A Test of the Habit-Goal Framework of Depressive Rumination and its Relevance to Cognitive Reactivity

Journal Pre-proof A Test of the Habit-Goal Framework of Depressive Rumination and its Relevance to Cognitive Reactivity

Ragnar P. Ólafsson, Sigfríð J. Guðmundsdóttir, Tanja D. Björnsdóttir, Ivar Snorrason PII:

S0005-7894(19)30110-8

DOI:

https://doi.org/10.1016/j.beth.2019.08.005

Reference:

BETH 928

To appear in:

Behavior Therapy

Received date:

4 January 2019

Accepted date:

8 August 2019

Please cite this article as: R.P. Ólafsson, S.J. Guðmundsdóttir, T.D. Björnsdóttir, et al., A Test of the Habit-Goal Framework of Depressive Rumination and its Relevance to Cognitive Reactivity, Behavior Therapy(2019), https://doi.org/10.1016/j.beth.2019.08.005

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Journal Pre-proof Running head: HABITUAL CHARACTERISTICS OF RUMINATION

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A Test of the Habit-Goal Framework of Depressive

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Rumination and its Relevance to Cognitive Reactivity

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Ragnar P. Ólafsson, Sigfríð J. Guðmundsdóttir, Tanja D. Björnsdóttir

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University of Iceland, Iceland

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Ivar Snorrason

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McLean Hospital/Harvard Medical School

Author Note

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Ragnar P. Ólafsson, Sigfríð J. Guðmundsdóttir and Tanja D. Björnsdóttir, Faculty of Psychology, School of Health Sciences, University of Iceland. Ivar Snorrason,

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McLean Hospital/Harvard Medical School.

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The study was supported by a research grant from the University of Iceland Research Fund, awarded to the first author. The authors declare no conflict of interest. Correspondence concerning this article should be addressed to Ragnar P. Ólafsson, Faculty of Psychology, University of Iceland, Nýi Garður, Sæmundargötu 12, 101 Reykjavík, Iceland. E-mail: [email protected]

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Abstract The aim of the present study was to test predictions derived from the habit-goal framework of depressive rumination and investigate its relevance to cognitive reactivity – another well-known vulnerability factor to depression. Formerly depressed (FD; n=20) and never depressed (ND; n=22) participants completed self-report measures of rumination, cognitive reactivity and habitual characteristics of rumination (e.g. lack of

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awareness, control, intent). A standard mood-induction task was also used to measure

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cognitive reactivity and an outcome-devaluation task to measure general habit vs. goal-

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directed behavior control. Habitual characteristics of ruminative thoughts were greater in

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the FD group and were related to depressive brooding and cognitive reactivity, but not reflective pondering. Reliance on habit on the outcome-devaluation task, was strongly

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correlated with number of depression episodes, although group differences were not

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observed in general habit vs. goal-directed control. Habitual characteristics of rumination (e.g. greater automaticity) may explain reactivity and persistence of negative thoughts in

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depression. Habitual behavior control may contribute to inflexible responding and

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vulnerability for depression episodes.

Keywords: major depression, vulnerability, rumination, habit, cognitive reactivity.

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A Test of the Habit-Goal Framework of Depressive Rumination and its Relevance to Cognitive Reactivity Inability to respond flexibly to changing situational demands is characteristic of many forms of psychopathology (Kashdan & Rottenberg, 2010). In depression, lack of flexible responding is evident in reactive and rigid ruminative thoughts and moodreactive negative attitudes. Depressive rumination is a passive mode of responding to

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distress by repetitively focusing on one’s problems and feelings of distress and their

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possible causes and consequences (Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008), and

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is well supported as a vulnerability marker for development and maintenance of

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depression (Mor & Winquist, 2002; Nolen-Hoeksema et al., 2008). The habit-goal framework of rumination

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Mental habits may underlie inflexible cognitive responding in depression.

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Watkins and Nolen-Hoeksema (2014) have recently proposed a habit-goal framework of rumination, that is based on the notion that patterns of negative thoughts in depression

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can be construed as mental habits that are initiated without awareness or effort (Hertel,

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2004). Habits may form through associative learning when responses are frequently contingent on particular contexts, resulting in stimulus triggered responses that are not mediated by personal goals (Wood & Neel, 2007). Habitual responses can be automatic in the way that they are initiated without conscious awareness, intent or effort and may be difficult to control (Verplanken, Friborg, Wang, Trafimow, & Wolf, 2007). According to the habit-goal framework, episodes of goal-directed ruminative thoughts arise because of perceived discrepancy between one’s goals and the progress towards these goals (cf. Martin & Tesser, 1996; Watkins, 2008). Because negative mood follows failed goal

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resolution, episodes of goal-directed rumination may over time develop into mood-linked habitual response tendencies if goals are frequently not reached. Situational factors that systematically thwart important personal goals (i.e. chronic stress, over-controlled parenting, reduced positive reinforcement, socialization factors), and person-specific factors that reduce flexible responding to environmental challenges (i.e. restricted coping repertoire, lack of behavioral and cognitive flexibility) should facilitate the formation of

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rumination as a habit (Watkins & Nolen-Hoeksema, 2014). According to the habit-goal

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framework, rumination should be more likely to develop into a mental habit if it is in the

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form of unconstructive passive and abstract depressive brooding, rather than reflective

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pondering, that is a more concrete and problem-focused way of thinking (Watkins & Nolen-Hoeksema, 2014).

