Running head: DEPRESSION AND SOCIAL SUPPORT 1

Depression and social support: Why social support may help those who are depressed?

Anastasiia Onatskaia

ANR 517209

Supervisor: Dr. Yvette van Osch

Second supervisor: Dr. Rob Nelissen

DEPRESSION AND SOCIAL SUPPORT 2

Abstract

Social support is well known to have negative effect on depression. However, relatively few studies focus on why social support is beneficial for mental health. Those who do, offer a few possible explanations for the relationship: (1) stress-buffering approach

(enhancing coping performance and appraising life events as less stressful) and (2) behavioral change approach (health improvement through health-promoting behaviors: choosing a healthy diet and exercising). The stress-buffering approach is the only theoretical concept that has an empirical evidence, the behavioral change approach has never been examined before.

Therefore, the current study is the first empirical test of the behavioral change approach, and it is also the first study that investigates more than one approach. The data (N=205) showed main effect of social support on depression; however no significant results confirming either explanation of social support effectiveness were found. In the exploratory analysis, social support moderated relationship between stress and depression for the group of participants that were not previously diagnosed with depression (no/no group); however failed to do the same in two other groups, consisted of participants who were previously diagnosed with depression, and did (yes/yes group) or did not (yes/no group) take medication at the moment of the study. Overall, I found very little evidence for suggested explanations of the relationship between social support and depression.

Keywords: depression, social support, stress, diet, physical activity.

DEPRESSION AND SOCIAL SUPPORT 3

Depression and social support: Why social support may help those who are depressed?

Major Depressive Disorder is one of the main causes of morbidity worldwide (World

Health Organization, 2001). The number of people affected by Major Depressive Disorder during their lifetime is in the range between 5 and 17% (Sadock, Sadock & Ruiz, 2017).

DSM-5 operationalizes Major Depressive Disorder in the following way: depressed mood; markedly diminished interest or pleasure in activities, significant weight loss when not dieting or weight gain; sleep disturbance; fatigue; feelings of worthlessness; diminished ability to think or concentrate; recurrent suicidal ideation, a suicide attempt or a specific plan for committing suicide (American Psychiatric Association, 2013, p.160).

Despite the prevalence of depression even in countries with well-organized health care systems it was estimated that between 44% and 70% of patients with Major Depressive

Disorder do not receive treatment (American Association of Suicidology, 2014). If left untreated, depression can lead to comorbid (emerging at the same time) mental disorders, recurrent episodes and higher rates of suicide (American Association of Suicidology, 2014).

However, depression is curable; the recovery probability during first six months is more than

50%, within 1 year is 70% and within 5 years is 88% (Keller et al., 1992). There are many methods that are used to cope with depression, including medicines, psychotherapy, electroconvulsive therapy (Gelenberg et al., 2010) and also tools such as yoga (Streeter,

Gerbarg, Saper, Ciraulo & Brown, 2012) and meditation (Chiesa & Serretti, 2010), etc.

Kraemer, Wilson, Fairburn and Agras (2002) questioned why and under what circumstances treatment of psychiatric disorder results in recovery. Researchers indicated that social support may be an important extra-therapeutic condition of successful depression treatment (Linville,

1987; Park, Cuijpers, van Straten & Reynolds, 2014).

The link between social support and depression is well established; many studies have shown a negative effect of social support on depression (e.g., Aneshensel & Frerichs, 1982; DEPRESSION AND SOCIAL SUPPORT 4

Brown et al., 1986; George, Blazer, Hughes & Fowler, 1989; Gottlieb & Bergen, 2010; Grav,

Hellzèn, Romild, & Stordal, 2012; Holahan & Holahan, 1987; Lin, Dean & Ensel, 2013;

Wang, Cai, Qian, & Peng, 2014). However, relatively few studies focus on why social support is beneficial for health (Cohen, 1988). It was suggested that there are multiple psychological pathways by which social support may influence both onset (Brown &

Andrews, 1986; Thoits, 1982) and progression (George, Blazer, Hughes & Fowler, 1989) of depression. Articles offering classifications of approaches that can potentially explain relationship between social support and depression are mainly theoretical; they are great for understanding multiple approaches one can use but they lack empirical evidence. To get a clear picture on why social support has significant effect on depression, multiple studies should be conducted to test all approaches, and then meta-analyses of the studies might help to understand how much of the relationship between social support and depression can be explained by each approach.

In this paper, I examine the two main approaches to influence of social support on health: the stress-buffering approach (e.g., change in the appraisal of stressful events, boost in coping performance) and the behavioral change approach (health improvement through health-promoting behaviors: choosing a healthy diet and exercising) (Cohen, 1988; Lakey &

Cohen, 2000). First of all, I want to replicate result of previous studies (Brown et al., 1986;

Grav, Hellzèn, Romild, & Stordal, 2012; George, Blazer, Hughes & Fowler, 1989; Wang,

Cai, Qian, & Peng, 2014) that shown significant negative correlation between social support and depression.

H1. Social support is negatively related to depression (figure 1).

Social support Depression

Figure 1. Effect of social support on depression

Stress-buffering approach DEPRESSION AND SOCIAL SUPPORT 5

The stress-buffering approach is the most influential theoretical perspective on why social support is beneficial for one’s health (Lakey & Cohen, 2000). It states that social support decreases the negative influence of stressful life events on mental health by enhancing coping performance and appraising life events as less stressful (Cohen, 1988).

There is a lot of empirical support for the relationship between stress and depression

(Aneshensel & Frerichs, 1982; Aneshensel & Stone, 1982; Billings & Moos, 1984; Hammen,

2005; Lechin, Van Der Dijs & Benaim, 1996). Some studies (Husaini, Newbrough, Neff &

Moore, 1982; Raffaelli, 2013; Takizawa, 2006) have found not only the main effect of the stress on depression (as did studies mentioned above), but also a buffering effect of social support on the relationship between stress and depression: people with a high quality and quantity of social support were less susceptible to stressful events and, therefore, had lower prevalence of depressive disorders.

H2. Social support will moderate the relationship between stress and depression (figure

2).

Social support

Stress Depression

Figure 2. Moderation of the relationship between stress and depression by social support

Although the stress-buffering hypothesis is central in studies of the effects of social support (Lin, Dean & Ensel, 2013) and has some empirical evidence (Husaini, Newbrough,

Neff & Moore, 1982; Raffaelli, 2013; Takizawa, 2006), it could not be applied to all cases of mood disorders. The stress-buffering hypothesis assumes that stress is required for depression to develop whereas Lakey and Cohen (2000) stated that it is not always the case: sometimes negative thoughts are enough to provoke negative emotions. Therefore, if stress is not always required for the depression onset (depression may develop without any stressful events), DEPRESSION AND SOCIAL SUPPORT 6

stress-buffering approach could not be the sole explanation of social support being beneficial for mental health. Alternative rationalization of the relationship between social support and depression can be the behavioral change approach.

