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Record W4417297939 · doi:10.2196/65491

A Brief, Affordable, Broad-Access Transdiagnostic Intervention (Project RE-THINK) for Adolescents: Quasi-Experimental Study

2025· article· en· W4417297939 on OpenAlexvenueno aff
Christopher S. Rozek, Maegan B. Arney, Benjamin Kedl, Jenalee R. Doom, David C. Rozek

Bibliographic record

VenueJMIR Mental Health · 2025
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionIntervention (counseling)CognitionCoping (psychology)CurriculumMental healthCognitive behavioral therapy

Abstract

fetched live from OpenAlex

Background: Adolescence is a crucial developmental period characterized by elevated stress and significant mental health challenges, including depression and anxiety. With barriers, such as stigma, accessibility, and cost hindering effective treatment, leveraging school systems for mental health interventions offers a strategic advantage due to their reach and potential for scalability. Objective: This study aimed to investigate the immediate impact of "Project RE-THINK," a single-session, digital thought record intervention delivered in a school setting, on negative cognitions and overall emotional valence among adolescents. Methods: Project RE-THINK helps adolescents to identify, examine, and challenge negative cognitions to improve their mental health, as demonstrated through changes in negative cognition and overall emotional valence. Adolescents (N=1052) in grades 10-12 enrolled in high school during the 2023-2024 school year completed the digital thought record intervention activity. Using a quasi-experimental pre/post design, participants read through an example thought record and completed their own thought record, which involved identifying and describing a recent upsetting situation, answering a series of questions to challenge their negative cognition, and learning and using emotion regulation skills regarding the upsetting situation. Measures of pre- and postintervention overall emotional valence and negative cognition were collected to determine the intervention effect on participants' mental health. Results: Descriptive statistics confirmed that smaller proportions of adolescents endorsed feeling negative emotions, such as anger, shame, anxiety, disgust, guilt, sadness, and fear, after the intervention. Paired samples t tests showed that adolescents experienced a significant reduction in their belief in their negative cognition from pre- to postintervention (t1051=27.71; P<.001; d=0.85, 95% CI 0.78-0.93), which demonstrates that the intervention helped them challenge their negative thoughts about their upsetting situation, as well as significant improvements to their overall emotional valence (t1051=-31.85; P<.001; d=-0.98, 95% CI -1.06 to -0.91), which demonstrates that the intervention helped them feel better about their upsetting situation. Findings also showed a significant correlation between change in negative cognition and change in overall emotional valence (r=0.25; P<.001), supporting our hypothesis that reducing the strength of belief in negative cognitions can help improve one's emotions. Finally, analysis of covariance (ANCOVAs) confirmed that there were no significant differences in intervention efficacy by gender, race and ethnicity, or socioeconomic status, suggesting broad intervention efficacy across adolescents from different backgrounds and experiences. Conclusions: Project RE-THINK effectively improved both cognitive and emotional outcomes among adolescents, demonstrating its potential as a scalable, low-cost intervention within school settings. Future studies should explore the longitudinal effects and potential integration of such interventions into regular school curricula to help adolescents learn effective emotions and coping skills as well as to help protect and sustain adolescent mental health.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.036
GPT teacher head0.420
Teacher spread0.384 · 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 designNon-randomized 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
Published2025
Admission routes1
Has abstractyes

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