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Record W4385710584 · doi:10.2196/49357

Effects of Using Websites on Physical Activity and Diet Quality for Adults Living With Chronic Health Conditions: Systematic Review and Meta-Analysis

2023· review· en· W4385710584 on OpenAlexfundno aff
Dina Pogrebnoy, Amy M Dennett, Dawn B. Simpson, Lesley MacDonald‐Wicks, Amanda Patterson, Coralie English

Bibliographic record

VenueJournal of Medical Internet Research · 2023
Typereview
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Center for Advancing Translational SciencesNational Research Foundation of KoreaMedical Research CouncilNational Health and Medical Research CouncilUniversity of California, San FranciscoRehabilitation Research and Development ServiceHelse Nord RHFFood and Health BureauNational Institute for Health and Care ResearchKorea Health Industry Development InstituteHealth and Medical Research FundUniversiteit MaastrichtZonMwNational Institutes of HealthEuropean CommissionMaastricht Universitair Medisch CentrumCanada Research ChairsHong Kong Baptist UniversityNational Cancer InstituteKWF KankerbestrijdingNational Research FoundationNational Heart Foundation of AustraliaU.S. Department of Veterans AffairsProstate Cancer Foundation
KeywordsMeta-analysisPhysical activityGerontologyQuality (philosophy)MedicinePsychologyPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Adults with chronic health conditions need support to manage modifiable risk factors such as physical inactivity and poor diet. Disease-specific websites with health information on physical activity and diet quality may be effective in supporting adults in managing their chronic illnesses. OBJECTIVE: The primary aim of this review was to determine whether using websites with health information can lead to improvements in physical activity levels or diet quality in adults with chronic health conditions. METHODS: Randomized controlled trials evaluating the effectiveness of website use on levels of physical activity or diet quality in adults with chronic health conditions were included. MEDLINE, Embase, CINAHL, and the Physiotherapy Evidence Database were searched from the earliest available record until February 2023. Data for outcomes measuring physical activity levels; diet quality; and, where reported, self-efficacy and quality of life were independently extracted by 2 reviewers. The risk of bias was assessed using the Physiotherapy Evidence Database scale, and the overall certainty of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach. Where values were presented as the same unit of measure, postintervention scores were pooled for meta-analysis to yield an overall mean difference (MD). A standardized MD (SMD) was calculated for the pooled data in which different units for the same outcome were used. Individual trial data were described in cases where the data of trials could not be pooled. RESULTS: A total of 29 trials (N=6418 participants) across 8 different disease groups with intervention periods ranging from 4 weeks to 12 months were included in the analysis. There was moderate-certainty evidence that using websites with health information increased levels of moderate to vigorous physical activity (MD=39 min/wk, 95% CI 18.60-58.47), quality of life (SMD=0.36, 95% CI 0.12-0.59), and self-efficacy (SMD=0.26, 95% CI 0.05-0.48) and high-certainty evidence for reduction in processed meat consumption (MD=1.1 portions/wk, 95% CI 0.70-1.58) when compared with usual care. No differences were detected in other measures of diet quality. There was no increased benefit for website users who were offered additional support. CONCLUSIONS: The use of websites for risk factor management has the potential to improve physical activity levels, quality of life, and self-efficacy as well as reduce processed meat consumption for adults living with chronic health conditions when compared with usual care. However, it remains unclear whether using websites leads to meaningful and long-lasting behavior change. TRIAL REGISTRATION: PROSPERO CRD42021283168; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=283168.

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)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.039
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0210.035
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.415
GPT teacher head0.663
Teacher spread0.248 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations6
Published2023
Admission routes1
Has abstractyes

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