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Record W2904394680 · doi:10.2196/11324

Supported Web-Based Guided Self-Help for Insomnia for Young People Attending Child and Adolescent Mental Health Services: Protocol for a Feasibility Assessment

2018· article· en· W2904394680 on OpenAlexvenueno aff
Bethany Cliffe, Abigail Croker, Megan Denne, Paul Stallard

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsInsomniaMental healthClinical psychologyCognitive behavioral therapy for insomniaPsychiatryPopulationPsychologySleep disorderCognitionMedicineProtocol (science)Cognitive behavioral therapyAlternative medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Sleep disturbance in adolescents is common, with up to one-third reporting significant symptoms of insomnia. Research with adults has demonstrated that Web-based cognitive behavioral therapy for insomnia (CBTi) can improve both sleep and mental health. However, research with adolescents is lacking, and we know little about whether CBTi would have similar effects on this younger population. OBJECTIVE: This paper summarizes the protocol of a study to assess the feasibility of adding supported Web-based CBTi to the usual care of young people aged 14-17 years attending specialist Child and Adolescent Mental Health Services (CAMHS). METHODS: This is an open trial where we will recruit young people (N=50) aged 14-17 years attending specialist CAMHS with primary or comorbid symptoms of insomnia. In addition to their usual care, young people will be provided with Sleepio, a 6-session, Web-based CBTi self-help program for insomnia. Sleepio teaches a range of techniques including sleep hygiene, relaxation training, stimulus control, sleep restriction, and cognitive techniques that participants will be helped to apply through brief, weekly telephone support calls. Questionnaires and interviews will be completed at baseline and postintervention (8-10 weeks) and will assess sleep, symptoms of depression and anxiety, and acceptability of Sleepio and telephone support. RESULTS: Recruitment started in May 2018 and continued until the end of October 2018. CONCLUSIONS: This study will provide preliminary evidence about whether supported Web-based CBTi is acceptable to young people with mental health problems and about the postintervention effects on sleep and symptoms of anxiety and depression. This information will determine whether a randomized trial to determine the effectiveness of Sleepio should be undertaken. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11324.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.041
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.087
Threshold uncertainty score0.293

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.028
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0870.022

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 head0.156
GPT teacher head0.562
Teacher spread0.405 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations11
Published2018
Admission routes1
Has abstractyes

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