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Record W4315620378 · doi:10.2196/42119

A Universal Mental Health–Promoting Mobile App for Adolescents: Protocol for a Cluster Randomized Controlled Trial

2023· article· en· W4315620378 on OpenAlexvenueno aff
Sabine Kaiser, Marte Rye, Reidar Jakobsen, Monica Martinussen, Helene Høgsdal, Henriette Kyrrestad

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
FundersHelsedirektoratetUniversitetet i Tromsø
KeywordsMental healthRandomized controlled trialCluster randomised controlled trialFeelingIntervention (counseling)ChecklistPsychologymHealthCoping (psychology)Psychological interventionMedicineClinical psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: In times of increasing mental health problems among young people, strengthening efforts to improve mental health through mental health promotion and prevention becomes increasingly important. Effective measures that support young people in coping with negative thoughts, feelings, and stress are essential, not just for the individual but also for society. OBJECTIVE: The aim of this paper is to provide a description of a cluster randomized controlled trial that will be conducted to examine the effectiveness of Opp, a universal mental health-promoting mobile app for adolescents aged 13 to 19 years that provides information and exercises to better cope with stress, negative thoughts, and negative feelings. The protocol was developed in accordance with the SPIRIT checklist. METHODS: An effectiveness study will be conducted with 3 measurement points: preintervention (T1), 2 weeks after the intervention (T2), and about 1 month after the intervention (T3). Adolescents will be recruited from middle and high schools in Norway and randomly assigned to the intervention or control groups. Randomization will be conducted on the school level. Opp can be downloaded from the Google Play or App Store but is password protected with a 4-digit code, which will be removed after study completion. Participants in the intervention group will receive a text message with the code to unlock the app. The participants in the intervention group can use Opp without limits on length or time of use. Objective data on how long or how often the participants use the app will not be collected. However, the second and third questionnaires for the intervention group contain app-specific questions on, for example, the use of the app. RESULTS: Recruitment and data collection started in August and September 2022. So far, 381 adolescents have answered the first questionnaire. Data collection was expected to end in December 2022 but has had to be prolonged to approximately June 2023. The results of the study will be available in 2023 at the earliest. CONCLUSIONS: This project will contribute unique knowledge to the field, as there are few studies that have examined the effects of universal health-promoting mobile apps for adolescents. However, several limitations have to be taken into account when interpreting the results, such as randomization on the school level, the short time frame in which the study was conducted, and the lack of objective data to monitor the use of the app. TRIAL REGISTRATION: ClinicalTrials.gov NCT05211713; https://www.clinicaltrials.gov/ct2/show/NCT05211713. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/42119.

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)0.035
metaresearch head score (Gemma)0.030
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.135
Threshold uncertainty score0.451

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.030
Meta-epidemiology (narrow)0.0070.004
Meta-epidemiology (broad)0.0130.007
Bibliometrics0.0040.005
Science and technology studies0.0050.004
Scholarly communication0.0050.004
Open science0.0040.003
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.1350.017

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 head0.215
GPT teacher head0.619
Teacher spread0.404 · 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
GenreProtocol

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

Citations4
Published2023
Admission routes1
Has abstractyes

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