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Record W2786835188 · doi:10.2196/mental.8098

Web-Based Decision Aid to Assist Help-Seeking Choices for Young People Who Self-Harm: Outcomes From a Randomized Controlled Feasibility Trial

2018· article· en· W2786835188 on OpenAlexvenueno aff
Sarah Rowe, Krisna Patel, Rebecca French, Claire Henderson, Dennis Ougrin, Mike Slade, Paul Moran

Bibliographic record

VenueJMIR Mental Health · 2018
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
FundersNIHR Nottingham Biomedical Research CentreUniversity of BristolUniversity College LondonKing's College LondonGuy's and St Thomas' CharityNational Institute for Health and Care ResearchNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
KeywordsRandomized controlled trialThematic analysisInformed consentHarmIntervention (counseling)MoodMedicineFeelingPsychologyQualitative researchClinical psychologyNursingSocial psychologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Adolescents who self-harm are often unsure how or where to get help. We developed a Web-based personalized decision aid (DA) designed to support young people in decision making about seeking help for their self-harm. OBJECTIVE: The aim of this study was to evaluate the feasibility and acceptability of the DA intervention and the randomized controlled trial (RCT) in a school setting. METHODS: We conducted a two-group, single blind, randomized controlled feasibility trial in a school setting. Participants aged 12 to 18 years who reported self-harm in the past 12 months were randomized to either a Web-based DA or to general information about mood and feelings. Feasibility of recruitment, randomization, and follow-up rates were assessed, as was acceptability of the intervention and study procedures. Descriptive data were collected on outcome measures examining decision making and help-seeking behavior. Qualitative interviews were conducted with young people, parents or carers, and staff and subjected to thematic analysis to explore their views of the DA and study processes. RESULTS: Parental consent was a significant barrier to young people participating in the trial, with only 17.87% (208/1164) of parents or guardians who were contacted for consent responding to study invitations. Where parental consent was obtained, we were able to recruit 81.7% (170/208) of young people into the study. Of those young people screened, 13.5% (23/170) had self-harmed in the past year. Ten participants were randomized to receiving the DA, and 13 were randomized to the control group. Four-week follow-up assessments were completed with all participants. The DA had good acceptability, but qualitative interviews suggested that a DA that addressed broader mental health problems such as depression, anxiety, and self-harm may be more beneficial. CONCLUSIONS: A broad-based mental health DA addressing a wide range of psychosocial problems may be useful for young people. The requirement for parental consent is a key barrier to intervention research on self-harm in the school setting. Adaptations to the research design and the intervention are needed before generalizable research about DAs can be successfully conducted in a school setting. TRIAL REGISTRATION: International Standard Randomized Controlled Trial registry: ISRCTN11230559; http://www.isrctn.com/ISRCTN11230559 (Archived by WebCite at http://www.webcitation.org/6wqErsYWG).

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)0.030
metaresearch head score (Gemma)0.038
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.038
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0020.002
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.044
GPT teacher head0.437
Teacher spread0.393 · 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
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

Citations29
Published2018
Admission routes1
Has abstractyes

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