Emotion and Mental Health –
Associations, Assessments, and Clinical Implications
Dissertation
submitted in partial fulfillment of the requirements for the degree of
Doctor rerum naturalium (Dr. rer. nat.)
August, 2019
Christina Totzeck
Faculty of Psychology
Ruhr-Universität Bochum
Printed with permission of the Faculty of Psychology,
Ruhr-Universität Bochum
First reviewer: Prof. Dr. Jürgen Margraf, Ruhr-Universität Bochum
Second reviewer: Prof. Dr. Stefan G. Hofmann, Boston University
Date of the thesis defense: October 17th, 2019
To the most wonderful Mom
Hallelujah
You were an angel in the shape of my mum
You got to see the person I have become
Spread your wings and I know
That when God took you back he said, "Hallelujah
You're home"
- Ed Sheeran -
Preface
Abstract
Emotion research, especially in the context of clinical psychology, is essential in order to promote the understanding of the complex interplay of emotions and mental health. The present thesis sets out to gain more insight into this association by addressing five specific aspects:
Emotion induction, habitual emotion regulation in particular clinical populations as well as its changes through cognitive behavioral therapy (CBT), and furthermore the effects of positive interventions on mental health including the role of positive mental health. To address these objectives, five research studies have been conducted. The results of Study 1 showed that the three targeted emotions happiness, sadness, and fear as well as a neutral state could be selectively induced in a German sample (N = 120). The findings of Study 2 revealed an association of affective styles with psychopathology in a large clinical outpatient sample (N =
917). In Study 3, changes of affective styles throughout exposure-based therapy were found in patients suffering from panic disorder, agoraphobia and specific phobia (N = 101). The results of Study 4 showed short- and long-term effects of a positive intervention on negative and positive mental health factors in German university students (N = 55), who significantly improved when compared to a matched control group (N = 55). Finally, Study 5 found positive mental health to be a strong predictor of treatment outcome in an anxiety disordered population
(N = 130) receiving exposure-based therapy. The results of the five studies are discussed in the broader context of emotion research and translated into clinical implications. Future research perspectives are suggested.
III Preface
Statement
I hereby declare that I have prepared this submitted thesis independently and without the help of others. I assure that I have not used any other sources or aids than those indicated. Those parts that have been taken literally or correspondingly from published or unpublished texts or other sources have been cited completely and correctly. This thesis has not been submitted before at this or any other institution. Furthermore, I assure that the electronic version submitted is completely consistent with the written version.
This thesis comprises five empirical studies; the reports of these studies have been submitted, are currently under review for publication or have already been published in peer-reviewed journals. The references below provide the relevant publication information:
Totzeck, C., Zhang, X.C., Pflug, V., Teismann, T., Margraf, J., & Adolph, D. Old movies vs. new movies – Development and validation of an emotional film set. Manuscript submitted for publication.
Totzeck, C., Teismann, T., Hofmann, S.G., Pflug, V., von Brachel, R., Zhang, X.C. & Margraf, J. (2018). Affective styles in mood and anxiety disorders – Clinical validation of the “Affective Style Questionnaire” (ASQ). Journal of Affective Disorders, 238, 392-398.
Totzeck, C., Teismann, T., Hofmann, S.G., von Brachel, R., Zhang, X.C., Wannemüller, A., Pflug, V., & Margraf, J. (in press). Affective styles in panic disorder and specific phobia: Changes through cognitive behavior therapy and prediction of remission. Behavior Therapy.
Totzeck, C., Teismann, T., Hofmann, S.G., von Brachel, R., Pflug, V., Wannemüller, A., & Margraf, J. May you be happy – Loving-kindness meditation promotes mental health in university students. Manuscript submitted for publication.
Teismann, T., Brailovskaia, J., Totzeck, C., Wannemüller, A., & Margraf, J. (2018). Predictors of remission from panic disorder, agoraphobia and specific phobia in outpatients receiving exposure therapy: The importance of positive mental health. Behaviour Research and Therapy, 108, 40–44.
IV Preface
Own contributions to these publications:
Publication 1: I was involved in the study conception and design as well as in the data acquisition. I analyzed and interpreted the data. I wrote the draft of the manuscript and incorporated the co-authors’ comments into the final version of the report.
Publication 2: I was responsible for the conception and design as well as the data analysis and interpretation. In addition, I wrote the draft of the manuscript and revised it with assistance of the co-authors’ feedback.
Publication 3: This was a secondary analysis of a study on genetic factors in exposure treatments. I was responsible for the conception and design as well as the data analysis and interpretation. I drafted and revised the manuscript. All co-authors provided essential conceptual, statistical, and editorial support and gave important intellectual feedback to all drafts of the manuscript.
Publication 4: I was responsible for the study design, data acquisition, analysis and interpretation. I translated the treatment manual, and I conducted the majority of treatment sessions. I was involved in data acquisition, I wrote the draft of the manuscript and incorporated the co-authors’ comments into the final report.
Publication 5: I contributed to the study design and provided feedback to the manuscript.
Date:
Signature:
V Preface
Acknowledgments
First of all, I would like to express my deepest gratitude to my supervisors and mentors Prof. Dr. Jurgen̈ Margraf and Prof. Dr. Stefan Hofmann for their enthusiastic encouragement, trust, and outstanding support. Without your excellent guidance and committed help, this dissertation would not have been possible. I would like to thank my wonderful colleagues and co-authors, especially PD Dr. Tobias Teismann, Dr. XiaoChi Zhang, and my good friend Verena Pflug for their valuable support, advice, and honesty. In addition, I would like to thank Helen Copeland-Vollrath: kiitos kaikesta, olet upea! My gratitude is extended to the Konrad-Adenauer Foundation: I feel honored and appreciative for receiving a PhD scholarship, and I am deeply grateful for the financial and individual support, for an amazing seminar program, and for unforgettable experiences and memories. I would also like to thank my dear brothers, PD Dr. Matthias Totzeck, Dr. Andreas Totzeck, and Dr. Markus Totzeck, and my brother in law, Dr. Björn Weiß, for their awesome support and encouragement throughout my study, and Jan Ellebrecht for his love and patience with me.
Special thanks go to my office colleagues Ike, Sam, and Franzi: Thank you for making every day bueno.
Zuguterletzt möchte ich meinem größten Vorbild danken: Meinem geliebten Vater, Dr. Baldur Totzeck. Danke für deine Unterstützung, für deinen unerschütterlichen Glauben an uns, dass du immer die richtigen Worte findest und diesen Weg überhaupt erst ermöglicht hast.
VI Contents
Table of Contents
Preface Abstract III
Statement IV
Acknowledgements VI
Contents Table of Contents VII
Figure Directory IX
List of Abbreviations X
CHAPTER 1 General Introduction 1
Definition of Emotion, Affect, and Mood 2
The Concept of Basic Emotion 5
Neural Substrates of Emotions 9
Emotion Regulation 10
Assessing Inter-Individual Differences in Emotion Regulation 12
Neurobiology of Emotion Regulation 14
Emotions and Psychopathology 16
Effects of Treatment 17
Positive Mental Health 19
Aims of this Thesis 20
CHAPTER 2 Study 1 Old movies vs. new movies – Development and validation of a new emotional film set 23
CHAPTER 3 Study 2 Affective styles in mood and anxiety disorders – Clinical validation of the “Affective Style Questionnaire” (ASQ) 46
VII Contents
CHAPTER 4 Study 3 Affective styles in panic disorder and specific phobia – Changes through cognitive behavior therapy and prediction of remission 53
CHAPTER 5 Study 4 May you be happy – Loving-kindness meditation promotes mental health in university students 64
CHAPTER 6 Study 5 Predictors of remission from panic disorder, agoraphobia and specific phobia in outpatients receiving exposure therapy: The importance of positive mental health 86
CHAPTER 7 General Discussion 91
Summary of the Main Findings 92
Answers to the Research Questions 94
Conclusions and Clinical Implications 100
Final Evaluation 103
References 104
Appendix
Curriculum Vitae 117
List of Publications 118
Conference Presentations 120
VIII Contents
Figure Directory
Figure 1. A schematic representation of circumplex model of affect. p. 4
Figure 2. A consensual process model of emotion generation. p. 6
Figure 3. Plutchik’s theoretical model of basic emotions. p. 7
Figure 4. Similarities and differences of basic emotions concepts. p. 7
Figure 5. Emotion regulation model. p. 11
Figure 6. The heuristic model of neural processing of emotion regulation. p. 14
Figure 7. The Cognitive-Neurobiological Information Processing Model of Fear and Anxiety. p. 15
Figure 8. Affective styles in different populations. p. 101
Figure 9. A hierarchical conception of affect regulation. p. 102
IX Contents
Abbreviations
ACC = anterior cingulate cortex. aMCC = anterior midcingulate cortex.
ASQ = Affective Style Questionnaire.
CBT = cognitive behavioral therapy. dlPFC = dorsolateral prefrontal cortex.
ERQ = Emotion Regulation Questionnaire.
LKM = Loving-kindness Meditation.
PFC = prefrontal cortex.
PMH-scale = Positive Mental Health-scale.
SMA = supplementary motor area.
STG = superior temporal gyrus. vlPFC = ventrolateral prefrontal cortex.
X CHAPTER 1
General Introduction Emotions are the music of our soul.
Emotions define our everyday lives; they shape how we feel, what we think and how we behave. They contribute to important decisions, such as who we fall in love with, what we want to work on, or what we prefer to avoid. Every human being is affected by emotions, as we all feel several different emotional states, daily. This applies not only to beautiful and positive emotions, but also, in particular, to negative ones. We all know the feeling of grief when we lose somebody we love, or the feeling of being afraid of something strange or unknown.
Although all these different emotions are part of being a human being, they can also give rise to psychological problems. When their intensity, frequency, or duration leads to suffering, or when they can no longer be managed and controlled, help is needed. Patients seek psychotherapeutic counseling because they feel sad, anxious or angry. Or they might no longer feel anything. The primary goal of psychotherapy, therefore, is to make the patient feel better.
In order to do so, we have to understand the exact mechanisms of emotions themselves, the process how we handle these emotions as well as what we need to change to optimize treatment.
In other words: We have to fully translate emotion research into clinical implications.
The present thesis sets out to build a bridge between emotion research and clinical implications by addressing the following research questions: How can we reliably induce emotional states in order to examine their impact on cognitive, social, and behavioral functioning (Study 1)? How do people suffering from mental disorders handle their emotions
(Study 2)? How do these strategies change through psychotherapeutic treatment (Study 3)?
What happens to mental health when we directly address positive emotions (Study 4)? And finally, how are positive factors of mental health associated with therapy outcome (Study 5)?
The introduction section of this thesis covers an overview of the most important definitions and differentiations between emotions, affects, and moods, followed by a brief outline of current findings on basic emotions, including neurobiological information.
1 CHAPTER 1
Afterwards, the most important findings of emotion regulation as well as its association with psychopathology are presented. Subsequently, the effects of psychotherapeutic treatment on emotional dysregulation and the effects of positive intervention on mental health are elaborated.
Finally, the role of positive mental health is presented. The introduction concludes with an overview of the main goals of the five empirical studies conducted as part of this thesis.
Definition of Emotion, Affect, and Mood The beginning of wisdom is the definition of terms. -Socrates-
Although the current definitions of the terms emotion, affect, and mood in psychological research will be presented below, this does not mean that these constructs should and can be considered completely independently as they are all part of affective phenomena (Ekkekakis,
2012). The definitions intend to promote clarity in the differences and similarities of the constructs.
The most frequently examined construct is emotion with its variety of associated definitions which express the complexity of emotions. However, there is mutual consensus that an emotion comprises not only physiological changes (e.g. on the neuroendocrine level through the release of hormones or reactions of the automatic nervous system), but also expressive, cognitive, motivational, and affective components (Lochner 2016). Whereas the expressive component refers to the expression of the emotion, such as nonverbal expression through mimic or gestural moves, the cognitive component includes all individual evaluations, the motivational component implies all action tendencies evoked, and the affective component refers to an individual’s experience of the emotion (Lischetzke & Eid, 2011; Lochner, 2016;
Scherer, 2005).
The definition of emotion by Hofmann (2016) comprises all contributing factors: “An emotion is (1) a multidimensional experience that is (2) characterized by different levels of
2 CHAPTER 1 arousal and degrees of pleasure-displeasure; (3) associated with subjective experiences, somatic sensations, and motivational tendencies; (4) colored by contextual and cultural factors; and that
(5) can be regulated to some degree through intra- and interpersonal processes” (Hofmann,
2016, p. 2).
The most difficult differentiation of the terms is the distinction between emotion and affect, because these two constructs are closely related (Hofmann, 2016). Philosophers have searched for definitions over centuries (Bradley & Lang, 2000). In psychology, the debate is on-going with respect to the question how to differentiate affect from emotion; most authors use the term affect as an umbrella term for emotion and mood (Frijda, 1994; Lochner, 2016).
However, some authors suggest that, at its core, affect refers to the subjective experience of an emotional state, which can be either positive or negative as well as arousing or calming (Barrett,
Mesquita, Ochsner, & Gross, 2007; Hofmann, 2016). This core affect is described as a state accessible to consciousness as a single and simple feeling, such as feeling either good or bad, tired or energized (Yik, Russell, & Steiger, 2011). This differentiation of valence and arousal has been labelled as “circumplex model of affect” (Russell, 1980; Colibazzi et al., 2010), which is presented in Figure 1. Its dimensions have also been referred to as core affect (Hofmann,
2016; Russell & Barrett, 1999; Yik, Russell, & Steiger, 2011). It is one of the most widely empirically supported dimensional models of affect (Russell & Barrett, 1999; Yik, Russell, &
Steiger, 2011), because of its robustness, utility, and parsimony (Hofmann, 2016). Although the model cannot account for all individual differences among affects, it provides an applicable way to describe the complexity of emotional experiences (Hofmann, 2016; Yik, Russell, &
Steiger, 2011).
Core affect is part of emotions and moods, but unlike them, it is seen to be accessible continuously: “Whenever asked, people can tell you how they feel” (Yik, Russell, & Steiger,
2011, p. 705). Thereby, the concept of core affect captures simple feelings that are present
3 CHAPTER 1 continuously, yet not always salient. “Core Affect is not equivalent to ‘mood’ or ‘emotion’, but is a key ingredient in both” (Yik, Russell, & Steiger, 2011, p. 723). Therefore, affect can be seen as an umbrella term for psychological states that involve valuating a relatively quick
“good-for-me/bad-for-me discrimination” (Gross, 2015; Scherer, 1984).
In the first study of this thesis, both emotions as well as core affect are assessed using different measures (see Study 1, Chapter 2). Furthermore, the differentiation between emotion and affect also plays an important role when examining the different patterns of regulation (see
Study 2 and Study 3, Chapters 3-4).
ACTIVATION
tense alert nervous excited stressed elated upset happy
UNPLEASANT PLEASANT sad contented depressed serene bored relaxed fatigue calm
DEACTIVATION
Figure 1. A schematic representation of circumplex model of affect. The horizontal axis represents the valence dimension (pleasant–unpleasant), and the vertical axis represents the arousal dimension. Modified from Colibazzi et al. (2010).
Although the terms emotion and mood are also often used interchangeably (Batson,
Shaw, & Oleson, 1992), they can be separated as they describe distinct phenomena (Lochner,
2016). Emotions mostly have a stimulus event; they are rather intense but short in duration, and they have behavioral implications (Scherer, 2005). When compared to these properties, moods differ from emotions as they contain global, undirected, and rather unconscious background sensations that are more stable than emotions (Lischetzke & Eid, 2011; Lochner, 2016). And
4 CHAPTER 1 finally, mood can be defined as “purely inner experience – an individual’s perception of his or her own inner state” (Lochner, 2016, p. 43).
In reference to the initial metaphor of emotions being the music of our soul in this introduction, affect would be like standing next to a booming base box and feeling the arousing bodily reaction to the vibration, whereas mood would be like a consistent background sound, such as elevator music that keeps playing without being constantly noticed. Emotion, on the other hand, would be like listening to a song that makes you sing and dance, feeling happy and excited.
The Concept of Basic Emotions Emotions are the captains of our lives, and we obey them without realizing it. -Vincent van Gogh-
Each palpitation or arousing feeling does not result in an emotion, because only our very individual evaluations based on our subjective individual experiences transform physical changes into an emotion. Van Gogh might have been correct in his view that we feel intense emotional experiences once in a while without having noticed their arising. Indeed, several previous studies investigated how emotions impact our cognitions, for example, our attention, memory, and decision-making, which we might not always be consciously aware of (Dolan
2002). However, we do not obey them as van Gogh assumed (Torre, 2011). Instead, we are rather capable of modulating our own emotions. As depicted in Figure 2, emotions arise whenever we evaluate a situation as offering important challenges or opportunities (Gross,
1998b; Tooby & Cosmides, 1990a, 1990b, 2008).
5 CHAPTER 1
Emotional Response Emotional Tendencies Emotional Cues - Behavioral Responses - Experiential - Physiological
Evaluation Modulation
Figure 2. A consensual process model of emotion generation. Modified from Gross (1998b).
We decide which stimuli to attend to and which to ignore. We, then, label what we feel and categorize the feeling in order to help our brain to react adequately. When we categorize something, we render it meaningful (Lindquist, Wager, Kober, Bliss-Moreau, & Barrett, 2012).
Although the concept of categorization dates back at least to a first-century Chinese encyclopedia (Fu, 2012), which identifies “like, dislike, joy, anger, sorrow and pleasure” as seven ‘feelings of men’, the categorization of basic emotions has been integrated in psychology research only since Paul Ekman’s studies (e.g. 1972, 1973). At first, his categorization of six basic emotions (happiness, sadness, fear, anger, disgust, and surprise) was proposed and often used in further emotion research. All of our other emotions are seen to build upon these basic emotions. For instance, jealousy originates from a combined feeling of anger and sadness, while admiration can be a type of happiness. However, Ekman’s categorization has often been criticized. Plutchik (1980), for instance, argued that eight instead of six basic emotions exist, which he grouped into four pairs of polar opposites (joy-sadness, anger-fear, trust-distrust, surprise-anticipation; see Figure 3). All other emotions are seen as different levels of arousal intensity of these basic emotions.
6 CHAPTER 1
optimism
aggressiveness love interest serenity
anticipation joy
annoyance acceptation vigilance ecstasy anger trust rage admiration contempt submission loathing terror disgust grief fear boredom amazement apprehension
sadness surprise
pensiveness distraction remorse awe
disapproval
Figure 3. Plutchik’s theoretical model of basic emotions. Modified from Plutchik (1980).
In 2011, Ekman and Cordaro (2011), Izard (2011), Levenson (2011), and Panksepp and
Watt (2011) outlined the latest instantiation of their theoretical models of basic emotions (Tracy
& Randles, 2011). Their models differ in the number and in some forms of basic emotions (see
Figure 4).
PANKSEPP EKMAN IZARD & LEVENSON & WATT CORDARO
Happiness Play Enjoyment Happiness Sadness Panic/Grief Sadness Sadness Fear Fear Fear Fear Anger Rage Anger Anger Disgust - Disgust Disgust Interest Seeking Interest? - Contempt? - - Contempt - Lust Love? - - Care Relief? Surprise
Figure 4. Similarities and differences of basic emotions concepts. Modified from Tracy and Randles (2011). Note: ? = Included in the authors’ model (by Tracy & Randles, 2011), but the author(s) suggested that clear-cut supporting evidence is not yet available.
7 CHAPTER 1
These theoretical models share the categorization of the four emotions, although label them differently: Happiness (or play or enjoyment), sadness (or grief), anger (or rage), and fear.
Using facial expression signals, Jack, Garrod, and Shyns (2014) also suggest exactly this distinction of four instead of six basic emotions: Happiness, sadness, anger/disgust and fear/surprise. Their results revealed that facial expressions of anger and disgust as well as fear and surprise were not as distinct as previously assumed (Jack, Garrod, & Shyns, 2014). Similar results were presented in a meta-analysis by Lench, Flores, and Bench (2011), who examined the extent to which discrete emotions elicit changes in cognition, judgment, behavior, and physiology. They included 687 studies using emotion elicitation methods to induce happiness, sadness, anger, and anxiety. In line with basic emotion theory, they found differences among these discrete emotions as well as correlated changes in behavior, experience, and physiology
(Lench, Flores, & Bench, 2011).
Although the discussion about categorization models continues, it is crucial to define fundamental categories to promote the investigation of emotions. In order to examine the exact mechanism of emotion and emotional processing, we rely on categorization. It enables us to make reasonable inferences about (a) what we perceive, (b) to predict what to do with it, and
(c) to communicate our experience to others (Lindquist et al., 2012). So besides the ongoing debate about how categorization works, the fact that it functions is not in question (Lindquist et al., 2012). The first study of this thesis adds on this aspect by developing and validating a new set of emotion induction film sequences that address the three main basic emotion categories (happiness, sadness, and fear) while assessing the previous six (happiness, sadness, fear, anger, disgust, and surprise) basic emotions (see Study 1, Chapter 2).
8 CHAPTER 1
Neural Substrates of Emotions The brain is not the mind. -David Brooks-
One way to underscore the concept of categorization is the examination of specific patterns of neural activation. Although it is impossible to predict or even understand emotions, affects, and moods only based on brain activation pattern, neural underpinnings are helpful in a further understanding of the exact mechanism of emotional experiences and furthermore in grasping the development of mental disorders. For instance, a meta-analysis by Fusar-Poli,
Placentino, Carletti and colleagues (2009) that included 105 functional Magnet Resonance
Imaging (fMRI) studies using emotional face processing showed that, at least with respect to the level of resolution of fMRI, there appear to be limbic and insular differences between the basic emotions. The following regions have been found to be relevant (adapted from Fusar-Poli et al., 2009):
1. Happy faces are associated with neural activation in the bilateral amygdala, left
fusiform gyrus and right anterior cingulate cortex.
2. Sad faces activate the right amygdala and the left lingual gyrus.
3. Angry faces are associated with increased neural response in the left insula and right
inferior occipital gyrus.
4. Fear is associated with activation in the bilateral amygdala and the fusiform and
medial frontal gyri.
5. Disgust is associated with neural activation in the insula bilaterally, right thalamus
and left fusiform gyrus.
Interestingly, the authors detected bilateral activation of the amygdala only when processing fearful and happy faces. Furthermore, they directly compared happy, fearful, and
9 CHAPTER 1 sad faces, which confirmed that amygdala sensitivity was greater during the fearful stimulus than in the other two conditions. Amygdala engagement during processing of fearful faces is therefore a strong and consistent finding in the available fMRI literature, which corresponds to previous findings showing a particularly important role of the amygdala in processing fear and anxiety (e.g., LeDoux, 2003).
Taken together the findings suggest that the processing of emotional faces is implemented by neural systems that are at least partially separable, although they are not represented by entirely distinct neural circuits (Fusar-Poli et al., 2009). When it comes to more general emotional processing above and beyond emotional faces, there are opposing findings:
A meta-analysis by Lindquist and colleagues (2012) which included fMRI studies on emotional processing in a more general way underscores the assumption that discrete emotion categories are constructed of more general brain networks not specific to those categories. Overall, a better understanding of emotional experiences can be promoted by a more complete knowledge of their accompanying neurology and physiology. Therefore, studies investigating which brain regions are activated during specific emotional experiences (e.g., Koenig & Mecklinger, 2008), and also which emotions are elicited by the stimulation of specific brain regions (e.g., Singer et al., 2008), will be helpful in the next stage of emotion research (Tracy & Randles, 2011).
The principal use of prudence or self-control is Emotion Regulation that it teaches us to be masters of our passions. -Descartes-
Just as we all differ in our taste of music, we differ in our minds’ and bodies’ creation of emotions. This relies to the speed and intensity of emotional reactions to similar threats and rewards and to the use of response strategies to these emotions (Dennis, 2007). As Gross
(1998b) defined, emotion regulation refers to “the processes by which individuals influence
10 CHAPTER 1 which emotions they have, when they have them, and how they experience and express these emotions” (Gross, 1998b, p. 275). These regulatory processes may be either automatic or controlled, they can be conscious or unconscious, and they have the goal to start, stop or otherwise modulate the trajectory of an emotion (Etkin, Büchel, & Gross, 2015; Gross, 1998b;
2015). Generally, we can regulate our own emotions (intrinsic/intrapersonal) or someone else’s emotions (extrinsic/interpersonal) (Gross & Jazaieri, 2014). Beside the fact that we typically try to decrease the experiential and/or behavioral aspects of negative emotions (Gross,
Richards, & John, 2006), we also down-regulate positive emotions to some extent (Gross,
2015). This, for example, happens when we try to avoid laughing at an inappropriate circumstance (Giuliani, McRae, & Gross, 2008), or when we try to look less happy about a positive message when a friend is feeling bad. Furthermore, we not only practice down- regulating but also up-regulating of positive emotions, as when we, for example, maintain enthusiasm in order to determine a thesis, or when we enhance joy and gratitude about a gift we do not really like. Gross (1998a, 1998b) categorized regulatory strategies as either antecedent-focused used to manipulate the input to the emotion generation system (see Figure
2) or alternately as response-focused when the output is manipulated. Figure 5 presents this emotion regulation model.
Situations Aspects Meanings Responses S1 S1x A1 M1 • B+ Emotional Response B • B Tendencies • B- S2x A1 A2 M1 • E+ S2 - Behavioral S2y A3 E • E - Experiential • E- S2z A4 M2 A5 - Physiological • P+ M3 P • P • P-
Situation Situation Attentional Cognitive Response Selection Modification Deployment Change Modulation
Antecedent-Focused Response-Focused Emotion Regulation Emotion Regulation
Figure 5. Emotion regulation model. Modified from Gross (1998b, 2015).
11 CHAPTER 1
According to Gross’ model, many situations (S2), although not all (S1), can be selected, modified (S2x-S2z), and selectively attended to (A1-A5). Using Cognitive Change refers to our selection out of the various possible meanings (M1-M3), and the attachment of this chosen meaning (M2) to the situation. It is this meaning (M2) that evokes emotional response tendencies, including behavioral, experiential, and physiological components. Once the emotional response tendencies have been evoked, response modulation is used to influence these tendencies (Gross, 1998b; 2015).
Two important aspects of this model have received particular empirical attention:
Cognitive reappraisal (as a part of Cognitive Change) and expressive suppression (Gross &
John, 2003; Ochsner, Bunge, Gross, & Gabrieli, 2002). Cognitive reappraisal as an antecedent- focus strategy serves to change the negative emotional impact before distress is fully activated.
Expressive suppression, on the other hand, as a response-focused strategy is used to avoid an ongoing negative emotion. The use of these two concrete emotion regulation strategies can be assessed with the “Emotion Regulation Questionnaire” (ERQ; Gross & John, 2003). Research using the ERQ has shown that antecedent-focused strategies are relatively effective, whereas response-focused strategies tend to paradoxically increase negative emotions (Gross, 1998a;
Aldao, Nolen-Hoeksema, & Schweizer, 2010).
Assessing Inter-Individual Differences We are all alike, on the inside. -Mark Twain- in Emotion Regulation
We all have our own specific habits in the use of the above-described strategies. Some people tolerate feeling sad or anxious, whereas others react to such emotions by immediately appraising them as intolerable and subsequently engage in maladaptive response-focused strategies (Gross & John, 2003). They try to suppress feeling sad or escape from an argument with a partner in order to suppress feeling angry. This broad range of individual responses to
12 CHAPTER 1 emotional stimuli is referred to as affective style (Davidson, 1998, 2000, 2002; Hofmann,
Sawyer, Fang, & Asnaani, 2012).
In order to promote the understanding of an adaptive versus maladaptive use of regulatory strategies, we need to gain more insight into affective styles, in particular of those people suffering from mental disorders. With the development of the “Affective Style
Questionnaire” (ASQ), Hofmann and Kashdan (2010) aimed to provide a tool to assess such inter-individual differences in the habitual use of emotion regulation strategies. Based on
Gross’ (1998b) process model of emotion regulation (see Figure 5), the ASQ distinguishes three main affective styles: concealing, adjusting, and tolerating (Hofmann et al., 2012). The concealing style includes suppression and other response-focused strategies aimed at concealing and avoiding emotions after they arise. Previous studies have shown that especially men tend to prefer to conceal emotions (Hofmann & Kashdan, 2010; Graser et al., 2012). The adjusting style involves the modulation of negative emotions by balancing and successfully readjusting emotional experiences and expressions as needed in a particular context. The tolerating style encompasses accepting and non-defensive responses to arousing emotional experiences as they exist in the present moment. The tolerating style, including acceptance strategies, allows tolerance of strong emotions and is more often used by women than men
(Hofmann & Kashdan, 2010; Graser et al., 2012). The results of previous validation studies provided evidence for the applicability of the ASQ within nonclinical populations (Hofmann &
Kashdan, 2010; Graser et al., 2012; Ito & Hofmann, 2014). However, there is still a lack of clinical data. The second study addresses this paucity (see Study 2, Chapter 3).
13 CHAPTER 1
Neurobiology of Emotion Regulation We are not thinking machines that feel; rather, we are feeling machines that think. -Antonio Damasio-
Besides the investigation of neural correlates of emotional experiences (see section
Neurobiology of emotions), previous studies have aimed to elucidate neurobiological processes that are involved in emotion regulation (e.g., Greening, Lee, & Mather, 2014). Kohn and colleagues (2014) published a meta-analysis examining the neural pathways involved in emotion regulation. In their conclusion, they present a heuristic model of neural processing of emotion regulation that relates to the modal model of emotion regulation by Gross (1998b; see
Figure 5). Briefly summarized, they propose that affective arousal is relayed via amygdala and basal ganglia to the anterior midcingulate cortex (aMCC), the ventrolateral prefrontal cortex
(vlPFC), and the anterior insula as well as supplementary motor area (SMA), the superior temporal gyrus (STG) and angular gyrus (see Figure 6.1). The vlPFC then initiates the appraisal and signals the need for regulation to the dorsolateral prefrontal cortex (dlPFC; see Figure 6.2).
Finally, the dlFPC processes the regulation itself and gives a feedforward signal (via the aMCC or directly) to angular gyrus, SMA, STG, amygdala and basal ganglia, which generate a
(regulated) emotional state (see Figure 6.3).
SMA SMA SMA dlPFC dlPFC dlPFC
aMCC aMCC aMCC angular gyrus angular gyrus angular gyrus
vlPFC/Insula STG vlPFC/Insula STG vlPFC/Insula STG Amygdala/ Amygdala/ Amygdala/ Basal ganglia Basal ganglia Basal ganglia
Figure 6.1 Figure 6.2 Figure 6.3
Figure 6. The heuristic model of neural processing of emotion regulation. Modified from Kohn et al. (2014). Note: aMCC = anterior midcingulate cortex, dlPFC = dorsolateral prefrontal cortex, SMA = supplementary motor area, STG = superior temporal gyrus, vlPFC = ventrolateral prefrontal cortex.
14 CHAPTER 1
Integrating previous findings, Hofmann, Ellard, and Siegle (2012) proposed their cognitive-neurobiological information processing model (see Figure 7).
Stimulus
Perception of Amygdala Early Potential Threat
Detection of Hippocampus Threat
Temporal Processing Selection of Insular Behavioral Coping Strategies Cortex Response
Emotion Autonomic PFC ACC Late Regulation Response
Psychological Biological Psychophysiological Level Level Level
Figure 7. The Cognitive-Neurobiological Information Processing Model of Fear and Anxiety. Modified from Hofmann, Ellard, & Siegle (2012). Note: PFC = prefrontal cortex, ACC = anterior cingulate cortex.
The model displays the interplay and relationship between different brain structures and the information processing stages on the psychological, biological, and psychophysiological levels. For instance, a pathological state, such as depression, appears to be associated with a decreased prefrontal function that then causes a decreased regulatory control. The patient has, therefore, less access to adaptive strategies to adequately regulate the depressive mood.
Excessive fear and abnormal anxiety, on the other hand, seem to involve preserved regulatory control. Here, learned beliefs regarding the appropriateness and use of avoidant coping strategies are activated. These strategies can then contribute to the maintenance of the maladaptive emotional states (Hofmann, Ellard, & Siegle, 2012). The authors understand anxious cognitions partially as decision points during the processing of a threatening stimulus.
15 CHAPTER 1
When the stimulus has been perceived and detected, these decision points activate the selection and use of an adequate coping strategy in order to regulate a fear response. The decision points are associated with an activation of brain structures such as the amygdala (see section
Neurobiology of emotions), which is followed by the hippocampus and the insular cortex, and afterwards the anterior cingulate and prefrontal cortices (Hofmann, Ellard, & Siegle, 2012).
Emotions and Psychopathology Conceal, don’t feel, don’t let it show. -Elsa in Disney’s Frozen-
Emotions, affects, and moods not only shape our everyday lives, they also determine the clinical picture of several mental disorders, such as major depression, bipolar disorder or anxiety disorder (Patel et al. 2015). These mental disorders are amongst the most common and most deleterious diseases facing society but are still far from being understood (Beddington et al. 2008). One reason is the complex interplay of emotions and mental health, which has not been fully investigated so far. Research has shown that deficits in the ability to regulate emotions seem to not only cultivate the experience of more intense and enduring maladaptive emotions, but also lead to a variety of psychological disorders (Campbell-Sills & Barlow, 2007;
Gross and Muñoz, 1995; Mennin, Heimberg, Turk, & Fresco, 2005; Putnam & Silk, 2005). In addition to mental disorders, such as affective or anxiety disorders, where the key component is either a disturbance in the person's mood or excessive fear, according to the Diagnostic and
Statistical Manual of Mental Disorders (DSM-5; APA, 2013), dysregulation has also been described in other mental disorders, such as borderline personality disorder (Linehan 1996a,
1996b; Levine, Marziali & Hood, 1997), bulimia nervosa (Sim & Zeman, 2004) or substance abuse (Kober, 2014).
With regard to depressive and anxiety disorders, a study by D’Avanzato, Joormann,
Siemer, and Gotlieb (2013) detected that patients suffering from depressive disorders assessed
16 CHAPTER 1 with the ERQ reported a less frequent use of reappraisal than patients suffering from anxiety disorders, who in turn showed more use of suppression. As described in the information processing model, this might partially be due to different prefrontal activation patterns in patients with mood and anxiety disorders (see also Davidson, 1998, 2000, 2002). However, less is known about the association of affective styles and mental disorders. So, is the strategy to conceal and not feel, a helpful way to regulate emotions or is concealing associated with psychopathology? What is the role of adjusting and tolerating when it comes to mental disorders? In the second study (Chapter 3), these questions were addressed by assessing the affective styles of a large outpatient sample suffering from affective and anxiety disorders.
Effects of Treatment May you be happy. May you be free from suffering. -Loving-kindness Meditation-
This part of the introduction of this thesis focuses on the research questions (a) what exactly happens to emotion regulation through psychotherapy, (b) whether patients’ habitual use of strategies change throughout treatment, and (c) if so, whether the remission from the specific disorder is associated with this change. This section concentrates on therapeutic effects on anxiety disorders that was the main goal of the third study (see Chapter 4).