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Rumination is frequently described as being habitual in the depression literature,

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although this has rarely been directly tested. Dysphoria and major depression are associated with lack of cognitive flexibility (e.g. Philippot & Brutoux, 2008) and reduced

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executive functioning (e.g. Snyder, 2013) that can make flexible and effortful behavior

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control more difficult, leaving people more susceptible to habitual responding in general (Wood & Rünger, 2016). Rumination also has some of the key characteristics of habitual behaviors, such as being difficult to control and lacking conscious intent (e.g. Watkins & Baracaia, 2001). Verplanken et al. (2007) administered the Habit Index of Negative Thinking (HINT) – a self-report questionnaire that measures habitual characteristics of negative thoughts (i.e. repetition, lack of conscious awareness and intent, mental efficiency, lack of control and self-descriptiveness of thought) in samples of university students. They found that, not only was HINT strongly correlated with measures of

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dysfunctional attitudes and ruminative thoughts, it also predicted increased symptoms of anxiety and depression over a 9 months interval. Habitual characteristics of negative thoughts may predispose people for symptoms of depression, suggesting it may be a characteristic of ruminative and other negative thoughts and independently contribute to cognitive vulnerability to depression. Habitual and goal-directed behavior control

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Interpersonal differences exist in ability to modulate behavior in general.

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Behaviour is guided by distinct but interrelated goal-directed and habit control systems

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with goal-directed control following predictions of future outcomes whereas habitual

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control being based on experiences of past reward (Dolan & Dayan, 2013). Individual differences in habit vs. goal-directed behavioural control have been found in different

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forms of psychopathology, including eating disorders, addiction and obsessive-

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compulsive disorder (e.g. Gillan & Robbins, 2014; Voon et al., 2015), where the balance between goal-directed and habit related behaviour control seems to be tilted towards

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greater habitual control, possibly contributing to more inflexible responding. The

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imbalance in interaction between the two systems can relate to difficulties implementing goal-directed control and may represent people’s general propensity towards faster formation of, or stronger, behavioural habits (Linnebank, Kindt, & de Wit, 2018). Individual differences in habitual vs. goal-directed behavioural control have been studied with outcome-devaluation tasks that assess people’s ability to alter behaviour when an outcome’s value changes. Previously trained responses that resulted in valued outcomes (i.e. were reinforced), lose their value as the outcome becomes devalued. Repeating previously reinforced but currently devalued responses (i.e. slips of action) can

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be taken as a persistence of previous goal-directed behaviour that has become habitual, and insensitive to outcome value. Recent evidence suggests that this paradigm may have relevance to the study of habitual characteristics of behaviors in real-life settings (Linnebank, et al., 2018). The habit-goal framework proposes that deficits in cognitive control may underly inflexible responding that, through specific context-response associations, can lead to

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formation of mental habits such as rumination (Watkins & Nolen-Hoeksema, 2014).

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Depression is indeed characterized with reduced flexibility across different domains of

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behaviors (Stange, Alloy, & Fresco, 2017) and poor performance on tasks measuring

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executive functioning (Snyder, 2013) or efficiency of specific cognitive control processes (Joormann & Tanovic, 2015), making goal-directed behavior control more difficult.

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Depression history is also strongly associated with stressful life events (Hammen, 2005),

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early adversities and more chronic forms of stress (Nelson, Klumparendt, Doebler & Ehring, 2016), that may make people more susceptible to habitual responding or even

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habit acquisition (Wood & Rünger, 2016). Depressed people or people with history of

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depression may therefore be more susceptible for habit formation across different behaviors, including mental habits. Other cognitive vulnerabilities According to the habit-goal framework, negative mood is the context that elicits cognitive responses (i.e. ruminations) in a habitual way (i.e. not mediated by goals). Although the framework focuses on rumination as a cognitive response, it may be relevant to other mood-linked cognitive vulnerabilities to depression. Cognitive reactivity is a well-known vulnerability factor and is the activation of negative thinking patterns

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resulting from increases in dysphoric mood (Lau, Segal, & Williams, 2004; Teasdale, 1999) that characterizes formerly depressed compared to never depressed groups (Scher, Ingram & Segal, 2005) and predicts relapse in depression (Segal, Gemar, & Williams, 1999; Segal et al., 2006). Although studies indicate that self-report measures of rumination and cognitive reactivity are strongly correlated (Moulds et al., 2008) and that these two vulnerabilities may be rooted in common underlying neural-networks for

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control of emotional activity (De Raedt & Koster, 2010; Farb, Irving, Anderson & Segal,

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2015), the study of them has mainly followed separate lines. Both constructs represent a

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form of self-focused attention, however, cognitive reactivity is focused on negative

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thought content (i.e. negative self-focused thoughts) while rumination is focused on a way of thinking (i.e. passive and abstract self-focused thoughts). In the present study, we

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investigate if cognitive reactivity is linked with habitual characteristics of rumination.

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Aims of the study and hypotheses

The aim of the present study was to test predictions derived from the habit-goal

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framework of rumination in individuals with or without a history of depression and

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explore its relevance to another well-known vulnerability factor – cognitive reactivity. Formerly depressed and never depressed university students were tested in a euthymic state to avoid confound with processes that are concomitant to, rather than posing vulnerability for, depression. Based on the habit-goal framework and previous research (e.g. Verplanken et al., 2007; Watkins & Baracaia, 2001), it was predicted that greater self-reported habitual characteristics of rumination (repetition, lack of conscious awareness and intent, mental efficiency, lack of control and self-descriptiveness of thought) would be observed in formerly compared to never depressed participants.

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Habitual characteristics of rumination were expected to be related to depressive brooding, rather than reflective pondering, and to cognitive reactivity. Because rumination as a habit should increase risk of depression, we expected habitual characteristics of rumination to be correlated to number of previous episodes in the formerly depressed group. As noted earlier, depression history may be associated with difficulties

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modulating behaviors in service of goals, that can make people more prone to habitual

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behaviors and to rely on less flexible response strategies. We explored if formerly

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depressed participants would be characterized by greater habit-directed, at the expense of

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goal-directed, control of behavior on an outcome-devaluation task. We explored if formerly depressed participants would show greater slips of action on this task and if

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such action slips would be related to habitual characteristics of rumination and number of

Method

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Participants

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previous depression episodes in formerly depressed participants.

