Self-discrepancy monitoring    and its impact on depressed      mood: an experimental             investigationChiara Manf...
Cognitive theories of depression• There is a greater risk for depression for  people who exhibit a dispositional negative ...
Three possible forms of these         dysfunctional attitudes• Selective attentional and interpretation biases• Chronic an...
Three possible forms of these            dysfunctional attitudes• Selective attentional and interpretation biases:    An a...
Three possible forms of these         dysfunctional attitudes• Selective attentional and interpretation biases• Chronic an...
Three possible forms of these         dysfunctional attitudes• Selective attentional and interpretation biases• Chronic an...
Three possible forms of these         dysfunctional attitudes• Selective attentional and interpretation biases• Chronic an...
Positive stimuli in depressionDifference between depressed and non-depressedindividuals in emotional response to positives...
Self-Discrepancy• The basis of Self-Regulation theory (Caver et al., 1999)   discrepancies between ideal and actual selve...
What can SDM lead to?• The hindering of positive emotional experiences• The re-orientation of attention towards the negati...
Distinguishing SDM from other cognitive                processes                                Self Discrepancy Monitorin...
Hypotheses• Inducing SDM when facing a positive situation  would enhance negative mood• The effect would be more significa...
Methods• Participants:   – Italian clinical sample: 28 outpatients (19 females) with a     diagnosis of moderate depressio...
Attentional manipulationTasks were adapted from Nolen-Hoeksema and Morrow’s (1993)distraction and rumination task1.   Part...
Procedure• Written informed consent, SCID-II, BDI, RRS and LOT-RAFTER ONE WEEK:• Current brooding, negative mood and thoug...
Results: Italian sample               Results of ANOVA                                        Paired t-test for SDM condit...
Results: Romanian sample                 Results of ANOVA             Paired t-test was for the SDM condition: t(28) = -  ...
Discussion• SDM leads to a significant decrease in mood and  to a significant increase in negative thoughts  independently...
Possible SDM consequences• Direct effect: a frequent engagement in discrepancy monitoring may  lead to a reduction of posi...
Limitations• Self-report data subject to errors in measurement• NMT in assessing the dependent variable• Lack of an indepe...
Clinical implications• Assessing SDM may be useful in identifying and  socializing a potential maladaptive cognitive  stra...
Future research• Deepen investigate both the SDM frequency of  use in depressed and non-depressed individuals,  and the mo...
Thank you for your attention                        Contact details                     Dr.ssa Chiara Manfredi  Cognitive ...
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Self-discrepancy monitoring and its impact on depressed mood: an experimental investigation

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Presented at EBACT 2012 Geneève, the research of italian scholar Chiara Manfredi.

Cognitive theories of depression
There is a greater risk for depression for people who exhibit a dispositional negative style and dysfunctional attitudes (Abramson et al., 1989; Beck 1987)

These dysfunctional attitudes can act as latent vulnerability factors for emotional and affective disorders (Mathews & MacLeod, 1994)

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Self-discrepancy monitoring and its impact on depressed mood: an experimental investigation