Behavioral change approach

In this approach social support is believed to stimulate behaviors beneficial for one’s health such as exercising and eating a healthy diet (Uchino, Cacioppo, & Kiecolt-Glaser,

1996). Therefore, negative effect of social support on depression is executed through diet and exercising. Behavioral change approach have never been tested empirically, however there are studies that showed significant relationships between the variables (social support – diet/physical activity and diet/physical activity – depression).

Researches (Aggarwal, Liao, Allegrante & Mosca, 2010; Kara, Caglar & Kilic, 2007) found that patients with low social support show poor adherence to the diet while people with high social support tend to stick to the diet. Tamers et al. (2011) demonstrated that people with higher social support had 14.3% higher physical activity and 4% higher fruit and vegetable consumption compared to participants with lower social support. Appelhans et al.

(2012) have shown that greater depression severity was associated with poorer diet quality whereas healthy diet (e.g., Mediterranean diet) correlates with lower levels of depression

(Sanchez-Villegas, Henriquez, Bes-Rastrollo & Doreste, 2006). Physical activity can reduce symptoms of depression (Dunn, Trivedi & O'Neal, 2001) and decrease the risk of subsequent depression (Strawbridge, Deleger, Roberts, & Kaplan, 2002).

To sum up, there is an empirical evidence that higher social support correlates with higher physical activity and better adherence to the diet (Aggarwal, Liao, Allegrante &

Mosca, 2010; Kara, Caglar & Kilic, 2007; Tamers et al., 2011), and quality diet and physical activity are negatively correlated with depression (Appelhans et al., 2012; Dunn, Trivedi & DEPRESSION AND SOCIAL SUPPORT 7

O'Neal, 2001; Sanchez-Villegas, Henriquez, Bes-Rastrollo & Doreste, 2006; Strawbridge,

Deleger, Roberts, & Kaplan, 2002).

H3a. Diet will partially mediate the relationship between social support and depression

(figure 3).

Diet

Social support Depression

Figure 3. Mediation of the relationship between social support and depression by diet

H3b. Physical activity will partially mediate the relationship between social support and

depression (figure 4).

Exercise

Social support Depression

Figure 4. Mediation of the relationship between social support and depression by

exercise

So, in this paper I will focus on diet and physical activity as possible mediators of the relationship between social support and depression. I would like to acknowledge that there are other possible mediators of this relationship have been suggested, such as self-esteem, positive emotions, companionship, low conflict, intimacy, alcohol abuse and drug use

(Cohen, 1988; Harlow, Newcomb & Bentler, 1986; House, Landis, & Umberson, 1988;

Lakey & Cohen, 2000). But I have good reasons not to use them in the particular study. Low self-worth and self-esteem, as well as depressed mood, are symptoms of the Major

Depressive Disorder itself; therefore, it is not reasonable to use self-esteem or positive emotions as mediators of the social support – depression relationship (American Psychiatric

Association, 2013). In their work Lakey and Cohen (2000) mention that social support could DEPRESSION AND SOCIAL SUPPORT 8

not be distinguished from intimacy, companionship and low conflict, they are highly overlapping; some of them are even included into social support questionnaires (Gottlieb &

Bergen, 2010; Weiss, 1974). Alcohol abuse and drug use were excluded from the study due to the constraints of the ethical review board.

Depression is a debilitating disorder with high prevalence in the population (Sadock,

Sadock & Ruiz, 2017), and it is crucial for researchers and mental health professionals to understand what can be done to prevent and cure depression. Besides medication and psychotherapy, there is an important extra-therapeutic condition of successful depression treatment - social support (Linville, 1987; Park, Cuijpers, van Straten & Reynolds, 2014).

The problem with social support is that studies consistently show that it is negatively correlated with depression but no one knows why. Current literature on social support and depression relationships is largely focused on the stress-buffering approach (Lakey & Cohen,

2000), it is the only approach that has an empirical evidence but as I mentioned previously it could not be sole explanation of social support being beneficial for mental health. Previous empirical studies (Husaini, Newbrough, Neff & Moore, 1982; Raffaelli, 2013; Takizawa,

2006) on the stress-buffering approach have never included any other approaches into their study. Therefore, I am not only conducting the study on the behavioral change approach that was not empirically tested before, but I also do it simultaneously with the stress-buffering hypothesis that had never been investigated together with any other approach. Utilizing two approaches in one study hopefully will help to achieve better understanding why social support is so important for mental health.

Method

Ethics statement. DEPRESSION AND SOCIAL SUPPORT 9

The present study has been ethically approved by the Tilburg University Ethics Review

Board. Participants were provided written informed consent prior to participating in the study.

Sample

Participants were the United Kingdom citizens who completed the survey at the

Prolific website for a monetary reward. Completion of the survey on average took 10 minutes. After removing subjects with unengaged responses (23 participants failed attention check, 1 participant did not give consent to participate, 5 participants gave contradictory or nonsensical responses to the International Physical Activity Questionnaire), I retained 205 filled questionnaires (59,3% female, Mage= 36,2, SD =12,4) out of 234 initially collected responses. Demographic characteristics of the sample are reflected in Table 1.

Table 1. Demographic characteristics. Male Female Other Variable n (%) n (%) n (%) Age (years) 18-24 22 (26,8) 13 (10,7) 0 (0) 25-39 46 (56,1) 56 (46,3) 2 (100) 40-59 13 (15,9) 40 (33,1) 0 (0) 60-85 1 (1,2) 12 (9,9) 0 (0) Marital status Married 20 (24,4) 60 (49,6) 2 (100) Divorced 2 (2,4) 4 (3,3) 0 (0) Separated 0 (0) 2 (1,7) 0 (0) Never married 60 (73,2) 55 (45,5) 0 (0)

Procedure

The current study was created with help of the Qualtrics; the survey was distributed online at the Prolific website. To estimate the sample size required for current study I roughly calculated average correlation coefficient from previous studies on social support and depression (Ayers et al., 2009; Greenglass, Fiksenbaum & Eaton, 2006; Holahan, C. K., &

Holahan, C. J, 1987; Leach, Frank, Bouman, & Farmer, 1994; Li et al., 2009; Lin & Hung,

2007; Maeda et al., 2013; Mutkins, Brown & Thorsteinsson, 2011; Raffaelli et al., 2013;

Sarason, I. G., Sarason, B. R., Shearin, & Pierce, 1987; Vyavaharkar et al., 2011; Wang, Cai, DEPRESSION AND SOCIAL SUPPORT 10

Qian & Peng, 2014; Wells, Booth-Jones & Jacobsen, 2009). The calculated average correlation coefficient was r=-0.28. Using G* Power 3 tool (Faul, Erdfelder, Lang &

Buchner, 2007) I estimated that current study requires at least 158 participants with power of

0.95.

