarten, 1974), although the label that is applied to the ages often varies. For example, one researcher could call an age group from 75 to 84 years-old the mid-old and another may label it as the old-old. The identification of distributions allowed Neugarten (1974) and subsequent
26 researchers to show that the young-old were more similar to their middle-adulthood peers than to the old-old.
Studies on within-group differences have generally supported the need for future comparisons within older adulthood. Age has correlated positively with losses in regards to new learning (Baltes & Kliegl, 1992; Kliegl, Smith, & Baltes, 1989), rates of dysfunction and morbidity (Smith & Baltes, 1997), loneliness, and positive affect: age correlated negatively with life satisfaction and aging satisfaction (Smith & Baltes, 1997;
Smith, Freund, Kunzmann, & Baltes, 2002). Speculation suggests that such age differences could be due to changes in intentionality, autonomy, independence, identity, and social connectedness (Baltes & Smith, 2003). To compensate for such changes, society may need to increase the supportive role of psychological resources, including the use of (and access to) empirically-supported techniques (Baltes & Smith, 2003).
One approach for comparing groups within older adulthood has been to distinguish between the young-old, mid-old, and old-old (Anstey, Hofer, & Luszcz, 2003;
Cicirelli, 2002, 2006; Dixon et al., 2004; Johnson & Barer, 1997; Orlinsky & Ronnestad,
2015; Zizza, Ellison, & Wernette, 2009). This method appears straightforward, but there are no established age-ranges to operationalize the young-old, mid-old, and old-old in research. Therefore, researchers are left to their own devices to determine the labels of each group and the age ranges within each group, and multiple age ranges have been used. See Table 1 for an overview of six studies that examined differences between different epochs in older adulthood.
Results from the studies in Table 1 supported the presence of group differences in cognition, memory, and vision (Antsety et al., 2003; Dixon et al., 2004), fear of death
27 and/or the unknown (Cicirelli, 2002b, 2006), feelings of security, flexibility, tolerance, and acceptance of personal limitations (Orlinsky & Ronnestad, 2015), and rates of water consumption (Zizza, Ellison, & Wernette, 2009). Table 1 demonstrates the lack of consensus about meaningful age ranges for research on epochs in older adulthood, likely because chronological age lacks substantial meaning in-and-of itself. Dixon and colleagues (2004) speculated that 10-year age groupings may be arbitrary when testing for differences between the different epochs of older adulthood.
Along the lines of Baltes and Smith (2003), Cicirelli (2006), and Neugarten
(1974), the present study will utilize the theoretical epochs of the young-old (65-74) and mid-old (75-84) to investigate similarities and differences in the attachment hierarchy and life satisfaction between two groups within older adulthood. To explore a potentially more meaningful relationship for distinguishing between meaningful age ranges to delineate epochs of older adulthood, the present study will also measure subjective age and analyze the difference between attachment hierarchies between groups based on subjective age by asking participants to report the age that they feel.
The majority of studies with older adults utilize convenience sampling (Anstey,
Hofer, & Luszcz, 2003; Cicirelli, 2002, 2006; Dixon et al., 2004; Johnson & Barer, 1997;
Orlinsky & Ronnestad, 2015; Zizza, Ellison, & Wernette, 2009). The number of participants in each epoch shows considerable differences which one researcher speculated as parallel to the bell-shaped curve of the population (Orlinsky & Ronnestad,
2015). The present study aims at using a convenience sample of older adults, but for statistical analyses purposes seeks to have equal size in each age group.
28 Table 2.1. List of Studies Which Investigated Epochs in Older Adulthood Number of Year of N Size Age Range Epochs Definitions of Authors Publication Epochs Antsey, 2003 1,243 65-84 3 70-74 (n = 461) Hofer, & 75-79 (n = 461) Luszcz 80-84 (n = 461) Cicirelli 2002b 109 70-97 5 70-74 (n = 27) 75-79 (n = 22) 80-84 (n = 27) 85-89 (n = 22) 90-97 (n = 11) Cicirelli 2006 192 60-84 3 60-74 (n = 132) 75-84 (n = 60) Dixon et 2004 530 54-84 3 54-64 (n = 148) al. 65-74 (n = 181) 75-84 (n = 71) Fiori, 2007 516 70-103 2 70-84 (n = 255) Smith, & 85-103 (n = 256) Antonucci Lu, Lum, 2016 372 60-80+ 3 60-69 (n = 96) & Lou 70-79 (n = 153) 80+ (n = 116) Orlinsky 2015 1,102 60-90 3 60-66 (n = 698) & 70-74 (n = 324) Ronnestad 75-90 (n = 80) Zizza, 2009 2, 054 65-85+ 3 65-74 (n = 1,105) Ellison, & 75-84 (n = 746) Wernette 85+ (n = 203)
The current section reviewed literature which measured group differences within the period of older adulthood and showed that methodologies for operationalizing group age ranges varies widely. The present study compared and contrasted the two theoretical age groups of the young-old (ages 65-74) and the mid-old (ages 75-84) as an initial investigation on attachment hierarchies and life satisfaction between two groups within older adulthood. Considering the exploration of different groups within older adulthood
29 for attachment process differences, Trinke (1995) reasoned that the exploration of the different epochs of older adulthood could yield age differences in the primary attachment figures chosen to fulfill attachment needs. Additionally, a measure of subjective age was used in order to further explore older adulthood for meaningful age groups to compare.
The next section reviews the impact that the current study could have on the field of psychology.
Counseling Psychology and the Attachment Hierarchy
Research suggests that a study investigating the relationship between the attachment hierarchy and life satisfaction in older adulthood could have a broad impact on psychology. There is the potential for guidance of future research directions, increased practitioner awareness of the impact of the attachment hierarchy, direction for the development of empirically-based therapeutic techniques, and the expansion of theory.
Studies on the social needs of older adults could help psychologists advocate for social policy changes which prevent discrimination based on age while also advancing psychological vitality.
Perhaps the most succinct collection of possible implications that research on the attachment hierarchy could have on psychology was published by Litwin, and Shiovitz-
Ezra (2010). These authors distinguished practical implications which could result from extending the knowledgebase about the attachment hierarchy. First, the awareness of the impact of different types of attachment figures in the attachment hierarchy, as well as their impact on life satisfaction, may help sensitize gerontological practitioners to the various interpersonal environments that older adults are exposed. Second, research on the attachment hierarchy could potentially highlight the need for creating practitioner-
30 friendly ways to measure the attachment hierarchy in a cost-effective and efficient manner. Third, any findings of the characteristics of the attachment hierarchy (i.e., size, types of attachment figures included, the order of preference of attachment figures) could serve as a basis for the establishment of an effective risk-assessment measurement, or as a means for determining the efficacy of interventions. For example, Litwin, Shiovitz, and
Ezra (2010) classified attachment hierarchies according to the types of attachment figures identified and found that having the majority of attachment figures of one type (i.e., friends, family, varied) in the attachment hierarchy predicted less social capital, smaller attachment hierarchies, and lower levels of sociability. These findings would suggest that transitions in the classification of one’s attachment hierarchy (i.e., from family to varied) could possibly be used in the future to gauge the effectiveness of interventions aimed at increasing the diversity of attachment figures.
In regard to theory, the present study could assist practitioners with conceptualizing clients. The current study could potentially strengthen the bridge between psychological research on attachment theory and gerontological research on healthy aging. Depending on the results of the current study, it was hypothesized that a positive correlation would be found between the size of the attachment hierarchy and life satisfaction, especially for the young-old. Although Bowlby failed to postulate the reasons for developmental changes within older adulthood, the convoy model (Kahn &
Antonucci, 1980) could augment attachment theory to provide an explanation: the relationship could be due to the probability of a larger number of attachment figures better fulfilling attachment needs or functional needs. Conversely, if results indicate a positive correlation between the size of the attachment hierarchy and life satisfaction,
31 socioemotional selectivity theory (Carstensen, 2006) could explain this relationship as a conscious or unconscious reduction in the size of the attachment hierarchy to better control 1) access to emotional or instrumental support; 2) the quality of attachment bonds; and 3) exposure to emotionally rewarding interactions.
Regarding the assessment and development of therapeutic techniques which improve the attachment hierarchy in older adulthood, old age has much latent potential that awaits activation through better social and psychological means (Baltes & Smith,
2003). Bowlby (1988) viewed the therapeutic relationship as one way to improve an adult client’s attachment processes:
The therapist strives to be reliable, attentive, and sympathetically responsive to his patient’s exploration, and so far as he can, to see and feel the world through his patient’s eyes, namely to be empathic (p. 152).
Therapists’ ability to become a secure base for clients can lead to positive results due to the automatic projection of healthier working models onto new relationships (Bowlby,
1988).
Research uncovering processes by which the attachment hierarchy is related to life satisfaction may also provide valuable insights into the development of effective intervention strategies for maintaining or enhancing the life satisfaction of older adults
(Kirchmann et al., 2013). Notably, the security of the attachment style has been linked to better success with the maintenance of social ties (Gillath, Johnson, Seluk, & Teel, 2011).
Studies suggest that intensive residential therapy in adolescence (Gur, 2006) and time- limited dynamic psychotherapy in adulthood (Travis, Bliwise, Binder, & Horne-Moyer,
2001) can positively impact the security of the attachment style in younger adults.
However, there is thus far no empirical evidence of the impact therapy could have on the
32 attachment hierarchy. There is also some evidence that the security of attachment styles in adolescence can be improved through residential treatment (Muller & Rosenkranz,
2009; Tasca, Balfour, Ritchie, & Bissada, 2007; Zuroff & Blatt, 2006). Unfortunately, impact of the security of the attachment style has not yet been investigated for any influence on the attachment hierarchy. One could speculate that increases in the attachment style could result in an improvement in the security of relationships with others, which would arguably effect the attachment hierarchy. For instance, the security of the attachment bond between a therapist and his or her client tends to increase the attachment style of the client, which could theoretically impact bonds with others
(Parpottas & Draghi-Lorenz, 2015). However, such speculation requires empirical exploration in order to gain knowledge about the relationship between attachment security and the attachment hierarchy, and more investigation into the impact different therapeutic approaches have on the attachment hierarchy could be fruitful.
Upon consideration of therapeutic interventions with older adults, Lawton (1977) stated that a counseling psychologist is often faced with a clinical situation where an older adult is experiencing stress due to the presses of the environment. As the problem is explored, it can become evident that the attachment figures in one’s life (particularly family members) impact the functioning of the older adult (Sterns, Weis, & Perkins,
1984). Specifically, if attachment bonds with family members are identified as an area which needs intervention, a practicing psychologist could provide psychoeducation, individual counseling, group counseling, family therapy, or referrals to social support groups to strengthen these bonds (Sterns, Weis, & Perkins, 1984).
33 In a study on the adaptation of interpersonal psychotherapy for use with an older adult population, Heisel, Duberstein, Talbot, King, and Tu (2009) reported that adults aged 60 and above (N = 12) demonstrated that current evidence-based therapeutic interventions effective with adults can be effectively adapted for use with older adults.
Additionally, a meta-analysis of well-being interventions found well-being to be amenable to effective interventions to improve the quality of life for older adults (Okun,
Olding, & Cohn, 1990).
Similar studies have shown that attachment processes may be amenable to change in older adulthood. For instance, Sabir, Henderson, Kang, and Pillemer (2016) measured the impact of eight weeks of two-hour, outpatient group therapy using attachment- focused integrative reminiscence interventions which were adapted from the Life Review and Experiencing Form (LREF). The LREF provided a structure for the sessions to guide participants toward each of Erikson’s developmental stages (beginning with trust vs mistrust and ending with integrity vs. despair) as well as toward the narratives that individuals had formed about attachment. The intent was to assist older adults with achieving Erikson’s idea of integrity—a retrospective sense that one’s life had purpose and meaning, which has been reportedly vital for well-being in the later stages of life
(Haight & Hendrix, 1995; Hearn et al., 2012; Molinari, Cully, Kendjelic, & Kunik, 2001;
Molinari & Reichlin, 1984; Nygren et al., 2005). Measures of well-being (self-rated health, number of doctor’s visits, and scales for sense of coherence, self-efficacy, self- acceptance, generativity, depression, and perceived stress) were taken at sessions one, eight, and six months after treatment. Results indicated that depression and perceived stress decreased in the treatment group, which suggests that interventions on attachment
34 processes in older adulthood may be a viable way to improve the attachment hierarchy in older adulthood.
Furthermore, studies on the strength of attachment bonds with different types of attachment figures suggests that strong attachment bonds with family can buffer the effects of criminal victimization (Holtfreter, Riesig , & Turanovic, 2017). Victims were found to have significantly less depression and behavioral avoidance coping than individuals without strong familial ties, which suggests that familial ties may prove to be quite influential on satisfaction with life. In another study, increased interaction with one’s neighbors (or community) decreased isolation and increased social inclusion
(Burns, Jean-Pierre, & Demaris, 2012), suggesting that for individuals who lack other types of relationships, interactions with individuals in one’s neighborhood could also improve the attachment hierarchy.
A focus on gains in older adulthood is consistent with positive psychology’s emphasis on core strengths, positive cognitions, and positive emotions to treat pathology.
In a meta-analysis conducted by Sin (2009), studies with samples anywhere from childhood to age 60 indicated that intentional techniques that cultivate positive feelings, positive behaviors, and positive cognitions significantly enhanced well-being. Sin explained that the benefits of positive psychology interventions increased with age, but more exploration of this trend is needed to determine if it continues throughout older adulthood.
Regarding specific interventions for older adults that effectively improved well- being, research supports the efficacy of positive psychology interventions. Ranzijn (2002) argued that this could be due to positive psychology’s view that older adults are a
35 resource and not a burden on society: He speculated that practitioners maximizing the person-environment fit and focusing on strengths could more effectively assist older adults with increasing both emotional and cognitive well-being. Support has been found for Ranzijn’s speculations: Cantarella, Borella, Merigo, and De Beni (2017) reported improvements in well-being and memory for nursing home residents whom completed a three-week psychological well-being intervention (the authors highlighted the particular improvements in cognitive well-being). Another study specified that an 8-week positive psychology intervention was effective at reducing stress and feelings of tiredness, and increasing feelings of calmness in older adults in senior centers (Friedman et al., 2019).
Similar results were reported by Greenawalt, Orsega-Smith, Turner, Goodwin, and Rathie
(2019), who found improvement in well-being with community-dwelling older adults who completed an 8-week positive psychology intervention (Friedman et al., 2017). The results of these studies suggest that it may be possible for psychologists to create an intervention regarding the attachment hierarchy that could improve life satisfaction in older adulthood.
Combined with the findings from Weissman, Markowitz, and Klerman (2000) and
Litwin and Shiovitz-Ezra (2010), the above findings provided direction for future research to focus on therapeutic interventions for older adults which improve the attachment hierarchy and life satisfaction of older adults. Ideally, the findings of the present study would also have the effect of increasing the awareness of practicing psychologists to be cognizant of the impact of the attachment hierarchy on the life satisfaction of older adults, then attend to the attachment hierarchy more effectively.
36 Research on aging has shown that interventions can be in the form of expanding and changing the way in which knowledge about aging can be applied to the design of services (Fisk & Rodgers, 2002). Psychologists have the ability to advocate for changes in social policy, which is another reason why psychology needs to further explore attachment hierarchies and life satisfaction in older adulthood. Science and social policy can be powerful sources for positive change and social justice (Baltes & Smith, 2003;
Max-Planck-Forum, 2002). Social policy and aging-friendly support structures, as well as preventative and corrective health policies, can include psychological strategies of life management (Baltes, 2003). Systematic changes can include ways for older adults to have greater ability for selecting, optimizing, and compensating for age-related losses
(Baltes & Carstensen, 1996; Freund & Baltes, 2000; Marsiske, Lang, & Baltes, 1995).
Psychologists need to advocate for policies which support increasing older adults’ opportunities to meet their needs, fulfill their desires, and maintain as much independence as possible (Neugarten, 1974). Advocacy is also needed in the area of the development of social services designed to prevent unnecessary decline in feelings of self-worth and dignity: social interaction and social contributions will be important (Neugarten, 1974).
Baltes and Smith (2003) recommended for psychologists to invest scientific and policy efforts to contribute to a better culture of old age. Society as a whole need to consider the question of how to allocate resources to the different subgroups: a vital society requires age fairness in resource allocation (Baltes & Smith, 2003; Neugarten, 1974). Calls for
Research on the Attachment Hierarchy
Several studies that made calls for research on attachment theory in older adulthood stressed overcoming the major limitation of the current literature on the
37 attachment hierarchy: the lack of attention paid to the unique period of older adulthood
(Doherty & Feeney, 2004; Fiori et al., 2008; Trinke & Bartholomew, 1997). Fiori and colleagues (2008) explained that the older adult population had special concerns, and suggested that understanding the way older adults relate to others could be the key to understanding issues such as social support and isolation (Kafetsios & Sideridis 2006), health service utilization (Consedine, Magai, & King 2004), and, more generally, successful aging (Consedine & Magai, 2003; as cited in Fiori et al., 2008).
There have also been recommendations for the investigation of differences within the years of older adulthood (Cicirelli, 2010; Doherty & Feeney, 2004; Freeman &
Simons, 2018; Trinke, 1995). Many researchers label any individual above age 65 as an older adult and make broad assumptions based on this life stage. However, research and theory have suggested that there can be significant differences within older adulthood.
The benefits of delineating between different epochs of older adulthood has been postulated to include the exploration of differences in elders’ needs to connect with others, and the need to understand the developmental trends which occur within the period of older adulthood (Cicirelli, 2010; Doherty & Feeney, 2004; Trinke, 1995). The exploration of within-stage age differences could lead to insight into the order in which individuals seek various persons to fulfill attachment needs, and the impact this has on life satisfaction.
Trinke and Bartholomew (1997) made the specific recommendation of the use of the ANQ (Trinke & Bartholomew, 1997) with a wider variety of ages and stages of life in order to extend attachment theory’s understanding of the attachment hierarchy across the entire lifespan. Trinke and Bartholomew (1997) created the ANQ with a sample of young
38 adults, and more research could aim at identifying the impact of the different types of attachment figures in older adulthood. Trinke and Bartholomew identified several strengths of the ANQ: the ability to identify the primary attachment figure in the attachment hierarchy; the inclusion of attachment figures regardless of the security of the relationship; and the ability to distinguish between attachment figures and individuals with whom one has frequent contact. The ANQ has been used in samples of adolescents
(Rowe & Carnelley, 2005), young adults (Freeman & Simons, 2018; Pitman & Sharfe,
2010; Trinke & Bartholomew, 1997), and older adults (Doherty & Feeney, 2004).
Research has shown that the ANQ has utility in older adulthood (Doherty & Feeney,
2004) for individuals between ages 61-90. Participants in Doherty and Feeney (2004) had an age range from 16-90 (N = 812), and the mean age was 35 years. Doherty and Feeney
(2004) failed to test for age differences between the group of older adults and younger adults, or between groups within older adulthood. A study exploring the differences in attachment hierarchies between epochs of older adulthood could help psychologists to better conceptualize the developmental trends in the attachment hierarchy, as well as the impact of these trends between different groups of older adults.
Another specific recommendation from the literature suggested the inclusion of a measure of well-being (Cicirelli, 2010). The Satisfaction with Life Scale (SWLS: Diener et al., 1985) has been used successfully in research with older adult samples (Lopez-
Ortega, Torres-Castro, & Rosas-Carrasco, 2016; Lovereide & Hagell, 2016), as well as research on the attachment hierarchy (Yildiz, 2016) and attachment styles (Nabi & Rizvi,
2015; Shahrazad, Kadir, Omar, & Halim, 2015; Sumer & Knight, 2001; Temiz &
Comert, 2018; Yoo & Kim, 2015). The SWLS has good psychometric properties:
39 Notably, the SWLS has been validated for use across multiple ethnicities (Esnaola,
Benito, Antonio-Agirre, Freeman & Sarasa, 2017; Jovanovic & Brdar, 2018; Lopez-
Ortega, Torres-Castro, & Rosas-Carrasco, 2016; Maroufizadeh, Ghaheri, Samini, &
Ezabadi, 2016; Wang, Hu, & Xu, 2017). One limitation of the research that used the
SWLS with older adults is that these studies failed to investigate the impact of the primary attachment figure on life satisfaction. A study on the primary attachment figure and life satisfaction between epochs of older adulthood could help psychologists to identify potential risk factors for low life satisfaction and identify any differences in the impact of the primary attachment figure between the young-old and mid-old, which could assist in a better conceptualization of both relationships and life satisfaction across the later stages of life.
Another measure of well-being that has good psychometric properties is the Life
Satisfaction Index A (Neugarten et al., 1961). The LSI-A was developed specifically for older adults and has shown utility since its creation in 1961 (Donnenworth, Guy, &
Norvell, 1978; Faegerstroem, Lindwall, Berg, & Rennemark, 2012; Neugarten et al.,
1961; Subasi & Hayran, 2005). The LSI-A has shown utility across multiple ethnicities
(Donnenworth, Guy, & Norvell, 1978; Faegerstroem, Lindwall, Berg, & Rennemark,
2012; Subasi & Hayran, 2005) and is commonly used to investigate healthy aging. One limitation of the LSI-A is that it has not yet been used to investigate the relationship between life satisfaction and the attachment hierarchy. The current study plans on comparing and contrasting levels of life satisfaction measured on the SWLS and the LSI-
A in two epochs of older adulthood. The use of two measures of life satisfaction will
40 afford greater insight into life satisfaction as well as how it is impacted by the attachment hierarchy.
In conclusion, this section reviewed the development of aging research, the potential impact the present study will have on the field of psychology, and the calls for research with older adults that were made by researchers examining attachment theory.
Recommendations that were particularly influential for the present study include
Cicirelli’s (2010) recommendation for exploration of differences in attachment hierarchies between epochs within older adulthood, and Trinke and Bartholomew’s
(1997) recommendation for the use of the ANQ to investigate the entire lifespan. The present study also used the LSI-A and compared it with the SWLS. The next section will review the origins and development of attachment theory.
Attachment Theory
The Origins and Development of Attachment Theory
In order to fully understand the importance of the present study in the context of contemporary counseling psychology, it is necessary to visit the historical underpinnings of the psychology field. Prior to the 1930’s, attachment was conceptualized as a process involving unconscious and conscious instinctive drives which led individuals to form attachment bonds (Freud, 1926). In the 1930’s, however, studies on Freudian theory began to question the ability of Freud’s theory to fully explain the attachment bond.
Specifically, studies were published which suggested that infants demonstrate preferences for certain attachment bonds (Harlow & Zimmerman, 1959; Lorenz, 1935, in Bowlby,
1980). These studies led to doubts in Freudian theory. Around this time, Bowlby was inspired by a book about “a small-scale model of external reality…to react in much
41 fuller, safer, and more competent manner to emergencies” (Craik, 1943, p. 61; as cited in
Bretherton, 1985), and Piaget’s (1953) theory of cognitive development which detailed his conceptualization of cognitive development in terms of assimilation, accommodation, and the incorporation of new information (Mikulincer & Shaver, 2007). All of these events eventually led to Bowlby’s search for a new explanation for the attachment bond.
Attachment theory was founded upon the work of both John Bowlby and Mary
Ainsworth, who—as a result of massive parental losses due to WWII—were originally interested in maternal loss, personality development, and the security of attachment bonds. Until his seminal work in the early 1950’s, Bowlby was a psychiatrist who worked with children. Bowlby’s original works were the result of his observations of the importance of the relationships between children and their mothers (Bowlby, Robertson,
& Rosenbluth, 1952). A few years later Bowlby (1958) postulated that attachment could be considered in an evolutionary context in which the mother, or caregiver, provides safety and security of the infant (Bretherton, 1992). Bowlby later explained that attachment was conceptualized as a process which enhanced one’s chances of survival, a bond which developed with a person outside the self, someone who was perceived to be stronger and/or wiser than the self (Bowlby, 1977). Soon after, Ainsworth et al. (1978) incorporated the idea that attachment was a type of affectionate bond formed between individuals.
Bowlby (1977) explained that attachment bonds initially develop in infancy, but clarified that attachment bonds are able to be formulated throughout the lifespan. In fact,
Bowlby’s attachment theory claimed that the attachment system was influential “from the cradle to the grave” (1969, p. 208). However, the primary periods of life which research
42 focused on continued to be infancy and childhood until interest in adulthood and older adulthood became prevalent beginning in the 1970’s.
The initial work of Bowlby and Ainsworth began independently. Ainsworth completed a study in Uganda and conducted the first empirical study on infant-mother attachment patterns, and Bowlby published three classic papers (and two unpublished works) which have been termed the ‘blueprint’ of attachment theory: “The Nature of the
Child’s Tie to His Mother” (1958), “Separation Anxiety” (1959), and “Grief and
Mourning in Infancy and Early Childhood” (1960; as cited in Bretherton, 1992). In the
1950’s Bowlby and Ainsworth joined forces. Ainsworth’s knowledge of innovative methodology contributed greatly to Bowlby’s ideas, making it possible to finally expand the theory further (Bretherton, 1992). One of their first publications together has been printed in four volumes entitled “Determinants of Infant Behavior (1961, 1963, 1965, and
1969, edited by Brian Foss, as cited in Bretherton, 1992).
In 1963, Ainsworth’s work led to the creation of the Strange Situation (Ainsworth
& Wittig, 1969), a study which examined the attachment and exploratory behaviors of one-year-olds under high and low stress conditions. The Strange Situation experiment eventually led to the Strange Situation classification system (Ainsworth et al., 1978) which classified the attachment bonds of children into one of three categories: secure, avoidant, or anxious. The creation of classifications of attachment styles was a momentous milestone in the development of attachment theory which impacted the field for decades to come because the classification system created a reliable way to measure and conceptualize attachment styles.
43 Next Ainsworth compiled her “Infancy in Uganda” (1967) article while Bowlby worked on what was later to become the first volume of the attachment trilogy,
“Attachment” (1969). This volume focused on the development of infant-mother attachment, instincts, and survival mechanisms. In later writings, Bowlby (1973) extended his theory to include natural cues of danger (i.e., darkness, loud noises, isolation, separation from an attachment figure).
In 1978, Ainsworth published “Patterns of Attachment” (Ainsworth et al., 1978), which compiled results from different samples on the attachment classifications in early childhood (Main, 1973; Matas, Arend, & Sroufe, 1978). Meanwhile, Bowlby completed his second and third volumes in the attachment trilogy: “Separation” (Bowlby, 1973), and
“Loss” (Bowlby, 1980a). These volumes reviewed his theory of motivation, personality development, danger cues in childhood, and the stability and/or distortion of working models. Finally, in the last 10 years of his life, Bowlby’s focus shifted toward attachment theory’s applicability in psychotherapy (Bowlby, 1988).
Following Bowlby’s contributions to attachment theory, in 1987 subsequent researchers published articles examining attachment theory’s applicability by studying the existence of attachment developed in adulthood. Hazan and Shaver’s (1987) pioneering work was based on two samples: one aged 14-82 (n = 620), another with a mean age of 18 years (n = 108) to examine working models, attachment styles, and perceptions of romantic love. They developed the WHOTO measure of attachment, which is a questionnaire used to assess preferences in the attachment hierarchy for situations in which closeness, safety, security, and distress reduction were needed.
Results indicated that the distribution of attachment styles in adulthood was similar to
44 those in infancy. Adults’ memories of attachment to parents was similar to individuals in childhood, that ideas about the self-influenced the way an individual viewed relationships that ideas about the self and the world had an impact on one’s perceptions of love. One limitation of the WHOTO is the ambiguous wording of the questions (i.e., “Who do you want to spend time with,” and “Who do you turn to when you are feeling down”) in that temporary and non-distressing desires such as popularity or sexual satisfaction could interfere with the measurement of true attachment bonds (Rosenthal & Kobak, 2010).
Questions which engender a sense of distress or emergent need for closeness and safety are more likely to prime an individual for reporting true attachment bonds (Rosenthal &
Kobak, 2010; Waters & Cummings, 2000).
Despite the WHOTO’s shortcomings, Hazan and Shaver’s (1987) seminal article has been lauded as the primary motivator for other researchers to begin analyzing attachment processes across the entire lifespan (Bretherton, 1992). Hazan and Shaver were the first researchers to examine romantic love as an attachment bond. Results indicated that the attachment bonds between romantic partners mimics the attachment bonds between an infant and his/her parents in that the working models and attachment styles formulated in childhood affect the attachment bond with a romantic partner later in life. Hazan and Shaver’s article was a major catalyst which spurred future studies to investigate the attachment bonds of adults and older adults, because it was the first to focus on an attachment bond between someone other than the parents, and on attachment bonds in adulthood.
The majority of research on attachment theory has consisted of populations between infancy and adulthood (Cicirelli, 2010; Doherty & Feeney, 2004; Pickard &
45 Nelson-Becker, 2011). Research suggests that there is indeed value in further exploration of attachment theory as applied to older adulthood. For example, Pickard and Nelson-
Becker (2011) claimed that although most research related to adult psychological attachment has failed to focus specifically on older adults, and clinical applications are still being defined, the focus on attachment processes in older adulthood has merit.
Kirchmann et al. (2013) claimed that research uncovering processes by which attachment is related to life satisfaction may provide valuable insights into the development of effective intervention strategies for maintaining or enhancing the life satisfaction of older adults. Perhaps this is due to the common assumption that there is a negative correlation between age and life satisfaction in older adulthood. The present study aims to add to the literature on healthy aging by helping to identify an adaptable aspect of life (i.e., the attachment hierarchy) that has the potential to impact life satisfaction. This is possible because life satisfaction is somewhat dependent upon one’s life circumstances (Oshio,
2012). The current study will investigate the relationships between the primary attachment figure and number of attachment figures on life satisfaction between two epochs of older adulthood. Such a study could potentially assist psychologists with identifying how to improve circumstances related to one’s attachment hierarchy by exploring which figure types are associated with the highest levels of life satisfaction.
In summary, attachment theory has been evolving since the 1950s. While initial focus was on infancy and the maternal bond, attention soon expanded to include adolescence, and then adulthood. What was needed was more empirical investigation into attachment theory in older adulthood. Such a study could ascertain which attachment
46 figure types meet the most attachment needs of older adults, as well as if there is are differences between the young-old and mid-old.
Contemporary Attachment Theory
In this section, the major concepts and terms of attachment theory are introduced and explained. Definitions of the following concepts will be covered: attachment bonds, attachment figures, attachment needs, the working model, attachment style, and attachment hierarchy.
The terms used for the concepts of attachment theory have evolved since attachment theory was first developed. Because of this, the terms which were often used in Bowlby’s initial works are slightly different than the terms used today (Bretherton,
1992). For these reasons, the current section will detail both the initial wording of
Bowlby and Ainsworth, as well as the common terminology used today. To explain the difficulty he himself experienced with establishing common terminology Bowlby (1973) wrote,
During this century, countless efforts have been made to clarify terminology, and a number of writers have proposed specific usages for words in common currency. No solution will satisfy everyone, or at least no solution will do so unless everyone shares a common theory. For as often as not the terms adopted are a reflection of theory (p. 404).
