MétaCan
Menu
Back to cohort
Record W2946463343 · doi:10.2196/12892

Evaluating a Web-Based Mental Health Service for Secondary School Students in Australia: Protocol for a Cluster Randomized Controlled Trial

2019· article· en· W2946463343 on OpenAlexvenueno aff
Bridianne O’Dea, Catherine King, Mirjana Subotic-Kerry, Melissa S. Anderson, Melinda Rose Achilles, Belinda Parker, Andrew Mackinnon, Josephine Anderson, Nicole Cockayne, Helen Christensen

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialMental healthMedicineCluster randomised controlled trialAnxietyIntervention (counseling)Service (business)Psychological interventionProtocol (science)Family medicinePsychologyNursingPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Mental health problems are prevalent among Australian secondary school youth; however, help-seeking is low. Schools offer an ideal setting to address these concerns. The Black Dog Institute has developed a Web-based mental health service for secondary schools that is modeled on the principles of stepped care. The Smooth Sailing service aims to improve help-seeking and reduce anxiety and depressive symptoms in secondary school students. The acceptability of this service has been demonstrated in a pilot study. A full trial is now warranted. OBJECTIVE: This study protocol for a cluster randomized controlled trial (RCT) aims to evaluate the effectiveness of the Smooth Sailing Web-based service for improving help-seeking intentions and behavior, and reducing depressive and anxiety symptoms, alongside other mental health outcomes, when compared with a school-as-usual control condition in secondary school youth. METHODS: This RCT aims to recruit 1600 students from 16 secondary schools in regional and urban locations throughout New South Wales, Australia. Schools are randomly assigned to the intervention or school-as-usual control condition at the school level. Approximately 100 students from 1 or multiple grades are recruited from each participating school. Participants complete measures at 3 timepoints: baseline, 6 weeks post, and 12 weeks post, with the primary outcome assessed at 12 weeks posttest. Participants assigned to the intervention condition register to the Web-based service at baseline and receive care in accordance with the service model. Participants in the control condition receive school-as-usual. RESULTS: The first baseline assessment occurred on February 22, 2018, with the 12-week endpoint assessments completed on Friday, June 29, 2018. Control schools are currently receiving the service, due for completion by June 30, 2019. The trial results are expected to demonstrate improved help-seeking intentions and behavior among students assigned to the intervention condition, alongside improvements in symptoms of depression, anxiety, distress, and other mental health outcomes when compared with students assigned to the control condition. CONCLUSIONS: To our knowledge, this is the first time that a Web-based mental health service based on the principles of stepped care will have been integrated into, and evaluated in, the Australian school context. The findings of this trial will have implications for the suitability of this type of service model in Australian schools and for the delivery of school-based mental health services more broadly. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12618001539224 https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375821&isReview=true (Archived by WebCite at http://www.webcitation.org/77N3MDGS6). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12892.

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)0.040
metaresearch head score (Gemma)0.032
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 score0.077
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.032
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0150.007
Bibliometrics0.0030.004
Science and technology studies0.0040.004
Scholarly communication0.0060.005
Open science0.0040.003
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0770.011

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 head0.377
GPT teacher head0.691
Teacher spread0.314 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

Explore more

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