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Participants were 42 students at the University of Iceland and were recruited through an Internet survey that was sent by e-mail to over 10.000 students at the university. The survey included a screening questionnaire for diagnosis of past and current major depressive episodes (the Major Depression Questionnaire; Van der Does, Barnhoefer, & Williams, 2003, see materials section) based on DSM-IV-TR criteria (APA, 2000). Students that were not currently depressed were contacted and offered to participate in a diagnostic interview for participation in the study. In all, 82 students were interviewed. The group of formerly depressed participants (FD) consisted of 20 students

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but 22 students were in the never-depressed group (ND). Only female students were included. Demographics and clinical history of participants is presented in Table 1. Inclusion criteria in the ND group was age between 18 and 65 years and participants were excluded if they met diagnostic criteria for any current psychiatric disorder or a history of a major depressive episode as assessed with the MINI diagnostic interview (see below). Inclusion criteria in the FD group was age between 18 and 65 years and a history of at

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least one major depressive episode (with ≥3 months from last episode), but exclusion

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criteria were current major depressive episode, current or past manic or hypomanic

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episode, and presence of psychotic disorders and substance abuse. We further excluded

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participants with moderate or severe depressive symptoms at study entry (BDI-II > 19). In total, 40 of those interviewed, were not included in the study for the following reasons:

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current episode of depression and/or BDI-II score > 19 (n=14); past manic/hypomanic

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episode (n=5); substance abuse (n=6); not meeting criteria for a past episode of

Materials

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depression (n=5), meeting criteria for a current psychiatric disorder (n=4); other (n=6).

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Psychiatric status: The Mini-International Neuropsychiatric Interview (M.I.N.I; Sheehan et al., 1998) was used to obtain psychiatric diagnoses. MINI is a semi structured interview for the most common Axis I disorder of the DSM-IV. Good interrater reliability and good convergent validity with lengthier diagnostic interviews such as the Composite International Diagnostic Interview (CIDI) have been reported for MINI (Sheehan et al., 1997). An Icelandic version of the MINI was administered for which adequate convergent validity with CIDI has been measured (Sigurðsson, 2008). The present study utilized a composite version of MINI with the depression module from MINI-Plus but

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other modules from the standard MINI. Questions were added at to assess number of past depressive episodes, duration of the index episode, as well as age at onset of first depression episode. After confirming the presence of a past major depressive episode with the MINI-Plus depression module, participants were asked to indicate how often they had experienced such an episode where symptoms of depression (just referred to) were present most of the day, nearly every day for two weeks or more and influencing

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daily life functioning during that period. Participants were asked to indicate the number

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and duration of such episodes that were followed by a period of two months or more with

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no symptoms of depression and age of onset of the first episode.

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Questionnaires

Demographics and treatment history: Information on participants age, gender,

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marital and occupational status, as well current and past treatment history (medications,

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psychotherapy, other) and number of previous hospital admission because of psychiatric problems, was obtained with an 11-item questionnaire constructed by the researchers.

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State positive and negative affect: Momentary positive and negative affective

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experiences were measured with the 20-item Positive and Negative Affect Scale (PANAS; Watson, Cark & Tellegen, 1988). The Icelandic translation has good internal consistency and validity (Halldórsson, 2007). Internal consistency of the positive (α=.85) and negative (α=.87) scales was good in the present study. Psychiatric symptoms: Severity of depression and anxiety symptoms was assessed with the Beck Depression Inventory-II (BDI-II; Beck, Steer & Brown, 1996) and Beck Anxiety Inventory (BAI; Beck & Steer, 1990). The Icelandic versions of the BDI (Arnason et al., 2008) and BAI (Sæmundsson et. al., 2011) possess good

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psychometric properties, including internal consistency and test-retest reliabilities. The internal consistency of the BDI (α=.76) and BAI (α=.79) was adequate in the present study. Cognitive vulnerabilities: Depressive rumination was measured with the Ruminative Response Scale (RRS; Nolen-Hoeksema & Morrow, 1991; Treynor et al., 2003), which includes 22 items that focus on rumination tendencies. The depressive

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brooding and reflective pondering subscales, containing five items each, were used in the

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present study to measure passive (brooding) and more active forms (pondering) of

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ruminative thinking. Factor analysis and validity estimates support the presence of two

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different subscales of brooding and reflective pondering, with both subscales being related to depression symptoms concurrently but only brooding being predictive of

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depression symptoms prospectively (Treynor et al., 2003). The Icelandic translation has

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good psychometric properties (Pálsdóttir & Pálsdóttir, 2008). The brooding (α=.89) and reflective pondering (α=.77) scales had good internal consistency in the present study.