Bowlby and Ainsworth’s work primarily focused on the enduring relationship between an infant and its mother (Bowlby, 1973; Bretherton, 1992). The relationship was initially referred to as an “attachment” (Ainsworth, 1972, p. 3), and later classified as an
“emotional bond” (Bowlby, 1988, p. 120). Today, researchers refer to an emotional bond as an attachment bond (Ainsworth, 1973; Bowlby, 1969; Bretherton, 1992; Mikulincer &
Shaver, 2007). Attachment bonds were said to be “present and active throughout the life
47 cycle” (Bowlby 1979, p. 39). Once formed, “an attachment bond endures…” and “the various forms of attachment behavior which contribute to it are active only when required…by conditions such as fatigue, anything frightening, or the unavailability or unresponsiveness of an attachment figure” (Bowlby, 1980b, p. 39). Although attachment bonds do tend to endure, this in no way implies that they are stable from birth unto death.
The attachment hierarchy adjusts in order to accommodate change—new attachments are added, old can be disregarded, or the order of preference can shift—which will be discussed in detail in the next section.
Notably, Bowlby (1969) considered attachment bonds as “conceptually distinct” from social bonds (p. 307): an attachment bond is sought when one is distressed, but a social bond is sought when in one is good spirits. Researchers have found support for the difference between an attachment bond and a social bond: friendships and romantic relationships were unstable (Berndt, 1982) and quickly erode in the face of conflict or decreased contact (Laursen, 1993). According to Ainsworth (1969), attachment bonds
“bridge gaps in time and space…are durable, even under the impact of adverse conditions” (p. 971). Any repeated contact between a caregiving person and an infant could result in the formation of an attachment bond (Howes, 1999). The attachment bond between a mother and her infant was considered to be the principal attachment bond which could affect the attachment processes of an individual throughout the lifespan
(Mikulincer, Shaver, & Pereg, 2003).
Bowlby (1988) argued that attachment bonds are most evident and perhaps most important early in life (Mikulincer & Shaver, 2007). In his classic trilogy, Attachment and Loss, Bowlby (1969, 1982, 1973, 1980b) argued that infants were born with a
48 repertoire of behaviors to influence their success at seeking closeness and security from supportive others. The supportive others were called “attachment figures” (Ainsworth,
1972, p. 3; Bowlby, 1973, p. 120). For childhood, an attachment figure has been conceptualized by Howes (1999) as someone who is continuously present, provides physical and/or emotional care, and is emotionally invested. Ainsworth (1940) thought of an attachment figure as a “secure base” from which an infant can explore the world (p.
45). Closeness and security are sought by an infant or toddler for protection against physical and psychological threats, and to alleviate distress (Mikulincer, Shaver, & Pereg,
2003). Seeking safety from attachment figures was thought to be adaptive in the sense that they assisted an infant or toddler with surviving despite their immature capabilities for locomotion, feeding, and defense (Mikulincer, Shaver, & Pereg, 2003).
Although the attachment bonds in the early years of life were the primary focus of
Bowlby and Ainsworth’s research, Bowlby postulated that attachment bonds remain critical over the entire life span and are manifested in thoughts and behaviors related to support seeking (Mikulincer, Shaver, & Pereg, 2003). Moreover, Howes’ (1999) conceptualization of an attachment figure as someone continually present in an individual’s life may not be as vital for attachment figures following childhood. Bowlby
(1969, 1982) theorized that God may be an attachment figure, and this has been supported for adolescents (Granqvist, 2002; Granqvist & Hagekull, 2003) and older adults (Cicirelli, 2010). It also appears that mental representations of attachment figures
(i.e., a parent who lives far away, a deceased spouse) may also act as attachment figures in adults and older adults (Cicirelli, 2010; Doherty & Feeney, 2004).
49 Bowlby (1969, 1982) also described what we today refer to as attachment needs
(Mikulincer & Shaver, 2007). The primary attachment needs that all people experience include the need for closeness (proximity), safety/comfort (safe haven), and security
(secure base). Another function of an attachment bond involves a feeling of distress when an attachment figure is unavailable (separation protest; Ainsworth, 1989; Doherty &
Feeney, 2004). Bowlby (1988) stated, “the concept of secure base is a central feature of the theory…when an individual (at any age) is feeling secure, he is likely to explore away from his attachment figure” (pp. 121-122). Bowlby (1988) explained that the three needs listed above can also be thought of as needs “for protection, comfort, and support” (p.
121). Attachment needs and desires ultimately motivate an individual to make themselves vulnerable by seeking support from attachment figures. According to Bowlby (1969), a child seeks his attachment-figure when he is tired, hungry, ill, in danger, or alarmed and also when he is uncertain of that figure’s whereabouts. Bowlby speculated that the main biological benefits of attachment needs are the survival and eventual reproductive capacity of individuals (Mikulincer & Shaver, 2007).
Attachment needs continue to be a factor in relationships throughout life. Humans of all ages seek and enjoy proximity to attachment figures in times of need, and experience distress upon separation from these figures (Mikulincer & Shaver, 2007;
Mikulincer, Shaver, & Pereg, 2003). Attachment figures fulfill these needs by providing support, comfort, and security for exploring and learning about the world, and opportunities for individuals to develop individual capabilities and personality
(Mikulincer, Shaver, & Pereg, 2003). Bowlby (1969, 1982, 1973) viewed one’s seeking of attachment needs as a primary inborn strategy for regulating affect. According to
50 Bowlby (1973), “Adults’ tendencies to seek and maintain proximity to an attachment figure and to move away from that figure in order to interact and master the environment are expressed, among other ways, in romantic relationships and in productive work” (p.
271).
When an attachment figure is routinely available and responsive to one’s attachment needs, the recipient of such attention develops a positive internalized conceptualization for how the process of developing and maintaining relationships works.
When attachment figures fail to be available and/or responsive to attachment needs, a negative, or insecure, conceptualization of the way relationships work can result. Bowlby
(1969) called this internalized mental representation of relationships the “working model”
(p. 112) and explained that a working model assists an individual with streamlining information and making quicker judgment about attachment figures (Merz & Consedine,
2009; Mikulincer & Shaver, 2007). The working model acts as a schema or set of beliefs about relationships which assist an individual with making quick decisions about the likelihood of getting attachment needs met. Repeated positive interactions with attachment figures in childhood ultimately leads to stable working models of the self, partner, and relationships (Mikulincer & Shaver, 2007). Access to open and responsive significant others impacts well-being across the lifespan (Mikulincer & Shaver, 2007).
When significant others are unavailable or unresponsive to an individual’s needs, the result tends to be a negative representation of the self and others which manifests as worries about the goodwill of others and doubts about self-worth (Mikulincer, Shaver, &
Pereg, 2003).
51 The patterns of anticipation, attention, interpretation, and recall of others’ behavior which make up one’s working models eventually formulate into what Bowlby termed “patterns of attachment” (Ainsworth, 1967, p. 331; Bowlby, 1969, p. 331) , or
“patterns of response” (Bowlby, 1973, p. 22). These patterns are what researchers now commonly call the attachment style (Bretherton, 1992; Mikulincer & Shaver, 2007). The attachment style has been described as the systemic pattern of relational expectations, emotions, and behavior which results from internalization of a particular history of attachment experiences and consequent reliance on a particular attachment-related strategy for emotional regulation (Fraley & Shaver, 2000; Mikulincer, Shaver, & Pereg,
2003; Shaver & Mikulincer, 2002). In other words, an attachment style is a categorization of the ways one views, and what one expects, out of relationships.
When a classification system for attachment styles was first introduced
(Ainsworth et al., 1978), Ainsworth conceptualized attachment styles as having three main classifications: secure, anxious, and avoidant. Attachment theory has since transitioned to a dimensional model with four classifications: secure, dismissing, preoccupied, and fearful (Bartholomew & Horowitz, 1991; Griffin & Bartholomew,
1994; Levy & Davis, 1988; Mikulincer & Shaver, 2007). Notably, some researchers continue to delineate between the three styles originally proposed by Ainsworth et al.
(1978), or between secure attachment (where anxiety and avoidance are low) and the other styles (collectively termed insecure attachment; Brennan, Clark, & Shaver, 1998;
Hazan & Shaver, 1987; La Guardia et al., 2000; Mikulincer & Shaver, 2007; Mikulincer,
Shaver, & Pereg, 2003; Simpson, 1990). Still other studies investigate the strength of the attachment bond (Doherty & Feeney, 2004; Feeney & Hohaus, 2001; La Guardia et al.,
52 2000; Trinke & Bartholomew, 1997; Yoo & Kim, 2015), or the perceived support provided by one’s attachment figures (Fraley & Davis, 1997; Kafetsios & Sideridis,
2006; La Guardia et al., 2000; Schimack, Oishi, Furr, & Funder, 2004; Trinke &
Bartholomew, 1997; Wang, 2016).
Although the original studies completed on attachment theory focused on infancy and toddlerhood, Bowlby theorized that attachment bonds continued to be critical in the well-being of individuals throughout the lifespan (Bowlby, 1988; Mikulincer, Shaver, &
Pereg, 2003). An infant originates life with one primary attachment bond, but eventually develops relationships with multiple attachment figures in childhood in order to maximize the fulfillment of needs (Bowlby, 1960, 1982; Howes, Rodning, Galluzzo, &
Myers, 1988). Bowlby (1982) termed the presence of multiple attachment figures an
“attachment hierarchy”—a set of individuals one seeks assistance from in times of need or distress (p. 34). He discussed the issue of multiple attachment figures, noting that
“almost from the first, children have more than one figure to whom they direct attachment behavior” (Bowlby, 1969, p. 34). He also stated, “It is a mistake to suppose that a young child diffuses his attachment over many figures in such a way that he gets along with no strong attachment to anyone, and consequently without missing any particular person when the person is away” (Bowlby, 1969, p. 308). Because the attachment hierarchy is one of the main variables of interest to the current study, more information about the attachment hierarchy will be provided in the next section.
The current section outlined the main theoretical constructs of Bowlby and
Ainsworth’s attachment theory, including attachment bonds, attachment figures, attachment needs, the working model, attachment styles, and the attachment hierarchy.
53 Because the attachment hierarchy is a major variable in the present study, the next section will delve into specific research which investigated characteristics of the attachment hierarchy, and how it is commonly measured.
The Attachment Hierarchy
This section begins with an outline of the potential benefits of a study on the attachment hierarchy in older adulthood could have on the field of psychology. The section then transitions to the theoretical conceptualization of the attachment hierarchy according to attachment theory.
The proposition of an attachment hierarchy which is organized by order of preference in times of need is fundamental to attachment theory. Having a preferred attachment figure affords greater protection and care (Bowlby, 1969, 1982; Cassidy,
2008), and having multiple preferred attachment figures improves survival even more.
Research supports Bowlby’s ideas that infants would demonstrate attachment to one primary attachment figure and children would begin to formulate multiple attachment bonds. Infants demonstrate affinity for one attachment figure: commonly the mother
(Mikulincer, Shaver, & Pereg, 2003; Pitman & Sharfe, 2010). According to Bowlby
(1969, 1982), between birth and two months of age, infants become responsive to social interaction with virtually anyone. Between two and six months of age, an infant begins to show preferences for different attachment figures. From roughly six to seven months of age, babies direct all bids for attention from the primary caregiver, and beyond two years of age, children can endure more separation and have an order of preference for attachment figures. At that point, multiple attachment figures become included in the
54 attachment hierarchy in order to more fully meet attachment needs (Ainsworth et al.,
1978; Bowlby, 1969; Hazan & Zeifman, 1994, 1999; Pitman & Sharfe, 2010).
Preferences for each attachment figure formulate, often unconsciously, based on one’s belief that the figure can and will respond satisfactorily in times of distress. Bowlby claimed that the attachment hierarchy is a rank-ordering of multiple attachment figures that are marked by “a clear order of preference” (Bowlby, 1979, p. 130). This suggests that attachment figures are not interchangeable, and an individual’s feelings toward the attachment figure influence his or her preferences for whom to seek when distressed. The order of preference for attachment figures transitions as one ages. Changes in preference are thought to be a function of relationship length, with longer relationships being more likely to become attachment bonds (Fraley & Davis, 1997). Moreover, preferences for attachment figures are dependent upon the satisfaction felt in getting attachment needs met, which could predict the strength and security of the attachment (La Guardia et al.,
2000; Weiss, 1991).
Attachment theory postulates that the purpose of a rank-order of preferred attachment bonds helps one to meet attachment needs more quickly and effectively. The development of a clear order of preferred attachment figures in one’s attachment hierarchy is theoretically adaptive (Bowlby, 1988; Cassidy, 2008). Bowlby (1988) stated,
“…whilst the attachment behavior may in differing circumstances be shown to a variety of individuals, …should a child fail to show such clear discrimination, it is likely he [is] severely disturbed” (p. 32). There are, however, some situations in which the rank-order of preferred attachment figures is not present. Attachment theorists have suggested that a failure to show preference for attachment figures in the attachment hierarchy may be
55 normative in situations when the individual cannot afford to have exclusive preferences in the fulfillment of attachment needs (Hrdy, 2009; van Ijzendoorn, Goldberg,
Kroonenberg, & Frenkel, 1992). Such lack of attachment preference is rare (3-8% of individuals) in young adulthood (N = 1,012; Freeman & Almond, 2010), but has not been investigated in older adulthood.
One of the ways researchers have studied the impact of the attachment hierarchy across the lifespan is to identify the primary attachment figure. Researchers often label the first person listed in the hierarchy as the primary attachment figure (Fraley & Davis,
1997; Friedlmeier & Granqvist, 2006; Hazan & Zeifman, 1994; Mikulincer, Gillath &
Shaver, 2002). However, Pitman and Sharfe (2010) pointed out that assigning the role of primary attachment figure to the first person listed in the attachment hierarchy may provide limitations, as the first attachment figure listed may not be consistent with the majority of the subsequent attachment figures (e.g., one family member and ten peers listed). Another way is to calculate the mean composite scores of each attachment figure and determine which attachment figure has the highest mean rank composite score
(Doherty & Feeney, 2004; Freeman & Simons, 2018; Rowe & Carnelley, 2005; Trinke &
Bartholomew, 1997). Mean composite scores allow for identification of a primary attachment figure that fulfills the most attachment needs (Doherty & Feeney, 2004). The present review now transitions to the theoretical conceptualization of the primary attachment figure, as well as evidence of developmental trends in the primary attachment figure across the lifespan.
When rank-ordering attachment figures, one attachment figure is assigned to the role of the primary attachment figure, with other attachment figures unconsciously
56 regarded as subsidiary attachment figures to be sought in the absence of the principal figure (Doherty & Feeney, 2004; Fraley & Davis, 1997; Freeman & Brown, 2001;
Freeman & Simon, 2018; Friedlmeier & Granqvist, 2006; Mikulincer & Shaver, 2007;
Pitman & Sharfe, 2010; Trinke & Bartholomew, 1997). The primary attachment figure is considered the person who the individual relies on for the majority of his or her attachment needs. The primary attachment figure stands apart from a constellation of secondary attachment figures which are relatively undifferentiated (Cassidy, 2008).
Bowlby (1958) conceptualized the presence of a primary attachment figure as a
“tendency for instinctual responses to be directed towards a particular individual or group of individuals and not promiscuously towards many” (p. 21). Freeman and Simons (2018) explained that while the presence of a primary attachment figure is adaptive, the ability to fulfill attachment needs with multiple attachment figures provides the assurance of a clear secondary target in the event of loss or disruption of the primary attachment which would provide safety and security across multiple settings and/or situations. Their research suggests that the primary attachment figure may have an influence on an individual’s well-being.
Identification of the primary attachment figure is one of the common ways to empirically examine the attachment hierarchy (Bretherton, 1985; Cassidy, 2008; Cicirelli,
2010; Collins & Read, 1994; Doherty & Feeney, 2004; Fraley & Davis, 1997; Freeman &
Brown, 2001; Friedlmeier & Granqvist, 2006; La Guardia et al., 2000; Pitman & Sharfe,
2010; Rowe & Carnelley, 2005; Trinke & Bartholomew, 1997). Therefore, this section will now transition to a review of empirical literature which identified the primary attachment figure across the lifespan.
57 From birth throughout young adulthood, an individual’s primary attachment figure is more likely than not to be a parent or peer, and later transition to a romantic partner (Allen & Land, 1999; Fraley & Davis, 1997; Freeman & Simons, 2018;
Friedlmeier & Granqvist, 2006; Hazan & Zeifman, 1999; Rowe & Carnelley, 2005;
Trinke & Bartholomew, 1997). A longitudinal study of infant attachment (N = 60) indicated that 93% of infants between 9-12 months exhibit a strong preference for a single primary attachment figure (Schaffer & Emerson, 1964). At 18 months, individuals continued to show preferences toward a single primary attachment figure, but they also began seeking out subsidiary attachment figures to meet attachment needs.
In adolescence through adulthood (as autonomy is sought from one’s parents) there is often a gradual transfer of primary attachment to a romantic partner (Allen &
Land, 1999; Friedlmeier & Granqvist, 2006; Hazan & Zeifman, 1999). High school students between the ages of 16 and 18 years (N = 47) reported primary attachment figures of the mother, father, siblings, other relatives, best friends, friends, romantic partners, and the self (in descending order) (Freeman & Brown, 2001): romantic partners were the highest ranked, and single individuals ranked best friends and mothers similarly, followed by fathers.
The attachment hierarchy continues to demonstrate some stability and some change into adulthood. 5% of adults reported the lack a primary attachment figure
(Trinke & Bartholomew, 1997), and 55% of individuals with romantic partners listed their partner as the primary attachment figure (Pitman & Sharfe, 2010), which could be dependent upon the length of the relationship. Table 2 provides an outline of research that explored the primary attachment figures in adulthood.
58 Table 2.2. A Summary of the Primary Attachment Figures in Adulthood Year of Author(s) Publication N Size Age Range PAF La Guardia 2000 (n = 136) (undergraduate Mother, father, romantic et al. (n = 152) students—ages partner, best friend (N =136) unknown)
Trinke and 1997 240 17-45 Mother, romantic partner, Bartholomew best friend, father, sibling Choi 2002 170 18-27 Parents Pitman & 2010 267 = 20 Romantic partner, friend, Sharfe family member
When considering both adulthood and older adulthood, Doherty and Feeney
(2004) asked university students (and the older adults which the students referred) aged
16-90 (N = 812) about the primary attachment figure: results indicated that adults and older adults preferred partners, mothers, friends, children, siblings, and fathers (in descending order). No differences between younger adults and older adults were reported, but older adults had significantly fewer attachment figures than younger adults.
Unfortunately, Doherty and Feeney (2004) noted that despite the promising results of studies examining the primary attachment figure in younger adulthood, investigation into the evolution of the attachment hierarchy—as new relationships are formed and others lost—into older adulthood has been neglected. What was needed was a study on the primary attachment figures with older adults aged 65 and above, which would offer insight into the developmental trends into the later stages of life.
There has been research which suggested that the preferences for different types of attachment figures in times of distress are unique in older adulthood as compared to younger periods of adulthood. Older adults between the ages of 60 and 99 (N = 80) reported primary attachment figures including a spouse, children, and intangible
59 attachment figures such as God or a deceased spouse (Cicirelli, 2010). Through the calculation of mean composite scores, rankings were given to each attachment figure listed. Lesser figures included in-laws, doctors, caregivers, clergy, and animals. Twenty- eight older adults had a primary attachment figure, determined by having the same attachment figure ranked first on all three attachment needs. Thirty-five had a partial primary attachment figure (the same attachment figure listed on two of the three attachment needs), and 17 did not have a primary attachment figure (a different attachment figure was ranked first for all three attachment needs). Those with primary attachment figures had smaller attachment hierarchies: individuals with primary attachments had an average of 3 attachment figures, individuals with a partial primary attachment had an average of 4 attachment figures, and individuals with no primary attachment figure had an average of 5 attachment figures. Of the 28 participants who identified a full primary attachment figure, 10 named a spouse, 8 named God, and the rest named various other attachment figure types.
In a study that analyzed the convoy theory of social networks (Antonucci, 2001;
Kahn & Antonucci, 1980), Fiori, Smith, and Antonucci (2007) used Kahn and
Antonucci’s (1980) convoy model and reported evidence of differences in the composition and functionality of the attachment hierarchy (referred to as the social network) across epochs of older adulthood. Older adults aged 70-103 (N = 516) completed a consecutive circle network-mapping procedure developed by Antonucci
(1986): in a series of three concentric circles, attachment figures (as represented by stickers) were placed according to the level of closeness felt. Figures closer to the “self” in the center of the inner-most circle were considered to be preferred over those placed in
60 the farther circles. An interview included questions about the structure, function, quality, and satisfaction with their social networks as well as questions about depression, morbidity, and health. Epochs of older adulthood were compared: young-old (ages 70-
84), and oldest-old (ages 85-103). Social networks were then classified according to the types of attachment figures reported: categories included diverse, family-focused, friend- focused, and restricted. Structures of the social network were associated with its functionality, which Fiori and colleagues concluded was in line with Kahn and
Antonucci’s convoy model. Individuals with structurally diverse social networks also reported higher levels of instrumental and emotional support. Individuals with friend networks reported fewer family members: some had high levels of support and others had minimal support. Seventy-seven percent of the unsupported individuals were in the young-old group, and 72% of the high-support individuals in the old-old group. The only network-type that was found to report low satisfaction was the restricted type with low numbers of friends. Individuals with a restricted network type with either less friends or less family reported very low levels of emotional support, suggesting that, for individuals with restricted networks, non-family networks are more satisfied than non-friend networks with less support and fewer attachment bonds. Most restricted networks were found in the old-old group, consistent with Baltes and Smith’s (2003) notion that the old- old experience heavy losses of partners and friends. Notably, only 7% (n = 17) of the old- old had friend networks with low levels of support; 3% had a diverse network with support and 40% had friend networks with support. These numbers highlight the heterogeneity of social networks even into very old age, and is consistent with the notion of within-network dynamics of compensation (Baltes, 1997). Individuals with friend
61 networks with high support had higher levels of depression and lower levels of well- being than individuals in the diverse network with support, the family network, or friend network without support. Individuals with friend networks without support had lower morbidity and higher well-being than individuals with restricted, non-friend network.
Individuals with restricted, non-family networks without support had higher depressive symptoms than those with family networks. They speculated that results may be due to differences in the frequencies of each type of network in the different age groups, the positive correlation that research has shown between friends and health, and the reduction of autonomy causing a need for support (and therefore dissatisfaction) in the friend networks with support. The current study aims at expanding upon the work of Fiori and colleagues (2007) by using peer-reviewed, standardized measures of the attachment hierarchy and two measures of life satisfaction, and analyzing the influence of the primary attachment figure.
The Size of the Attachment Hierarchy
This section addresses the importance of the size of the attachment hierarchy. The size of the attachment hierarchy is most often assessed by summing the number of attachment figures listed, and demonstrates developmental trends across the lifespan.
The size of the attachment hierarchy has been postulated to be a vital part of one’s adaptation to the environment throughout the lifespan (Bowlby, 1982, 1983; Cicirelli,
2010; Doherty & Feeney, 2004). The number of attachment figures one has is potentially related to adaptation due to the emotional and instrumental support others can provide, as explained by the social convoy model (Kahn & Antonucci, 1980), or the influence of the attachment figures on the individual’s emotion-regulation, as in SST (Carstensen, 2006).
62 Empirical studies suggest that the number of attachment figures in the attachment hierarchy has been related to well-being (Iyer et al., 2009; Osborn et al., 2003).
Specifically, reports from students aged 17-20 (n = 55, n = 51, n = 264) showed that the number of attachment figures in the attachment hierarchy correlated negatively with depression (Iyer et al., 2009). Analyses from older adults aged 75 and above (N =
14,217), showed that the size of the attachment hierarchy buffered the negative effects of life transitions: an increase in the number of attachment figures was negatively correlated with depression (Osborn et al., 2003).
The number of people that an individual includes in his or her attachment hierarchy follows a somewhat predictable pattern across the lifespan. One attachment figure is usually seen in infancy (Pitman & Sharfe, 2010). In childhood and adolescence, frequency analyses showed a transition to multiple attachments (Ainsworth et al., 1978;
Pitman & Sharfe, 2010). Indeed, an analysis of variance showed that a dramatic increase in the size of the attachment hierarchy occurs in adolescence and young adulthood (Rowe
& Carnelley, 2005), with the average number of ten attachment figures (Doherty &
Feeney, 2004; Trinke & Bartholomew, 1997). Frequency analyses indicated that this trend resulted in a peak in middle adulthood (Doherty & Feeney, 2004; Small, 2007), and what appears to be an eventual decline in older adulthood (Cicirelli, 2010; Cornwell,
Laumann, & Schumm, 2008; Cornwell, et al., 2014; Doherty & Feeney, 2004; Small,
2007; Smith et al., 2015; Trinke & Bartholomew, 1997). Specifically, the size of the attachment hierarchy in older adulthood has ranged in different studies between 1.5
(Smith et al., 2015) and 4.3 (Cicirelli, 2010). No studies have yet examined the differences in the size of the attachment hierarchy across periods within older adulthood,
63 which points to the need for the current study which compares the number of attachment figures in the attachment hierarchies of the young-old and the mid-old, as well as the impact these numbers have on life satisfaction.
Some researchers have assessed the size of the attachment hierarchy by summing the number of attachment figures listed in the attachment hierarchy. Calculating the sum has been accomplished through multiple different questionnaires and measures. In a study on the general aspect of well-being in older adulthood, Gillath, Johnson, Seluk, and Teel
(2011) found support for socioemotional selectivity theory (SST; Carstensen, 2006).
They used the Social Network Inventory (SNI: Treadwell, Leach, & Stein, 1993), the
Experience in Close Relationships Inventory (ECR: Brennan, Clark, & Shaver, 1998), and the Center for Epidemiologic Studies Depression Survey (CES-D: Gupta, Punetha, &
Diwan, 2006). Young adults aged 18-25 (n = 74) and older adults aged 58-85 (n = 26) indicated that older adults optimized their social networks to buffer depression associated with life’s transitions by selectively focusing on fewer, but closer, ties in the social network. Older adults were less likely to initiate new ties and more likely to terminate existing social ties when compared to younger adults. Less frequent contact, fewer new attachment bonds, and the termination of more attachment bonds with attachment figures were all associated with higher levels of depression. Older adults reported less frequent contact with network members. Maintaining social ties was easier for older adults who were low in attachment anxiety and those high in attachment security. Depression was predicted by the initiation of new ties and the termination of old ties. Social network size was negatively correlated with depression: but older adults who decreased their network size did not show increased depression.
64 In a similar study that examined SST, English and Carstensen (2014) asked participants to complete the social convoy questionnaire (Kahn & Antonucci, 1980), The
Cornell Medical Index (CMI; Brodman, Erdmann, & Wolff, 1956), and author-created questions about emotions. The size of the attachment hierarchy (referred to as the social network) was the sum of the number of figures listed in the social convoy questionnaire.
Closeness of relationships was considered, with results indicating that, for individuals aged 18-94 (N = 184), older adults were more likely to list non-biological family as close attachment figures, with lower numbers of family and higher numbers of peers which were the network but not considered as close. Age differences were found in frequency of emotional experiences, but not in intensity of emotion. There were declines in not-as- close [periphery] figures, but stability in the number of close attachment figures as age increased. The emotional tone of the social network was associated with overall well- being. Size did not associate with daily emotional tone. English and Carstensen interpreted these results in the terms of SST: individuals selectively prune their social networks in order to maximize positive and satisfying experiences and limit negative or taxing experiences.
Multiple studies have used the ANQ as a questionnaire to assess the size of the attachment hierarchy: individuals aged 16-90 (N = 812) reported approximately 10 attachment figures in the attachment hierarchy (Doherty & Feeney, 2004). They calculated the size of the attachment hierarchy by summing the number of attachment figures on the ranking questions on the ANQ. In a second study, two groups of university students with a mean age of 20 years (n = 129) and a mean age of 19 years (n = 106)
65 completed the ANQ, and a sum of the attachment figures listed resulted in an average of
9 attachment figures in the attachment hierarchy (Rowe & Carnelley, 2005).
Another common method researchers used to analyze the size of the attachment hierarchy was the semi-structured interview. For instance, individuals between the ages of 8 and 12 reported more close attachment figures than individuals aged 80-93 (N =
1,703) (Antonucci, Akiyama, & Takahashi, 2004). Participants completed a semi- structured interview and Antonucci’s (1986) concentric circle. Furthermore, results indicated that 8-12 year-olds reported more close attachment figures than individuals aged 80-93, while young adults aged 20-39 reported more close attachment figures than individuals aged 60-93. Middle-aged adults aged 40-59 reported more close attachment figures than older adults aged 60-93. In a similar study, Cicirelli’s (2010) author-created questions about the attachment hierarchy showed that older adults aged 60-99 (N = 80) reported an average of 4.3 attachment figures in older adulthood. Cicirelli (2010) failed to investigate the impact of the size of the attachment hierarchy and other psychological variables. Consedine and Magai (2003) used a semi-structures interview to calculate the size of the attachment hierarchy. Individuals aged 65-86 (N =1,118) completed a semi- structured interview, the Relationship Scales Questionnaire (RSQ: Griffin &
Bartholomew, 1997) and the Differential Emotions Scale (DES: Izard, 1972). The size of the attachment hierarchy was calculated by summing the number of attachment figures listed in the interview: individuals with more secure beliefs about relationships had more attachment figures. Jurkuvenus et al. (2017) also used an interview: individuals aged 50-
65 (n =368), and individuals aged 65 and above (n = 420) who had traits of neuroticism had lower levels of well-being. The size of the attachment hierarchy was the sum of the
66 attachment figures reportedly seen once per week over the last year. Larger attachment hierarchies were associated with higher well-being, as were variables such as education, employment, extraversion, openness, agreeableness, conscientiousness.
Other studies which utilized the semi-structured interview to assess the size of the attachment hierarchy made use of national databases for recruitment purposes. For example, in a sample of individuals with a mean age of 74 (N = 800), Magai et al. (2001) calculated the size of the attachment hierarchy was the sum of the attachment figures which a participant listed in the NAP semi-structured social network interview (Cohen &
Sokolovsky, 1979; Sokolovsky & Cohen, 1981). European Americans had an average of
5 attachment figures and African Americans had an average of 3 attachment figures. In a similar study, Small (2015) used data from the UPFLS (Wilson, 1987): individuals aged
18-47 (N = 2,490) to answer questions about race and the attachment hierarchy. They calculated the size of the attachment hierarchy by summing the number of attachment figures mentioned in the interview conducted by National Opinion Research Center.
Results showed that 38% of Caucasians reported no “crisis support ties” (p. 328) compared to 26.9% of African Americans. Of those who listed crisis support ties,
Caucasians listed an average (with standard deviation in parentheses) of 1.86 (2.01) crisis support ties and African Americans reported an average of 1.69 (1.56) crisis support ties.
In other words, Caucasians were more likely to be isolated in terms of crisis support ties, yet those who did report crisis support ties reported the presence of more attachment figures than African Americans. However, racial differences disappeared once neighborhoods (proportion poor, proportion black, proportion who lived there for five or more years, ethnic heterogeneity, and population density) were controlled for. For
67 example, they predicted that approximately 16% of individuals living in a neighborhood with 0% poverty would report no crisis support ties, while 39% of individuals living in a neighborhood with 66% poverty would report no crisis support ties, suggesting a negative relationship between neighborhood poverty and number of attachment figures. Hispanic
Americans were more likely to report the presence of no attachment figures.
