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Record W1560847144 · doi:10.2196/resprot.4032

A Mobile Phone and Web-Based Intervention for Improving Mental Well-Being in Young People With Type 1 Diabetes: Design of a Randomized Controlled Trial

2015· article· en· W1560847144 on OpenAlexvenueno aff
Janine Clarke, Veronica Vatiliotis, Charles F. Verge, JANE HOLMES-WALKER, Lesley V. Campbell, Kay Wilhelm, Judith Proudfoot

Bibliographic record

VenueJMIR Research Protocols · 2015
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
FundersAustralian Rotary Health
KeywordsRandomized controlled trialMedicineMental healthDistressType 2 diabetesAnxietyIntervention (counseling)Quality of life (healthcare)Short Message ServiceClinical psychologyPsychiatryDiabetes mellitusNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Young people with type 1 diabetes experience elevated levels of emotional distress that impact negatively on their diabetes self-care, quality of life, and disease-related morbidity and mortality. While the need is great and clinically significant, a range of structural (eg, service availability), psychological (eg, perceived stigma), and practical (eg, time and lifestyle) barriers mean that a majority of young people do not access the support they need to manage the emotional and behavioral challenges of type 1 diabetes. OBJECTIVE: The aim of this study is to examine the effectiveness of a fully-automated cognitive behavior therapy-based mobile phone and Web-based psychotherapeutic intervention (myCompass) for reducing mental health symptoms and diabetes-related distress, and improving positive well-being in this vulnerable patient group. METHODS: A two-arm randomized controlled trial will be conducted. Young people with type 1 diabetes and at least mild psychological distress will be recruited via outpatient diabetes centers at three tertiary hospitals in Sydney, Australia, and referred for screening to a study-specific website. Data will be collected entirely online. Participants randomized to the intervention group will use the myCompass intervention for 7 weeks, while at the same time a control group will use an active placebo program matched to the intervention on duration, mode of delivery, and interactivity. RESULTS: The primary outcome will be mental well-being (ie, depression, anxiety, diabetes-related distress, and positive well-being), for which data will be collected at baseline, post-intervention, and after 3 months follow-up. Secondary outcomes will be functional (work and social functioning and diabetes self-care), biochemical measures (HbA1c), and mental health self-efficacy. We aim to recruit 280 people into the study that will be conducted entirely online. Group differences will be analyzed on an intention-to-treat basis using mixed models repeated measures. CONCLUSIONS: We hypothesize that scores on the outcome measures will improve significantly for young people who use the mobile phone and Web-based intervention compared to the control group. myCompass is a public health intervention that is broadly available and free to use. If effective, the program has the capacity to provide convenient and accessible evidenced-based care to the large group of young people with type 1 diabetes who do not currently access the psychosocial support they need. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12614000974606; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366607 (Archived by WebCite at http://www.webcitation.org/6YGdeT0Dk).

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)0.014
metaresearch head score (Gemma)0.013
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 score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.013
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0080.005
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.068
GPT teacher head0.440
Teacher spread0.372 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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