Podsakoff, MacKenzie, Lee and Podsakoff (2003) suggested that common method bias is the main source of measurement errors. The major concern with common method bias is that when the same method is used to measure multiple constructs (approach that was used in the current study), result that researcher receives might be method specific and not construct-specific (Schaller, Patil & Malhotra, 2015). To reduce common method variance in the current study I incorporated following steps suggested by the authors (Podsakoff,

MacKenzie, Lee & Podsakoff, 2003): (1) The items were presented to the participants in a random order to avoid the response pattern that can influence results; (2) Respondents were assured that all the data will be completely anonymous and available only to the researcher;

(3) I chose scales with simple items without complicated syntax; also almost all of the selected scales have different answer options (e.g., Likert scale; yes/no answers; open questions).

Measures

Depression. To measure level of depression I used the Center for Epidemiologic

Studies Depression Scale (Radloff, 1977). It is a well-established 20-item self-report questionnaire (e.g., I felt that everything I did was an effort) with a 4-point Likert-type scale

(Rarely or none of the time/less than one day = 0; Most or all of the time/ 5-7 days = 4;

Cronbach’s α = .94; all α’s presented were calculated for this particular sample) that measures participants’ experiences during the past week. Although, Radloff (1977) originally created the measure for general population, subsequent studies (Santor et al., 1995;

Weissman et al., 1977) have proved the Center for Epidemiologic Studies Depression Scale DEPRESSION AND SOCIAL SUPPORT 11

can also be a relevant tool for a clinical sample. The instrument was examined by exploratory factor analysis: KMO measures of the sampling adequacy =.94, which is well above required minimum of .6; according to Kaiser's criterion and Cattell's scree plot, factor solution for the scale involves one factor, total variance explained by the factor is 48.8%, which is close to the acceptable 50% of total explained variable.

Social support. Two types of social support can be distinguished: perceived and received social support (Table 7). Perceived social support is a recipient’s subjective perception that providers will offer help when recipient needs it; whereas received social support is a particular supportive behavior offered by providers when recipient needs it

(within a certain time). Therefore, received social support is an actual behavior of the support provider that happened in the past, whereas perceived social support is the belief of the support recipient that he/she will receive help if needed. Apparently, the difference between definite behavior of support provider and recipient’s belief about availability of the support plays a big role in affecting well-being, as perceived social support had proved to have positive effects on mental health whereas results for received social support were less consistent (Barrera, 1986; Bolger, Zuckerman & Kessler, 2000; Halbesleben & Ronald

Buckley, 2006; Lakey & Cronin, 2008; Uchino, 2009). However, as effects of received support on one’s health has strong theoretical base (Haber, Cohen, Lucas & Baltes, 2007;

Norris & Kaniasty, 1996; Nurullah, 2012; Wethington & Kessler, 1986) and some studies

(Finch et al., 1997; Halbesleben & Ronald Buckley, 2006; Schwarzer, 1991) did find empirical support for it, I decided to include measures of both perceived and received social support into the study.

The Multidimensional Scale of Perceived Social Support (Zimet, Dahlem, Zimet &

Farley, 1988) was used to measure perceived social support. It is a 12-item self-report questionnaire (e.g., There is a special person who is around when I am in need) with a 7-point DEPRESSION AND SOCIAL SUPPORT 12

Likert-type scale (1= very strongly disagree, 7 =very strongly agree; Cronbach’s α = .94).

The scale evaluates perceptions of support from 3 sources: family (Cronbach’s α = .92), friends, (Cronbach’s α = .95), and a significant other (Cronbach’s α = .97), therefore it can be subdivided into 3 subscale with 4 items in each. The instrument was examined by exploratory factor analysis: KMO measures of the sampling adequacy =.89, which is well above required minimum of .6; according to Kaiser's criterion and Cattell's scree plot, factor solution for the scale involves three factors, total variance explained by these factors is 88.4%, which is higher than the acceptable 50% of total explained variable.

To measure received social support I used the Inventory of Socially Supportive

Behaviors short version (Barrera & Baca, 1990). It is a 19-item self-report questionnaire (e.g.,

During the past four weeks, how often did other people gave or loaned you over $25?) with a

5-point Likert-type scale (1= Not at all, 5= About every day; Cronbach’s α = .92). The instrument was examined by exploratory factor analysis: KMO measures of the sampling adequacy =.92, which is well above required minimum of .6; according to Kaiser's criterion and Cattell's scree plot, factor solution for the scale involves one factor, total variance explained by the factor is 57.4%, which is higher than 50% of total explained variable.

Stress. The social readjustment rating scale (Holmes & Rahe, 1967) was used to measure stress levels of the participants. It is a 43-item self-report questionnaire with dichotomous (two-point) questions (yes or no). Participants report whether certain life events occurred to them over the past year. Each of the items (specific life events) is assigned a value (e.g., divorce = 73 points, pregnancy = 40 points, vacation = 13 points) selected to reflect the relative amount of stress the item provokes. Stress is cumulative, therefore to assess stress levels, sum of all life events for the past year is calculated.

Diet. I used the Questionnaire of Mediterranean diet adherence (Martínez-González et al., 2002; Martínez-González et al., 2012) to measure quality of the diet. Originally it was a DEPRESSION AND SOCIAL SUPPORT 13

14-item self-report questionnaire (e.g., How many servings of red meat, hamburger, or meat products (ham, sausage, etc.) do you consume per day?), however due to ethics limitations the question on wine consumption was eliminated resulting in 13 items. For each item participant can be assigned one point; final score on Mediterranean diet adherence is sum of all items: the higher the final score – the higher adherence to the Mediterranean diet, which indicates a better quality of the diet.

Physical activity. The short version of the International Physical Activity

Questionnaire (Craig et al., 2003) was used to measure level of physical activity. It is a 7- item self-report questionnaire (e.g., During the last 7 days, on how many days did you do moderate physical activities?) with open-ended questions. The scale evaluates three types of activity: walking, moderate-intensity activities and vigorous-intensity activities. A score for each type of activity is calculated separately (each type of activity has its own formula); total physical activity score is the sum of results for walking, moderate-intensity activities and vigorous-intensity activities. The exact formulas for calculating scores and description of the scale can be found in the guidelines for data processing and analysis of the International

Physical Activity Questionnaire (IPAQ Research Committee, 2005).

Control variables. I collected data on participants’ age, gender (male, female, other), marital status (married, widowed, divorced, separated, never married) and economic strain.