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The Leiden Index of Depression Sensitivity-Revised (LEIDS-R; van der Does, 2002) was

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used to measure self-reported cognitive reactivity. The LEIDS-R includes 34 items and has good internal consistency and concurrent validity (Van der Does, 2002). The psychometric properties of the Icelandic translation are satisfactory (Ólafsson, 2016). Only the total score of the LEIDS-R was used in the present study and this scale had good internal consistency (α=.90). Habitual characteristics of rumination: The Self-Report Habit Index (SRHI; Verplanken & Orbell, 2003) was adapted to measure self-reported habitual characteristic of self-focused thoughts about one’s feelings, strengths and shortcomings. The SRHI has

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shown good test–retest reliability and has discriminant validity over and above past frequency of behavior in predicting future behavior (Verplanken & Orbell, 2003; Verplanken, 2006). The SRHI included a target (i.e. Please indicate what applies when you start thinking about your feelings, strengths and shortcomings) and 12 items tapping frequency, lack of conscious awareness and control, lack of conscious intent, and selfdescriptiveness of the target. Sample items are: 1. I do it frequently; 2. I do it

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automatically; and 6. It would require effort not to do it. Confirmatory factor analysis of

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the Icelandic translation in a sample of 137 university students (mean age was 23.6 years;

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105 were female) showed that all items had high and significant loadings (from .50 to

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.94) in a single latent factor model that fitted the data reasonably well (CFI=.96; NNFI=.95; RMSEA=.097) and was internally consistent (α=.88) (Ólafsson, 2018). The

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scale had good internal consistency in the present study (α=.93).

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Dysfunctional attitudes: The Dysfunctional Attitudes scale (DAS; Weissman & Beck, 1978) was used to measure dysfunctional attitudes, such as rigid world view,

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perfectionistic performance standards and concern with judgement of others. DAS is

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available in two parallel 40-item forms, that were used to measure mood-linked changes in attitudes during a mood-induction task (see below). Each statement on the DAS is rated on a scale form 1 (totally disagree) to 7 (totally agree) with higher DAS scores indicating more dysfunctional attitudes. Good internal consistence and test-retest reliability have been reported for the DAS (Hamilton & Abramson, 1983; Weissman, 1979). The Icelandic translation shows good internal consistency estimates and strong correlation between the two parallel forms (Helgadóttir & Jóhannsdóttir, 2016). Both DAS-A (α=.95) and DAS-B (α=.92) had good internal consistency in the present study.

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Experimental tasks Cognitive reactivity: Cognitive reactivity was assessed in a standard mood induction procedure used in previous studies (e.g. Segal et al., 2006). To induce mild levels of dysphoria, participants listened to approximately eight-minute long excerpt from Prokofievs “Russia Under the Mongolian Yoke” that was remastered at half speed. Participants were also instructed to think back to a time in their lives when they felt sad.

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This combination of music and autobiographical recall has been found to be effective in

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inducing transient dysphoric mood (Martin, 1990). Before and after the mood induction,

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the two parallel forms of the DAS were administered in a counter balanced order.

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Increases in dysfunctional attitudes following mood induction are taken to reflect reactive mood-dependent negative attitudes (i.e. cognitive reactivity). Mood ratings were obtained

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with a visual analog scale (VAS) that was administered before and after the mood

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induction. The VAS was a 152 mm line with arrows indicating increased strength of happy and sad moods from the middle of the scale with corresponding labels located at

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the left (sad) and right (happy) of the center (e.g. Segal et al., 2006).

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Habit vs. goal-directed response tendencies: The Fabulous Fruit Game (FFG) is a computerized task (programmed in Visual Basic 6.0) designed to measure the extent to which instrumental performance is under the control of habitual versus goal-directed action strategies. We used a modified version (see Worbe et al., 2015) of the original FFG (see e.g., de Wit et al., 2007; Gillan et al., 2011). Instrumental Training. In brief, participants learned two instrumental responses (left or right button-presses) to gain rewarding outcomes (points earned by collecting fruits inside boxes) (Figure 1A). A series of six boxes were presented at the center of the

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screen, one at a time. Each box had a unique fruit image on the front (e.g., bananas) and a different fruit image inside (e.g. pineapple). When a box appeared on the screen, participants were asked to open it by pressing either the left or the right button on a keyboard. Correct responses revealed the fruit outcome inside (points awarded) but incorrect responses showed an empty box (no points awarded). Participants were instructed to learn (by trial and feedback) which was the correct response (left vs. right)

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for each outcome (fruit inside). The fruits at the outside served as discriminative stimuli

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(three fruits signaled that the right response was correct, and the other three that the left

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response was correct). The fruits inside the boxes were worth points (cumulative scores

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shown on the screen), with more points earned for faster correct responses (from 1 to 5 points). The training included eight blocks during which each of the six boxes was

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presented twice in random order.

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Slips-of-action Test. This test was designed to assess the relative contribution of habitual versus goal-directed control over instrumental responses learned during the

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instrumental training phase. Before each block, all six rewards from the instrumental

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training phase (i.e. the six fruit outcomes inside the boxes) were presented for ten seconds on the screen (Figure 1B). Two of the six fruits had a red cross on them, indicating that they were now devalued. Following the ten-second presentation, each of the boxes was presented one at a time, showing only the discriminative stimulus (the fruit image outside the box). Participants were instructed to use their contingency knowledge from the instrumental training in order to press the correct button to earn the reward inside. However, they were instructed not to respond to the boxes that contained the devalued fruit inside, because these now led to subtraction of points. No feedback was provided

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during this stage (i.e., the boxes remain closed even if the subject pressed the left or right key). Each box was shown two times per block, and each outcome was devalued three times across blocks. Failure to withhold responses to stimuli linked with devalued outcomes (i.e., ‘slips of actions’) is thought to reflect stimulus-response habits, whereas selective inhibition of responding on the basis of current outcome value is thought to reflect goal-directed action control.

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Baseline Test. This test was designed to control for general test demands on

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working memory and response inhibition of the slips-of-action test and has an identical

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structure. The only difference is that the discriminative stimuli (fruits outside a box) are devalued rather than the outcomes (fruits inside a box) (Figure 1C). Therefore, this test

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does not require evaluation of an anticipated outcome of one’s actions. The order of the

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baseline and slips-of-action test was counterbalanced between participapants.