  1. 1. Self-discrepancy monitoring and its impact on depressed mood: an experimental investigationChiara Manfredi1,4 ,Gabriele Caselli1,2, Alina Decsei-Radu3, Francesca Fiore1, Sara Querci1, Sara Sgambati1, Daniela Rebecchi1, Giovanni M. Ruggiero1 & Sandra Sassaroli11 Studi Cognitivi, Cognitive Psychotherapy School, Italy2 London South Bank University, UK3 University of Oradea, Romania4 University of Pavia, Italy
  2. 2. Cognitive theories of depression• There is a greater risk for depression for people who exhibit a dispositional negative style and dysfunctional attitudes (Abramson et al., 1989; Beck 1987)• These dysfunctional attitudes can act as latent vulnerability factors for emotional and affective disorders (Mathews & MacLeod, 1994)
  3. 3. Three possible forms of these dysfunctional attitudes• Selective attentional and interpretation biases• Chronic and embedded pessimism• Ruminative brooding
  4. 4. Three possible forms of these dysfunctional attitudes• Selective attentional and interpretation biases: An active and conscious The tendency to distort thedirection of attention to mood- interpretation of specific irrelevant congruent information events in terms of personal (Mathews et al., 1996) failure, and to generalize events that hold any semblance of negative information about the self STRATEGIC NATURE (Beck, 1964)• Chronic and embedded pessimism• Ruminative brooding
  5. 5. Three possible forms of these dysfunctional attitudes• Selective attentional and interpretation biases• Chronic and embedded pessimism: a generalized negative outcome expectancy (Armor & Taylor, 1998); a proximal predictor of adjustment (Scheier & Carver, 1985)• Ruminative brooding
  6. 6. Three possible forms of these dysfunctional attitudes• Selective attentional and interpretation biases• Chronic and embedded pessimism• Ruminative brooding: a mode of thinking that involves repetitive and passive focus on one’s depressive symptoms as well as their causes and consequences; a cognitive risk factor for depressive mood (Nolen-Hoeksema, 1991).
  7. 7. Three possible forms of these dysfunctional attitudes• Selective attentional and interpretation biases• Chronic and embedded pessimism• Ruminative broodingThese dysfunctional attitudes have beenconceptualized as a reaction to negative self-related information.
  8. 8. Positive stimuli in depressionDifference between depressed and non-depressedindividuals in emotional response to positivestimuli:• Smaller electromyographic response (Schwartz etal., 1976)• Rating hedonic images as less pleasant and lessarousing (Dunn et al., 2004; Sloan et al., 1997,2001)Diminished subjective emotional response indepression refers not only to negative stimuli
  9. 9. Self-Discrepancy• The basis of Self-Regulation theory (Caver et al., 1999)  discrepancies between ideal and actual selves as predictors for depression• Different attention directed to detecting signals of discrepancies in different people• Self Discrepancy Monitoring: a strategic and voluntary allocation of attentional resources towards the monitoring of possible discrepancies between ideal and actual selves, even in positive experiences (Higgins, 1987) It may represent a relevant process in discriminating between usual and transitional self-discrepancy experiences and the sustained negative evaluation of the self, others and future typical of depressed patients
  10. 10. What can SDM lead to?• The hindering of positive emotional experiences• The re-orientation of attention towards the negative and even less important aspects of a situation• The influences upon conscious interpretations (discounting positive ones)• The enhancement of the frequency of negative triggers by focusing attention on negative content and, in turn, increasing the number of negative thoughts
  11. 11. Distinguishing SDM from other cognitive processes Self Discrepancy Monitoring Negative - Voluntary and non intrusive nature (Wells, 2008) intrusive - Not directly associated with instrumental behavior thoughts and employed to control or eliminate the outcomes that can memories result from it (Wegner, Eich & Bjork, 1994)Cognitive biases - Automatic interpretations - Repetitiveness Brooding - Activating stimuli - “what” vs. “why” - Stability over time (Carver, Scheier & Segerstrom, 2010) - Global vision and negative expectancies vs. Intentional Pessimism focus and search for elements of distance between current and ideal selves
  12. 12. Hypotheses• Inducing SDM when facing a positive situation would enhance negative mood• The effect would be more significant between depressed individuals than healthy controls• A change in ruminative brooding would in a certain degree mediate the relationship between SDM and negative mood in both the samples
  13. 13. Methods• Participants: – Italian clinical sample: 28 outpatients (19 females) with a diagnosis of moderate depression (mean = 38.8 years; SD = 12.9; range = 18-64) – Italian non-clinical sample: 28 non-depressed subjects (19 females) recruited from general population (mean= 39.3 years; SD = 13.9; range = 21-67) – Romanian clinical sample: 30 inpatients (15 females) with a diagnosis of severe depression (mean = 39.6 years; SD = 10.9; range = 23-57) – Romanian non-clinical sample: 30 non-depressed subjects (14 females) recruited from general population (mean = 34.0 years; SD = 8.7; range = 21-55)• Measures: Depression (BDI), Rumination (RRS), Pessimism (LOT-R), Negative mood and thoughts measure (NMT), Current brooding (RRS modified)
