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Record W4402975693 · doi:10.2196/55576

Effectiveness of Internet-Based Telehealth Programs in Patients With Hip or Knee Osteoarthritis: Systematic Review and Meta-Analysis

2024· review· en· W4402975693 on OpenAlexaff
Haonan Wang, Shuyue Liu, Yunyi Liu, Xiao Zhang, Jian Li

Bibliographic record

VenueJournal of Medical Internet Research · 2024
Typereview
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsMcGill UniversityUniversity of Calgary
FundersWest China Hospital, Sichuan UniversitySichuan UniversityUniversidade de MacauChina Scholarship Council
KeywordsMedicinePhysical therapyTelehealthMeta-analysisOsteoarthritisPsychological interventionRandomized controlled trialInclusion and exclusion criteriaSubgroup analysisPhysical medicine and rehabilitationHealth careTelemedicineInternal medicineAlternative medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Osteoarthritis (OA) is a chronic musculoskeletal disease that causes pain, functional disability, and an economic burden. Nonpharmacological treatments are at the core of OA management. However, limited access to these services due to uneven regional local availability has been highlighted. Internet-based telehealth (IBTH) programs, providing digital access to abundant health care resources, offer advantages, such as convenience and cost-effectiveness. These characteristics make them promising strategies for the management of patients with OA. OBJECTIVE: This study aimed to evaluate the effectiveness of IBTH programs in the management of patients with hip or knee OA. METHODS: We systematically searched 6 electronic databases to identify trials comparing IBTH programs with conventional interventions for hip and knee OA. Studies were selected based on inclusion and exclusion criteria, focusing on outcomes related to function, pain, and self-efficacy. Standardized mean differences (SMDs) with 95% CIs were calculated to compare outcome measures. Heterogeneity was assessed using I² and χ² tests. The methodological quality of the selected studies and the quality of evidence were also evaluated. RESULTS: A total of 21 studies with low-to-high risk of bias were included in this meta-analysis. The pooled results showed that IBTH has a superior effect on increasing function (SMD 0.30, 95% CI 0.23-0.37, P<.001), relieving pain (SMD -0.27, 95% CI -0.34 to -0.19, P<.001), and improving self-efficacy for pain (SMD 0.21, 95% CI 0.08-0.34, P<.001) compared to the conventional intervention group. Subgroup analysis revealed that IBTH with exercise can significantly alleviate pain and improve function and self-efficacy, but IBTH with cognitive-behavioral therapy only had the effect of reducing pain. CONCLUSIONS: The meta-analysis provides moderate-quality evidence that IBTH programs have a beneficial effect on improving function, relieving pain, and improving self-efficacy compared to conventional interventions in patients with hip or knee OA. Limited evidence suggests that the inclusion of exercise regimens in IBTH programs is recommended. TRIAL REGISTRATION: PROSPERO CRD42024541111; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=541111.

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)0.010
metaresearch head score (Gemma)0.022
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0190.034
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
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 head0.124
GPT teacher head0.435
Teacher spread0.311 · 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

Citations24
Published2024
Admission routes1
Has abstractyes

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