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Insert Figure 1 (A, B & C) about here Procedure

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The study was reported to the Data Protection Authority of Iceland and approved

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by the National Bioethics Committee. All participants completed two study sessions, 4-7 days apart. Upon arrival in the first visit, participants signed informed consent before answering self-report questionnaires (demographics/treatment history, BDI-II, BAI) and participating in the MINI diagnostic interview. The second visit was a testing session. Participants first filled in self-report questionnaires (PANAS, RRS, SRHI, LEIDS-R) before participating in the FFG and cognitive reactivity paradigm. Participants received small financial compensation for their participation in the study. Statistical analyses

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Statistical analyses were carried out in SPSS 24.0. For discriminative performance on the FFG, a Devaluation Sensitivity Index (DSI; see also Snorrason, Lee, de Wit, & Woods 2016) was computed to use in correlational analyses. The DSI was constructed for the slips-of-action test (DSI-Slip) and for the base-line test (DSI-Base). The DSI-Slip was computed by subtracting the percentage of responses made to cues linked to devalued outcome (i.e. when a response should be withheld) from the percentage of responses

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made to cues linked to valued outcomes (i.e. when a response should be elicited) on the

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slips-of-action test. Thus, lower DSI-Slip values reflected less sensitivity to devaluation

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(i.e. habitual responding). Similarly, the DSI-Base was computed by subtracting the

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percentage of responses made to devalued cues from the percentage of responses made to valued cues on the baseline test. Raw number of past depression episodes in the FD

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group was used in correlational analyses.

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Results

Demographic and clinical characteristics

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Baseline characteristics of participants in the ND and FD groups are reported in

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Table 1. The two groups did not differ in age, t(40)=-.760, p=.452, and the distribution in marital status was comparable in the groups (p=0.756). Severity of depression and anxiety symptoms was greater in the FD than the ND group. T-tests revealed significant group differences on the BDI-II (t(40)=-2.61, p=.013) and BAI (t(40)=-2.49, p=.017) but not the PANAS positive (t(40)=-1.14, p=.260) or negative (t(40)=-1.00, p=.325: Thus, the FD and ND groups differed in symptom severity but not in state affectivity during the study session. BDI-II and BAI scores were therefore entered as covariates in all subsequent group comparisons to control for symptom severity.

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Insert Table 1 about here Habitual characteristics of cognitive vulnerability Depressive rumination was expected to have greater habitual characteristics in the FD group (see Table 2). Results from an ANCOVA with group as the independent variable, BDI-II and BAI scores as covariates and scores on the SRHI as the dependent variable, confirmed this, F(3,38)=6.00, p=.019, partial η2=.14. The groups also differed in

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brooding, F(3,38)=9.46, p=.004, partial η2=0.20, and reflective pondering,

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F(3,38)=12.03, p=.001, partial η2=.24. The group difference in habitual characteristics

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(SRHI) remained significant when rumination (RRS total score) was added as a covariate

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(data not shown).

Insert Table 2 about here

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Participants in the FD group had significantly greater self-reported cognitive

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reactivity on the LEIDS-R, F(3, 38)=7.75, p=.008, partial η2=.17. Cognitive reactivity was also measured with a mood induction procedure. Manipulation of mood was

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successful according to a mixed ANCOVA that revealed a significant main effect of time

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(pre vs. post induction), F(1, 38)=7.35, p=.01, partial η2=.16, but not group (FD vs. ND) nor interaction of time and group (p>.10 in both cases) on mood. However, a mixed ANCOVA showed a significant interaction effect between group and time on dysfunctional attitudes on the DAS in this task, F(1, 38)=4.29, p=.045, partial η2=.10, that was, contrary to expectations, evident in a slight and marginally significant (Pairedsamples t-test; t=1.85; p=.08) reduction in dysfunctional attitudes following induction of dysphoric mood in the FD group (see Table 2).

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The relationship of rumination and cognitive reactivity with habitual characteristics of rumination was investigated using three linear regression analyses with brooding, reflective pondering and self-reported cognitive reactivity (LEIDS-R) as outcomes. Self-reported habitual characteristics (mean centered) and group (coded with ND as the reference group) were the predictors along with the interaction between the two. The results are summarized in Table 3. In addition to the significant contribution of

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group in all three analyzes, self-reported characteristics significantly predicted brooding

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and cognitive reactivity but not reflective pondering (model 1). The interaction between

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the two was not significant in any of the three analyzes (model 2) indicating that group

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did not moderate the relationship between habitual characteristics and rumination or cognitive reactivity.

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Insert Table 3 about here

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Habit and goal-directed behavior control

We first compared performance of the two groups on the eight blocks of the

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instrumental learning phase of the FFG. A mixed 2 x 8 ANCOVA with group (FD, ND)

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and blocks in the learning phase as between and within-subjects factors was computed with severity of anxiety and depression symptoms as covariates. The Greenhouse-Geisser method was used to correct for lack of sphericity. The main effect of block was significant, F(4.102, 155.87)=18.42, p<.001, partial η2=.33, but the main effect of group, F(1, 38)=.373, p=.545, and the interaction between block and group, F(4.102, 155.87)=.252, p=.912, was not. This means that discriminative performances improved through the learning phase and at similar rate in the two groups.

