MétaCan
Menu
Back to cohort
Record W2954691515 · doi:10.2196/14571

A Mobile App to Support Parents Making Child Mental Health Decisions: Protocol for a Feasibility Cluster Randomized Controlled Trial

2019· article· en· W2954691515 on OpenAlexvenueno aff
Shaun Liverpool, Helen Webber, Rob Matthews, Miranda Wolpert, Julian Edbrooke‐Childs

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialProtocol (science)Psychological interventionMental healthIntervention (counseling)MedicineQuality of life (healthcare)mHealthCluster randomised controlled trialNursingPsychologyApplied psychologyPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Shared decision making (SDM) is recognized as a person-centered approach to improving health care quality and outcomes. Few digital interventions to improve SDM have been tested in child and adolescent mental health (CAMH) settings. One such intervention is Power Up, a mobile phone app for young people (YP), which has shown some evidence of promise that YP who received Power Up reported greater levels of SDM. However, even though parents play a critical role in CAMH care and treatment, they often feel excluded from services. OBJECTIVE: This protocol is for a pilot trial to determine the feasibility of a large-scale randomized trial to develop and evaluate a Web app called Power Up for Parents (PUfP) to support parents and promote involvement in CAMH decisions. METHODS: A 2-stage process, consisting of the development stage and pilot-testing stage of the initial PUfP prototype, will be conducted. At the development stage, a qualitative study with parents and clinicians will be conducted. The interviews will aim to capture the experience of making CAMH decisions, preferences for involvement in SDM, and determine situations within which PUfP can be useful. At the pilot-testing stage, up to 90 parents and their clinicians will be invited to participate in the testing of the prototype. Parents will be randomly allocated to receive the intervention or be part of the control group. This study design will allow us to assess the acceptability and usefulness of PUfP in addition to examining the feasibility of a prospective randomized trial. Clinicians' perceptions of the prototype and how it has influenced parents' involvement in SDM will also be examined. RESULTS: Recruitment began in January 2019 and is scheduled to last for 10 months. Interviews and baseline data collection are currently in progress. To date, 11 CAMH sites have been recruited to take part in the study. It is anticipated that data collection will be completed by October 2019. CONCLUSIONS: The lack of parents' involvement in CAMH care and treatment can lead to higher rates of dropout from care and lower adherence to therapeutic interventions. There are significant benefits to be gained globally if digital SDM interventions are adopted by parents and shown to be successful in CAMH settings. TRIAL REGISTRATION: ISRCTN Registry ISRCTN39238984; http://www.isrctn.com/ISRCTN39238984. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14571.

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)0.055
metaresearch head score (Gemma)0.048
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 score0.129
Threshold uncertainty score0.431

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.048
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0090.006
Bibliometrics0.0040.004
Science and technology studies0.0050.004
Scholarly communication0.0060.004
Open science0.0040.003
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.1290.021

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 head0.301
GPT teacher head0.655
Teacher spread0.354 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research ProtocolsSame topicDigital Mental Health InterventionsFrench-language works237,207