Neighborhood conditions accounted for the racial differences in the number of close friends, and the presence of everyday supportive others. In a study with individuals aged
57-85 (N = 3,005) Cornwell, Laumann and Schumm (2008) asked participants to complete a semi-structured interview. The size of the attachment hierarchy was determined by summing the number of attachment figures listed in a semi-structured interview conducted by the National Opinion Research Center (NORC). Results showed age correlated negatively with the size of the attachment hierarchy. In another study,
Smith et al. (2015) calculated the size of the attachment hierarchy by summing the number of attachment figures listed in the interview which was conducted by American
Social Fabric Study (ASFS), including questions about network structure, community outcomes, and the geography of social ties. Individuals aged 18-102 (N = 3,084) reported an average of ten attachment figures, some meeting more than one personal need (i.e., social activities, job leads). At approximately age 50, individuals had an average of 4.5 attachment figures; at approximately age 60 participants reported an average of 1.5 attachment figures. Age was correlated with the inclusion of more family members in the attachment hierarchy.
In summary, the size of the attachment hierarchy has been related to well-being, acting as a buffer to life transitions. It appears that older adults report an average of
68 between 1.5 and 4.3 attachment figures as compared to the average of ten in adulthood.
Support has been found for SST (Carstensen, 2006), which explains this reduction as a selective pruning of the attachment network in order to improve the quality of the hierarchy. There are different methods of calculating the size of the attachment hierarchy, and the present study measured the size of the attachment hierarchy by summing the number of attachment figures which participants list in the ANQ. The present study also adding a measure of life satisfaction to assess the relationship between the attachment hierarchy and well-being. Few studies which investigated the size of the attachment hierarchy also included a measure of well-being. What was needed was a study which analyzed; 1) the relationship between the size of the attachment hierarchy and levels of life satisfaction; 2) differences in the size of the attachment hierarchy in the young-old and mid-old; and; 3) the relationship between the primary attachment figure and the size of the attachment hierarchy.
Types of Attachment Figures in the Attachment Hierarchy
This section provides a review of theoretical and empirical research which examined the types of people individuals identify in their attachment hierarchies across the lifespan. Also included is research on the types of attachment figures in the attachment hierarchy in childhood through adulthood. Then, this section provides two in- depth reviews of influential studies which investigated the attachment hierarchy in older adulthood.
The types of attachment figures included for an individual is theoretically tied to change across the lifespan: Bowlby (1969, 1982) speculated that other adults may come to assume an importance equal or greater than that of the parents. The transitions in the
69 attachment hierarchy can occur quickly or slowly, depending on the individual and his or her circumstances (Bretherton, 1992), although research supports a tendency toward a gradual shift of the attachment hierarchy across the lifespan (Bartholomew & Horowitz ,
1991; Doherty & Feeney, 2004; Freeman & Simons, 2018; Hazan & Shaver, 1987;
Hazan & Zeifman, 1999; Main, Kaplan, & Cassidy, 1985; Mikulincer & Shaver, 2007;
Pitman & Sharfe, 2010; Schachner, Shaver, & Gillath, 2008).
Empirical evidence supports the presence of predictable developmental trends in the types of attachment figures included in the attachment hierarchy in young adulthood.
Hazan and Zeifman (1999) used two samples, one with children ages 6-17 (n = 100), and another with adults ages 18-82 (n = 100). They conducted interviews and found support for a gradual transition throughout adolescence and into young adulthood, when individuals place same-sex friends, romantic partners, and spouses higher in the hierarchy than parents (meaning they seek the fulfillment of attachment needs from these sources before seeking out their parents).On the other hand, Pitman and Sharfe (2010) reported that, for young adults with a mean age of 20 years (N = 267), age correlated negatively with the inclusion of non-family members in the attachment hierarchy. Finally, Fraley and Davis’ (1997) study indicated that young adults with a mean age of 20 (N = 237) listed parents for the secure base need and peers for proximity and safe haven needs.
Romantic peers were more likely to be listed for each need if the relationship length was two years or more. Results supported Hazan, Hutt, Sturgeon, and Bricker’s (1991) model that proximity seeking is transferred from parents to peers first, followed by the transfer of the safe-haven component, then by the transfer of the need for a secure base.
70 A particularly influential study was conducted by Freeman and Simons (2018) who found that for university students aged 18-35 (N = 2,055), preferred primary attachment figures included the mother, romantic partners, best friends, fathers, and
‘others,’ respectively. Freeman and Simons used the ANQ (Trinke & Bartholomew,
1997), a single item from Hazan and Shaver (1987) to measure attachment security, and the Experiences in Close Relationships Questionnaire (ECR-R: Fraley, Waller, &
Brennan, 2000). Participants were more likely to include the romantic partner in the attachment hierarchy if the relationship was two or more years strong; they were also more likely at two or more years to list the romantic partner as a primary attachment figure. The attachment hierarchy was assessed through identification and comparisons of the first three attachment figures in the attachment hierarchy, and the attachment hierarchy was classified into one of four categories, depending upon the comparisons made between the primary and secondary attachment figures, and between the secondary and tertiary attachment figures. Forty percent of the sample had three very different attachment figure types in the top three attachment figures listed (i.e., the inclusion of a variety of different attachment figures: for example, first a parent, then a romantic partner, then a peer), 32% had a clearly differentiated primary attachment figure with the secondary and tertiary attachment figures of similar type, 19% reported the first two attachment figures to be of a similar type and the third to be different, and 9% reported no preference between the top three attachment figures. Freeman and Simons (2018) stressed that the presence of a romantic partner in adolescence and adulthood involves a process of attachment transfer in which an existing attachment hierarchy is shuffled to accommodate the rising importance of the romantic partner. Limitations of Freeman and
71 Simons (2018) included that a large portion of their focus was on comparing the attachment hierarchies which included romantic partners with those which did not.
Another limitation was their focus on younger adults to the exclusion of any other ages.
A third limitation was their focus on the classification of the hierarchy as a whole rather than the identification of the primary attachment figure. A fourth limitation was their failure to include a measure of well-being. What was needed was a study which identifies the primary attachment figure in different stages of older adulthood, and compares this to older adults’ well-being.
Gradual shifts in the attachment hierarchy appear to continue throughout adulthood. For instance, between the ages of 16-90 years (N = 812), Doherty and Feeney
(2004) used the ANQ (Trinke & Bartholomew, 1997) and found that the mother, father, and siblings continued to be listed as primary attachment figures well into young adulthood. Schachner, Shaver, and Gillath (2008) found that adults aged 25-55 (N = 142) listed attachment figures such as children, significant others, friends, siblings, and parents. Siblings were included well into adulthood. Main, Kaplan, and Cassidy (1985) reported that “mothers and fathers” (ages unknown; N = 40) included peers in the attachment hierarchy well into young adulthood. Hazan and Shaver (1987) reported that individuals aged 14-82 (n = 620), and individuals with a mean age of 18 years (n = 108) included peers in the attachment hierarchy well into adulthood. Bartholomew and
Horowitz (1991) reported that students between the ages of 18-22 (N = 77) also included peers in the attachment hierarchy. Finally, Pitman and Sharfe (2010) reported that university students with a mean age of 20 years (N = 267) also reported peers in their hierarchy. Individuals between the ages of 16 and 90 (N = 812) reported that attachment
72 to siblings decreased in the middle-adult years, yet increased in subsequent years
(Doherty & Feeney, 2004). In summary, support has been found for gradual shifts in the attachment hierarchy across adulthood. Adults continue to list figures such as their mother, father, and siblings as primary attachments well into young adulthood. Secondary attachment figures included children, romantic partners, friends, siblings, and parents.
Attachment to siblings decreased in the middle-adult years, yet increased in subsequent years.
Less is known about the attachment figures in older adulthood. One study linked the types of attachment figures included to well-being: Litwin (2007) used a household survey, the GHQ-12 (Goldberg, 1972) and author-created questions of the attachment hierarchy social engagement, and biological symptomology. Individuals aged 70 and above (N = 1,811) who reported the presence of friends and neighbors in the attachment hierarchy were also found to have reduced mortality, possibly due to the instrumental support exchanged. Interestingly, the presence of family, romantic partners, and congregational attachment figures correlated positively with mortality. Litwin (2007) also suggested that there is some debate as to the reasons for this relationship: do friends have a beneficial influence on health, or are healthier older adults more social? Another explanation could be that friendship ties reflect autonomy and control, which could reduce mortality. Some limitations of Litwin (2007) were the use of author-created measures of the attachment hierarchy. Another limitation was the failure to report the primary attachment figure: what was studied was the frequency of contact with attachment figures. Finally, Litwin failed to attend to the impact of the size of the attachment hierarchy. What was needed was a study which identified the size and
73 primary attachment figures in older adults’ attachment hierarchies, and examined the impact they had on life satisfaction.
Litwin and Shiovitz-Ezra (2010) authored an influential study that indicated findings similar to Litwin (2007). They used the loneliness question from the CES-D
(Gupta, Punetha, & Diwan, 2006), a modified version of the Hospital Anxiety and
Depression Scale (Zigmond & Snaith, 1983), a single question about happiness, and author-created questions about the attachment hierarchy. According to Litwin and
Shiovitz-Ezra (2010), attachment hierarchies can be categorized into five types (i.e., diverse, friend, congregant, neighbor, family, and restricted). For individuals aged 57-85
(N = 3,005) frequency distributions showed that 25% of older adults had attachment hierarchies consisting of mostly friends, 20% had a lack of differing types of attachment figures, 20% had a variety of attachment figures, 16% had mostly people from religious connections, and 16% had mostly family members. The inclusion of friends in the attachment hierarchy was negatively associated with anxiety and positively with happiness. Individuals with the most friends as attachment figures were the least likely to feel anxious, although the causality of these relationships needs further investigation. The presence of attachment figures such as congregation members correlated positively with happiness. A wide variety of different types of attachment figures (i.e., family, friends, people at church)—in other words, a diverse attachment hierarchy—correlated negatively with loneliness, perhaps because of increased social opportunities. Individuals with less diversity regarding the types of attachment figures had more non-family attachment figures and had fewer opportunities to socialize. Interestingly, those with more family members in their hierarchy had fewer other types of attachment figures. Hierarchies with
74 the majority of attachment figures as family members were correlated with worse functional health and lower levels of anxiety. One limitation of Litwin and Shiovitz-Ezra
(2010) included the classification of the attachment hierarchy in terms of the most popular types of individuals which participants reported. Primary attachment figures were not identified. Another limitation was the inclusion of individuals under the age of 65, which is the usual cutoff for the period of older adulthood in the literature (Cameron,
1969; Cicirelli, 2010; Drevenstedt, 1976; Zizza, Ellison, & Wernette, 2009). A third limitation was the lack of attention paid to the size of the attachment hierarchy. Finally,
Litwin and Shiovitz-Ezra (2010) measured well-being through measures such as happiness, depression, and anxiety, but failed to include a measure of life satisfaction.
What was needed was a study with older adults which focused on the size and primary attachment of the attachment hierarchy, changes which occurred within older adulthood, and the impact of the size of the attachment hierarchy on the life satisfaction of older adults.
Another study that captured a wide range of ages was completed by Antonucci,
Akiyama, and Takahashi (2004). They analyzed age differences in the closeness and types of people included in the attachment hierarchy throughout the lifespan. Measures included a semi-structured interview, and Antonucci’s (1986) concentric circle procedure. Individuals aged 8-93 (N = 1,703) participated in the study, and results indicated that close relationships for individuals aged 8-19 included the mother, father and siblings. In young adulthood (ages 21-39), close relationships consisted of the mother, spouse, father, friends, and children. In older adulthood (ages 60-79) close relationships included the spouse, children, siblings, and friends. In those aged 80-93
75 close relationships consisted of spouse, children, siblings, friends and grandchildren.
Limitations of Antonucci, Akiyama, and Takahashi (2004) include the failure to include a measure of life satisfaction, and the use of a concentric circle procedure to measure the attachment hierarchy rather than a more standardized measure.
A final influential study on the attachment hierarchies of older adults was published by Cicirelli (2010). Cicirelli (2010) examined the attachment hierarchy in a small sample of older adults ages 60-99 (N = 80). Participants were recruited from senior centers and independent living residences. He used an author-created measure for the attachment hierarchy and the Relationship Scales Questionnaire (RSQ: Bartholomew &
Horowitz, 1991). An univariate analyses of variance indicated that a substantial number of older adults reported that having a variety of attachment figures in their attachment hierarchy: he speculated that as compared to the literature on attachment figures in younger adulthood (i.e., romantic partners, friends, and siblings), older adults transitioned toward intangible attachment figures (i.e., God, deceased spouse), which were only superseded by spouses and adult children. Examples of popular attachment figures included adult children, deceased spouses, God, in-laws, doctors, caregivers, clergy, and animals. One limitation of Cicirelli (2010) was his use of an author-created measure of attachment hierarchy. Another limitation was the inadequate power due to the small sample size. A third limitation was the failure to report upon the primary attachment figure. The fourth limitation was his failure to include a measure of well-being. Finally,
Cicirelli (2010) included individuals under the age of 65. What was needed was a study which used peer-reviewed questionnaires to investigate the influence of the primary attachment figure and the size of the attachment hierarchy on life satisfaction.
76 As can be seen, there is a limited amount of high-quality research on the relationship between life satisfaction and both the size and the types of attachment figures
(particularly the primary attachment figure) included in the attachment hierarchy in older adulthood. Researchers who investigated the unique impact of age on the attachment hierarchy in younger cohorts have suggested that future research on the attachment hierarchy in older adulthood would be fruitful for discovering the unique characteristics which impact the attachment hierarchy in the later stages of life (Hazan & Zeifman, 1994,
1999; Mikulincer & Shaver, 2007). Speculation about predictable developmental trends in the attachment hierarchy in older adulthood is more prevalent than research
(Carstensen, 1993; Erikson, 1959; Kafetsios & Sideridis, 2006; Levinson, 1986). What was needed was research to provide empirical evidence of the relationships between the size and types of people included in the attachment hierarchy on the life satisfaction of older adults, which could aid understanding of the impact of the attachment hierarchy on well-being in older adulthood, and enable psychologists to advocate for maximizing healthy aging. The next section will outline how to identify the primary attachment figure as well as the most commonly used questionnaire which assesses the primary attachment figure, the size of the attachment hierarchy, and the types and order of attachment figures listed.
Measuring Attachment Type and its Hierarchy
This section reviews the methods by which researchers have measured the types of attachment figures included in the attachment hierarchy and the primary attachment figures. This section also reviews the ANQ, which is one of the most frequently used questionnaires to assess the attachment hierarchy (Oishi, 2006).
77 The majority of literature on the attachment hierarchy distinguishes between three main types of attachment figures in the attachment hierarchy; family members, romantic partners, and peers. The category of “family” is used as a broad descriptor for attachment figures such as the mother, father, siblings, children, grandchildren, cousins, aunts/uncles
(Antonucci, Akiyama, & Takahashi, 2004; Doherty & Feeney, 2004; Feeney, Hohaus,
Noller, & Alexander, 2001; Fraley & Davis, 1997; Hazan & Zeifman, 1994, 1999; La
Guardia et al., 2000; Schachner, Shaver, & Gillath, 2008; Trinke & Bartholomew, 1997).
“Romantic partners” were often distinguished according to the length of time one has been in the relationship, with the period of two years as a noteworthy cutoff for the inclusion of a partner as a primary attachment figure (Fraley & Davis, 1997; Freeman &
Simons, 2018). Romantic partners of less than two years were still included in the attachment hierarchy, but not as the primary attachment figure (Fraley & Davis, 1997;
Freeman & Simons, 2018). The category of “peers” includes best friends and friends
(Antonucci, Akiyama, & Takahashi, 2004; Doherty & Feeney, 2004; Feeney et al., 2001;
Fraley & Davis, 1997; Hazan & Zeifman, 1994, 1999; La Guardia et al., 2000; Schacher,
Shaver, & Gillath, 2008; Trinke & Bartholomew, 1997).
A final category of “other” is usually used to account for attachment figure types which do not fit in one of the other three categories. Some of the less common attachment figure types which have been named have included roommates, teachers, employers (La
Guardia et al., 2000), people at church (Litwin & Shiovitz-Ezra, 2010; Pitman & Sharfe,
2010), neighbors (Litwin & Shiovitz-Ezra, 2010), step-family (Freeman & Brown, 2001), nieces/nephews, in-laws (Cicirelli, 2004, 2010; Doherty & Feeney, 2004; Rowe &
Carnelley, 2005; Trinke & Bartholomew, 1997), healthcare professionals, clergy, God,
78 deceased family members (Cicirelli 2004, 2010), and pets (Cicirelli, 2010; Doherty &
Feeney, 2004; Pitman & Sharfe, 2010). Notably, theoretical speculation for older adults has made mention of attachment figures such as residential social workers, nurses, and therapists (Antonucci, Akiyama, & Takahashi, 2004).
Along the lines of previous research (Antonucci, Akiyama, & Takahashi, 2004;
Doherty & Feeney, 2004; Feeney et al., 2001; Fraley & Davis, 1997; Hazan & Zeifman,
1994, 1999; La Guardia et al., 2000; Schachner, Shaver, & Gillath, 2008; Trinke &
Bartholomew, 1997), the present study investigated the attachment hierarchies of older adults by distinguishing between the primary types of attachment figures: 1) family (i.e., parents, siblings, children, grandchildren, cousins, aunts/uncles); 2) romantic partners
(i.e., spouse, boyfriend, girlfriend); and 3) peers (i.e., best friends, friends). Along the lines of Cicirelli (2010) and Freeman and Simons (2018), a fourth category of “other” was included to capture the less common attachment figures which may be included (i.e., roommates, teachers, employers, people at church, neighbors, step-family, nieces/nephews, in-laws, healthcare professionals, clergy, God, deceased family members, pets, other).
Along with categorizing the types of attachment figures present in the attachment hierarchy, research commonly established the type of attachment figure which was considered to be the primary attachment figure (Cicirelli, 2010; Doherty & Feeney, 2004;
Fraley & Davis, 1997; Freeman & Brown, 2001; Freeman & Simons, 2018; La Guardia et al., 2000; Pitman & Sharfe, 2010; Rowe & Carnelley, 2005; Trinke & Bartholomew,
1997). The identification of the primary attachment figure can be done in several different ways. La Guardia et al. (2000) wanted to test Hazan and Shaver’s (1987) claim
79 that the only attachment figures which could qualify as primary attachment figures were the parents or a romantic partner. La Guardia et al. simply identified the set of attachment types which were empirically supported in the literature (i.e., mother, father, best friend, romantic partner), then added three more arbitrary attachment figure types (i.e., roommate, teacher, employer). They analyzed all attachment types to determine if the new attachment figure types were also correlated as positively with need satisfaction, well-being, and life satisfaction. In other words, La Guardia et al. identified the attachment figures they wanted to examine and compare, and called them primary attachment figures. Because no research has indicated a high incidence of teachers and employers in the attachment hierarchy of older adults, the present study will include them in the category of “other.”
Another way to identify the primary attachment figure is by assessing the attachment figure listed for the secure base attachment need as measured with Hazan and
Shaver’s (1987) WHOTO Scale (Friedlmeier & Granqvist, 2006; Hazan & Zeifman,
1994; Mikulincer, Gillath & Shaver, 2002). The majority of studies which used this method focused on the theoretically and empirically-based transition from parents to peers in adolescence and adulthood. A limitation of the WHOTO is that only one attachment figure can be listed for each attachment need. Another limitation is the phrasing on the WHOTO: 1) leads participants to answer in terms of who they would like to be with, which is more indicative of a social bond than an attachment bond, and 2) does not allow individuals to identify attachment figures whom they would like to seek in times of distress, but choose not to (possibly due to an insecure attachment with said figure).
80 Fraley and Davis (1997) also used the WHOTO, but used a slightly different method to identify the primary attachment figure. In a sample of university students with an average age of 20 (N = 237), Fraley and Davis defined the primary attachment figure as one who is listed first to meet any of the three attachment needs (proximity, safe haven, and secure base).
In a similar endeavor to investigate the theoretical transition from parents to peers in adolescence, Freeman and Brown (2001) used an author-created question about the primary attachment figure and the Attachment Support Inventory (ASI: Fraley & Davis,
1997). The sample consisted of individuals aged 16-18 (N = 47). The author-created question allowed individuals to nominate their own primary attachment figure by answering who they felt they relied on most for emotional support and closeness. On the
ASI, the higher the score, the higher the ranking of attachment support. A limitation of the ASI is its specifications of only four attachment figure types (i.e., best friends, partners, mother, father) to explore primary attachments in adolescence; it therefore may not be appropriate for older adults. What was needed was a study which identified both the primary attachment figure, and the attachment hierarchy.
Cicirelli (2010) used a somewhat different method to identify the primary attachment figure. He categorized what he called “full primary attachment” (p. 196). This was done by assessing if the same attachment figure was ranked first for the attachment needs of proximity, secure base, and safe haven. He also assessed for a partial primary attachment (attachment figures listed first for two of the attachment needs). The rest of the attachment hierarchy was assessed through mean rankings given to each type of attachment figure.
81 Yet another way of identifying the primary attachment figure—one which enables researchers to simultaneously consider the attachment hierarchy—is to identify the attachment figure with the highest composite rank score in the attachment hierarchy through the use of the ANQ (Trinke & Bartholomew, 1997; Doherty & Feeney, 2004;
Freeman & Simons, 2018; Rowe & Carnelley, 2005; Trinke & Bartholomew, 1997). The
ANQ allows for individuals to list up to 15 attachment figures across the attachment needs: most adults did not list more than four or five (Doherty & Feeney, 2004). Mean composite scores assess the primary attachment figure, and t-tests investigate group differences in the primary attachment figure. This method was used in the current study because the calculation of a mean composite score allows for an average rank across attachment needs to be assessed for each attachment figure rather than simply depending upon the first person listed in the attachment hierarchy. Mean composite scores allowed for the testing of group differences between the young-old and mid-old.
Several researchers have used mean composite scores on the ANQ to identify the primary attachment figure (Doherty & Feeney, 2004; Freeman & Simons, 2018; Pitman
& Sharfe, 2010; Rowe & Carnelley, 2005; Trinke & Bartholomew, 1997). For example,
Doherty and Feeney (2004) used the ANQ a sample of individuals aged 16-90 (N =812) and reported calculating mean composite scores by giving a score of 3 to the first attachment figure listed, 2 to the second, and 1 to the third. The number of attachment needs which an attachment figure was listed for was used to calculate the strength of the attachment, not the rank-order. If equal composite scores were calculated for any of the attachment figures listed, they were classified as not having a clear primary attachment figure. The attachment figures who met the requirements for primary attachment figures
82 included (in descending order of frequency) partners, mothers, friends, children, siblings, and fathers. Rowe and Carnelley (2005) used the ANQ with two samples: one of individuals with a mean age of 20 (n = 129) and one with a mean age of 19 (n = 106).
Attachment figures were distinguished from social bonds by assessing if the attachment figure was used for all attachment needs. The primary attachment figure was identified by using mean rankings across items for each attachment figure listed. By this means Rowe and Carnelley (2005) also identified the ranking of the attachment figures in the attachment hierarchy by placing the figure with the lowest mean as the primary attachment figure, the second lowest as the second attachment figure, and so on. Trinke and Bartholomew (1997) used the ANQ with a sample of individuals aged 17-45 (N =
123) and reported calculating the mean composite score by assigning a score of 1 to the first attachment figure listed, 2 for the second, 3 for the third, and so on. Lower scores reflected a higher tendency to use that attachment figure for the attachment needs.
Primary attachment figures included (in descending order of frequency) mothers, partners, best friends, fathers, and siblings. Freeman and Simons (2018) used the ANQ with a sample of individuals (mean age 20; N = 1,454) and calculated mean difference scores for sum scores of the top three figures (ranking lower by one point on one item =
1; ranking lower by 1 point on 2 items = 2, ranking lower by one point on three items =
3). Primary attachment figures included (in order of descending frequency) mothers, partners, best friends, fathers, and ‘others.’ Finally, Pitman and Sharfe (2010) used the
ANQ with a sample of individuals with a mean age of 20 (N = 267). The attachment hierarchy was assessed by summing and averaging (over the number of questions answered) the rank listings for each attachment figure. The individual with the lowest
83 average was the primary attachment figure, and the rest of the hierarchy was assessed in order of ascending averages. What was needed was a study to identify the primary attachment figure in older adulthood through the calculation of mean composite scores on the ANQ.
It is important to note that some researchers chose to focus on the composition of the attachment hierarchy as a whole rather than identify the primary attachment figure.
Such researchers identified the number of each type of attachment figure in the attachment hierarchy to explore the impact of the attachment hierarchy on well-being.
For these researchers, the proportions of each type of attachment figure in the attachment hierarchy were examined to classify the attachment hierarchy into different categories
(Litwin & Shiovitz-Ezra, 2010; Pitman & Sharfe, 2010). For example, Fiori and colleagues’ (2007) study classified older adults’ hierarchies into five categories: diverse, family-focused, friend-focused, and restricted. Litwin and Shiovitz-Ezra (2010) found support for a sixth category: they classified hierarchies into categories of diverse, friend, congregant, neighbor, family, and restricted. Pitman and Sharfe (2010) delineated between family attachment hierarchies and peer attachment hierarchies. In yet another study, a similar, yet unique, way of establishing the type of the attachment hierarchy was established by Freeman and Simons (2018), who classified attachment hierarchies based on the relationship between the first and second, second and third, and first and third attachment figure types. They established four categories: diversified, monotropic, joint principal, and distributed. Until more research is completed on the attachment hierarchy in older adulthood, the current study is recommending for the identification of the primary attachment figure, in line with methods for calculating the mean composite
84 ranking scores which were outlined in multiple studies (Doherty & Feeney, 2004;
Freeman & Simons, 2018; Pitman & Sharfe, 2010; Rowe & Carnelley, 2005; Trinke &
Bartholomew, 1997).
In addition to the types of attachment figures and the primary attachment figure, another important methodological consideration is the questionnaire to be used. As can be seen in the sections above, one of the most widely used questionnaires for measuring the attachment hierarchy is the Attachment Network Questionnaire (ANQ; Trinke &
Bartholomew, 1997). Freeman and Simons (2018) claimed that the ranking nature of the
ANQ is a good approach to testing the attachment hierarchy because of its ability to test
Bowlby’s (1958) notion that individuals will exhibit “a clear hierarchy of preference” (p.
27). The ANQ contains six ranking questions designed to capture emotions and behaviors which are involved in one’s desire to seek fulfillment of attachment needs. The ANQ’s strengths include that it is a quantitative measure which assesses information regarding the type of relationships in the hierarchy as well as the number of people included in the attachment hierarchy. Another strength is the ability to distinguish between attachment bonds and triggers of attachment needs, which similar measures of the attachment hierarchy have failed to accomplish (Rosenthal & Kobak, 2010).
In summary, this section detailed methods for classifying the types of attachment figures in the attachment hierarchy, which is important for drawing conclusions about the impact of different types of attachment figures across the lifespan. This section also reviewed several ways which can be used to identify the primary attachment figure.
Finally, this section introduced the ANQ. The ANQ is a questionnaire which has been used in attachment theory research with adults and older adults. Further exploration of the
85 psychometric properties of the ANQ will be reviewed in chapter 3. The next section will review the concept of life satisfaction, with particular attention given to research which has examined life satisfaction in adolescence and adulthood.
Life Satisfaction
The current section introduces an important component underlying the current empirical questions. First, the current section explores the conceptualization and definition of the concept of life satisfaction, followed by a review of evidence supporting the utility of life satisfaction as a similar, yet unique, aspect of well-being. Next, this section explores research on life satisfaction in older adulthood. Then, this section reviews the SWLS (Diener et al., 1985), and the LSI-A (Neugarten et al., 1961) two of the most commonly utilized measures of life satisfaction (Faegerstroem, Lindwall, Berg,
& Rennemark, 2012; Lawton, 1977; McCulloch, 1992; McKenzie & Campbell, 1987;
Oishi, 2006; Wallace & Wheeler, 2002).
Conceptualization of Life Satisfaction
The investigation of life satisfaction can be traced back to two fundamental theories: activity theory (Havighurst & Albrecht, 1953) and disengagement theory
(Cumming & Henry, 1961; Lemon, Bengston, & Peterson, 1972). Activity theory posited that older adults would be happiest when socially involved into later life, while disengagement theory suggested that society and older adults gradually and mutually drew apart into older adulthood at the benefit of both. Disengagement theory claimed that older adults would benefit from being released from any obligations and society benefitted by allowing the individual to prepare for death. Although these theories had
86 mixed results and no longer hold the theoretical positions they once did, interest in life satisfaction continues to grow.
Given the great heterogeneity in both affective and cognitive functioning among older adults, investigations into the multidimensional concept of life satisfaction are essential. More and more researchers are focusing on healthy and successful aging
(Cummins, Lau, Davey, & McGillivray, 2010; Ku, Fox, & Chen, 2016; Peel et al., 2005;
Rowe & Kahn, 1997). These terms should be operationalized as more than just more years of life—they should also consist of the quality of life, which can be done through measures of life satisfaction. Assessing levels of life satisfaction can also measure growth, which is in line with the goals of researchers interested in healthy and successful aging (Kane & Kane, 2000). Given Counseling Psychology’s values of social justice and focus on positive psychology, it is understandable why the concept of life satisfaction continues to be a variable of interest. Including measures of life satisfaction can also help to shift popular views of older adulthood from deficit models to views that consider both gains and losses (Baltes, 1987; Wallace & Wheeler, 2002).
Many measures of well-being focus on emotional aspects such as depression or anxiety; possibly due to primary concerns with the emotional aspects of mental illness
(Kane & Kane, 2000). Life satisfaction, on the other hand, compares expectations and perceptions of outcomes for salient components of life such as social situations, relationships, and self-worth (Kane & Kane); making it a sensible choice for researchers interested in both well-being and the attachment hierarchy. According to the literature, the structure of subjective well-being has been conceptualized as consisting of two major components: the emotional (affective) component and the judgmental (cognitive)
87 component (Diener, 1984; Veenhoven, 1996, 2013). Andrews and Withey (1976) conceptualized the judgmental component as life satisfaction. Whereas the emotional component has received considerable attention from researchers, the judgmental component has been relatively neglected (Pavot, Diener, Colvin, & Sandvik, 1991).
Measures of life satisfaction could be used to evaluate treatment outcomes (Kersher,
1992), better understand the cognitive aspects of mental illness, and increase sensitivity to changes in one’s mental state.
According to Pavot and Diener (1993) life satisfaction has been conceptualized as a comprehensive and inclusive component of well-being which embodies a distinct dimension of well-being representing a cognitive and global evaluation of the quality of life as a whole. An individual’s perceptions can have a substantial impact on his or her quality of life, and is arguably just as important as more emotional aspects of well-being.
Measures of life satisfaction can be used to capture an individual’s conscious, judgmental evaluation of life quality (Campbell, 1976; Davern et al., 2007; Diener & Diener, 1996;
Ku, Fox, & Chen, 2016; Pavot & Diener, 1993; Steel & Ones, 2002; Veenhoven, 1994).
According to Diener and colleagues (1985), life satisfaction is one’s perceptions about the quality of one’s life as compared to what is thought to be an appropriate standard.
Life satisfaction is an aspect of well-being which has been understudied in attachment theory research (Pavot & Diener, 1993; Webster, 1998), and a study measuring life satisfaction could add beneficial insight into the impact of the attachment hierarchy in older adulthood. Researchers have also suggested that the complexities of social relations should be taken into account when considering life satisfaction (Subasi & Hayran, 2005):
88 the complexities of social relations is one of the main variables of interest for the current study.