So far, cognitive behavioral therapy (CBT) is empirically the best supported psychological treatment for anxiety disorders (e.g., Hofmann & Smits, 2008; Ruhmland &
Margraf, 2001a, 2001b, 2001c). Therefore, CBT appears to be strongly effective in helping patients overcome their anxiety. The main effect is based on reducing avoidance behavior, which contributes to extinction learning and, thereby regaining control over feeling anxious
(Craske, Treanor, Conway, Zbozinek, & Vervliet, 2014). But does CBT really change the patient’s habitual use of regulating anxiety and how? A patient suffering from spider phobia
17 CHAPTER 1 undergoing CBT could serve as an example: Which precise impact has this effective treatment on the regulatory processes? Does the patient learn to tolerate anxiety? Does the patient conceal less afterwards? Or does the patient learn a superior adjusting strategy when confronted with a spider? The prior goal of exposure exercises within CBT is the prevention of the manifestation of avoidant patterns (Abramowitz, Deacon, & Whiteside, 2011; Barlow et al., 2011; Craske,
Treanor, Conway, Zbozinek, & Vervliet, 2014), which allows patients to experience the entire range of emotional reactions. Affective styles should therefore be measurably influenced by treatment. Furthermore, CBT aims to decrease anxiety symptoms by preventing maladaptive concealing styles and by promoting more adaptive adjusting and tolerating styles (Ito &
Hofmann, 2014). However, these effects have not yet been empirically examined. Therefore, whether this indeed occurs in an anxiety-disordered population undergoing CBT was the main research question of the third study (see Chapter 4).
Psychotherapeutic interventions mostly focus on helping patients to overcome negative emotions. However, as described above, people also regulate positive emotions at least to some extent. Since previous research on how we savor or dampen our positive emotions is scarce, the understanding of associations between positive emotion regulation and mental health is still at its beginning (Quoidbach, Berry, Hansenne, & Mikolajczak, 2010). In the search of ways to strengthen positive emotions, traditional Buddhist exercises, for example, have found their way into clinical psychological research and treatment. Besides mindfulness-based interventions, which have been shown to be associated with decreased symptoms of anxiety and lower levels of depression and cortisol (Regehr, Glancy, & Pitts, 2013), positive forms of interventions, such as Loving-kindness meditation (LKM), have only recently been examined as a potential intervention for mental health.
Loving-kindness (or metta in Pali) describes a mental state of unconditional kind attitudes toward all beings. LKM contains the practice of mindfulness (Hofmann, Grossmann,
18 CHAPTER 1
& Hinton, 2011), and its core psychological operation is to generate one’s kind intentions toward certain targets. The silent repetition of phrases such as “may you be happy” or “may you be free from suffering” toward targets are the key component. Targets change gradually with practice, from easy to difficult; generally beginning with oneself, followed by loved ones, then neutral people, difficult individuals, and finally all beings. The practice of LKM exercises is believed not only to broaden attention, but also to enhance positive emotions, and lessen negative emotional states (Dalai Lama & Cutler, 1998; Hofmann, Grossmann, & Hinton, 2011).
So is it possible to up-regulate positive emotions through LKM treatment? And if so, what happens to mental health then? This was the main goal of the fourth study of this thesis, which is presented in Chapter 5.
Positive Mental Health Happiness is the highest form of health. -Dalai Lama-
The traditional understanding of mental health in psychology has been defined as the absence of psychopathology (Keyes, 2005), where an individual was seen as being either mentally ill or mentally healthy. More recently, research has developed a wider understanding of mental health focusing on positive factors (Keyes, Fredrickson & Park, 2012). The field of positive psychology addresses not only positive emotions but also positive characteristics of the individual: talents, abilities, values, and strengths of character (Peterson, 2006). Research has, therefore, acknowledged that positive mental health and psychopathology are not to be seen as opposite ends of a continuum but instead as correlated axes (Trompetter, Lamers,
Westerhof, Fledderus, & Bohlmeijer, 2017). Two dimensions of positive mental health have been described (Deci & Ryan, 2008): Hedonic and eudaimonic components. Whereas the hedonic component contains positive affect and life satisfaction, the eudaimonic component concentrates on human potential and optimal functioning (Schönfeld, Brailovskaia & Margraf,
19 CHAPTER 1
2017). Taking these two key components into account, positive mental health can be defined as the presence of subjective and psychological well-being (Keyes, 2005; Keyes, Shmotkin, &
Ryff, 2002).
The Positive Mental Health Scale (PMH-scale; Lukat, Margraf, Lutz, van der Veld, &
Becker, 2016) assesses these aspects of subjective and psychological well-being. Addressing not only the decrease of negative mental health factors but also considering the increase of positive mental health factors appears to be a new way of investigating treatment outcomes.
The fourth study of this thesis investigated the effects of LKM on negative mental health factors, such as depression, anxiety, and stress, but additionally aimed to examine the role of positive mental health prior to and after LKM intervention. Finally, the last study of this thesis examined whether positive mental health might also be predictive of symptom severity and remission from anxiety disorders in patients receiving exposure therapy. The fifth study is presented in Chapter 6.
Aims of this Thesis
The main goal of this thesis is the attempt to build a bridge between emotions and mental health by stretching an arc from emotion induction via emotion regulation to mental health.
Picking up on the questions from the introduction of this thesis, the following studies were conducted:
• How can we reliably induce emotional states in order to examine their impact on
cognitive, social, and behavioral functioning (Study 1)?
The aim of the first study was the development and validation of a new emotional film set that would provide an emotion induction method for the clinically most relevant emotions: happiness, sadness and fear. Overall, N = 120 German participants viewed previously validated and novel film clips and rated each film on multiple dimensions. After each film presentation,
20 CHAPTER 1 participants were asked to rate the intensity of the six basic emotions (happiness, sadness, fear, anger, disgust, and surprise) as well as the valence and intensity of the emotional arousal. In addition, participants were asked, whether the just rated emotional reaction would last after the termination of questionnaires. Further background information as well as the methods and results of this study are presented in Chapter 2.
• How do people suffering from mental disorders handle their emotions (Study 2)?
The second study aimed to investigate three aspects: The main goal was the validation of the ASQ within a large clinical sample (N = 917 treatment-seeking patients). We, further, examined possible differences of the three affective styles concealing, adjusting, and tolerating between patients suffering from affective versus anxiety disorders. Finally, we aimed at investigating associations of these three affective styles and anxiety, depression, and stress symptoms. The study procedures, data analysis, results, and implications are presented in
Chapter 3.
• How do these strategies change through psychotherapy (Study 3)?
Based on the findings of Study 2, we were interested to examine how CBT changes the three affective styles concealing, adjusting, and tolerating of patients undergoing treatment. The aims of this third study were, therefore, to investigate changes in affective styles of patients with panic disorder and specific phobia, as a result of undergoing CBT, and to identify a possible link between specific affective styles and remission from disorder. The sample consisted of N = 101 outpatients suffering from panic disorder, specific phobia, or agoraphobia who completed the ASQ before and after therapy, as well as at 6-month follow-up assessment.
Further information, the methods and results of this study are presented in Chapter 4.
• What happens to mental health when we directly address positive emotions (Study 4)?
The main goal of the fourth study was to examine the effects of LKM intervention on positive and negative mental health in university students. The sample (N = 110) consisted of
21 CHAPTER 1 university students in Germany. One half of them (N = 55) underwent LKM treatment. They were compared to a matched control group (N = 55) that did not receive treatment. All participants completed positive and negative mental health measures at baseline and at the one- year follow-up assessments. LKM completers additionally completed all measures prior to and after intervention. A detailed description of research background, as well as the study procedures, data analysis, results, and implications are presented in Chapter 5.
• And finally, how are positive factors of mental health associated with therapy outcome
(Study 5)?
This last study aimed at investigating whether positive mental health as assessed with the PMH-scale is predictive of symptom severity and remission from anxiety disorders in patients receiving exposure therapy. The sample (N=130) consisted of outpatients suffering from panic disorder, agoraphobia, or specific phobia who received exposure-based therapy. The patients completed the PMH-scale prior to and after therapy as well as at follow-up assessment six months after treatment termination. Further information, the methods and results of this study are presented in Chapter 6.
A summary and discussion of the results of the five studies as well as conclusions for future research are presented in Chapter 7.
22 CHAPTER 2
Study 1: Old movies vs. new movies: Development and validation of an emotion film set. Manuscript submitted for publication.
Cognition and Emotion Page 2 of 34
1 2 3 4 Old movies vs. new movies: Development and validation of an 5 6 7 emotional film set 8 9 10 Christina Totzeck a*, Xiao Chi Zhang a, Verena Pflug a, Tobias Teismann a, 11 12 Jürgen Margraf a, and Dirk Adolph a 13 14 15 aDepartment of Clinical Psychology and Psychotherapy, Ruhr University Bochum, 16 17 Bochum, Germany 18 For Peer Review Only 19 20 21 Christina Totzeck, Dept. of Clinical Psychology and Psychotherapy, Ruhr 22 23 University Bochum; Xiao Chi Zhang, Dept. of Clinical Psychology and Psychotherapy, 24 25 26 Ruhr University Bochum; Verena Pflug, Dept. of Clinical Child and Adolescent 27 28 Psychotherapy, Ruhr University Bochum; Tobias Teismann, Dept. of Clinical 29 30 Psychology and Psychotherapy, Ruhr University Bochum; Jürgen Margraf, Dept. of 31 32 33 Clinical Psychology and Psychotherapy, Ruhr University Bochum; Dirk Adolph, Dept. 34 35 of Clinical Psychology and Psychotherapy, Ruhr University Bochum. 36 37 This research did not receive specific grants from funding agencies in the public, 38 39 commercial, or not-for-profit sectors. 40 41 a 42 *Correspondence concerning this article should be addressed to Christina 43 44 Totzeck, Dept. of Psychology and Psychotherapy, Ruhr University Bochum, 45 46 Massenbergstrasse 11, 44787 Bochum, Germany. E-mail: [email protected] 47 48 49 50 51 52 53 54 55 56 57 58 59 60
URL: http://mc.manuscriptcentral.com/pcem Email: [email protected]
23 CHAPTER 2
Old movies vs. new movies: Development and validation of an emotional film set
The aim of the present study was the development and validation of a new emotional film set that would provide an emotion induction method for the three basic emotions: happiness, sadness and fear. At first, students were asked to name emotional films. The 20 most frequently mentioned films were selected and cut into film clips. The new film excerpts were compared to 12 previously validated emotional film sequences. Next, N = 120 German participants (age range 20-67 years) viewed the film clips in small group sessions and rated each film on multiple dimensions: After each film presentation, every participant was asked to rate the intensity of basic emotions (happiness, sadness, fear, anger, disgust, and surprise) as well as the valence and intensity of the emotional arousal using visual analogue scales (based on SAM; Bradley & Lang, 1994). In addition, the duration of emotional reactions was examined. The results showed that three target emotions happiness, sadness and fear as well as a neutral state could be selectively induced. They were effective with regard to several criteria such as emotional discreteness, arousal, positive and negative affect. Therefore, the effectiveness and validity of the new emotional and neutral film excerpts could be confirmed.
Keywords: emotion induction; film set; basic emotions; moods; SAM
24 CHAPTER 2
Introduction Emotions are the center of everyday lives. In order to examine the association of emotions and social, cognitive, and behavioral functioning, it is necessary to evoke emotional states under laboratory conditions. This creates a need for reliable methods for emotion induction
(Schaefer, Nils, Philippot, & Sanchez, 2010).
A variety of methods has been developed, validated and applied in research so far, for instance: music listening (Västfjäll, 2015), the Velten technique (Velten, 1968), respiratory feedback (Philippot, Chapelle, & Blairy, 2002), or autobiographical recollection (Schaefer &
Philippot, 2005). In addition, the presentation of emotional film clips (e.g. Gross & Levenson,
1995; Rottenberg, Ray, & Gross, 2007; Schaefer, Nils, Philippot, & Sanchez, 2010; Uhrig,
Trautmann, Baumgärnter, et al., 2016) has also established itself as a research method. Since the earliest beginning of psychological research on movies in the 1910s (Tan, 2018), film sequences have been used to examine several phenomena, such as sad mood induced smoking behavior (Fucito, & Juliano, 2009),subjective and autonomic responses in psychopaths
(Pham, Philippot, & Rime, 2000), affective reactions related to frontal brain-asymmetry
(Tomarken, Davidson, & Henriques, 1990), or the association of emotion and chocolate eating behavior (Macht, Roth, & Ellgring, 2002).
When compared to other emotion induction methods, the presentation of film clips has several advantages (Schaefer et al., 2010): First of all, the fact that probably everyone has watched a movie in the past makes the situation familiar and comfortable for participants.
Second, presenting a film is very easy to implement technically. Third, film sequences provide a multimodal set of stimuli, as they provide visual and acoustic information mostly combined with a story to follow. Fourth, film scenes provide a model of reality, without causing ethical and practical problems of real-life techniques. Finally, according to the results of several studies, the presentation of film sequences has been shown to provoke strong subjective and physiological changes (e.g., Frazier, Strauss, & Steinhauer, 2004; Gross, 1998;
25 CHAPTER 2
Palomba, Sarlo, Angrilli, Mini, & Stegagno, 2000). A meta-analysis by Westermann, Spies,
Stahl, and Hesse (1996) has even shown that the presentation of film clips was the strongest method to elicit positive and negative emotional states in viewers.
Previous studies have demonstrated that films have the capacity to induce distinct target emotions like fear (Bosse, Gerritsen, de Man, & Stam, 2014), sadness (Kuijsters, Redi, de Ruyter, & Heynderickx, 2016) or happiness (Fredrickson & Branigan, 2005). However, several important aspects have rarely been taken into account: The development of most film databases relied exclusively on college students as participants. This is reasonable as students are often easy to recruit for participation in research studies. However, findings are obviously limited in their generalizability. Jenkins and Andrewes (2012) addressed this issue by developing a new standardized film database using a sample with a wider age range (18–88 years). In their study, all animated movies were excluded because of previous critique of their ecological validity (Rottenberg, Ray, & Gross, 2007). In fact, these animated movies, such as the Disney movie “Bambi”, have been shown to reliably provoke emotional states (Gross &
Levenson, 1995). The present study, therefore, included animated movies and aimed to compare these old and previously validated scenes (from Gross & Levenson, 1995, and
Tomarken et al., 1990) to new ones.
In addition, we aimed at assessing two distinct aspects of emotion that have received much attention and tend to be very popular dimensions (Bradley & Lang, 2000; Gray, 2001):
Emotional valence (the dissociation between positive and negative states) and arousal (the intensity of the emotion; Ford, Addis, & Giovanello, 2012). Furthermore, we examined the duration of the emotional reaction to each movie clip in order to gain more insight into the question, whether emotional states or moods might be evoked. Although the terms emotion and mood are often used interchangeably in emotion research (Batson, Shaw, & Oleson,
1992), they can be separated as they describe distinct phenomena (Lochner, 2016). Emotions mostly have a stimulus event; they are rather intense but short in duration, and they have
26 CHAPTER 2 behavioral implications (Scherer, 2005). When compared to these properties, moods differ from emotions as they contain global, undirected, and rather unconscious background sensations that are more stable than emotions (Lischetzke & Eid, 2011; Lochner, 2016). The technique of using short emotional film sequences may be limited to the capacity to induce emotional states but not moods, which is linked to the important conceptual distinction between mood and emotion (Ekman & Davidson, 1994; Frijda, 1993; Schaefer et al., 2010).
The purpose of the present study was the development of a validated film set comprised out of the most potent clips from old and new movies (Gross & Levenson, 1995;
Tomarken et al., 1990; Rottenberg, Ray, & Gross, 2007; Hewig et al., 2005) that would provide an emotion induction method for the three basic emotions happiness, sadness and fear as well as a neutral state. We aimed at validating this new film set using a wider age range of participants in order to examine not only gender- but also age-related differences.
Furthermore, since intensity and duration are two salient features of an emotional response
(Frijda, 2007), we additionally examined the duration of emotional reactions.
Methods
Participants A total of n = 120 German speaking participants (60 females, 50%) took part in the film-viewing sessions. The subjects were 20-67 years old (M= 34.18, SD = 13.64) and were not paid for participation. Participants were included when their native language was German, and when they had normal or corrected vision and auditory functions. Prior to the experimental procedure, participants gave written and informed consent. The Ethics
Committee of the Faculty of Psychology at the Ruhr University Bochum approved the study.
27 CHAPTER 2
Stimulus Material In order to collect stimulus material the first step was the selection of a relatively large number of film excerpts suggested by students. They were asked to name films corresponding to four a priori emotional categories: sadness, fear, happiness, and a neutral state. In the next step, a film preselection was drawn by the research group consisting of five clinical psychology students, a certified psychotherapist and a psychophysiologist. Decisions were based on the following criteria: (1) the length of the film clip; (2) statutorily regulated age limits; (3) accessibility of the movie; (4) understandable thematic content without additional explanation; (5) the film elicited only one target emotion; and (6) appropriately high level of arousal of emotion. For each emotional category, the most frequently mentioned films were selected and cut into film clips. These 14 new film excerpts were compared to 10 previously validated emotional film sequences (from Gross & Levenson, 1995; Tomarken et al., 1990;
Rottenberg, Ray, & Gross, 2007). In addition, 2 previously validated (Hewig et al., 2005) and
6 new neutral film sequences were presented. Each cut scene lasted between 1.05 and 4.27 minutes. An overview of the stimulus material is presented in Table 1.
Measures
Basic Emotions The intensity of the six basic emotions was assessed using Emotion Report Forms; they contained visual analogue scales (VAS) in the form of six horizontal lines ranging from
0 (“Not at all”) to 10 (“Totally”). After each film, participants rated the levels felt with respect to all six emotions (happiness, anger, sadness, fear, surprise, and disgust).
Self-Assessment Manikin The SAM (Bradley, & Lang, 1994) is a pictorial assessment technique that measures the valence and arousal associated with the participant’s affective reaction to stimuli. For the valence rating, the scale ranges from (-4) = very negative to (4) = very positive. The arousal 28 CHAPTER 2 scale ranges from (8) = the highest level of arousal to (0) = the lowest level. The SAM-scale has been shown to be a useful instrument in both healthy as well as clinical populations
(Bynion & Feldner, 2017). It was presented after each film sequence.
Duration and subjective effectiveness ratings In addition to the above-mentioned scales, participants were asked whether the just rated emotion would still continue (yes/no) after having completed all above-mentioned ratings (within three minutes after the movie clip). Furthermore, participants rated the potential of the movie to elicit the same target emotion in others, again on a VAS raging from
(0) = not at all to (10) = totally.
Procedure Prior to the first movie, participants rated their initial emotional state using the above- mentioned ratings. Afterwards, participants viewed the selected clips in small group sessions.
Each group had an average of 5 participants (max: 6 and min: 3); each participant watched eleven film sequences. After each film presentation, every participant was asked to rate the intensity of the six emotions (happiness, anger, sadness, fear, surprise, and disgust) as well as the valence and intensity of the emotional arousal using the above-mentioned scales. To control for potential order effects, each group differed in the order of presented stimuli. In addition, the order of presentation was also set in such a way that films targeting the same emotion were not shown consecutively, and participants never watched more than two films of the same valence consecutively. Overall, each movie was watched and rated by n = 40 participants.
Data analysis The Statistical Package for the Social Sciences (SPSS) 24.0 was used to analyze the data. Generalized linear models (GLM) with the three target emotions (happiness, sadness,
29 CHAPTER 2 and fear) and the neutral condition as within-subject factors were performed. Movies served as between-subject factors. In order to examine gender and age effects, the two variables were included in the analyses as covariates. The same GLM were conducted for the arousal level and valence rating. In order to examine emotion-specific differences, multivariate analyses of variance (MANOVA) were computed including further pairwise comparisons between the different emotions. Homogeneity of error variances was tested using the Mauchly-test for sphericity. In case of significant results of the Mauchly-test, if Epsilon < .75, a Greenhouse-
Geisser correction was conducted; if Epsilon >.75, a Huynh-Feldt correction was recommended. All post-hoc multiple pairwise comparisons were performed using
Bonferroni's correction. The level of statistical significance was set as p < .05. Partial η2 was calculated as an estimate of effect size. According to Cohen (1988; 1992) a partial η2 of 0.01 can be viewed as small, 0.06 as medium, and 0.14 as large effect.
Results
Main effects The results of the GLM revealed a significant main effect of emotions, F(2, 1366) =
40.75, p < .001 (ηp² = .06), as well as a significant interaction effect of emotions and movies,
F(64, 2734) = 133.69, p < .001 (ηp² = .76). Further pairwise comparisons of mean scores among all emotional categories revealed significant differences between each target emotion and the further assessed emotions: Within each specific category, the happiness, F(7, 1907) =
5.17, p < .001 (ηp² = .019), sadness, F(7, 1907) = 8.16, p < .001 (ηp² = .03), and fear level,
F(7, 1907) = 9.99, p < .001 (ηp² = .03), were significantly higher than the other emotions.
However, within the neutral category, happiness was also significantly evoked, F(7, 1907) =
2.84, p = .006 (ηp² = .01).
30 CHAPTER 2
Movie-specific effects in each category Mean scores and standard deviations of all emotional ratings are presented in Table 2.
Happiness Movies
The highest ratings in the happiness category were found for the new movie “500
Days of Summer” (M = 7.32, SD = 2.01) and the old movie “The Jungle Book” (M = 7.16, SD
= 2.51). The old movie “An Officer and a Gentleman” was rated the lowest (M = 5.42, SD =
2.86).
Sadness Movies
The highest ratings in the sadness category were found for the new movies “My
Sister’s Keeper” (M = 7.84, SD = 1.56) and “The Green Mile” (M = 7.62, SD = 2.12). The lowest rating in this category was found for the old movie “The Champ” (M = 6.72, SD =
2.69).
Fear Movies
The highest ratings in the fear category were found for the old movies “Halloween”
(M = 7.16, SD = 2.01) and “The Shining” (M = 7.16, SD = 2.50). The new movie “The White
Noise” was rated the lowest (M = 3.82, SD = 2.86) in this category.
Neutral Movies
In the neutral category, three (new) movies significantly evoked emotional reactions:
“Brokeback Mountain”, F(2, 1366) = 42.19, p < .001 (ηp² = .06), “Railroads” F(2, 1366) =
25.83, p < .001 (ηp² = .04), and “Earth-NEUTRAL”, F(2, 1366) = 16.77, p < .001 (ηp² = .02).
Here, happiness was rated significantly high. The other five neutral sequences did not evoke any emotions significantly.
Arousal level The results of the GLM revealed an overall significant interaction effect of movies and arousal, F(31, 1247) = 26.78, p < .001 (ηp² = .040). Mean scores of arousal levels are presented in Figure 1. In addition to the eight neutral scenes, three further movie clips 31 CHAPTER 2 provoked significantly lower arousal levels: “An Officer and a Gentleman” (M = 3.22, SD =
2.39), “Eat Pray Love” (M = 3.45, SD = 2.01), and “Earth-HAPPINESS” (M = 3.77, SD = 2.57).
The highest arousal levels were found for “The Green Mile” (M = 6.22, SD = 1.86),
“My Sister’s Keeper” (M = 6.00, SD = 1.89), and “Bambi” (M = 5.95, SD = 2.29), all part of the sadness category. The highest arousal levels of fear-categorized movies were found for
“Inglourious Basterds” (M = 5.90, SD = 2.27), “The Silence of the Lambs-OLD” (M = 5.87, SD
= 2.46), and “Halloween” (M = 5.87, SD = 2.42). In the happiness category, the highest arousal levels were rated for “500 Days of Summer” (M = 5.47, SD = 1.89) and “The
Intouchables” (M = 5.02, SD = 1.91).
Valence Ratings Mean scores of all valence ratings are also presented in Figure 1. All movies of the happiness category were positively rated, whereas all movies of the sadness and fear category were negatively rated. In the neutral category, the movie “All the President’s Men” was also negatively rated, whereas the other neutral movies were slightly positively rated.
Age and gender effects The results revealed no significant effect of age, F(2, 1364) = 0.65, p = .519 (ηp² <
.01). With regard to gender effects, a significant interaction effect of emotion and gender was found, F(2, 1364) = 4.60, p = .010 (ηp² < .01). Further pairwise comparisons resulted in significantly higher ratings of female participants in the fear, F(1, 1366) = 9.56, p = .002 (ηp²
< .01), as well as in the sadness category, F(1, 1366) = 12.05, p = .001 (ηp² < .01). No gender differences were found in the happiness category, F(1, 1366) = 0.38, p = .537 (ηp² < .01).
32 CHAPTER 2
Duration of emotional reactions and subjective potential of each movie The results of the MANOVA revealed a significant main effect of effectiveness of all movies, F(31, 1247) = 18.53, p < .001 (ηp² = .31) based on participants’ subjective ratings of the potential to induce the same emotions in others.
In the happiness category, the highest ratings were found for “500 Days of Summer”
(M = 7.49, SD = 2.06), “The Jungle Book” (M = 6.99, SD = 2.70), and “Titanic-HAPPINESS” (M
= 6.63, SD = 2.87). The lowest rating was found for “An Officer and a Gentleman” (M = 4.97,
SD = 3.24). In the sadness category, the highest effectiveness ratings were found for “My
Sister’s Keeper” (M = 8.00, SD = 1.37), “Hachiko” (M = 7.84, SD = 2.03), and “The Green
Mile” (M = 7.73, SD = 1.42). The lowest rating in this category was found for “The Champ”
(M = 6.38, SD = 2.82). In the fear category, “Halloween” (M = 7.76, SD = 2.02), “The
Shining-FEAR” (M = 6.36, SD = 2.90), and “The Silence of the Lambs-OLD” (M = 6.31, SD =
2.54) were rated the highest, and “The White Noise” (M = 4.48, SD = 2.74) was rated the lowest.
With respect to the duration of emotional reactions, a significant overall effect was found, F(1, 1247) = 9.42, p < .001 (ηp² = .19). Although the duration of the previously highest rated emotional reactions (“500 Days of Summer”, “My Sister’s Kepper”, “Bambi”, “The
Green Mile”, and “Halloween”) was significantly higher than the duration of the lowest rated as well as neutral movies (all p values < .047), all mean scores ranged from M = 0.00 to M =
1.00 (range: 0-10). Mean ratings of effectiveness as well as mean scores of duration of emotional reactions are presented in Figure 2.
Discussion The main goal of the present study was the development and validation of a new emotional film set that would provide an emotion induction method for the three basic emotions happiness, sadness, and fear as well as a neutral state. We compared 12 previously validated movies (from Gross & Levenson, 1995; Tomarken et al., 1990; Rottenberg, Ray, & 33 CHAPTER 2
Gross, 2007; Hewig et al., 2005) to 20 new ones in order to select the most potent emotion induction film scenes.
Our results revealed that the three target emotions happiness, sadness, as well as fear were selectively evoked. The results also show, that it remains necessary to update stimulus material; when compared to previously validated older movies, the majority of the newly selected film sequences was superior in the induction of emotions. In the happiness and sadness category, the new film sequences (e.g. “500 Days of Summer” or “My Sister’s
Keeper”) evoked a more intense emotion when compared to the old movies (e.g. “When
Harry Met Sally” or “The Champ”). Only within the fear category, the older movies (e.g.
“Halloween”) induced a more intense emotion than the new movies (e.g. “The White Noise”).
With regard to the presentation of neutral film sequences, which were supposed to not induce any emotional reactions, we found an increase of happiness in three movies; in particular the sequences showing nature (“Earth-NEUTRAL”, “Brokeback Mountain”, and
“Railroads”) evoked an emotional reaction. Although the arousal ratings of these movies were low, they appear to be too intense to be used as a neutral movie clip. Since the concept of happiness has been described as multifaceted including other positive emotions (Hagemann et al., 1999), these sequences might have induced feelings of contentment and serenity as previous studies have used to evoke positive emotions (e.g. Fredrickson & Branigan, 2005).
We included different forms of neutral sequences; in addition to report and documentary scenes, we added neutral scenes of movies which also provide emotion induction scenes. As previous researchers have pointed out, neutral film sequences often differ from emotional film stimuli because they have not been taken from commercially available feature films (Hewig et al., 2005; Jenkis & Andrewes, 2012). Our results show that these scenes, although taken from movies such as “The Girl with the Dragon Tattoo”, can be used as neutral film sequences in future research studies.
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Furthermore, we aimed at validating this new film set using a wider age range of participants. Our results did not reveal any age-related differences. This finding is in line with the results of the study by Jenkins and Andrewes (2012) showing no specific differences in age groups. These results suggest that the presentation of film sequences provides an applicable emotion induction method for all age groups. Therefore, age appears to be less important when the researcher is interested in eliciting intense and discrete emotional reactions (Jenkins & Andrewes, 2012).
With regard to gender-related specificities, our results revealed differences in the negative emotion induction categories; whereas women reported higher levels of negative emotions than men, in both the sadness as well as fear category, no significant gender differences were found in the happiness category. These results are also in line with previous studies using emotion induction via film presentation (Gross & Levenson, 1995; Hagemann et al., 1999; Schaefer et al., 2010) and are consistent with many studies showing that women usually report more intense emotions than men (Brody & Hall, 2008). Moreover, taking the very small effect sizes of these differences into account, gender-specific differences in this present sample can even be neglected.
Finally, the duration of emotional reactions was very short as they mostly did not last until the termination of questionnaires. This finding underlines the assumption, that the duration of emotional stimuli is connected to the kind of emotional reaction being evoked
(Uhrig et al., 2016). Using short film sequences appears to induce emotional states and affects but not moods, which needs to be considered when conducting laboratory studies.
To sum up, several conclusions can be drawn from the data obtained in this study.
First of all and most importantly, short film clips appear to be an effective method for eliciting basic emotions. Secondly, they can be used for all age-groups. Thirdly, short film clips do not appear to elicit moods but rather basic emotions. The question of whether this is due to the length of the film clips needs to be addressed in future research studies.
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Limitations The following limitations must be taken into consideration while evaluating the present study. First of all, our arousal measurement was based on self-report ratings instead of physiological measures. We, therefore, caution against overestimating these results as subjective ratings of arousal level may differ from actual physiological changes. Secondly, the assessment of the duration of emotional reactions was based on the final question, whether the just rated emotions would still continue. We did not implement within-assessments or stepwise examination of emotional reactions and arousal. Future studies should imbed these information in order to gain more insights into the exact duration of emotional experiences.
Finally, our film database was validated using Western film material and a German population. Therefore, the results cannot be generalized as previous studies have already pointed out that culture-specific differences have mostly been ignored when using emotion induction techniques (Deng, Yang, & Zhou, 2017).
Conclusions The results of the present study provide a new emotional film set that can be used in future laboratory studies using emotion induction techniques. The newly validated film sequences have the potential to evoke happiness, sadness, and fear responses in all age groups.
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References Batson, C. D., Shaw, L. L., & Oleson, K. C. (1992). Differentiating affect, mood, and
emotion: Toward functionally based conceptual distinctions. In M. S. Clark (Ed.),
Review of personality and social psychology, No. 13. Emotion (pp. 294-326).
Thousand Oaks, CA, US: Sage Publications, Inc.
Bosse, T., Gerritsen, C., de Man, J., & Stam, M. (2014). Inducing Anxiety through
Video Material. In C. Stephanidis (Ed.), HCI International 2014 - Posters’ Extended
Abstracts (pp. 301–306). Cham: Springer International Publishing.
Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: the self-assessment manikin
and the semantic differential. Journal of Behavior Therapy and Experimental
Psychiatry, 25(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9
Bradley, M. M., & Lang, P. J. (2000). Affective reactions to acoustic stimuli.
Psychophysiology, 37(2), 204–215. https://doi.org/10.1017/S0048577200990012
Brody, L. R., & Hall, J. A. (2008). Gender and emotion in context. In M. Lewis, J. M.
Haviland-Jones, & L. F. Barrett (Eds.), Handbook of emotions (pp. 395-408). New
York, NY: The Guilford Press.
Bynion, T. M., & Feldner, M. T. (2017). Self-Assessment Manikin. In: Zeigler-Hill V.,
Shackelford T. (Eds) Encyclopedia of Personality and Individual Differences.
Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.).
Hillsdale, NJ: Erlbaum.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.
http://psycnet.apa.org/doi/10.1037/0033-2909.112.1.155.
Deng, Y., Yang, M., & Zhou, R. (2017). A new standardized emotional film database
for Asian culture. Frontiers in Psychology, 8(11).
https://doi.org/10.3389/fpsyg.2017.01941
37 CHAPTER 2
Ekman, P., & Davidson, R. J. (Eds.). (1994). Series in affective science. The nature of
emotion: Fundamental questions. New York, NY: Oxford University Press.
Frazier, T. W., Strauss, M. E., & Steinhauer, S. R. (2004). Respiratory sinus arrhythmia
as an index of emotional response in young adults. Psychophysiology, 41, 75–83.
https://org.doi.10.1046/j.1469-8986.2003.00131.x
Fredrickson, B. L., & Branigan, C. (2005). Positive emotions broaden the scope of
attention and thought-action repertoires. Cognition and Emotion, 19(3), 313–332.
https://doi.org/10.1080/02699930441000238
Frijda, N. H. (1993). Mood, Emotion Episodes, and Emotions. In M. Lewis, & J. M.
Haviland (Eds.), Handbook of Emotions (pp. 381-403). New York, NY: Guilford
Press.
Frijda, N. H. (2007). The laws of emotion. Mahwah, NJ: Lawrence Erlbaum Associates
Publishers.
Fucito, L. M., & Juliano, L. M. (2009).. Depression moderates smoking behavior in
response to a sad mood induction. Psychology of Addictive Behaviors, 23(3), 546-551.
http://dx.doi.org/10.1037/a0016529
Gray, J. R. (2001). Emotional modulation of cognitive control: Approach-withdrawal
states double-dissociate spatial from verbal two-back task performance. Journal
of Experimental Psychology: General, 130(3), 436-452.
https://doi.org/10.1037/0096-3445.130.3.436
Gross, J. J. (1998). The emerging field of emotion regulation. Review of General
Psychology, 2(5), 271–299.
Gross, J. J., & Levenson, R. W. (1995). Emotion Elicitation using Films. Cognition and
Emotion, 9(1), 87–108. https://doi.org/10.1080/02699939508408966
Hagemann, D., Naumann, E., Maier, S., Becker, G., Lürken, A., & Bartussek, D.
38 CHAPTER 2
(1999). The assessment of affective reactivity using films: Validity, reliability and sex
differences. Personality and Individual Differences, 26(4), 627–639.
https://doi.org/10.1016/S0191-8869(98)00159-7
Hewig, J., Hagemann, D., Seifert, J., Gollwitzer, M., Naumann, E., & Bartussek, D.
(2005). A revised film set for the induction of basic emotions. Cognition and Emotion,
19(7), 1095-1109. http://dx.doi.org/10.1080/02699930541000084
Jenkins, L. M., & Andrewes, D. G. (2012). A new set of standardised verbal and non-
verbal contemporary film stimuli for the elicitation of emotions. Brain Impairment,
13(2), 212–227. https://doi.org/10.1017/BrImp.2012.18
Kuijsters, A., Redi, J., de Ruyter, B., & Heynderickx, I. (2016). Inducing sadness and
anxiousness through visual media: Measurement techniques and persistence. Frontiers
in Psychology, 7(8), 1–14. https://doi.org/10.3389/fpsyg.2016.01141
Lischetzke, T., Angelova, R. & Eid, M. (2011). Validating an indirect measure of clarity
of feelings: Evidence from laboratory and naturalistic settings. Psychological
Assessment, 23(2), 447-455. https://doi.org/10.1037/a0022211
Lochner, K. (2016). Affect, Mood, and Emotions. In Successful Emotions: How
Emotions Drive Cognitive Performance (pp. 43–67). https://doi.org/10.1007/978-3-
658-12231-7_3
Macht, M., Roth, S., and Ellgring, H. (2002). Chocolate eating in healthy men during
experimentally induced sadness and joy. Appetite 39, 147–158.
https://doi.org.10.1006/appe.2002.0499
Palomba, D., Sarlo, M., Angrilli, A., Mini, A., & Stegagno, L. (2000). Cardiac
responses associated with affective processing of unpleasant film stimuli.
