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Record W3011843031 · doi:10.1186/s13643-020-01301-0

Rates of compliance and adherence to high-intensity interval training in insufficiently active adults: a systematic review and meta-analysis protocol

2020· review· en· W3011843031 on OpenAlexaff
Alexandre Santos, Chris Lonsdale, David R. Lubans, Diego Vasconcellos, Nathanial J. Kapsal, Mathew Vis‐Dunbar, Mary E. Jung

Bibliographic record

VenueSystematic Reviews · 2020
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMedicineCINAHLHigh-intensity interval trainingMEDLINEObservational studyPhysical therapyCompliance (psychology)Protocol (science)Interval trainingConfidence intervalMeta-analysisData extractionAlternative medicineInternal medicinePsychological interventionPathologyPsychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Both high-intensity interval training and moderate-intensity continuous training demonstrate beneficial physiological outcomes for active and insufficiently active populations. However, it remains unclear whether compliance to exercise in supervised settings translates to long-term adherence to physical activity in real-world, unstructured environments. To our knowledge, no comprehensive review is available on compliance and/or adherence rates to either modes of exercise for insufficiently active individuals. Furthermore, it is unclear which training modality insufficiently active individuals comply and/or adhere more readily to. Based on these gaps, the following two questions will be addressed: (1) What are compliance and adherence rates to high-intensity interval training for insufficiently active adults aged 18-65 years and (2) How do compliance and adherence rates differ between high-intensity interval training and moderate-intensity continuous training? METHODS: Both observational and experimental studies that report on compliance and/or adherence rates to high-intensity interval training will be included. Relevant studies will be retrieved from Medline, EMBASE, PsychINFO, SPORTDiscus, CINAHL, and Web of Science using a pre-specified search strategy. Pre-defined inclusion and exclusion criteria will be used by two independent researchers to determine eligible studies. Of those meeting the inclusion criteria, data extraction and narrative synthesis will be completed, and where applicable, random-effects meta-analyses will be computed to compare compliance and adherence rates between high-intensity interval training and moderate-intensity continuous training. Meta-regressions and sensitivity analyses will be used to further explore factors that could influence aggregate effect sizes. Risk of bias will be assessed using established tools by the Cochrane association, and quality assessment of the cumulative evidence will be assessed using the GRADE approach. DISCUSSION: Results from this study may have the potential to inform future physical activity recommendations and guidelines on the ideal mode of exercise for the general population. This review will add to the body of literature on the feasibility of high-intensity interval training for an insufficiently active population, conclusively addressing the ongoing debate of whether it is an appropriate exercise choice for this demographic. With this new information, individuals working towards a healthier lifestyle through physical activity engagement may be better equipped to make an evidence-based decision. SYSTEMATIC REVIEW REGISTRATION: This review has been registered in the PROSPERO database and assigned the identifier CRD42019103313.

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)0.075
metaresearch head score (Gemma)0.103
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 score0.075
Threshold uncertainty score0.396

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.103
Meta-epidemiology (narrow)0.0070.006
Meta-epidemiology (broad)0.0260.033
Bibliometrics0.0140.012
Science and technology studies0.0030.004
Scholarly communication0.0080.007
Open science0.0060.005
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0480.005

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 head0.255
GPT teacher head0.434
Teacher spread0.178 · 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 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

Citations18
Published2020
Admission routes1
Has abstractyes

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