Notably, studies examining the convergent and discriminant validity between life satisfaction and other measures of well-being demonstrate that life satisfaction is a similar, yet unique, aspect of well-being. For example, McKnight, Huebner, and Suldo
(2002), using a sample of adolescents in grades 6-12 (N = 1,201), conducted hierarchical regression using the Student’s Life Satisfaction Scale (SLSS; Huebner, E. S., Laughlin,
Ash, & Gilman, 1991) and the Abbreviated Junior Eysenck Personality Questionnaire
(JEPQ-A; Francis, 1996). Results indicated that 16% of the variance in life satisfaction could be predicted by neuroticism and extroversion. In another study on individuals with a mean age of 16 (N = 515), Gilman, Huebner, and Laughlin (2000) completed canonical correlational analyses between the Multidimensional Student’s Life Satisfaction Scale
(MSLSS; Huebner et al., 1998) and the Behavior Assessment System for Children
(BASC; Reynolds & Kamphaus, 1992). Results indicated that 42% of the variation of the
MSLSS scales was related to the variation in the BASC, suggesting convergent validity between the MSLSS Self scale and the BASC Self-Esteem scale and discriminant validity between the MSLSS scales and the BASC Clinical scales. Greenspoon and Saklofske
(2001) conducted discriminant function analyses between the MLSS (Harner & Heal,
1993) and the social stress, anxiety, and depression subscales of the BASC (Reynolds &
Kamphaus, 1992) with a sample with a mean age of 10.5 years (N = 407), and reported that the BASC predicted 90.7% of the variance in life satisfaction. Finally, Gullone and
Cummins (1999) used a sample aged 12-18 years (N = 264) to conduct correlational analyses between the Comprehensive Quality of Life Scale (ComQol; Cummins,
89 McCabe, Romeo, & Gullone, 1994) with two self-report measures of fear and anxiety.
They found that both fear and anxiety were related to low levels of quality of life.
Life Satisfaction and Older Adults
The study of subjective well-being is crucial in research on aging. Investigations into life satisfaction have shown significant relationships between life satisfaction, age and social interaction (Larson, 1978). Such relationships indicate that the attachment hierarchy, which is social in nature, may be associated with levels of life satisfaction, and that it may be different between the young-old and mid-old. Low levels of life satisfaction often indicate a serious deficit in physical health, mental health, and/or social relationships (Fred, 1984; Subasi & Hayran, 2005), which have been linked to length and quality of life (Litwin, 2007). Levels of life satisfaction should be considered alongside the core issue of prolonging life (Ebersole, 1995; Subasi & Hayran, 2005) and promoting healthy and successful aging. Along with the connection between life satisfaction and physical and affective functioning, life satisfaction has become a reliable tool in rehabilitation and determining the efficacy of health care services (Ebersole, 1995). For example, researchers have linked life satisfaction with overall cognitive functioning and physical activity (Subasi & Hayran, 2005; Tulske & Rosenthal, 2003). However, little attention has been paid to the possible impact of the attachment hierarchy.
As was stated previously, well-being was found to be amenable to effective interventions to improve the quality of life for older adults (Okun, Olding, & Cohn,
1990). Although the benefits dissipated over the period of one month post-treatment, control-enhancement, psychoeducation, and social activity interventions were all found to positively impact the well-being of older adults. Results from Okun and colleagues
90 suggest the possibility for interventions that improve life satisfaction in older adulthood, possibly through improvements in the attachment hierarchy. Additionally, because life satisfaction in older adulthood varies across age (Berg, Hoffman, Hassing, McClearn, &
Johansson, 2009; Chen, 2001; Faegerstroem et al., 2012), there is reason to wonder about potential associations linking the attachment hierarchy and life satisfaction between the young-old and mid-old.
Life satisfaction is a complex variable in older adulthood because it is associated with a myriad of other variables. For older adults, life satisfaction intimately relates to variables such as physical health, mental health, mortality (Litwin, 2007), and ability to participate in social activities and engage with their families (Hsu, 2016; Lu, Lum, &
Lou, 2016), healthy aging, optimism, the maintenance of well-being, (Kiarsipour,
Borhani, Esmaeili, & Zayeri, 2017; Olson, Fanning, Awick, Chung, & Edward, 2014), health (Bishop, Martin, & Poon, 2006), and resiliency (Hayat, Khan, & Sadia, 2016;
Zhang, Yu, Zhang, & Zhou, 2017). Multiple studies have included the variable of life satisfaction in an effort to test the assumption that life satisfaction decreases with age
(Hsu, 2016; Kim, Lee, & Ji, 2018). For instance, Hsu (2016) reported that 21.8% of older adults had stable low life satisfaction; 39.7% had stable mid-range life satisfaction;
25.9% had increasing levels of life satisfaction; and 12.5% had declining levels of life satisfaction across older adulthood. Having more education and better physical and psychological health, social support, and economic satisfaction were predictors of a higher life satisfaction trajectory, and maintaining good physical and emotional health, having a spouse, and having better economic satisfaction were associated with an increase in life satisfaction over time. Conversely, Kim, Lee, and Ji (2018) found that
91 when physical health was limited or one has a disability, life satisfaction declined across all of the following domains: age, sex, marital status, education, health, socioeconomic status, social life, finances, leisure activities, and career.
Studies which investigated the impact of the types of attachment figures in the attachment hierarchy on life satisfaction in older adulthood suggest that family may play an important role in the life satisfaction. For example, older adults aged 69-73 (N = 81) who participated in a study by Kirchmann et al. (2013) completed the Life Satisfaction
Index A (Neugarten, Havighurst, & Tobin, 1961). Results indicated that the presence of romantic partners in the attachment hierarchy were associated with higher levels of life satisfaction. Bai, Guo, and Fu (2018) used author-created questions about intergenerational relationships and the Chinese version of the Satisfaction With Life
Scale: the Chinese version of the SWLS which was psychometrically validated by Bai,
Wu, Zheng, and Ren (2011). Individuals aged 60-96 (N = 1,099) who reported close relationships with their children and grandchildren also reported high levels of life satisfaction.
In a similar study, both familial attachment figures and community attachment figures correlated positively with life satisfaction. Lu, Lum, and Lou (2016) used the Life
Satisfaction Scale for Chinese older adults (Lou, Chi, & Mjelde-Mossey, 2008) and the
Intergenerational Solidarity Inventory (Mangen, Bengston, & Landry, 1988). Lu and colleagues evenly distributed participants into groups of 60-69, 70-79, and 80-89 (N =
362). Unfortunately, the age groups were not compared for significant differences.
Results indicated that support from family members and support from the community both played a part in the life satisfaction levels of older adults. Intergenerational
92 relationships with grandchildren mediated the correlation between relationships within the community and life satisfaction. Relationships with grandchildren were related with more stable mental health and higher resilience. For those without intergenerational relationships, relationships within the community was positively correlated with life satisfaction. The authors recommended that interventions which increase interactions between older adults and their community can assist those who do not have relationships with grandchildren.
The SWLS and the LSI-A
The complexity of capturing meaning of life satisfaction calls for instruments that have been developed and validated carefully and which instruments which show robustness and adaptability to different populations (Faegerstroem et al., 2012). Two of the most popular and widely used scales for measuring life satisfaction are the
Satisfaction with Life Scale (SWLS: Diener et al., 1985; Oishi, 2006) and the LSI-A
(Neugarten et al., 1961). The SWLS and LSI-A were developed as measures of the judgmental component of subjective well-being and have been shown to be reliable and valid (Diener et al., 1985; Faegerstroem et al., 2012; Koeker, 1991; Kooshar & Bonab,
2011; Lane, 2016; Lawton, 1977; Pavot & Diener, 2008; Post, van Leeuwen, van
Kopenhagen, & de Groot, 2012; Scharfe, 2016; Vassar, 2008; Wallace & Wheeler, 2002;
Wang, 2016).
The SWLS is a short questionnaire which can be completed quickly to save time and resources as compared to many other measures of life satisfaction (Pavot, Diener,
Colvin, & Sandvik, 1991). In addition, the high convergence of self- and peer-reported measures of subjective well-being and life satisfaction provide strong evidence that
93 subjective well-being is a relatively global and stable phenomenon, not simply a momentary judgment based on fleeting influences (Pavot, Diener, Colvin, & Sandvik,
1991). The SWLS is a Likert Scale which includes five items (i.e., In most ways my life is close to my ideal). Questions are ranked from one to seven (1 = strongly disagree, 7 = strongly agree). To develop this scale, Diener et al. (1985) generated a list of 48 self- report items about the cognitive aspects of satisfaction with life, with a few affective items included. Initial factor analyses resulted in three factors: positive affect, negative affect, and life satisfaction. The affective items were removed, as well as factors which had loadings of less than .60. Ten items remained, and five were eliminated due to semantic similarity.
One of the most influential studies completed thus far regarding life satisfaction and the attachment hierarchy was completed by Yildiz (2016), who used the SWLS and the Inventory of Parent and Peer Attachment (IPPA; Armsden & Greenberg, 1987).
Yildiz reported that high school students with a mean age of 15 years (N = 218) whom included the mother, father, and peers in the attachment hierarchy had higher levels of life satisfaction. Correlational analyses, ordinal least-squares regression with bootstrap method analyses, and serial multiple mediation model were conducted. Some limitations of this study included its failure to include older adults, and its reliance on measurements of the attachment hierarchy with a questionnaire which restricted the focus of attachment hierarchies to the mother, father, and peers. What was needed was a study which allows for the identification of a variety of attachment figures in the attachment hierarchy and an examination into how the primary attachment figure is related to life satisfaction in older adulthood.
94 Several other studies have used the SWLS to investigate life satisfaction in young adulthood. For example, for individuals approximately age 20 (N = 136) who completed the NEO-PI-R (Costa & McCrae, 1992) and the SWLS, personality traits were found to relate with life satisfaction (Schimmack et al., 2004). Neuroticism and extraversion accounted for 22-26% of the variance in life satisfaction, and depression as measured in the neuroticism scale accounted for 27%. In a similar study, Shahrazad, Kadir, Omar, and
Halim (2015) found that young adults aged 18-21 (N = 315) who had traits of neuroticism had lower levels of life satisfaction. They used the NEO-FFI (Costa & McCrae, 1980), the Attachment Style Questionnaire (ASQ: Feeney, Noller, & Hanrahan, 1994), and the
SWLS. Extraversion and conscientiousness correlated positively with life satisfaction.
In other studies which used the SWLS with young adults, life satisfaction was found to correlate positively with vitality (Tremblay et al., 2006), perceived social support, self-compassion, (Toplu-Demirtas, Kemer, Pope, & Moe, 2018); and negatively with depressed mood (Tremblay et al., 2006). Toplu-Demirtas, Kemer, Pope, and Moe
(2018) reported that adults ages 18-28 years (N = 291) listed friends, family, and peers as attachment figures; familial support was the biggest predictor of life satisfaction. Toplu-
Demirtas and colleagues interpreted their results as support for attachment theory: the associated of family and life satisfaction could be explained as parental warmth and safeness increasing feelings of belonging and decreasing feelings of isolation. For adults with an average age of 43 years (N = 481), life satisfaction correlated positively with job satisfaction (Sumer & Knight, 2001).
The studies above reviewed how researchers measured life satisfaction in adulthood. Although Diener and colleagues (1985) showed initial utility of the SWLS
95 with older adults, few researchers have utilized the SWLS to investigate the attachment hierarchy. What was needed was a study investigating the relationship between one’s attachment hierarchy and life satisfaction in older adulthood, as this may offer unique insight into the cognitive aspect of well-being which has not yet been thoroughly examined. If the impact of the attachment hierarchy on life satisfaction can be better understood, it may be possible for psychologists to develop interventions that assess and improve the attachment hierarchy to maximize healthy aging. This section now transitions to review studies that have used the SWLS with older adults.
One influential study which examined the relationship between the size of the attachment hierarchy and life satisfaction in older adulthood was conducted by Wang
(2016), who reported that individuals aged 61-71 (N = 314) with higher numbers of attachment figures also had high life satisfaction. Wang asked participants to answer author-created questions about the number of people in the attachment hierarchy, and complete the Multidimensional Scale of Perceived Social Support (PSSS: Zimet et al.,
1988) and the SWLS. Results showed that the positive effects between the size of the attachment hierarchy and life satisfaction was mediated by perceived support. Wang
(2016) demonstrated the utility of using the SWLS with older adults. However, Wang
(2016) did not investigate the influence of either the primary attachment figure or the types of people in the attachment hierarchy. What was needed was a study exploring the influence of the primary attachment figure and the types of attachment figures included in the attachment hierarchies within different epochs of older adulthood, as well as the impact of the attachment hierarchy on life satisfaction levels of older adults.
96 Finally, it is important to note that the SWLS has also been used with older adults in research on topics outside of attachment theory for the assessment of life satisfaction in older adults. In addition to the study completed by Wang (2016), numerous studies indicated the successful utility of the SWLS in samples of older adults (Bai, Guo, & Fu
2018; Haron, Foong, & Hamid, 2018; Karadag Arli, Bakan,& Aslan, 2018; Kiarsipour et al., 2017; Lamoureux-Lamarche & Vasiliadis, 2017; Lu, Lum, & Lou 2016).
In addition to the SWLS, the current study also proposes to use the LSI-A
(Neugarten et al., 1961), which is one of the most frequently used measures of life satisfaction in studies of aging, and is reported as having “the most careful psychometric derivation” (Lawton, 1977, p. 13). In fact, The LSI-A is one of the earliest and most widely used measures of life satisfaction that was developed specifically for older adults
(Faegerstroem et al., 2012; Wallace & Wheeler, 2002). With the goal of identifying successful aging, and a desire to develop a measure of life satisfaction specifically for older adults, Neugarten and colleagues conducted a thematic analysis of the existing measures of adjustment and morale. The result was a measure of life satisfaction that was independent from various other psychological and social variables. They developed operational definitions for five components; zest vs. apathy, resolution and fortitude, congruence, self-concept, and mood tone. Zest measures the extent to which one takes pleasure from activities of daily life. Resolution and fortitude measures the degree that a person regards life as meaningful and accepts their earlier life experiences. Congruence measures the congruence between desired and achieved life goals. Self-concept measures whether a person holds a positive image of the self. Mood tone measures the degree to which a person maintains happy and optimistic attitudes and mood.
97 In support of the merit of studying the impact of the attachment hierarchy on the life satisfaction levels of two groups within older adulthood, researchers have reported that social activities had a direct effect on LSI-A scores (Iwatsubo et al., 1996; Neugarten et al., 1961). The LSI-A is a widely used, 20 item questionnaire that is answered through self-report in an agree/disagree format. The questions tap trait characteristics which makes answers stable over time (Lawton, 1997). The limited-response format reduces the complexity of the instrument and increases brevity. Twelve items are positively worded, and eight are negatively worded. Scores are generated by summing the responses that match keyed responses.
Subasi and Hayran (2005) showed that life satisfaction in older adulthood may be linked to leisure activities. Older adults above age 60 (N = 183) who prioritized fulfilling leisure activities had higher life satisfaction. Participants completed the LSI-A and answered questions about leisure activities. Scoring methods reflected the more conventional method outlined in Wood et al. (1969) which added the answer response of don’t know, and scores ranged from zero to forty. Subasi and Hayran (2005) concluded that the complexities of personality, demographics, and social factors must collude to influence life satisfaction levels. In a similar study by Ku, Fox, and Chen (2016) individuals aged 70 and above (N = 1,268) completed the CES-D, the LSI-A and provided information about their leisure time activities. They used the original method of scoring in which participants indicated if they agreed or disagreed with questions. Results indicated that both leisure-time sedentary behaviors and leisure-time physical activity were positively correlated with life satisfaction. They speculated that cognitive and social leisure activities (regardless of their physical or sedentary nature) benefit life satisfaction
98 because they satisfy human needs for relaxation and social, psychological, cognitive and educational desires.
Other studies using the LSI-A (Neugarten et al., 1961) with older adults linked life satisfaction to levels strain. Older adults aged 60-96 (N = 2,602) in caregiving relationships were found to report a negative relationship between strain in the caregiving relationship and life satisfaction (Dahlrup, Elkstroem, Nordell, & Elmstahl, 2015).
Dahlrup and colleagues used the Goeteborg Quality of Life instrument (Tibblin,
Bengtsson, Furunes, & Lapidus, 1990), the Health locus of control (HCL; Wallston,
Wallston, Kaplan, & Maides, 1976), the Short Form Health Survey (SF12; Sullivan,
Karlsson, & Ware, 1995), the LSI-A, and a model of social anchorage, social support, and social participation. The LSI-A was scored with a version of the scoring method outlined in Wood et al. (1969) which allowed participants to answer disagree, doubtful, or agree, and produced scores ranging from zero to forty. They speculated that caregivers with higher strain likely find it difficult to spend time with friends or family.
Redmond (1990) used the LSI-A (Neugarten et al., 1961) with individuals aged
18-90 (N = 414) and reported a decrease in zest and mood tone (decreased pleasure in daily activities, as well as feelings of happiness and optimism), and an increase in congruence (increased satisfaction between desired and attained goals) in individuals aged 75 and older. Redmond speculated that this may be due to older-adults’ ability to maintain positive evaluations of life’s accomplishments even when they are relatively unhappy.
Finally, one study investigated the impact of age on life satisfaction within older adulthood by using the LSI-A (Donnenworth et al., 1978; Neugarten et al., 1961).
99 Participants were also asked questions about their frequency of contact with attachment figures. Frequency of contact positively correlated with life satisfaction (r = .29, p
<.001), and age negatively correlated with life satisfaction (r = -.15, p <.001).
In summary, the current section reviewed the distinctions between life satisfaction and other aspects of subjective well-being. Life satisfaction measures the cognitive aspects of well-being, which have been relatively neglected in research on the attachment hierarchy. The SWLS and the LSI-A are questionnaires that have been widely used to measure life satisfaction which are viable measures for the current study because of their good psychometrics, ease of use, and concise presentation. The next section will review the main tenants of the current study and identify the research hypotheses.
Conclusion and the Present Study
The present section includes an outline of the current study, including the research questions and hypotheses of the empirical questions. To summarize this literature review, this study examined the relationships between attachment hierarchies (size and types of attachment figures) and life satisfaction across two major epochs of older adulthood. Few studies have explored the attachment hierarchy in the later stages of life, and the present study expanded counseling psychology’s overall conceptualization of the impact of the attachment hierarchy throughout the lifespan by focusing on older individuals.
Specifically, this study addressed the following research questions among an older population: 1) Does the size of the attachment hierarchy correlate positively with life satisfaction in either the young-old or mid-old groups? 2) Is there a substantial difference in the size of the attachment hierarchy between the young-old and mid-old? 3)
Do individuals with different primary attachment figures have different numbers of
100 attachment figures in the attachment hierarchy in either the young-old or mid-old groups?
4) Do individuals with different primary attachment figures have different levels of life satisfaction in the young-old or mid-old groups? 5) Does the primary attachment figure identified differ between young-old and mid-old?
Due to the positive association between life satisfaction and various aspects of healthy aging (Bishop, Martin, & Poon, 2005; Hayat, Khan, & Sadia, 2016; Olson et al.,
2014), there is potential for psychology to positively influence the life satisfaction of older adults through theoretical conceptualization of developmental trends and therapeutic interventions focused on attachment activities. The present study will help counseling psychology better understand the relationship between attachment hierarchies and life satisfaction, and create potential direction for research to further explore interventions which could effectively increase the size and quality of the attachment hierarchy, and to increase the life satisfaction of older adults.
Hypotheses
My first hypothesis was that the size of the attachment hierarchy would correlate positively with life satisfaction. This relationship was tested within each age epoch separately: a) the young-old (ages 65-74); and b) the mid-old (ages 75-84). Each age group was assessed for significant correlations between the size of the attachment hierarchy and life satisfaction levels. This hypothesis was based on attachment theory’s conceptualization of the attachment hierarchy as a resource for fulfilling attachment needs. Hypothesis one was in line with the convoy model (Kahn & Antonucci, 1980) which would see an increased number of people in the attachment hierarchy as an increased likelihood for the fulfillment of emotional and/or instrumental needs.
101 Additionally, empirical evidence suggests that environmental factors [such as social support] are strong predictors of life satisfaction (Kooshar & Bonab, 2011), and that the size of the attachment hierarchy has been correlated positively with general measures of well-being (Cohen & Janicki-Deverts, 2009; Jetten, Haslam, & Branscombe, 2009), and negatively with depression (Gillath, Johnson, Seluk, & Teel, 2011; Iyer et al., 2009;
Osborn et al., 2003).
My second hypothesis was that there would be differences in the size of the attachment hierarchy between the young-old and mid-old groups. Specifically, I expected the size of the attachment hierarchy to be significantly reduced in the mid-old group. The main components of this hypothesis were tested through the separation of two age epochs based on chronological age. Another aspect considered was subjective age, which the present study measured in order to further explore meaningful age ranges by which to explore developmental differences across older adulthood.
Hypothesis two was in line with SST (Carstensen, 2006) which would explain a decrease in the size of the attachment hierarchy as a selective pruning of the attachment hierarchy in order to better control the quality of the relationship and his or her ability to regulate emotions by surrounding the self with positive others. In addition, empirical research suggests that, compared to younger adults, older adults have fewer attachment figures in the attachment hierarchy (Cicirelli, 2010; Doherty & Feeney, 2004).
Additionally, some studies suggest a negative correlation between age and the number of attachment figures in the attachment hierarchy (Cornwell, Laumann & Schumm, 2008;
Smith et al., 2015).
102 My third hypothesis was that individuals with different primary attachment figure types (as assessed according to the categories of family, romantic partner, peer, and other) would have pointedly different numbers of attachment figures in the attachment hierarchy. To test this, the data were assessed for significant group differences (as identified by the primary attachment figure) in the number of attachment figures in the attachment hierarchy. Theoretically, attachment theory would explain that different types of primary attachment figures would have different abilities to meet an older adult’s attachment needs, which could impact an older adult’s need for more or less subsequent relationships to fulfill attachment needs. The convoy model (Kahn & Antonucci, 1980) would describe it in similar terms, but replace attachment needs with emotional and instrumental needs. This is also based on empirical research of individuals aged 18-94 which suggested that individuals who listed the same attachment figure for all three attachment needs tended to have fewer attachment figures in the attachment hierarchy
(Doherty & Feeney, 2004). Individuals who listed their children (Feeney et al., 2001), or family (Litwin & Shiovitz-Ezra, 2010) as primary attachment figures list fewer attachment figures in the attachment hierarchy. Litwin and Shiovitz-Ezra (2010) reported that older adults with friend hierarchies had significantly larger attachment hierarchies.
There is a noteworthy lack of research investigating the influence of romantic relationships on the size of the attachment hierarchy. According to Feeney et al. (2001), friendships and other relationship types are likely to suffer as adults enter committed relationships and juggle the demands of family and work. Less is known about the impact of romantic partners as primary attachment figures on the size of the attachment hierarchy. Carr and Boerner (2013) suggested that older adults who begin dating risk
103 conflict with family members (especially children). Therefore, I expected to find that individuals with a primary attachment figure who was family and/or romantic partner would have significantly fewer attachment figures in their attachment hierarchies, and individuals with a primary attachment figure of friend would have significantly more attachment figures than individuals with a primary attachment figure of “other.”
My fourth hypothesis was that individuals with different primary attachment figure types (as measured according to the categories of family, romantic partner, peer, and other) would have significantly different levels of life satisfaction. Theoretically, attachment theory would explain the differences in the relationships between the types of primary attachment figures and life satisfaction as due to each figure’s ability to meet the attachment needs. Late-life attachment is theoretically predicted by indices of intra- individual and inter-individual functioning. The convoy model (Kahn & Antonucci,
1980), on the other hand, would explain that each figure would have a different ability to meet the emotional or instrumental needs of the older adult. This is also based on empirical research which suggests that the types of people comprising the attachment hierarchy appear to have an impact on well-being (Litwin & Shiovitz-Ezra, 2010; Yildiz,
2016), especially for the relationships between an older adult and his or her children and grandchildren (Bai, Guo, & Fu, 2018; Lu, Lum, & Lou, 2016). According to Lopez,
Ramos, and Kim (2018), older adults reported higher anxiety for potential abandonment from family members than romantic partners. I expected to find that individuals who had friends or family as primary attachment figures would report higher levels of life satisfaction than individuals who choose romantic partners or “other.”
104 My fifth hypothesis was similar to the fourth: the young-old and mid-old groups would report different primary attachment figures. It was my hypothesis that the primary attachment figures in each epoch would be unique. Attachment theory would suggest that differences in the environment and in an individual’s needs would require the attachment hierarchy to adapt. The convoy model (Kahn & Antonucci, 1980) would suggest that adaptations in the attachment hierarchy would reflect an individual’s attempt to manage the hierarchy to improve its ability to meet functional needs. Additionally, empirical research has suggested there may be a possible shift from family toward friends and intangible attachment figures in older adulthood (Cicirelli, 2010; Pitman & Sharfe, 2010).
On the other hand, it has also been suggested that an orientation toward family may increase across older adulthood (Doherty & Feeney, 2004; Freeman & Brown, 2001;
Neugarten, 1974; Smith et al., 2015). Freeman and Simons (2018) and Hrdy (2011) espoused that the preference for attachment figures depends upon the individual’s circumstances: when one cannot afford to choose a preferred attachment due to necessities of care-taking, the preferred attachment may become the attachment figure which is present. Because health is more likely to decline with increasing age, I hypothesized that significantly larger numbers of the mid-old would report primary attachment figures who were categorized as “other.”
105
CHAPTER III
METHODS
This chapter provides detailed information regarding participants for the study, measures used, procedures that were followed, and my hypotheses. Information about participants is presented first, followed by a review of the measures which were utilized.
Included in the measures section are tables outlining the distributions of demographic variables for the current study’s participants, and a presentation of established reliability and validity for each measure. Next is the procedures section, followed by a description of the current study’s hypotheses.
Participants
The population of interest for this study was older adults between the ages of 65 and 74, with participants ages 65-74 labeled as the young-old and participants ages 75-84 labeled as the mid-old. These ages were chosen based on literature suggesting age ranges to test for different developmental trends occurring across the years of older adulthood
(Cicirelli, 2002b, 2006, 2010). To combat the arbitrary nature of age determinants for the different epochs of older adulthood, subjective age was also assessed and included in analyses.
106 Recruiting older adult participants can be a time-consuming process with substantial challenges (Chatters et al., 2018; Howatson, 2007; Piantodosi et al., 2004;
Piantodosi et al., 2015; Richards, Pound, Dickens, Greco, & Campbell, 2007). Like other stages of life, recruitment for older adults has no “one size fits all” approach (Stahl &
Vasquez, 2004). To minimize the potential barriers to obtaining older adult participants, the current study collected data for the first two subgroups identified in the literature. The old-old were excluded due to an empirically documented difficulty obtaining data within this age group and the desire to focus the work of the present study. In line with the literature, (Corcoran et al., 2016; Ellish, Scott, Royak-Schaler, & Higginbotham, 2010;
Miller et al., 2017; Piantodosi et al., 2015) a combined method for the recruitment methods were considered in order to overcome general recruitment challenges with the older adult population. However, following the recruitment methods of several researchers (Stothart, Boots & Simons, 2015; Syme, Cohn, & Barnack-Tavlaris, 2017;
Webb, Cui, Titus, Fiske, & Nadorff, 2018), enough data were collected (N = 209) through Turk Prime that no other method was required.
Data collection occurred in a cross-sectional questionnaire survey approach. The survey was created on Qualtrics.com and linked to MK Turk to establish security and confidentiality (Mason & Suri, 2012; Paolacci, Chandler, & Ipeiroris, 2010; Schmidt,
2007). Qualtrics is a survey platform which is often used in research studies at The
University of Akron. Participants on MK Turk provided answers anonymously, and the link to Qualtrics ensured that responses could not be linked to their identity (Paolacci,
Chandler, & Ipeiroris, 2010). MK Turk studies are often exempt from IRB review due to these security measures (Paolacci, Chandler, & Ipeiroris, 2010). Connecting to Qualtrics
107 also allowed for guarding against multiple submissions, increased control over the content, and the use of multiple pages in the survey (Birnbaum, 2004; Mason & Suri,
2012).
MK Turk is an open online marketplace with over 380,000 users (Difallah,
Filatova & Ipeirotis, 2018; Simons & Chabris, 2012; Stothart, Boot, & Simons, 2015) from over 100 countries (Buhrrmester, Kwang, & Gosling, 2011; Difallah et al., 2018).
MK Turk is as representative of the U.S. population as traditional subject pools (Difallah et al., 2018; Gosling et al., 2004; Ipeirotis, 2009; Paolacci, Chandler, & Ipeiroris, 2010;
Ross et al., 2010). MK Turk provided easy access to an inexpensive and rapid data collection method of heterogeneous samples with greater demographic diversity (age, ethnicity, socioeconomic stats, language, and country of origin) than traditional online sampling (Buhrmester, Kwang, & Gosling, 2011; Mason & Suri, 2012; Paolacci,
Chandler, & Ipeiroris, 2010; Stothart, Boot, & Simons, 2015).
MK Turk has been validated as a means to collect behavioral (Crump,
McDonnell, & Gureckis, 2013; Eriksson & Simpson, 2010; Mason & Watts, 2009; Suri
& Watts, 2009) and clinical data (Shapiro, Chandler, & Mueller, 2013). MK Turk has also been validated in aging research for use with older adults (Stearns, Nadorff, Lantz, &
McKay, 2018; Stothart, Boot, & Simons, 2015; Syme, Cohn, & Barnack-Tavlaris, 2017).
To test for accuracy, Stothart, Boot, and Simons (2015) asked participants to report both age and year of birth, and 98% of participants reported their age accurately. As of 2012, more than 5,337 MK Turk participants were aged 65 and above (Simons & Chabris,
2012); the number would no doubt be larger today. It has been speculated that the number
108 of older adults online will increase rapidly, expanding the number of older adult participants on MK Turk as well (Pew Research Center, 2014).
Prior to data collection, several power analyses were completed in G*Power
(Faul, Erdfelder, Lang, & Buchner, 2007) to determine required sample sizes to adequately test each hypothesis. The statistical test that required the largest number of participants was the one-way ANOVA required for hypothesis three. G*Power calculations used an estimation of an effect size approximating f = 0.25 (medium; Cohen,
1988) and results indicated a target goal of 158 participants—79 in each epoch—for 0.80 power.
Approximately $235.00 was paid to MK Turk for program fees and monetary incentives ($1.00) provided to each participant. This participation incentive was comparable to other studies of similar length according to Dr. J. Stanley at The
University of Akron (personal communication, May 3, 2019) and the literature (Stothart,
Boots, & Simons, 2015; Webb, Cui, Titus, Fiske, & Nadorff, 2018). Every participant who completed the survey was provided with the incentive regardless of missing data or answer quality. A subset of individuals did not complete the survey, which automatically excluded them from the incentive due to MK Turk policies and procedures.
Incentives on MK Turk can range from one cent (Buhrmester, Kwang, & Gosling,
2011) to $3.00 for a thirty-minute survey (J. Stanley, personal communication, May 3,
2019). Studies have shown that MK Turk participants were not driven by financial incentive, that data did not differ depending on the financial incentive amount, and that the incentive only affected the speed of data collection (Buhrmester, Kwang, & Gosling,
2011; Marge, Banerjee, & Rudnicky, 2010; Mason & Suri, 2012; Mason & Watts, 2009).