International Journal of Psychophysiology, 36(1), 45–57.
https://doi.org/10.1016/S0167-8760(99)00099-9
Pham, T. H., Philippot, P., & Rime, B. (2000). Subjective and autonomic responses to
39 CHAPTER 2
emotion induction in psychopaths. L'Encéphale: Revue de psychiatrie clinique
biologique et thérapeutique, 26(1), 45-51.
Philippot, P., Chapelle, G., & Blairy, S. (2002). Respiratory feedback in the generation
of emotion. Cognition and Emotion, 16(5), 605–627.
https://doi.org/10.1080/02699930143000392
Rottenberg, J., Ray, R. D., & Gross, J. J. (2007). Emotion Elicitation Using Films. In J.
A. Coan, & J. J. B. Allen (Eds.), The Handbook of Emotion Elicitation and
Assessment (pp. 9-28). London: Oxford University Press.
Schaefer, A., Nils, F., Philippot, P., & Sanchez, X. (2010). Assessing the effectiveness
of a large database of emotion-eliciting films: A new tool for emotion researchers.
Cognition and Emotion, 24(7), 1153–1172.
https://doi.org/10.1080/02699930903274322
Schaefer, A., & Philippot, P. (2005). Selective effects of emotion on the phenomenal
characteristics of autobiographical memories. Memory, 13(2), 148–160.
https://doi.org/10.1080/09658210344000648
Scherer, K. R. (2005). What are emotions? And how can they be measured? Social
Science Information, 44(4), 695–729. https://doi.org/10.1177/0539018405058216
Tan, E. S. (2018). A psychology of the film. Palgrave Communications, 4(1), 82.
https://doi.org/10.1057/s41599-018-0111-y
Tomarken, A. J., Davidson, R. J., & Henriques, J. B. (1990). Resting frontal brain
asymmetry predicts affective response to films. Journal of Personality and Social
Psychology, 59(4), 791-801. http://dx.doi.org/10.1037/0022-3514.59.4.791
Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W.,
& Marschall, S. (2016). Emotion Elicitation: A Comparison of Pictures and Films.
Frontiers in Psychology, 7(180), 1-12.
https://www.frontiersin.org/article/10.3389/fpsyg.2016.00180
40 CHAPTER 2
Västfjäll, D. (2015). Emotion induction through music: A review of the musical mood
induction procedure. Musicae Scientiae, 5(1), 173–211.
https://doi.org/10.1177/10298649020050s107
Velten, E. (1968). A laboratory task for induction of mood states. Behaviour Research
and Therapy, 6(4), 473–482. https://doi.org/10.1016/0005-7967(68)90028-4
Westermann, R., Spies, K., Stahl, G., & Hesse, F. W. (1996). Relative effectiveness and
validity of mood induction procedures: A meta-analysis. European Journal of
Social Psychology, 26(4), 557–580. https://doi.org/10.1002/(SICI)1099-
0992(199607)26:4<557::AID-EJSP769>3.0.CO;2-4
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Table 1: Overview of the Stimulus Material Emotion Movie Old/New Scene Length Movie (min)
Happiness 500 Days of Summer New The main actor is singing and dancing through the city after he had a sexual experience. 2:06
The Jungle Book Old Mogli is singing and dancing with his friends. 1:55
Titanic-HAPPINESS New Irish party scene, where Rose and Jack are dancing together. 3:00
When Harry met Sally Old Harry and Sally discuss about whether Harry would notice a fake orgasm. 2:35
Eat Pray Love New Liz makes a poor family happy with a successful collection of donations. 1:36
The Intouchables New The two friends Philippe and Driss are joking around and having fun together. 1:51
Earth-HAPPINESS New Polar bear babies are rolling and playing around. 2:53
An Officer and a Old Romantic scene between Paula and her marine officer Zack 1:51 Gentleman
Sadness My Sister's Keeper New At the hospital, Anna gives her mother a book she made with all of her family 3:36 memories.
The Green Mile New John Coffey is being unjustly executed. 3:42
Bambi Old Bambi’s mother dies. 2:19
Hachiko New The dog Hachiko has lost his owner and best friend, who had died at work. Hachiko is 3:31 waiting for his return every day at the train station until he passes away.
Titanic-SADNESS New Good-bye scene between Rose and Jack. 4:27
The Lion King Old Simba’s Dad dies. 1:47
Return to me Old Bob has lost his wife due to an accident, he is sitting on the floor with his dog crying. 3:36
The Champ Old Billy got severely injured in a boxing match and is lying on a table, when his little son 2:51 enters.
Fear Halloween Old Laurie is working as a babysitter at a friend’s house, where she finds a corpse and is 3:28 being pursued by the killer.
The Shining-FEAR Old Wendy is hiding from a serial killer who finds her in the bathroom. 2:08
Silence of the Lambs- Old The FBI agent Clarice is searching for a serial killer. She follows him into a basement. 3:22 OLD
96 Hours New Kim is watching her friend being kidnapped and is hiding from the perpetrators. 2:43
Silence of the Lambs- New A serial killer in the dark follows Clarice. 1:38 NEW
Titanic-FEAR New Cal is trying to kill Rose and Jack. 3:37
Inglourious Basterds New Nazi soldiers are searching Jews, who are hiding in a farmer’s house. 2:45
The White Noise New Lukas loses his mind. 1:25
Neutral All the President’s Men Old Bob is reporting about a court case and asks one of the attendees what had just 1:05 happened.
Brokeback Mountain New Ennis and Jack are watching over their sheep. 1:12
Railroad New Reporting scene about railroads. 2:02
Hannah and her Sisters Old Hannah and Holly are shopping and talking about last night. 1:32
Machines New Reporting scene about working machines. 1:45
The Shining-NEUTRAL New A hotel manager is showing his guests around. 1:28
Earth-NEUTRAL New Reporting scene about nature. 1:30
The Girl with the New Mikael is sitting on a table talking to a woman. 1:33 Dragon Tattoo
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Table 2: Mean scores and standard deviations of all basic emotion ratings Happiness Sadness Fear Anger Surprise Disgust Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD)
500 Days of Summer 7.32(2.01) 0.18(0.55) 0.15(0.32) 0.11(0.19) 2.40(2.51) 0.21(0.78) The Jungle Book 7.16(2.51) 0.15(0.21) 0.13(0.15) 0.32(0.58) 0.79(1.05) 0.35(0.59)
Titanic-HAPPINESS 6.60(2.21) 0.16(0.26) 0.25(0.8) 0.17(0.35) 1.01(1.32) 0.10(0.16) When Harry met Sally 6.44(2.31) 0.22(0.46) 0.20(0.26) 0.40(0.64) 1.31(1.54) 0.21(0.40) Eat Pray Love 6.27(2.13) 1.41(1.40) 0.26(0.4) 0.32(0.60) 2.05(2.45) 0.18(0.33) The Intouchables 6.23(2.24) 0.84(1.74) 0.29(0.91) 1.35(2.07) 2.50(2.45) 0.21(0.53)
Earth-HAPPINESS 6.00(2.23) 0.34(0.89) 0.37(0.92) 0.30(0.90) 1.33(1.72) 0.12(0.21) An Officer and a Gentleman 5.42(2.86) 0.23(0.30) 0.17(0.29) 0.20(0.37) 1.79(2.38) 0.14(0.24) My Sister’s Keeper 1.04(1.43) 7.84(1.57) 2.92(2.48) 1.12(2.05) 1.10(2.26) 0.39(0.82) The Green Mile 0.23(0.54) 7.62(2.12) 2.28(2.17) 3.01(2.89) 0.70(1.62) 2.36(2.75) Bambi 0.33(0.62) 7.42(2.13) 1.63(1.93) 2.62(2.54) 0.44(0.85) 0.97(1.55) Hachiko 2.20(2.45) 7.29(2.49) 0.93(1.65) 0.75(1.84) 2.00(2.60) 0.11(0.24)
Titanic-SADNESS 0.38(0.59) 7.23(2.43) 1.85(2.26) 0.81(1.54) 0.42(0.70) 0.82(1.78) The Lion King 0.18(0.41) 7.07(2.36) 1.04(1.52) 0.65(1.3) 0.69(1.02) 0.14(0.22) Return to me 1.24(2.13) 6.82(2.30) 1.73(2.07) 0.73(1.44) 3.45(2.70) 0.16(0.45) The Champ 0.24(0.56) 6.72(2.69) 0.77(1.46) 1.14(1.79) 0.96(1.51) 0.82(1.57) Halloween 0.37(0.93) 0.40(0.90) 7.33(2.12) 0.69(1.10) 3.54(2.82) 2.18(2.41)
Shining-FEAR 0.51(1.32) 0.89(1.84) 5.99(2.84) 2.00(2.38) 1.70(1.94) 2.87(3.12)
The Silence of the Lambs-OLD 0.21(0.39) 0.42(0.91) 5.96(2.22) 1.17(1.43) 3.39(2.52) 2.04(2.33) 96 Hours 0.84(1.57) 1.90(2.20) 5.69(2.46) 2.00(2.29) 3.80(2.83) 1.15(1.40)
The Silence of the Lambs-NEW 0.18(0.38) 0.43(0.67) 5.62(2.47) 0.58(0.94) 3.00(2.70) 1.13(2.06)
Titanic-FEAR 0.57(1.12) 2.17(1.93) 5.16(3.02) 1.84(2.26) 2.45(2.50) 0.25(1.02) Inglourious Basterds 0.53(1.53) 3.67(2.97) 4.72(3.23) 3.8(3.38) 2.49(2.61) 2.42(3.04) The White Noise 0.18(0.18) 1.39(1.46) 3.82(2.62) 1.30(1.63) 1.30(1.49) 0.78(1.61) Brokeback Mountain 3.41(2.60) 0.33(0.40) 0.15(0.16) 0.19(0.25) 0.53(1.34) 0.16(0.36) Railroads 2.68(2.34) 0.21(0.43) 0.20(0.50) 0.16(0.22) 0.36(0.69) 0.10(0.12)
Earth-NEUTRAL 2.29(2.20) 0.42(1.15) 0.15(0.46) 0.27(0.95) 0.60(1.60) 0.07(0.18) Machines 1.53(1.89) 0.34(0.98) 0.40(1.24) 0.31(1.02) 1.09(2.02) 0.12(0.17)
The Shining-NEUTRAL 1.00(1.68) 0.22(0.28) 0.43(0.62) 0.3(0.41) 0.87(1.80) 0.14(0.19) The Girl with the Dragon Tattoo 0.92(1.60) 0.55(1.69) 0.24(0.65) 0.27(0.49) 0.35(0.71) 0.09(0.17) Hannah and her Sisters 0.89(1.53) 0.69(1.12) 0.23(0.52) 0.31(0.74) 0.69(1.23) 0.31(0.75) All the President’s Men 0.38(0.69) 0.21(0.24) 0.37(0.63) 0.67(1.24) 0.73(0.97) 0.25(0.46) Note: Mean scores sorted from high to low; SD = standard deviation. Highest ratings of each category are bold.
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Figure 1: Mean scores of arousal (range: 0 to 10) and valence ratings (range: -4 to 4) of all movies.
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Figure 2: Mean scores of duration of emotional reactions and subjective ratings of potential to induce the same emotional reaction in others (both ranges: 0-10).
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Study 2: Affective styles in mood and anxiety disorders – Clinical validation of the “Affective Style Questionnaire” (ASQ).
Contents lists available at ScienceDirect
Journal of Affective Disorders
journal homepage: www.elsevier.com/locate/jad
Research Paper Affective styles in mood and anxiety disorders – Clinical validation of the “Affective Style Questionnaire” (ASQ) Christina Totzecka,⁎, Tobias Teismanna, Stefan G. Hofmannb, Ruth von Brachela, Xiao Chi Zhanga, Verena Pfluga, Jürgen Margrafa a Mental Health Research and Treatment Center, Ruhr-Universität Bochum, Massenbergstrasse 9-13, 44787 Bochum, Germany b Psychological and Brain Sciences, Boston University, Boston, USA
ARTICLE INFO ABSTRACT
Keywords: Background: Emotion regulation plays a critical role in the development and maintenance of psychological Emotion regulation disorders. Less is known about the association of affective styles and psychopathology. The 20-item “Affective ff A ective styles Style Questionnaire” (ASQ) has been validated in nonclinical samples. The American and German validation ASQ studies resulted in a three-factor structure (concealing, adjusting, and tolerating). The present study aimed to Affective disorders investigate three aspects: (1) the validation of the ASQ within a clinical sample, (2) the examination of possible Anxiety disorders differences in affective styles between patients suffering from affective versus anxiety disorders, and (3) the association of affective styles and anxiety, depression, and stress symptoms. Methods: Overall 917 patients receiving cognitive-behavioral therapy at an outpatient clinic participated in this study, 550 participants were female. All data were collected before the beginning of treatment. Results: Confirmatory factor analyses revealed the same three-factor structure found in the previous Western samples (CFI = 0.90, RMSEA = 0.06): Concealing (α = 0.81), adjusting (α = 0.71), and tolerating (α = 0.70). Significantly lower scores in the ASQ subscale adjusting were found in patients suffering from affective disorders than patients suffering from anxiety disorders. The results of the regression analyses showed that the ASQ ad- justing and concealing behavior seem to play a more important role than the ERQ reappraisal and suppression for depression, anxiety, and stress among clinical populations. Limitations: A number of limitations must be taken into consideration while evaluating the present study. First and foremost, the clinical data were based on primary diagnoses. We did not ascertain comorbid diagnoses. This distinction may be important, since affective and anxiety disorders are often linked to each other. In addition, we only used data collected before the beginning of psychotherapeutic treatment and were therefore not able to analyze changes in affective styles during and after intervention. Furthermore, all data were based on self- reported information of patients. We did not implement either a therapeutic rating of affective styles or phy- siological measures, for instance arousal, which could have shown whether the used strategies successfully reduce negative emotions. Future research should address this question. Another limitation is the fact that we concentrated on the main categories of mental disorders and, therefore, did not subdivide patients with affective and anxiety disorders in terms of their concrete diagnoses. This is of special importance, because there might also be differences in affective styles within the main categories.
1. Introduction expressive suppression (Gross & John, 2003; Ochsner et al., 2002). Cognitive reappraisal as an antecedent-focus strategy serves to change Every human being experiences negative emotions but people's the negative emotional impact before distress is fully activated. Ex- ways of coping vary greatly. Emotion regulation depicts the process by pressive suppression as a response-focused strategy is used to avoid an which individuals consciously and unconsciously modulate their emo- ongoing negative emotion. Research has shown that antecedent-focused tions to respond to environmental demands (Rottenberg & Gross, 2003; strategies are relatively effective, whereas response-focused strategies Campbell-Sills & Barlow, 2007). Two regulation strategies that have tend to paradoxically increase negative affect (Gross, 1998; Aldao et al., received considerable empirical attention are cognitive reappraisal and 2010).
⁎ Corresponding author. E-mail addresses: [email protected], [email protected] (C. Totzeck).
https://doi.org/10.1016/j.jad.2018.05.035 Received 17 January 2018; Received in revised form 27 April 2018; Accepted 25 May 2018
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C. Totzeck et al.
Individuals vary in their use of strategies, in the speed and in the measure affective styles in a healthy population. However, as of now, the intensity of emotional reactions to similar threats and rewards ASQ factor structure and psychometric properties have not been in- (Dennis, 2007). This broad range of individual responses is referred to vestigated in a clinical sample. This is of special importance, since a better as affective style (Davidson, 1998, 2000, 2002; Hofmann et al., 2012). understanding of emotion dysregulation might help to provide a more For instance, some people tolerate feeling sad or anxious, whereas detailed picture of different psychological disorders, their common factors others react to the onset of such emotions by immediately appraising as well as their differences. The present study addresses this paucity and them as intolerable and subsequently engage in maladaptive response- aimed to investigate three aspects: (1) the validation of the ASQ within a focused strategies (Gross & John, 2003). With the development of the clinical sample, (2) the examination of possible differences in affective “Affective Style Questionnaire” (ASQ), Hofmann and Kashdan (2010) styles between patients suffering from affective versus anxiety disorders, aimed to provide a tool to assess such inter-individual differences in the and (3) the association of affective styles and anxiety, depression, and habitual use of emotion regulation strategies. The ASQ was developed stress symptoms. in a two-phase study: In their first study, the authors compiled a pool of Regarding the validation, we first hypothesized that the three-factor 127 items related to the construct of emotion regulation strategies, structure of concealing, adjusting, and tolerating would also emerge in mostly based on the work by Gross and John (1997; 2003), as well as on a clinical outpatient population in Germany. We expected the three- the acceptance and mindfulness based literature (e.g., Hayes et al., factor structure, because the only deviation from this factor structure 1999). Items and self-report measurements were presented to a student was found in an Asian population, which suggests cultural differences sample (N = 457). Analyses revealed three meaningful and inter- in affective styles. Furthermore, we hypothesized that previous findings pretable factors, which led to the following three affective styles: con- on the correlations between the ASQ and ERQ would be replicated cealing, adjusting, and tolerating. (Hofmann et al., 2010; Ito & Hofmann, 2014): We predicted that ad- Concealing describes the tendency to avoid intrapersonal and inter- justing would be positively correlated with ERQ reappraisal, and that personal emotions that surface (eight items; e.g., “I often suppress my concealing would be positively correlated with ERQ suppression. In emotional reaction to things”)includingsuppressionandotherresponse- addition, we expected to find a negative correlation between tolerating focused strategies. Adjusting reflects the perception of an emotion as in- and ERQ suppression. formation, and the ability to use this information to modulate the emo- Secondly, we sought to examine differences of affective styles in tional experience and expression in response to the situational demands of patients suffering from mood and anxiety disorders. As part of emotion aparticularcontext.Thisincludesnotonlycognitivereappraisalbutalso regulation research, previous studies have provided empirical data other tactics that help to successfully balance emotions as needed (seven showing associations between different strategies and psychopathology items; e.g., “I can get out of a bad mood very quickly”). Finally, tolerating (for an overview see the meta-analysis by Aldao et al., 2010). Less is refers to the perception of an emotion without any effort to fight this known about the association of affective styles and mental disorders. feeling, even if this emotion is negative and causes distress (five items; e.g., One study by D’ Avanzato et al. (2013) found that patients suffering “It's ok if people see me being upset”). from depressive disorders showed a less frequent use of reappraisal In order to further evaluate the structure and psychometric prop- assessed with the ERQ than patients suffering from anxiety disorders, erties of the ASQ, Hofmann and Kashdan conducted a second study who in turn reported more use of suppression. These differences might administering the ASQ to another student sample (N = 495). Results be explained by different prefrontal activation patterns in patients with supported the three-factor structure of concealing, adjusting, and tol- mood and anxiety disorders (Davidson, 1998, 2000, 2002). We ex- erating. Internal consistency values were acceptable for all three sub- pected to find similar differences of patients with anxiety and mood ff scales (Cronbach's alpha values of concealing: α = 0.84, adjusting: disorders with regards to their use of a ective styles. Assuming that ff ff fi α = 0.82, and tolerating: α = 68). Construct validity was also sa- patients su ering from a ective disorders show de cits in the suc- tisfactory, results showed strong relations with other emotion regula- cessful use of cognitive reappraisal, they might also have difficulties in tion scales. For instance, correlations were found for ASQ adjusting and adjusting to situational demands. We, therefore, hypothesized to find the “Emotion Regulation Questionnaire” (ERQ; Gross & John, 2003) lower scores in adjusting for patients suffering from affective disorders subscale reappraisal (r = 0.57), ASQ concealing with ERQ suppression when compared to patients suffering from anxiety disorders. Con- (r = 0.52), and ASQ tolerating was negatively correlated with ERQ versely, we assumed to find a similar effect of concealing. More pre- suppression (r = − .32). cisely, we hypothesized higher scores in concealing for patients suf- Graser et al. (2012) translated the original ASQ into German and fering from anxiety disorders when compared to patients suffering from conducted a validation study with a student sample (N = 640). Results affective disorders. With regard to possible differences in tolerating, we of factor analyses replicated the original three-factor structure. How- did not set hypotheses a priori. ever, two items of the adjusting subscale (Item 2: “I have my emotions Thirdly, we were interested in the associations of different affective well under control” and Item 8: “I am able to let go of my feelings”) styles and psychopathology. As mentioned before, associations between loaded onto the other subscales, and thus, were reassigned to the affective styles and both depression as well as anxiety symptoms were concealing and tolerating subscale. Internal consistencies were sa- found in a student sample (Ito & Hofmann, 2014). Analogue to this tisfactory and consistent with the original version (concealing scale: healthy population, we presumed a negative association of adjusting ff α = 0.84; adjusting scale: α = 0.75; tolerating scale: α = 0.72). Within with depression, anxiety, and stress symptoms in both patients su ering the German sample, male and female participants differed significantly from affective disorders and anxiety disorders. Even though concealing in all three subscales: Men scored significantly higher in concealing and did not show significant associations in a healthy population (Ito & adjusting, whereas women scored significantly higher in tolerating. In Hofmann, 2014), we also expected a positive association of concealing summary, both validation studies provide evidence for the applicability with depression, anxiety and stress symptoms in a clinical sample. This of the ASQ within nonclinical US and German populations. assumption is mostly based on previous studies showing a significant Another cross-validation study was conducted (Ito & Hofmann, 2014) association of the maladaptive strategy suppression with mood and using a Japanese student sample (N = 1,041). Here, a fourth factor labeled anxiety disorders (Aldao et al., 2010). Because of the similarities be- holding was found. In addition, the authors examined the influence of tween suppression and concealing, we assumed that concealing might affective styles on depression and anxiety symptoms in this study. Results also contribute to depression, anxiety, and stress symptoms in patients ff ff showed strong associations of adjusting with depression (β = −0.19) and su ering from a ective and anxiety disorders. In reverse, we presumed anxiety (β = −0.29). Whether these results generalize to a clinical po- a negative association of tolerating with depression, anxiety, and stress pulation has not been examined so far, and will be addressed in the pre- symptoms. sent study. In conclusion, the ASQ seems to be a suitable instrument to
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2. Methods items are scored on a 7-point Likert scale ranging from (1) = “strongly disagree” to (7) = “strongly agree” . Internal consistency values of the 2.1. Participants German version were: α = 0.74 for the score of suppression (0.73 for the original version) and α = 0.78 for the score of reappraisal (0.79 A total of N = 917 treatment-seeking patients participated in this original version). In the current sample, alpha values were α = 0.74 for study before receiving cognitive-behavioral therapy at an outpatient the score of suppression and α = 0.86 for the score of reappraisal. clinic in the Ruhr region in Germany between April 2012 and December 2016. Five hundred-fifty participants (60.0%) were female and 367 2.2.4. Depression Anxiety Stress Scale-21 (30.0%) were male. The mean age was 37.87 years (SD = 12.90; Range: The Depression Anxiety Stress Scale (DASS; Lovibond & 18–78 years). All data were collected before the beginning of treatment. Lovibond, 1995; German version: Nilges, & Essau, 2015) is a 42-item The most common primary diagnoses were affective disorders self-report instrument measuring the three negative emotional states of (n = 462; 50.4%), including n = 9 patients suffering from a manic or depression, anxiety and tension/stress. We used 21 selected items from bipolar disorder, n = 177 patients suffering from a single major de- the DASS-42 to assess levels of depression, anxiety, and stress over the pression episode, n = 229 patients suffering from a recurrent major past week on three 7-item subscales using 4-point Likert scales from depression, and n = 47 patients suffering from persistent or unspecified (0) = “did not apply to me at all” to (3) = “applied to me very much or mood disorders. The second most common primary diagnoses were most of the time”. Consistency values for the three DASS subscales were neurotic, stress-related and somatoform disorders (n = 377; 41.1%), α = 0.91 for the score of depression, α = 0.81 for the score of anxiety, ff including n = 162 patients su ering from phobic anxiety disorders, and α = 0.86 for the score of stress in the current sample. n = 39 patients suffering from a panic disorder, n = 26 patients suf- fering from a general anxiety disorder, n = 28 patients with an ob- 2.3. Statistical analysis sessive-compulsive disorder, and n = 122 patients suffering from either a reaction to severe stress, respectively an adjustment disorder, a so- The Statistical Package for the Social Sciences (SPSS) 24.0 and matoform disorder or an unspecified anxiety disorder. This was fol- AMOS 24.0 were used to analyze the data. In order to cross-validate the lowed by behavioral syndromes associated with physiological dis- factor structure of the ASQ, a confirmatory factor analysis was con- turbances and physical factors (3.7%), personality disorders (2.5%), ducted. Goodness-of-fit indices, including the Comparative Fit Index schizophrenia, schizotypal and delusional disorders (1.0%), substance (CFI) and the root mean square error of approximation (RMSEA) were abuse (0.7%), and other disorders (0.6%). Comorbidity was not ascer- examined to determine how well the model fit the data. The following tained in this present study. thresholds were considered: CFI > 0.90 and RMSEA close to 0.06 in- fi 2 Prior to assessments, participants were informed about the purpose dicate a good t(Hu & Bentler, 1999). Since the chi-square (χ ) statistic of the study, the voluntary nature of their participation, data storage is very sensitive to sample sizes, it was not used as goodness-of-fit index and security. They provided written informed consent prior to partici- (Schlermelleh-Engel et al. 2003). Standardized factor loadings were pation. Ethics Committee of the Faculty of Psychology at the Ruhr- used to assess the appropriateness of the measurement. Means and Universität Bochum approved the study. standard deviations of the ASQ subscales were calculated, and internal consistencies were determined by calculating Cronbach's alpha. Multi- 2.2. Measures variate analyses of variance with age and gender as covariates (MAN- COVA) were performed to test for gender and age effects on the ASQ ff 2 2.2.1. Diagnostic interview subscales. E ect sizes were calculated using partial eta squared (ηp ) as Diagnoses were made by trained clinical psychologists using the suggested by Cohen (1988) with > 0.01 indicating a small ef- DIPS (“Diagnostisches Interview bei psychischen Störungen”; Schneider fect, > 0.06 indicating a medium effect and > 0.14 indicating a large & Margraf, 2006), a structured clinical interview to assess mental dis- effect. Correlations between the subscales of the ASQ, ERQ, and DASS orders according to the criteria of the Diagnostic and Statistical Manual were calculated to examine the ASQ's convergent and discriminant for Mental Disorders (DSM-IV-TR; APA, 2000). The results of previous validity. Lastly, we conducted MANOVAs of the ASQ subscales among validation studies using the DIPS indicate high interrater-reliability the two largest groups of patients, consisting of patients with affective coefficient scores (Cohen's kappa coefficient (κ)), especially for the and anxiety disorders. Multiple regression analyses were performed to major diagnostic categories of anxiety (κ = 0.78) and mood (κ = 0.81) examine the influence of the ASQ and ERQ subscales as well as gender disorders (Suppiger et al., 2008; In-Albon et al., 2008) as well as high and age on affective and anxiety symptoms. The ERQ was included in retest-reliability coefficient scores (κ = 0.80 for affective and κ = 0.76 the regression analysis because most studies on emotion regulation used for anxiety disorders). All diagnoses were verified through supervising the ERQ and were based on the process model of emotion regulation senior psychotherapists. proposed by Gross (1998). Following the procedure of previous vali- dation studies (see Ito & Hofmann, 2014), the ASQ and ERQ subscales 2.2.2. Affective Style Questionnaire were simultaneously entered into analyses. The ASQ (Hofmann & Kashdan, 2010; German version: Graser et al., 2012) is a 20-item scale, measuring the three affective styles con- 3. Results cealing, adjusting, and tolerating, on a 5-point Likert scale ranging from (1) = “not true of me at all” to (5) = “extremely true of me”. The in- 3.1. Factor structure ternal consistency values (Cronbach's alpha) of the scores of the ASQ fi fi subscales in the US student samples were α = 0.84 (concealing), The results of the rst CFA showed that the goodness of t indices fi α = 0.80 − 0.82 (adjusting), and α = 0.66 − 0.68 (tolerating). In the were below the threshold for an acceptable model t (CFI = 0.78, German student sample, the consistency values for the scores of the RMSEA = 0.09). The model was re-examined by exploring modification three subscales were α = 0.82 (concealing), α = 0.76 (adjusting), and indices, allowing error terms to be correlated with each other. α = 0.71 (tolerating). Following these adjustments, the results of the CFA showed that the goodness of fit indices were acceptable: The Comparative Fit Index 2.2.3. Emotion Regulation Questionnaire (CFI = 0.91) indicated a good fit, and the root mean square error of The ERQ (Gross & John, 2003; German version: Abler & approximation (RMSEA = 0.06, 90% CI: 0.06 − 0.07) was acceptable. Kessler, 2009) is a 10-item scale used to assess two types of emotion The standardized loadings were at least moderately high (load- regulation strategies: cognitive reappraisal and expressive suppression. The ings > 0.40), except for two items on the factor concealing (item
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2 p = .001; ηp = 0.012), with males showing higher scores than females. No further sex or age differences were found (all other p 〉 .10).
3.3. Correlations of ASQ subscales with ERQ and DASS
Correlations between the ASQ subscales and the ERQ and DASS subscales were calculated. Results are presented in Table 1.
3.4. Comparison of ASQ, ERQ, and DASS subscales among affective and anxiety disorders
Means and standard deviations of ASQ, ERQ, and DASS subscales as well as p-values and effect sizes are presented in Table 2. Further analysis of variance in the two largest groups, consisting of patients suffering from affective and anxiety disorders, resulted in significant differences within the ASQ subscale adjusting (F(1, 798) = 17.41, 2 p < .001, ηp = 0.021) and the ERQ subscale reappraisal (F(1, 2 798) = 12.36, p < .001, ηp = 0.015). In addition, the depression (F(1, 2 798) = 84.12, p < .001, ηp = 0.095) and stress subscales (F(1, 2 ff fi 798) = 5.78, p = .016, ηp = 0.007) of the DASS di ered signi cantly between affective and anxiety disorders. In order to further examine differences within these two groups of patients, we first conducted multivariate analyses of variances within affective disorders and then within anxiety disorders. Results did not reveal significant differences (all p > .05).
3.5. Summary for the regression analyses on Depression, Anxiety, and Stress of ASQ and ERQ subscales
To examine the relationship between the DASS subscales depres- sion, anxiety, and stress and the ASQ subscales, multiple regression analyses were conducted based on all patients suffering from affective or anxiety disorders. Results are presented in Tables 3.1 and 3.2. Overall, the ASQ adjusting subscale showed the highest negative asso- Fig. 1. Results of the CFA. Confirmatory factor analysis of the Affective Style ciation with depression, anxiety, and stress symptoms in patients suf- Questionnaire. Ovals represent latent variables, squares represent the twenty fering from anxiety disorders. Lower scores on the ASQ adjusting sub- items of the ASQ. Numbers next to arrows indicate factor loadings. scale were also associated with higher depression and stress symptoms in patients suffering from affective disorders. #1 = 0.26 and item #2 = 0.34) and two items on the factor tolerating Whereas concealing was positively associated only with depressive (item #3 = 0.34 and item #11 = 0.36). Results are presented in Fig. 1. symptoms in patients suffering from affective disorders, it was posi- tively associated with the entire range of anxiety, depression, and stress 3.2. Internal consistency and sex differences symptoms in patients with anxiety disorders. Tolerating only showed a negative association with anxiety symptoms in patients with affective fi The internal consistency value of the ASQ score was α = 0.77 in this disorders. Neither of the ERQ subscales showed signi cant relations to clinical sample. Internal consistency values of the scores of the three depression, anxiety, or stress symptoms (all p > .05). subscales were α = 0.82 for the concealing factor, α = 0.76 for the adjusting factor, and α = 0.71 for the tolerating factor. The inter-cor- 4. Discussion relations of the three factors were as followed (all ps 〈 0.01): r = 0.21 for concealing and adjusting, r = 0.46 for adjusting and tolerating, and This was the first study to investigate affective styles in a large r = −0.31 for concealing and tolerating. Female and male patients clinical outpatient sample using the ASQ. Although previous studies differed significantly in the ASQ subscale adjusting (F(1, 915) = 11.29; have shown that the ASQ is applicable to assess affective styles in
Table 1 Correlations of ASQ, ERQ, and DASS subscales.
ASQ-concealing ASQ-adjusting ASQ-tolerating ERQ reappraisal ERQ suppression DASS-depression DASS-anxiety
ASQ-adjusting −0.18⁎⁎ . ASQ-tolerating 0.13⁎⁎ 0.44⁎⁎ . ERQ-reappraisal 0.11⁎⁎ 0.51⁎⁎ 0.23⁎⁎ . ERQ-suppression 0.62⁎⁎ −0.04 −0.36⁎⁎ 0.07* . DASS-depression 0.18⁎⁎ −0.38⁎⁎ −0.29⁎⁎ −0.26⁎⁎ 0.29⁎⁎ . DASS-anxiety 0.06 −0.24⁎⁎ −0.22⁎⁎ −0.14⁎⁎ 0.09⁎⁎ 0.52⁎⁎ . DASS-stress −0.02 −0.44⁎⁎ −0.20⁎⁎ −0.27⁎⁎ 0.02 0.60⁎⁎ 057⁎⁎
Note: ASQ = Affective Style Questionnaire, DASS = Depression Anxiety Stress Scale, ERQ = Emotion Regulation Questionnaire. *p < .05 ⁎⁎p < .01.
