Internet-delivered cognitive processing therapy for individuals with a history of bullying victimization: a randomized controlled trial
Bibliographic record
Abstract
The purpose of this randomized controlled trial was to test an internet-delivered version of cognitive processing therapy (CPT) for the psychological distress associated with bullying victimization. The sample comprised 52 adults (i.e. 69.20% women; mean age = 43.37 (SD = 12.47); 3.85% ethnic minority) who self-identified as having a lifetime history of bullying victimization. Participants were randomized into three groups, which received 12 sessions of internet-delivered, therapist-guided, and content-modified version of CPT, 12 sessions of internet-delivered and therapist-guided stress management (SM), or a waitlist. Treatment outcomes included maladaptive trauma appraisals, symptoms of posttraumatic stress disorder (PTSD), depression, general anxiety and stress, social anxiety, and anger. Hierarchical linear modeling was used to analyse the data. Findings indicated that CPT was effective in reducing the strength of maladaptive appraisals related to bullying victimization and symptoms of PTSD compared to the waitlist and SM. SM outperformed CPT and the waitlist in reducing symptoms of depression, general anxiety, and stress. In conclusion, the results of this trial suggest that internet-delivered CPT is effective for the psychological distress and maladaptive appraisals associated with bullying victimization but that adaptions might be needed to target more effectively symptoms of anxiety and depression.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".