  14. 14. Attentional manipulationTasks were adapted from Nolen-Hoeksema and Morrow’s (1993)distraction and rumination task1. Participants were asked to retrieve images of a positive life event for 3 minutes while keeping their eyes closed2. Participants were asked to focus on one of two lists of audio recorded items that were presented with an interval of 20 seconds, for 8 minutes – In the experimental condition participants were asked to focus their attention on what they felt was preventing their lives from being completely happy or satisfied in the actual moment (e.g. “focus on what is missing to fully reach your ideal goals”, “focus on what you think you should do to feel near your ideal”) – In the control condition items suggested to focus attention on emotion, sensation and thoughts participants had in the contingent moment (e.g. “focus on what you are feeling right now”, “focus on your bodily sensations”)
  15. 15. Procedure• Written informed consent, SCID-II, BDI, RRS and LOT-RAFTER ONE WEEK:• Current brooding, negative mood and thoughts measure (Time 1)• 3 minutes of imagery retrieving and 8 minutes working through their assigned attentional task• Current brooding, negative mood and thoughts measure (Time 2)• Open-ended question investigating what the participants thought the study was testing• Debriefing
  16. 16. Results: Italian sample Results of ANOVA Paired t-test for SDM condition: t(27)=-22.2; p<.05 Group: F=248.06*** BDI Group x Condition: F=.37 Group: F=71.83*** ANCOVA between conditions with the change score of RRS-B NMT between Time 1 and Time 2 as dependent Group x Condition: F=.96 variable, and change in current brooding between Time Current Group: F=59.00*** 1 and Time 2 as covariate.brooding Group x Condition: F=.93 The effect of the conditions remained significant [F(1) = Group: F=44.17*** 4.90, p=.03] but change score for current brooding LOT-R appeared to have a significant effect [F(1) = 9.21, p = Group x Condition: F=.20 .004], too. Results of ANCOVA Group: F=27.70*** Condition: F=10.84** The increase in depressed mood following SDM induction depended on both experimental condition Time: F=.28 and levels of current brooding. Condition x Group: F=.51 NMT Time x Condition: F=6.91** Time x Group: F=.40 Time x Condition x Group: F=1.86
  17. 17. Results: Romanian sample Results of ANOVA Paired t-test was for the SDM condition: t(28) = - Group: F=245.24*** 2.70, p = .01 BDI Group x Condition: F=.80 Group: F=66.93*** ANCOVA between conditions with the change RRS-B Group x Condition: F=.06 score of NMT between Time 1 and Time 2 as Current Group: F=68.05*** dependent variable, and change in currentbrooding Group x Condition: F=.17 brooding between Time 1 and Time 2 as covariate. Group: F=152.98*** The effect of the conditions remained significant LOT-R Group x Condition: F=2.54 [F(1, 54) = 19.89, p < .001], while the impact of change score for current brooding appeared not Results of ANCOVA significant. Group: F=5.27* Condition: F=17.38*** Time: F=.734 Thus the increase in depressed mood following SDM induction was not purely dependent on the Condition x Group: F=.30 concurrent levels of brooding. NMT Time x Condition: F=27.34*** Time x Group: F=2.42 Time x Condition x Group: F=2.34
  18. 18. Discussion• SDM leads to a significant decrease in mood and to a significant increase in negative thoughts independently on the severity and presence of depressive symptoms and not purely dependently on the concurrent change in levels of brooding.• These results may reflect the importance of the time spent in monitoring self-discrepancy, instead of the importance of the degree of discrepancy perceived by the person.
  19. 19. Possible SDM consequences• Direct effect: a frequent engagement in discrepancy monitoring may lead to a reduction of positive reinforcement in everyday life, and to an impairment in self-reinforcement skills. As a consequence, even positive stimuli could become more and more perceived as triggers for a lowering of mood.• Indirect effect: following a positive stimulus, individuals may re- orientate attention on the negative part of experience as an intermediate step for the resumption of negative attitudes (such as negative biased interpretations, pessimistic forecasts and ruminative brooding) which, in turn, can trigger negative thoughts or depressive sensations, worsening mood’s state.• Hindering the degree of acceptance of alternative beliefs emerging from cognitive restructuring techniques. Functional beliefs could play the role of positive stimuli and act as a triggers for SDM.
  20. 20. Limitations• Self-report data subject to errors in measurement• NMT in assessing the dependent variable• Lack of an independent check for the reliability of the SCID diagnosis• The sampling strategy may have lead to different levels of motivation and engagement in the research process
  21. 21. Clinical implications• Assessing SDM may be useful in identifying and socializing a potential maladaptive cognitive strategy that could have an impact on mood, even independently from the diagnosis of depression• Address SDM may be beneficial for a reduction in negative emotion but also for enhancing the degree of acceptance of alternative beliefs emerging from cognitive restructuring techniques.
  22. 22. Future research• Deepen investigate both the SDM frequency of use in depressed and non-depressed individuals, and the motivations or beliefs that lead people to undertake it Understanding these aims, therapists will be able to call them into question and try to bring evidences of the maladaptive nature of SDM Patients would be able to learn how to manage the orientation of attention in a different way, and learn flexible control over it
  23. 23. Thank you for your attention Contact details Dr.ssa Chiara Manfredi Cognitive Psychotherapy School Studi Cognitivi, Modena, Italy University of Pavia, Italy c.manfredi@studicognitivi.net chiara.manfredi@unipv.it

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