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Table 2 Table 3.2 Means and standard deviations of ASQ, ERQ, and DASS subscales of affective Results of the regression analyses on anxiety, depression, and stress of the ASQ and anxiety disorders. and the ERQ subscales in anxiety disorders.
ff 2 2 A ective disorders Anxiety disorders p ηp R β tp (n = 462) Mean (n = 377) Mean (SD) (SD) Anxiety Overall 0.07 Gender −0.124 −2.372 0.018 ASQ concealing 3.02 (0.77) 2.93 (0.73) 0.079 0.004 Age 0.002 .034 0.973 ASQ adjusting 2.25 (0.73) 2.48 (0.74) <0.001 0.021 ASQ concealing 0.140 2.054 0.041 ASQ tolerating 2.87 (0.68) 2.97 (0.71) 0.083 0.004 ASQ adjusting −0.214 −3.307 0.001 ERQ reappraisal 3.46 (1.19) 3.79 (1.23) <0.001 0.015 ASQ tolerating −0.055 −0.879 0.380 ERQ suppression 3.84 (1.29) 3.71 (1.27) 0.143 0.003 ERQ reappraisal 0.000 −0.007 0.995 Depression 1.56 (0.78) 1.07 (0.73) <0.001 0.095 ERQ suppression −0.021 −0.298 0.766 Anxiety 0.87 (0.58) 0.94 (0.67) 0.104 0.003 Depression Overall 0.23 Stress 1.58 (0.66) 1.47 (0.67) 0.016 0.007 Gender −0.093 −1.942 0.053 Age −0.034 −0.736 0.462 Note: ASQ = Affective Style Questionnaire, DASS = Depression Anxiety Stress ASQ concealing 0.202 3.255 0.001 Scale, ERQ = Emotion Regulation Questionnaire. ASQ adjusting −0.320 −5.420 <0.001 ASQ tolerating −0.056 −0.988 0.324 ERQ reappraisal −0.086 −1.618 0.107 Table 3.1. ERQ suppression 0.129 1.960 0.051 Results of the regression analyses on depression, anxiety, and stress of the ASQ Stress Overall 0.18 and the ERQ subscales in affective disorders. Gender −0.132 −2.682 0.008 Age −0.051 −1.063 0.289 2 R β tp ASQ concealing 0.188 2.929 0.004 ASQ adjusting −0.379 −6.222 <0.001 Depression Overall 0.14 ASQ tolerating 0.068 1.154 0.249 Gender 0.034 0.765 0.445 ERQ reappraisal −0.092 −1.663 0.097 Age −0.050 −1.109 0.268 ERQ suppression −0.048 −0.704 0.482 ASQ concealing 0.149 2.519 0.012 ASQ adjusting −0.268 −4.724 <0.001 Note: ASQ = Affective Style Questionnaire, DASS = Depression Anxiety Stress ASQ tolerating −0.061 −1.189 0.235 Scale, ERQ = Emotion Regulation Questionnaire. ERQ reappraisal −0.100 −1.938 0.053 ERQ suppression 0.077 1.267 0.206 Anxiety Overall 0.09 the adjusting subscale (Hofmann & Kashdan, 2010). Due to double Gender −0.099 −2.145 0.033 factor loadings in the German validation study (Graser et al., 2012), the Age 0.125 2.700 0.007 item was reassigned to the concealing subscale, still showing a poor ASQ concealing 0.047 0.780 0.436 loading. The reappearance of these precarious items, which mostly ASQ adjusting −0.107 −1.836 0.067 ASQ tolerating −0.176 −3.321 0.001 show a poor factor loading (see Ito & Hofmann, 2014, Graser et al., ERQ reappraisal −0.084 −1.576 0.116 2012), suggests that these items might need to be eliminated, thereby ERQ suppression 0.016 −0.254 0.800 shortening the ASQ. Stress Overall .17 Regarding convergent validity, we found that adjusting was posi- Gender −0.031 −0.702 0.483 Age 0.002 0.036 0.971 tively correlated with ERQ reappraisal, and concealing was positively ASQ concealing 0.062 1.071 0.285 correlated with ERQ suppression. In addition, tolerating was negatively ASQ adjusting −0.387 −6.951 <0.001 correlated with ERQ suppression. These findings are in line with the ASQ tolerating −0.041 −0.811 0.418 results of previous studies (Hofmann & Kashdan, 2010; Graser et al., ERQ reappraisal −0.058 −1.149 0.251 2012) as well as with our hypothesis. Surprisingly, we did not find the ERQ suppression −0.060 −1.005 0.315 gender differences described in previous studies (Graser et al., 2012). In Note: ASQ = Affective Style Questionnaire, DASS = Depression Anxiety Stress line with the German validation study (Graser et al., 2012), we found a Scale, ERQ = Emotion Regulation Questionnaire. gender effect in the adjusting subscale, wherein male patients scored significantly higher than female patients. However, no significant dif- healthy populations (Hofmann & Kashdan, 2010; Graser et al., 2012; Ito ferences were found for the other two subscales. This inconsistent & Hofmann, 2014; Erreygers & Spooren, 2017), this was the first clin- finding highlights the need for clinical validation studies in the use of ical validation study. scales as clinical instruments instead of relying on data from normative The first aim was, therefore, to examine whether the three-factor or student samples. Additional research is needed to clarify, whether model, found in previous validation studies in Western cultures, would psychopathology might mitigate gender differences in affective styles, fit the data of our clinical sample. As we expected, the known three- and, if so, whether this effect might change in the course of treatment. factor structure of concealing, adjusting, and tolerating, emerged in our The second aim of this study was to investigate possible differences clinical German population. The model fit the data adequately, and the in affective styles across various psychological disorders. In order to goodness of fit was acceptable. This finding underlines the assumption examine a wide variety of disorders, we did not implement exclusion that the previously found deviation of the three-factor structure in a criteria. Since most outpatients met the criteria for a primary diagnosis Japanese sample might reveal cultural differences in affective styles. of either an affective or an anxiety disorder, we based our further The majority of ASQ items loaded at least moderately high onto the analysis on detecting differences between patients suffering from af- previously assigned factors. Two items on the concealing subscale (Item fective or anxiety disorders. Taking a closer look at the affective styles, 1: “People usually can't tell how I am feeling inside.” and Item 2: “I have the patients suffering from affective disorders scored significantly lower my emotions well under control.”), and two items on the tolerating on the adjusting subscale as well as on the ERQ subscale reappraisal subscale (Item 3: “I can tolerate having strong emotions.” and Item 11: than patients with anxiety disorders. These findings are in line with our “It's ok to feel negative emotions at times.”) did not show sufficient hypotheses that not only concrete emotion regulation strategies but also loadings. Previous validation studies (e.g., Ito & Hofmann, 2014; Graser affective styles differ between affective and anxiety disorders, and et al., 2012) also revealed items with poor loadings. For instance, Item furthermore, that affective disorders lead to lower scores in adjusting. 2(“I have my emotions well under control”) was originally assigned to Although this finding does not explain whether a possible deficit in
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C. Totzeck et al. adjusting might contribute to mood disorders or whether the mood reappraisal and suppression for depression, anxiety, and stress among disables the process of adjusting, there still seems to be a difference in clinical populations. adjusting skills in patients suffering from affective versus anxiety dis- ff ff orders. Further di erences in the other two a ective styles were not 5. Limitations found: Neither concealing nor tolerating differed significantly between ff ff patients su ering from a ective or anxiety disorders. A number of limitations must be taken into consideration while The third purpose of this study was to examine the associations of evaluating the present study. First and foremost, the clinical data were ff ff di erent a ective styles and psychopathology. Surprisingly, the ERQ based on primary diagnoses. We did not ascertain comorbid diagnoses. emotion regulation strategies, cognitive reappraisal and expressive This distinction may be important, since affective and anxiety disorders fi ff suppression did not show signi cant associations, neither in a ective are often linked to each other. In addition, we only used data collected nor in anxiety symptomology. However, our results revealed an inter- before the beginning of psychotherapeutic treatment and were there- ff esting pattern of associations with a ective styles: adjusting turned out fore not able to analyze changes in affective styles during and after ff to be clearly positive for patients with di erent psychopathology. The intervention. Furthermore, all data were based on self-reported in- adjusting subscale showed a strong negative association with depres- formation of patients. We did not implement either a therapeutic rating ff ff sion and with stress in patients su ering from a ective disorders. We of affective styles or physiological measures, for instance arousal, which also found that the adjusting subscale was negatively associated with could have shown whether the used strategies successfully reduce ne- ff anxiety, depression, and stress in patients su ering from anxiety dis- gative emotions. Future research should address this question. Another fi orders. This nding is in line with our hypothesis and consistent with limitation is the fact that we concentrated on the main categories of fi previous ndings in a healthy population (Ito & Hofmann, 2014). Since mental disorders and, therefore, did not subdivide patients with affec- the ASQ adjusting items assess the extent rather than the exact way, the tive and anxiety disorders in terms of their concrete diagnoses. This is of individual feels to be able to adjust (e.g., “I know exactly what to do to special importance, because there might also be differences in affective get myself into a better mood.”), further research is needed to clarify styles within the main categories. For instance, due to the very different ff the di erences of adjusting between healthy and clinical populations. moods that need to be regulated, a patient suffering from a bipolar Even though the adjusting subscale did not explain much of the var- disorder might show different affective styles than a patient suffering ff iance, the a ective style adjusting seems to play a more important role from a recurrent depressive disorder. In addition, a patient suffering than the use of cognitive reappraisal. Here, mood and anxiety disorders from social anxiety disorder might display a very different affective seem to reveal an inability to adapt to situational demands above and style than a patient suffering from general anxiety disorder, because beyond cognitive reappraisal. their anxiety symptoms are elicited differently depending on the si- In addition, concealing showed a positive association with the tuation. symptomatology: It was positively associated with depression in pa- tients suffering from affective disorders, and there was also a strong 6. Conclusions positive association of anxiety, depression, and stress in patients suf- fering from anxiety disorders. Contrary to previous findings of con- In conclusion, these results provide evidence that the ASQ is ap- cealing in a healthy population (Ito & Hofmann, 2014), and consistent plicable in clinical populations and seems to be a helpful instrument in with our hypothesis, this affective style also seems to be relevant in uncovering functional and dysfunctional affective styles. A better un- terms of the development of psychopathology, especially in anxiety derstanding of patient's initial tendency to dysregulate emotions may disorders. Concealing seems to play a more important role in anxiety contribute to an optimized treatment outcome. Future research should, disorders than in affective disorders. Although patients with anxiety therefore, assess whether affective styles change through psychother- disorders do not seem to use the concealing tendency more often or apeutic interventions, and if so, in which way. Furthermore, treatments more intensely than patients suffering from affective disorders, the could be developed directly aiming at advancing functional and redu- process of concealing still appears to be related to their anxiety symp- cing dysfunctional affective styles. These findings warrant additional tomatology. The reason for the especially maladaptive role of con- research on the use of affective styles throughout the course of psy- cealing in anxiety disorders might, at least partially, be caused by the chotherapeutic treatment. paradoxical effect of suppression increasing anxiety symptoms (Gross & Levenson, 1997; Campbell-Sills et al., 2006). However, since the ERQ Contributors suppression did not show such relations, the ASQ concealing seems to account for more maladaptive concealing behavior. Another con- All authors reviewed and approved the final manuscript. tributing factor might be the fact that concealing assesses the tendency Christina Totzeck, Tobias Teismann, and Stefan Hofmann conducted not only to suppress (e.g., “I often suppress my emotional reactions to the study design and wrote the draft of the manuscript. Ruth von things.”), but also to hide different negative emotions (e.g., “People Brachel and Verena Pflug contributed to the data assessment and data usually can't tell when I am upset.” or “People usually can't tell when I preparation. Xiao Chi Zhang conducted the statistical analyses. Jürgen am sad.”). Therefore, evaluation by others becomes more important and Margraf proofread the draft of the article. seems to determine emotional reactions. This might especially apply to All authors state their compliance with the Code of Ethics of the patients suffering from social anxiety disorders. Further research is World Medical Association (Declaration of Helsinki). They also agree to needed to clarify the exact role of concealing. the ethical standards of the Faculty of Psychology's Ethical Commission Finally, tolerating only showed a negative association with anxiety of the Ruhr-Universität Bochum. symptoms in patients suffering from affective disorders. This finding is partly in line with our hypothesis, however, we expected to find a more fl prominent role of tolerating in the psychopathology of both affective Con ict of interest and anxiety disorders. Nevertheless, this finding underlines the as- fl sumption that affective styles differ in patients suffering from affective Con icts of interest: none. and anxiety disorders. Taken together, the majority of previous emotion regulation studies Role of the funding source tend to focus on the subscales of ERQ reappraisal and suppression. The results of this present study, however, show that the ASQ adjusting and This research did not receive any specific grant from funding concealing behavior seem to play a more important role than agencies in the public, commercial, or not-for-profit sectors.
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References Gross, J.J., John, O.P., 2003. Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. J. Personal. Soc. Psychol. 85, 348–362. Abler, B., Kessler, H., 2009. Emotion regulation questionnaire – Eine deutschsprachige Hayes, S.C., Strosahl, K.D., Wilson, K.G., 1999. Acceptance and Commitment Therapy: An Fassung des ERQ von Gross & John. Diagnostica 55, 144–152. Experimental Approach to Behaviour Change. Guilford Publications, Incorporated, Aldao, A., Nolen-Hoeksema, S., Schweizer, S., 2010. Emotion-regulation strategies across New York. psychopathology: a meta-analytic review. Clin. Psychol. Rev. 30, 217–237. http://dx. Hofmann, S.G., Kashdan, T.B., 2010. The affective style questionnaire: development and doi.org/10.1016/j.cpr.2009.11.004. psychometric properties. J. Psychopathol. Behav. Assess. 32, 255–263. http://dx.doi. American Psychiatric Association (APA), 2000. Diagnostic and Statistical Manual of org/10.1007/s10862-009-9142-4. Mental Disorders, fourth ed., text rev. American Psychiatric Association, Hofmann, S.G., Sawyer, A.T., Fang, A., Asnaani, A., 2012. Emotion dysregulation model Washington, DC. of mood and anxiety disorders. Depress. Anxiety 29, 409–416. http://dx.doi.org/10. Campbell-Sills, L., Barlow, D.H., 2007. Incorporating emotion regulation into con- 1002/ da.21888. ceptualizations and treatments of anxiety and mood disorders. In: Gross, JJ (Ed.), Hu, L., Bentler, P.M., 1999. Cutoff criteria for fit indexes in covariance structure analysis: Handbook of Emotion Regulation, editor. Guilford Press, New York, pp. 542 559. – conventional criteria versus new alternatives. Struct. Equ. Model. 6, 1–55. Campbell-Sills, L., Barlow, D.H., Brown, T.A., Hofmann, S.G., 2006. Acceptability and In-Albon, T., Suppiger, A., Schlup, B., Wendler, S., Margraf, J., Schneider, S., 2008. suppression of negative emotion in anxiety and mood disorders. Emotion 6, 587–595. Validität des Diagnostischen Interviews bei psychischen Störungen (DIPS für DSM-IV- Cohen, J., 1988. Statistical Power Analysis For the Behavioral Sciences, second ed. TR). Zeitschrift für Klinische Psychologie und Psychotherapie 37, 33–42. http://dx. Lawrence Earlbaum Associates, Hillsdale, NJ. doi.org/10.1026/1616-3443.37.1.33. D'Avanzato, C., Joormann, J., Siemer, M., Gotlieb, I.H., 2013. Emotion regulation in Ito, M., Hofmann, S.G., 2014. Culture and affect: the factor structure of the Affective Style fi depression and anxiety: examining diagnostic speci city and stability of strategy use. Questionnaire and its relation with depression and anxiety among Japanese. BMC Cognit. Ther. Res. 37, 968–980. http://dx.doi.org/10.1007/s10608-013-9537-0. Res. Notes 7, 590. http://dx.doi.org/10.1186/1756-0500-7-590. ff ff ff Davidson, R.J., 1998. A ective style and a ective disorders: Perspectives from a ective Lovibond, S.H., Lovibond, P.F., 1995. Manual For the Depression Anxiety Stress Scales, neuroscience. Cognit. Emot. 12, 307–330. second. ed. Psychology Foundation, Sydney. ff Davidson, R.J., 2000. A ective style, psychopathology, and resilience: brain mechanisms Nilges, P., Essau, C., 2015. Depression, anxiety and stress scales: DASS-A screening pro- and plasticity. Am. Psychol. 55, 1196–1214. cedure not only for pain patients. Schmerz 29, 649 657. ff – Davidson, R.J., 2002. Anxiety and a ective style: role of prefrontal cortex and amygdala. Ochsner, K.N., Bunge, S.A., Gross, J.J., Gabrieli, J.D.E., 2002. Rethinking feelings: an Biol. Psychiat. 51, 68–80. fMRI study of the cognitive regulation of emotion. J. Cognit. Neurosci. 14, Dennis, T.A., 2007. Interactions between emotion regulation strategies and affective style: 1215–1229. implications for trait anxiety versus depressed mood. Motivat. Emot. 31, 200–207. Rottenberg, J., Gross, J., 2003. When emotion goes wrong: realizing the promise of af- ff Erreygers, S., Spooren, P., 2017. Factor structure of the a ective style questionnaire in fective science. Clin. Psychol. Sci. Pract. 10, 227 232. http://dx.doi.org/10.1093/ fl – emish adolescents. Psychol. Belgica 57, 112–122. http://dx.doi.org/10.5334/pb. clipsy.bpg012. 369. Schermelleh-Engel, K., Moosbrugger, H., Müller, H., 2003. Evaluating the fit of structural Graser, J., Bohn, C., Kelava, A., Schreiber, F., Hofmann, S.G., Stangier, U., 2012. Der equation models: tests of significance and descriptive goodnessof-fit measures. Affective Style Questionnaire (ASQ) : Deutsche adaption und validitäten. “ ” Methods Psychol. Res. Online 8, 23–74. Diagnostica 58 (2), 100–111. http://dx.doi.org/10.1026/0012-1924/a000056. Schneider, S., Margraf, J., 2006. Diagnostisches Interview bei Psychischen Störungen ff Gross, J.J, Levenson, R.W., 1997. Hiding feelings: the acute e ects of inhibiting negative (DIPS Für DSM-IV-TR). Springer, Berlin. and positive emotion. J. Abnorm. Psychol. 106, 95–103. Suppiger, A., In-Albon, T., Herren, C., Bader, K., Schneider, S., Margraf, J., 2008. Gross, J.J, John, O.P., 1997. Revealing feelings: facets of emotional expressivity in self- Reliabilität des Diagnostischen Interviews bei Psychischen Störungen (DIPS für DSM- reports, peer ratings, and behavior. J. Personal. Soc. Psychol. 72, 435 448. – IV-TR) unter klinischen Routinebedingungen. Verhaltenstherapie 18, 237–244. Gross, J.J., 1998. Antecedent- and response-focused emotion regulation: divergent con- http://dx.doi.org/10.1159/000169699. sequences for experience, expression, and physiology. J. Personal. Soc. Psychol. 74, 224–237. http://dx.doi.org/10.1037/0022-3514.74.1.224.
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Study 3: Affective styles in panic disorder and specific phobia: Changes through cognitive behavior therapy and prediction of remission.
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Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Prediction of Remission
Christina Totzeck Tobias Teismann Ruhr University Bochum Stefan G. Hofmann Boston University Ruth von Brachel Xiao Chi Zhang Andre Wannemüller Verena Pflug Jürgen Margraf Ruhr University Bochum
remission. The sample consisted of outpatients (N = 101) Affective styles appear to be relevant to the development of suffering from panic disorder, specific phobia, or agora- psychopathology, especially anxiety disorders. The aim of phobia who completed the Affective Style Questionnaire the current study was to investigate changes in affective (ASQ) before and after therapy, as well as at a 6-month styles in patients with panic disorder and specific phobia, as follow-up assessment. Multivariate analyses of variance a result of undergoing cognitive-behavioral therapy, and to were conducted to test for changes due to therapy. Logistic identify a possible link between certain affective styles and regression analyses were calculated to test for the impact of affective styles on remission from anxiety disorders, and hierarchical regression analyses were calculated to examine This research did not receive specific grants from funding agencies in the association between changes in affective styles and the public, commercial, or not-for-profit sectors. Stefan G. Hofmann symptom reduction. Results indicated significant increases receives financial support from the Alexander von Humboldt on the ASQ subscales adjusting and tolerating after therapy. Foundation (as part of the Humboldt Prize), NIH/NCCIH (R01AT007257), NIH/NIMH (R01MH099021, U01MH108168), Concealing did not decrease significantly after therapy. In and the James S. McDonnell Foundation 21st Century Science Initiative addition, higher scores on adjusting significantly predicted in Understanding Human Cognition—Special Initiative remission from anxiety disorders. Finally, we found a (JSMF#220020479.01). He receives compensation for his work as editor from SpringerNature and the Association for Psychological significant association between increases on the adjusting Science, and as an advisor from the Palo Alto Health Sciences and for scale and the reduction of anxiety symptoms. his work as a subject matter expert from John Wiley & Sons, Inc. and SilverCloud Health, Inc. Support by the Alexander von Humboldt Professorship awarded to JürgenMargrafbytheAlexandervon Humboldt Foundation is gratefully acknowledged. Keywords: affective styles; panic disorder; specific phobia; Affective ⁎ Address correspondence to Christina Totzeck, Department of Style Questionnaire Psychology and Psychotherapy, Ruhr University Bochum, Massen- bergstrasse 11, 44787 Bochum, Germany; e-mail: christina. [email protected]. FEELINGS OF ANGER TOWARD ce:smallaps]a friend or a 0005-7894/© 2019 Association for Behavioral and Cognitive Therapies. partner, feelings of fear of a spider on the wall, or of Published by Elsevier Ltd. All rights reserved. sadness saying good-bye to someone—every human
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
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2 totzeck et al. being is confronted with the necessity to regulate true for patients suffering from panic disorder or such negative emotions on a daily basis. However, specific phobia. Tolerating appears to play a less individuals vary widely, not only in the speed and in important role: a negative association with anxiety the intensity of emotional reactions to these kinds of symptoms was found only in patients suffering environmental challenges, but also in the use of from mood disorders (Totzeck et al., 2018). These regulatory strategies to handle these emotions findings point to intriguing diagnostic differences in (Dennis, 2007). Whereas some people can easily affective styles. Tolerating might play a more tolerate feeling sad or anxious, others experience important role in panic disorder and agoraphobia, these emotions as intolerable and immediately possibly due to the inability to tolerate the intense engage in avoidance, concealment, or other mal- physical sensations associated with anxiety adaptive response-focused strategies (Gross & (Margraf & Schneider, 2009). John, 2003). This broad range of individual Although these affective styles are part of the sensitivity and responsiveness is referred to as processes targeted by modern cognitive-behavioral affective style (Davidson, 1998, 2000, 2002; therapy (CBT; Ito & Hofmann, 2014), no study has Hofmann, Sawyer, Fang, & Asnaani, 2012). specifically examined a resultant change of these Emotion researchers have described several three affective styles in patients suffering from affective styles for regulating emotions (Hofmann anxiety disorders undergoing treatment. Moreover, & Kashdan, 2010; Hofmann et al., 2012; Mennin, so far, no study has been conducted to examine Heimberg, Turk, & Fresco, 2002). So far, three whether the three affective styles—concealing, main styles are commonly distinguished, based on adjusting, and tolerating—are substantially alter- Gross’s (1998) process model of emotion regula- able in the first place. Previous studies have tion: concealing, adjusting, and tolerating described the individual’s affective style rather as (Hofmann et al., 2012). The concealing style atemperamentalandtrait-likevariable(e.g., includes suppression and other response-focused Davidson, 1992; Davidson & Tomarken, 1989; strategies aimed at concealing and avoiding emo- Wheeler, Davidson, & Tomarken, 1993). The tions after they arise. The adjusting style encom- present investigation addresses the paucity of passes the modulation of negative emotions as research in this field by examining the variability needed in a particular context by balancing and of affective styles in relation to psychological successfully readjusting emotional experience and treatment. Examining the short- and long-term expression as needed. The tolerating style refers to effects of treatment on affective styles could lead to an accepting and nondefensive response to arousing improved intervention strategies for anxiety disor- emotional experiences as they exist in the present ders. As the goal of exposure exercises within CBT moment. This third style, including acceptance is the prevention of the manifestation of avoidant strategies, allows tolerance of strong emotions. patterns (Abramowitz, Deacon, & Whiteside, Individual affective style can be measured using 2011; Barlow et al., 2011; Craske, Treanor, the Affective Style Questionnaire (ASQ; Hofmann Conway, Zbozinek, & Vervliet, 2014), allowing & Kashdan, 2010), a 20-item scale consisting of the patients the experience of the entire range of three subscales that correspond to these affective emotional reactions, affective styles should be styles. A clinical validation study of the ASQ measurably influenced by treatment. Furthermore, suggests that affective styles play an important CBT aims to reduce anxiety symptoms by prevent- role in patients with mental disorders (Totzeck et ing maladaptive concealing styles and by promoting al., 2018). Among patients with anxiety disorders, more adaptive adjusting and tolerating styles (Ito & this study revealed that adjusting was negatively Hofmann, 2014). Whether this indeed does occur associated with depression, anxiety, and stress in an anxiety-disordered population undergoing symptoms. This suggests that patients suffering CBT is examined in the present study. from anxiety disorders have problems with suc- When examining a possible change in affective cessfully adapting to the situational demands in styles through therapy, the question arises as to order to reduce fear, anxiety, or other negative whether a specific affective style might also be emotions. Furthermore, concealing was found to be associated with therapy outcome. So far, little is positively associated with depression, anxiety, and known about consistent predictive factors contrib- stress symptoms among patients suffering from uting to successful treatment outcomes in anxiety anxiety disorders. In addition to avoiding emotions, disorders. For instance, variables such as symptom concealing also involves hiding negative emotions severity, depressive symptoms, or anxiety sensitiv- in front of others. Because the sample in the ity, in past research, have mostly led to inconsistent previous study consisted of patients with a variety predictions of remission from panic disorder or of anxiety disorders, it is unclear whether this is also agoraphobia (Porter & Chambless, 2015). The
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
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affective styles in panic disorder and specific phobia 3 results of the study by Porter and Chambless recruited at our outpatient clinic in the Ruhr region (2015), however, show that avoidance behavior in Germany. They were offered participation if they assessed prior to therapy significantly predicts met the following criteria: (a) Diagnostic and remission from panic disorder and agoraphobia Statistical Manual of Mental Disorders, Fourth after treatment termination. These findings might Edition (DSM-IV; American Psychiatric suggest that one’s individual tendency to regulate Association, 2000) criteria for panic disorder with negative emotions also contributes to treatment agoraphobia, agoraphobia without a history of outcome. The further aims of the present study are, panic disorder, specific phobia; (b) the anxiety therefore, to explore the role of affective styles in disorder was considered to be the most severe the prediction of remission from anxiety disorders disorder if comorbid disorders were present; (c) as well as to examine the association between a 18–70 years of age; (d) not meeting DSM-IV criteria change in affective styles and reduction of anxiety for psychosis, mania, current substance abuse/ symptoms. dependency; (e) no concurrent psychological or In line with previous findings (e.g., Gross & John, psychopharmacological treatment; and (f) no sui- 2003), a German ASQ validation study revealed cide ideation/behavior in need of immediate treat- that men tend to use the concealing style more often ment. Prior to treatment, participants gave written than women (Graser et al., 2012). In addition, and informed consent. The study was approved by results indicated significantly higher scores in men the Ethics Committee of the Faculty of Psychology in adjusting and significantly higher scores in at the Ruhr University Bochum. women in tolerating (Graser et al., 2012). The same gender differences were also found in the participants Belgian ASQ validation study using an adolescent A total of n = 182 outpatients (mean age: M = population (Erreygers & Spooren, 2017). Howev- 36.63, SD = 11.82; 121 female [66.5%]) fulfilled er, within the clinical population, the only gender inclusion criteria in the pretreatment assessment; effect was found in adjusting with male patients n = 145 of them (mean age: M = 36.93, SD = 12.24; scoring higher than female patients (Totzeck et al., 99 female [68.3%]) completed therapy and took 2018). Based on these inconsistent findings, the part in posttreatment assessment; and n = 101 present study also serves to explore possible gender (mean age: M = 37.11, SD = 12.73; 68 female differences in concealing, adjusting, and tolerating [67.3%]) of these attended follow-up assessment. in patients suffering from anxiety disorders, and Since we were interested in long-term changes in furthermore, whether these differences are affected affective styles, only patients with complete data by treatment. sets including follow-up data were considered in the Taken together, the paucity of research on analysis. The current sample did not differ signif- affective styles and possible changes through CBT icantly from the full patient sample in age, F(1, 281) points to the need for more in-depth research. The = 0.01, p = .908, distribution of gender, F(1, 281) = present study is a partially exploratory examination 0.02, p = .886, or diagnoses, F(1, 281) = 0.18, p = with the following four hypotheses and questions: .685, nor in symptom severity, F(1, 281) = 0.18, p = We predicted that (a) CBT increases the use of .672, or ASQ scores (all p values N .40). adjusting and tolerating, and decreases the use of Age at baseline ranged from 19 to 65 years (M = concealing; (b) in addition, we aimed to investigate 37.11, SD = 12.73), and 67.3% (n = 68) of the whether concealing, adjusting, and tolerating might sample were female. At the pretreatment assess- predict a remission from anxiety disorders; (c) ment, 57 patients (56.4%) suffered from panic moreover, we aimed to examine whether a possible disorder with agoraphobia, 5 (5.0%) from agora- change in affective styles might be associated with a phobia without history of panic disorder, and 39 reduction of anxiety symptoms; and (d) last, we (38.6%) from specific phobia, predominantly of the intended to explore gender differences in affective animal (n = 11; 10.9%) and environmental (n = 10; styles and whether these differences might change in 9.9%) subtype. Thirty-five patients (33%) suffered the course of treatment. from at least one comorbid diagnosis (see Table 1). The most common comorbid diagnosis was another Methods specific phobia (n = 19; 18.8%) followed by social The current study is a secondary analysis of a study phobia (n = 8; 7.9%). Comorbid diagnoses ranged on genetic factors in exposure treatments for panic from a minimum of one (n = 35; 33%) to a disorder, agoraphobia, and specific phobia maximum of three additional diagnoses (n = 1). (Roberts et al., 2017). Treatments included in the This rather low comorbidity rate was in part due to current analysis were conducted between December the inclusion and exclusion criteria of the primary 2011 and October 2015. All participants were study on genetic factors in exposure treatment. All
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
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4 totzeck et al.
Table 1 Primary and Comorbid Disorders at Pretherapy Assessment First diagnosis Second diagnosis Third diagnosis Fourth diagnosis N (%) N (%) N (%) N (%) Panic disorder with agoraphobia 57 (56.4) 1 (1.0) - - Specific phobia 39 (38.6) 19 (18.8) 4 (4.0) - Agoraphobia 5 (5.0) - - - Social phobia - 8 (7.9) - - Major depressive disorder - 3 (3.0) 4 (4.0) 1 (1.0) Hypochondriasis - 2 (2.0) 1 (1.0) - Panic disorder without agoraphobia - 1 (1.0) - - Bulimia nervosa - 1 (1.0) - - Insomnia - - 2 (2.0) - Generalized anxiety disorder - - 1 (1.0) - Dysthymia - - 1 (1.0) - Somatoform disorder - - 1 (1.0) - Posttraumatic stress disorder - - - - Overall 101 (100) 35 (33.0) 14 (13.9) 1 (1.0) Note. Comorbid diagnoses were not ordered by severity or impairment.
participants were Caucasian. Diagnoses were made situational exposure exercises. All therapists were by trained clinical psychologists with a master’s trained psychologists with a CBT orientation and degree using a structured diagnostic interview (see had M = 3.57 years (SD = 1.47, range: 1–5 years) of below) for mental disorders. The diagnostic inter- experience in conducting CBT. All of them were view was conducted at all three assessments, prior trained in conducting exposure-based CBT for to and after therapy as well as during follow-up panic disorder, agoraphobia, and specific phobia assessment. Posttherapy, n = 68 patients (67.3%) prior to participating in the active phase of no longer met the criteria for primary anxiety treatment. Furthermore, psychotherapists were disorder. N = 40 patients (70.2%) with panic supervised once weekly by a senior psychotherapist, disorder, n = 26 patients (66.7%) with specific to ensure treatment adherence. In order to provide phobia, and n = 2 patients (40.0%) with agora- supervision, all therapy sessions were videotaped. phobia achieved remission. At follow-up assess- ment n = 66 of those patients (65.3%) retained remission (n = 39 patients (68.4%) with panic MEASURES disorder, n = 24 patients (61.5%) with specific Diagnostic Interview phobia, and n = 3 patients (60.0%) with agora- Diagnoses were made using the Diagnostisches phobia. Interview bei Psychischen Störungen (DIPS; Schneider & Margraf, 2011), a structured clinical TREATMENT interview to assess mental disorders according to All patients received exposure-based treatment the criteria of the DSM-IV (American Psychiatric according to a treatment manual by Teismann Association, 2000). The results of previous valida- and Margraf (2018),whichisbasedonthe tion studies using the DIPS indicate high interrater treatment manual by Craske, Antony, and Barlow reliability. According to Landis and Koch (1977),a (2006). Whereas the treatment by Craske et al. coefficient score (Cohen’s kappa coefficient [κ]) (2006) is a 12-week program, the manual by between .61 and .80 can be seen as “substantial Teismann and Margraf is delivered in the form of agreement.” The interrater reliability of the major 25 weekly sessions. Because the health care diagnostic category of anxiety disorders (κ = .78), insurance system in Germany allows 25 therapy as well as the retest reliability coefficient scores (κ = sessions as short-term therapy, more therapist- .76 for anxiety disorders) are, therefore, both high guided exposure exercises were conducted here (In-Albon et al., 2008; Suppiger et al., 2008). All than in the treatment by Craske et al. (2006). assessments were videotaped; each diagnosis was Therapy was administered in one-to-one sessions made by a DIPS-certified psychotherapist and was that lasted 50 minutes (M = 22.68 sessions; SD = also verified through supervising senior psycho- 9.1). Treatment included psychoeducation on the therapists. Furthermore, the assessors of posttreat- nature of anxiety as well as interoceptive and ment and follow-up interviews were blinded.
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
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affective styles in panic disorder and specific phobia 5
Affective Style Questionnaire (MANOVA) for repeated measures were computed: The ASQ (Hofmann & Kashdan, 2010; German The three experimental times (Time 1 = pretherapy, version: Graser et al., 2012) is a 20-item scale, Time 2 = posttherapy, Time 3=follow-upassessment) measuring the three affective styles—concealing served as independent within-subjects variables and (e.g., “I often suppress my emotional reaction to the three ASQ subscales (concealing, adjusting, and things”), adjusting (e.g., “I know exactly what to tolerating) as dependent variables. In order to analyze do to get myself into a better mood”), and gender differences, gender was added as a between- tolerating (e.g., “Icantoleratehavingstrong subjects factor in further analyses. emotions”)—on 5-point Likert scales ranging Homogeneity of error variances was tested using from 1 (not true of me at all) to 5 (extremely true the Mauchly test for sphericity. In case of significant of me). The factor structure and validity of the ASQ results of the Mauchly test, a Greenhouse-Geisser have been examined in several different countries, correction was conducted. The level of significance including the United States (Hofmann & Kashdan, was set as p b .05 (two-tailed). Partial η2 was 2010), Germany (Graser et al., 2012; Totzeck et al., calculated as an estimate of effect size. According to 2018), Japan (Ito & Hofmann, 2014), and Belgium Cohen (1988, 1992) a partial η 2 of .01 can be (Erreygers & Spooren, 2017). The results of these viewed as small, .06 as medium, and .14 as large effect. studies supported the utility of the ASQ in healthy As effect size for further pairwise comparisons, samples of the general population. In the clinical Cohen’s d was calculated with d of 0.2 being a sample, the internal consistency values (Cronbach’s small, 0.5 being a medium, and 0.8 being a large effect. alpha [α]) of the scores of the ASQ subscales were α In order to test for a possible link between = .82 for the concealing factor, α = .76 for the affective styles and remission, logistic regression adjusting factor, and α = .71 for the tolerating analyses with ASQ subscales as predictor variables factor (Totzeck et al., 2018). According to and remission (yes/no) as criterion were calculated. Nunnally (1978), a score of at least α = .70 can Linearity of the logit assumption was tested; all be seen as acceptable. In the current sample, the interaction terms were not significant (all p N .05; consistency value scores for the three subscales were Hosmer & Lemeshow, 1989). In addition to α = .85 (concealing), α = .80 (adjusting), and α = .70 gender, we also took into account age and primary (tolerating). diagnosis, as well as anxiety levels (BAI scores) to control for other possible contributing factors. No Beck Anxiety Inventory violation of the multicollinearity assumption was The Beck Anxiety Inventory (BAI; Beck, Epstein, found as all variance inflation factor (VIF) values Brown, & Steer, 1988; German version: Margraf & were b5(Urban & Mayerl, 2006). Ehlers, 2007) is a 21-item scale, measuring the Furthermore, two separate hierarchical regres- severity of symptoms (e.g., “heart pounding/rac- sion analyses were conducted with gender, age, ing” or “numbness or tingling”) on a 4-point Likert primary diagnosis, and BAI scores in Step 1 and the scale ranging from 0 (not at all) to 3 (severely—it change scores of the three ASQ subscales (post- bothered me a lot). The German version of the BAI minus pretherapy assessment; follow-up minus has just recently been shown to possess good posttherapy assessment) added in Step 2 to psychometric properties (Geissner & Huetteroth, determine the association with symptom reduction 2018). Consistency value score for the BAI was α = (BAI scores post- minus pretherapy assessment; .94 in the current sample. follow-up minus posttherapy assessment). PROCEDURE Results After signing informed consent, all patients were CHANGES OF AFFECTIVE STYLES THROUGH assessed by structured interview to determine the TREATMENT presence of primary anxiety disorder as well as to AsignificantmultivariateeffectoftimeonASQ screen for comorbid and excluded psychiatric subscales, F (2, 99) = 12.50, p b .001; Wilks’s λ =.798; disorders. Before and after their therapeutic treat- 2 ηp =.20,wasfound.Significantchangesofaffective ment as well as at follow-up assessment 6 months styles throughout treatment were found for adjusting, after therapy, all patients completed both the ASQ 2 F (2, 99) = 12.32, p b .001; Wilks’s λ =.801;ηp =.20, and BAI questionnaires. and tolerating, F (2, 99) = 12.98, p b .001; Wilks’s λ = 2 Data Analysis .792; ηp =.21,butnotforconcealing, F (2, 99) = 0.65, 2 The Statistical Package for the Social Sciences (SPSS, p =.524;Wilks’s λ =.798;ηp =.01.Furtherpairwise version 24.0) was used to analyze the research data. comparisons between pre- versus posttreatment and In order to assess the psychotherapeutic effect on posttreatment versus follow-up assessment data were affective styles, multivariate analyses of variance conducted. Results are presented in Table 2.