There is a large pool of studies on how these demographic factors are affecting mental well- being: (1) females have higher rates of depressive disorders than males do (Angst et al., 2002;

Culbertson, 1997; Kuehner, 2003; Ustün, 2000); (2) married people have lower levels of distress and depression (Pearlin & Johnson, 1977; Ross, 1995; Simon, 2002); (3) low socioeconomic status is connected to higher prevalence of depression (Gilman, Kawachi,

Fitzmaurice & Buka, 2003; Lorant et al., 2007; Murata et al., 2008); (4) evidence for DEPRESSION AND SOCIAL SUPPORT 14

differences in depression levels between age groups is mixed (Jorm, 2000; Mirowsky, 1996;

Mirowsky & Ross, 1992; Stordal et al., 2001).

Economic strain was measured by the Economic strain measure (Miech & Shanahan,

2000): a 3-item self-report questionnaire (During the past 12 months, how often did it happen that you had trouble paying the bills?) with a 4-point Likert-type scale (1= never, 4=very often; Cronbach’s α = .77). The instrument was examined by exploratory factor analysis:

KMO measures of the sampling adequacy =.63, which is above required minimum of .6; according to Kaiser's criterion and Cattell's scree plot, factor solution for the scale involves one factor, total variance explained by the factor is 69.3%, which is higher than 50% of total explained variable.

I also inserted two additional questions into the survey (“Were you previously diagnosed with depression?” and “Do you take any medications for depression treatment at the moment?”) to conduct exploratory analysis on whether participants with clinically diagnosed depression differ from the participants who was not previously diagnosed.

Data analysis

I investigated effects of social support and stress on level of depression in regression analysis in 3 steps: (1) evaluation of control variables effects on depression, (2) assessing main effects of social support and stress on depression, (3) examination of interaction effect between social support and stress on depression. First step is required to ensure that results of the regression are not caused by differences in age or socioeconomic status.

To test mediation hypothesis I used simple mediation analysis Process Macro model 4

(Hayes, 2012; Hayes, 2013). The analyses involves four steps: (1) assessing main effect of social support on a diet/physical activity (path a); (2) measuring main effects of diet/physical activity (path b) and social support (path c’) on depression; (3) exanimating main effect of DEPRESSION AND SOCIAL SUPPORT 15

social support on depression (path c); (4) computing the difference between path c and path

c'. Confidence intervals for the variables was created through bootstrapping.

Results

Correlations

Table 2 reports means, standard deviations and correlation between variables. Depression

was correlated with stress (r = .28, p < .01) and perceived social support (r = -.49, p < .01).

No significant correlation were found between depression and received social support, diet,

and physical activity. Therefore, received social support was excluded from the regression

analysis, although all three variables still were included into the mediation analyses Process

Macro model 4 due to less strict requirements to significance of relationships between

variables. Regarding the control variables, economic strain was found to be significantly

correlated with depression (r = .38, p < .01), stress (r = .23, p < .01), and perceived social

support (r = -.34, p < .01); age were correlated with depression (r = -.18, p < .01), stress (r = -

.20, p < .01), received social support(r = -.15, p < .01), and diet (r = .29, p < .01).

Consequently, both economic strain and age was included into the regression analyses as

control variables; age was also included as the control variable in the mediation analyses for

diet.

Table 2. Means, standard deviations, and correlations among study variables M (SD) 1 2 3 4 5 6 7 1. Depression 18,9 (13) 2. Perceived 5 (1,4) -,49** social support 3. Received social 41,6 (14,8) -,11 ,49** support 4. Stress 137 (92) ,28** ,03 ,13 5. Diet 5,2 (2,1) -,13 ,11 -,00 -,03 6. Physical 2562 ,03 -,10 -,02 -,00 -,19** activity (2849) 7. Economic 4,9 (2,3) ,38** -,34** -,13 ,23** ,04 ,03 strain 8. Age 36,2 (12,4) -,18** ,05 -,15* -,20** ,29** ,04 -,02 *p < .05. **p < .01**

DEPRESSION AND SOCIAL SUPPORT 16

Hypothesis testing

Hypothesis 1 stated that social support is negatively related to depression. As shown in Table

2, perceived social support found to be negatively related to depression (r = -.49, p < .01), whereas correlation between received social support and depression was not significant.

Therefore, hypothesis 1 is partially confirmed.

Hypothesis 2 stated that social support will moderate the relationship between stress and depression. Table 3 contains results of the regression analysis that was conducted to test the hypothesis. First step showed significant effects of economic strain (β= .38, p < .001) and age

(β= -.17, p < .01) on depression. In the second step, I found main effects of perceived social support (β= -.43, p < .001) and stress (β= .23, p < .001) on depression. Third step showed that interaction effect was not significant. Hence, hypothesis 2 was not supported.

Table 3. Results of regression analyses. Predictor B SE B β t p Step 1 Economic strain ,38 ,06 ,38 5,91 ,000 Age -,17 ,06 -,17 -2,75 ,007 Step 2 Economic strain ,18 ,06 ,18 2,91 ,004 Age -,11 ,06 -,11 -1,97 ,050 Perceived social -,43 ,06 -,43 -7,19 ,000 support Stress ,23 ,06 ,226 3,81 ,000 Step 3 Economic strain ,18 ,06 ,18 2,97 ,003 Age -,10 ,06 -,10 -1,70 ,091 Perceived social -,43 ,06 -,43 -7,14 ,000 support Stress ,23 ,06 ,23 3,86 ,000 Perceived social ,09 ,06 ,09 1,52 ,131 support×Stress

Hypothesis 3 stated that diet (a) and physical activity (b) will partially mediate the relationship between social support and depression. To test these hypotheses, I used

Mediation analysis Process Macro model 4 with number of bootstrap samples = 5000 and confidence interval of 95%. As I mentioned previously, age was included as the control variable in the analyses for diet. Mediation analysis showed that neither perceived nor DEPRESSION AND SOCIAL SUPPORT 17

received social support were significant predictors of diet and physical activity; and both

mediators were not significant predictors of depression. Subsequently, hypothesis 3a and 3b

were not supported.

Exploratory analysis

Based on the two additional questions I included into the survey (“Were you previously

diagnosed with depression?” and “Do you take any medications for depression treatment at

the moment?”) I created three groups: (1) participants who were previously diagnosed with

depression and do take medication for it at the moment (yes/yes); (2) participants who were

previously diagnosed with depression and do not take medication for it at the moment

(yes/no); and (3) participants who were not previously diagnosed with depression and do not

take medication for it at the moment (no/no). First group consisted of 45 participants, second

group included 42 participants and third group contained 117 participants. One respondent

indicated that she was not previously diagnosed with depression but does take medication for

depression at the moment (no/yes). As people without diagnosis could not legally access the

medication, this response was not included into the analysis. Demographic characteristics of

the groups are reflected in Table 4.