109 MK Turk is comparable to the behavior of laboratory subjects (Fehr & Gachter, 2000;
Gosling, Vazire, Srivastava, & John, 2004; Horton, Rand, & Zeckhauser, 2011; Krants &
Dalal, 2000; Mason & Suri, 2012; Paolacci, Chandler, & Ipeirotis, 2010). Internal consistency of self-reported demographics on MK Turk has been high, with a false response rate below 3% (Mason & Suri, 2012). Non-response rates are less of a concern in MK Turk than internet convenience samples (Paolacci, Chandler, & Ipeiroris, 2010).
Test-retest reliabilities were high for MK Turk collection (r = .80-.94; mean r = .88), and were been compared favorably with test-retest correlations of traditional methods
(Buhrmester, Kwang, & Gosling, 2011).
In line with the work of Mason and Suri (2012), as well as the recommendation of
Dr. J. Stanley at The University of Akron (personal communication, May 3, 2019), the current study included a repeated verifiable question (“What is your favorite color?”) to reduce the chance of submissions from non-human sources and participants who answer hastily without considering the question. It was made clear in the instructions that surveys with incorrect verifiable answers would not be accepted. Additional consideration was taken for patterns of responses, in line with Zhu and Carterette (2010) and Mason and
Suri (2012).
Data collection began on 07/25/2019 with a pilot study consisting of 20 participants to ensure that the study was proceeding as anticipated. Thereafter, data were continuously collected until 08/09/2019. MK Turk was programmed to continue data collection in each of the two epochs of older adulthood—young-old (age 65-74) and mid- old (age 75-84), as recommended by Cicirelli (2010)—until a minimum of 88 participants completed the survey. As a result, an approximately equal number of
110 participants were recruited for the subgroups of young-old (ages 65-74; n = 89) and mid- old (ages 75-84; n = 88). The length of time taken to complete the survey ranged from 2 minutes and 47 seconds to 46 minutes and 26 seconds, with an average of 8 minutes and
22 seconds. No one was found to have a time that reflected work done faster than a human could possibly complete the survey. A total of 209 participants completed the questionnaire through Turk Prime. Exclusion criteria included those who did not meet the following criteria: a) from the U.S.A. (screened before data collection), b) aged 65 to 84, c) mis-matched answers on the repeated attention-check question (“What is your favorite color?”), d) those who reported no attachment figures or inconsistent information about the attachment hierarchy, e) first-time responding to the questionnaire.
Measures
In an effort of consistency, the questionnaires were provided in the same order for all participants. Consistency was particularly important due to the multiple methods that the current study used to gather data. Additionally, communication with the author of the
ANQ (K. Bartholomew; personal communication, May 6, 2019), as well as a review of literature (Doherty & Feeney, 2004; Freeman & Simons, 2018; Rowe & Carnelley, 2004;
Trinke & Bartholomew, 1997) suggested that order effects were not indicated for the questions on the ANQ.
Demographic Questionnaire
Participants started the survey by answering demographic questions (See
Appendix A) regarding, their age, subjective age, sex, race/ethnicity, marital status, education, health, employment status, finances, and living arrangements. To combat the arbitrary nature of age in distinguishing epochs of older adulthood, subjective age was
111 also measured. In line with Choi, DiNitto, and Kim (2018), who found that age related with well-being in older adulthood, subjective age was measured with the question:
“Sometimes people feel older or younger than their age. During the last month, what age did you feel most of the time?” Answers were coded as continuous variables. Table 3.1 provides a summary of the distribution statistics for the total sample as well as in each epoch.
Sex was measured according to best practices with two sets of questions. The first question inquired about sex at birth with options for male and female. The second question asked about current gender identification with options for male, female, transgender, and I don’t consider myself male, female, or transgender. These two questions were shown to have utility with the older adult population (Michaels et al.,
2017). Race/ethnicity was measured through participants choosing as many of the following options that apply: American Indian or Alaskan Native, Asian, Black or
African American, Hispanic or Latino, Native Hawaiian or Other Pacific Islander, White or Caucasian, and/or Other. These categories were identified by U.S. Census Bureau
(2010). Marital Status was measured with the choice of seven options: in a committed relationship of less than two years, in a committed relationship of two years or more, married, separated, divorced, widowed, and not in a committed relationship. These seven options were created for the current study with the assistance of Dr. J. Stanley at The
University of Akron (personal communication, May 3, 2019), with special consideration on this variable due to the social nature of the empirical question. Education was measured with the options of less than primary education, primary education, high school
(as measured by Celik et al., 2018). At the suggestion of Dr. Stanley at The University of
112 Table 3.1. Age and Subjective Age Distribution Statistics for the Total Sample Variable M SD Range Skew Kurtosis Young-Old (n = 86) Age 68.5 2.63 65-74 0.37 -1.02 Subjective Age 59.56 13.38 20-100 0.14 0.92 Mid-Old (n = 85) Age 77.65 2.38 75-84 0.89 -0.005 Subjective Age 67.47 11.15 30-85 -0.90 0.61 Total Sample (N = 171) Age 73.10 5.23 65-84 0.004 -1.15 Subjective Age 63.54 12.90 20-100 -0.37 0.27
Akron, (personal communication, May 3, 2019), two options for higher education were added: undergraduate education, and graduate education. Celik and colleagues (2018) only included one option for higher education. Health was measured with the question
“How do you regard your health compared to others your age?” Answers were coded as
0, 1, or 2, with 0 being not as good as others, 1 being as good as others, and 2 being better than others, as done in Bratt et al. (2017). Employment status was measured with the question “Are you employed?” Options included yes or no, as was measured in Celik and colleagues (2018). Financial status was self-ranked from 1-5 (very poor, poor, fair, rich, very rich), as measured in Bai, Gui, and Fu (2018). Living arrangements was measured with the options of living alone, living with a spouse or partner and child(ren; or grandchildren), living with a spouse or partner only, living with children (or grandchildren) only, living with others, living in a nursing home. These categories were identified and used by Mao and Han (2018), and altered to include the option of grandchildren and partners for the purposes of the present study.
Table 3.2 provides data on the demographic variables in the young-old, mid-old, and across the total sample. Across the total sample, participants ranged in age from
113 Table 3.2. Demographic Variables for Total Sample and by Age Group Demographic Young-Old Mid-Old Total Sample Variable (n = 86) (n = 85) (N = 171) Age 65-74 years - - 86 75-84 years - - 85 Sex Male 47 35 82 Female 39 50 89 Race White or Caucasian 79 72 151 Black or African American 3 6 9 Native Hawaiian or Other Pacific 1 1 2 Islander Asian 1 1 2 Hispanic or Latino 1 1 2 “Other” 1 4 5 Marital Status Married 44 39 83 Widowed 11 29 40 Divorced 18 10 28 Not in a Committed Relationship 8 6 14 Separated 2 - 2 In a Committed Relationship 3 1 4 Education Primary School - - 1 High School 28 34 62 Undergraduate Education 34 33 67 Graduate Education 24 17 41 Health Worse than Others 19 20 39 Same as Others 46 37 83 Better than Others 21 28 49 Employment Employed 26 7 33 Not Employed 60 78 138 Financial Very Poor 4 1 5 Status Poor 14 7 21 Fair 60 72 132 Rich 7 5 12 Very Rich 1 - 1 Living Living with Spouse Only 38 32 70 Arrangements Living Alone 30 33 63 Living with Spouse and 11 6 17 Children/Grandchildren Living with Children/ 3 10 13 Grandchildren Living with Others 4 4 8
114 65 years to 84 years. The platykurtic distribution is understandable considering the strict inclusion criteria of individuals between the ages of 65 and 84. In regards to subjective age, 41 (23.2%) of participants reported no age difference between their age and subjective age. One hundred and seventeen (66.1%) reported subjective ages that were an average of 15.64 years younger than their age; 19 (10.73%) reported subjective ages that were an average of 10.4 years older than their age. Of the four people who reported being in a committed relationship, three (1.7%) reported that it was a length of two years or more, and one (0.6%) reported that it was less than two years in length. Therefore, these two variables were combined into “In a Committed Relationship.”
Attachment Network Questionnaire
The attachment hierarchy was assessed in the current study using an adapted version of the Attachment Network Questionnaire (ANQ; Trinke & Bartholomew, 1997;
See Appendix B). Questions that were used included 1) questions about whom participants would go to when distressed (safe haven), 2) whom they would count on to support them no matter what (secure base), 3) and whom it is important to see or talk to regularly (proximity). To avoid tedium, the number of lines for listing attachment figures was reduced from 15 to 12 because older adults were found to rarely list more than four or five figures for any attachment need (Doherty & Feeney, 2004; Freeman & Simons,
2018).
The ANQ is a 14-item questionnaire assessing characteristics of the attachment hierarchy. Although several scales have been developed to measure attachment hierarchies (Antonucci, 1986; Hazan & Zeifman, 1994; Trinke & Bartholomew, 1997), the ANQ was deemed to be the most appropriate measure to meet the goals of the current
115 study for several reasons. One reason is because of the ANQ’s strengths as a quantitative measure which assesses information regarding the type of relationships in the hierarchy as well as the number of people included in the attachment hierarchy. Another reason is that it has established standardized and tested reliability and validity in a number of studies, whereas several researchers who examined the attachment hierarchy used author- created measures (Cicirelli, 2010; Litwin, 2007).The next reason is that the ANQ has been used in populations of adolescents (Rowe & Carnelley, 2005), young adults
(Freeman & Simons, 2018; Pitman & Sharfe, 2010; Rowe & Carnelley, 2005; Trinke &
Bartholomew, 1997), adults (Doherty & Feeney, 2004; Trinke & Bartholomew, 1997), and older adults (Doherty & Feeney, 2004). A final reason includes the limitations of other measures in their ability to distinguish between true attachment bonds; whereas the ambiguous nature of the questions in other questionnaires left room for temporary desires such as popularity and sexual gratification to infiltrate participant responses (Rosenthal &
Kobak, 2010; Walters & Cummings, 2000).
Trinke and Bartholomew (1997) created the ANQ in a study which focused on the content and rank-ordering of attachment figures in the attachment hierarchy. Their sample included 223 (93 male, 130 female) undergraduate students between the ages of
17 and 45 years. The ANQ essentially asked participants to list up to 15 people whom they felt were important in their lives, regardless of whether the relationship was positive, negative, or mixed. The ANQ then gathered information about the characteristics of each attachment figure: including the type of relationship (i.e., friend, brother), sex, age, distance from the participant, frequency of contact, and amount of time known. Next, the
ANQ asked participants to rank the following; 1) Whom they would want to go to to help
116 them feel better when something happens or they feel upset; 2) Whom they would actually go to to help them feel better when something happens or they feel upset; 3)
Whom they would like to count on to always be there for them no matter what; 4) Whom they can actually count on to always be there for them no matter what; 5) Whom it is important for them to see or talk to regularly; 6) Whose death would have the greatest impact on them; 6) Who can make them feel upset; 7) A rank order of all the people on their list in terms of who they feel most emotional connected to, regardless of whether the connection is positive, negative, or mixed. Trinke and Bartholomew (1997) used the rankings to produce a primary attachment figure head, the second in the hierarchy, and so on.
Trinke and Bartholomew (1997) conducted multiple reliability analyses for the
ANQ: internal consistency for the attachment needs questions ranged from acceptable to excellent (α = .70 -.90). Individual items correlate adequately with the total scale
(Cronbach’s alphas ranged from 0.26 to 0.78). Trinke and Bartholomew (1997) explained that the item asking about the participant’s tendency to become upset did not correlate with the total scale. Composite mean ranks were calculated within relationships both with and without the conflictual emotion question (item G), and the two sets of scores were highly correlated (r = .93 — .99). One-month test-retest reliability was high (r = 0.60—
0.93) for the number of relationships listed and mean composite scores for the highest ranked attachment figure (the primary attachment figure) across the different attachment needs. This approach has also been used by other researchers investigating attachment hierarchies in adulthood to identify the primary attachment figures (Doherty & Feeney,
117 2004; Freeman & Simons, 2018). Freeman and Simons (2018) used this method to identify the top three attachment figures in the attachment hierarchy.
The ANQ was judged to have good face validity, and Trinke and Bartholomew
(1997) stated that the items “clearly and directly describe each theoretically derived attachment component in a single item” (p. 618). Convergent validity was moderate
(r(220) = 0.31, p < .001) between the ANQ and the Social Support Questionnaire-Short
Form (SSQ-Short Form: Sarason, Sarason, Shearin, & Pierce, 1987), which Trinke and
Bartholomew (1997) explained as being due to the two measures targeting different constructs to some degree—the perceived social support as measured by the SSQ-Short
Form was stated to be a narrower construct than the construct of attachment as measured by the ANQ. Convergent validity was high, however (r(220) = .87, p < .001) between the
ANQ and an experienced judge-rating of the attachment status based on the pattern of answers provided on the ANQ. Discriminant validity was shown in the differences between the ANQ and attachment status (r(220) = .04, NS) or attachment security (r(220
= 0.13, NS).
Following the development of the ANQ in 1997, subsequent studies demonstrated further support for high internal consistency (.80; Doherty & Feeney, 2004). Convergent validity for the ANQ was established by Rowe and Carnelley (2004), who found a significant Pearson correlation between the ANQ and a hierarchical mapping technique (r
= 0.54). Similarly, using multigroup invariance testing, Pitman and Sharfe (2010) concluded that the ANQ and hierarchical testing measures provide similar, but unique, results. In the current study, the ANQ was found to have Cronbach’s alpha of 0.74 for the total sample, 0.77 for the young-old, and 0.75 for the mid-old.
118 Satisfaction with Life Scale
Life satisfaction was assessed using the Satisfaction With Life Scale (SWLS;
Diener, Emmons, Larsen, & Griffin, 1985; See Appendix C), a 5-item questionnaire assessing one’s global judgment of life satisfaction. The SWLS measures the judgmental component of subjective well-being (Pavot & Diener, 2008), and has been noted as one of the most popular and widely used scales for the measurement of life satisfaction which stands up to the confines of culture (Oishi, 2006) and age (Diener et al., 1985; Wang,
2016). The SWLS is a short questionnaire which can be completed quickly to save time and resources as compared to many other measures of life satisfaction (Pavot, Diener,
Colvin, & Sandvik, 1991). The high convergence of self-and-peer-reported measures of subjective well-being and life satisfaction provide strong evidence that life satisfaction is a relatively global and stable phenomenon, not simply a momentary judgment based on fleeting influences (Pavot, Diener, Colvin, & Sandvik, 1991).
The SWLS was used in studies investigating the relationship between the attachment bonds and life satisfaction of adolescents (Shahrazad, Kadir, Omar, & Halim,
2015; Yildiz, 2016), young adults (Nabi & Rizvi, 2015; Temiz & Comert, 2018; Yoo &
Kim, 2015), adults (Sumer & Knight, 2001), and older adults (Diener et al., 1985; Wang,
2016). Outside of attachment theory research, the SWLS has been used in studies investigating the life satisfaction of older adults (Bai, Guo, & Fu 2018; Diener et al.,
1985; Haron, Foong, & Hamid, 2018; Karadag Arli et al., 2018; Kiarsipour et al., 2017;
Lamoureux-Lamarche & Vasiliadis, 2017; Lu, Lum, & Lou 2016). The SWLS is a five- item, 7-point Likert scale (In most ways my life is close to my ideal; The conditions of my life are excellent; I am satisfied with my life; So far I have gotten the important things I
119 want in life; If I could live my life over, I would change almost nothing). Answers range from one to seven (1 = strongly disagree, 7 = strongly agree). Researchers have previously used categories to determine the level of satisfaction with life according to the total score (the sum of responses to the five items, with scores ranging from 5 to 35).
Scores between 5 and 9 indicate an extreme dissatisfaction with life; scores between 10-
14 indicate dissatisfaction with life; scores between 15-19 indicate slightly below average satisfaction with life; scores from 20-24 indicate average satisfaction with life; scores between 25-29 indicate high satisfaction with life; and scores between 31 and 35 indicate an extreme satisfaction with life. The current study used SWLS total scores as a continuous variable in order to calculate correlational analyses.
The SWLS was developed by Diener and colleagues (1985) in three studies. In the first study undergraduates (ages unknown; N = 176) completed the SWLS in a group setting. A subset of students completed the SWLS again two months later (n = 76). The test-retest reliability correlation coefficient was 0.82, and coefficient alpha was 0.87. The inter-item correlation matrix was factor-analyzed with principal factor analysis. An inspection of a scree plot of eigenvalues resulted in a single factor accounting for 66% of the variance. Factor loadings ranged from 0.61 to 0.83, and item-total correlations ranged from 0.57 to 0.75. The second study used two different samples of undergraduates (n =
176, n = 163). Both samples were given a battery of either nine or fifteen subjective well- being measures. Correlations between the SWLS and the other measures of well-being ranged between 0.09 to 0.75. Diener and colleagues then removed the items that were more affective in nature (leaving the cognitive items) resulted in correlations with othe4r measures of well-being ranging between -.32 and .75. Study 3 assessed the psychometric
120 properties of the SWLS in a sample of community-dwelling older adults (N = 53) with an average age of 75. An interview was conducted, and the SWLS correlated .43 with the interview. The item-total correlations for the five items ranged from .61 to .81, demonstrating good internal consistency in older adulthood.
Several studies have used principal factor analyses of the SWLS which demonstrated a single-factor loading (Arrindell et al., 1991; Diener et al., 1985; Neto,
1993; Pavot et al., 1991; Pavot & Diener, 1993, 2008), for which the single factor accounted for 65-74% of the variance of the scale (Diener et al., 1985; Pavot & Diener,
2008). Test-retest reliability coefficients have ranged between 0.82 and 0.85 for up to a two-month period, with coefficients decreasing to .54 over a longer period (Diener et al.,
1985; Koeker, 1991; Pavot & Diener, 2008). Reliability analyses have shown a range of
Cronbach’s alphas between 0.78 and 0.90 (Diener et al., 1985; Kooshar & Bonab, 2011;
Lane, 2016; Pavot & Diener, 2008; Post, van Leeuwen, van Kopenhagen, & de Groot,
2012; Sharfe, 2016; Vassar, 2008). Item-total correlations ranged between 0.55 and 0.81
(Diener et al., 1985; Köker, 1991; Pavot & Diener, 2008). Concurrent validity ranged
.59-.60 between the SWLS and LSI-A (Neugarten et al., 1961) and Life Satisfaction
Questionnaire 9 (LiSat-9; Fugl-Meyer et al., 1991; Post et al., 2012). Convergent validity has been demonstrated through correlations ranging between -0.37 and 0.81 between the
SWLS and other measures of subjective well-being (Diener et al., 1985; Mrower &
McCarver, 2002; Pavot & Diener, 2008), suggesting that such scales overlap but also measure unique aspects of well-being. Evidence of discriminate validity was measured with a Marlowe Crowne analysis which resulted in a correlation of 0.02 between the
SWLS and a measure of social desirability (Diener et al., 1985). Divergent validity was
121 also reported between the SWLS and the Multicultural Experience Inventory (r = -.24;
Ramirez, 1983). In the current study, Cronbach’s alpha was 0.90 for the total sample,
0.92 for the young-old, and 0.87 for the mid-old.
The Life Satisfaction Index A
Early attempts to examine subjective psychological well-being in older adulthood took two approaches: the first considered well-being a function of one’s social participation and the relative continuity in social participation (Neugarten et al., 1961).
The second approach defined well-being in terms of subjective perceptions about one’s past and/or present life. The second approach led to a variety of scales attempting to tap into one’s internal evaluations of well-being. The development of these measures was part of Neugarten et al.’s (1961) five-year study of subjective well-being. Neugarten and colleagues contended that life satisfaction in older adulthood needed to be conceptualized differently than life satisfaction in other life stages. With the goal of identifying successful aging, and a desire to develop a measure of life satisfaction specifically for older adults, Neugarten and colleagues conducted a thematic analysis of the existing measures of adjustment and morale with the motivation of developing a measure of life satisfaction independently from various other psychological and social variables. They developed operational definitions for five components; definitions were weighed against case material and independent judgments were made, compared, and refined. The five dimensions they narrowed their analyses to included; zest vs. apathy, resolution and fortitude, congruence, self-concept, and mood tone. Zest measures the extent to which one takes pleasure from activities of daily life. Resolution and fortitude measures the degree that a person regards life as meaningful and accepts their earlier life experiences.
122 Congruence measures the congruence between desired and achieved life goals. Self- concept measures whether a person holds a positive image of the self. Mood tone measures the degree to which a person maintains happy and optimistic attitudes and mood.
The LSI-A (Neugarten et al., 1961; See Appendix D) was developed with the intention of considering an individual’s perception about his or her past, present, and future. The LSI-A consists of 20 questions (i.e., “As I grow older, things seem better than
I thought they would be”). Total scores are calculated by summing the positive responses to the questions (given a score of 1), and range between zero and twenty. Answers of unsure were coded as a negative response (given a score of 0), and higher scores indicate higher life satisfaction. I propose to use the scoring method proposed by Wood et al.
(1969) which was subsequently used by Redmond (1990): add an option of I don’t know to the responses and score it with one point. Wood and colleagues note that when interviewed, the explanations of an I don’t know response did not compare to a score that warranted a label as a “wrong answer.” Adding the option for three answers to the questions adjusts the total score range to between zero and forty. The addition of I don’t know as an option has been found to produce a significantly wider range of scores than the original, dichotomous scoring method; it has been suggested that the wider range of scores allows for a better understanding of life satisfaction (Dahlrup et al., 2015; Subasi
& Hayran, 2005).
Individuals aged 50-90 (n = 177) participated in Neugarten and colleagues’ study which created the Life Satisfaction Rating Scale (LSR); an in-depth interview rated by 14 independent judges. Inter-rater reliability was adequate (r = .78); enabling the use of the
123 Spearman-Brown coefficient raised the internal reliability to good levels (r = .87). A refinement led to the development of the LSI-A (Neugarten et al., 1961), consisting of 20 agree/disagree items measuring attitude. The scales were validated against the judgments of a clinical psychologist: correlation with the LSR was .64, which was interpreted by
Neugarten and colleagues as providing a satisfactory degree of validation. Further analyses resulted in poor convergent validity between the LSR and the LSI-A (r = .05) for younger adults (ages unknown; n = 80). With older adults aged 50-90, however, correlation coefficients approached more adequate levels of convergent validity between the psychologist’s ratings and the LSI-A (r = .55). Neugarten and colleagues speculated that the low correlation coefficient for younger adults could have been due to a low consistency in psychological behavior in young adulthood, and concluded that whatever the reason, the instrument was shown to have adequate validity in older adulthood.
The psychometric properties of the LSI-A (Neugarten et al., 1961) were not subjected to methodological analyses by subsequent research for several years after its creation. The analyses that were completed since then have mixed results (Redmond,
1990). Factor analyses have shown that life satisfaction is indeed multidimensional
(Neugarten et al., 1961; Redmond, 1990), yet despite numerous methodological analyses, no consensus has been reached about the best way to apply the LSI-A and it is still used in many forms. Cronbach’s alpha’s have ranged between .77 and .92 (Ku, Fox, & Chen,
2016; Lobello, Underhill, & Fine, 2004). In a meta-analysis, Wallace and Wheeler (2002) reported that, out of 157 studies that used the LSI-A, only 19.11% reported reliability coefficients that were actually collected in that study. The average reliability coefficient across 34 relevant and thorough studies that could be analyzed was calculated to be .79
124 (SD = .10) and the median reliability score was .79. They reported that score reliability was unrelated to a variety of sample characteristics. Reliability scores ranged from .42 to
.98, which has a range of .56. Two studies of the LSI-A have examined the capability of items to discriminate between high and low scorers (Adams, 1969; as cited in Neugarten et al., 1961). Adams and Neugarten and colleagues produced fair to good item discriminative values ranging from 16.0 to 75.4 percent, with means of 42 and 58.7 percent. Test-retest reliability has ranged from .42-.77 (Lobella, Underhill, & Fine, 2004).
Convergent validity for the LSI-A (Neugarten et al., 1961) was moderate (r337 =
.43, p < 0.001) between the LSI-A and the Family Satisfaction Scale (FSS; Olson &
Wilson, 1982; Lobello, Underhill, & Fine, 2004), suggesting that life satisfaction is moderately related to satisfaction with one’s family dynamics. Convergent validity was also found by Lohmann (1977), who tested correlations between the LSI-A and
Philadelphia Geriatric Center Morale Scale (r = .76; Lawton, 1975), a modified version of the Philadelphia Geriatric Center Morale Scale (r = .77; Morris-Sherwood, 1975), the
Cavan Adjustment Scale (r = .79; Cavan, Burgess, Havighurst, & Goldhamer, 1949), the
LSI-B (r = .63; Neugarten et al., 1961), the Dean Scale (r = .41; Cumming, Dean, &
Newell, 1958), the Kutner Morale Scale (r = .65; Kutner, Fanshel, Togo, & Langner,
1956), and the LSI-Z (r = .94; Neugarten et al., 1961). Concurrent validity was examined between the LSI-A and the CES-D; Pearson’s correlations ranged from -.55 to -.63, which indicated that life satisfaction is moderately negatively correlated with depression
(Lobello, Underhill, & Fine, 2004). Divergent validity was found between a modified version of the LSI-A and the Multicultural Experience Inventory (r = .00; Ramirez, 1983, as cited in Lohmann, 1977), and the Multicultural Perspective Index (r = .24; Mrower &
125 McCarver, 2002). In the current study, Cronbach’s alpha was 0.87 for the total sample,
0.90 for the young-old, and 0.83 for the mid-old.
Procedures
IRB approval was provided through email on 07/25/2019 (see Appendix E), and the survey was activated on the same date. A description of the study was provided for participants on MK Turk, stating, “Participants are needed for a study on social networks.
In the study, participants were asked to complete questions about demographics, their social network, and life satisfaction. This study will take 10-15 minutes to complete and participants will receive $1.00 for completing it. You may complete this study only once.”
For individuals who chose to complete the study, a screen with information about the study was provided (see Appendix F: Cover Letter) before the survey officially began. Following the study, a screen with debriefing information was provided (see
Appendix G: Debriefing Letter). Approximately five participants emailed me with questions. All questions regarded the timing of the financial incentive. Participant email addresses were kept separate from the survey results to prevent breaches of confidentiality. None of the participants were contacted again after they completed the survey and/or their concerns were addressed through email.
Hypotheses
In my first hypothesis the size of the attachment hierarchy was theorized to correlate positively with levels of life satisfaction. Hypothesis one was based on theoretical research which suggested that the size of the attachment hierarchy was postulated to be a vital part of one’s adaptation to the environment throughout the
126 lifespan (Bowlby, 1982, 1983). Attachment theory conceptualizes the attachment hierarchy as a resource for fulfilling attachment needs. Hypothesis one was in line with the convoy model (Kahn & Antonucci, 1980) which would conceptualize an increased number of people in the attachment hierarchy as an increased likelihood for the fulfillment of emotional and/or instrumental needs. Empirical evidence suggested that environmental factors [such as social support] were strong predictors of life satisfaction
(Kooshar & Bonab, 2011), and that the size of the attachment hierarchy has been correlated positively with general measures of emotional well-being (Cohen & Janicki-
Deverts, 2009; Jetten, Haslam, & Branscombe, 2009), and negatively with depression
(Gillath, Johnson, Seluk, & Teel, 2011; Iyer et al., 2009; Osborn et al., 2003). The size of the attachment hierarchy also buffered the negative effects of life transitions (Osborn et al., 2003). I expected to find that individuals with more attachment figures would report significantly greater life satisfaction than individuals with fewer attachment figures. The relationship between the size of the attachment hierarchy and life satisfaction was tested both across age and in each epoch of older adulthood through the completion of
Pearson’s correlational analyses, as well as partial correlational analyses in SPSS.
In my second hypothesis the average size of the attachment hierarchy was proposed to be significantly different between young-old and mid-old adults. More specifically, the mid-old was hypothesized to have a significantly smaller number of attachment figures than the young-old. The size of the attachment hierarchy has been postulated to be a vital part of one’s adaptation to the environment throughout the lifespan (Bowlby, 1982, 1983). Hypothesis two was in line with socioeconomic selectivity theory (SST; Carstensen, 2006) which would explain a decrease in the size of
127 the attachment hierarchy with age as a selective pruning of the attachment hierarchy in order to better control the quality of the relationship and his or her ability to regulate emotions by surrounding the self with positive others. Furthermore, disengagement theory (Cunning & Henry, 1961). would argue that older adults withdraw from social roles, which could possibly result in fewer attachment figures as one ages. Hypotheses 2 was also based on empirical research which suggested that, compared to younger adults, older adults had fewer attachment figures in the attachment hierarchy (Cicirelli, 2010;
Doherty & Feeney, 2004). Similar studies suggested a negative correlation between the continuous variable of age and the number of attachment figures in the attachment hierarchy (Cornwell, Laumann & Schumm, 2008; Smith et al., 2015). Between-group differences in the size of the attachment hierarchy were tested with an independent samples t-test. Correlations between age, subjective age, and the size of the attachment hierarchy were assessed through correlational analyses in SPSS.
In my third hypothesis the size of the attachment hierarchy was theorized to be significantly different depending upon the primary attachment figure identified. The primary attachment figure was categorized into one of four categories (family, romantic partner, peer, or “other”), and identified based on the calculation of mean composite scores. Hypothesis 3 was based on Bowlby’s (1969, 1982) assertion that the types of individuals included in the attachment hierarchy would demonstrate predictable developmental trends across the lifespan. Theoretically, attachment theory would explain that different types of primary attachment figures would have different abilities to meet an older adult’s attachment needs, which could impact an older adult’s need for more or less subsequent relationships to fulfill attachment needs. The convoy model (Kahn &
128 Antonucci, 1980) would describe different individuals’ choices of primary attachment figures in similar terms, explaining that the primary attachment figure would be chosen due their ability to meet an older adult’s emotional and instrumental needs. Empirical research suggested that individuals who listed their children (Feeney et al., 2001) or family (Litwin & Shiovitz-Ezra, 2010) as primary attachment figures listed fewer overall attachment figures in the attachment hierarchy. Litwin and Shiowitz-Ezra (2010) reported that older adults with friend hierarchies had significantly larger attachment hierarchies.
According to Feeney and colleagues (2001) friendships and other relationship types are likely to suffer as adults enter committed relationships and juggle the demands of family and work. Carr and Boerner (2013) suggested that older adults who begin dating risk conflict with family members (especially children). Therefore, I expected to find that individuals with a primary attachment figure that was family or a romantic partner would have significantly fewer attachment figures in their attachment hierarchies, and individuals with a primary attachment figure whom is a friend would have significantly more attachment figures than individuals who listed a primary attachment figure of
“other.” Differences in group means were tested with a one-way, one-tailed ANOVA, followed by a one-way, one-tailed ANCOVA, controlling for group differences in the young-old and mid-old for marital status and employment.
In my fourth hypothesis levels of life satisfaction were hypothesized to be significantly different based on the primary attachment figure identified. The primary attachment figure was again categorized into one of four categories (family, romantic partner, peer, or other), and identified through the calculation of mean composite scores.