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
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Table 2 Mean Differences, Standard Errors, and P Values of ASQ Subscale Changes Between Pre- and Postttherapy as Well as Between Posttherapy and Follow-Up Assessment ASQ subscales Time Mean difference Standard error p 95% CI Cohen’s d Concealing 1 2 .040 .047 1.000 [–.073, .154] .05 2 3 .011 .042 1.000 [–.092, .114] -.01 Adjusting 1 2 -.255⁎ .059 b.001 [–.398, –.113] .33 2 3 -.034 .054 1.000 [–.165, .098] .05 Tolerating 1 2 -.287⁎ .057 b.001 [–.425, –.149] .50 2 3 .051 .045 .770 [–.058, .160] .02 Note: ASQ = Affective Style Questionnaire; Time 1 = pretherapy assessment; Time 2 = posttherapy assessment; Time 3 = follow-up assessment; CI = confidence interval.
Adjusting (p b .001, d = .33) and tolerating (p b ASSOCIATIONS OF THE CHANGES IN AFFECTIVE .001, d = .50) both significantly increased from pre- STYLES WITH REDUCTION OF ANXIETY SYMP- to posttherapy. No further changes in adjusting and TOMS tolerating between posttherapy and follow-up The first hierarchical regression analysis revealed that at assessment were found (all p values N .58). Step 1, the baseline BAI score contributed significantly to Concealing did not decrease significantly in either the reduction of BAI scores, F(4, 95) = 37.97, pb .001, the pre- versus posttherapy or the posttherapy and accounted for 60% of the variation in anxiety versus follow-up comparison (both p = 1.0). symptom reduction. Introducing the change scores of the three ASQ variables at Step 2 explained an additional PREDICTION OF REMISSION FROM ANXIETY DIS- 7% of variation in anxiety symptom reduction and this ORDERS change in R2 was significant, F(7, 92) = 23.45, pb .001. The results of the two logistic regression analyses The results are presented in Table 4a. are shown in Table 3.Neithergender,age, The results of the second hierarchical regression diagnosis, pretherapy BAI score, nor concealing or analysis are presented in Table 4b. They showed tolerating predicted posttherapy remission. The that at Step 1, the BAI score at posttherapy only significant effect was found for adjusting (p = assessment contributed significantly to the reduc- .043): A higher pretherapy adjusting score signifi- tion of BAI scores at follow-up, F(4, 94) = 16.81, p cantly predicted remission from anxiety disorders = .047), and accounted for 40% of the variation in posttherapy. anxiety symptom reduction. Introducing the change The only significant prediction of follow-up scores of the three ASQ variables at Step 2 did not remission was found for posttherapy BAI score explain additional variation in anxiety symptom (p = .048): A lower BAI score at posttherapy reduction (all p values N .05). assessment significantly predicted remission from anxiety disorders at the follow-up assessment 6 GENDER DIFFERENCES IN THE THREE AFFECTIVE months after treatment. None of the other post- STYLES therapy scores served as significant predictors of A significant interaction between gender and the remission (all p values N .16). ASQ subscales was found, F(2, 98) = 3.64, p= .030
Table 3 Results of the Logistic Regression Analyses Pre- to Posttherapy and Posttherapy to Follow-Up Pre- to posttherapy Posttherapy to follow-up Regression coefficient (β) p OR 95% CI Regression coefficient (β) p OR 95% CI Gender .173 .733 1.189 [.440, 3.215] .008 .988 1.008 [.356, 2.850] Age -.016 .399 .985 [.950, 1.021] .005 .786 1.005 [.968, 1.044] Diagnosis .002 .983 1.002 [.871, 1.151] -.040 .531 .961 [.850, 1.088] BAI -.011 .628 .989 [.948, 1.033] -.059 .048 .942 [.889, .999] ASQ concealing .055 .865 1.056 [.561, 1.987] .380 .268 1.462 [.746, 2.864] ASQ adjusting .813 .043 2.254 [1.025, 4.953] .519 .160 1.680 [.815, 3.463] ASQ tolerating -.519 .299 .595 [.224, 1.585] .388 .501 1.474 [.477, 4.555] Note. OR = odds ratio; CI = confidence interval; BAI = Beck Anxiety Inventory; ASQ = Affective Style Questionnaire.
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
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affective styles in panic disorder and specific phobia 7
Table 4a Results of the Hierarchical Regression Analysis for Pre- to Posttherapy Changes β tpR2 Adjusted R2 Step 1 Gender -.13 -1.95 .059 .615 .599 Age -.00 -.03 .975 Diagnosis .04 .52 .603 BAI -.75 -10.38 b.001 Step 2 Gender -.17 -1.81 .074 .681 .674 Age -.02 -.33 .744 Diagnosis .05 .63 .530 BAI -.69 -9.37 b.001 Change in concealing -.08 -1.28 .204 Change in adjusting .15 2.15 .034 Change in tolerating -.02 -.26 .795 Note. Dependent variable: change score BAI = Beck Anxiety Inventory.
2 (ηp = .07). The results of further pairwise compar- rate of CBT studies on anxiety disorders (53% for isons revealed a significant difference between completers at posttreatment; see the meta-analysis female and male patients in concealing at all three by Springer, Levy, & Tolin, 2018). The remission assessments, in that male patients scored signifi- was mostly stable throughout follow-up assessment cantly higher than female patients. No significant 6 months after therapy, except for two patients difference was found in adjusting or tolerating (all showing relapses. p values N .06). The results are presented in Table 5. We initially hypothesized that CBT would increase the use of adjusting and tolerating and Discussion decrease the use of concealing. Although our results The main purposes of the present study were to did not reveal a significant decrease in concealing, investigate whether the three affective styles— both of the other affective styles increased signifi- concealing, adjusting, and tolerating—change over cantly according to our hypotheses. These findings time in patients suffering from anxiety disorders are partly in line with our predictions and reveal and undergoing CBT, and whether specific affective that therapy appears to change the individual styles can predict remission from disorders. With affective styles. Both adjusting and tolerating two thirds of the treated patients showing a full increased after therapy in patients suffering from remission from anxiety disorders after therapy, the panic disorder, agoraphobia, and specific phobia. rates are slightly higher than the overall remission Since psychophysiological and cognitive models
Table 4b Results of the Hierarchical Regression Analysis for Posttherapy to Follow-Up Changes β tpR2 Adjusted R2 Step 1 Gender .03 .35 .723 .428 .417 Age -.05 -.60 .547 Diagnosis -.09 -.95 .345 BAI -.68 -7.37 b.001 Step 2 Gender .01 .13 .896 .447 .418 Age -.03 -.41 .686 Diagnosis .11 1.16 .249 BAI -.64 -6.90 b.001 Change in concealing .09 1.07 .285 Change in adjusting -.16 -1.83 .070 Change in tolerating -.02 -.27 .790 Note. Dependent variable: change score BAI = Beck Anxiety Inventory.
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
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8 totzeck et al.
Table 5 Gender Differences in the ASQ Subscales Pre- and Posttherapy as Well as During Follow-Up Assessment Time Subscales Gender Mean Standard score error p ηp2 Pretherapy Concealing Women 2.73 .088 .004 .08 Men 3.17 .126 Adjusting Women 2.75 .091 .232 .01 Men 2.94 .131 Tolerating Women 3.23 .072 .775 .00 Men 3.19 .103 Posttherapy Concealing Women 2.70 .084 .006 .07 Men 3.11 .121 Adjusting Women 2.96 .094 .064 .03 Men 3.27 .135 Tolerating Women 3.49 .063 .820 .00 Men 3.52 .090 Follow-up Concealing Women 2.69 .083 .007 .07 Men 3.09 .119 Adjusting Women 3.05 .085 .345 .00 Men 3.19 .122 Tolerating Women 3.46 .062 .704 .00 Men 3.42 .089
posit exaggerated appraisal of threat being a core We did not find any changes in affective styles element underlying pathological anxiety (Beck & between posttherapy and follow-up assessment, Haigh, 2014; Clark & Beck, 2010; Margraf & which suggests that affective styles are relatively Ehlers, 1989), it is reasonable to expect that a stable individual traits. The development of the successful treatment should be closely linked to ASQ was to some extent based on the studies on improved adjusting in response to situational emotion regulation by Gross and colleagues (e.g., demands. Analogue to the improved adjusting, a Gross & John, 1997, 2003), showing convergent strengthened ability to tolerate fear, anxiety, and other validity with the Emotion Regulation Question- negative emotions should be, though not always naire (ERQ; Gross & John, 2003), which is a state directly addressed, one of the goals of exposure measure (see Hofmann & Kashdan, 2010). Habitual exercises. The increase of tolerating after therapy affective styles, especially adjusting, appear to be more found in this study fits into this assumption. associated with psychopathology than situation- Our results did not reveal a significant decrease of specific and state-dependent emotion regulation concealing after therapy. This result is in contrast to strategies (Totzeck et al., 2018). Future research our hypothesis, as we have expected that the rather should further examine the role of habitual affective maladaptive concealing tendency would decrease styles and situation-specificemotionregulationstrat- through therapy. However, the effect of concealing egies in psychopathology and treatment. might be less relevant in patients suffering from In addition, we aimed to investigate whether panic disorder, agoraphobia, or specific phobia. concealing, adjusting, and tolerating might predict Since the ASQ subscale concealing not only implies remission from anxiety disorders. For prediction of suppressing negative emotions (e.g., “Ioften remission, neither concealing nor tolerating seemed suppress my emotional reactions to things”) but to play an important role, overall. However, we did also hiding negative emotions in front of others find that the adjusting style assessed prior to (e.g., “People usually can’t tell how I am feeling therapy appeared to be a significant predictor of inside”), concealing might play a more important remission from anxiety disorders after therapy. The role in social anxiety disorders, where patients aim ability to adjust to situational demands in order to to hide negative emotions in social contexts handle negative emotions (e.g., “I can get out of a (Hofmann, 2007). This assumption should be bad mood very quickly”), therefore, seems to addressed in further research. contribute to successful treatment outcome. This
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
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affective styles in panic disorder and specific phobia 9 ability could impact the compliance of patients and Spooren, 2017; Graser et al., 2012). In order to consequently their motivation, their own expecta- interpret these inconsistent findings, cutoff scores of tion to succeed, or simply reveal a higher flexibility the ASQ subscales would be a helpful addition to a to change cognitions and behavior. The same future study. Unfortunately, cutoff scores for the prediction from therapy termination to follow-up three affective styles have not been gathered to date. assessment, wherein only the BAI score served as However, on the descriptive level, our patients’ predictor, was not found. sample shows smaller mean scores compared to the We, furthermore, aimed to examine whether a healthy German population (Graser et al., 2012), possible change in affective styles might be associ- even after therapy. Since other factors, such as age ated with a reduction of anxiety symptoms. In or educational background, might play an impor- addition to the important role of the symptom tant role, further research should address these severity as assessed with the BAI score, our results questions. An examination of differences in affec- also suggest that those patients, who were able to tive styles in psychotherapy patients, as compared increase their adjusting to a greater extent, benefit- to a healthy population, might help investigators to ed more from therapy and experienced greater further understand not only the gender differences symptom reduction. Contrary to this result, an but also the adaptive and maladaptive functioning increase in adjusting was not associated with a of affective styles. Interestingly, on the descriptive reduction of anxiety symptoms at follow-up assess- level, our patients’ sample scores higher in adjusting ment 6 months after treatment termination. Unfor- and tolerating and lower in concealing than the tunately, these results do not enable further previously investigated patients’ sample with anx- conclusions about the potential cause–effect rela- iety disorders (Totzeck et al., 2018). Further tionship. However, the exact role of adjusting for research is needed to clarify whether this might be treatment success should be investigated in further due to the form of anxiety disorder or other factors, therapy studies, which should also assess whether such as the symptom severity. these effects might be different in other forms of In conclusion, despite the inherent relationship treatment. For instance, it might be interesting to between anxiety disorders and emotion regulation examine whether mindfulness-based or acceptance deficits, there is a relative lack of studies examining and commitment therapy (ACT) causes a greater the effects of treatment on affective styles within increase of tolerating than traditional CBT. clinical samples of anxiety disorders. To our Finally, we aimed to investigate gender differ- knowledge, this is the first study exploring changes ences in affective styles and, furthermore, whether in the three affective styles of concealing, adjusting, these differences might change in the course of and tolerating in patients undergoing CBT, overall. treatment. In contrast to previous findings (Errey- Since this body of research is quite new, more data gers & Spooren, 2017; Graser et al., 2012), we did will be needed to determine the ultimate utility of not find gender differences on all three of the incorporating functional and dysfunctional affec- affective styles. The only significant difference was tive styles into theories of anxiety disorders. found for concealing, where male patients scored higher than female patients. This difference was LIMITATIONS invariant throughout all three assessments, prior The following limitations must be taken into and after therapy, as well as at assessment 6 months consideration while evaluating the present study. after therapy. Neither of the other affective styles First of all, we did not have a control group in this differed between female and male patients at any study. This, unfortunately, prohibits further com- assessment. It is, therefore, assumable that psycho- parisons between changes in affective styles in pathology, especially anxiety disorders, might people who are and are not undergoing treatment. mitigate gender differences in affective styles. Second, our patient sample was based on panic Conceivably, the intensity of emotions perceived disorder, agoraphobia, and specific phobia and by patients with anxiety disorders might contribute was, therefore, quite homogeneous. Because we did to this effect. Whereas in healthy populations, men not include other forms of anxiety disorders, our and male adolescents tend to use adjusting more results cannot be generalized. This limitation is often than women and female adolescents (Errey- underlined by the fact that the comorbid depressive gers & Spooren, 2017; Graser et al., 2012), in an disorder rate as well as the range of other disorders, anxiety-disordered population, this difference does such as generalized anxiety disorder, were rather low. not appear. Further, female patients suffering from This might be due to the fact that the patients were anxiety disorders do not use tolerating more often recruited for the primary study on genetic factors in than male patients, although this effect has exposure treatments. Furthermore, we excluded been found in healthy populations (Erreygers & patients with concurrent psychopharmacological
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10 totzeck et al. treatment. Further studies will be needed to test for Unified protocol for transdiagnostic treatment of emotional effects in other forms of anxiety disorders and also in disorders: Therapist guide. New York, NY: Oxford University Press. samples with higher comorbidity of depressive and Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988). An other disorders. Additionally, the results should be inventory for measuring clinical anxiety: Psychometric interpreted with caution because no adjustments of properties. Journal of Consulting and Clinical Psychology, the family-wise error rate were conducted. Third, we 56, 893–897. https://doi.org/10.1037/0022-006X.56.6.893 did not ascertain the past treatment history in detail. Beck, A. T., & Haigh, E. A. (2014). Advances in cognitive theory and therapy: The generic cognitive model. Annual This might also be a contributing factor, because Review of Clinical Psychology, 10 ,1–24. https://doi.org/10. patients with a treatment history might have already 1146/annurev-clinpsy-032813-153734 increased their ability to adjust or tolerate due to Clark, D. A., & Beck, A. T. (2010). Cognitive theory and previous interventions. Fourth, we did not implement therapy of anxiety and depression: Convergence with amidtherapyassessment.Futureresearchshould neurobiological findings. Trends in Cognitive Sciences, 14 , 418–424. https://doi.org/10.1016/j.tics.2010.06.007 address these questions in order to examine a possible Cohen, J. (1988). Statistical power analysis for the behavioral mediating role of affective styles on therapy outcome. sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Furthermore, this could also help to examine whether Cohen, J. (1992). A power primer. Psychological Bulletin, 112 , those patients who do not complete treatment are 155–159.http://psycnet.apa.org/doi/10.1037/0033-2909. individuals who have more difficulties modifying their 112.1.155. Craske, M. G., Antony, M. M., & Barlow, D. H. (2006). affective styles. Fifth, the lack of gender differences in Mastering your fears and phobias: Therapist guide (2nd ed.). adjusting and tolerating might also be due to low New York, NY: Oxford University Press. https://doi.org/10. statistical test power. The conducted power analyses 1093/med:psych/9780195189179.001.0001 resulted in adequate power for the main associations, Craske, M. G., Treanor, M., Conway, C., Zbozinek, T., & except for the analysis of gender effects. Further Vervliet, B. (2014). Maximizing exposure therapy: An inhibitory learning approach. Behaviour Research and therapy studies with greater sample sizes, and Therapy, 58 , 10–23. https://doi.org/10.1016/j.brat.2014. especially more male patients, should investigate 04.006 possible gender differences. Last, we did not assess Davidson, R. J. (1992). Emotion and affective style: Hemi- treatment adherence psychometrically. This is also a spheric substrates. Psychological Science, 3, 39–43. https:// limiting factor with regardtotheinterpretationof doi.org/10.1111/j.1467-9280.1992.tb00254.x Davidson, R. J. (1998). Affective style and affective disorders: therapeutic effects on changes of affective styles Perspectives from affective neuroscience. Cognition and through treatment. Emotion, 12 , 307–330.http://psycnet.apa.org/doi/10.1080/ 026999398379628. CONCLUSIONS Davidson, R. J. (2000). Affective style, psychopathology, and The findings of the present study emphasize the resilience: Brain mechanisms and plasticity. American Psychologist, 55, 1196–1214.http://psycnet.apa.org/doi/10. interaction between affective styles and anxiety 1037/0003-066X.55.11.1196. disorders. Furthermore, examining changes in Davidson, R. J. (2002). Anxiety and affective style: Role of affective styles due to CBT might provide a new prefrontal cortex and amygdala. Biological Psychiatry, 51, approach to identifying and understanding behav- 68–80. https://doi.org/10.1016/S0006-3223(01)01328-2 ior patterns of patients suffering from anxiety Davidson, R. J., & Tomarken, A. J. (1989). Laterality and emotion: An electrophysiological approach. In F. Boller, & disorders and to gain insight into the effects of J. Grafman (Eds.), Handbook of neuropsychology CBT. This might also help to optimize both the (pp. 419–441). Amsterdam, Netherlands: Elsevier. understanding of emotion regulation as well as the Dennis, T. A. (2007). Interactions between emotion regulation psychotherapeutic treatment for patients suffering strategies and affective style: Implications for trait anxiety from anxiety disorders. Finally, it might also be versus depressed mood. Motivation and Emotion, 31, 200–207. https://doi.org/10.1007/s11031-007-9069-6 interesting to investigate the effect of directly Erreygers, S., & Spooren, P. (2017). Factor structure of the addressing affective styles in therapy and the impact Affective Style Questionnaire in Flemish adolescents. Psycholo- on therapy outcome. gica Belgica, 57 ,112–122. https://doi.org/10.5334/pb.369 Geissner, E., & Huetteroth, A. (2018). Beck Anxiety Inventory German version: A reliable, valid, patient-friendly instru- References ment for measuring clinical anxiety. Psychotherapie Psy- chosomatik Medizinische Psychologie, 68 , 118–125. https:// doi.org/10.1055/s-0043-122941 Abramowitz, J. S., Deacon, B. J., & Whiteside, S. P. (2011). Graser, J., Bohn, C., Kelava, A., Schreiber, F., Hofmann, S. G., Exposure therapy for anxiety: Principles and practice. New & Stangier, U. (2012). Der Affective Style Questionnaire York, NY: Guilford Press. (ASQ): Deutsche Adaption und Validitäten. Diagnostica, American Psychiatric Association (2000). Diagnostic and 58 , 100–111. https://doi.org/10.1026/0012-1924/a000056 statistical manual of mental disorders (4th ed., text rev.). Gross, J. J. (1998). The emerging field of emotion regulation: Washington, DC: Author. An integrative review. Review of General Psychology, 2 , Barlow, D. H., Farchione, T. J., Fairholme, C. P., Ellard, K. K., 271–299.http://psycnet.apa.org/doi/10.1037/1089-2680.2. Boisseau, C. L., Allen, L. B., & Ehrenreich, J. T. (2011). 3.271.
Please cite this article as: C. Totzeck, T. Teismann, S.G. Hofmann, et al., Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Predict..., , https://doi.org/10.1016/j.beth.2019.06.006
62 CHAPTER 4
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Gross, J. J., & John, O. P. (1997). Revealing feelings: Facets of emotion regulation framework to integrative approaches to emotional expressivity in self-reports, peer ratings, and generalized anxiety disorder. Clinical Psychology: Science behavior. Journal of Personality and Social Psychology, 72 and Practice, 9 , 85–90. https://doi.org/10.1080/1047840X. (2), 435–448. 2015.969624 Gross, J. J., & John, O. P. (2003). Individual differences in two Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New emotion regulation processes: Implications for affect, York, NY: McGraw-Hill. relationships, and well-being. Journal of Personality and Porter, E., & Chambless, D. L. (2015). A systematic review of Social Psychology, 85 , 348–362.http://psycnet.apa.org/doi/ predictors and moderators of improvement in cognitive- 10.1037/0022-3514.85.2.348. behavioral therapy for panic disorder and agoraphobia. Hofmann, S. G. (2007). Cognitive factors that maintain social Clinical Psychology Review, 42, 179–192. https://doi.org/ anxiety disorder: A comprehensive model and its treatment 10.1016/j.cpr.2015.09.004 implications. Cognitive Behaviour Therapy, 36, 193–209. Roberts, S., Wong, C. C. Y., Breen, G., Coleman, J., DeJong, S., https://doi.org/10.1080/16506070701421313 Jöhren, P. … Eley, T. C. (2017). Genome-wide expression Hofmann, S. G., & Kashdan, T. B. (2010). The Affective Style and response to exposure-based psychological therapy for Questionnaire: Development and psychometric properties. anxiety disorders. Translational Psychiatry, 7(8)e1219 Journal of Psychopathology and Behavioral Assessment, 32, Schneider, S., & Margraf, J. (2011). Diagnostisches Interview 255–263. https://doi.org/10.1007/s10862-009-9142-4 bei psychischen Störungen (4th ed.). Berlin, Germany: Hofmann, S. G., Sawyer, A. T., Fang, A., & Asnaani, A. (2012). Springer. Emotion dysregulation model of mood and anxiety disor- Springer, K. S., Levy, H. C., & Tolin, D. F. (2018). Remission in ders. Depression and Anxiety, 29 , 409–416. https://doi.org/ CBT for adult anxiety disorders: A meta-analysis. Clinical 10.1002/da.21888 Psychology Review, 61,1–8. https://doi.org/10.1016/j.cpr. Hosmer, D. W., & Lemeshow, S. (1989). Applied logistic 2018.03.002 regression. New York, NY: Wiley. https://doi.org/10.1002/ Suppiger, A., In-Albon, T., Herren, C., Bader, K., Schneider, S., sim.4780100718 &Margraf,J.(2008).Reliabilitätdesdiagnostischen In-Albon, T., Suppiger, A., Schlup, B., Wendler, S., Margraf, J., & Interviews bei psychischen Störungen (DIPS für DSM-IV- Schneider, S. (2008). Validität des Diagnostischen Interviews bei TR) unter klinischen routinebedingungen. Verhaltensther- Psychischen Störungen (DIPS für DSM-IV-TR). Zeitschrift für apie, 18, 237–244. https://doi.org/10.1159/000169699 Klinische Psychologie und Psychotherapie, 37,33–42. https:// Teismann, T., & Margraf, J. (2018). Exposition und Kon- doi.org/10.1026/1616-3443.37.1.33 frontation. Göttingen, Germany: Hogrefe. https://doi.org/ Ito, M., & Hofmann, S. G. (2014). Culture and affect: The factor 10.1026/02825-000 structure of the Affective Style Questionnaire and its relation Totzeck, C., Teismann, T., Hofmann, S. G., von Brachel, R., with depression and anxiety among Japanese. BMC Research Zhang, X. C., Pflug, V., & Margraf, J. (2018). Affective Notes, 7,590.https://doi.org/10.1186/1756-0500-7-590 styles in mood and anxiety disorders: Clinical validation of Landis, J. R., & Koch, G. G. (1977). The measurement of the “Affective Style Questionnaire” (ASQ). Journal of observer agreement for categorical data. Biometrics, 33, Affective Disorders, 238,392–398. https://doi.org/10. 159–174. https://doi.org/10.2307/2529310 1016/j.jad.2018.05.035 Margraf, J., & Ehlers, A. (1989). Etiological models of panic: Urban, D., & Mayerl, J. (2006). Regressionsanalyse: Theorie, Psychophysiological and cognitive aspects. In R. Baker Technik und Anwendung. Wiesbaden, Germany: Springer. (Ed.), Panic disorder: Theory, research and therapy https://doi.org/10.1007/978-3-531-90141-1 (pp. 205–231). Oxford, UK: Wiley. Wheeler, R. E., Davidson, R. J., & Tomarken, A. J. (1993). Frontal Margraf, J., & Ehlers, A. (2007). Beck Angst Inventar BAI: brain asymmetry and emotional activity: A biological substrate Manual. Frankfurt, Germany: Pearson Assessment GmbH. of affective style. Psychophysiology, 30 ,82–89. https://doi.org/ Margraf, J., & Schneider, S. (2009). Panikstörung und 10.1111/j.1469-8986.1993.tb03207.x agoraphobie. In J. Margraf, & S. Schneider (Eds.), Lehrbuch der verhaltenstherapie (pp. 3–30). Berlin, Germany: Spring- er. https://doi.org/10.1007/978-3-540-79543-8_1 RECEIVED: August 14, 2018 Mennin, D. S., Heimberg, R. G., Turk, C. L., & Fresco, D. M. ACCEPTED: June 16, 2019 (2002). Commentary on Roemer and Orsillo: Applying an AVAILABLE ONLINE: xxxx
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Study 4: May you be happy: Loving-kindness meditation promotes mental health in university student. Manuscript submitted for publication.
Mindfulness
May you be happy: Loving-kindness meditation promotes mental health in university students --Manuscript Draft--
Manuscript Number: MIFU-D-19-00177 Full Title: May you be happy: Loving-kindness meditation promotes mental health in university students
Article Type: Original Research Keywords: Loving-kindness meditation; LKM; Positive mental health; university students; prevention
Corresponding Author: Christina Totzeck Ruhr-Universitat Bochum GERMANY Corresponding Author Secondary Information: Corresponding Author's Institution: Ruhr-Universitat Bochum Corresponding Author's Secondary Institution: First Author: Christina Totzeck First Author Secondary Information: Order of Authors: Christina Totzeck Tobias Teismann, PD Dr. Stefan G. Hofmann, Prof. Dr. Ruth von Brachel, Dr. Verena Pflug Andre Wannemüller, Dr. Jürgen Margraf, Prof. Dr. Order of Authors Secondary Information:
Funding Information: Alexander von Humboldt-Stiftung Mr. Stefan G. Hofmann Konrad-Adenauer-Stiftung Ms. Christina Totzeck (PhD Scholarship) Alexander von Humboldt-Stiftung Mr. Jürgen Margraf (Professorship)
Abstract: Objectives: Loving-kindness meditation (LKM) has been shown to improve wellbeing and positive emotions in clinical and non-clinical populations. The main goal of the present study was to examine, whether LKM might be an effective intervention to promote mental health in university students. Methods: The sample (n = 110) consisted of university students in Germany. One half of them (n = 55) underwent LKM treatment. They were compared to a matched control group (n = 55) which did not receive treatment. All participants completed positive and negative mental health measures at baseline and one-year follow-up assessments. LKM participants additionally completed the same measures before and after treatment. Multiple analyses of variance were conducted to test for short- and long- term effects of LKM on positive and negative mental health. Results: A significant short-term effect of LKM on anxiety and positive mental health was found. Long-term analyses revealed a significant decrease of depression, anxiety, and stress for LKM completers, in contrast to a significant increase of depression, anxiety, and stress for the control group. Conclusions: The results suggest that LKM enhances mental health in university
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May you be happy: Loving-kindness meditation promotes mental health in
university students
The time as a student is often associated with many positive things. It provides you the opportunity to do the things you are interested in and the freedom to manage time yourself.
However, research shows that a lot of students might not feel that way. In fact, evidence suggests that college and university students in the USA have greater levels of stress and psychopathology than any time before (Lipson, Lattie, & Eisenberg, 2019). Self-reported diagnoses, especially depression and anxiety disorders, are increasing (Eisenberg, Hunt, &
Speer, 2013), suggesting that mental health problems are a growing public health concern on campuses. In comparison to students not suffering from mental health problems, affected students additionally report poorer relationships with other students and faculty members, less of engagement in campus clubs and activities, lower grade point average as well as lower rates of graduation (Byrd & McKinney, 2012; Keyes et al., 2012; Salzer, 2012; Storrie,
Ahern, & Tuckett, 2010).
Similar results have not only been found among US students, but also in a variety of other countries (Auerbach et al., 2018; Orygen, 2017). According to a recent study by the
Barmer health insurance (Grobe, Steinmann, & Szecsenyi, 2018) on German university students, between 2005 and 2016, the proportion of 18- to 25-year-olds diagnosed with mental disorders in Germany rose by 38 percent. Furthermore, about 17 percent of students corresponding to almost half a million (around 470,000) people, who had previously been regarded as healthy appeared to be affected by a mental disorder. In particular, depression, anxiety disorders and panic attacks among young people seem to be on the rise (Grobe,
Steinmann, & Szecsenyi, 2018).
Despite this, only a small minority of students seem to receive adequate treatment for their mental disorders (Auerbach et al., 2016). A lack of psychotherapeutic support, coupled with a fear of stigma, prevent many from accessing the treatment they need (Vidourek, King,
65 CHAPTER 5
Nabors, & Merianos, 2014). It might, therefore, be useful to implement low-threshold treatments to reach a high number of students.
A meta-analysis by Regehr, Glancy, and Pitts (2013) identified the effectiveness of various interventions aimed at reducing stress in university students. Their results revealed that cognitive, behavioural, and mindfulness interventions were associated with decreased symptoms of anxiety and lower levels of depression and cortisol (Regehr, Glancy, & Pitts,
2013). Whereas mindfulness-based interventions have successfully been conducted in university settings (Collard, Avny, & Boniwell, 2008; Galante et al., 2018; Halland et al.,
2015; Solhaug et al., 2016; de Vibe et al., 2013, 2015), Loving-kindness meditation (LKM) has only recently been examined as a potential intervention for university students’ mental health.
Loving-kindness, also known as metta (in Pali), is derived from Buddhism and refers to a mental state of unconditional kind attitudes toward all beings. LKM is centrally related to, and includes the practice of, mindfulness (Hofmann, Grossmann, & Hinton, 2011). The core psychological operation is to train to generate one’s kind intentions toward certain targets. Practitioners silently repeat phrases, such as “may you be happy” or “may you be free from suffering” toward targets. Targets change gradually with practice, from easy to difficult; generally beginning with oneself, followed by loved ones, then neutral people, difficult individuals, and finally all beings. LKM exercises are believed not only to broaden attention, but also to enhance positive emotions, and lessen negative emotional states (Dalai Lama &
Cutler, 1998; Hofmann, Grossmann, & Hinton, 2011).
Meta-analyses suggest that LKM interventions improve health and wellbeing more generally, and positive emotions more specifically in clinical and non-clinical populations
(Galante, Galante, Bekkers, & Gallacher, 2014; Zeng, Chiu, Wang, Oei, & Leung, 2015). For instance, LKM has been shown to enhance daily experiences of positive emotions in working adults (Fredrickson, Cohn, Coffey, Pek, & Finkel, 2008). With regard to university students,
66 CHAPTER 5 only a few studies have examined the effect of LKM on positive emotions (May et al., 2011;
May, Weyker, Spengel, Finkler, & Hendrix, 2014) or connectedness (Aspy & Proeve, 2017).
May et al. (2011; 2014), for instance, explored the efficacy of a self-training focused on loving-kindness among university students. They found increases of positive affect and decreases of negative affect right after meditation practice. Unfortunately, there are no studies so far investigating either long-term effects of LKM on students’ mental health or the effect of LKM on positive mental health. However, LKM might be a potential intervention to increase mental health in students as it provides a low-threshold treatment without stigmatization; it can be conducted in group settings and can be easily practiced almost everywhere.
Since researchers have concluded that universities should employ preventive interventions that potentially reach larger groups of students and not merely rely on individual counselling services (Regehr, Glancy, & Pitts, 2013), the present study aims at investigating whether LKM might be such a useful treatment.
The main goal of the present study was, therefore, to examine whether LKM might be an effective intervention to promote mental health: We hypothesized (1) positive mental health to increase and (2) negative mental health to decrease in participants receiving LKM treatment. In addition, we aimed at (3) examining whether potential short-term effects endure over a follow-up period of six months.
Methods
Participants
The sample of the present study consisted of participants of the Bochum Optimism and
Mental Health (BOOM) program, a cross-sectional and longitudinal study, collecting information about students’ mental health, annually. To assess data, a collective e-mail including a participation invitation and an online-link of the self-report survey is sent to freshmen at our university, who gave permission to be contacted for study participation, at the
67 CHAPTER 5 beginning of winter semester. Data for this study were collected in five subsequent years
(2011–2016) in student populations. All students, who completed at least the second online inquiry (N = 540) were offered to participate in LKM. Overall n = 96 (17.7%) students showed general interest in participation, n = 70 of them decided to participate; n = 15 students were not enrolled in the study because they could not make time for the training. Therefore, n
= 55 students attended at least one LKM session, n = 5 (9.1%) participants dropped out after the first and second training session, n = 3 (5.45%) students did not complete the post-LKM assessment. Finally, n = 40 LKM completers (72.72%) took part in the follow-up assessment six months after the intervention and one year after baseline assessment. Because the purpose of the program was health promotion rather than psychotherapy, no exclusion criteria were used and the students were not screened for mental disorders.
