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The Relationship Between Goal- Oriented Motivation and Mood Variability: Implications for Bipolar Disorder PhD (Clinical) Research Project Student Investigator:

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Presentation on theme: "The Relationship Between Goal- Oriented Motivation and Mood Variability: Implications for Bipolar Disorder PhD (Clinical) Research Project Student Investigator:"— Presentation transcript:

1 The Relationship Between Goal- Oriented Motivation and Mood Variability: Implications for Bipolar Disorder PhD (Clinical) Research Project Student Investigator: James Collett Primary Supervisor: Greg Murray Secondary Supervisor: Conrad Perry


3  Classified as an affective disorder.  Can consist of: - Manic episodes - Depressive episodes - Mixed episodes - Occurrence of hypomania - Returns to euthymic mood  Unipolar mania considered to be spurious.

4  Piquer (1759), Falret (1854), Baillarger (1854), Kraepelin (1899): Dual-form insanity and manic-depressive illness.  Kraepelin (1899): Cyclicity and recurrence originally prioritised.  Leonhard (1957): Term “bipolar” applied, bipolar depression differentiated from unipolar depression.  Idea of reactive versus recurrent depression.  American Psychiatric Association (2000): DSM approach emphasises component episodes.

5  The DSM-5 contains several categories of recurrent affective disorder: - Bipolar I Disorder - Bipolar II Disorder - Major Depressive Disorder - Cyclothymia - Persistent Depressive Disorder (Dysthymia) - Disruptive Mood Dysregulation Disorder

6  Several factors have been suggested as being involved in the causation and exacerbation of bipolar disorder: - Evolutionary theories - Manic defence versus primacy-of- mania hypotheses - Genetic linkage - Monoamine hypothesis - Circadian rhythm hypothesis - Social rhythm hypothesis - Behavioural activation system (BAS) hypersensitivity model

7  Like most mental disorders, bipolar disorder can be conceptualised under a diathesis- stress (vulnerability-trigger) model.  Can think of disorders as differing in their balance of diathesis versus stress.  Bipolar disorder appears to be weighted more towards diathesis, but episodic nature often keyed to exogenous environmental stressors.  Kindling effect observed where occurrence of mood episodes may become more endogenous over time.

8  As with many disorders, bipolar disorder can be thought of as occurring on a quantitative spectrum with normal mood.  Vulnerability trait of emotion dysregulation.  Difference between being sad versus being depressed, and between being energised and being manic.  Extremes of vulnerability trait more likely to be defined as being of clinical severity.

9  It is useful to separate mania and depression as distinct vulnerability traits: - Concordant with factor analytic evidence - Allows ranking of affective diagnoses based on severity - Facilitates explanation of reactive and recurrent unipolar depressions - Enhances sensibility of mixed episodes - Provides more complex diagnostic groups (Md, MD, Dm, md)

10 versus Mania Depression Mania Depression &

11  If bipolar disorder involves extreme mood states, this raises question of how traits (dispositional) and states (transient) interact.  Can view traits as underlying predispositions towards certain states.  Can also view traits as signifying that baseline personality is likely to be characterised by state attributes.  Research attempting complex state-trait models of affective disorder is still in its infancy.

12  There are several reasons why examining bipolar disorder vulnerability as a personality trait can be useful: - Supports evolutionary retention of disorder traits as adaptive - Matches multifactorial nature of genetic transmission - Permits much larger sample sizes - Allows for research that avoids prodomal and residual state effects and pharmacological “scarring” effects - Avoids over-stigmatising bipolar disorder and conceptualising it as wholly alien to “normal” human experience

13  While the trait approach is useful, it is important to keep in mind the following caveats: - The treatment model for bipolar disorder is dominantly medical, possibly implying a biologically distinct disorder - Interaction between both quantitative and qualitative factors - Research does not always replicate findings between clinical and non-clinical samples - Trait content is usually developed from a top-down clinic perspective, and hence may be out of touch with non-clinical trait expressions (resulting in pronounced positive skew).