Table 4. Demographic characteristics of the yes/yes group, yes/no group and no/no group. yes/yes yes/no no/no Variable n (%) n (%) n (%) Gender Male 14 (31,1) 14 (33,3) 54 (46,2) Female 30 (66,7) 27 (64,3) 63 (53,8) Other 1 (2,2) 1 (2,4) 0 (0) Age (years) 18-24 5 (11,1) 4 (9,5) 26 (22,2) 25-39 28 (62,2) 22 (52,4) 54 (46,2) 40-59 11 (24,4) 13 (31) 28 (23,9) 60-85 1 (2,2) 3 (7,1) 9 (7,7) Marital status Married 13 (28,9) 20 (47,6) 46 (39,3) Divorced 2 (4,4) 0 (0) 4 (3,4) Separated 0 (0) 1 (2,4) 1 (0,9) Never married 30 (66,7) 21 (50) 66 (56,4)

DEPRESSION AND SOCIAL SUPPORT 18

Mean and standard deviations of study variables could be found in the Table 5. First

group (yes/yes) has the highest scores on depression MD=29.5, SD= 11.2, stress MS=180,

SD=105 and economic strain MES=6.3, SD=2.4, and the lowest scores on perceived and

received social support MPSS=4.56, SD=1.44, MRSS=38.8, SD=12.1. Second group (yes/no)

has middle scores for these five variables: MD=20.5, SD= 13.6, MS=149.5, SD=91, MES=5.1,

SD=2.4, MPSS=4.97, SD=1.28 and MRSS=42.1, SD=13.7. Third group has the lowest scores on

depression MD=14.5, SD= 10.9, stress MS=117, SD=81 and economic strain MES=4.3,

SD=1.9, and the highest scores on perceived and received social support MPSS=5.25,

SD=1.35, MRSS=42.6, SD=16. Cut-off score for the depression scale (the Center for

Epidemiologic Studies Depression Scale) is 16, suggesting that scores above 16 signal

presence of common depression symptoms and participant should be further evaluated.

Table 5. Mean and standard deviations of study variables in the yes/yes, yes/no and no/no groups. yes/yes yes/no no/no M (SD) M (SD) M (SD) Depression 29,5 (11,2) 20,5 (13,6) 14,4 (11) Perceived social 4,6 (1,4) 5,0 (1,3) 5,2 (1,3) support Received social 38,8 (12,1) 42,1 (13, 7) 42,6 (16) support Stress 180 (105) 149,5 (91) 116,6 Diet 5,2 (2,3) 5,7 (2,0) 5,1 (2,0) Physical activity 2605 (3203) 2289 (1771) 2663,7 (3033) Economic strain 6,3 (2,4) 5,1 (2,4) 4,3 (1,9) Age 35,3 (9,7) 38,0 (11,7) 35,8 (13,5)

It becomes apparent that there is an explicit pattern from group one (yes/yes) to group

three (no/no): levels of depression, stress and economic strain are decreasing (see figure 5)

and levels of both perceived and received social support are increasing (see figure 6). No

clear pattern was found among groups on the diet quality or physical activity. DEPRESSION AND SOCIAL SUPPORT 19

1.00 0.80 0.60 depression 0.40 stress 0.20 0.00 economic strain -0.20 -0.40 -0.60 GROUP 1 GROUP 2 GROUP 3

Figure 5. Standardized means of depression, stress and economic strain among three groups.

0.30 0.20 0.10

0.00 perceived social -0.10 support -0.20 received social -0.30 support -0.40 -0.50 -0.60 GROUP 1 GROUP 2 GROUP 3

Figure 6. Standardized means of perceived and received social support among three groups.

I recreated the regression analysis (was previously used to test hypothesis 2) and the mediation analysis Process Macro model 4 (was previously used to test hypotheses 3a and

3b) for each group.

Regression analysis showed no significant interaction effect for yes/yes group (see

Table 6, higher panel in figure 7) and yes/no group (see Table 7, middle panel in figure 7); DEPRESSION AND SOCIAL SUPPORT 20

however interaction effect between perceived social support and stress was significant for the no/no group (β= -.17, p < .05; see Table 8, lower panel in figure 7).

Table 6. Results of regression analyses for group yes/yes Predictor B SE B β t p Step 1 Economic strain ,11 ,12 ,14 ,91 ,367 Age ,20 ,17 ,18 1,22 ,227 Step 2 Economic strain ,02 ,12 ,03 ,20 ,846 Age ,23 ,16 ,20 1,39 ,172 Perceived social -,20 ,12 -,24 -1,56 ,126 support Stress ,25 ,11 ,33 2,27 ,028 Step 3 Economic strain ,03 ,12 ,03 ,21 ,835 Age ,21 ,17 ,19 1,26 ,214 Perceived social -,18 ,14 -,22 -1,30 ,201 support Stress ,24 ,12 ,32 2,04 ,048 Perceived social -,03 ,11 -,04 -,26 ,794 support×Stress

Table 7. Results of regression analyses for group yes/no Predictor B SE B β t p Step 1 Economic strain ,15 ,14 ,15 1,06 ,295 Age -,48 ,16 -,43 -3,02 ,004 Step 2 Economic strain ,10 ,15 ,11 ,69 ,495 Age -,44 ,16 -,40 -2,69 ,011 Perceived social -,19 ,17 -,17 -1,15 ,259 support Stress ,04 ,16 ,04 ,24 ,811 Step 3 Economic strain ,11 ,15 ,11 ,73 ,468 Age -,43 ,16 -,39 -2,64 ,012 Perceived social -,22 ,17 -,20 -1,31 ,198 support Stress ,06 ,16 ,05 ,35 ,726 Perceived social ,20 ,19 ,15 1,06 ,295 support×Stress

DEPRESSION AND SOCIAL SUPPORT 21

Table 8. Results of regression analyses for group no/no Predictor B SE B β t p Step 1 Economic strain ,32 ,08 ,32 3,78 ,000 Age -,17 ,07 -,22 -2,56 ,012 Step 2 Economic strain ,13 ,07 ,13 1,75 ,084 Age -,10 ,05 -,13 -1,83 ,070 Perceived social -,51 ,06 -,60 -8,17 ,000 support Stress ,17 ,07 ,17 2,41 ,017 Step 3 Economic strain ,13 ,07 ,13 1,88 ,066 Age -,09 ,05 -,12 -1,66 ,099 Perceived social -,45 ,07 -,52 -6,37 ,000 support Stress ,12 ,07 ,12 1,66 ,099 Perceived social ,16 ,08 ,17 2,10 ,038 support×Stress

Figure 7 provides visual aid for the regression analysis results. Although the interaction effects in the yes/yes and yes/no groups were not significant, they were still included into the figure 7 to compare with group no/no.

For the mediation analysis I used the same Process Macro model 4 with number of bootstrap samples = 5000 and confidence interval of 95%. Age was included as the control variable in the analyses for the diet. The mediation analysis showed no significant mediation of the relationship between social support and depression by either diet or physical activity for any of the groups.