Age at baseline ranged from 19 to 30 years (M = 22.83, SD = 2.11) and n = 39
(70.9%) of the sample were female. Twenty-five participants (45.5%) were not in a relation- ship, none of the participants had children. At baseline, the majority (n = 29) of the sample was in their fifth semester of study (M = 5.49, SD = 1.38) and the three most common faculties were Philology, Psychology, and Law. The LKM treatment group was not randomized but compared to a matched control group.
Control group
Among BOOM participants a control group (n = 55) was drawn matching age (M =
22.92, SD = 2.19), gender (70.9% female), semester (M = 5.48, SD = 0.75), and faculty affiliation of the LKM treatment sample. Thirty-eight of them (69.09%) completed the follow-up assessment one year after baseline assessment.
Treatment
Participants received LKM according to the treatment manual by Totzeck and colleagues (unpublished manual), based on the LKM manual by Sandra M. Finkel (see
Fredrickson et al., 2008). LKM was administered in five group sessions with 3-8 participants
68 CHAPTER 5 per group. The median number of sessions attended was five (M = 4.32, SD = 0.82). All sessions lasted 60 minutes, they were conducted by one of the four – previously LKM trained
- psychologists (n = 3 female), who were also meditation experienced trainers, and supervised by a licensed psychotherapist. Treatment adherence of the trainers was assessed after each session with a one-item self-report (“I managed to adhere to the manual”) on a scale ranging from 0 (“Not at all”) to 7 (“Totally”). Overall, self-reported treatment adherence was very good (M = 6.01, SD = 0.82).
Each session started with a group meditation (15-25 min), followed by a check on participants’ progress and answering questions (20 min), as well as a presentation about features of the meditation and how to integrate concepts from the workshop into one’s daily life (20 min). At the first session, participants were given a CD that included a short version of LKM meditation (10 min), and they were assigned to practice this recording at home, at least five days per week. In each session, all participants were asked whether or not they had managed to practice five days per week. During the first week, participants practiced a meditation directing love and kindness toward themselves. During the second week, the meditation added loved ones. During subsequent weeks, the meditation expanded from self, to loved ones, to acquaintances, to strangers, and finally, to all living beings. The first meditation lasted 15 min, and the final one lasted 25 min.
Measures
DASS-21. The Depression Anxiety Stress Scale (Henry & Crawford, 2005) is a 21- item self-report instrument measuring the three negative emotional states of depression, anxiety and tension/stress over the past week using a 4-point Likert scale from 0 (“did not apply to me at all”) to 3 (“applied to me very much or most of the time”). Consistency values for the three DASS subscales were α = .87 for depression (DASS-D), α = .77 for anxiety
(DASS-A), and α = .84 for stress (DASS-S) in the current sample.
69 CHAPTER 5
PMH. The Positive Mental Health Scale (Lukat, Margraf, Lutz, van der Veld, &
Becker, 2016) assesses emotional and psychological aspects of wellbeing across nine items, rated on a scale ranging from 1 (“do not agree”) to 4 (“agree”), with higher scores indicating greater positive mental health. Unidimensional structure, good convergent and discriminant validity have been demonstrated in various populations (Lukat et al., 2016). Cronbach’s alpha was excellent in this study: α = .91.
SHS. The Subjective Happiness Scale (Lyubomirsky & Lepper, 1999) is a 4-item scale that assesses global subjective happiness. Two items ask respondents to characterize themselves using both absolute ratings ranging from 1 (“not a very happy person”) to 7 (“a very happy person”) and ratings relative to peers also ranging from 1 (“less happy”) to 7
(“more happy”). Two items of the SHS offer brief descriptions of happy and unhappy individuals and ask respondents the extent to which each characterisation describes them from
1 (“not at all”) to 7 (“a great deal”). Convergent and discriminant validity have been confirmed in several studies (e. g. Lyobomirsky, 2001), in the present study, Cronbach’s alpha was also very good: α = .86.
Procedure
After being informed about the procedure of the study, all participants gave written informed consent. As part of the BOOM study, participants completed the above-mentioned questionnaires at baseline assessment (Time 1) and at follow-up assessment (Time 4) one year after baseline. In addition to their participation in the BOOM study, LKM participants also completed the above-mentioned questionnaires right before the first session of LKM (Time
2), which took place five months after baseline, and directly after the last session of LKM intervention (Time 3), five weeks after Time 2.
The study was approved by the Ethics Committee of the Faculty of Psychology at the
Ruhr University Bochum.
Data analysis
70 CHAPTER 5
The Statistical Package for the Social Sciences (SPSS, version 24.0) was used to analyze the research data. In order to investigate baseline differences between LKM and control group, a multivariate analysis of variance (MANOVA) was conducted using the two groups as between-subjects variables and DASS, PMH, and SHS as dependent variables.
Short-term effects of LKM intervention on mental health were examined using a MANOVA with repeated measures: The two experimental times (pre-LKM = Time 2 and post-LKM =
Time 3), served as within-subjects variables and DASS, PMH, and SHS scores as dependent variables. Finally, another MANOVA with repeated measures was conducted to examine long-term effects: Baseline (Time 1) and follow-up assessment (Time 4) served as within- subjects variables, LKM and control group as between-subjects variables, and DASS, PMH, and SHS as dependent variables. Pairwise comparisons between assessments and between groups were computed. Homogeneity of error variances was tested using the Mauchly-test for sphericity. In case of significant results of the Mauchly-test, a Greenhouse-Geisser correction was conducted. The level of significance was set as p < .05 (two-tailed). Partial η2 was calculated as an estimate of effect size. According to Cohen (1992; 1988) a partial η2 of 0.01 can be considered as small, 0.06 as medium, and 0.14 as large effect.
Results
Baseline analyses
Although the DASS scores were slightly higher as well as the PMH and SHS scores slightly lower in the LKM group when compared to the control group, these differences were not significant (all p values > .07). Baseline results are presented in Table 1.
Short-term effects of LKM
Between baseline and pre-LKM assessment (Time 2) five months after baseline, all scores had not changed significantly (all p values > .70). Throughout LKM intervention, a significant multivariate effect of Time on measures (F(1, 46) = 21.54, p < .001; Wilks’ λ =
.681; ηp² = .32) was found. Significant changes throughout LKM were found only for DASS-
71 CHAPTER 5
Anxiety (F(1, 46) = 10.08, p = .003; Wilks’ λ = .820; ηp² = .18), and PMH (F(1, 46) = 6.92, p
= .012; Wilks’ λ = .869; ηp² = .13), but not for the other measures (all p values > .08). All mean scores as well as changes between pre- and post-intervention assessment are presented in Table 2.
Long-term effects of LKM
Results revealed a significant interaction effect of Time*Intervention (F(1, 76) = 7.87, p = .003; Wilks’ λ = .906; ηp² = .09). All changes of DASS, PMH, and SHS scores between baseline (Time 1) and follow-up assessment (Time 4) are presented in Table 3.
All three DASS-subscale scores significantly decreased in the LKM intervention group between baseline and follow-up assessment: DASS-D (F(1, 76) = 22.16, p < .001;
Wilks’ λ = .774; ηp² = .23), DASS-A (F(1, 76) = 22.16, p < .001; Wilks’ λ = .774; ηp² = .23), and DASS-S (F(1, 76) = 11.40, p = .001; Wilks’ λ = .870; ηp² = .13). Within the control group, none of the three DASS-subscales decreased. Instead, DASS-D (F(1, 76) = 8.20, p =
.005; Wilks’ λ = .903; ηp² = .10) significantly increased. In addition, the DASS-S (F(1, 76) =
4.62, p < .035; Wilks’ λ = .943; ηp² = .06) also significantly increased within the control group between baseline and follow-up assessment.
With regard to the positive measures, no further significant increase was found; neither in the LKM treatment group, nor in the control group (all p values > .10). However, results did reveal a significant decrease of SHS within the control group (F(1, 76) = 4.95, p =
.029; Wilks’ λ = .939; ηp² = .06).
Finally, both groups differed significantly in DASS-D (F(1, 79) = 6.01, p = .016; ηp² =
.07), and DASS-S (F(1, 79) = 4.38, p = .04; ηp² = .05) scores at follow-up. Further significant differences were not found (all other p values > .30). An overview about these findings is presented in Figures 1a and 1b.
Discussion
72 CHAPTER 5
The main purpose of the present study was to investigate whether LKM might be an effective intervention to promote mental health in university students: We previously hypothesised (1) positive mental health to increase and (2) negative mental health to decrease in participants receiving LKM treatment.
According to the first hypothesis, subjective happiness did not change, whereas positive mental health increased significantly after LKM termination. In addition, results revealed a significant decrease of anxiety scores after LKM participation. However, depression and stress scores did not decrease. Therefore, our second hypothesis was only partially confirmed. These findings are in contrast with previous studies showing a stronger short-term effect of LKM on negative emotions (e. g. Fredrickson et al., 2008; May et al.,
2014). However, our intervention was conducted during a very stressful period for the participating students: The majority of them was in their fifth semester of study and, therefore, right before graduation (B. Sc.). This might have provoked further increases in negative mental health scores. However, even more surprising though is our finding of a short-term decrease in anxiety symptoms throughout LKM. Similar to other mindfulness- based treatments, the meditation might have caused a relaxation effect leading to the decrease of anxiety symptoms. However, we additionally found a short-term increase of positive mental health after LKM termination suggesting a stronger effect above and beyond relaxation. Positive mental health, as assessed with the PMH, comprises emotional as well as psychological components of wellbeing and indicates positive functioning (Lukat et al.,
2016). Furthermore, positive mental health has been shown to be a significant predictor of remission from anxiety disorders (Teismann et al., 2018). Although the exact mechanism of
LKM still remains unclear (Zeng et al., 2015), it appeared to promote positive mental health in the present study.
Our third aim was to examine whether short-term effects of LKM have enduring effects over a follow-up period of six months. Interestingly, all three DASS subscale scores of
73 CHAPTER 5
LKM participants significantly decreased from baseline to follow-up assessment: Depression, anxiety, as well as stress levels decreased. With regard to the control group, the opposite effect was found; all three DASS subscale scores increased, including a significant increase in depression and stress scores. These results fit into the picture of previous studies.
Encountering new experiences, relationships, and living situations (Byrd & Mckinney, 2012;
Lipson, Gaddis, Heinze, Beck, & Eisenberg, 2015) during the university period give rise to stress experiences that can impact mental health (Soet & Sevig, 2006). Another contributing factor might be the fact that the onset of common mental disorders, such as anxiety or depressive disorders, occurs during late adolescence and early adulthood (Kessler et al.,
2007). The university years, therefore, represent a period of increased vulnerability for the development of mental health challenges. LKM treatment appeared to not only impede the progress of mental health problems, but might have contributed to a more positive mental health of LKM participants when compared to their matched counterparts in the control group.
We allowed every interested student to attend LKM. Although we did not randomize participants to the conditions, the self-selection of students also displays that these students were probably aware of their increasing mental health challenges. At baseline assessment, we did find subclinical scores on the DASS measure. According to the DASS cut-off scores, the mean scores of LKM participants were within the category of “mild depressive” and “mild anxious”. Their acceptance to participate in LKM training, hereby, also represents a search for assistance to enhance mental health.
Unfortunately, we did not assess the actual amount of participants’ weekly practice time. Since previous studies reported that there was no significant association between practice time and daily positive emotions in their intervention (e. g. May et al., 2011; Jazaieri et al., 2014), we focused on the information, whether or not participants managed to practice at least five days per week. However, it remains unclear, whether the intensity of practice
74 CHAPTER 5 might influence individual improvement. Furthermore, we cannot determine which part of the
LKM intervention might be the effective component. As the meta-analysis by Zeng et al.
(2015) already pointed out, several components of LKM might contribute to positive effects.
Future research should, therefore, address this question by examining the effect of the single components of LKM.
In conclusion, the present study confirmed the positive short- and long-term effects of
LKM on mental health. Although studies on LKM are still at the early stages of research, it appears to be a promising intervention to promote mental health in university students.
75 CHAPTER 5
References
Aspy, D. J., & Proeve, M. (2017). Mindfulness and Loving-Kindness Meditation: Effects on
Connectedness to Humanity and to the Natural World. Psychological Reports, 120(1),
102–117. https://doi.org/10.1177/0033294116685867
Auerbach, R. P., Alonso, J., Axinn, W. G., Cuijpers, P., Ebert, D. D., Green, J. G., …
Bruffaerts, R. (2016). Mental disorders among college students in the World Health
Organization World Mental Health Surveys. Psychological medicine, 46(14), 2955-
2970. https://org.doi:10.1017/S0033291716001665
Auerbach, R. P., Mortier, P., Bruffaerts, R., Alonso, J., Benjet, C., Cuijpers, P., … WHO
WMH-ICS Collaborators (2018). WHO World Mental Health Surveys International
College Student Project: Prevalence and Distribution of Mental Disorders. Journal of
Abnormal Psychology, 127, 623-638. http://dx.doi.org/10.1037/abn0000362
Byrd, D., & McKinney, K. (2012). Individual, interpersonal, and institutional level factors
associated with the mental health of college students. Journal of American College
Health, 60(3), 185–193. https://doi.org/10.1080/07448481.2011.584334
Cohen J. (1988). Statistical Power for the Behavioural Science (2nd ed). Hillsdale, NJ:
Erlbaum
Cohen J. (1992). A power primer. Psychological Bulletin 112, 155–159.
http://psycnet.apa.org/doi/10.1037/0033-2909.112.1.155
Collard, P., Avny,N., Boniwell,I. (2008). Teaching mindfulness based cognitive therapy
(MBCT) to students: the effects of MBCT on the levels of mindfulness and subjective
well-being. Counselling Psychology Quarterly, 21(4), 323–336.
https://doi.org/10.1080/09515070802602112
Dalai Lama and Cutler, H. (1998). The Art of Happiness: A Handbook for Living. Rockland:
Compass Press.
Eisenberg, D., Hunt, J., & Speer, N. (2013). Mental health in American colleges and
76 CHAPTER 5
universities: Variation across student subgroups and across campuses. Journal of
Nervous and Mental Disease, 201, 60–67.
http://dx.doi.org/10.1097/NMD.0b013e31827ab077
Fredrickson, B. L., Cohn, M. A., Coffey, K. A., Pek, J., & Finkel, S.M. (2008). Open hearts
build lives: Positive emotions, induced through loving-kindness meditation, build
consequential personal resources. Journal of Personality and Social Psychology, 95,
1045–1062. https://doi: 10.1037/a0013262
Galante, J., Dufour, G., Vainre, M., Wagner, A. P., Stochl, J., Benton, A., Lathia, N.,
Howarth, E, & Jones, P. B. (2018). A mindfulness-based intervention to increase
resilience to stress in university students (the Mindful Student Study): a pragmatic
randomised controlled trial. The Lancet. Public health, 3(2), e72-e81.
https://doi.org/10.1016/S2468-2667(17)30231-1
Galante, J., Galante, I., Bekkers, M.-J., & Gallacher, J. (2014). Effect of kindness-based
meditation on health and well-being: A systematic review and meta-analysis. Journal
of Consulting and Clinical Psychology, 82(6), 1101-1114.
http://dx.doi.org/10.1037/a0037249
Grobe, T. G., Steinmann, S., & Szecsenyi, J. (2018). Barmer Medical Report (7th edition).
Berlin: Barmer.
Halland, E., de Vibe, M., Solhaug, I., Tyssen, R., Friborg, O., Rosenvinge, J. H., & Bjørndal,
A. (2015). Mindfulness training improves problem-focused coping in psychology and
medical students. College Student Journal, 49(3), 387–398.
Henry, J. D., & Crawford, J. R. (2005). The short-form version of the Depression Anxiety
Stress Scales (DASS-21): construct validity and normative data in a large non-clinical
sample. British Journal of Clinical Psychology, 44, 227-239.
https://doi.org/10.1348/014466505X29657
Hofmann, S. G., Grossman, P., & Hinton, D. E. (2011). Loving-kindness and compassion
77 CHAPTER 5
meditation: Potential for psychological interventions. Clinical Psychology Review, 31,
1126–1132. https://doi.org/10.1016/j.cpr.2011.07.003
Jazaieri, H., McGonigal, K., Jinpa, T., Doty, J. R., Gross, J. J., & Goldin, P. R. (2014). A
randomized controlled trial of compassion cultivation training: effects on mindfulness,
affect, and emotion regulation. Motivation and Emotion 38, 23–35.
https://doi.org/10.1007/s11031-013-9368-z
Kessler, R. C., Amminger, G. P., Aguilar-Gaxiola, S., Alonso, J., Lee, S., & Ustün, T. B.
(2007). Age of onset of mental disorders: a review of recent literature. Current
Opinion in Psychiatry, 20(4), 359-64.
https://doi.org/10.1097/YCO.0b013e32816ebc8c
Keyes, C. L. M., Eisenberg, D., Perry, G. S., RD, Dube, S. R., Kroenke, K., & Dhingra, S. S.
(2012). The Relationship of Level of Positive Mental Health With Current Mental
Disorders in Predicting Suicidal Behavior and Academic Impairment in College
Students. Journal of American College Health, 60(2), 126-133.
https://doi.org.10.1080/07448481.2011.608393
Lipson, S., Gaddis, S., Heinze, J., Beck, K., & Eisenberg, D. (2015). Variations in student
mental health and treatment utilization across U.S. colleges and universities. Journal
of American College Health, 63(6), 388-396.
https://doi.org/10.1080/07448481.2015.1040411
Lipson, S. K., Lattie, E. G., & Eisenberg, D. (2019). Increased Rates of Mental Health
Service Utilization by U.S. College Students: 10-Year Population-Level Trends
(2007–2017). Psychiatric Services, 70, 60-63.
https://doi.org/10.1176/appi.ps.201800332
Lukat, J., Margraf, J., Lutz, R., van der Veld, W. M., & Becker, E. S. (2016). Psychometric
properties of the Positive Mental Health Scale (PMH-scale). BMC Psychology, 4, 8.
http://dx.doi.org/10.1186/s40359-016-0111-x
78 CHAPTER 5
Lyubomirsky, S., & Lepper, H. S. (1999). A measure of subjective happiness: Preliminary
reliability and construct validation. Social Indicators Research, 46, 137–155.
http://dx.doi.org/10.1023/A:1006824100041
Lyubomirsky, S. (2001). Why are some people happier than others?: The role of cognitive
and motivational processes in well-being. American Psychologist, 56, 239-249.
May, C. J., Burgard, M., Mena, M., Abbasi, I., Bernhardt, N., Clemens, S., … Williamson, R.
(2011). Short-term training in loving-kindness meditation produces a state, but not a
trait, alteration of attention. Mindfulness, 2(3), 143-153.
http://dx.doi.org/10.1007/s12671-011-0053-6
May, C. J., Weyker, J. R., Spengel, S. K., Finkler, L. J., & Hendrix, S. E. (2014). Tracking
longitudinal changes in affect and mindfulness caused by concentration and loving-
kindness meditation with hierarchical linear modeling. Mindfulness, 5(3), 249-258.
http://dx.doi.org/10.1007/s12671-012-0172-8
Orygen (2017). The National Centre of Excellence in Youth Mental Health. Under the radar.
The mental health of Australian university students. Melbourne: Orygen, The National
Centre of Excellence in Youth Mental Health.
Regehr, C., Glancy, D., & Pitts, A. (2013). Interventions to reduce stress in university
students: A review and meta-analysis. Journal of Affective Disorders, 148, 1–11.
https://doi.org/10.1016/j.jad.2012.11.026
Storrie, K., Ahern, K., Tuckett, A. (2010). A systematic review: students with mental health
problems: a growing problem. International Journal of Nursing Practice, 16 (1), 1–6.
https://doi.org/10.1111/j.1440-172X.2009.01813.x
Salzer, M. (2012). A comparative study of campus experiences of college students with
mental illnesses versus a general college sample. Journal of American College Health,
60(1), 1–7. https://doi.org/10.1080/07448481.2011.552537
Soet, J., & Sevig, T. (2006). Mental Health Issues Facing a Diverse Sample of College
79 CHAPTER 5
Students: Results from the College Student Mental Health Survey. Journal of Student
Affairs Research and Practice, 43(3), 410-431. https://doi.org/10.2202/1949-
6605.1676
Solhaug, I., Eriksen, T. E., de Vibe, M., Haavind, H., Friborg, O., Sørlie, T., & Rosenvinge,
J. H. (2016). Medical and Psychology Student's Experiences in Learning Mindfulness:
Benefits, Paradoxes, and Pitfalls. Mindfulness, 7, 838-850.
https://doi.org/10.1007/s12671-016-0521-0
Teismann, T., Brailovskaia, J., Totzeck, C., Wannemüller, A., & Margraf, J. (2018).
Predictors of remission from panic disorder, agoraphobia and specific phobia in
outpatients receiving exposure therapy: The importance of positive mental health
Behaviour Research and Therapy, 108, 40-44.
https://doi.org/10.1016/j.brat.2018.06.006 de Vibe, M., Solhaug, I., Tyssen, R., Friborg, O., Rosenvinge, J. H., Sorlie, T., & Bjørndal,
A. (2013). Mindfulness training for stress management: a randomised controlled study
of medical and psychology students. BMC Medical Education, 13, 107.
https://doi.org/10.1186/1472-6920-13-107 de Vibe, M., Solhaug, I., Tyssen, R., Friborg, O., Rosenvinge, J. H., Sorlie, T., Halland, E., &
Bjorndal, A. (2015). Does personality moderate the effects of mindfulness training for
medical and psychology students? Mindfulness, 6(2), 281–289.
https://doi.org/10.1007/s12671-013-0258-y
Vidourek, R. A., King, K. A., Nabors, L. A., & Merianos, A. L. (2014). Students' benefits
and barriers to mental health help-seeking. Health psychology and behavioral
medicine, 2(1), 1009-1022. https://dx.doi.org/10.1080%2F21642850.2014.963586
Zeng, X., Chiu, C. P. K., Wang, R., Oei, T. P. S., & Leung, F. Y. K. (2015). The effect of
loving-kindness meditation on positive emotions: a meta-analytic review. Frontiers in
Psychology, 6, 1693. https://doi.org/10.3389/fsyg.2015.01693
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Table 1
Baseline scores of the DASS, PMH, and SHS in the LKM group and control group and mean differences between both groups
Mean Mean difference Sign.
Measures Group score SD between groups p
DASS-D LKM 5.73 5.19 1.66 .092 Control group 4.07 4.11
DASS-A LKM 4.36 4.26 1.39 .078 Control group 2.97 3.10
DASS-S LKM 7.76 4.94 1.33 .181 Control group 6.44 4.57
PMH LKM 17.34 6.33 -.933 .461 Control group 18.27 5.83
SHS LKM 18.59 4.63 -1.22 .203 Control group 19.81 4.59
Note: DASS = Depression, Anxiety, and Stress Scale, PMH = Positive Mental Health Scale,
SHS = Subjective Happiness Scale; LKM = Loving-kindness Meditation
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Table 2
Mean differences, standard errors, and p-values of the DASS, PMH, and SHS between pre- and post-LKM intervention
Mean scores (SD) Mean Standard Sign. 95% CI
Measures Time 2 Time 3 Difference error p LL UL
DASS-D 5.06 (4.41) 3.57 (3.23) 1.49 .84 .084 -.208 3.187UL
DASS-A 4.59 (3.84) 2.45 (2.62) 2.15* .68 .003 .787 3.511
DASS-S 8.19 (4.90) 7.55 (4.09) .68 .97 .515 -1.318 2.595
PMH 16.28 (6.52) 19.40 (4.56) -3.13* 1.19 .012 -5.521 -.734
SHS 16.21 (3.98) 17.59 (5.43) -1.38 .94 .148 -3.274 .509
Note: DASS = Depression, Anxiety, and Stress Scale, PMH = Positive Mental Health Scale,
SHS = Subjective Happiness Scale; Time 2 = pre-intervention, Time 3 = post-intervention; CI
= Confidence interval, LL = lower level, UL = upper level.
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Table 3
Mean differences, standard errors, and p-values of the DASS, PMH, and SHS between baseline and follow-up assessment
Mean Standard Sign. 95% CI
Measures Group Time Difference error p LL UL
DASS-D LKM 1 4 2.82* .60 .000 1.630 4.020
Control group 1 4 -1.76* .62 .005 -2.989 -.537
DASS-A LKM 1 4 1.10* .53 .040 .053 2.147
Control group 1 4 -.58 .54 .287 -1.654 .496
DASS-S LKM 1 4 2.17* .64 .001 .892 3.458
Control group 1 4 -1.42* .66 .035 -2.737 -.105
PMH LKM 1 4 -.95 .91 .300 -2.763 .863
Control group 1 4 .71 .93 .449 -1.149 2.570
SHS LKM 1 4 -1.02 .64 .116 -2.311 .261
Control group 1 4 1.47* .66 .029 .155 2.793
Note: DASS = Depression, Anxiety, and Stress Scale, PMH = Positive Mental Health Scale,
SHS = Subjective Happiness Scale; Time 1 = baseline, Time 4 = follow-up; CI = Confidence interval, LL = lower level, UL = upper level.
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Negative mental health scale
10 * 9 8 * * 7 6 * 5 * 4 3 2 1 0
DASS_D_1DASS_D_2DASS_D_3DASS_D_4 DASS_A_1DASS_A_2DASS_A_3DASS_A_4 DASS_S_1DASS_S_2DASS_S_3DASS_S_4 LKM Control group
Figure 1a. Changes of DASS scores of LKM treatment group and control group between baseline and follow-up assessment. DASS = Depression, Anxiety, and Stress Scale; Numbers represent the four assessment times.
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Positive mental health scales 25
20 *
15
10
5
0 PMH_1 PMH_2 PMH_3 PMH_4 SHS_1 SHS_2 SHS_3 SHS_4
LKM Control group
Figure 1b. Changes of PMH and SHS scores of LKM treatment group and control group between baseline and follow-up assessment. PMH = Positive Mental Health Scale; SHS =
Subjective Happiness Scale; Numbers represent the four assessment times.
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Study 5: Predictors of remission from panic disorder, agoraphobia and specific phobia in outpatients receiving exposure therapy: The importance of positive mental health.
Contents lists available at ScienceDirect
Behaviour Research and Therapy
journal homepage: www.elsevier.com/locate/brat
Predictors of remission from panic disorder, agoraphobia and specific phobia in outpatients receiving exposure therapy: The importance of positive mental health
Tobias Teismann∗, Julia Brailovskaia, Christina Totzeck, Andre Wannemüller, Jürgen Margraf
Department of Clinical Psychology and Psychotherapy, Ruhr-Universität Bochum, Germany
ARTICLE INFO ABSTRACT
Keywords: Positive mental health has been shown to predict remission from anxiety disorders in community samples. Exposure therapy However, it is unclear, whether positive mental health is also predictive of symptom severity and remission from Anxiety disorders anxiety disorders in patients receiving exposure therapy. A total of 130 adult outpatients suffering from panic Positive mental health disorder, agoraphobia, or specific phobia received manualized exposure-therapy. Positive mental health was considered as a predictor of symptom severity and remission at the post-treatment assessment and at the follow- up assessment six months after treatment termination – controlling for depression, anxiety, anxiety cognitions, bodily sensations, number of treatment sessions, age and gender. Pre-treatment positive mental health was the only predictor of post-treatment symptom severity and remission status. Post-treatment positive mental health and avoidance behavior predicted symptom severity and remission status at the follow-up assessment. In con- clusion, the current study highlights the importance of positive mental health in understanding remission from anxiety disorders.
1. Introduction contrary, specific phobia characteristics (i.e., severity, age at onset), stress, coping skills, a negative cognitive style and psychopathology at Mental health has traditionally been defined as the absence of baseline did not predict remission. A comparable result pattern was psychopathology (Keyes, 2005): Individuals were seen as either men- found by Vriends et al. (2007): In a multivariate regression model, tally ill or presumed to be mentally healthy. Meanwhile, it is widely positive mental health was the strongest predictor of remission from acknowledged that positive mental health (PMH) and psychopathology social phobia – even after controlling for avoidance behavior, dys- are not opposite ends of a single continuum; rather they constitute functional attitudes, daily hassles, psychopathology, anxiety sensitivity, distinct but correlated axes (Trompetter, Lamers, Westerhof, Fledderus, self-efficacy, social support and life satisfaction. These findings suggest & Bohlmeijer, 2017). Two broad traditions describe the key compo- that the natural course of specific and social phobia in young women is nents of positive mental health (Deci & Ryan, 2008): The hedonic tra- dependent on facets of subjective and psychological well-being, dition deals with positive affect and life satisfaction, whereas the eu- whereas it is relatively independent of the disorder's characteristics. daimonic tradition focuses on human potential and optimal Furthermore, positive mental health seems to be an especially im- functioning. Taking both the hedonic and eudaimonic tradition into portant salutogenetic factor compared to other protective factors (cf., account, positive mental health may be defined as the presence of Siegmann et al., 2018). subjective and psychological well-being (Keyes, 2005; Keyes, Shmotkin, However, it remains unclear to what extent the above-mentioned & Ryff, 2002). results generalize to remission following exposure therapy in patients Positive mental health, as assessed with the Positive-Mental Health suffering from panic disorder, agoraphobia and specific phobia. Scale (Lukat, Margraf, Lutz, van der Veld, & Becker, 2016), was found Previous studies found agoraphobic avoidance to be the most consistent to be of central importance to the remission of anxiety disorders. In a predictor of improvement in cognitive-behavioral therapy for panic prospective community study, Trumpf, Becker, Vriends, Meyer, and disorder and agoraphobia, whereas other variables – such as symptom Margraf (2009) found positive mental health to be the most important severity, depressive symptoms, anxiety sensitivity – are only incon- predictor of remission from specific phobia in young women. On the sistently related to outcome (Porter & Chambless, 2015). The number of
∗ Corresponding author. Department of Clinical Psychology and Psychotherapy, Faculty of Psychology, Ruhr-Universität Bochum, Massenbergstraße 11, 44787, Bochum, Germany. E-mail address: [email protected] (T. Teismann).
https://doi.org/10.1016/j.brat.2018.06.006 Received 22 February 2018; Received in revised form 30 May 2018; Accepted 21 June 2018
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T. Teismann et al. therapy sessions has been found to be associated with treatment re- 2.3. Therapists sponse in patients suffering from specific phobia (Wolitzky-Taylor, Horowitz, Powers, & Telch, 2008). To our knowledge, the importance Therapy was provided by 18 therapists (n = 15 women). All of positive mental health for the remission of anxiety disorders in pa- therapists were psychologists with a CBT orientation and had M = 3.57 tients receiving exposure therapy has not been studied so far. Therefore, years (SD = 1.47; range: 1–5 years) of experience in conducting CBT. the purpose of the present prospective study was to evaluate the asso- All therapists were Caucasian and trained in conducting exposure-based ciation between (1) pre-treatment positive mental health and post- CBT for panic disorder, agoraphobia and specific phobia prior to par- treatment remission status as well as symptom severity and between (2) ticipating in the active phase of treatment. post-treatment positive mental health, remission status and symptom severity at a 6-month follow-up assessment in an outpatient sample of 2.4. Measures patients suffering from panic disorder, agoraphobia or specific phobia. On the background of the above mentioned studies, we hypothesized 2.4.1. DSM-IV diagnoses that positive mental health predicts remission and symptom severity Diagnoses at the pre-, post-, and follow-up assessment were made by following exposure therapy - after controlling for disorder character- trained clinical psychologists using the “Diagnostisches Interview bei istics, psychopathology, cognitive factors, session number, age and psychischen Störungen” (DIPS), a structured clinical interview with gender. well-established reliability, validity, and patient acceptance (Schneider & Margraf, 2006), which is based on the Anxiety Disorders Interview Schedule (ADIS-IV-L; Di Nardo, Brown, & Barlow, 1995). Remission was 2. Method defined as no longer meeting full diagnostic criteria for a diagnosis of panic disorder, agoraphobia or specific phobia. The current study is a secondary analysis of a study on genetic factors in exposure treatments for anxiety disorders (Roberts et al., 2.4.2. Clinical global impression – severity scale (CGI-S; Guy, 1976) 2017). Treatments included in the current analysis were conducted The CGI-S requires a clinician to rate the severity of the patient's between December 2011 and October 2015. All participants were re- disorder from 1 to 7, with a score of 1 representing no symptoms of cruited at an outpatient clinic in the Ruhr region in Germany. They concern and a score of 7 representing extremely severe illness requiring ff were o ered participation if they met the following criteria: (a) DSM-IV hospitalization. The scale was chosen as it is widely used (Busner & (APA, 2000) criteria for Panic Disorder with Agoraphobia, Agoraphobia Targum, 2007) and captures severity in a disorder-independent fashion. without a history of Panic Disorder, Specific Phobia; (b) the anxiety disorder was considered to be the most severe disorder if co-morbid 2.4.3. Positive mental health scale (PMH-scale; Lukat et al., 2016) disorders were present; (c) 18–70 years of age; (d) not meeting DSM-IV The PMH-scale assesses aspects of subjective and psychological criteria for psychosis, mania, current substance abuse/dependency; (e) well-being across nine items (e.g., “I enjoy my life”, “All in all, I am no concurrent psychological or psychopharmacological treatment; (f) satisfied with my life”, “I feel that I am actually well equipped to deal no suicide ideation/behavior in need of immediate treatment. Prior to with life and its difficulties”) rated on a scale ranging from 1 (do not treatment, participants gave written and informed consent. The study agree) to 4 (agree), with higher scores indicating greater positive mental was approved by the Ethics Committee of the Faculty of Psychology at health. Unidimensional structure, good convergent, and discriminant the Ruhr-Universität Bochum. validity have been demonstrated in various populations (Lukat et al., 2016). Cronbach's alpha was good in this study: α = .94. 2.1. Participants 2.4.4. Depression-Anxiety-Stress scales (DASS; Henry & Crawford, 2005) In total 130 participants (n = 91 female; age: M = 41.98, Depressive and anxious symptoms were assessed using the re- spective subscales of the DASS. Participants are asked to indicate to SD = 12.65, range: 24–70) took part at the pre-treatment assessment and the post-treatment assessment. Most participants (n = 68) were not what extent seven statements on depressive symptoms (DASS-D) and married, n = 53 were married and n = 9 were separated/divorced. anxiety (DASS-A) applied to them over the past week (0 = did not apply Ninety-six were working either as employees or freelancers, n = 18 to me at all;3=applied to me very much or most of the time). Internal were students, n = 11 were unemployed and n = 2 were retired. consistency in the current sample were α = .91 (DASS-D) and α = .88 Seventy-one patients suffered from panic disorder with agoraphobia, (DASS-A), respectively. n = 5 from agoraphobia without history of panic disorder and n = 54 from specific phobia, predominantly of the animal (n = 13) and en- 2.4.5. Agoraphobic cognitions questionnaire (ACQ; Chambless, Caputo, vironmental (n = 16) subtype. All participants were Caucasian. One- Bright, & Gallagher, 1984) hundred sixteen participants (n = 78 female; age: M = 42.03, The ACQ is a 14-item self-report questionnaire that measures the frequency of catastrophic beliefs about the possible consequences of SD = 12.87, range: 24–70) took part in a follow-up assessment six months after treatment termination. Completers of the follow-up as- experienced anxiety and panic. Each item is rated on a 5-point scale sessment and non-completers did not significantly differ in any of the ranging from 1 (never) to 5 (always). The internal consistency of the study variables at the pre- and post-treatment assessment. ACQ in this sample was α = .80.