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Next, it was tested if more-reliance on habit-related relative to goal-directed learning was associated with depression history (see descriptives in Table 2). A 2 x 2 mixed ANCOVA with type of group (FD vs. ND) as the between-subjects factor, outcome value (valued vs. devalued) as the within-subjects factor and BDI-II and BAI scores as covariates, showed a significant main effect of outcome, F(1,38)=64.93, p<.001, partial η2=0.63, but no group nor the interaction of group and outcome on the

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slips of action test (p>.10 in both cases). Same pattern was observed on the baseline test

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for outcome, F(1,38)=270.20, p<.001, partial η2=.88, group and the group x outcome

-p

interaction (p>.10 in both cases). This means that on both tests, correct responses were

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significantly more frequent when outcome was valued compared to devalued and did not depend on depression history. Thus, there was no support for greater habit-directed

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responding in the FD group on the FFG task.

na

Number of past depression episodes in the FD group correlated significantly with the DSI-Slip, r=-.63, p=.003, but not with habitual characteristics of rumination on the

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SRHI, r=.03, p=.903. A comparable sensitivity index for responses on the base-line test

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(DSI-Base), did not correlate significantly with number of past episodes in the FD group, r=-.21, p=.371, but had strong and significant correlation with DSI-Slip, r=.57, p=.008. Partial correlation between DSI-Slip and number of past depression episodes was however unchanged when controlling for DSI-Base, r=-.63, p=.004. This means that, as number of past depression episodes increased, sensitivity to devaluation of outcome decreased and this relationship was only observed on the slips-of action test (i.e. increased habit-directed responding). Discussion

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Formerly depressed participants endorsed greater habitual characteristics of rumination than never depressed participants, and this difference was independent of anxiety, depression and trait rumination. Greater habitual characteristics were also associated with brooding rumination, but not reflective pondering, in both groups. These findings are generally in line with the habit-goal framework of depressive rumination (Watkins & Nolen-Hoeksema, 2014) and underscores the importance of investigating

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automaticity of ruminative thoughts as a separate aspect of depressive rumination.

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The habit-goal framework predicts that depressive brooding, rather than reflective

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pondering, should be associated with habitual characteristics of ruminative thoughts. The

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present finding that brooding is associated with increased automaticity, lack of conscious control, intent and awareness of ruminative thoughts, suggests the possibility that

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habitual nature of abstract and analytical processing style could contribute to greater

na

maladaptive consequences in depression. Although the hypothesized interaction between habitual characteristics and group was not significant when predicting brooding, the

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pattern in the data was in line with expectations. Studies show that brooding, rather than

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reflective pondering, predicts symptom worsening prospectively (e.g. Treynor et al., 2003) and is associated with greater cognitive inflexibility, hopelessness and suicidal ideation (e.g. Miranda, Valderrama, Tsypes, Gadol & Gallagher, 2013). It will have to be examined in future studies if greater vulnerability to depression may be in the form of passive, negative and abstract thoughts (i.e. brooding) being habitually triggered. Because habits are initiated without intent or awareness, habitual rumination should go unnoticed, delaying signals that active control strategies should be applied (e.g. Koster, Lissnyder, Derekshan & De Raedt, 2011). Once rumination is initiated, detrimental effects of

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increased negative affect on executive functioning (Curci, Lanciano, Soleti & Rimé, 2013; Watkins & Brown, 2002), could make flexible adaptation of behavior difficult. We tested if depression history would be associated with greater tendency towards general habit-related, at the expense of more goal-directed, behavior control. Although differences were not observed at the group level, slips-of-action (i.e. impaired goal-directed control/reliance on habits) correlated strongly with number of past

of

depression episodes in the FD group. Sensitivity to devaluation of outcome decreased

ro

with greater number of episodes, suggesting a link between habitual responding and

-p

depression recurrence. Greater reliance on habitual, rather than goal-directed, behavior

re

control in general, may predispose people to depression recurrence because dysfunctional coping behaviors can become easily manifested and more rigidly applied. It has been

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suggested that sensitization in major depression reflects stronger fixation of attention on

na

negative material, coupled with increased ruminative elaboration of that material (Farb et al., 2015). Inflexible and dysfunctional coping reactions may be more reactive and

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executed with less awareness in those with greater general tendency towards habitual

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responding and with impaired ability to modulate behavior as a function of changes in reinforcement contingencies. The study of habits may therefore be highly relevant to the literature on reduced flexibility in depression (Kashdan & Rottenberg, 2010; Stange et al., 2017). Habitual rumination and situational factors that facilitate habit formation (i.e. chronic stress, reduced positive reinforcement, socialization factors) may make selection of coping behaviors less flexible (Watkins & Nolen-Hoeksema, 2014) and increase reflexive (i.e. habitual), at the expense of reflective (i.e. goal-directed), decision making (Heller, Ezie, Otoo & Timpano, 2018), that is associated with dysfunctional reward

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processing and lack of motivation in anhedonia (e.g. Pizzagalli, 2014). It is possible that habitual responding becomes more of a default mode for those who make pessimistic attributions and have learned that none of one’s actions affect outcomes. It could be argued that the association between greater habit-related (and therefore less goal-directed) control on the FFG and depression history, reflects the detrimental effects of repeated episodes on cognitive control (e.g. Beevers, 2005; Snyder, 2013) or

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lack of efficient response inhibition (e.g. Joormann & Tanovic, 2015). Number of

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previous episodes of depression was not significantly correlated with performance on the

-p

baseline test where stimuli instead of outcome was devalued. The relationship between

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the slips-of-action test and number of past depression episodes was also unchanged when controlling for the base-line-test. This means that general demands that the structure of

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the slips-of-action test makes on working memory and inhibition of prepotent responses,

na

does not account for the relationship between action slips during outcome devaluation and previous depression episodes. Studies on cognitive control in depression show that

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depression is associated with less efficient updating of content in working memory and

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inhibition of dominant responses using emotional material (Joormann & Tanovic, 2015). Such inhibition related deficiencies may fuel depressive rumination via impaired disengagement of attention to negative material (e.g. Koster et al., 2011). It is possible that weaknesses in cognitive control come into play when negative mood states tax working memory resources. The FFG uses neutral stimuli. Application of an outcome devaluation tasks with emotional or disorder-specific stimuli, would be interesting to explore in future studies.