Hypothesis four was based on Bowlby’s (1969, 1982) assertion that the types of
129 individuals included in the attachment hierarchy would theoretically demonstrate predictable developmental trends across the lifespan. Theoretically, attachment theory would explain the differences in the relationships between the types of primary attachment figures and life satisfaction as due to each figure’s ability to meet the attachment needs. Late-life attachment would be predicted by indices of intra-individual and inter-individual functioning. The convoy model (Kahn & Antonucci, 1980), on the other hand, would explain that each figure would have a different ability to meet the emotional or instrumental needs of the older adult. Empirical evidence suggested that the types of people comprising the attachment hierarchy appeared to have an impact on affective aspects of well-being (Litwin & Shiovitz-Ezra, 2010; Yildiz, 2016), especially for the relationships between an older adult and his or her children and grandchildren
(Bai, Guo, & Fu, 2018; Lu, Lum, & Lou, 2016). The presence of peers in the attachment hierarchy correlated positively with emotional well-being (Litwin, 2007; Litwin &
Shiovitz-Ezra, 2010). Litwin and Shiovitz-Ezra (2010) observed that 25% of older adults had attachment hierarchies consisting of mostly peers, and 16% had mostly family. I expected that the influence of the primary attachment figure on life satisfaction would replicate this trend, with individuals who had family and peer primary attachment figures reporting higher life satisfaction, and individuals who listed “other” primary attachment figures reporting lower life satisfaction. Differences in group means were tested in a one- way, one-tailed MANOVA, followed by a one-way, one-tailed MANCOVA.
My fifth hypothesis anticipated differences in the expected and observed frequencies of each primary attachment figure in the young-old versus mid-old. Primary attachment figures were again identified through mean composite scores and categorized
130 into one of four types (family, romantic partner, peer, or other). The types of attachment figures in the attachment hierarchy theoretically changes across the lifespan (Bowlby,
1969, 1982). Attachment theory would suggest that differences in the environment and in an individual’s needs would require the attachment hierarchy to adapt. How quickly such changes occur throughout the years of older adulthood has not yet been studied. The convoy model (Kahn & Antonucci, 1980) would suggest that adaptations in the attachment hierarchy would reflect an individual’s attempt to manage the hierarchy to improve its ability to meet functional needs. Additionally, empirical research suggested that there may be a possible shift from family toward friends and intangible attachment figures in older adulthood (Cicirelli, 2010; Pitman & Sharfe, 2010). On the other hand, it has been suggested that an orientation toward family may increase across older adulthood
(Doherty & Feeney, 2004; Freeman & Brown, 2001; Neugarten, 1974; Smith et al.,
2015). Freeman and Simons (2018) stated that the preference for attachment figures would depend upon the individual’s circumstances: when one cannot afford to choose a preferred attachment due to necessities of care-taking, the preferred attachment may become the attachment figure which is present. Because health is more likely to decline with increasing age, I hypothesized that significantly larger numbers of the mid-old, as compared to the young-old, would report primary attachment figures who were “other.”
The frequency patterns were tested through a Pearson’s Chi-Square analysis.
131
CHAPTER IV
RESULTS
This chapter begins with a summary of the data cleaning methods which were used in the present study. Next is a review of the statistical tests that were completed prior to beginning testing for the hypotheses, followed by a section outlining the descriptive statistics of the data used for the present study. Following the descriptive statistics is a section providing detailed information about the main statistical analyses used for testing hypotheses one through five, followed by a summary of the results.
Data Cleaning
Once data collection was complete for both age groups (n = 209), the data were entered into excel, transferred to SPSS, and visually scanned for outliers, entry errors, and missing data. Entry errors were fixed by comparing the values with the original data.
Missing data were also found through frequency analyses. Two missing data responses were found: two participants failed to report their birth sex. Because the difference between birth and current sex was not a key factor in the current study, and because all other participants reported the same birth sex as their current sex, current sex was used in data analyses rather than birth sex.
132 Exclusion criteria resulted in the removal of one participant (0.48%) due to answers that did not make sense. Specifically, all 12 attachment slots were filled in with names, but the descriptions of the relationship type were all “none.” Two participants
(0.96%) were excluded due to mismatching attention check questions. Three participants
(1.44%) were excluded due to age (i.e., above 84 years), and 26 participants (12.44 %) were excluded due to not “finishing” the survey as per MK Turk procedures. Unfinished surveys had 25 or more incomplete responses. The final dataset consisted of surveys completed by 177 participants.
Next, SPSS was used to clean the data through the use of labeling and formatting, ensuring appropriate variable types, and assigning measurement categories. Data distribution was checked through Shapiro-Wilk’s tests and visual scans of data plots.
Visual analyses of the Normal Quantile-Quantile Plots indicated approximately normal distribution. Therefore, analyses of variance were used for hypothesis testing. Shapiro-
Wilks tests for the total sample indicated non-normal distributions for SWLS total score
(M = 21.64, SD = 7.06), LSI-A total score (M = 24.15, SD = 9.55), and average attachment hierarchy size (M = 2.66, SD = 1.56).
Tests for univariate outliers included box plots and Tukey’s hinges. Values that were outside of three interquartile ranges from the lower and upper quartiles were considered outliers (Hoaglin & Iglewicz, 1987), and corrected with pairwise deletion
(Peugh & Enders, 2004). No outliers were found for the variables of SWLS or LSI-A total scores. One outlier was found for the number of attachment figures reported on the third question on the ANQ. Two outliers each were found for 1) the number of attachment figures reported on first question on the ANQ, 2) the number of attachment
133 figures reported on the second question on the ANQ, and 3) the average number of attachment figures reported across all three questions on the ANQ (ANQ AVE).
Univariate outliers were corrected for with pairwise deletion. Tests for multivariate outliers were completed with Mahalanobis Distance in SPSS. Six participants were shown to have combinations of unusual scores. Comparisons of statistical test results with and without the inclusion of the six participants showed that their inclusion yielded significant results, and their exclusion led to non-significant results. Therefore, the six cases were excluded from final analyses, and the total sample size for statistical tests was
171.
Data Preparation for Hypotheses
Chi-square analyses were completed in SPSS to examine group differences in the demographic variables between the young-old and mid-old. Tests for group differences between categorical demographic variables (i.e., sex, race/ethnicity, marital status, education, health, employment, financial status, and living arrangements) were completed in SPSS. Marital status and financial status were adjusted to remove cells with fewer than five participants in order to meet the assumptions of the test. In regards to marital status,
“in a committed relationship” and “separated” were removed. In regards to financial status, “very poor” and “very rich” were removed. Significant results were found for group differences in both marital status and employment (see Tables 4.1 and 4.2). Both marital status and employment could potentially impact the attachment hierarchy through access to different social relationships. Because of the significant group differences, marital status and employment were controlled for in subsequent analyses. Results were
134 Table 4.1. Chi Square Analyses with Marital Status in the Young-Old and Mid-Old Groups Young- Mid-Old Total Variable Old (n = 84) Sample Df X2 P (n = 81) (N = 165) Marital Status 3 10.92 .012* Married Observed 44 39 83 Expected 10.7 42.3 83 Divorced Observed 18 10 28 Expected 13.7 14.3 28 Widowed Observed 11 29 40 Expected 19.6 20.4 40 Not in a Committed Relationship Observed 8 6 14 Expected 6.9 7.1 14 The minimum expected count was 6.87 *p < .05
Table 4.2. Chi Square Analyses with Employment in the Young-Old, Mid-Old, and Total Sample Total X2 Young- Mid-Old Sample Df P Variable Old (n = 85) (N = 171) (n = 86) Employment (N = 171) 1 13.28 < .001** No Observed 60 78 138 Expected 69.4 68.6 138 Yes Observed 26 7 33 Expected 16.6 16.4 33 The minimum expected count was 16.40 **p < .001
135 non-significant for sex (X² (1, N = 171) = 3.11, p = .078), race/ethnicity (X² (5, N = 171)
= 3.12, p = .682), education (X² (2, N = 170) = 1.77, p = .413), health (X² (2, N = 171) =
2.00, p = .369), financial status (X² (3, N = 170) = 5.56, p = .135), and living arrangements (X² (4, N = 171) = 5.89, p = .207).
Descriptive Statistics: The Attachment Hierarchy and Life Satisfaction
Table 4.3 summarizes correlational analyses in the total sample between three of the main variables in the current study (i.e., age, attachment hierarchy size, and life satisfaction). Correlational analyses for these variables in each epoch were completed for hypothesis one, and will be discussed later in this chapter.
The size of the attachment hierarchy was measured by averaging the number of attachment figures reported for the three attachment needs (ANQ AVE; see Table 4.4). In the total sample, ANQ AVE was non-normally distributed with a moderate skewness of
0.67 (SE = 0.19) and slight platykurtic distribution with a kurtosis of 0.33 (SE = 0.37).
For the young-old, ANQ AVE was non-normally distributed with a moderate skewness of 0.55 (SE = 0.26) and a kurtosis of 0.46 (SE = 0.52). In the mid-old, ANQ AVE was non-normally distributed with a moderate skewness of 0.74 (SE = 0.26) and a kurtosis of
0.15 (SE = 0.52).
The hypotheses of the current study categorized the types of attachment figures into four types: family, friends, romantic partners, and “other.” In the total sample, consideration of the first attachment figure listed (Table 4.5) showed that, across all three questions on the ANQ, the majority of participants listed a friend, followed by family, romantic partners, and “other.” The same pattern was found in the young-old. In the mid- old, however, reliance on family was found to either tie that of friends, or surpass it.
136 Table 4.3. Partial Correlations between Age, Attachment Hierarchy Size, and Life Satisfaction for the Total Sample Variable Age Subjective Age ANQ AVE SWLS Total Score Subjective .27** - - - Age ANQ AVE .15* -.12 - -
SWLS .21* -.25** .13 - Total Score LSI-A Total .26** -.24* .20* .76** Score ANQ AVE: Average number of attachment figures reported across all 3 ANQ questions (N = 170) Control variables: marital status and employment * p ≤ .05 **p ≤ .001
Table 4.4. Average Attachment Hierarchy Sizes in the Young-Old, Mid-Old, and Total Sample Attachment Hierarchy Sizes ANQ AVE Young-Old M (n = 86) 2.36 SD 1.23 Range 0-6 Mid-Old M (n = 85) 2.66 SD 1.33 Range 1-6 Total Sample M (N = 171) 2.51 SD 1.29 Range 0-6
ANQ AVE: Average number of attachment figures reported across all 3 ANQ questions (N = 170)
These same patterns were found when considering the primary attachment figure as calculated through mean composite scores (Table 4.6). In the section about hypothesis
137 Table 4.5. Attachment Figure Distribution for the 1st Attachment Figure Listed on Each ANQ Question Attachment Figure Friend % Family % Romantic % Other % None % Type Partner Young- Old (n = 86)
ANQ1 39 45.3% 23 26.7% 17 19.8% 3 3.5% 4 4.7%
ANQ2 39 45.3% 24 27.9% 10 11.6% 7 8.1% 6 7.0%
ANQ3 36 41.9% 28 32.6% 14 16.3% 4 4.7% 4 4.7% Mid-Old (n = 85)
ANQ1 32 37.6% 33 38.8% 18 21.2% 2 2.4% 0 0%
ANQ2 32 37.6% 42 49.4% 6 7.1% 2 2.4% 3 3.5%
ANQ3 31 36.5% 31 36.5% 17 20.0% 3 3.5% 3 3.5% Total Sample (N = 171)
ANQ1 71 41.5% 56 32.7% 35 20.5% 5 2.9% 4 2.3%
ANQ2 71 41.5% 66 38.6% 16 9.4% 9 5.3% 9 5.3%
ANQ3 67 39.2% 59 34.5% 31 18.1% 7 4.1% 7 4.1%
ANQ1: Question 1 on the ANQ ANQ2: Question 2 on the ANQ ANQ3: Question 3 on the ANQ
five that can be found later in this chapter, testing results are provided that were used to determine if these differences were statistically significant.
For the purposes of hypothesis five, the identification of the primary attachment figure was accomplished by calculation of mean composite scores. In line with previous research (Doherty & Feeney, 2004; Rowe & Carnelley, 2005; Trinke & Bartholomew,
1997), attachment figures were ranked with consideration given to the rank order they were placed in across the first, second, and third questions on the ANQ (measuring the
138 Table 4.6. Primary Attachment Figure Distributions Assessed Through Mean Composite Scores Romantic PAF Type Partner % Family % Friend % Other %
Young-Old 45 52.3% 25 29.1% 12 14.0% 4 4.7% (n = 86)
Mid-Old 32 37.6% 36 42.4% 13 15.3% 4 4.7% (n = 85)
Total Sample 77 45.0% 61 35.7% 25 14.6% 8 4.7% (n = 171)
respective attachment needs of safety, security, and proximity). Specifically, calculations were computed according to the methodology outlined in Doherty and Feeney (2004) in that a score of three was given to the first attachment figure listed, a score of two was given to the second attachment figure listed, and a score of one was given to the third attachment figure listed. Scores for each attachment figure could therefore range from one to nine, and the attachment figure with the highest mean composite score was determined to be the primary attachment figure. This method took into account the number of attachment needs that an attachment figure was listed for as well as the rank order in which he or she was listed.
In the total sample Cronbach’s alpha for the ANQ was 0.74. Item-total correlations ranged between -0.002 - 0.760 (M = 0.25). Item-total correlations would not have improved with the removal of any items. Cronbach’s alpha would have improved to
0.75 with the removal of the third option for the first question on the ANQ. In the young- old, Cronbach’s alpha for the ANQ was 0.77. Item-total correlations ranged from 0.001 –
0.81 (M = 0.29). Item-total correlations would not have increased with the removal of any items. Cronbach’s alpha would have increased to 0.80 with the removal of the first option
139 on the third question on the ANQ. In the mid-old, Cronbach’s alpha for the ANQ was
0.75. Item-total correlations ranged from 0.04 – 0.82 (M = 0.25). Item-total correlations would not have increased with the removal of any items. Cronbach’s alpha would have increased to 0.77 with the removal of the third option on the first question on the ANQ,
0.76 with the removal of the second option on the second question on the ANQ, and 0.76 with the removal of the third option on the third question on the ANQ.
In regards to the questionnaires measuring life satisfaction, a summary of information about scores and Cronbach’s alpha levels is provided in Table 4.7. On the
SWLS, in the total sample, inter-item correlations ranged from 0.53-0.81 (M = 0.65).
Inter-item correlations on the SWLS would increase to 0.84 with the removal of item one.
Cronbach’s alpha would not have increased with the removal of any items. In the young- old, inter-item correlations ranged from 0.60 – 0.83 (M = .71). Inter-item correlations would have increased to 0.86 with the removal of item one, and 0.87 with the removal of item three. Cronbach’s alpha would not have increased significantly with the deletion of any items. In the mid-old, inter-item correlations ranged from 0.45 - 0.78 (M = 0.58) for the SWLS. Inter-item correlations on the SWLS would increase to 0.83 with the removal of item one. Cronbach’s alpha would have increased to 0.88 with the removal of item four.
On the LSI-A, in the total sample, inter-item correlations ranged from 0.01-0.59
(M = 0.23). The inter-item correlation on the LSI-A would have increased to 0.61 with the removal of items one or twelve, 0.62 with the removal of item nine, and 0.63 with the removal of item four. Cronbach’s alpha for the LSI-A would have increased to 0.88 with the removal or item one. In the young-old, inter-item correlations ranged from 0.02 - 0.86
140 Table 4.7. Life Satisfaction Measure Scores
SWLS LSI-A Young-Old Mean (n = 86) 21.26 22.91 Standard 7.65 10.32 Deviation Range 5-33 2-40 Alpha .92 .90 Mid-Old Mean (n = 85) 21.69 25.42 Standard 6.25 8.39 Deviation Range 7-33 0-40 Alpha .87 .83 Total Sample Mean (N = 171) 21.47 24.16 Standard 6.97 9.47 Deviation Range 5-33 0-40 Alpha .90 .87
(M = 0.30). Inter-item correlations and Cronbach’s alpha would not have increased with the removal of any items. In the mid-old, inter-item correlations ranged from 0.001 - 0.57
(M = 0.20). The inter-item correlation on the LSI-A would have increased to 0.59 with the removal of items one or four, and 0.65 with the removal of item 12. Cronbach’s alpha for the LSI-A would have increased to 0.84 with the removal or items 11 or 16.
Main Statistical Analyses
Hypothesis 1
My first hypothesis was that there would be a positive correlation between the size of the attachment hierarchy and levels of life satisfaction reported. Hypothesis one was analyzed in SPSS with Pearson’s Correlational Analyses and partial correlational
141 analyses. Analyses were completed for the total sample as well as for the young-old and mid-old. Size was analyzed through the average number of attachment figures across the three questions on the ANQ. Partial correlational analyses controlled for the variables of marital status and employment.
As shown in Tables 4.8, 4.9, and 4.10, results suggest that the number of attachment figures in the attachment hierarchy is influential on one of the two measures of life satisfaction used (see Table 4.8). Relationship strengths were weak. Table 4.8 shows the results of the initial correlational analyses and the partial correlational analyses in the total sample. Prior to controlling for marital status and employment, a weak, positive correlation was significant between age and LSI-A total score, but not for SWLS total score. Age did not significantly relate to SWLS total score. In partial correlational analyses, results showed weak positive correlations between age and SWLS and LSI-A total scores. Subjective age also had a weak negative correlation with both SWLS and
LSI-A total scores, both before and after controlling for marital status and employment.
Results before and after controlling for marital status and employment were similar in that weak, but significant, positive correlations were found between attachment hierarchy size and LSI-A total score. The similar results suggest that the strength and significance of the relationships between attachment hierarchy size and life satisfaction may not have been significantly impacted by the control variables.
To further test hypothesis one, correlational analyses (see Table 4.9) and partial correlational analyses (see Table 4.10) were completed in the two epochs of older adulthood. The size of the attachment hierarchy related significantly and positively to
LSI-A total scores in the young-old in both correlational and partial correlational
142 Table 4.8. Tests of Hypothesis 1: Correlations and Partial Correlations between Age, Attachment Hierarchy Size and, Life Satisfaction for the Total Sample ANQ AVE Variable Age Subjective Age (N = 170 ) Correlations
SWLS Total Score .11 -.27** .13
LSI-A Total Score .18* -.25** .20*
Partial Correlations SWLS Total Score .21* -.25** .13
LSI-A Total Score .26** -.24* .20*
Partial Correlation Control variables: Marital Status, Employment, and the Difference Between Age and Subjective Age * p ≤ .05 **p ≤ .001
Table 4.9. Tests of Hypothesis 1: Correlations between Age, Attachment Hierarchy Size, and Life Satisfaction for the Young-Old and Mid-Old Subjective Age ANQ AVE Variable Age (n = 85) Young-Old
SWLS Total Score .27* -.40** .19
LSI-A Total Score .23* -.38** .26*
Mid-Old
SWLS Total Score .06 -.14 .06
LSI-A Total Score .01 -.20 .10
* p ≤ .05 **p ≤ .001
143 Table 4.10. Tests of Hypothesis 1: Partial Correlations between Age, Attachment Hierarchy Size, and Life Satisfaction in the Young-Old and Mid-Old Variable Age Subjective Age ANQ AVE Young-Old
SWLS Total Score .31* -.38* .19
LSI-A Total Score .27* -.36* .27*
Mid-Old
SWLS Total Score .09 -.17 .05
LSI-A Total Score .03 -.23* .10
Control variables: Marital Status, Employment, and the Difference Between Age and Subjective Age. * p ≤ .05
analyses. The relationship was weak. The relationship between the attachment hierarchy size and SWLS scores was not significant in the correlational analyses or partial correlational analyses for the young-old. In the mid-old, the attachment hierarchy size did not relate to either measure of life satisfaction in the correlational analyses or partial correlational analyses.
The size of the attachment hierarchy related significantly and positively to LSI-A total scores in the young-old in both correlational and partial correlational analyses. The relationship was weak. The relationship between the attachment hierarchy size and
SWLS scores was not significant in the correlational analyses or partial correlational analyses for the young-old. In the mid-old, the attachment hierarchy size did not relate to either measure of life satisfaction in the correlational analyses or partial correlational analyses.
144 Overall, the results of the correlational analyses and partial correlational analyses completed between the size of the attachment hierarchy and life satisfaction indicated partial support for my first hypotheses. Differences between the young-old and mid-old was found, as well as evidence that the SWLS and LSI-A may capture similar, yet unique, aspects of life satisfaction. Further discussion of these results are provided in chapter five.
Hypothesis 2
My second hypothesis was that the young-old would have significantly more attachment figures than the mid-old. More specifically, the number of attachment figures listed in the attachment hierarchy was hypothesized to be significantly less in the mid-old group as compared to the young-old group. Hypothesis two was tested with an independent t-test in SPSS.
First, the data were tested for homogeneity of variance. Levene’s statistics were non-significant (F(1, 168) = 0.93, p = .337). Results of the one-sample independent t-test
(see Table 4.11) showed no significant relationships. These results suggest that there is no difference in the average size of the attachment hierarchy between the young-old and the mid-old.
Notably, before the six multivariate outliers were removed, a significant difference was found (t(172) = 1.99, p = .048) in the attachment hierarchy sizes of the young-old (M = 2.35) and mid-old (M = 2.75). The non-significance of these results after the removal of the outliers suggests that the relationships found before their removal were due to the unusual response combinations of six participants rather than a true
145 Table 4.11. Tests of Hypothesis 2: Independent T-test for Attachment Hierarchy Size between the Young-Old and Mid-Old Groups p-value M SD T Df (2-tailed) ANQ AVE -1.53 168 .127 Young-Old (n = 85) 2.36 1.23 Mid-Old (n = 85) 2.66 1.33
developmental phenomenon in the size of the attachment hierarchy between the young- old and the mid-old.
Hypothesis 3
My third hypothesis was that the type of primary attachment figure reported (as categorized into four types including family, romantic partners, friends, and “other”) would have a significant impact on the number of people included in the attachment hierarchy. Specifically, I hypothesized that individuals with family and/or romantic partners as primary attachment figures would have fewer attachment figures in the attachment hierarchy, and individuals with friends as primary attachment figures would have significantly more attachment figures in the attachment hierarchy than individuals who listed “other” primary attachment figure types. The primary attachment figure was identified using mean composite scores. The size of the attachment hierarchy was calculated by averaging the number of attachment figures listed across the three questions on the ANQ. Table 4.12 provides information about the average attachment hierarchy sizes based on the type of primary attachment figure reported in the total sample, young- old, and mid-old. To test hypothesis three, ANOVA’s and ANCOVA’s were completed in SPSS.
146 Table 4.12. Average Size of the Attachment Hierarchy based on Primary Attachment Figure Type (N = 170) Romantic Variable Family S.D. Partner S.D Friend S.D. “Other” S.D. Young- 2.60 1.67 2.33 1.34 2.33 0.79 1.33 1.12 Old (n = 85) Mid-Old 2.48 1.04 3.03 1.56 2.28 1.33 2.58 1.62 Total 2.53 1.08 2.62 1.47 2.31 1.09 1.96 1.45 Sample (n = 85)
To begin, an ANOVA was conducted in the total sample to examine the relationships between the type of primary attachment figure and the number of attachment figures in the attachment hierarchy. Levene’s homogeneity of variance test was non-significant (see Table 4.13), showing equal variances for primary attachment figure type. ANOVA results were interpreted with consideration for a Bonferroni- adjusted significance level (p = .013), which compensated for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses.
Results were not significant (see Table 4.14). Notably, partial eta-squared showed small effect sizes (η² = .02; Richardson, 2011). These results suggest that the type of primary attachment figure may not have an impact on the size of the attachment hierarchy.
Next, an ANOVA was completed after separating the data into groups of young- old and mid-old (see Table 4.13). In the young-old, Levene’s statistics were non- significant (see Table 4.13), showing equal variance in primary attachment figure type.
Partial eta-squared showed small effect sizes (η² = .05; Richardson, 2011). In the mid- old, Levene’s statistics were non-significant (see Table 4.13), showing equal variance in
147 Table 4.13. Tests of Hypothesis 3: Levene’s Statistics Tests for Homogeneity of Variance
Variable Df1 Df2 F p-value Levene’s Statistics for ANOVA’s Young-Old 3 81 0.79 .501 Mid-Old 3 81 1.87 .141 Total Sample 3 166 1.99 .117 Levene’s Statistics for ANCOVA Young-Old 3 81 0.79 .501 Mid-Old 3 81 1.87 .141 Total Sample 3 166 2.04 .110
Table 4.14. Tests of Hypothesis 3: ANOVA’s for Primary Attachment Figure Type and Size in the Young-Old and Mid-Old Groups Sum of Source Squares Df F η² p-value Young-Old 5.72 3, 81 1.27 .05 .291 Mid-Old 7.44 3, 81 1.41 .05 .245 Total Sample 3, 166 0.88 .455
primary attachment figure type. To compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses, a
Bonferroni-adjusted significance level (p =.013) was used, leading to non-significant
ANOVA results (see Table 4.14) for the young-old and mid-old. Partial eta-squared showed small effect sizes (η² = .05; Richardson, 2011). The results suggest that the primary attachment figure type may not significantly impact the size of the attachment hierarchy in the young-old or mid-old.
148 Table 4.15. Tests of Hypothesis 3: ANCOVA’s between Primary Attachment Figure Type and Attachment Hierarchy Size in the Young-Old, Mid-Old, and Total Sample Source Sum of Squares Df F η² p-value Young-Old 5.48 3, 84 1.21 .04 .313 Mid-Old 7.21 3, 84 1.34 .05 .269 Total Sample 4.29 3, 169 0.85 .02 .469 Control variables: Marital Status and Employment
The next step consisted of ANCOVA’s computed for the total sample with the control variables of marital status and employment. Table 4.15 shows a summary of the results of the ANCOVA. Non-significant Levene’s statistics results showed that the variances for primary attachment figure type were equal (see Table 4.13). To compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses, a Bonferroni-adjusted significance level was used (p =.013). The ANCOVA results for the total sample showed non-significance (see
Table 4.15). Partial eta-squared showed small effect sizes (η² = .02; Richardson, 2011).
Results of the ANCOVA for the total sample suggest that the type of primary attachment figure chosen does not likely have an impact on the size of the attachment hierarchy.
Table 4.14 also shows the results of ANCOVA’s that were completed after separating the data into groups for the young-old and mid-old. Levene’s statistics were non-significant in the young-old (see Table 4.13), showing equal variance in primary attachment figure type. For the mid-old, Levene’s statistics were non-significant, showing equal variance in primary attachment figure type (see Table 4.13). ANCOVA results for the total sample were non-significant after calculating a Bonferroni-adjusted significance level (p =.013; see Table 4.15). The Bonferroni-adjusted significance level
149 was used to compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses. Partial eta-squared showed small effect sizes (η² = .04; Richardson, 2011). ANCOVA results for the mid-old were also non-significant after calculating a Bonferroni-adjusted significance level (p =.013; see
Table 4.15). Partial eta-squared in the mid-old showed small effect sizes (η² = .05;
Richardson, 2011). Results of the ANCOVA’s completed after separating the data into the young-old and mid-old suggest that the type of primary attachment figure chosen does not likely have an impact on the size of the attachment hierarchy in the young-old or mid-old.
In summary, ANOVA and ANCOVA results showed non-significance for group differences in the size of the attachment hierarchy based on the type of the primary attachment figure. Effect sizes as measured by partial eta-squared in SPSS were notably small for all relationships (Richardson, 2011). Results suggested that the type of primary attachment figure chosen may not have an impact on the size of the attachment hierarchy in the total sample, the young-old, or the mid-old.
Hypothesis 4
My fourth hypothesis investigated the impact of the primary attachment figure on levels of life satisfaction. Specifically, I expected to find that individuals who had friends or family as primary attachment figures would report higher levels of life satisfaction than individuals who choose romantic partners or “other.” The primary attachment figure was identified through the calculation of mean composite scores. Life satisfaction was measured through SWLS and LSI-A total scores. To test hypothesis four, MANOVA and
MANCOVA analyses were conducted in SPSS.
150 Before running the MANOVA, histograms were plotted for each of the four types of primary attachment figures on the dependent variables of SWLS total score and LSI-A total score for the total sample. Visual analyses of all histograms showed distributions that were within the normal range. Next, correlation testing established a moderate correlation between the scores on the SWLS and the scores on the LSI-A (see Table 4.3).
Box’s Test of Equality of Covariance Matrices were non-significant (F(9, 4405.15) = .66, p = .746). A Bonferroni-adjusted significance level was used to compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses (p =.013). Wilk’s Lambda was non-significant (see Table
4.16). Effect sizes were notably small (η² = .01; Richardson, 2011). Results of the initial
MANOVA suggest that the type of primary attachment figure may not have a significant impact on life satisfaction.
To determine the impact of the type of primary attachment figure on life satisfaction in the young-old and mid-old, MANOVA’s were completed after separating the data into the two epochs. Histograms were plotted in each epoch for each of the four types of primary attachment figures on the dependent variables of SWLS total score and
LSI-A total score. Visual analyses of all histograms showed distributions that were within the normal range. Next, the SWLS and LSI-A total scores were established to have moderate correlation in the young-old (r(86) = .85, p ≤ .001 ) and the mid-old (r(85) =
.69, p ≤ .001). For the young-old, Box’s Test of Equality of Covariance Matrices were non-significant (F(9, 794.82) = 0.32, p = .968). A Bonferroni-adjusted significance level was used to compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses (p =.013). Wilk’s Lambda was
151 Table 4.16. Tests of Hypothesis 4: MANOVA’s between Primary Attachment Figure Type and Life Satisfaction in the Young-Old, Mid-Old, and Total Sample, Source Df F η² p-value Wilk’s Lambda 6, 81 0.49 .02 .819 (YO) Wilk’s Lambda 6, 80 0.74 .03 .617 (MO) Wilk’s Lambda (TS) 6, 166 0.70 .01 .704 YO = Young-Old. MO = Mid-Old. TS = Total Sample.
non-significant (see Table 4.16). Effect sizes were small (η² = .02; Richardson, 2011).
For the mid-old, Box’s Test of Equality of Covariance Matrices were non-significant
(F(9, 781.60) = 0.69, p = .721). A Bonferroni-adjusted significance level was used to compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses (p =.013). Wilk’s Lambda was non-significant
(see Table 4.16). Effect sizes were small (η² = .03; Richardson, 2011). Results of the
MANOVA when participants were separated into the young-old and mid-old also suggest that the primary attachment figure type does not likely have a significant impact on levels of life satisfaction.
To further test hypothesis four, a MANCOVA was completed in SPSS with the total sample to determine the impact of the type of primary attachment figure on life satisfaction while controlling for variables of marital status and employment. In the total sample, Box’s Test of Equality of Covariance Matrices were non-significant (F(9,
4405.15) = 0.66, p = .746). A Bonferroni-adjusted significance level was used to compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses (p =.013). MANCOVA results for Wilk’s
152 Lambda were non-significant (see Table 4.17). Effect sizes were small (η² = .01;
Richardson, 2011). Results for the MANCOVA completed for the total sample suggest that the primary attachment figure does not appear to have a significant impact on levels of life satisfaction.
After splitting the data into groups according to epoch, the young-old showed a non-significant Box’s Test of Equality of Covariance Matrices (F(9, 794.82) = 0.32, p =
.968). A Bonferroni-adjusted significance level was used to compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses (p =.013). Wilk’s Lambda was non-significant for the young-old (see
Table 4.17). Effect sizes were small (η² = .02; Richardson, 2011). For the mid-old, Box’s
Test of Equality of Covariance Matrices were non-significant (F(9, 781.60) = 0.69, p =
.721). A Bonferroni-adjusted significance level was used to compensate for the increased likelihood of rejecting the null hypothesis that occurred due to completing multiple statistical analyses (p =.013). Wilk’s Lambda was non-significant (see Table 4.17). Effect sizes were small (η² = .03; Richardson, 2011). Results for the MANCOVA’s completed for the young-old and mid-old suggest that the primary attachment figure type may not have a significant impact on levels of life satisfaction.