2.4.6. Bodily sensations questionnaire (BSQ; Chambless et al., 1984) 2.2. Treatment The BSQ is a 17-item self-report questionnaire that measures the degree of anxiety elicited by body sensations. Each item is rated on a 5- Participants received exposure-based treatment delivered according point scale ranging from 1 (not at all) to 5 (extremely). Internal con- to a treatment manual (Teismann, Margraf, & Schneider, 2011) and in sistency of the BSQ in this sample was α = .91. individual sessions. The mean number of sessions attended was M = 21.99 (SD = 8.79). Treatment included psychoeducation on the 2.4.7. Mobility inventory (MI; Chambless, Caputo, Jasin, Gracely, & nature of anxiety, interoceptive and situational exposure exercises as Williams, 1985) well as elements of cognitive restructuring. In order to ensure treatment The MI is a self-report questionnaire that measures the degree to protocol integrity, all treatments were regularly supervised by experi- which 27 situations are avoided. Items are scored from 1 (never avoid enced senior clinicians using audio-visual recordings. the situation) to 5 (always avoid the situation), with the mean of all items
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T. Teismann et al. as the total score. For this study, only the ratings for the “alone” sub- Table 2 scale were utilized. The internal consistency of the MI in this sample Logistic regression analyses. was α = .95. Prediction of post-treatment Prediction for follow-up remission remission 2.5. Design and analyses OR, 95% CI p OR, 95% CI p
Statistical analyses were conducted with the Statistical Package for Model 1 the Social Sciences (SPSS) 24. To identify significant predictors of re- Gender 1.42, .57–3.54 n.s. 1.17, .40–3.43 n.s. Age 1.00, .96 1.03 n.s. 1.01, .97 1.05 n.s. mission (no = 0, yes = 1) at the post-treatment and at the follow-up – – DASS: Anxiety 1.05, .94–1.17 n.s. 1.11, .91–1.35 n.s. assessment, four logistic regression analyses were calculated. In order MI .64, .38–1.10 n.s. .08, .02–.29 .000 to control for the possibility of false-positive results due to a large PMH-scale 1.11, 1.03–1.20 .010 1.18, 1.04–1.33 .010 number of covariates, two preliminary regression analyses were con- Model 2 ducted using only gender, age, anxiety symptoms (DASS-A), avoidance Gender 1.38, .54–3.54 n.s. 1.00, .32–3.15 n.s. Age .99, .96–1.03 n.s. 1.01, .97–1.05 n.s. behavior (MI) and positive mental health (PMH) as predictors of re- Diagnosis (panic vs. .88, .31–2.52 n.s. .48, .15–1.52 n.s. mission. Following this, further regression analyses included the vari- phobia) ables gender, age, session number, diagnosis (panic disorder/agor- Session number 1.02, .97–1.07 n.s. .98, .93–1.05 n.s. aphobia vs. specific phobia), as well as pre-treatment depressive DASS: Depression 1.00, .88–1.14 n.s. 1.00, .82–1.22 n.s. symptoms (DASS-D), anxiety symptoms (DASS-A), avoidance behavior DASS: Anxiety 1.07, .94–1.22 n.s. 1.10, .84–1.43 n.s. MI .65, .36–1.18 n.s. .08, .02–.32 .000 (MI), anxiety cognitions (ACQ), bodily sensations (BSQ) and positive ACQ .58, .21–1.57 n.s. .84, .15–4.86 n.s. mental health (PMH). In the first analysis, the variables assessed at the BSQ 1.00, .49–2.05 n.s. 1.01, .29–3.58 n.s. pre-treatment assessment served as potential predictors of remission at PMH-scale 1.11, 1.01–1.21 .028 1.18, 1.03–1.36 .017 the post-treatment assessment, and in the second analysis, the variables Note. N = 130; OR = Odds Ratio, CI = Confidence Interval, p = significance; assessed at the post-treatment assessment served as potential predictors significant odds ratios are denoted by bold typeface; DASS = Depression- of remission at the follow-up assessment. Derived odds ratios (including Anxiety-Stress Scales, MI = Mobility Inventory, ACQ = Agoraphobic fi 95% con dence interval, CI) are presented for each predictor variable Cognitions Questionnaire, BSQ = Bodily Sensations Questionnaire, PMH- fi in both models. To identify signi cant predictors of symptom severity scale = Positive Mental Health Scale. at the post-treatment and at the follow-up assessment, two hierarchical regression analyses were calculated using the same variables as the controlling for gender, age, anxiety, and avoidance behavior. Post- above mentioned logistic regression analyses. Assuming a medium- treatment positive mental health and avoidance behavior predicted ff 2 sized e ect (f = 0.15), an alpha error level of 5%, ten predictors and a remission at the follow-up assessment. The results were essentially the sample size of N = 130, the test power was 1-β≥0.80 and therefore same, when controlling for a larger number of potential predictors (age, ffi su cient according to Cohen (1988). In all models, there was no vio- gender, diagnosis, session number, depression, anxiety, anxiety cogni- lation of the multicollinearity assumption as all values of tolerance tions, bodily sensations): Only pretreatment positive mental health fl were > .25, and all variance in ation factor values were < 5 (Urban & predicted post-treatment remission from anxiety disorders. Post-treat- Mayerl, 2006). ment avoidance behavior and positive mental health served as sig- nificant predictors for remission at the follow-up assessment six months 3. Results after treatment termination. The results of the hierarchical regression analyses are shown in Full remission was achieved by n = 89 (68.5%) participants at the Table 3. Post-treatment symptom severity was predicted by pre-treat- post-treatment assessment and by n = 80 (69%), at the follow-up as- ment positive mental health. Symptom severity at the follow-up as- sessment six months after treatment termination. Table 1 presents de- sessment was predicted by post-treatment positive mental health and scriptive data of the variables considered as possible predictors of re- avoidance behavior. None of the other variables predicted symptom mission at the pre- and post-treatment assessment. severity at the post-treatment and/or follow-up assessment. The results of the logistic regression analyses are shown in Table 2. Preliminary analyses revealed that pre-treatment positive mental health 4. Discussion predicted post-treatment remission from anxiety disorders – after The aim of the present study was to examine predictors of symptom Table 1 severity and remission from panic disorder, agoraphobia and specific Descriptive values and correlations of main study variables. phobia in outpatients receiving exposure therapy. There were two main Pre-treatment CGI-S post- Post-treatment CGI-S follow- findings: (1) Pre-treatment positive mental health was the only pre- variables treatment variables up dictor of post-treatment symptom severity and remission status. (2) Post-treatment positive mental health and avoidance behavior pre- M (SD) rM(SD) r dicted symptom severity and remission status at the follow-up assess- DASS-D 3.93 0.289** DASS-D 2.55 0.387** ment six months after treatment termination. (4.57) (3.55) These results complement previous research showing an association DASS-A 5.45 0.239** DASS-A 2.64 0.369** between positive mental health with remission from specific and social (4.92) (3.02) ACQ 1.91 (.54) 0.245** ACQ 1.47 (.43) 0.441** phobia within community samples (Trumpf et al., 2009; Vriends et al., BSQ 2.39 (.84) 0.218** BSQ 1.71 (.65) 0.452** 2007) as well as between avoidance behavior and treatment improve- MI 2.04 (.88) 0.299** MI 1.42 (.56) 0.608** ment in patients suffering from panic disorder and agoraphobia (Porter PMH 25.73 −0.338** PMH 28.51 −0.544** & Chambless, 2015). While the connection between increased avoid- (6.03) (5.12) ance behavior and a reduced response to exposure therapy seems Notes. N=130; CGI = Clinical Global Impression; DASS = Depression- comprehensible, the question arises as to how positive mental health Anxiety-Stress Scales, MI = Mobility Inventory, ACQ = Agoraphobic contributes to an improved response to exposure therapy. On the Cognitions Questionnaire, BSQ = Bodily Sensations Questionnaire, PMH- background of the broaden-and-build-theory (Fredrickson, 2001), one scale = Positive Mental Health Scale. **p<.01. may speculate that positive mental health translates into more frequent
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Table 3 Hierarchical regression.
ß 95% CI T F Adjusted R2 Changes in R2
Prediction of post CGI Step 1 1.301, n.s. .009 .040 Gender -.108 [-.939;.229] −1.203 Age -.068 [-.030;.013] .759 Diagnosis (panic vs. phobia) -.196* [-1.157;-.041] -.2124 Session number .051 [-.022;.039] .566 Step 2 1.856, n.s. .056 .082 DASS: Depression .202 [-.013;.147] 1.654 DASS: Anxiety -.027 [-.097;.081] -.185 MI .228 [-.016;.795] 1.900 ACQ .097 [-.401;.939] .795 BSQ -.095 [-.639;.297] -.723 Step 3 2.251* .088 .037 PMH-scale -.268* [-.123;-.009] −2.283 Prediction of follow-up CGI Step 1 1.596, n.s. .020 .054 Gender -.111 [-.966;.251] −1.164 Age .011 [-.021;.024] .120 Diagnosis (panic vs. phobia) -.232* [-1.306;-.115] −2.364 Session number .059 [-.022;.042] .616 Step 2 7.610** .341 .338 DASS: Depression .174 [-.007;.155] 1.802 DASS: Anxiety -.003 [-.113;.110] -.031 MI .492** [.850;.1.848] 5.358 ACQ .016 [-.729;.842] .143 BSQ .087 [-.360;.793] .746 Step 3 8.004** .379 .040 PMH-scale -.274* [-.147;-.023] −2.722
Notes. N=130; ß=standardized coefficient beta; CI = confidence interval; CGI = Clinucal Global Impression; DASS = Depression-Anxiety-Stress Scales, MI = Mobility Inventory, ACQ = Agoraphobic Cognitions Questionnaire, BSQ = Bodily Sensations Questionnaire, PMH-scale = Positive Mental Health Scale. *p<.05; **p < . 01. everyday positive affect, which in turn has been shown to broaden an mental health for the success of anxiety treatment. Moreover, the individual's mindset in ways that, over time, help to accumulate and number of patients suffering from either panic disorder with agor- build one's personal resources, such as resilience and social closeness aphobia, agoraphobia without panic disorder or specific phobia was not (Fredrickson, 2013). Garland et al. (2010, p. 855) speculate that posi- large enough to perform separate analyses in the current study. The tive emotions may counter anxiety cognitions “by facilitating sufficient same applies to different subtypes of specific phobia. attentional disengagement from negative stimuli to allow perception of In conclusion, positive mental health was the only short- and long- the pleasant aspects of experience and the re-association of formerly term predictor of remission from anxiety disorders in the current study; negatively-construed events.” Furthermore, frequent positive affect has whereas a variety of pathogenetic factors were of minor importance for been shown to help individuals to rebound from adversity (Tugade & addressing exposure treatment. Fredricksson, 2004) and may therefore help to regulate negative emo- tional experience during exposure therapy in ways that individuals Conflict of interest keep up practicing exposure tasks. However, this is only speculative, as the association between positive mental health - assessed with the The authors declare that they have no conflict of interests. PMH-scale (Lukat et al., 2016) - and everyday positive affect has not been studied so far. Funding source Identifying predictors of outcome allows clinicians to identify pa- tients at risk of poorer outcome before they commence therapy and may Data collection and data analysis was supported by the Alexander von help guide the development of more effective treatments for these pa- Humboldt-Professorship of Jürgen Margraf. The funding source was not tients. Similar to other studies (Loerinc et al., 2015), the remission rate involved in the interpretation of the data, in the writing of the report; in the present study was nearly 70%; accordingly, a non-negligible part and in the decision to submit the article for publication. of patients does not or does not sufficiently benefit from a classic ex- posure treatment. Since positive mental health is significantly asso- References ciated with remission, it may be beneficial to think of fostering well- being in clinical interventions for anxiety disorders (cf., Fava, 2016). American Psychiatric Association (2000). Diagnostic and statistical manual of mental dis- This should be examined in future studies. On a theoretical level, the orders (4th ed.). Washington, DC: Author text rev. Busner, J., & Targum, S. D. (2007). The clinical global impressions scale: Applying a current results underscore the necessity that theoretical models of an- research tool in clinical practice. Psychiatry, 4, 28–37. xiety disorders should strive to integrate both pathogenetic and pro- Chambless, D. L., Caputo, G. C., Bright, P., & Gallagher, R. (1984). Assessment of fear of tective factors – this is all the more so as there are indications that fear in agoraphobics: The body sensations questionnaire and the agoraphobic cog- ff nitions questionnaire. Journal of Consulting and Clinical Psychology, 52, 1090–1097. di erent factors are associated with incidence and remission of anxiety Chambless, D. L., Caputo, G. C., Jasin, S. E., Gracely, E. J., & Williams, C. (1985). The disorders (Trumpf et al., 2009). mobility inventory for agoraphobia. Behaviour Research and Therapy, 23, 35–44. In principle, however, it should be noted that although a significant Cohen, J. (1988). Statistical power analysis for the behavioural sciences. Hillsdale: Erlbaum. influence of positive mental health on the remission rate could be found Deci, E. L., & Ryan, R. M. (2008). Hedonia, eudaimonia, and well-being: An introduction. Journal of Happiness Studies, 9,1–11. in the current study, this effect is only of moderate size. It must Di Nardo, P. A., Brown, T. A., & Barlow, D. H. (1995). Anxiety disorders interview Schedule therefore be warned against overestimating the importance of positive for DSM-IV (ADIS-IV). Albany, New York: Graywind Publications.
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Fava, G. (2016). Well-being therapy. Basel: Karger. Roberts, S., Wong, C. C. Y., Breen, G., Coleman, J., DeJong, S., Jöhren, P., et al. (2017). Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The Genome-wide expression and response to exposure-based psychological therapy for broaden-and-build theory of positive emotions. American Psychologist, 56, 218–226. anxiety disorders. Translational Psychiatry, 7(8) e1219. Fredrickson, B. L. (2013). Positive emotions broaden and build. Advances in Experimental Schneider, S., & Margraf, J. (2006). Diagnostisches Interview bei psychischen Störungen. Social Psychology, 47,1–53. Berlin: Springer. Garland, E. L., Fredrickson, B., Kring, A. M., Johnson, D. P., Meyer, P. S., & Penn, D. L. Siegmann, P., Teismann, T., Fritsch, N., Forkmann, T., Glaesmer, H., Zhang, X. C., et al. (2010). Upward spirals of positive emotions counter downward spirals of negativity: (2018). Resilience to suicide ideation: A cross-cultural test of the buffering hypoth- Insights from the broaden-and-build theory and affective neuroscience on the treat- esis. Clinical Psychology and Psychotherapy, 25(1), e1–e9. ment of emotion dysfunctions and deficits in psychopathology. Clinical Psychology Teismann, T., Margraf, J., & Schneider, S. (2011). CBT of phobias and panic. Unpublished Review, 30, 849–864. treatment manual. Guy, W. (1976). Clinical global impression scale. The ECDEU assessment manual for psy- Trompetter, H. R., Lamers, S. M. A., Westerhof, G. J., Fledderus, M., & Bohlmeijer, E. T. chopharmacology-revised, 338, 218–222 Volume DHEW Publ No ADM 76. (2017). Both positive mental health and psychopathology should be monitored in Henry, J. D., & Crawford, J. R. (2005). The short-form version of the Depression Anxiety psychotherapy: Confirmation for the dual-factor model in acceptance and commit- Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical ment therapy. Behaviour Research and Therapy, 91, 58–63. sample. British Journal of Clinical Psychology, 44, 227–239. Trumpf, J., Becker, E. S., Vriends, N., Meyer, A. H., & Margraf, J. (2009). Rates and Keyes, C. L. M. (2005). Mental illness and/or mental health? Investigating axioms of the predictors of remission in young woman with specific phobia. Journal of Anxiety complete state model of health. Journal of Consulting and Clinical Psychology, 73, Disorders, 23, 958–964. 539–548. Tugade, M. M., & Fredricksson, B. L. (2004). Resilient individuals use positive emotions to Keyes, C. L. M., Shmotkin, D., & Ryff, C. D. (2002). Optimizing well-being: The empirical bounce back from negative emotional experiences. Journal of Personality and Social encounter of two traditions. Journal of Personality and Social Psychology, 82, Psychology, 86, 320–333. 1007–1022. Urban, D., & Mayerl, J. (2006). Regressionsanalyse: Theorie, Technik und Anwendung (2. Loerinc, A. G., Meuret, A. E., Twohig, M. P., Rosenfield, D., Bluett, E. J., & Craske, M. G. Aufl.). Wiesbaden: VS Verlag für Sozialwissenschaften. (2015). Response rates for CBT for anxiety disorders: Need for standardized criteria. Vriends, N., Becker, E., Meyer, A., Williams, S., Lutz, R., & Margraf, J. (2007). Recovery Clinical Psychology Review, 42, 72–82. from social phobia in the community and its predictors. Journal of Anxiety Disorders, Lukat, J., Margraf, J., Lutz, R., van der Veld, W. M., & Becker, E. S. (2016). Psychometric 21, 320–337. properties of the positive mental health scale (PMH-scale). BMC Psychology, 4,1–14. Wolitzky-Taylor, K. B., Horowitz, J. D., Powers, M. B., & Telch, M. J. (2008). Porter, E., & Chambless, D. L. (2015). A systematic review of predictors and moderators of Psychological approaches in the treatment of specific phobias: A meta-analysis. improvement in cognitive-behavioral therapy for panic disorder and agoraphobia. Clinical Psychology Review, 28, 1021–1037. Clinical Psychology Review, 42, 179–192.
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General Discussion The heart of psychological research is emotion.
Emotional problems receive considerable attention because of their high prevalence in various clinical conditions (Sheppes, Suri, & Gross, 2015). Therefore, emotion research, especially in the context of clinical psychology, is essential in order to promote the understanding of the complex interplay of emotions and mental health. Although research has already shown that dysregulation of emotions can lead to several mental disorders (Campbell-
Sills & Barlow, 2007; Gross and Muñoz, 1995; Mennin et al., 2005; Putnam & Silk, 2005), there is still a lack of knowledge regarding the point where adaptive regulation ends and where maladaptive regulation begins. Furthermore, it has not been examined how specifically patients with mental disorders regulate their everyday emotions, moods, and affects, and in which respect they differ from a healthy population. It is assumable that dysfunctional regulation styles might change through CBT. However, whether such improvement indeed happens, has not been fully investigated.
The present thesis set out to gain more insight into these questions by addressing five different aspects: Emotion induction, habitual emotion regulation within clinical populations as well as its changes through CBT, and furthermore the effects of a positive intervention on mental health including the role of positive mental health. In the following, the results of the five studies, which have been presented in Chapters 2 to 6, are briefly summarized. This is followed by providing answers to the questions presented in the introduction of this thesis while integrating the research topics into the broader context of emotion research and suggesting future research perspectives: How can we reliably induce emotional states in order to examine their impact on cognitive, social, and behavioral functioning (Study 1)? How do people suffering from mental disorders handle their emotions (Study 2)? How do these strategies change through psychotherapeutic treatment (Study 3)? What happens to mental health when we directly address positive emotions (Study 4)? And finally, how are positive factors of mental
91 CHAPTER 7 health associated with therapy outcome (Study 5)? The section thereafter intends to translate the findings into clinical implications. Finally, the chapter closes with a summarized evaluation.
Summary of the Main Findings
In Study 1, emotion induction via emotional film sequences was investigated. The aim of the first study was the development and validation of a new emotional film set that would provide a valid emotion induction method for the three basic emotions: happiness, sadness and fear. Overall, N = 120 German participants viewed previously validated as well as novel film clips and rated each film on multiple dimensions. In addition, the duration of emotional reactions was examined. The results showed that the three targeted emotions happiness, sadness, and fear as well as a neutral state could be induced selectively. They were effective with regard to several criteria such as emotional discreteness, arousal, and valence. Therefore, the effectiveness and validity of the new emotional and neutral film excerpts could be confirmed.
Study 2 set out to examine affective styles in mood and anxiety disorders. The main goal of the second study was the validation of the ASQ within a large clinical sample (N = 917 treatment-seeking patients). Furthermore, possible differences of the three affective styles - concealing, adjusting, and tolerating - between patients suffering from affective versus anxiety disorders were examined. In addition, associations of these three affective styles and anxiety, depression, and stress symptoms were investigated. The clinical validation of the ASQ supported its applicability. Furthermore, significantly lower scores in the ASQ subscale adjusting were found in patients suffering from affective disorders than patients suffering from anxiety disorders. Finally, the results of the regression analyses showed that the ASQ adjusting and concealing behavior seemed to play a more important role than the ERQ reappraisal and suppression for depression, anxiety, and stress among clinical populations.
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Study 3 aimed to investigate changes in affective styles in patients suffering from anxiety disorder as a result of undergoing CBT, and to identify a possible link between certain affective styles and remission. The sample consisted of outpatients (N = 101) suffering from panic disorder, specific phobia, or agoraphobia who completed the ASQ before and after therapy, as well as at a 6-month follow-up assessment. Results indicated significant increases on the ASQ subscales adjusting and tolerating after therapy. Concealing did not decrease significantly after therapy. In addition, higher scores on adjusting significantly predicted remission from anxiety disorders. Finally, a significant association between increases on the adjusting scale and the reduction of anxiety symptoms was found.
The main goal of Study 4 was to examine, whether LKM might be an effective intervention to promote mental health in university students. The sample (N = 110) consisted of university students in Germany. One half of them (N = 55) underwent LKM treatment. They were compared to a matched control group (N = 55) which did not receive treatment. All participants completed positive and negative mental health measures at baseline and at one- year follow-up assessments. LKM participants additionally completed the same measures before and after treatment. The results revealed a significant short-term effect of LKM on anxiety and positive mental health. Long-term analyses resulted in a significant decrease of depression, anxiety, and stress for LKM completers, in contrast to a significant increase of depression, anxiety, and stress for the control group.
Study 5 investigated whether positive mental health might be predictive of symptom severity and remission from anxiety disorders in patients receiving exposure therapy. N = 130 outpatients suffering from panic disorder, agoraphobia, or specific phobia completed the PMH- scale prior to and after CBT as well as at 6-month follow-up assessment. Positive mental health was considered as a predictor of symptom severity and remission at the post-treatment assessment and at the follow-up assessment – controlling for depression, anxiety, anxiety cognitions, bodily sensations, number of treatment sessions, age and gender. Pre-treatment
93 CHAPTER 7 positive mental health was the only predictor of post-treatment symptom severity and remission status. Post-treatment positive mental health and avoidance behavior predicted symptom severity and remission status at the follow-up assessment.
Answers to the Research Questions How can we reliably induce emotional states in order to examine their impact
on cognitive, social and behavioral functions (Study 1)?
As the results of Study 1 showed, the presentation of emotional film sequences appears to be a potent emotion induction method: The target emotions happiness, sadness, and fear as well as a neutral state could be evoked. This underlines the categorization of basic emotions described in the introduction of this thesis as each of the target emotions was selectively induced. However, the results of the study also show, that it is vital to update stimulus material; when compared to previously validated older movies, the majority of the newly selected film sequences was superior in the induction of emotion in this sample. In the happiness and sadness category, the new film sequences evoked more intense emotions when compared to the old movies. Only within the fear category, the older movies induced more intense emotions than the new movies. The fact that the results of this study did not reveal any age-related differences shows that the presentation of film sequences provides an applicable emotion induction method for all age groups. Although the results revealed gender differences in the negative emotion ratings, wherein female participants scored higher than male participants, these differences can be ignored because of their very small effect sizes. Finally, the duration of emotional reactions was rather short as they mostly did not last until the termination of questionnaires. This finding underlines the assumption, that the duration of emotional stimuli is connected to the kind of emotional reaction being evoked (Uhrig et al., 2016). Using short film sequences appears to induce emotional states or even affects but not moods, which needs to be considered when conducting laboratory studies.
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How do people suffering from mental disorders handle their emotions (Study 2)?
The results of the second study revealed that patients suffering from affective disorders used less adjusting and cognitive reappraisal than patients with anxiety disorders. As described in the introduction of this thesis, depressive mood appears to be associated with decreased prefrontal activation, which causes a decreased regulatory control (Hofmann, Ellards, & Siegle,
2012). Therefore, patients suffering from mood disorders have less access to adaptive strategies to adequately regulate their depressive mood. Further differences in the other two affective styles were not found: Neither concealing nor tolerating differed significantly between patients suffering from affective or anxiety disorders.
Surprisingly, the results revealed that the ERQ emotion regulation strategies, cognitive reappraisal and expressive suppression did not show significant associations with psychopathology, neither in affective nor in anxiety symptomology. However, the results unfolded an interesting pattern of associations with affective styles: adjusting turned out to be clearly positive for patients with various mental disorders. The adjusting subscale showed a strong negative association with depression and with stress in patients suffering from affective disorders. We also found that the adjusting subscale was negatively associated with anxiety, depression, and stress in patients suffering from anxiety disorders. This finding is consistent with previous findings in a healthy population (Ito & Hofmann, 2014). Even though the adjusting subscale did not explain much of the variance, the affective style adjusting seems to play a more important role than the use of cognitive reappraisal. Here, patients suffering from mood and anxiety disorders seem to reveal an inability to adapt to situational demands above and beyond cognitive reappraisal. In addition, concealing showed a positive association with the symptomatology: It was positively associated with depression in patients suffering from affective disorders, and there was also a strong positive association of anxiety, depression, and stress in patients suffering from anxiety disorders. Contrary to previous findings of concealing
95 CHAPTER 7 in a healthy population (Ito & Hofmann, 2014), this affective style also seems to be relevant in terms of the development of psychopathology, especially in anxiety disorders.
Concealing seems to play a more important role in anxiety disorders than in affective disorders. Although patients with anxiety disorders do not seem to use the concealing tendency more often or more intensely than patients suffering from affective disorders, the process of concealing still appears to be related to their anxiety symptomatology. The reason for the especially maladaptive role of concealing in anxiety disorders might, at least partially, be caused by the paradoxical effect of suppression increasing anxiety symptoms (Gross &
Levenson, 1997; Campbell-Sills, Barlow, Brown, & Hofmann, 2006). However, since the ERQ suppression did not show such relations, the ASQ concealing seems to account for more maladaptive concealing behavior. Finally, tolerating only showed a negative association with anxiety symptoms in patients suffering from affective disorders. Here, we would have expected to find a more prominent role of tolerating in the psychopathology of both affective and anxiety disorders. Nevertheless, this finding underlines the assumption that affective styles differ in patients suffering from affective and anxiety disorders.
How do these strategies change through psychotherapeutic treatment (Study 3)?
The findings of this study revealed that CBT appears to change individual affective styles.
Adjusting and tolerating increased after therapy in patients suffering from panic disorder, agoraphobia, and specific phobia. However, concealing did not change throughout therapy.
Since psychophysiological and cognitive models posit exaggerated appraisal of threat to be a core element underlying pathological anxiety (Margraf & Ehlers, 1989; Beck & Haigh, 2014;
Clark & Beck, 2010), it is reasonable to expect that a successful treatment should be closely linked to an improved adjusting in response to situational demands. Analogue to improved adjusting, a strengthened ability to tolerate fear, anxiety, and other negative emotions should
96 CHAPTER 7 be, though not always directly addressed, one of the goals of exposure exercises. The increase of tolerating after therapy found in this study is in line with this assumption.
The fact, that the results of this study did not show a significant change in concealing was surprising, as we had expected that the rather maladaptive concealing tendency would decrease through therapy. However, effect of concealing might be less relevant in patients suffering from panic disorder, agoraphobia or specific phobia. Since the ASQ subscale concealing not only implies suppressing negative emotions (e.g., “I often suppress my emotional reactions to things.”), but also hiding negative emotions in front of others (e.g., “People usually can’t tell how I am feeling inside.”), concealing might play a more important role in social anxiety disorders, where patients aim to hide negative emotions in social contexts (Hofmann, 2007).
This assumption should be addressed in further research.
What happens to mental health when we directly address positive emotions
(Study 4)? As the results of the fourth study showed, the LKM treatment appeared to reduce anxiety symptoms and to promote positive mental health short-term. Long-term analyses resulted in a significant decrease of depression, anxiety, and stress for LKM completers, in contrast to a significant increase of depression, anxiety, and stress for the control group.
Furthermore, the results revealed that subjective happiness did not change, whereas positive mental health increased significantly after completing LKM. In addition, results showed a significant decrease of anxiety scores after LKM participation. However, depression and stress scores did not decrease. These findings are in contrast with previous studies showing a stronger short-term effect of LKM on negative emotions (e.g., Fredrickson, Cohn, Coffey, Pek, &
Finkel, 2008; May, Weyker, Spengel, Finkler, & Hendix, 2014). However, our intervention was conducted during a very stressful period for the participating students: The majority of them was in their fifth semester of studies and, therefore, just before graduation (B. Sc.). This might
97 CHAPTER 7 have provoked further increases in negative mental health scores. However, even more surprising is the finding of a short-term decrease in anxiety symptoms throughout LKM. Similar to other mindfulness-based treatments, the meditation might have caused a relaxation effect leading to the decrease of anxiety symptoms. However, we additionally found a short-term increase of positive mental health after LKM, suggesting a stronger effect above and beyond relaxation. As described in the introduction of this thesis, positive mental health, as assessed with the PMH-scale, comprises emotional as well as psychological components of wellbeing and indicates positive functioning (Lukat et al., 2016). Although the exact mechanism of LKM still remains unclear (Zeng, Chiu, Wang, Oei, & Leung, 2015), it appeared to promote positive mental health in this study.
Interestingly, all three DASS subscale scores of LKM participants significantly decreased from baseline to follow-up assessment: Depression, anxiety, as well as stress levels decreased.
With regard to the control group, the opposite effect was found; all three DASS subscale scores increased, including a significant increase in depression and stress scores. These results fit into the picture of previous studies. Encountering new experiences, relationships, and living situations (Byrd & Mckinney, 2012; Lipson, Gaddis, Heinze, Beck, & Eisenberg, 2015) during the university years give rise to stress experiences that can impact mental health (Soet & Sevig,
2006). Another contributing factor might be the fact that the onset of common mental disorders, such as anxiety or depressive disorders, occurs during late adolescence and early adulthood
(Kessler et al., 2007). The university years, therefore, represent a period of increased vulnerability for the development of mental health challenges. LKM treatment appeared to not only impede the progress of mental health problems, but might have contributed to a more positive mental health of LKM participants when compared to their matched counterparts in the control group. Since participants were not randomized to the conditions, the self-selection of students also indicates that these students were probably aware of their increasing mental health challenges. At baseline assessment, we did find subclinical scores on the DASS measure.
98 CHAPTER 7
According to the DASS cut-off scores, the mean scores of LKM participants were within the category of “mild depressive” and “mild anxious”. Their acceptance to participate in LKM training, hereby, also represents a search for assistance to enhance mental health.
And finally, how are positive factors of mental health associated with therapy outcome (Study 5)?
Positive mental health appeared to be a strong predictor of both symptom severity and remission status of patients suffering from panic disorder, agoraphobia, and specific phobia.
The results are in line with previous studies showing an association between positive mental health with remission from specific and social phobia within community samples (Trumpf,
Becker, Vriends, Meyer, & Margraf, 2009; Vriends et al., 2007) as well as between avoidance behavior and treatment improvement in patients suffering from panic disorder and agoraphobia
(Porter & Chambless, 2015). Whereas it appears comprehensible that an increase in avoidance behavior and a reduction of response to exposure therapy are connected, the question arises in which way positive mental health contributes to an improved response to exposure therapy.
Based on the broaden-and-build-theory (Fredrickson, 2001), positive mental health might evoke more frequent everyday positive affect, which has been connected to an individual's broadened mindset (Fredrickson, 2013). This, in turn, promotes the ability to accumulate and strengthen personal resources, such as resilience and social closeness (Fredrickson, 2013). In addition, frequent positive affect appears to not only help individuals to rebound from adversity
(Tugade & Fredrickson, 2004) but also to regulate negative emotional experiences during CBT so that patients continue to practice exposure exercises. This needs to be examined in future research studies, as the association of positive mental health and everyday positive affect has not been investigated yet.
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Conclusions and Clinical Implications Tell me and I forget. Teach me and I remember. Involve me and I learn. -Benjamin Franklin-
Taking the findings of the five studies together, the following conclusions can be drawn.
(1) The first issue that is of great theoretical and practical importance is the consideration of differences in affective phenomena (Ekkekakis, 2012; Gross, 2015) as failures to distinct basic emotion episodes from affects and moods (or generally emotion-cognition interactions) might be one of the biggest sources of misconceptions in emotion science (Izard
2007, 2009; Gray, Schaefer, Braver, & Most, 2005). In addition, age-related and gender-related as well as cultural aspects should be taken into account in the examination of emotional processing (Izard, 2002, 2007, 2009).
(2) From a clinical perspective, the consideration of multimodal emotional processing is promising for the understanding of several mental disorders (Gerdes, Wieser & Alpers,
2014). The results of the second and third study provide evidence that the ASQ is applicable in clinical populations and, furthermore, that it seems to be a helpful instrument in uncovering functional and dysfunctional affective styles. When comparing the affective styles of different populations (see Figure 8), a tendency can be found: In concealing, there appear to be no particular differences. In adjusting and tolerating, German university students (Graser et al.,
2012) scored higher than American university students (Hofmann & Kashdan, 2010), followed by the group of patients suffering from anxiety disorders (Study 2 of this thesis). Patients suffering from affective disorders scored the lowest in adjusting and tolerating (Study 2 of this thesis). Although this effect has not been examined statistically, there might be an association of the degree of psychopathology and the ability to adjust and tolerate negative emotions and moods. Future research studies should, therefore, investigate this effect.
100 CHAPTER 7
AFFECTIVE STYLES IN DIFFERENT POPULATIONS 4
3
2
1
0 Concealing Adjusting Tolerating University Students Germany University Students USA Patients with Anxiety Disorders Patients with Affective Disorders
Figure 8. Affective styles in different populations (German university students, American university students, patients suffering from anxiety disorders, and patients suffering from affective disorders).
(3) The results also underpin Gross’ assumption of a hierarchical conception of affect regulation (see Figure 9). According to this model, affect regulation is seen as superordinate to coping, emotion regulation, and mood regulation (Gross, 1998b, 2015); therefore, affect regulation contains all of our efforts to influence our valenced responses (Gross, 2015; Westen,
1994). Integrating the findings of Study 2 and Study 3 into this model, affective styles - as assessed with the ASQ - involve not only emotion regulation strategies but also individual coping strategies as well as mood regulation. This interpretation might also explain the differences found between the ASQ and the ERQ in clinical populations.
Furthermore, as the results of Study 3 showed, affective styles appear to be relatively stable individual traits. However, they are alterable through therapy. Future research should examine the role of habitual affective styles and situation-specific emotion regulation strategies in psychopathology and treatment. A better understanding of patient's tendency to dysregulate emotions, affects, and moods may contribute to an optimized treatment outcome. In addition, treatments could be developed to directly aim at advancing functional and reducing
101 CHAPTER 7 dysfunctional affective styles. These findings warrant additional research on the use of affective styles throughout the course of psychotherapeutic treatment of various mental disorders.
Affect Regulation
Coping Mood Regulation
Emotion Regulation
Figure 9. A hierarchical conception of affect regulation. Modified from Gross (2015).
(4) With regard to developments in society and work life, it is essential to look for feasible improvements in psychotherapeutic practice which can be implemented without major obstacles. Since the fourth study confirmed the positive short- and long-term effects of LKM on mental health, it appears to be a promising intervention to promote mental health in university students. From a psychotherapeutic point of view, it is important to gain a holistic approach to the factors that promote people's mental health. Access to such treatment forms might also help to further develop prevention programs.