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Habitual characteristics of ruminative thoughts also predicted self-reported cognitive reactivity (LEIDS-R scores), suggesting that the habit-goal framework may extend to mood-reactive negative attitudes as well. Cognitive reactivity is often construed as a depression scar, building up through repeated episodes as a result of the contingency between depressed mood and negative thinking patterns during depression (Lau et al., 2004; Teasdale, 1999). During episodes of depression, specific context-response

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associations may form, resulting in negative cognitive content being habitually triggered

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when mood worsens. However, no cognitive reactivity was observed in the FD group on

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the mood induction task, in fact, a slight decrease in dysfunctional attitudes was observed

re

in this group. Null findings have been reported, although inconsistently, in past research on cognitive reactivity (e.g. Brosse, Craighead & Craighead, 1999; Van der Does, 2005).

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Reasons for this are not clear but previously proposed explanations include sample

na

characteristics (Fresco, Heimberg, Abramowitz & Bertram, 2006) and unreliability of measures of cognitive changes with the DAS questionnaires (Van der Does, 2005). Given

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that cognitive-behavioral therapy (CBT) is associated with reduced cognitive reactivity

Jo

(e.g. Segal et al., 1999), it is possible that the observed reduction in dysfunctional attitudes following mood-induction could be related to participant’s treatment history. Our inspection of DAS change scores by treatment history does not support this, although the relatively small group size precludes statistical analyses of the data. It should be noted that our questions on treatment history were not designed to capture the nature of the treatment received in more detail (groups vs. individual format; number of sessions completed etc.). The absence of cognitive reactivity on the mood-induction task means that our finding that self-reported cognitive reactivity (LEIDS-R) may share habitual

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characteristics with depressive rumination is only tentative at present and should be explored further in future studies. As noted earlier, group differences were not observed in habit-related control on the FFG task. It is possible that our FD group, that were university students, experienced less functional impairment resulting from their depression history because of strengths that may have proved to be beneficial when tested in a euthymic state in the study. We

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belief however that our group assignment is valid because it relied on structured

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assessment of participants depression symptoms and history. Also, our FD group

-p

presented with greater symptoms of anxiety and depression, and self-reported cognitive

re

vulnerabilities compared to the ND group. Self-reported habitual characteristics were unrelated to number of previous depression episodes in the FD group. Although habitual

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characteristics of ruminative thoughts can contribute to the tendency to ruminate, it may

na

not result in greater episode recurrence on its own. It is possible that any role rumination habit may have, depends on the presence or absence of other factors leading up to the

ur

onset of a depression episode (e.g. stressful life events). Habitual characteristics were

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also unrelated to habit-related control on the FFG. Although this may suggest that formation of rumination as a habit is independent of proneness to habitual responding in general, this finding can also be the result of specific variance associated with the assessment methods that were used (self-report vs. behavioral task). This will have to be addressed in future studies. The study of habitual characteristics of cognitive vulnerabilities to depression may have important clinical implications. Habits are behaviors that are not mediated by goals (Wood & Neal, 2007). Cognitive strategies will therefore be less successful in

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directly influencing habitual rumination, although they may indirectly do so by reducing negative mood that triggers habitual rumination. As noted by Watkins and NolenHoeksema (2014), more emphasis may be placed on behaviorally oriented strategies, for example counter conditioning that replace habitual rumination with a competing response. Strategies that strengthen cognitive control (e.g. Van den Bergh, Hoorelbeke, De Raedt & Koster, 2018) may also help to increasing peoples control over habitual

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responses when they are triggered. Mindfulness based approaches such as Mindfulness-

ro

Based-Cognitive Therapy can increase peoples cognitive distancing or decentering

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making people more aware of their habitual response patterns when they arise and may

re

increase the likelihood of more flexible responding (e.g. Bernstein et al., 2015). Finally, rumination focused therapy incorporating methods of behavioral activation, has been

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shown to be effective in reducing rumination and depression (Watkins et al., 2011). All

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these strategies may be beneficial to tackle habitual rumination in depression and underline the importance of measuring habitual characteristics of rumination to include in

ur

the case conceptualization of depression and to inform treatment selection.

Jo

We note some limitations of the study. The study uses a cross-sectional remitteddepressed design and causal relationships between constructs need to be tested using longitudinal or experimental designs. Remitted designs are efficient to study vulnerabilities in relation to repeated episodes and without the confound of acute symptoms of depression, although high risk designs may be needed to better determine the statues of vulnerabilities as depression risks or scars (Just, Abramson & Alloy, 2001). The sample consisted of female university students precluding generalization of the findings to males, the general population and formerly depressed groups differing in

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disorder severity. Also, our diagnostic interview relied on DSM-IV conceptualization of depression. The results should be interpreted with the relatively small sample size of the study in mind. Although the results should be considered preliminary, awaiting replication in larger samples, they represent one of the first attempts to address hypotheses directly derived from the novel habit-goal framework of depressive rumination. Measuring habitual characteristics via self-report is a valid method that has

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been used in previous studies (e.g. Verplanken et al., 2007), but laboratory tasks to assess

ro

context-response associations in line with the habit-goal framework should be included in

-p

future studies. The same applies to the assessment of rumination. The adapted version of

re

the SRHI used in the present study, focused on habitual characteristics of ruminative thoughts. Given the results of Verplanken et al. (2007), the Habit Index of Negative

lP

Thinking (HINT) may capture habitual characteristics of negative thoughts in general and

na

could be used in studies of the habitual nature of mood-reactive dysfunctional cognitions. The present results provide initial support for the habit-goal framework of

ur

rumination and underline the importance of considering automaticity as a separate aspect

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of cognitive vulnerability that is present after episode remission. The predictive role of automaticity in episodes of depression needs to be tested in future studies. The habit-goal framework is a developmental account of how habitual rumination forms and should also be investigated in non-clinical samples to elucidate specific factors associated with the transition of state episodes of rumination to a habitual ruminative response. Finally, the application of experience sampling methods should be explored in future studies, since they may be an ideal way to capture the dynamic relationship that exists between mood and rumination in the flow of daily life.

