“I can’t escape my scars, even if I do get better”: A qualitative exploration of how adolescents talk about their self-harm and self-harm scars during cognitive behavioural therapy for depression
Bibliographic record
Abstract
Emerging evidence indicates that perceptions of self-harm behaviours and self-harm scars may thwart recovery from depression, yet limited research has explored adolescent accounts of their self-harm and scars during therapy. This study sought to explore how adolescents describe their self-harm behaviours and scars during Cognitive Behavioural Therapy (CBT) and explore the sociocultural discourses that may influence these descriptions. The participants were six female adolescents (aged 14-17 years old) with clinical depression, who were engaging in self-harm. All participants accessed CBT as part of clinical trial evaluating three psychological treatments for major depressive disorder in Child and Adolescent Mental Health Services. Audio-taped CBT sessions were analyzed using discourse analysis. Within CBT sessions, adolescents drew upon stigma discourses in talking about their self-harm. Adolescent also described their self-harm scars as shameful and stigmatizing, and as "proof" of the legitimacy of their depression. It is important for CBT practitioners to understand the context of sociocultural discourses around self-harm behaviours and self-harm scars, which are reflected in how adolescents with depression describe these within therapy and may serve to maintain distress. The study indicates that awareness of use of language and intersecting sociocultural discourses can inform CBT practice.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".