DEPRESSION AND SOCIAL SUPPORT 22

GROUP YES/YES 5

4.5

4 Low Perceived social support 3.5

3 High Perceived

2.5 social support DEPRESSION

2

1.5

1 LOW STRESS HIGH STRESS GROUP YES/NO 5

4.5

4 Low Perceived 3.5 social support

3 High Perceived social support

2.5 DEPRESSION 2

1.5

1 LOW STRESS HIGH STRESS

5 GROUP NO/NO

4.5 Low Perceived 4 social support 3.5

3 High Perceived social support 2.5

2 DEPRESSION

1.5

1 LOW STRESS HIGH STRESS

Figure 7. Interaction effect of stress and perceived social support on depression for all groups DEPRESSION AND SOCIAL SUPPORT 23

Discussion

In the current research, I attempted to discover underlying reasons of why social support is beneficial for mental health. I examined two theoretical approaches on how social support can influence one’s health: the stress-buffering approach (enhancing coping performance and appraising life events as less stressful) and the behavioral change approach

(health improvement through health-promoting behaviors: choosing a healthy diet and exercising).

Before testing selected approaches, I needed to confirm that social support has indeed the expected effect on depression. I discovered that perceived social support had significant negative correlation with depression. This finding converges well with the prior research reporting perceived social support to be associated with improved physical and mental health

(Bolger, Zuckerman & Kessler, 2000; Lakey & Cronin, 2008; Uchino, 2009). Unfortunately,

I did not find significant correlation between received social support and depression as some studies did (Finch et al., 1997; Halbesleben & Ronald Buckley, 2006; Schwarzer, 1991). I think future research on social support should focus on developing better understanding of the discrepancies in the effects of perceived and received social support.

The first theoretical approach I examined was the stress-buffering approach. It is the most influential perspective on why social support is beneficial for one’s health (Lakey &

Cohen, 2000) and the only theoretical concept that actually has an empirical evidence

(Husaini, Newbrough, Neff & Moore, 1982; Raffaelli, 2013; Takizawa, 2006). However, I did not find support for the stress-buffering approach: social support failed to moderate relationship between stress and depression in the sample. I think the exploratory analysis results can help in understanding why I did not find evidence for the model.

In the exploratory analysis I divided the sample into the three groups: participants in the first two groups were previously diagnosed with depression (yes/yes and yes/no groups) DEPRESSION AND SOCIAL SUPPORT 24

and participants in the third one were not (no/no). Results of the exploratory analysis suggested that social support mediated relationship between stress and depression in the third group (no/no) but failed to do the same in the first (yes/yes) and the second (yes/no) groups.

Therefore, results of the moderation analysis in the full sample was not significant because the nonsignificant results in the first and the second groups outweighed the significant results in the third group. It happened due to the atypically high percentage of clinically depressed people in the sample. First and second group combined are 42,4% of the sample. And as these groups consisted of participants who were diagnosed with depression, the lifetime prevalence of depression (amount of people who were diagnosed with depression at some point in their lives) in the full sample equals the amount of participants in first and second groups and is 42,4%. The general population usually falls in the range between 5 and 17%

(Sadock, Sadock & Ruiz, 2017). I think it is safe to say that the lifetime prevalence in the current sample is much higher (almost two and a half times higher than the upper limit of the range) than in general population.

Consequently, there is a possibility that if a sample composition in the previous studies was closer to a general population composition (5 to 17 percent of the lifetime depression prevalence) then social support appeared to moderate relationship between stress and depression in a full sample, whereas in reality significant moderation was driven only by a portion of the sample without clinical diagnosis. I could not confirm my suggestion as previous empirical studies (Husaini, Newbrough, Neff & Moore, 1982; Raffaelli, 2013;

Takizawa, 2006) did not report amount of clinically depressed people in their samples but I think it can be an interesting research question for a future empirical study.

The last thing I would like to discuss regarding the exploratory analysis is the reasoning behind the ability of social support to only buffer stress for the participants without clinically diagnosed depression (and not for clinically depressed participants). Statistically DEPRESSION AND SOCIAL SUPPORT 25

wise, it is very simple: participants with the highest depression levels had the highest stress levels and lowest levels of social support (see Table 5, Figure 5 and Figure 6), and it is no wonder that low levels of social support could not buffer high levels of stress. Nevertheless, a lot of questions still remain unanswered: why do clinically depressed participants report lower levels of social support and higher levels of stress? Do they have a very stressful life and almost no one around to support them? Or are there other possible explanations?

I think the main reason why clinically depressed participants reported lower levels of social support and higher levels of stress is an inaccurate estimation of the environment due to cognitive symptoms of depression. This skewed perception of reality is incorporated in a

Beck’s cognitive triad (Beck et al., 1987) that represents three main elements of the cognition prevalent in depression, including negative views about oneself, negative views about the future and negative views about the world. Negative views about the world make people to interpret life events to be more negative and stressful than they actually are. Negative views about oneself lead people to an excessive reassurance seeking: they need constant confirmation that they are loveable, worthy and valuable. And when their environment could not meet their needs, they feel they lack social support when in reality they have sufficient support (Oppenheimer et al., 2012).

There also can be another explanation of participants reporting lower levels of social support: participants previously diagnosed with depression might indeed have smaller support system. Coyne’s (1976) offered the interaction theory of depression where he suggested that people with depression often make their environment feel guilty and this provokes irritation and even aggression that people surrounding person with depression could not freely express due to social norms. Instead, they offer nongenuane reassurance and support. With time, depressed person realizes discrepancies between reassurance he/she was provided and actual behavior of support provider and realizes that he/she was rejected. As people experience DEPRESSION AND SOCIAL SUPPORT 26

more rejections, they start to isolate themselves from people, resulting in decrease in social connections and social support.

Reader should keep in mind that all results reported here were obtained in the cross- sectional study with only one point of assessment. At that moment participants with clinically diagnosed depression might have skewed interpretation of their environment or they might indeed have less supportive people around them. Therefore, results of the moderation analysis should not lead to hasty conclusions about the ineffectiveness of social support in buffering stressful events for participants with depression. Although I did not manage to find any longitudinal studies testing the stress buffering approach, I did find a few longitudinal studies

(Glass, De Leon, Bassuk, & Berkman, 2006; Kamen et al., 2011) demonstrating that social support does actually decrease levels of depression with time and is crucial aspect of recovery for people with depression. It is a valuable finding signaling that cross-sectional study should not be used for the studies on the stress-buffering approach in the clinical sample (people with clinically diagnosed mental disorder).