15  Attempts to establish and explain the relationship between trait bipolar disorder and reward sensitivity using Reinforcement Sensitivity Theory (RST).  Examines correlations between bipolar disorder traits and RST traits.  Assesses how traits influence behavioural task performance.  Explores how mood state manipulation interacts with traits to alter behavioural task performance.

16  By definition, mania is a state of almost pure BAS.  Similar physiological systems (largely dopaminergic) have been implicated.  BAS sensitivity has been observed in euthymic bipolar disorder.  Elevated BAS scores predictive of bipolar disorder onset and of greater frequency of mania once diagnosed.  Individuals with bipolar disorder experience greater mobilization in response to goal progress (whereas non-psychiatric controls more likely to decrease effort if goal progress is going well).

17  Many scales available assessing depression (e.g., BDI, DASS, HAMDS).  Scales also available to measure mania (e.g., YMRS).  Few scales conceptualise both.  General Behavior Inventory (GBI) provides valid measure of depression and (hypo)mania.  Also allows separation of biphasic symptoms.

18  BIS/BAS Scales (BBS) measure BAS and behavioural inhibition system (BIS).  Validated on Australian sample.  Divide BAS into statistically-identified subscales (Drive, Fun-Seeking, Reward Responsiveness).  Alternate measures (SPSRQ, GRAPES, AGQ) either more simplistic in structure, measure subtly different content, or are simply redundant.

19  Do mood variability traits correlate with RST traits?  How is risky decision-making influenced by mood variability and RST traits?  Does mood variability impair cognitive flexibility, and if so, does this occur generally or only during tasks that engage reward sensitivity processes?  Are individuals more or less likely to engage in riskier decision-making dependent on their mood state?  How is the effect of mood state modulated by underlying personality traits?

20  Study 1 ( N = 760) : Self-report trait investigation examining the structure of mood variability and RST using exploratory and confirmatory factor analysis.  Study 2 ( N = 118) : Behavioural investigation examining performance on a range of cognitive-affective tasks assessing risky decision-making and set-shifting.  Study 3 (Positive n = 53, Negative n = 68) : Mood induction experiment examining how state manipulations interact with underlying traits to influence performance on a risky decision- making task.

21 GBIBIS/BAS Scales Hypomania and Biphasic Symptoms Depression BAS-RR BAS-FS BIS BAS-D

22 Note. These results were not replicated in the smaller Study 2 sample.


24  Systematic exploration at level of (i) bivariate correlations, (ii) hierarchical regression controlling for affect, (iii) structural regression models testing for mediation.  No consistent pattern of correlation present across tasks at any level of analysis, despite task outcomes and self-report traits purporting to measure similar constructs.  This finding conflicts with previous research and the theory that BAS dysregulation is of key importance to phenomena characteristic of bipolar disorder.

25 Positive Mood Induction Group Negative Mood Induction Group Neutral False Feedback BART (Baseline Mood) Positive False Feedback BART (Positive Mood) Neutral False Feedback BART (Baseline Mood) Negative False Feedback BART (Negative Mood)

26  Mood induction appeared to function as expected.  Although significant differences were found between and within BART trials, these appeared to be artefacts of fatigue and baseline variance.  Underlying traits did not predict behaviour change on the BART.  Underlying traits did not predict mood induction susceptibility in a consistent manner.

27  Despite the range of evidence linking BAS dysregulation to bipolar disorder, this was not evident in the present study.  Rigorously tested observationally and experimentally across range of studies.  Potential explanations for lack of significance: - Possible that BAS is important to individual clinical phenomenology but this is obscured at more general trait level. - Possible that BAS dysregulation is only a significant influence upon clinically severe cases (implying a qualitative difference). - Possible that what has been labelled as euthymic BAS dysregulation is in fact prodromal or residual symptom of manic or hypomanic state.

28  I hope that you enjoyed the presentation.  Does anyone have any questions?

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