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37

Table 1 Descriptive statistics for participant groups in the study Formerly depressed

Never depressed

(n=20)

(n=22)

Age, M (SD)

28.0 (9.8)

30.3 (9.4)

Marital status (single), n (%)

11 (52.4)

11 (44.0)

Age of onset of major depression, M

17.7 (5.9)

--

4.2 (2.6)

--

Number of previous major depression

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(SD)

…2 episodes n (%)

3 (15.0)

…3 episodes n (%)

5 (25.0)

…4 to 9 episodes n (%)

9 (45.0)

MINI diagnosis of anxiety disorder, n

6 (30.0)

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(%) Current treatment status n (%)

-----

7 (35.0)

--

1 (5.0)

--

2 (10.0)

--

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Past treatment history

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…other, n (%)

--

7 (35.0)

…antidepressant use, n (%) ...CBT, n (%)

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3 (15.0)

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…1 episode n (%)

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episodes, M (SD)

17 (85.0) 7 (35.0)

--

...CBT, n (%)

8 (40.0)

--

12 (60.0)

--

…psychiatric admission

2 (10.0)

--

BDI-II

7.1 (4.5)

3.8 (3.7)

BAI

8.5 (6.2)

4.6 (4.0)

PANAS positive

33.6 (5.7)

31.4 (6.3)

PANAS negative

13.9 (4.1)

12.5 (4.6)

…other, n (%)

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…antidepressant use, n (%)

Note. MINI=Mini-International Neuropsychiatric Interview; CBT=Cognitive Behavioural Therapy; BDIII=Becks Depression Inventory-II; BAI=Beck Anxiety Inventory; PANAS positive=Positive and Negative Affect Scale -positive affect subscale; PANAS negative=Positive and Negative Affect Scale -negative affect subscale.

HABITUAL CHARACTERISTICS OFJournal RUMINATION Pre-proof

38

Table 2 Mean scores (SD) on measures of habitual characteristics of rumination, habit vs. goaldirected behaviour control and cognitive vulnerabilities (rumination and cognitive reactivity) Never depressed

(n=20)

(n=22)

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Formerly depressed

49.4 (14.3)

34.8 (14.8)*

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SRHI

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Habitual characteristics of rumination

Habit vs. goal-directed behaviour control (FFG)

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Slips-of-action test 89.0 (12.5)

82.3 (25.5)

…devalued outcome

20.7 (24.4)

23.4 (22.1)

95.9 (5.7)

90.1 (20.6)

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…valued outcome

Baseline test

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…valued outcome

11.1 (16.1)

10.2 (8.5)

11.10 (3.97)

7.05 (2.08)*

11.50 (3.30)

7.72 (2.07)*

48.30 (16.78)

28.81 (14.52)*

…pre induction

42.75 (17.32)

43.41 (21.14)

…post induction

11.80 (33.24)

15.41 (28.71)

…pre induction

122.05 (26.39)

98.27 (26.19)

…post induction

117.45 (27.64)

100.36 (29.89)

Depressive rumination

RRS reflection

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RRS brooding

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…devalued outcome

Cognitive reactivity LEIDS-R

Mood induction task Mood levels (VAS)

Dysfunctional attitudes (DAS)

HABITUAL CHARACTERISTICS OFJournal RUMINATION Pre-proof

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Note. SRHI=Self-Report Habit Index; FFG=Fabulous Fruit Game. RRS brooding=Rumination Responses Scale-brooding subscale; RRS reflection=Rumination Responses Scale-reflective pondering subscale; LEIDS-R=Leiden Index of Depression Sensitivity-Revised; VAS=Visual Analog Scale; DAS=Dysfunctional Attitude Scale. *Group means differ significantly according to statistical tests (see main text).

Table 3

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Results from linear regression analyzes with self-reported habitual characteristics

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(SRHI) and group predicting rumination (RRS) and cognitive reactivity (LEIDS-R)

2

SE B

Beta

(.407)

SRHI

.082

.032

.357*

Group

2.861

1.016

.390*

2

SRHI

.037

Group

2.765

SRHI x Group

.099

Beta

Cognitive reactivity (LEIDS-R) B

SE B

Beta

(.366)

.046

.029

.223

.352

.162

.311*

3.108

.930

.476*

14.352

5.193

.396*

(.377)

(.367)

.042

.160

.033

.040

.163

.403

.223

.356

.999

.377*

3.081

.941

.472*

14.461

5.262

.399*

.063

.279

.027

.059

.085

-.112

.330

-.064

Jo

(.443)

ur

2

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R

Model 2 (R )

SE B

(.374)

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Model 1 (R )

B

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B

Reflective pondering (RRS)

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Brooding (RRS)

Note. SRHI=Self-Report Habit Index; RRS brooding=Rumination Responses Scale-brooding subscale; RRS reflection=Rumination Responses Scale-reflective pondering subscale; LEIDS-R=Leiden Index of Depression Sensitivity-Revised. Group was coded 0=never depressed, 1=formerly depressed. SRHI was mean centrered in the analyses. *

p<.05

HABITUAL CHARACTERISTICS OFJournal RUMINATION Pre-proof

Highlights Formerly depressed participants endorsed greater habitual characteristics of rumination. Habitual characteristics were associated with brooding but not pondering.

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ur

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Habitual behavior control was strongly correlated with number of depression episodes.

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Figure 1