(5) Finally, the vital role of positive mental health needs to be further examined; not only assessing negative mental health factors but also positive mental health in psychotherapy contributes to an extensive understanding of mental health. Furthermore, understanding and applying the concept of a continuum of positive and negative mental health might help to unfold further risk factors as well as protective factors of mental health.
102 CHAPTER 7
Final Evaluation Mental health …is not a destination, but a process. It’s about how you drive, not where
you’re going. -Noam Shpancer-
To sum up, research has shown that emotion regulation is essential for healthy functioning (Berking & Wupperman, 2012; Rehm & Staiger, 2018). However, we need to gain more insights into the interplay of emotions and mental health. We can optimize treatment, when we have a better understanding of the way patients not only dysregulate their everyday emotions, but also their moods and affects. To reiterate a statement made in the introduction of this thesis, the research on affect, mood, and emotion is not an area of singular constructs or singular theories (Ekkekakis, 2012). “To the contrary, it is an area characterized by a very long history, a vast literature, an astounding diversity of theoretical views, and considerable confusion and controversy” (Ekkekakis, 2012; p. 330). However, despite some yet to be resolved challenges, affective phenomena and their regulation have a significant heuristic value for research in mental health. A better understanding of affective phenomena and their regulation is, therefore, crucial in order to promote the investigation of emotions and their impact on mental health. The present thesis aimed at making a small yet empirical contribution to this end.
103 References
References
Abramowitz, J. S., Deacon, B. J., & Whiteside, S. P. (2011). Exposure Therapy for Anxiety:
Principles and Practice. New York, NY: Guilford Press.
Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across
psychopathology: a meta-analytic review. Clinical Psychology Review, 30, 217–237.
American Psychiatric Association (2013). Diagnostic and statistical manual of mental
disorders (5th ed.). Arlington, VA: American Psychiatric Association.
Barlow, D. H., Farchione, T. J., Fairholme, C. P., Ellard, K. K., Boisseau, C. L., Allen, L. B.,
& Ehrenreich, J. T. (2011). Unified Protocol for Transdiagnostic Treatment of Emotional
Disorders: Therapist Guide. New York, NY: Oxford University Press.
Barrett, L. F., Mesquita, B., Ochsner, K. N., & Gross, J. J. (2007). The Experience of
Emotion. Annual Review of Psychology, 58(1), 373–403.
Batson, C. D., Shaw, L. L., & Oleson, K. C. (1992). Differentiating Affect, Mood, and
Emotion: Toward Functionally-Based Conceptual Distinctions. In M. S. Clark (Ed.),
Review of Personality and Social Psychology (Vol. 13, pp. 294-326). Newbury Park,
CA: Sage.
Beck, A. T., & Haigh, E. A. (2014). Advances in cognitive theory and therapy: the generic
cognitive model. Annual Review of Clinical Psychology, 10, 1-24.
Beddington, J., Cooper, C. L., Field, J., Goswami, U., Huppert, F. A., Jenkins, R., Jones, H.
S., Kirkwood, T. B. L., Sahakian, B. J., & Thomas, S. M. (2008). The mental wealth of
nations. Nature, 455, 1057-1060.
Berking, M., & Wupperman, P., (2012). Emotion regulation and mental health: recent
findings, current challenges, and future directions. Current Opinion in Psychiatry, 25(2),
128–134.
Bradley, M. M., & Lang, P.J. (2000). Measuring emotion: Behavior, feeling, and physiology.
In R. D. Lane & L. Nadel (Eds.), Cognitive neuroscience of emotion (pp. 242-276). New
104 References
York, NY: Oxford University Press.
Byrd, D., & McKinney, K. (2012). Individual, interpersonal, and institutional level factors
associated with the mental health of college students. Journal of American College
Health, 60(3), 185–193.
Campbell-Sills, L., & Barlow, D. H. (2007). Incorporating emotion regulation into
conceptualizations and treatments of anxiety and mood disorders. In J. J. Gross (Ed.),
Handbook of emotion regulation (pp. 542–559). New York, NY: Guilford Press.
Campbell-Sills, L., Barlow, D. H., Brown, T. A., & Hofmann, S. G. (2006). Effects of
suppression and acceptance on emotional responses of individuals with anxiety and
mood disorders. Behaviour Research and Therapy, 44(9), 1251-1263.
Clark, D. A., & Beck, A. T. (2010). Cognitive Theory and Therapy of Anxiety and
Depression: Convergence with Neurobiological Findings. Trends in Cognitive Science,
14, 418-424.
Colibazzi, T., Posner, J., Wang, Z., Gorman, D., Gerber, A., Yu, S., … Peterson, B. S. (2010).
Neural Systems Subserving Valence and Arousal During the Experience of Induced
Emotions. Emotion, 10(3), 377-389.
Craske, M. G., Treanor, M., Conway, C. C., Zbozinek, T., & Vervliet, B. (2014). Maximizing
exposure therapy: An inhibitory learning approach. Behaviour Research and Therapy,
58, 10-23.
Dalai Lama, & Cutler, H. (1998). The Art of Happiness: A Handbook for Living. Rockland:
Compass Press.
D’Avanzato, C., Joormann, J., Siemer, M., & Gotlieb, I. H. (2013). Emotion Regulation in
Depression and Anxiety: Examining Diagnostic Specificity and Stability of Strategy
Use. Cognitive Therapy and Research, 37, 968–980.
Davidson, R. J., (1998). Affective style and affective disorders: Perspectives from affective
neuroscience. Cognition and Emotion, 12, 307–330.
105 References
Davidson, R. J., (2000). Affective style, psychopathology, and resilience: brain mechanisms
and plasticity. American Psychologist, 55, 1196–1214.
Davidson, R. J., (2002). Anxiety and Affective Style: Role of Prefrontal Cortex and
Amygdala. Biological Psychiatry, 51, 68–80.
Deci, E. L., & Ryan, R. M. (2008). Hedonia, eudaimonia, and well-being: An introduction.
Journal of Happiness Studies, 9, 1–11.
Dennis, T.A., (2007). Interactions between emotion regulation strategies and affective style:
Implications for trait anxiety versus depressed mood. Motivation and Emotion, 31, 200–
207.
Dolan, R. J. (2002). Emotion, Cognition, and Behavior. Science’s Compass, 298, 1191-1194.
Ekkekakis, P. (2012). Affect, Mood, and Emotion. In G. Tenenbaum, R. C. Eklund, and A.
Kamata (Eds.), Measurement in Sport and Exercise Psychology (pp. 321- 332).
Champaign, IL: Human Kinetics.
Ekman, P. (1972). Universals and cultural differences in facial expressions of emotion. In J.
R. Cole (Ed.), Nebraska Symposium on Motivation (Vol. 19, pp. 207–283). Lincoln:
University of Nebraska Press.
Ekman, P. (1973). Cross-cultural studies of facial expression. In P. Ekman (Ed.), Darwin and
facial expression: A century of research in review (pp. 169–222). New York, NY:
Academic Press.
Ekman, P., & Cordaro, D. (2011). What is meant by calling emotions basic. Emotion Review,
3, 364–370.
Etkin, A., Büchel, C., & Gross, J. J. (2015). The neural bases of emotion regulation. Nature
Reviews Neuroscience, 16, 693-700.
Frijda, N. H. (1994). Varieties of affect: Emotions and episodes, moods, and sentiments. In P.
Ekman & R. J. Davidson (Eds.), The nature of emotion (pp. 59-67). New York, NY:
Oxford University Press.
106 References
Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-
and-build theory of positive emotions. American Psychologist, 56, 218–226.
Fredrickson, B. L. (2013). Positive emotions broaden and build. Advances in Experimental
Social Psychology, 47, 1–53.
Fredrickson, B. L., Cohn, M. A., Coffey, K. A., Pek, J., & Finkel, S. M. (2008). Open hearts
build lives: Positive emotions, induced through loving-kindness meditation, build
consequential personal resources. Journal of Personality and Social Psychology, 95,
1045–1062.
Fu, C.-S. (2012). What are Emotions in Chinese Confucianism? Linguistics for Intercultural
Education, 1, 78-93.
Fusar-Poli, P., Placentino, A., Carletti, F., Landi, P., Allen, P., Surguladze, S., … Politi, P.
(2009). Functional atlas of emotional faces processing: a voxel-based meta-analysis of
105 functional magnetic resonance imaging studies. Journal of Psychiatry &
Neuroscience, 34(6), 418–432.
Gerdes, A. B., Wieser, M. J., & Alpers, G. W. (2014). Emotional pictures and sounds: a
review of multimodal interactions of emotion cues in multiple domains. Frontiers in
psychology, 5, 1351.
Giuliani, N. R., McRae, K., & Gross, J. J. (2008). The up- and down-regulation of
amusement: experiential, behavioral, and autonomic consequences. Emotion, 8(5), 714-
719.
Graser, J., Bohn, C., Kelava, A., Schreiber, F., Hofmann, S. G., & Stangier, U. (2012). Der
“Affective Style Questionnaire (ASQ)”: Deutsche Adaption und Validitäten.
Diagnostica, 58(2), 100–111.
Gray, J. R., Schaefer, A., Braver, T. S., & Most, S. B. (2005). Affect and the resolution of
cognitive control dilemmas. Emotion and Consciousness (pp. 67–94). New York, NY:
Guilford Press.
107 References
Greening, S. G., Lee, T-H., & Mather, M. (2014). A dual process for the cognitive control of
emotional significance: implications for emotion regulation and disorders of emotion.
Frontiers in Human Neuroscience, 8, 253.
Gross, J. J. (1998a). Antecedent- and Response-Focused Emotion Regulation: Divergent
Consequences for Experience, Expression, and Physiology. Journal of Personality and
Social Psychology, 74, 224-237.
Gross, J. J. (1998b). The Emerging Field of Emotion Regulation: An Integrative Review.
Review of General Psychology, 2, 271-299.
Gross, J. J. (2002). Emotion regulation: Affective, cognitive, and social consequences.
Psychophysiology, 39, 281-291.
Gross, J. J. (2015). Emotion Regulation: Current Status and Future Prospects. Psychological
Inquiry, 26, 1–26.
Gross, J. J., & Jazaieri, H. (2014). Emotion, Emotion Regulation, and Psychopathology: An
Affective Science Perspective. Clinical Psychological Science, 2(4), 387-401.
Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes:
Implications for affect, relationships, and well-being. Journal of Personality and Social
Psychology, 85, 348–362.
Gross, J. J., & Levenson, R. W. (1997). Hiding Feelings: The Acute Effects of Inhibiting
Negative and Positive Emotion. Journal of Abnormal Psychology, 106, 95-103.
Gross, J. J., & Muñoz, R. F. (1995). Emotion regulation and mental health. Clinical
Psychology Science and Practice, 2, 151-164.
Gross, J. J., Richards, J. M., & John, O. P. (2006). Emotion Regulation in Everyday Life. In
D. K. Snyder, J. Simpson, & J. N. Hughes (Eds.), Emotion regulation in couples and
families: Pathways to dysfunction and health (pp. 13-35). Washington, DC: American
Psychological Association.
Hofmann S. G. (2007). Cognitive factors that maintain social anxiety disorder: A
108 References
comprehensive model and its treatment implications. Cognitive Behaviour Therapy,
36(4), 193–209.
Hofmann, S. G. (2012). Emotion in Therapy: From Science to Practice. New York, NY:
Guilford Press.
Hofmann, S. G., Ellard, K. K., & Siegle, G. J. (2012). Neurobiological correlates of
cognitions in fear and anxiety: a cognitive-neurobiological information-processing
model. Cognition & Emotion, 26(2), 282–299.
Hofmann, S. G., Grossman, P., & Hinton, D. E. (2011). Loving-kindness and compassion
meditation: Potential for psychological interventions. Clinical Psychology Review, 31,
1126–1132.
Hofmann, S. G., & Kashdan, T. B. (2010). The Affective Style Questionnaire: Development
and psychometric properties. Journal of Psychopathology and Behavioral Assessment,
32, 255–263.
Hofmann, S. G., Sawyer, A. T., Fang, A., & Asnaani, A. (2012). Emotion dysregulation
model of mood and anxiety disorders. Depression and Anxiety, 29, 409–416.
Hofmann, S. G., & Smits, J. A. J. (2008). Cognitive-behavioral therapy for adult anxiety
disorders: A meta-analysis of randomized placebo-controlled trials. Journal of Clinical
Psychiatry, 69, 621-632.
Ito, M., & Hofmann, S. G. (2014). Culture and affect: The factor structure of the Affective
Style Questionnaire and its relation with depression and anxiety among Japanese. BMC
Research Notes, 7, 590.
Izard, C. E. (2002). Translating emotion theory and research into preventive interventions.
Psychological Bulletin, 128, 796–824.
Izard, C. E. (2007). Basic Emotions, Natural Kinds, Emotion Schemas, and a New Paradigm.
Perspectives on Psychological Science, 2(3), 260–280.
Izard, C. E. (2009). Emotion Theory and Research: Highlights, Unanswered Questions, and
109 References
Emerging Issues. Annual Review of Psychology, 60, 1-25.
Izard, C. E. (2011). Forms and functions of emotions: Matters of emotion–cognition
interactions. Emotion Review, 3, 371–378.
Jack, R. E., Garrod, O. G. B., & Schyns, P. G. (2014). Dynamic Facial Expressions of
Emotion Transmit an Evolving Hierarchy of Signals over Time. Current Biology, 24,
186-192.
John, O. P., & Gross, J. J. (2004). Healthy and Unhealthy Emotion Regulation: Personality
Processes, Individual Differences, and Life Span Development. Journal of Personality,
72, 1301-1334.
Kalisch, R., Wiech, K., Critchley, H. D., Seymour, B., O’Doherty, J. P., Oakley, D. A., Allen,
P., & Dolan, R. J. (2005). Anxiety Reduction through Detachment: Subjective,
Physiological, and Neural Effects. Journal of Cognitive Neuroscience, 17, 874-883.
Kessler, R. C., Amminger, G. P., Aguilar-Gaxiola, S., Alonso, J., Lee, S., & Ustün, T. B.
(2007). Age of onset of mental disorders: a review of recent literature. Current Opinion
in Psychiatry, 20(4), 359-64.
Keyes, C. L. M. (2005). Mental illness and/or mental health? Investigating axioms of the
complete state model of health. Journal of Consulting and Clinical Psychology, 73, 539–
548.
Keyes, C. L. M., Fredrickson, B. L., & Park., N. (2012). Positive psychology and the quality
of life. In K. C. Land, A. C. Michalos, and M. J. Sirgy (Eds.), Handbook of Social
Indicators and Quality of Life Research (pp. 99-112), Dortrecht, Netherlands: Springer.
Keyes, C. L. M., Shmotkin, D., & Ryff, C. D. (2002). Optimizing well-being: The empirical
encounter of two traditions. Journal of Personality and Social Psychology, 82, 1007–
1022.
Kober, H. (2014). Emotion regulation in substance use disorders. In J. J. Gross (Ed.),
Handbook of emotion regulation (pp. 428-446). New York, NY: Guilford Press.
110 References
Koenig, S., & Mecklinger, A. (2008). Electrophysiological correlates of encoding and
retrieving emotional events. Emotion, 8(2), 162-73 .
Kohn, N., Eickhoff, S. B., Scheller, M., Laird, A. R., Fox, P. T., & Habel, U. (2014). Neural
network of cognitive emotion regulation - An ALE meta-analysis and MACM analysis.
NeuroImage, 87, 345–355.
LeDoux, J. E. (1992). Brain Mechanisms of Emotion and Emotional Learning. Current
Opinion in Neurobiology, 2, 191-197.
LeDoux, J. E. (2003). The emotional brain, fear, and the amygdala. Cellular and Molecular
Neurobiology, 23(4-5), 727-38.
Lench, H. C., Flores, S. A., & Bench, S. W. (2011). Discrete Emotions Predict Changes in
Cognition, Judgment, Experience, Behavior, and Physiology: A Meta-Analysis of
Experimental Emotion Elicitations. Psychological Bulletin, 137(5), 834-855.
Levenson, R. W. (2011). Basic emotion questions. Emotion Review, 3, 379–386.
Levine, D., Marziali, E., & Hood, J. (1997). Emotion Processing in Borderline Personality
Disorders. The Journal of Nervous & Mental Disease, 185(4), 240-246.
Lindquist, K., Wager, T., Kober, H., Bliss-Moreau, E., & Barrett, L. (2012). The brain basis
of emotion: A meta-analytic review. Behavioral and Brain Sciences, 35(3), 121-143.
Linehan, M. M. (1996a). Dialektisch-Behaviorale Therapie der Borderline-
Persönlichkeitsstörung. München: CIP-Medien.
Linehan, M. M. (1996b). Trainingsmanual zur Dialektisch-Behaviorale Therapie der
Borderline-Persönlichkeitsstörung. München: CIP-Medien.
Lipson, S., Gaddis, S., Heinze, J., Beck, K., & Eisenberg, D. (2015). Variations in student
mental health and treatment utilization across U.S. colleges and universities. Journal of
American College Health, 63(6), 388-396.
Lischetzke, T. & Eid, M. (2011). Diagnostik affektiver Zustände. In L. F. Hornke, M.
Amelang, & M. Kersting (Eds.), Persönlichkeitsdiagnostik (pp. 411-465). Göttingen:
111 References
Hogrefe.
Lischetzke, T., Angelova, R., & Eid, M. (2011). Validating an indirect measure of clarity of
feelings: Evidence from laboratory and naturalistic settings. Psychological Assessment,
23(2), 447–455.
Lochner, K. (2016). Affect, Mood, and Emotions. In Successful Emotions: How Emotions
Drive Cognitive Performance (pp. 43–67). Wiesbaden: Springer.
Lukat, J., Margraf, J., Lutz, R., van der Veld, W. M., & Becker, E. S. (2016). Psychometric
properties of the positive mental health scale (PMH-scale). BMC Psychology, 4, 1–14.
Margraf, J., & Ehlers, A. (1989). Etiological models of panic — psychophysiological and
cognitive aspects. In R. Baker (Ed.), Panic Disorder: Research and Therapy. London:
Wiley.
May, C. J., Weyker, J. R., Spengel, S. K., Finkler, L. J., & Hendrix, S. E. (2014). Tracking
longitudinal changes in affect and mindfulness caused by concentration and loving-
kindness meditation with hierarchical linear modeling. Mindfulness, 5(3), 249-258.
Mennin, D. S., Heimberg, R. G., Turk, C. L., & Fresco, D. M. (2005). Preliminary evidence
for an emotion regulation deficit model of generalized anxiety disorder. Behaviour
Research and Therapy, 43, 1281– 1310.
Ochsner, K. N., & Gross, J. J. (2005). The cognitive control of emotion. Trends in Cognitive
Sciences, 9, 242-249.
Ochsner, K. N., Bunge, S. A., Gross, J. J., & Gabrieli, J. D. E. (2002). Rethinking feelings: an
fMRI study of the cognitive regulation of emotion. Journal of Cognitive Neuroscience,
14, 1215–1229.
Patel, R., Lloyd, T., Jackson, R., Ball, M., Shetty, H., Broadbent, M., … Taylor, M. (2015).
Mood instability is a common feature of mental health disorders and is associated with
poor clinical outcomes. BMJ open, 5(5), e007504.
Panksepp, J., & Watt, D. (2011). What is basic about basic emotions? Lasting lessons from
112 References
affective neuroscience. Emotion Review, 3, 387–396.
Peterson, C. (2006). A primer in positive psychology. New York, NY: Oxford University
Press.
Plutchik, R. (1980). A general psychoevolutionary theory of emotion. In R. Plutchik & H.
Kellerman (Eds.), Emotion: Theory, research, and experience: Vol. 1. Theories of
emotion (pp. 3-33). New York, NY: Academic.
Porter, E., & Chambless, D. L. (2015). A systematic review of predictors and moderators of
improvement in cognitive-behavioral therapy for panic disorder and agoraphobia.
Clinical Psychology Review, 42, 179–192.
Putnam, K., M., & Silk, K. R. (2005). Emotion dysregulation and the development of
borderline personality disorder. Development and Psychopathology, 17, 899–925.
Quoidbach, J., Berry, E. V., Hansenne, M., & Mikolajczak, M. (2010). Positive emotion
regulation and well-being: Comparing the impact of eight savoring and dampening
strategies. Personality and Individual Differences, 49(5), 368-373.
Regehr, C., Glancy, D. R., & Pitts, A. (2013). Interventions to reduce stress in university
students: a review and meta-analysis. Journal of Affective Disorders, 148(1), 1-11.
Rehm, I., & Staiger, R. (2018). Emotion regulation and psychopathology: Current
understanding and new directions. Clinical Psychologist, 22(2), 109–111.
Richards, J. M., & Gross, J. J. (2000). Emotion Regulation and Memory: The Cognitive
Costs of Keeping One’s Cool. Journal of Personality and Social Psychology, 79, 410-
424.
Ruhmland, M., & Margraf, J. (2001a). Effektivität psychologischer Therapien von
generalisierter Angststörung und sozialer Phobie: Meta-Analysen auf Störungsebene.
Verhaltenstherapie, 11, 27-40.
Ruhmland, M., & Margraf, J. (2001b). Effektivität psychologischer Therapien von Panik und
Agoraphobie: Meta-Analysen auf Störungsebene. Verhaltenstherapie, 11, 41-53.
113 References
Ruhmland, M., & Margraf, J. (2001c). Effektivität psychologischer Therapien von
spezifischer Phobie und Zwangsstörung: Meta-Analysen auf Störungsebene.
Verhaltenstherapie, 11, 14-26.
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social
Psychology, 39, 1161-1178.
Russell, J. A., & Barrett, L. F. (1999). Core affect, prototypical emotional episodes, and other
things called emotion: Dissecting the elephant. Journal of Personality and Social
Psychology, 76, 805-819.
Scherer, K. R. (1984). On the nature and function of emotion: A component process
approach. In K. R. Scherer & P.E. Ekman (Eds.), Approaches to emotion (pp. 293–317).
Hillsdale, NJ: Erlbaum.
Scherer, K. R. (2005). What are emotions? And how can they be measured? Social Science
Information, 44(4), 695–729.
Schönfeld, P., Brailovskaia, J., & Margraf, J. (2017). Positive and negative mental health
across the lifespan: A cross-cultural comparison. International Journal of Clinical and
Health Psychology, 17, 197-206.
Sheppes, G., Suri, G., & Gross, J. J. (2015). Emotion regulation and psychopathology. Annual
Review of Clinical Psychology, 11, 379-405.
Sim, L., & Zeman, J. (2004). Emotion awareness and identification skills in adolescent girls
with bulimia nervosa. Journal of Clinical Child and Adolescent Psychology, 33(4), 760-
771.
Singer, T., Snozzi, R., Bird, G., Petrovic, P., Silani, G., Heinrichs, M., & Dolan, R. J. (2008).
Effects of oxytocin and prosocial behavior on brain responses to direct and vicariously
experienced pain. Emotion, 8(6), 781-791.
Soet, J., & Sevig, T. (2006). Mental Health Issues Facing a Diverse Sample of College
Students: Results from the College Student Mental Health Survey. Journal of Student
114 References
Affairs Research and Practice, 43(3), 410-431.
Thompson, R. A. (1994). Emotion Regulation: A Theme in Search of Definition.
Monographs of the Society for Research in Child Development, 59, 25-52.
Tooby, J., & Cosmides, L. (1990a). The past explains the present: emotional adaptations and
the structure of ancestral environments. Ethology and Sociobiology, 11, 375–424.
Tooby, J., & Cosmides, L. (1990b). On the universality of human nature and the uniqueness
of the individual: The role of genetics and adaptation. Journal of Personality, 58, 17–67.
Tooby, J., & Cosmides, L. (2008). The Evolutionary Psychology of the Emotions and Their
Relationship to Internal Regulatory Variables. In M. Lewis, J. M. Haviland-Jones & L.
F. Barrett (Eds.), Handbook of Emotions, 3rd Ed. (pp. 114-137.) New York, NY:
Guilford Press.
Torre, J. (2011). Emotional control strategies we use for regulating our emotions. On
psychology in action. https://psychinaction.wordpress.com/2011/04/08/emotional-
control-strategies-we-use-for-regulating-our-emotions/
Tracy, J. L., & Randles, D. (2011). Four Models of Basic Emotions: A Review of Ekman and
Cordaro, Izard, Levenson, and Panksepp and Watt. Emotion Review, 3(4), 397–405.
Trompetter, H. R., Lamers, S. M. A., Westerhof, G. J., Fledderus, M., & Bohlmeijer, E. T.
(2017). Both positive mental health and psychopathology should be monitored in
psychotherapy: Confirmation for the dual-factor model in acceptance and commitment
therapy. Behaviour Research and Therapy, 91, 58–63.
Trumpf, J., Becker, E. S., Vriends, N., Meyer, A. H., & Margraf, J. (2009). Rates and
predictors of remission in young woman with specific phobia. Journal of Anxiety
Disorders, 23, 958–964.
Tugade, M. M., & Fredrickson, B. L. (2004). Resilient individuals use positive emotions to
bounce back from negative emotional experiences. Journal of Personality and Social
Psychology, 86, 320–333.
115 References
Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., &
Marschall, S. (2016). Emotion Elicitation: A Comparison of Pictures and Films.
Frontiers in Psychology, 7(180), 1-12.
Vriends, N., Becker, E., Meyer, A., Williams, S., Lutz, R., & Margraf, J. (2007). Recovery
from social phobia in the community and its predictors. Journal of Anxiety Disorders,
21, 320–337.
Westen, D. (1994). Toward an Integrative Model of Affect Regulation: Applications to
Social‐Psychological Research. Journal of Personality, 62, 641-667.
Yik, M., Russell, J. A., & Steiger, J. H. (2011). A 12-Point Circumplex Structure of Core
Affect. Emotion, 11(4), 705-731.
Zeng, X., Chiu, C. P. K., Wang, R., Oei, T. P. S., & Leung, F. Y. K. (2015). The effect of
loving-kindness meditation on positive emotions: a meta-analytic review. Frontiers in
Psychology, 6, 1693.
116 Appendix
Curriculum Vitae
Personal Details Name: Dipl. Psych. Christina M. Totzeck Work address: Massenbergstrasse 9-13, BF 03/19, 44787 Bochum, Germany Home address: Munckelstrasse 15, 45879 Gelsenkirchen, Germany
Education Since 2012 PhD student, Department of Clinical Psychology and Psychotherapy, Ruhr-Universität Bochum, Germany 2009 – 2012 Post graduate training (Staatsexamen) in cognitive behavioral therapy, Mental Health Research and Treatment Center, Ruhr-Universität Bochum, Germany 2003 – 2008 Studies of Psychology (Diplom), Ruhr-Universität Bochum, Germany (Diploma Thesis at the Department of Cognitive Neurosciences) 2003 Higher education entrance qualification (Abitur), Carl-Friedrich-Gauß- Gymnasium Gelsenkirchen, Germany 2001 High School Diploma, Ponderosa High School, Shingle Springs, CA, USA
Professional Experience Since 2015 Clinical project management of the multicenter RCT study PROTECT- AD P1 (BMBF grant no. 01FF1402A), Ruhr-Universität Bochum, Germany 2012 – 2015 Clinical psychologist, Mental Health Research and Treatment Center, Ruhr-Universität Bochum 2010 – 2012 Research assistant in the German Research foundation (DFG) project “MBCT for chronic depression”, Ruhr-Universität Bochum and Stiftungs Universität Hildesheim, Germany 2009 – 2010 Clinical psychologist, LWL Clinic Dortmund-Aplerbeck, Germany 2007 – 2009 Student assistant, TRIALOG – Residential treatment center for adolescents with schizophrenia, Essen and Düsseldorf, Germany 05-06/2007 Research internship, University of Washington, Seattle, WA, USA
Scholarships and Awards 2017 Travel Award (VGA GmbH) for the 44th Annual Congress of the European Association for the Behavioural and Cognitive Therapies, Ljubljana, Slovenia 2016 Travel Award (VGA GmbH) for the 8th World Congress of the Behavioural and Cognitive Therapies, Melbourne, Australia 2012 – 2015 PhD scholarship, Konrad Adenauer Foundation (KAS) 2013 Travel Award (KAS) for the 43rd Annual Congress of the European Association for Behavioural and Cognitive Therapies, Marrakesh, Morocco.
117 Appendix
List of Publications
Submitted for publication
Totzeck, C., Zhang, X. C., Pflug, V., Teismann, T., Margraf, J., & Adolph, D. Old movies vs. new movies – Development and validation of a new emotional film set. Manuscript submitted for publication. [included in this thesis]
Pflug, V., Zhang, X. C., Totzeck, C., In-Albon, T., & Schneider, S. Vigilance, maintenance, and avoidance in visual attention of children with social phobia and separation anxiety disorder. Manuscript submitted for publication.
Totzeck, C., Teismann, T., Hofmann, S. G., von Brachel, R., Pflug, V., Wannemüller, A., & Margraf, J. May you be happy – Loving-kindness meditation promotes mental health in university students. Manuscript submitted for publication. [included in this thesis]
Journal Articles
Totzeck, C., Teismann, T., Hofmann, S.G., von Brachel, R., Zhang, X.C., Wannemüller, A., Pflug, V., & Margraf, J. (in press). Affective Styles in Panic Disorder and Specific Phobia: Changes Through Cognitive Behavior Therapy and Prediction of Remission. Behavior Therapy. https://doi.org/10.1016/j.beth.2019.06.006 [included in this thesis]
Raeder, F., Woud, M.L., Schneider, S., Totzeck, C., Adolph, A., Margraf, J., & Zlomuzica, A. (2019). Reactivation and Evaluation of Mastery Experiences Promotes Exposure Benefit in Height Phobia. Cognitive Therapy and Research, 43(5), 948-958.
Totzeck, C., Teismann, T., Hofmann, S.G., Pflug, V., von Brachel, R., Zhang, X. & Margraf, J. (2018). Affective Styles in mood and anxiety disorders – clinical validation of the “Affective Style Questionnaire” (ASQ). Journal of Affective Disorders, 238, 392-398. [included in this thesis]
Teismann, T, Brailovskaia, J, Totzeck, C, Wannemüller, A & Margraf, J (2018). Predictors of remission from panic disorder, agoraphobia and specific phobia in outpatients receiving exposure therapy: The importance of positive mental health. Behaviour Research and Therapy, 108, 40-44. [included in this thesis]
Heinig, I., Pittig, A., Richter, J., Hummel, K., Alt, I., Dickhöver, K., Gamer, J., Hollandt, M., Koelkebeck, K., Maenz, A., Tennie, S., Totzeck, C., … & Wittchen, H.U. (2017).
118 Appendix
Optimizing exposure-based CBT for anxiety disorders via enhanced extinction: Design and methods of a multicentre randomized clinical trial. International Journal of Methods in Psychiatric Research, 2017, e1560.
Zlomuzica, A., Preusser, F., Totzeck, C., Dere, E., & Margraf, J. (2016). The impact of different emotional states on the memory for what, where and when features of specific events. Behavioural Brain Research, 298, 181-187.
Michalak, J., Totzeck, C., & Heidenreich, T. (2011). Mit Achtsamkeit gegen Depressionen. Ärztliche Praxis Neurologie und Psychiatrie, 3, 24-28.
Book Chapters
Totzeck, C. (2018). Artifizielle Störungen (Factitious Disorders). In J. Margraf & S. Schneider (Eds.). Lehrbuch der Verhaltenstherapie, Band 2: Psychologische Therapie bei Indikationen im Erwachsenenalter (pp. 445-454). Berlin: Springer.
Eggers, C., & Totzeck, C. (2011). Soziale Kognitionen (Social cognitions). In C. Eggers (Ed.) Schizophrenie des Kindes- und Jugendalters (pp. 55-58). Berlin: MWV.
Eggers, C., & Totzeck, C. (2011). Kognitionen (Cognitions). In C. Eggers (Ed.) Schizophrenie des Kindes- und Jugendalters (pp. 52-55). Berlin: MWV.
119 Appendix
Conference Presentations Organized Symposia
Totzeck, C. (2019). Neue Entwicklungen in der Kognitiven Verhaltenstherapie bei Angststörungen (New Developments in cognitive-behavioral therapy for anxiety disorders). Symposium at the 9th World Congress of Behavioural and Cognitive Therapies (WCBCT), Berlin, Germany.
Talks and Poster Presentations
Totzeck, C. (2019). Dysfunktionen der Emotionsregulation bei Angststörungen sowie deren Veränderungen durch Expositionstherapien (Dysfunctional emotion regulation in anxiety disorders, and changes through exposure therapy). Talk at the 9th World Congress of Behavioural and Cognitive Therapies (WCBCT), Berlin, Germany.
Totzeck, C., & Jürgen Margraf (2019). Effects of Munchausen Syndrome by Proxy on Victim’s Health. Poster presented at the 9th World Congress of Behavioural and Cognitive Therapies (WCBCT), Berlin, Germany.
Totzeck, C., Teismann, T., Hofmann, S. G., von Brachel, R., Zhang, X. C., Wannemüller, A., Pflug, V., & Margraf, J. (2019). Affective styles in panic disorder and specific phobia: Changes through cognitive behavior therapy and prediction of remission. Poster presented at the pre-conference symposium, 14-16 July, Bochum, Germany.
Preusser, F., Schneider, S., Adolph, D., Totzeck, C., Margraf, J., & Zlomuzica, A. (2018). Reactivation of positive mastery experiences boosts exposure-like treatment outcome. Poster presented at the International Graduate School of Neuroscience (IGSN) conference on “extinction learning: the neural, behavioural, ontogenetic, educational and clinical mechanisms”, Bochum, Germany.
Totzeck, C., von Brachel, R., Pflug, V., Siempelkamp, D., & Margraf, J. (2017). Affective styles and their changes during CBT. Poster presented at the 43th congress of the European Association for Behavioural and Cognitive Therapies (EABCT), Ljubljana, Slovenia.
Preusser, F., Schneider, S., Totzeck, C., Margraf, J., & Zlomuzica, A. (2017). The impact of cognitive regulation strategies on extinction-based therapy outcome. Poster presented at the 47th European Brain and Behavior Society (EBBS) Meeting, Bilbao, Spain.
120 Appendix
Totzeck, C., Zhang, X. C., Hofmann, S. G., Teismann, T., & Margraf, J. (2016). CBT changes affective styles in anxiety disorders. Poster presented at the 8th World Congress of Behavioural and Cognitive Therapies (WCBCT), Melbourne, Australia.
Bieda, A., Totzeck, C., Scholten, S., Zhang, X., & Margraf, J. (2016). Are all happy families really alike? An examination of the structure of well-being. Talk at the 8th Congress of the European Conference of Positive Psychology (ECPP), Angers, France.
Totzeck, C., & Margraf, J. (2015). Ändert Verhaltenstherapie Emotionsregulation? (Does CBT change emotion regulation?). E-Poster presented at the 33rd symposium for clinical psychology and psychotherapy of group of clinical psychology and psychotherapy of the German Association of Psychology (DGPs), Dresden, Germany.
Totzeck, C., Adolph, D., & Margraf, J. (2014). Entwicklung und Validierung eines Filmsets zur Emotionsinduktion (Development and validation of a new emotion induction film set). Poster presented at the 49th congress of the German Association of Psychology (DGPs), Bochum, Germany.
Totzeck, C., & Michalak, J. (2013). Affective styles in a clinical population. Poster presented at the 43th congress of the European Association for Behavioural and Cognitive Therapies (EABCT), Marrakech, Morocco.
121