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Record W3136342147 · doi:10.1080/16506073.2021.1938663

Internet-delivered cognitive processing therapy for individuals with a history of bullying victimization: a randomized controlled trial.

2022· article· en· W3136342147 on OpenAlexaff

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsRandomized controlled trialDistressAnxietyCognitionCognitive processing therapyCognitive therapySocial anxietyMultilevel modelCognitive restructuring

Abstract

fetched live from OpenAlex

= 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.

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.053
GPT teacher head0.314
Teacher spread0.262 · 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 designRandomized trial
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

Citations0
Published2022
Admission routes1
Has abstractyes

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