In summary, all statistical analyses for hypothesis four were non-significant, suggesting that the type of primary attachment figure does not seem to influence life satisfaction in the total sample, young-old, or mid-old. All effect sizes found in the
MANOVA and MANCOVA statistical analyses for this hypothesis were notably small
(Richardson, 2011).
153 Table 4.17. Tests of Hypothesis 4: MANCOVA’s between Primary Attachment Figure Type and Life Satisfaction in the Young-Old, Mid-Old, and Total Sample Source Df F η² p-value Wilk’s Lambda 6, 158 0.43 .02 .856 (YO) Wilk’s Lambda 6, 156 0.88 .03 .511 (MO) Wilk’s Lambda 6, 328 0.79 .01 .582 (TS) Control variables: Marital Status, Employment, and the Difference between Age and Subjective Age. YO = Young-Old. MO = Mid-Old. TS = Total Sample.
Hypothesis 5
My fifth hypothesis was that each age group would have a significantly different proportion of people who reported each of the four types of primary attachment figures.
Specifically, I expected to find that the mid-old would report larger numbers of “other” primary attachment figure types than the young-old. Hypothesis five was tested with a chi-square analysis in SPSS.
An initial chi-square test on the distributions of the four types of primary attachment figures in the young-old and mid-old were not found to be significant (X2 (3,
N = 171) = 4.21, p = .239). However, 25% of cells had an expected count of less than five, violating an assumption of the chi-square test. Therefore, the category of “other” primary attachment figure (n = 4) was removed, and a second chi-square analysis was completed. The results of the second chi-square test were non-significant (see Table
4.18). In conclusion, hypothesis five was not supported. The proportions of people who listed each of the four primary attachment figure types were not significantly different in the young-old than in the mid-old cohorts.
154 Table 4.18. Tests of Hypothesis 5: Final Chi-Square Analysis Testing Primary Attachment Figure Distributions between the Young-Old and Mid-Old Groups Attachment Young- Mid-Old Df X2 P Figure Old Type Romantic Observed 45 32 2 4.21 .122 Partner Expected 38.7 38.3 Family Observed 25 36 Expected 30.7 30.3 Friend Observed 12 13 Expected 12.6 12.4 Zero cells had an expected count less than 5. Minimum expected count was 12.42
Summary of Results
In summary, results of hypothesis one provided partial support for a relationship between the size of the attachment hierarchy and levels of life satisfaction. Specifically, after partialling out effects of marital status and employment, the size of the attachment hierarchy was found to correlate positively with LSI-A total scores in the total sample and the young-old. The size of the attachment hierarchy did not appear to significantly impact total scores on the SWLS. In the mid-old, the size of the attachment hierarchy did not appear to have a significant impact on levels of life satisfaction as measured by either
SWLS or LSI-A total scores. All of the significant relationships reported for hypothesis one were notably weak. In addition, the majority of the correlational analyses were non- significant, suggesting that the size of the attachment hierarchy may have a complicated relationship with levels of life satisfaction that requires careful consideration and further attention.
Statistical analyses for hypothesis two demonstrated that the size of the attachment hierarchy was not significantly different in the young-old and the mid-old.
155 Interestingly, results prior to the removal of the six multivariate outliers indicated a significant difference, with the mid-old having a larger attachment hierarchy size compared to the young-old. The non-significant results after the removal of the six multivariate outliers suggests that the significant results prior to the removal of the multivariate outliers were more related to the unusual combinations of answers provided by the six identified participants (i.e, multivariate outliers) than a true reflection of a developmental shift in the size of the attachment hierarchy between the young-old and mid-old.
Regarding the primary attachment figure, hypothesis three showed non- significance for the impact of the primary attachment figure on the size of the attachment hierarchy. Similarly, hypothesis four showed non-significance for the influence of the primary attachment figure type on levels of life satisfaction. Hypothesis five showed non- significance for the differences in the distributions of each attachment figure type between the young-old and mid-old. These results suggest that 1) the size of the attachnment hierarchy, 2) levels of life satisfaction, and/or 3) the distributions of the types of primary attachment figures may be similar between the young-old and mid-old.
The type of primary attachment figure does not appear to have a significant influence on the size of the attachment hierarchy or levels of life satisfaction. More discussion will be provided about each of these results in chapter five.
156
CHAPTER V
DISCUSSION
The primary purpose of this study was to explore relationships between the size of the attachment hierarchy, the types of primary attachment figures chosen to meet attachment needs, and levels of life satisfaction between two epochs of older adulthood.
Statistical testing yielded mixed results regarding the relationship between the attachment hierarchy and life satisfaction. Mixed results were also found for differences in the attachment hierarchies and life satisfaction between the young-old and mid-old. Study results expanded upon previous published articles on successful aging and attachment theory. In addition to attachment theory, the convoy model (Antonucci, 2001; Kahn &
Antonucci, 1980), socioemotional selectivity theory (SST; Carstensen, 2006), and disengagement theory (Cumming & Henry, 1961) were considered in the interpretation of the results. This chapter reviews the results of statistical tests that were used to test the current study’s hypotheses and provides related empirical and theoretical interpretation.
Discussion also reviews potential meaning of the overall findings, including implications for research, clinical practice, and counseling psychology. Finally, this section reviews study limitations and strengths, and provides overall conclusions.
157 A Review of the Study
The literature review for the current study revealed much speculation about the application of attachment theory in older adulthood. Much of the literature has focused on
Bowlby’s (1982) views of the attachment hierarchy as vital for adaptation from “the cradle to the grave” (p. 208), but little research has investigated the attachment hierarchy into older adulthood. In particular, empirical research is lacking on the impact of the attachment hierarchy on well-being in older adulthood. What studies were completed indicated that the size of the attachment hierarchy declined significantly in older adulthood (Cicirelli, 2010; Doherty & Feeney, 2004). The attachment figures included in the attachment hierarchy were found to include intangible attachment figures (i.e., God, a deceased spouse), and/or healthcare workers and children/grandchildren (Cicirelli, 2010).
Research has supported the presence of developmental patterns in the attachment hierarchy across the younger years of the lifespan (Doherty & Feeney, 2004; Freeman &
Simons, 2018; Trinke & Bartholomew, 1997), yet few studies have explored the relationship between attachment hierarchies and cognitive well-being in older adulthood.
Of particular note is the dearth of research investigating differences in the attachment hierarchy and/or cognitive well-being between epochs within older adulthood.
Attachment styles and attachment bonds have been linked to life satisfaction—a cognitive aspect of well-being—in older adulthood (Hsu, 2016; Kim, Lee, & Ji, 2018).
What was needed to expand upon previous research was a study investigating the relationships between attachment hierarchies and life satisfaction in older adulthood. The current study was the first of its kind to examine the impact of the size of the attachment hierarchy, and the type of primary attachment figure in the attachment hierarchy, on life
158 satisfaction. Furthermore, the current study expanded upon previous research by investigating group differences between the young-old and mid-old epochs within older adulthood. The current study addressed these gaps in the literature by using a non- experimental survey with convenience sampling to examine differences in the attachment hierarchy and life satisfaction between the young-old (ages 65-74) and the mid-old (ages
75-84) adults.
In addition to attachment theory, the work of Carstensen (2006) on socioemotional selectivity theory (SST), the work of Kahn and Antonucci (1980) and
Antonucci (2001) on the convoy model, and the work of Cumming and Henry (1961) on disengagement theory, have overlapped somewhat in consideration of the attachment hierarchy. Articles on attachment processes often cited SST, the convoy model, and/or disengagement theory alongside or in combination with literature on attachment theory.
Therefore, socioemotional selectivity theory, the convoy model, and disengagement theory are also considered in the interpretation of the current study’s results.
Both attachment theory and SST consider attachment bonds as reliant upon the attachment figure’s ability to meet an individual’s needs. Developmental trends in the attachment hierarchy across the lifespan are theorized to depend upon the changing needs of the individual. SST further explains that individuals prune their attachment bonds as they age to prioritize attachment figures who provide positive emotional experiences and assist with emotion regulation. The quality of the relationship appears to be of the utmost importance in SST, and the attachment hierarchy is thought to decrease significantly in size as one prunes relationships that are poor in quality. Relationships that are high in
159 quality are fostered and given precedence over superficial or unfulfilling relationships
(Carstensen, Gross, & Fung, 1998; English & Carstensen, 2014).
The convoy model, on the other hand, elucidates that an individual’s relationship preferences rely on an attachment figure’s ability to meet one’s instrumental and emotional needs. Attachment figures who are preferred over others tend to remain in the attachment hierarchy because they meet the functional needs of the individual. It could be argued that the quantity of attachment figures present in the attachment hierarchy may be beneficial for individuals because it maximizes the chances of functional needs being met.
Disengagement theory (Cumming & Henry, 1961; Neugarten, 1967) postulates that older adults tend to withdraw, or disengage from, social relationships and obligations that had been central to life earlier in the lifespan. The loss of social ties is said to be due to a shift in one’s thinking toward the few years remaining in life. Although much research focuses on the isolation and loneliness that this incurs (McGarry & Schoni,
2000; Schnittker, 2007), disengagement theory states that such disengagement is accompanied by life satisfaction (Crossman, 2019). Life satisfaction possibly results from the reduction of social norms one is required to follow, or the presence of a confidant—a term that is often analogous to attachment figure—that provides social interaction and satisfies one’s needs. The presence of a confidant, or trusted other, was strongly related to both emotional well-being (Lowenthal & Haven, 1968), and life satisfaction (Strain &
Chappell, 1982) in older adulthood. The results of hypothesis one could be interpreted along the lines of disengagement theory in that the quantity of attachment figures may not
160 be as imperative to life satisfaction as the presence of at least one trusted other to whom one can turn when experiencing distress.
The current study used a survey that included items from an adapted measure of the attachment hierarchy [the Attachment Network Questionnaire (ANQ: Trinke &
Bartholomew, 1997)), and two measures of life satisfaction (the Satisfaction with Life
Scale (SWLS: Diener et al., 1985); and the Life Satisfaction Index A; (LSI-A: Neugarten et al., 1961)]. An approximately equal number of participants in the young-old (n = 86), and mid-old (n = 85) completed the online survey, and differences across the entire sample, as well as differences between the young-old and the mid-old, were assessed.
A Review of the Hypotheses and Results
The current study involved five hypotheses examining various aspects of the attachment hierarchy, life satisfaction, and age. This section will address each of the five hypotheses.
Hypothesis 1
The first hypothesis addressed the relationship between the size of the attachment hierarchy and life satisfaction in old age. The size of the attachment hierarchy was measured according to the average number of attachment figures listed on the three questions on Trinke and Bartholomew’s (1997) ANQ. The three questions were created to capture an individual’s rank-ordered preference for attachment figures for each of the three attachment needs (i.e., safety, security, and proximity), as well as the overall number of attachment figures in the attachment hierarchy. The size of the attachment hierarchy was calculated by averaging the number of attachment figures reported on the three ANQ questions. Levels of life satisfaction were assessed in line with other
161 researchers who used the SWLS (Bai, Guo, & Fu, 2018; Wang, 2016) or the LSI-A
(Redmond, 1990; Wood et al., 1969). The total scores on the SWLS and LSI-A were calculated by summing the numerical values assigned to each questionnaire answer.
In regard to hypothesis one, I posited that the number of attachment figures reported in the attachment hierarchy would correlate positively with levels of life satisfaction. In the total sample and the young-old, partial correlation analyses showed that the size of the attachment hierarchy correlated positively with LSI-A total scores.
Notably, the relationships found for the total sample and the young-old showed small effect sizes, suggesting weak relationships. The significance of the results suggests that these relationships would not have been due to chance, but the coefficient of determination for the total sample was .04, and the coefficient of determination for the young-old was .0676. In other words, the variance in the size of the attachment hierarchy accounted for 4.0% and 6.76% of the variance in levels of life satisfaction (in the total sample and young-old, respectively), as measured by the LSI-A. Such small effect sizes make it impractical to identify meaning in the relationship (Akoglu, 2018). The small effect sizes suggest that the role may not be a key role, but it has a role nonetheless. In addition, future research may discover other variables that relate more strongly to the size of the attachment hierarchy and/or life satisfaction in older adulthood.
The finding that the relationship between the size of the attachment hierarchy and
LSI-A total scores was significant for the young-old, but not the mid-old, suggests that there may be developmental differences in the impact of the attachment hierarchy on life satisfaction between the first two epochs of older adulthood. Future research could benefit from continuing to investigate differences between the epochs within older
162 adulthood, as well as expanding attachment theory by including participants in the old- old.
Tests of hypothesis one showed that age and subjective age seem to capture distinctive aspects of aging and have different relationships with life satisfaction. For instance, Tables 4.8 and 4.10 show that age was positively correlated to both SWLS and
LSI-A total scores in the total sample and in the young-old. At the same time, subjective age correlated negatively with SWLS and LIS-A total scores in the total sample and the young-old. Although the effect sizes were small, the directionality and significance of the results suggest that as age increases, life satisfaction appears to increase as well. When considering the mid-old, however, the relationship between age and life satisfaction was not significant. Perhaps the mid-old are not as dependent upon age for life satisfaction, or different variables (such as the quality of relationships with significant others or the frequency of contact with attachment figures) is more salient in determining life satisfaction. On the other hand, for subjective age, it seems that the older one feels, the lower one’s life satisfaction. This negative correlation was also found for the mid-old, but only for the LSI-A, but not the SLWS total scores. Such results support the need for further research into the different aspects of age and subjective age in the period of older adulthood.
The fact that the size of the attachment hierarchy related to one measure of life satisfaction but not the other suggests that while similar, the SWLS and LSI-A assess unique aspects of life satisfaction. Correlations between the SWLS and LSI-A in the total sample (r = .76), young-old (r = .82), and mid-old (r = .67) showed moderate-to-strong convergent validity. It is notable that the LSI-A total score correlated positively with the
163 size of the attachment hierarchy while the SWLS did not. Therefore, further investigations into the specific properties of the LSI-A versus the SWLS in this population are needed.
Attachment theory would conceptualize the significant relationships in the young- old and non-significant relationships in the mid-old as support for a developmental difference in the attachment hierarchy between the young-old and mid-old. The notable lack of relationships in the current study between the size of the attachment hierarchy and life satisfaction in the mid-old indicates that the size of the attachment hierarchy has a greater influence on life satisfaction in the early years of older adulthood (ages 65-74), and little to no impact on life satisfaction in the middle years of older adulthood (ages 75-
84). Future research should consider variables such as the impact of the strength and/or security of one’s relationships with attachment figures (Fiori, Smith, & Antonicci, 2007), the closeness of one’s relationships with attachment figures (Cornwell et al., 2008,
Cornwell et al., 2014, Fiori, Smith, & Antonicci, 2007), the satisfaction felt with the fulfillment of each attachment need, and/or the frequency of contact with attachment figures (Cornwell et al., 2008, Cornwell et al., 2014) on the relationship between the size of the attachment hierarchy and life satisfaction. Of further interest would be any trends which occur into the third stage of older adulthood (i.e., the old-old).
SST (Carstensen, 2006) would conceptualize the results as support for the selective pruning of unfulfilling relationships from one’s attachment hierarchy. One possibility is that the effectively-pruned attachment hierarchies of the mid-old are so successful in meeting one’s needs that the number of attachment figures becomes irrelevant. Another possibility is that the fulfillment of each attachment need is what
164 determines levels of life satisfaction, not the number of attachment figures present in the hierarchy.
Disengagement theory (Cumming & Henry, 1961; Neugarten, 1967) postulates that older adults tend to withdraw, or disengage, from society as their awareness of less and less time in the life span increases. Disengagement theory would interpret the results of hypothesis one by explaining that the young-old continue to value social relationships, which explains why life satisfaction increases with larger numbers of attachment figures.
The non-significance of the results for the mid-old, however, could indicate support for disengagement theory’s idea that older adults isolate and withdraw from social ties, yet continue to show high levels of life satisfaction. The results of hypothesis one could be interpreted as support for the mid-old demonstrating less reliance on the number of attachment figures in the attachment hierarchy, at least in relation to levels of life satisfaction. Disengagement theory might also speculate that the mid-old in the current study possibly had confidants, which would better explain levels of life satisfaction. This could explain the weak relationships found for hypothesis one, as well as provide a possible explanation for the non-significant relationship between the size of the attachment hierarchy and SWLS total score.
In summary, replication of hypothesis one with different recruitment methods and/or different demographical distributions could yield insight into the reasons behind the low effect sizes found in the current study. Another suggestion for future research includes the influence of the closeness of relationships [maybe even the presence of a confidant] to attachment figures and/or satisfaction with the fulfillment of each attachment need. Attention could also be paid to the satisfaction one feels with each
165 attachment relationship. Additionally, exploration into the unique aspects of life satisfaction assessed by each questionnaire is warranted. Finally, the differences observed between the young-old and mid-old suggest that investigation into the relationship between the size of the attachment hierarchy and life satisfaction in the old-old could further illuminate differences that occur into the last stage of older adulthood.
Hypothesis 2
My second hypothesis addressed the research question of the differences in attachment hierarchy size between two epochs in older adulthood. My specific hypothesis was that the size of the attachment hierarchy in the mid-old would be significantly smaller than for the young-old. Again, the size of the attachment hierarchy was measured through Trinke and Bartholomew’s (1997) method of summing the number of attachment figures listed on the ANQ. Consideration for all three ANQ questions was taken by averaging the number of attachment figures listed on all three ANQ questions. Epochs of older adulthood were categorized according to age: the young-old consisted of participants ages 65-74, and the mid-old consisted of participants ages 75-84.
T-test results showed no significant group differences in the size of the attachment. Notably, before the removal of the multivariate outliers, the mean sizes of the attachment hierarchy were shown to be smaller in the young-old than the mid-old. This was surprising, not only because it was the opposite of what prior research would suggest, but also because the literature has thus far reported both theoretical and empirical support for the reduction in the size of the attachment hierarchy with age.
However, after the removal of six multivariate outliers, the results of the t-test analyses showed non-significance for differences in attachment hierarchy size between the young-
166 old and mid-old. The disparity in t-test results before and after the removal of outliers suggests that the larger attachment hierarchies previously found in the mid-old were, in fact, more related to the unusual combinations of responses of the outliers than an observed difference in attachment hierarchy size between the young-old and mid-old.
Results of hypothesis two suggest that there is no difference in the size of the attachment hierarchy between the young-old and the mid-old. The non-significance of the results for hypothesis two were surprising given the support that has been found for the negative correlation between the size of the attachment hierarchy and age (Cicirelli,
2010; Doherty & Feeney, 2004; Osborn et al., 2003). The number of attachment figures theoretically relates to an individual’s ability to adapt to one’s needs throughout the lifespan (Bowlby, 1982, 1983; Cicirelli, 2010; Doherty & Feeney, 2004). Attachment theory postulates that this occurs through the ability of attachment figures to meet the attachment needs of the individual (i.e., safety, security, and proximity; Bowlby, 1982,
1983).
Notably, methodological considerations should be made when generalizing the results of research that suggests a decline in the size of the attachment hierarchy with age.
Although there are a few studies that had relatively large sample sizes within older adulthood (Fiori, Smith, & Antonucci, 2007; Liwtin & Shiovitz-Ezra, 2010), other research that reported negative correlations between the size of the attachment hierarchy and age notably used relatively small samples of older adults (Doherty & Feeney, 2004).
Some studies failed to extend the age range of participants into older adulthood at all
(Small et al., 2007, Smith et al., 2015), and others had small sample sizes (e.g., Cicirelli,
2010). In addition, cross-sectional research with unequal numbers in each age group
167 and/or small sample sizes could potentially skew the results or make it difficult to generalize the findings to other populations.
Simply put, the current study did not find support for a decline in the size of the attachment hierarchy between the young-old and mid-old. There are a few explanations for these results. First, it is possible that the decline in the size of the attachment hierarchy does not occur until later stages of older adulthood. Therefore, exploration into the size of the attachment hierarchy in the old-old could have merit. Other possibilities include influences such as the racial homogeneity of the sample leading to biased results.
Perhaps White or Caucasian individuals show different developmental experiences in the size of the attachment hierarchy with age, but a more heterogeneous sample would yield different results. Additionally, the current study was completed with an online sample that potentially has more facility with finding attachment figures and meeting attachment needs in the online arena. Another possibility is the influence of a monetary incentive.
The financial reward could have encouraged participants who would otherwise not have completed the survey to get involved in the present study. Although the literature suggests that financial incentives have not been found to influence the motivation of participants in other studies (Buhrmester, Kwang, & Gosling, 2011; Marge, Banerjee, &
Rudnicky, 2010; Mason & Suri, 2012; Mason & Watts, 2009) the possibility must be considered.
Attachment theory would conceptualize the results of hypothesis two as an indication that the young-old and the mid-old have similar numbers of attachment figures that theoretically meet his or her attachment needs. This could imply that developmental shifts in the number of attachment figures would not improve the effectiveness of the
168 attachment hierarchy between the young-old and mid-old. It could also mean that developmental shifts occur within the quality of the relationships with each attachment figure (i.e., levels of closeness, strength, security, supportiveness, satisfaction, or frequency of contact with each attachment figure) rather than the number of attachment figures. What is needed is a study that investigates the size of the attachment hierarchy into the old-old in order to investigate the presence of developmental differences in the size of the attachment hierarchy into the third epoch of older adulthood.
SST (Carstensen, 2006) emphasizes the role of the attachment figures in assisting individuals with regulating emotions—attachment figures that are unable to do this, or who create emotional turmoil, are eventually pruned from the attachment hierarchy. SST theorizes that older adults unconsciously prune their attachment hierarchy, which results in fewer, but higher quality, relationships in the attachment hierarchy. SST (Carstensen,
2006) would conceptualize the results of hypothesis two in that the unconscious pruning of the attachment hierarchy may not be necessary between the young-old and the mid- old. Perhaps the pruning occurs more in the old-old. Alternatively, the pruning may occur with individuals who aren’t considered close enough to be considered an attachment figure. The pruning of one’s attachment figures is likely both a mental process as well as a representation of the reality of experiencing real-life losses. Perhaps the young-old have pruned their attachment figures so effectively that no further pruning is needed in the mid-old. In other words, by the time one reaches the second stage of older adulthood, he or she has possibly prioritized emotionally-gratifying relationships, and the attachment hierarchy is kept the same. Another possibility is that the mid-old are adept at replacing
169 the loss of quality relationships with others of similar quality, which would maintain the size of the attachment hierarchy.
The results of hypothesis two provide further support that the unconscious, selective pruning of attachment figures does not appear to progress in a linear fashion across older adulthood. In the current study the time period of young-old to mid-old appears to show a plateau in the selective pruning of attachment figures. The two epochs of older adulthood included in the present study may face similar challenges regarding who to include in the attachment hierarchy.
According to the social convoy model (Kahn & Antonucci, 1980), attachment figures help with adaptation across the lifespan by providing emotional and/or instrumental support. The convoy model would suggest that the needs of the young-old and mid-old are met by a similar number of attachment figures (Antonucci, 2001; Kahn
& Antonucci, 1980). Perhaps the attachment needs in the first two epochs of older adulthood are similar enough to require similar numbers of attachment figures.
Finally, the results of hypothesis two also support disengagement theory
(Cumming & Henry, 1961) in that the number of attachment figures may not be as important as the presence of a mutually satisfactory relationship with a confidant.
Disengagement theory would argue that the presence of at least one satisfying relationship in the attachment hierarchy would be more beneficial to an older adult than the overall number of attachment figures. Perhaps the size of the attachment hierarchy only changes between the two epochs if an individual is found to be without a confidant.
Because the present study did not assess the attachment hierarchy for the presence of a confidant, there is no way to know how many participants had a confidant in this sample.
170 An investigation into the presence of a confidant in the attachment hierarchy, the impact of such a relationship on the size of the attachment hierarchy, and the possibility that the quality of the relationship could be what determines whether one’s primary attachment figure is also considered to be a confidant could expand attachment theory exponentially.
In summary, hypothesis two was not supported. There do not appear to be group differences in the size of the attachment hierarchy between the young-old and the mid- old. There appears to be stability in the size of the attachment hierarchy between the young-old and mid-old. Alternatively, perhaps older adults in the first two epochs of older adulthood have similar skill or facility with replacing lost attachment figures. It is also possible that the presence of a confidant could be what determines if there is a difference between the young-old and mid-old in the size of the attachment hierarchy.
Perhaps the participants in the present study were similar in that regard, resulting in similar sizes. What was needed now is further investigation into how the size of the attachment hierarchy manifests in the old-old. Also of interest could be processes that were not included in the present study, such as the closeness, satisfaction, frequency of contact, and/or security felt in the relationships with each attachment figure.
Hypothesis 3
The third hypothesis addressed the research question of the impact of the primary attachment figure on the size of the attachment hierarchy. The size of the attachment hierarchy was calculated as the average number of attachment figures listed on the three questions on the ANQ. In line with Doherty and Feeney (2004), Freeman and Simon
(2018), and Trinke and Bartholomew (1997), the identification of the primary attachment figure was assessed through the calculation of a mean composite score for the top three
171 attachment figures listed on the three ANQ questions. Types of primary attachment figures were predetermined according to literature, and included 1) family (i.e., father, mother, brother, sister, aunt, cousin), 2) significant other (i.e., romantic partner, spouse, wife, husband), 3) friend (peers), and 4) “other” (i.e., God, pets, ex-partners).
Specifically, my third hypothesis was that participants with a primary attachment figure of family or significant other would have significantly larger attachment hierarchies, and individuals with a primary attachment figure of friend would have significantly smaller attachment hierarchies than those with a primary attachment figure of “other.”
Results for the ANOVA and ANCOVA tests used to investigate hypothesis three showed that the type of primary attachment figure did not significantly impact the size of the attachment hierarchy in the total sample, the young-old, or the mid-old. The analyses for hypothesis three did not support my hypothesis that primary attachment figures of family and romantic partners would have fewer subsequent attachment figures in the attachment hierarchy, or that individuals with peers as the primary attachment figure would have larger attachment hierarchies. No group differences in the size of the attachment hierarchy were found, indicating that each primary attachment figure type had a similar number of attachment figures in the young-old and mid-old.
The effect sizes for partial eta squared in the current study were remarkably small for each of the ANOVA and ANCOVA tests conducted in the total sample, young-old, and mid-old (Richardson, 2011). Small sample sizes for hypothesis three suggests that the relationship between the type of primary attachment figure and the size of the attachment hierarchy may not be as direct, or possibly impactful, as theory or empirical evidence would intimate.
172 It is important to note that the identification of the primary attachment figure has been measured in several different ways in the literature, and that different measurements may yield different results. Additionally, the classification of types of relationships into four categories was somewhat artificial, and further research could possibly establish a more meaningful measurement. The arbitrary nature of the assignments for each relationship type (i.e., brother, niece, deceased spouse) into four overall categories could have possibly impacted the results. Participants in the present study reported a remarkable number of relationship types (n = 43) that were then classified into one of four categories (i.e., family, peer, romantic partner, “other”). Although the progression of categorizing relationship types in the current study was based on theoretical (Bowlby,
1969, 1982) and empirical studies (Carr & Boerner, 2013, Feeney et al., 2001, Litwin &
Shiovitz-Ezra, 2010), these methods are not a standardized process with substantiated reliability. Therefore, I recommend that future studies compare and contrast several different methods of categorizing the types of relationships in the attachment hierarchy in order to identify one that is reliable.
Attachment theory would conceptualize the results of hypothesis three as indication that the type of primary attachment figure may not be a vital component in the determination of the size of the attachment hierarchy for the young-old or mid-old. The primary attachment figure is theoretically the preferred attachment figure sought in times of distress. However, the type of relationship had with one’s preferred primary attachment figure does not appear to impact the number of subsequent attachment figures one reports. Of note, the type of relationship between an individual and his or her primary attachment figure does not bear any indication of the quality of the relationship, or the
173 ability of that type of attachment figure to meet attachment needs. An individual’s ability to meet attachment needs likely impacts the number of people required as subsequent attachment figures. Therefore, future research should attend to the primary attachment figure’s ability to meet attachment needs as well as the impact of the relationship type on the overall size of the attachment hierarchy.
Attachment theory would also account for the possibility that the type of primary attachment figure was not as meaningful as the closeness of the relationships (English &
Antonucci, 2014) and/or the distinction of the composition of the entire attachment hierarchy rather than the primary attachment figure type (Freeman & Simmons, 2018;
Litwin & Shiovitz-Ezra, 2010). Furthermore, future studies could investigate the extent that the following aspects of relationships with one’s primary attachment figure impact the size of the attachment hierarchy: the extent to which each primary attachment figure type was able to fulfill the attachment needs, the subjective emotional closeness felt in each relationship, levels of satisfaction with the primary attachment figure, frequency of contact with attachment figures, or the security of one’s relationship with the primary attachment figure.
Similar to attachment theory, SST (Carstensen, 2006) would likely conceptualize the results by explaining that the type of primary attachment figure chosen may not impact the overall number of attachment figures one has. This would likely be explained as due to individual differences in the ability of attachment figures to help regulate emotions and/or provide positive emotional experiences. The type of primary attachment figure chosen does not seem to impact the quantity of figures relied on to meet one’s needs.
174 The convoy model (Antonucci, 2001; Kahn & Antonucci, 1980) would suggest that the type of primary attachment figure chosen appears to be independent of the overall attachment hierarchy size because the quantity of attachment figures is likely more relevant to an individual’s ability to meet emotional and/or instrumental needs. The convoy model would argue that one’s functional needs can be met by anyone in the attachment hierarchy, not just the primary attachment figure.
Disengagement theory (Cumming & Henry, 1961) might explain the result of hypothesis three by stating that the type of relationship had with the primary attachment figure was not as important as if one also considered the primary attachment figure (or any other attachment figure) to be a confidant. As Freeman and Simons (2018) explained, an older adult does not always have multiple options from which to choose a primary attachment figure. For example, declining health may reduce ability to access and/or engage in social interactions. Based on resources, one may have to manage with what is available, and the environment one is in may not always provide a significant other who has limited availability or someone who could also be considered a confidant. The size of the attachment hierarchy could depend on whether the individual considered his or her primary attachment figure (or another figure) to be a confidant, and another study would be needed to explore that possibility.
In summary, no group differences were apparent in the young-old, mid-old, or total sample in the size of the attachment hierarchy between the four types of primary attachment figures. Future research on the size of the attachment hierarchy in epochs of older adulthood should consider measuring aspects of relationship quality on the size of the attachment hierarchy. One possible variable could be the presence of a confidant. The
175 results of hypotheses two and three together indicate that the size of the attachment hierarchy may be stable across epochs of older adulthood as well as between groups who report different types of primary attachment figures. Future research is needed to explore the manifestation of attachment hierarchy size in the old-old.
Hypothesis 4
Hypothesis four addressed the research question of the impact of the primary attachment figure on life satisfaction. Specifically, I hypothesized that primary attachment figures that were family and friend would have higher life satisfaction, and those with “other” to have lower life satisfaction levels than individuals with a primary attachment figure of significant other. Mean composite scores were used to determine the primary attachment figure type, and life satisfaction was determined through total scores on the SWLS and the LSI-A.
Results of the MANOVA’s and MANCOVA’s indicated that, for the total sample and in the young-old and mid-old, the type of primary attachment figure had no impact on levels of life satisfaction as measured by the SLWS or LSI-A. My hypothesis that the type of primary attachment figure reported would impact levels of life satisfaction was not supported.
