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Record W4414057392 · doi:10.2196/71433

Evaluating the Preliminary Efficacy of the TRUST Intervention on Alone-Time and Communication During Well-Adolescent Visits: Quasi-Experimental Study

2025· article· en· W4414057392 on OpenAlexvenueno aff
Jyu‐Lin Chen, Marissa Raymond‐Flesch, Thomas J. Hoffmann, Chen-Xi Lin, Ling Xu, Kimberly A. Koester

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)Psychological interventionData collectionQualitative researchAffect (linguistics)

Abstract

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BACKGROUND: Alone time with health care providers is critical for adolescents, and several professional organizations recommend it. Alone time with providers promotes better utilization of health services, empowers adolescents to manage their health, and facilitates discussions on sensitive issues. However, only 40% of adolescents have private conversations with clinicians during visits. The advancement of mobile health technology provides an excellent opportunity to deliver effective interventions to promote adolescent-provider alone time with adolescents, parents, and providers. OBJECTIVE: This pilot study aims to explore the preliminary efficacy of a technology-based intervention designed to increase alone time with providers during well-adolescent visits and its impact on trustworthiness, parent-adolescent communication, sexual risk communication, parental monitoring, and parental support before and after the intervention. METHODS: A pre- and postintervention design was used. Participants were recruited through local clinics. After obtaining consent, participants accessed a study website to complete a baseline survey, independently interact with 4 educational modules on a website or cellphone, and complete a post-test survey 1 month after their well-adolescent visits. The surveys assessed alone time with providers, trustworthiness, parent-adolescent communication, sexual risk communication, parental monitoring, and parental support. Mixed model analysis and effect sizes were used to evaluate changes in these outcomes from pre- to postintervention. RESULTS: Thirty-two dyads (38 adolescents and 32 mothers) participated in this pilot study. About 86% (n=33) of adolescents and 87% (n=28) of mothers completed the pre- and post-test assessments and the intervention. This study found a trend toward an increase in alone time from 81.6% to 84.4%, albeit not statistically significant. Adolescents initiating alone time with providers rose from 6.45% (n=2) to 18.5% (n=5). Over 90% (n=26) of adolescents reported feeling comfortable in one-on-one interactions with providers postintervention. Mixed model analysis revealed significant improvements among adolescents in parental monitoring (z=2.93, P<.001), sexual risk communication (z=3.11, P<.001), parent-adolescent communication (z=3.11, P<.001), open family communication (z=2.00, P=.04), and parental support (z=2.87, P<.001). For mothers, significant improvements were found in parental monitoring (z=2.45, P<.001) and problem family communication (z=2.24, P=.03). CONCLUSIONS: This pilot study demonstrates promising results regarding the preliminary efficacy of a technology-based intervention to increase alone time with providers during well-adolescent visits and to enhance communication and parenting practices. Improving access to alone time and strengthening communication between parents and adolescents facilitates discussions about sensitive topics, including parental monitoring, sexual and reproductive health, and may strengthen overall satisfaction with health care. TRIAL REGISTRATION: ClinicalTrials.gov NCT07064070; https://clinicaltrials.gov/study/NCT07064070.

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)0.011
metaresearch head score (Gemma)0.014
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 score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.085
GPT teacher head0.468
Teacher spread0.383 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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