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Record W4414788876 · doi:10.2196/76830

Acceptability, Relevance, and Short-Term Outcomes of the STAC-T Bullying Bystander App: Feasibility Quantitative Study

2025· article· en· W4414788876 on OpenAlexvenueno aff
Diana M. Doumas, Aida Midgett, Robin Hausheer, Amanda Winburn, Mary Klein Buller, Taylor Perron

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institutes of Health
KeywordsRelevance (law)Bystander effectPoison controlSuicide preventionHuman factors and ergonomicsIntervention (counseling)

Abstract

fetched live from OpenAlex

Background: Bullying is a significant public health issue, with approximately 25% of middle school students reporting being a target of bullying in the past year. Students who are targets of bullying or witness bullying are at high risk for negative mental health outcomes, including depression and anxiety. STAC is an evidence-based bullying bystander intervention for middle school students, with program outcomes that include reductions in bullying perpetration and victimization, as well as associated mental health risks. We developed a technology-based version of STAC (STAC-T) to reduce implementation barriers associated with in-person bullying prevention programs. STAC-T is an interactive app that includes a 40-minute training and a 15-minute booster session. Objective: This study aimed to evaluate the acceptability and relevance of the STAC-T program. We were also interested in how program acceptability and relevance are related to the use of specific bystander intervention skills (eg, STAC strategies) students learn in the program. Methods: This study was part of a larger study in which students recruited from 6 middle schools in rural, low-income communities in the United States were randomized to either the STAC-T intervention or a control condition. Participants in this study were 229 students in the intervention group who completed the 30-day follow-up survey, including the acceptability and relevance questionnaire. The survey assessed program acceptability and relevance, whether or not students witnessed bullying posttraining, and the use of the STAC strategies to intervene in bullying situations. Descriptive statistics were used to assess acceptability, relevance, and the use of STAC strategies. Linear regression analysis was used to assess the relationship of program acceptability and relevance to STAC strategy use. Results: Of the 229 student participants, the majority reported the program was acceptable (188, 82.1%, to 206, 90.0%) and relevant (180, 78.6%, to 190, 83.0%) for students at their school. Of the 54.6% (125/229) of students who witnessed bullying posttraining, 88.8% (111/125) reported the use of at least one STAC strategy to intervene when witnessing bullying. Students were most likely to use the STAC bystander intervention strategies Turning it Over and Accompanying Others, relative to Stealing the Show and Coaching Compassion. Regression analyses revealed that program relevance was a significant predictor of posttraining use of STAC strategies (P=.016). In contrast, program acceptability was not a significant predictor of posttraining STAC strategy use (P=.660). Conclusions: This study provides support for the acceptability and relevance of STAC-T and its effectiveness in promoting the use of the STAC strategies to intervene in bullying situations. Furthermore, program relevance was related to STAC strategy use, highlighting the importance of assessing program relevance for specific student populations.

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)0.020
metaresearch head score (Gemma)0.041
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 score0.020
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.121
GPT teacher head0.489
Teacher spread0.367 · 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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