Cognitive Behavioural Therapy through PowerPoint: Efficacy in an Adolescent Clinical Population with Depression and Anxiety
Bibliographic record
Abstract
BACKGROUND: Limited help-seeking behaviours, among adolescents with mental health concerns and many barriers to accessing mental health services, make innovative approaches to administering mental health therapies crucial. Therefore, this study evaluated the efficacy of e-CBT given via PowerPoint slides to treat adolescents with anxiety and/or depression. METHOD: 15 adolescents referred to an outpatient adolescent psychiatry clinic to treat a primary DSM-IV diagnosis of anxiety and/or depression chose between 8 weeks of e-CBT (n=7) or 7 weeks of live CBT (n=8). The e-CBT modules were presented using PowerPoint delivered weekly through email by either a senior psychiatry resident or an attending physician. Within each session, participants in both groups had personalized feedback on their mandatory weekly homework assignment from the previous week's module. BYIs were completed before treatment and and after final treatment within both groups to assess changes in depression, anxiety, anger, disruption, and self-concept. FINDINGS: Before treatment, BYI scores did not sig. differ between groups. After treatment, e-CBT participants reported sig. improved depression, anger, anxiety, and self-concept BYI scores while live CBT participants did not report any sig. changes. Only the Beck Anxiety Inventory sig. differed between groups after CBT. CONCLUSION: Despite the low sample size within this study, using email to deliver e-CBT PowerPoint slides and individualized homework feedback shows promise as an alternate method of CBT delivery that reduces barriers to receiving mental health treatment that occur internationally.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".