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Record W2604352892

Coping Strategies in Major Depression and over the Course of Cognitive Therapy for Depression/Les Stratégies D'adaptation Associées À la Dépression et Leur éVolution Au Cours D'un Traitement Cognitif

2017· article· fr· W2604352892 on OpenAlexvenueaboutno aff
Martin Drapeau, Emily Blake, Keith S. Dobson, Annett Körner

Bibliographic record

VenueCanadian Journal of Counselling and Psychotherapy · 2017
Typearticle
Languagefr
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)Coping (psychology)PsychologyMoodMental healthPsychiatryExcellenceMedicineGerontologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Major depression is predicted to become the primary contributor to disease burden in high-income countries such as Canada by 2030 (Mathers & Loncar, 2006). While the disorder's worldwide lifetime prevalence is estimated to be in the 8-12% range, these rates are slightly higher in Canada, with a 24% lifetime prevalence among women and a 15% lifetime prevalence among men (Andrade et al., 2006; Hirschfeld et al., 1997). Beyond the individual suffering that major depression is associated with, which limits activities of daily living at home, work, and school, depression also poses a serious economic problem to society. In Canada alone, overall economic losses have been estimated at $4.5 billion annually, making depression one of the costliest health problems in Canada (Stephens & Joubert, 2001). It is no surprise, then, that a considerable amount of attention has been given to developing effective treatments for depression.Cognitive therapy (CT) is one such treatment; it has been shown to be both efficacious and effective in treating major depression, and is now recommended in most reputable practice guidelines (e.g., National Institute for Health and Care Excellence, 2009; Parikh et al., 2009). However, a successful treatment should not only alleviate symptoms but also alter the underlying factors theoretically linked to the onset and maintenance of a clinical condition. Hence, as support for the efficacy of CT for treating depression increased, the focus in research also shifted toward the mechanisms through which CT achieves its results (Ekers, Richards, & Gilbody, 2008; Kazdin, 2007). For example, because mood disorders are believed to be related to a person's negatively biased information-processing and to dysfunctional beliefs that influence motivation, behaviour, and affect (e.g., Beck, Rush, Shaw, & Emery, 1979), a plethora of studies have examined how core cognitive processes such as cognitive errors, dysfunctional attitudes, and negative automatic thoughts, amongst others, are related to depression (e.g., Blake, Dobson, Sheptycki, & Drapeau, 2016; Clark, Beck, & Alford, 1999; Marton, Connolly, Kutcher, & Korenblum, 1993; Pothier, Dobson, & Drapeau, 2012; Schwartzman, Stamoulos, et al., 2012).Other studies have focused on another construct that is central to cognitive behavioural theories of depression: coping (see Beck, 1976), which refers to strategies that are used to respond to and produce an acceptable adaptation to stressors and situations (Perry, Drapeau, & Dunkley, 2007). Indeed, developing appropriate and adaptive coping strategies and eliminating maladaptive coping strategies are two of the aims of therapy (e.g., David, 2006; Wenzel, 2013). Over the last few decades, it has been shown that depression is related to such maladaptive coping strategies as helplessness (e.g., Pryce et al., 2011), rumination (e.g., Hong, 2007), wishful thinking and avoidance (e.g., Trew, 2011), escape (e.g., Ottenbreit & Dobson, 2004), social isolation (e.g., Hawton et al., 2011), and other types of maladaptive coping strategies (e.g., Mahmoud, Staten, Hall, & Lennie, 2012; Morris, Kouros, Fox, Rao, & Garber, 2014). It has also been found that depressed individuals use fewer adaptive coping strategies (including problem-solving strategies) and less positive reappraisal and negotiation strategies than non- or less-depressed individuals (Garnefski, Legerstee, Kraaij, van den Kommer, & Teerds, 2002; Gloria & Steinhardt, 2014; Sinclair, Wallston, & Strachan, 2016).However, a subset of early studies concluded that use of coping strategies that focus on problem solving are not different in individuals suffering from depression compared to nondepressed individuals (e.g., Coyne, Aldwin, & Lazarus, 1981), while others suggested that there may even be increased levels of coping involving self-reliance among participants with higher levels of depressive symptoms (see Folkman & Lazarus, 1986). …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.368
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2017
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Counselling and Psychotherapy→Same topicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes→French-language works237,207→