All in all, I consider the stress-buffering approach to be a great model explaining relationship between social support and depression, it is the only model I found some empirical evidence for. Nevertheless, I think there is a lot of things researchers can implement in their studies to improve an understanding of the model. Firstly, future researchers studying stress-buffering approach can include similar questions (e.g., Were you previously diagnosed with depression?) into their studies and then explicitly report amount of the participants diagnosed with depression in their overall sample. It will help to approve or reject my proposition that in the cross-sectional studies the significant moderation of the stress - depression relationship by social support is driven only by portion of the sample without clinical depression. Secondly and most importantly, future researches can conduct longitudinal studies to test stress-buffering approach, which will help to (1) establish causal DEPRESSION AND SOCIAL SUPPORT 27

relationship between stress, social support and depression for both clinically depressed participants and for participants without disorder and (2) avoid report biases due to cognitive symptoms of depression for clinically depressed part of the sample.

Second theoretical approach that I examined was the behavioral change approach. As

I mentioned previously it has never been tested before but studies found significant relationships between the variables: social support – diet/physical activity (Aggarwal, Liao,

Allegrante & Mosca, 2010; Kara, Caglar & Kilic, 2007; Tamers et al., 2011) and diet/physical activity – depression (Appelhans et al., 2012; Dunn, Trivedi & O'Neal, 2001;

Sanchez-Villegas, Henriquez, Bes-Rastrollo & Doreste, 2006; Strawbridge, Deleger, Roberts,

& Kaplan, 2002). However, I did not only fail to find any confirmation for behavioral change approach model, I also did not find any significant relationships between variables themselves. I consider my choice of measures for the diet quality and physical activity to play a big role in the results I received.

I used the Questionnaire of Mediterranean diet adherence (Martínez-González et al.,

2002; Martínez-González et al., 2012) to measure quality of the diet. Previous studies

(Psaltopoulou et al., 2013; Sanchez-Villegas, Henriquez, Bes-Rastrollo & Doreste, 2006;

Skarupski, 2013) have found negative effect of the adherence to Mediterranean diet on depression that I did not find in the current research. Multiple reasons could have caused that:

(1) I removed one item from the Questionnaire of Mediterranean diet adherence, it could have influenced reliability and validity of the scale. (2) It can be result of a publication bias: these studies were published and seen only because they found significant results, and there could be studies that did not find this result and was not published. (3) The Questionnaire of

Mediterranean diet adherence might not be the best scale to assess the quality of a diet. It does asses nutrients that were linked with depression (omega-3 fatty acids, olive oil - connected to lower levels of depression; trans fatty acids [commercial bakery products] – can DEPRESSION AND SOCIAL SUPPORT 28

contribute to higher depression risk), but there are more nutritional factors that can influence mental health like salt, sugar, vitamins, etc. (Appelhans et al., 2012; Sanchez-Villegas &

Martínez-González, 2013). Therefore, I think it would be great to use broader scales like the

Food Frequency Questionnaire (Willett et al., 1985) to assess the quality of a diet. I also received comment from the participant that he was a vegetarian, and a question on a meat preferences (Do you preferentially consume chicken, turkey, or rabbit meat instead of veal, pork, hamburger, or sausage?) is not applicable to him; I assume that less specific and more broad questionnaire would solve this problem as well.

To assess levels of physical activity I used the short version of the International

Physical Activity Questionnaire (Craig et al., 2003). Previous studies (Hallgren et al., 2016;

Hoffmann et al., 2016; Josefsson, Lindwall & Archer, 2014; Knapen, Vancampfort, Moriën

& Marchal, 2015) have shown that physical activity is beneficial for mental health; some of the systematic review studies (Schuch at al., 2016) were even adjusted for publication bias and still found significant effect of the physical activity on mental health. Therefore, I would not consider publication bias to be a problem for a physical activity measure. However, another bias did affect the results of the study – the social desirability bias. It can be defined as the response tendency to give socially desirable responses instead of declaring true attitudes or behaviors (Fisher, 1993). Adams et al. (2005) showed that people are susceptible to the social desirability bias when reporting their physical activity: participants tend to overestimate the physical exercise duration in their reports compared to objective measures of an energy expenditure (doubly labeled water). I can see similar patterns in the current study.

According to physical activity statistics by British Health foundation (Townsen,

Wickramasinghe, Williams, Bhatnagar, Rayner, 2015) on average women spend 5.4 hour/week and men 6.5 hours/week engaging in any physical activity (including walking, exercise, household duties). In the current research, woman on average spend 2.15 DEPRESSION AND SOCIAL SUPPORT 29

hours/week doing vigorous physical activities, 2.9 hours/week for moderate physical activities and 3.9 hours/week walking, resulting in 8.95 hours/week; man on average spend

2.6 hours/week doing vigorous physical activities, 2.85 hours/week for moderate physical activities and 3.85 hours/week walking, resulting in 9.3 hours/week. Those results are 43% higher than the UK national average for males and 66% higher than the UK national average for females. Based on this comparison I can make a conclusion that people responded in socially desirable manner rather than declared their true behaviors. Therefore, data that I obtained is not very reliable.

It raises the question: if people fail to truthfully report their physical activity levels then how previous studies (Hallgren et al., 2016; Hoffmann et al., 2016; Josefsson, Lindwall

& Archer, 2014; Knapen, Vancampfort, Moriën & Marchal, 2015) managed to find the positive effects of physical activity on mental health? The answer is simple: most of them are randomized control studies: all training sessions were supervised, and researchers had accurate information about levels of physical activity of each participant.

Ultimately, even though I did not find any support for behavioral change approach I still believe it is a great theoretical model that can potentially be one of the explanation of the relationship between social support and depression. I do not think it should be rejected based only on the current study due to the measures’ limitations that I mentioned previously. For the future research on behavioral change approach I would advise to conduct randomized control studies that will provide precise information on participants’ nutrition and physical activity.

Limitations

Besides the limitations that I previously mentioned (cross-sectional design, measures used to assess diet quality and physical activity), there also are couple limitations that should be acknowledged. DEPRESSION AND SOCIAL SUPPORT 30

First limitation is sample collection at Prolific for a monetary reward. I think it is not fully representable of the general population of the UK; and it can also alter results of the study. For example, I found economic strain to be stronger connected to depression than overall stress in the sample (see Table 2) which could be connected to the fact that participants spend their free time to earn additional income. Second limitation is self-report data. Self – reported data is susceptible to multiple biases: selective memory bias, social desirability bias, question order bias, acquiescence bias, etc. As it is mentioned earlier in the discussion, I consider the current study to be affected by social desirability bias and would advise to include the Social Desirability Scale or implement another approach to assess physical activity in the successive research.

Conclusion

Although the current study did not fully confirmed any explanation of social support effectiveness, it revealed implicit pattern in the stress-buffering approach and provided a clear path for future research on the subject.

DEPRESSION AND SOCIAL SUPPORT 31

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Appendix

Table 7. Types of social support.