Similar to hypothesis three, it is important to note that the identification of the primary attachment figure has been measured in several different ways in the literature, and that different methods may yield different results. Future research could focus on improving the way that primary attachment figures are categorized, as well as identifying the most effective way to classify each relationship type into a category.
176 Attachment theory would explain these results as verification that similar levels of life satisfaction are obtained in the young-old and mid-old, seemingly regardless of the primary attachment figure type. Considering the results of hypothesis one together with the results from hypothesis four, the size of the attachment hierarchy appears more influential for life satisfaction in the young-old than the type of primary attachment figure. Neither the size nor the primary attachment figure type appears to have an influence on life satisfaction in the mid-old. Perhaps individuals in older adulthood begin to adapt with time, or with the accumulation of wisdom, to make their current circumstances work for themselves. Although the attachment hierarchy and other attachment processes are impactful across the entire lifespan, it is important to consider that the type of primary attachment figure may not be as important in appraisals of life satisfaction as other aspects of the attachment hierarchy, such as closeness to one’s attachment figures, the composition of the entire attachment hierarchy, or some other more distal variable such as overall health. Similar to hypothesis three, future research should investigate the importance of the quality of the relationship with one’s primary attachment figure, as well as the ability of the primary attachment figure to meet attachment needs between the epochs of older adulthood. Furthermore, research is needed to investigate the relationship between the type of primary attachment figure reported and life satisfaction in the old-old.
SST (Carstensen, 2006) would argue that the impact of the type of primary attachment figure on cognitive appraisals of life satisfaction does not appear to be a vital component of the selective pruning that occurs in the attachment hierarchy as one ages.
The type of primary attachment figure one has seems to be independent of his or her
177 cognitive appraisals of life satisfaction. SST may even argue that cognitive appraisals of well-being would not be as effective in older adulthood as emotional appraisals because the selective pruning of the attachment hierarchy relates to one’s satisfaction with emotional needs as well as an attachment figure’s ability to provide positive emotional experiences.
The convoy model (Antonucci, 2001; Kahn & Antonucci, 1980) would likely suggest that the type of primary attachment figure one has does not significantly influence the overall fulfillment of emotional and/or instrumental needs in older adulthood, potentially because these needs can be met by anyone in the attachment hierarchy. The convoy model would likely consider both emotional and cognitive well- being as related to the emotional and instrumental needs one has, and his or her ability to meet those needs with his or her current attachment hierarchy. Similar to hypothesis three, the convoy model would consider aspects of the attachment hierarchy as a whole to be more important than the primary attachment figure type, especially since hypothesis four showed no significance in the type of primary attachment figure on levels of life satisfaction.
In summary, no group differences were found in the young-old, mid-old, or total sample in levels of life satisfaction between the four primary attachment figure types.
Future research on life satisfaction in the epochs of older adulthood should consider aspects such as relationship quality between and individual and his or her primary attachment figure. Future research should also consider exploring the relationship between the primary attachment figure and life satisfaction in the old-old. The combined results of hypothesis one and hypothesis four suggest that the size of the attachment
178 hierarchy may have more of an impact on levels of life satisfaction [at least in the young- old] than the type of primary attachment figure chosen in older adulthood.
Hypothesis 5
Hypothesis five addressed the research question of the observed frequencies in primary attachment figure type in the young-old versus the mid-old. Specifically, I expected a larger number of the mid-old reporting “other” primary attachment figures than the young-old. Primary attachment figures were identified with mean composite scores. Epochs were identified by age.
Hypothesis five was not supported. The observed frequency differences in the distributions of those with varying types of primary attachment figures was shown to be similar between the young-old and mid-old. Attachment theory would likely explain these results by stating that the distributions of people who had each type of primary attachment figure was similar in the young-old and the mid-old. Another probable explanation could be that, when possible, the type of primary attachment figure potentially remains stable across the epochs of older adulthood. Taken together with the fact that older adults experience more loss than younger cohorts across the lifespan, it is possible that when an older adult in the first two epochs of older adulthood establishes a meaningful relationship, as would theoretically be true of one’s relationship with his or her primary attachment figures, much effort is placed in maintaining the relationship and sustaining its functionality. Fear of inability to replace such relationships could keep one invested in its maintenance, even if the quality was poor. An alternative explanation could be that comfortability leads to the replacement of a lost primary attachment with another of a similar type.
179 SST (Carstensen, 2006) would likely conceptualize the results of hypothesis five by explaining that the primary attachment figure may not be a viable attachment figure to prune from the attachment hierarchy. The primary attachment figure is relied on— sometimes frequently or with great intensity—and the pruning of such a figure from the attachment hierarchy would theoretically cause unbearable distress. If pruning of the primary attachment figure became necessary, perhaps it is replaced with a relationship of a similar type. It could also be that pruning does not occur until the old-old. The present study’s results suggest that there may possibly be stability between the young-old and mid-old in relation to the distributions of each type of primary attachment figure. A longitudinal study would be better able to investigate this possibility through within- person comparisons.
The convoy model (Antonucci, 2001; Kahn & Antonucci, 1980) would suggest that if one is satisfied with his or her primary attachment figure, changes would not be likely to occur. Particularly if one is able to meet his or her emotional and instrumental needs through the attachment with the primary attachment figure, no changes would be needed. Similar to attachment theory and SST, the convoy model would likely state that, when necessary, changes may be made to another person that was of similar type to the previous attachment figure.
In summary, the distributions of participants who reported each type of primary attachment figure (three types, since the group with “other” was small enough to violate the assumptions of the chi-square analysis, and was therefore removed) was not found to be significantly different in the young-old and mid-old. It is possible that one maintains his or her primary attachment across the two epochs, with effort being placed into the
180 maintenance of its functionality. Or perhaps necessary replacements are made with someone of a similar type. Further research is needed on the distributions of each primary attachment figure type within the epoch of the old-old.
Implications for Research
This exploratory study focused on the variables of age, attachment hierarchies, and life satisfaction. As the first study thus far to examine this specific combination of variables, replication of these results is vital for expanding research on this topic.
Generalizability could also be expanded by replicating this study in other populations.
One important implication of the current study was that age appeared to be a poor determinant for distinguishing epochs within older adulthood. In line with previous research, (Neugarten et al., 1961; Neugarten, 1967), the current study’s results suggest that age may not be the most meaningful variable by which to compare different periods within older adulthood. Further exploration into other variables, such as overall health or retirement status may discover a more prominent and/or salient variable for delineating epochs of older adulthood for this age cohort. On the other hand, perhaps the current study’s results indicate that age does not matter as much as other variables in this particular age cohort. Future research could investigate the benefits and consequences of multiple methodologies for measuring the epochs within older adulthood and discuss the strengths and limitations of each. Attachment theory could benefit from further discussion about potentially meaningful ways to measure differences in the attachment hierarchy and/or life satisfaction between epochs within older adulthood.
Furthermore, results of the current study showed that age and subjective age appear to have different relationships with life satisfaction. In the total sample and young-
181 old, as age increased, life satisfaction was shown to increase. However, in the total sample and the young-old, as subjective age increased, life satisfaction appeared to decrease. Because individuals have both age and their subjective experience of age, it appears that different combinations of age and subjective age may show different influences on life satisfaction. Further exploration into age and subjective age may be warranted.
A second implication of the current study was that the size of the attachment hierarchy was found to correlate positively with one measure of life satisfaction for the total sample and the young-old. Notably, these results were mixed, and the size of the relationships were small. The mixed results suggest a complicated relationship between the size of the attachment hierarchy and levels of life satisfaction. Perhaps one’s need for a large attachment hierarchy depend upon his or her situation in life. For instance, one’s health could lead one to feel confident in meeting his or her attachment needs when feeling well, but to desire more, or different, attachment figures when feeling poorly and unable to complete activities of daily living. Furthermore, exploration into the identification of effective ways to enhance the size of the attachment hierarchy for older adults with low levels of life satisfaction could begin by exploring the impact of the presence of a confidant, or the quality of the relationships with each attachment figure, on both the overall size of the attachment hierarchy, and levels of life satisfaction.
A third important finding included the unique developmental differences in the attachment hierarchy between the young-old and mid-old. The significant relationships between the size of the attachment hierarchy and life satisfaction found in the young-old were non-significant in the mid-old. Perhaps the mid-old are better able to meet their own
182 needs, or that their levels of life satisfaction are not as reliant on the size of the attachment hierarchy as in the young-old. Perhaps, in line with SST, the mid-old are more reliant on their ability to attend to positive experiences than they are on their attachment hierarchy for cognitive appraisals of well-being. For example, the mid-old have more experience managing emotions and needs, which possibly makes them more adept at maintaining life satisfaction independent of the attachment hierarchy. Regardless, the results of the present study support the need for further investigation of differences between the epochs of older adulthood that could otherwise be overlooked. I highly recommend the inclusion of the old-old in any future studies exploring the attachment hierarchy.
A fourth important finding of the current study was that investigation into the type of primary attachment figure showed non-significance on the size of the attachment hierarchy and levels of life satisfaction, along with differences between the distributions of each type in the young-old and mid-old. Because no relationships were found between the type of primary attachment figure and the size of the attachment hierarchy or levels of life satisfaction, the results of the current study suggest that although there are some developmental changes observed between the young-old and mid-old, there may also be some areas of stability. The findings of the current study suggest that the size and levels of life satisfaction remain similar in the young-old and mid-old regardless of the type of primary attachment figure one has. Moreover, the distributions of the types of primary attachment figures was not significantly different between the young-old and mid-old, suggesting a possible stability in the type of primary attachment figures chosen. It is possible that individuals keep the same primary attachment figure in the first two epochs
183 within older adulthood. It is also possible that the racial homogeneity of the participants in the present study, or even the influence of a financial reward, led to a cultural phenomenon that would not be replicated with a more homogenous sample.
Theoretically, the non-significant relationships with the primary attachment figure in the current study were surprising because previous studies alluded to the likelihood that developmental differences would be found in the types of primary attachment figures chosen, size of the attachment hierarchy, and levels of life satisfaction across the epochs of older adulthood. Likewise, empirical research, as discussed previously, has found support for developmental changes that occur across the stages within older adulthood.
The current study’s results indicated that the developmental changes possibly occur in the old-old period in adulthood, or involve variables that were not measured in this study.
What was suggested by the current study is that there may be more stability, in regards to the attachment hierarchy, than was anticipated.
It is important to consider that variables which were not measured in the current study could potentially demonstrate developmental differences between the epochs of older adulthood in regards to the attachment hierarchy. Some potentially influential variables could relate to the quality of one’s relationship to the primary attachment figure
(i.e., closeness felt, levels of support provided, ability to fulfill attachment needs, frequency of contact, the strength and security of the relationship). Other variables could include the ability of the attachment hierarchy as a whole to meet an individual’s needs, or even the presence of a confidant. Conversely, and perhaps particularly true for this
American population, may be the role of growing self-reliance throughout one’s lifetime.
184 In addition to the findings that the primary attachment figure type did not appear to influence the size of the attachment hierarchy or levels of life satisfaction, and did not appear to show different distributions in the young-old and mid-old, it is important to note that the way in which the primary attachment figure was measured may have impacted the results. In the current study, the primary attachment figure was identified through the calculation of mean composite scores and then labelled according to predetermined categories of relationship type. Although these methods were based on previous literature, the assessment of the primary attachment figure type was ultimately artificial and arbitrary. One could argue that different assessment methods may show different results. More research is needed to examine how the methods chosen for this measurement impacted the results. Future research could also focus on examining how the variable of the primary attachment figure manifests in the old-old.
A fifth consideration of the current study’s results is that future research on the within-person changes in the attachment hierarchy and life satisfaction across the epochs of older adulthood could be beneficial for determining what changes, and/or stability, may occur within an individual as he or she experiences each epoch of older adulthood.
The current study relied on a cross-sectional approach, which makes comparisons between individuals rather than within individuals. The salience of the relationships found in the present study (i.e., the attachment needs, the overall average of attachment size) were significant between the young-old and mid-old, but these variables could possibly shift with time within the same individual as he or she traverses the stages of older adulthood. Therefore, a longitudinal study could provide unique insight that a cross- sectional design would miss.
185 A sixth indication the present study results is that the investigation of the attachment hierarchy may show different results depending on the aspects that are being measured. The current study measured the influence of the primary attachment figure.
Other studies, such as Freeman and Simons (2018) or Litwin and Shiovitz-Ezra (2010), measured the attachment hierarchy in terms of its overall compilation of types of attachment (i.e., a friend-network, diverse network, family-network) that could potentially explain the influence of the attachment hierarchy in a uniquely different perspective than the present study. Similar to the ways one classifies the type of relationship for the primary attachment figure, researchers should deliberate on the pros and cons of each method for operationalizing the types of relationships in the attachment hierarchy before beginning their study.
A seventh important finding of the current study was the significance of results often relied upon which measure of life satisfaction was being used. Further exploration is needed to distinguish the unique abilities of the SWLS and LSI-A in measuring life satisfaction. For example, the young-old and the total sample were found to have significant relationships with life satisfaction as measured by the LSI-A, but not the
SWLS. The strong correlations between the SLWS and LSI-A suggest convergent reliability, but further research is needed on the unique ways in which each questionnaire measures life satisfaction.
Implications for Clinical Practice
Due to the exploratory nature of this study, a goal was to investigate the relationships between the attachment hierarchy and life satisfaction in two epochs of older adulthood. Because of the increasing number of individuals age 65 and above (von
186 Humboldt, & Leal, 2017), there is a natural influx of older adult clientele in need of psychological intervention. Scientific interest in the unique needs of the older adult population has been increasing, but more studies are needed to examine the applicability of technique and theory to individuals beyond the stage of the young-old (Baltes &
Smith, 2003).
One important implication for clinical practice and training gained from the current study is increased awareness. Practicing psychologists who are aware of the impact of the size of the attachment hierarchy on life satisfaction and the importance of assessing which epoch of older adulthood a client is in are more likely to consider the multifaceted nature of such variables when conceptualizing and providing treatment to clients. The current study shows that there is merit in psychological reflection upon the number of attachment figures one has, the epoch of older adulthood one is in, and levels of life satisfaction.
For practitioners interested in quantifying the attachment hierarchy, epochs of older adulthood, or life satisfaction, the current study emphasized the possibility that there are multiple ways of measuring and classifying the primary attachment figure that may influence how it is understood. In regards to the primary attachment figure, there does not appear to be any indication at this time that a practitioner could benefit from assessing the type of relationship this is or how to alter the type of relationship one chooses. However, awareness that there may be an impact of the methods for measuring and categorizing the primary attachment figure could ultimately save time and effort. In addition, practitioners should be aware that there is currently no best practice for identifying the epoch of older adulthood one is in. Chronological age does not appear to
187 be the best way to determine psychological needs, yet no standardized or validated measure has yet been created that provides a more meaningful method for quickly contextualizing a person’s life. In regard to life satisfaction, awareness that the SWLS and LSI-A possibly measure different aspects of life satisfaction could help one be aware that each could possibly yield helpful information and be attentive for future studies that investigate their strengths and weaknesses. An additional time-and-effort saver could be consideration of the fact that the current study shows between-group differences, and that nothing is yet known about intra-individual differences in the attachment hierarchy or life satisfaction in older adulthood.
The findings that the size of the attachment hierarchy can impact levels of life satisfaction in the young-old can help practitioners to better assess when an older adult may be at risk for lower levels of life satisfaction. Although more research is needed, these results suggest that practicing psychologists can consider the epoch in which an older adult is in to determine an appropriate size for the attachment hierarchy, as well as the prospective effectiveness of therapeutic techniques aimed at altering the size of the attachment hierarchy or increasing life satisfaction in that stage of life. The results of this study suggest that therapeutic techniques aiming to impact the size of the attachment hierarchy and/or life satisfaction may be found to influence the young-old in different ways than the mid-old.
The lack of relationship between the type of primary attachment figure reported and 1) the size of the attachment hierarchy, and 2) levels of life satisfaction suggest that clinical practitioners can reassure clients that the primary attachment figure does not appear to impact the number of subsequent attachment figures or levels of life
188 satisfaction in the first two epochs of older adulthood. For those with few choices for whom they rely on, this may provide some relief. There appears to be potential for any type of attachment figure to be effective in improving life satisfaction. Practitioners can focus on the similarities between the young-old and mid-old in regard to the size of the attachment hierarchy, levels of life satisfaction, and types of primary attachment figures.
Simply put, the knowledge that there is no indication of change in regard to the size of the attachment hierarchy or levels of life satisfaction between the epochs (at least in relation to the primary attachment figure), may assist practitioners in reaffirming the potential for growth and/or stability. Additionally, there appears to be a broad potential for improvement in life satisfaction regardless of the type of primary attachment figure one has. A practitioner’s awareness of the potential for growth and/or stability between the young-old and mid-old could assist that practitioner with educating clients and coworkers on the potential for increased life satisfaction and/or possible stability between epochs of older adulthood.
Although further investigation into the intra-individual stability of the primary attachment figure, levels of life satisfaction, and the size of the attachment hierarchy throughout older adulthood is needed, it is notable that there has not yet been any indication that an older adult could benefit from switching the type of primary attachment figure he or she has. Attempts to help clients in the young-old or mid-old shift to a different type of attachment figure would not likely impact the size of the attachment hierarchy or change levels of life satisfaction, and this could save practitioners time and effort. Furthermore, practitioner’s awareness that the distributions of the primary attachment figure were not significantly different in the young-old and mid-old could
189 help him or her to rule out the primary attachment figure as a sole indicator of life satisfaction.
The current study expanded upon attachment theory, SST, the convoy model, and disengagement theory by interpreting results on the attachment hierarchy and life satisfaction in two epochs of older adulthood. Results supported Bowlby’s notion that the attachment hierarchy was vital to adaptation from birth until death. The current study showed that there appear to be both changes and possible stability in the attachment hierarchy between the stages of the young-old and mid-old. Few studies have thus far investigated developmental differences and/or similarities between epochs within older adulthood. Furthermore, the results of the present study were able to also be examined through the lenses of SST’s conceptualization of the selective pruning of social networks, social convoy model’s ideas of the inclusion of attachment figures based on the fulfillment of emotional and instrumental needs, and disengagement theory’s ideas that the eventual detachment of an older adult from his or her social roles increases life satisfaction.
Finally, this study will aid psychologists in social justice efforts aimed at addressing views of older adulthood as a period of decline and degeneration (Himes &
Fang, 2007). For example, a broadening of connections in the young-old may help older adult clients to increase life satisfaction. The result of the present study can challenge the notion that older adulthood is simply a period of decline and provide guidance to future researchers interested in examining these relationships. Results of the current study can also aid in guiding future research to further support the concepts and awareness of successful aging.
190 Study Limitations and Strengths
There are several limitations to be considered when interpreting the results. First, the study was based on a convenience sample, which restricts generalizability to those represented in the current sample. The survey was provided on an online website, which no doubt limited the present study to individuals who were required to be literate and skilled at navigating a computer. Additionally, the majority of participants were married
(51.88%), had a high school or undergraduate education (66.08%), were not employed
(83.63%), reported average health (49.71%), had fair financial status (79.53%), and were living with a spouse (42.69%). The distributions of the demographic variables were uneven across all of the options available, which makes it important to consider that the findings of the current study could potentially indicate a cultural phenomenon, or possibly a trend within this particular cohort . Replication of this study with specific attention to marital status and employment could yield more insight, as these variables were found to show significant differences between the young-old and mid-old, and could arguably impact one’s attachment hierarchy. One particular limitation of the current study was that the participants were primarily White or Caucasian (75.1%). Race was not found to correlate with the dependent variables in the present study, but the results are undeniably based on a predominantly White population. It is possible that a different racial distribution would yield different results.
An additional limitation of the current study was the artificial use of age in the delimitation of young-old and mid-old. There currently is no validated or peer-reviewed best-standard for distinguishing between the epochs of older adulthood, which could have influenced the result of the current study. Age appears to have little meaning in
191 separating epochs within older adulthood. The current study included a measure of subjective age in an attempt to overcome this. To focus the work of the present study, the inclusion of participants in the stage of the old-old were not collected. Additionally, obtaining samples of the old-old has been notoriously difficult. However, attachment theory could benefit from further examination into the manifestation of the relationships between the attachment hierarchy, life satisfaction, and age into the last stage of older adulthood.
Another limitation includes the artificial (i.e., lack of a psychometrically validated measure) nature for determining a precise typology of attachment figures. In addition, the methods used in the current study were based on a limited examination of the type of primary attachment figures included in previous research. Four empirically-guided classifications for the type of primary attachment figure were chosen in the present study.
Based on the work of several researchers (Antonucci, Akiyama, & Takahashi, 2004;
Doherty & Feeney, 2004; Feeney, Hohaus, Noller, & Alexander, 2001; Fraley & Davis,
1997; Hazan & Zeifman, 1994, 1999; La Guardia et al., 2000; Schachner, Shaver, &
Gillath, 2008; Trinke & Bartholomew, 1997), the present study included the categories of family, peer, romantic partner, and “other” as types to classify primary attachment figures. There were over 40+ relationships reported by participants in the present study, and categorizing most of them into “other” may have had an impact on data analyses.
Moreover, the use of a mean composite score to determine the primary attachment figure for each participant could also have impacted the results. Also, the self-report nature of all instruments may have obscured the reality of just what is going on in participants’ lives. Interviews and third-party reports of their experiences is needed.
192 Another limitation included the undeniable uniqueness of participants’ willingness to complete not only online surveys, but specifically one listed on MKTurk.
Participants were provided with $1.00 for the completion of the study, which could have influenced the type of participants obtained and/or motivation levels. There is no way of determining exactly how much, if any, incentive this had on participants. Replication of this study is needed to increase the generalizability of the results to populations outside of online surveys and/or computer literate individuals.
There are also several strengths of the current study. First, this study is the first to examine the impact of the size and types of primary attachment figures on the cognitive aspect of well-being (life satisfaction) in older adulthood. This study examined several assertions from previous literature and found support for developmental trends in the attachment hierarchy in older adulthood. Second, this study is the first to explicitly examine the attachment hierarchy and life satisfaction between two epochs of older adulthood. This study provided evidence that epochs within older adulthood have an impact of the number of attachment figures, the relationship between the number of attachment figures on levels of life satisfaction, and the influence of the primary attachment figure on the number of attachment figures. Finally, this study is the first to examine the distributions of participants with each type of primary attachment figure between the epochs of the young-old and the mid-old.
The current study had an approximately equal number of individuals in each epoch, and an approximately equal number of males and females. There were limited missing data, and relatively few outliers that required pairwise deletion. The findings of the present study addressed gaps in the literature related to positive aging, attachment
193 processes, and the cognitive aspect of well-being (life satisfaction). Additionally, this study advances research of attachment theory, SST, social convoy model, and disengagement theory.
Conclusion
This exploratory study adds to the scant literature on attachment theory in older adulthood. Results showed that there are complex relationships between the size of the attachment hierarchy and life satisfaction. No differences in the size of the attachment hierarchy or life satisfaction were found based on the type of primary attachment figure reported. In addition, no differences in the distributions of the types of primary attachment figures was found between the young-old and mid-old. The SWLS and LSI-A appear to have similar, but unique, abilities for measuring life satisfaction that need to be explored further. No relationships were found between the primary attachment figure and life satisfaction, and no differences were found in the distributions of people reporting each primary attachment figure type between the young-old and mid-old. Of particular consequence was the support found for the merit in examining developmental differences in the size and type of primary attachment figure and life satisfaction between different epochs within older adulthood. Future research should expand upon the current study by including the period of old-old in examinations.
The current study provided evidence that there is potential for benefits and gains in older adulthood. Specifically, the size of the attachment hierarchy was found to correlate positively with life satisfaction in the young-old. This finding indicates that there may be the potential for improving life satisfaction by increasing the size of the attachment hierarchy in the young-old. Such findings are an important addition to the
194 literature on positive psychology. Psychologists are in a unique position to combat the negative beliefs in our society that older adulthood is simply a period of deficits. By educating clients and colleagues and advocating for the development of interventions which effectively increase the size of the attachment hierarchy, psychologists can help practitioners to focus on improvement and stability that can occur within older adulthood.
The findings of the current study can aid in the effort of psychologists who are attempting to further research on successful aging, develop and provide therapeutic techniques which enhance the lives of older adults, and modify beliefs that people hold about older adulthood. The current study has the potential for assisting with all three of these benefits to society.
195
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APPENDICES
230
APPENDIX A:
DEMOGRAPHIC QUESTIONS
Please Answer the following Questions about Yourself:
1. How did you hear about this survey?
In-person request
I found it online (e.g., MK Turk, Qualtrics)
I received a link in an email through a listserv
Other: please explain
2. What is your age?
years
3. Sometimes people feel older or younger than their age. During the last month,
what age did you feel most of the time?
years
4. What was your sex at birth?
Male
Female
231 5. What is your current gender identity?
Male
Female
Transgender
I don’t consider myself male, female, or transgender
6. What is your race/ethnicity? Check all which apply:
American Indian or Alaskan Native
Asian
Black or African American
Hispanic or Latino
Native Hawaiian or Other Pacific Islander
White or Caucasian
Other: please explain
232 7. What is your marital status?
In a committed relationship for less than two years
In a committed relationship for two or more years
Married
Separated
Divorced
Widowed
Not in a committed relationship
Other: please explain
8. What is the highest level of school you completed?
Less than primary education
Primary education
High school
Undergraduate education
Graduate education
9. How do you regard your health compared to others your age?”
Not as good as others
As good as others
Better than others
233 10. Are you employed?
Yes
No
11. How would you rank your financial situation?
Very poor
Poor
Fair
Rich
Very rich
12. How would you describe your living arrangements?
Living alone
Living with a spouse and child(ren) (or grandchildren)
Living with a spouse only
Living with children (or grandchildren) only
Living with others
Living in a nursing home
234
APPENDIX B:
ATTACHMENT NETWORK QUESTIONNAIRE
Instructions:
Think of the significant people in your life, those you currently feel a strong emotional tie to. List only the individuals which actually relate to each question. List them in order of preference.
Whom do you go to, to help you feel better when something bad happens to you or you feel upset. List as many or as few people as you feel necessary in order of preference.
NAME RELATIONSHIP TO YOU (e.g., friend, brother)
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
235 Whom do you feel you can count on to always be there for you and care about you, no matter what? List as many or as few people as you feel necessary, in order of preference.
NAME RELATIONSHIP TO YOU (e.g., friend, brother)
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
236 Whom is it important for you to see or talk with regularly? List as many or as few people as you feel necessary, in order of preference.
NAME RELATIONSHIP TO YOU (e.g., friend, brother)
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
237
APPENDIX C:
SATISFACTION WITH LIFE SCALE
DIRECTIONS: Below are five statements with which you may agree or disagree. Using the 1-7 scale below, indicate your agreement with each item by placing the appropriate number in the line preceding that item. Please be open and honest in your responding.
1 = Strongly Disagree 2 = Disagree 3= Slightly Disagree 4 = Neither Agree or Disagree 5 = Slightly Agree 6 = Agree 7 = Strongly Agree
1. In most ways, my life is close to my ideal.
2. The conditions of my life are excellent.
3. I am satisfied with life.
4. So far I have gotten the important things I want in life.
5. If I could live my life over, I would change almost nothing.
238
APPENDIX D
LIFE SATISFACTION INDEX A
DIRECTIONS: Below are twenty statements with which you may agree or disagree. Please indicate your response to each item by placing a check next to agree, disagree, or I don’t know. Please be open and honest in your responding.
Items with an asterisk (*) require reverse-scoring.
1. As I grow older, things seem better than I thought they would be. Agree Disagree I don’t know
2. I have gotten more of the breaks in life than most of the people I know. Agree Disagree I don’t know
3. This is the dreariest time of my life.* Agree Disagree I don’t know
4. I am just as happy as when I was younger. Agree Disagree I don’t know
5. My life could be happier than it is now.* Agree Disagree I don’t know
6. These are the best years of my life. Agree Disagree I don’t know
239 7. Most of the things that I do are boring or monotonous.* Agree Disagree I don’t know
8. I expect some interesting and pleasant things to happen to me in the near future. Agree Disagree I don’t know
9. The things I do are as interesting to me now as they ever were. Agree Disagree I don’t know
10. I feel old and somewhat tired.* Agree Disagree I don’t know
11. I feel my age, but it does not bother me. Agree Disagree I don’t know
12. As I look back on my life, I am fairly well satisfied. Agree Disagree I don’t know
13. I would not change my past life even if I could. Agree Disagree I don’t know
14. Compared to other people my age, I’ve made a lot of foolish decisions in my life.* Agree Disagree I don’t know
15. Compared to other people my age, I make a good appearance. Agree Disagree I don’t know
240 16. I have made plans for things I’ll be doing a month or a year from now. Agree Disagree I don’t know
17. When I think back over my life, I didn’t get most of the important things I wanted.* Agree Disagree I don’t know
18. Compared to other people, I get down in the dumps too often.* Agree Disagree I don’t know
19. I’ve gotten pretty much what I expected out of life. Agree Disagree I don’t know
20. In spite of what people say, the lot of the average man is getting worse, not better. Agree Disagree I don’t know
241
APPENDIX E:
IRB APPROVAL
242
APPENDIX F:
COVER LETTER
You are being invited to participate in a research project being conducted by Bethanie Cavalier, MA, LPC, a graduate student in the Department of Psychology at The University of Akron. The purpose of this research is to explore the attachment styles, attachment hierarchies (support networks), and life satisfaction in adults.
If you decide to participate, you will be asked to complete a few questions about your demographic information, and three questionnaires. There are minimal risks involved with your participation, and the primary benefit is scientific. The questionnaires should take no more than 10 minutes to complete. I hope to recruit 159 participants.
You have the right to withdraw from this study at any time. You will not be penalized if you withdraw. The questionnaires will not collect any information that could identify you and no one will be able to connect your responses to you. Your anonymity is further protected by not asking you to sign and return a consent form. The data collected will be secured in a locked file cabinet which will only be accessed by Bethanie Cavalier. Your completion of these questionnaires will serve as your consent. Please keep this cover letter for future reference.
If you have any questions about this study you may contact me at [email protected], or my advisor, Dr. Charles A. Waehler, at [email protected]. This project has been reviewed and approved by The University of Akron Institutional Review Board. If you have any questions about your rights as a research participant, you may call the IRB at (330) 972-7666. Thank you for your participation.
243
APPENDIX G:
DEBRIEFING STATEMENT
Thank you for participating in this study! I hope you enjoyed the experience. This form provides background about our research to help you learn more about why we are doing this study. Please feel free to ask any questions or to comment on any aspect of the study.
You have just participated in a research study conducted by: Bethanie Cavalier; [email protected]
The purpose of this study was to examine the relationships between age, the attachment hierarchy (your support network), and life satisfaction. Attachment theory has been studied in younger populations, and one goal of this study is to expand our knowledge on older adulthood. The size and primary attachment figures in the attachment hierarchy follow predictable trends throughout the lifespan, but little is known about these trends in older adulthood, or their influence on life satisfaction.
As you know, your participation in this study was voluntary. If you so wish, you may withdraw after reading this debriefing form, at which point all records of your participation will be destroyed. You will not be penalized if you withdraw.
You may keep a copy of this debriefing for your records.
If you have questions now about the research, please ask. If you have questions later, please email Bethanie Cavalier, [email protected]. If, as a result of your participation in this study, you experienced any adverse reaction, please contact The University of Akron IRB at (330) 972-7666.
244