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Record W2971751424 · doi:10.2196/15022

Smartphone Cardiac Rehabilitation, Assisted Self-Management Versus Usual Care: Protocol for a Multicenter Randomized Controlled Trial to Compare Effects and Costs Among People With Coronary Heart Disease

2019· article· en· W2971751424 on OpenAlexvenueno aff
Jonathan C Rawstorn, Kylie Ball, Brian Oldenburg, Clara K Chow, Sarah A. McNaughton, Karen E. Lamb, Lan Gao, Marj Moodie, John Amerena, Voltaire Nadurata, Christopher Neil, Stuart Cameron, Ralph Maddison

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsMedicineRandomized controlled trialPhysical therapyHealth coachingCoachingRehabilitationQuality of life (healthcare)Health careSports medicineNursingPsychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Alternative evidence-based cardiac rehabilitation (CR) delivery models that overcome significant barriers to access and delivery are needed to address persistent low utilization. Models utilizing contemporary digital technologies could significantly improve reach and fidelity as complementary alternatives to traditional center-based programs. OBJECTIVE: The aim of this study is to compare the effects and costs of the innovative Smartphone Cardiac Rehabilitation, Assisted self-Management (SCRAM) intervention with usual care CR. METHODS: In this investigator-, assessor-, and statistician-blinded parallel 2-arm randomized controlled trial, 220 adults (18+ years) with coronary heart disease are being recruited from 3 hospitals in metropolitan and regional Victoria, Australia. Participants are randomized (1:1) to receive advice to engage with usual care CR or the SCRAM intervention. SCRAM is a 24-week dual-phase intervention that includes 12 weeks of real-time remote exercise supervision and coaching from exercise physiologists, which is followed by 12 weeks of data-driven nonreal-time remote coaching via telephone. Both intervention phases include evidence- and theory-based multifactorial behavior change support delivered via smartphone push notifications. Outcomes assessed at baseline, 12 weeks, and 24 weeks include maximal aerobic exercise capacity (primary outcome at 24 weeks), modifiable cardiovascular risk factors, exercise adherence, secondary prevention self-management behaviors, health-related quality of life, and adverse events. Economic and process evaluations will determine cost-effectiveness and participant perceptions of the treatment arms, respectively. RESULTS: The trial was funded in November 2017 and received ethical approval in June 2018. Recruitment began in November 2018. As of September 2019, 54 participants have been randomized into the trial. CONCLUSIONS: The innovative multiphase SCRAM intervention delivers real-time remote exercise supervision and evidence-based self-management behavioral support to participants, regardless of their geographic proximity to traditional center-based CR facilities. Our trial will provide unique and valuable information about effects of SCRAM on outcomes associated with cardiac and all-cause mortality, as well as acceptability and cost-effectiveness. These findings will be important to inform health care providers about the potential for innovative program delivery models, such as SCRAM, to be implemented at scale, as a complement to existing CR programs. The inclusion of a cohort comprising metropolitan-, regional-, and rural-dwelling participants will help to understand the role of this delivery model across health care contexts with diverse needs. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ACTRN): 12618001458224; anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374508. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15022.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.083
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.485
Teacher spread0.445 · 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 teacher head, 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

Citations38
Published2019
Admission routes1
Has abstractyes

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