Authors Types of support Definitions Example

Norris & Kaniasty, Perceived support Recipient’s Knowing family is

1996 subjective perception always there to help

that providers will you Wethington & offer help when he or Kessler, 1986 she needs it

Received support Particular supportive Friends taking care

behavior offered by of your dog while

providers when you are traveling

recipient needs it

(within a certain

time)

Gottlieb & Bergen, Emotional (esteem) Provision of Saying that one is

2010 support empathy, doing great in sport

encouragement, during tennis game Schwarzer, Knoll & concern, love, trust, Rieckmann, 2004 acceptance,

reassurance or caring

Tangible support Provision of material Providing place to

goods, services or stay for someone

tangible aid

Informational support Provision of Giving information DEPRESSION AND SOCIAL SUPPORT 45

suggestions, advice, on how to file tax

information, papers

guidance or feedback

to someone.

Belonging Provision with Saying that one is a

(companionship) intimate interactions, great team member

support feelings of closeness

and belonging

The Center for Epidemiologic Studies Depression Scale (CES-D)

1. I was bothered by things that usually don’t bother me

2. I did not feel like eating; my appetite was poor

3. I felt that I could not shake off the blues even with help from my family or friends

4. I felt that I was just as good as other people

5. I had trouble keeping my mind on what I was doing

6. I felt depressed

7. I felt that everything I did was an effort

8. I felt hopeful about the future

9. I thought my life had been a failure

10. I felt fearful DEPRESSION AND SOCIAL SUPPORT 46

11. My sleep was restless

12. I was happy

13. I talked less than usual

14. I felt lonely

15. People were unfriendly

16. I enjoyed life

17. I had crying spells

18. I felt sad

19. I felt that people disliked me

20. I could not get “going”

Multidimensional Scale of Perceived Social Support (MSPSS)

1. There is a special person who is around when I am in need.

2. There is a special person with whom I can share my joys and sorrows.

3. My family really tries to help me.

4. I get the emotional help and support I need from my family.

5. I have a special person who is a real source of comfort to me.

6. My friends really try to help me. DEPRESSION AND SOCIAL SUPPORT 47

7. I can count on my friends when things go wrong.

8. I can talk about my problems with my family.

9. I have friends with whom I can share my joys and sorrows.

10. There is a special person in my life who cares about my feelings.

11. My family is willing to help me make decisions.

12. I can talk about my problems with my friends.

The Inventory of Socially Supportive Behaviors short version (ISSB – short version)

1. Gave you some information on how to do something.

2. Helped you understand why you didn’t do something well.

3. Suggested some action you should take.

4. Gave you feedback on how you were doing without saying it was good or bad.

5. Made it clear what was expected of you.

6. Told you what he/she did in a situation that was similar to yours.

7. Told you that he/she feels close to you.

8. Let you know that he/she will always be around if you need help.

9. Told you that you are OK just the way you are.

10. Expressed interest and concern in your well-being. DEPRESSION AND SOCIAL SUPPORT 48

11. Comforted you by showing you some physical affection.

12. Told you that he/she would keep the things you talk about private.

13. Agreed that what you wanted to do was the right thing.

14. Did some activity together to help you get your mind off things.

15. Gave or loaned you over $25.

16. Provided you with a place to stay.

17. Loaned you or gave you something (a physical object) that you needed.

18. Pitched in to help you do something that needed to get done.

19. Went with you to someone who could take action.

The social readjustment rating scale.

1. Death of spouse

2. Divorce

3. Marital Separation

4. Jail Term

5. Death of close family member

6. Personal injury or illness

7. Marriage DEPRESSION AND SOCIAL SUPPORT 49

8. Fired at work

9. Marital reconciliation

10. Retirement

11. Change in health of family member

12. Pregnancy

13. Sex difficulties

14. Gain of a new family member

15. Business readjustment

16. Change in financial state

17. Death of a close friend

18. Change to a different line of work

19. Change in number of arguments with spouse

20. Mortgage over $20,000

21. Foreclosure of mortgage or loan

22. Change in responsibilities at work

23. Son or daughter leaving home

24. Trouble with in-laws DEPRESSION AND SOCIAL SUPPORT 50

25. Outstanding personal achievement

26. Spouse begins or stop work

27. Begin or end school

28. Change in living conditions

29. Revisions of personal habits

30. Trouble with boss

31. Change in work hours or conditions

32. Change in residence

33. Change in schools

34. Change in recreations

35. Change in church activities

36. Change in social activities

37. Mortgage or loan less than $20,000

38. Change in sleeping habits

39. Change in number of family get-togethers

40. Change in eating habits

41. Vacation DEPRESSION AND SOCIAL SUPPORT 51

42. Christmas approaching

43. Minor violation of the law

Questionnaire of Mediterranean diet adherence.

1. Do you use olive oil as main culinary fat?

2. How much olive oil do you consume in a given day (including oil used for frying, salads, out-of-house meals, etc.)?

3. How many vegetable servings do you consume per day? (1 serving : 200 g [consider side dishes as half a serving])

4. How many fruit units (including natural fruit juices) do you consume per day?

5. How many servings of red meat, hamburger, or meat products (ham, sausage, etc.) do you consume per day? (1 serving: 100–150 g)

6. How many servings of butter, margarine, or cream do you consume per day? (1 serving: 12 g)

7. How many sweet or carbonated beverages do you drink per day?

8. How much wine do you drink per week?

9. How many servings of legumes do you consume per week? (1 serving : 150 g)

10. How many servings of fish or shellfish do you consume per week? (1 serving 100–150 g of fish or 4–5 units or 200 g of shellfish) DEPRESSION AND SOCIAL SUPPORT 52

11. How many times per week do you consume commercial sweets or pastries (not homemade), such as cakes, cookies, biscuits, or custard?

12. How many servings of nuts (including peanuts) do you consume per week?

13. Do you preferentially consume chicken, turkey, or rabbit meat instead of veal, pork, hamburger, or sausage?

14. How many times per week do you consume vegetables, pasta, rice, or other dishes seasoned with sofrito (sauce made with tomato and onion, leek, or garlic and simmered with olive oil)?

International Physical Activity Questionnaire.

1. During the last 7 days, on how many days did you do vigorous physical activities?

2. How much time did you usually spend doing vigorous physical activities on one of those days?

3. During the last 7 days, on how many days did you do moderate physical activities?

4. How much time did you usually spend doing moderate physical activities on one of those days?

5. During the last 7 days, on how many days did you walk for at least 10 minutes at a time?

6. How much time did you usually spend walking on one of those days?

7. During the last 7 days, how much time did you usually spend sitting on a weekday?

The Economic Strain Measure DEPRESSION AND SOCIAL SUPPORT 53

1. During the past 12 months, how often did it happen that you had trouble paying the bills?

2. During the past 12 months, how often did it happen that you did not have enough money to pay for medical care?

3. During the past 12 months, how often did it happen that you did not have enough money to buy food, clothes, or other things your household needed?