Le modèle de la flexibilité psychologique : une approche nouvelle de la santé mentale
Bibliographic record
Abstract
OBJECTIVE: This paper presents a vision of mental health using the model of psychological flexibility of Acceptance and Commitment Therapy (ACT). ACT is a representative approach of the third wave of cognitive-behavioural therapy (CBT). This article first describes the theoretical and practical aspects of ACT and, in a second part, reviews some of the empirical data supporting its clinical use. Due to the high rate of comorbidity in mental health settings, transdiagnostic approaches in CBT, such as ACT, have recently become popular and particularly appealing to various clinical settings. METHOD: The theoretical aspects underlying ACT, as well as its clinical components in the treatment of psychopathology were described based on major books in this area, such as Hayes, Strosahl and Wilson (2012). A descriptive literature review was undertaken to explore the data on the efficacy of ACT for the treatment of mental health problems. Psycinfo and Medline, as well as the Association for Contextual Science website were analyzed for relevant articles. The key search terms were: "Acceptance and Commitment therapy" or "ACT" or "acceptance" or "mindfulness" or "defusion." The reference lists of the articles retrieved were also analyzed. The articles that were not in English or French were excluded. RESULTS: Data suggest that ACT is particularly effective for stress, anxiety disorders, depression, substance abuse and various chronic medical conditions. The six processes of the model of psychological flexibility have been validated based on the results of correlational and meditational studies. More than seventy randomized clinical trials and a meta-analysis including 18 randomized control trials conclude that ACT is more effective than waiting list, placebo and treatment as usual control conditions. CONCLUSION: ACT is a promising and evidence-based approach in mental health for the treatment of anxiety and depression as well as for complex and chronic conditions. More research is needed to further validate its theoretical model and further refine our understanding of how ACT could be effective for the management of mental health illness and how it could enhance quality of life for people who suffer from these conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".