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Record W3021141263 · doi:10.2196/15779

Effectiveness of Mobile App-Assisted Self-Care Interventions for Improving Patient Outcomes in Type 2 Diabetes and/or Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials

2020· review· en· W3021141263 on OpenAlex
Kaifeng Liu, Zhenzhen Xie, Calvin Kalun Or

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR mhealth and uhealth · 2020
Typereview
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersUniversity of Hong Kong
KeywordsMedicineRandomized controlled trialCochrane LibraryPsychological interventionMeta-analysisCINAHLType 2 diabetesBlood pressureMEDLINEPsychosocialPhysical therapyDiabetes mellitusInternal medicineNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Mobile app-assisted self-care interventions are emerging promising tools to support self-care of patients with chronic diseases such as type 2 diabetes and hypertension. The effectiveness of such interventions requires further exploration for more supporting evidence. OBJECTIVE: A systematic review and meta-analysis of randomized controlled trials (RCTs) were conducted to examine the effectiveness of mobile app-assisted self-care interventions developed for type 2 diabetes and/or hypertension in improving patient outcomes. METHODS: ) levels, systolic blood pressure (SBP), and diastolic blood pressure (DBP). Changes in other clinical-, behavioral-, knowledge-, and psychosocial-related outcomes were included as secondary outcomes. Primary outcomes and objective secondary outcomes that were reported in at least two trials were meta-analyzed; otherwise, a narrative synthesis was used for data analysis. RESULTS: levels (standardized mean difference [SMD] -0.44, 95% CI -0.59 to -0.29; P<.001), SBP (SMD -0.17, 95% CI -0.31 to -0.03, P=.02), and DBP (SMD -0.17, 95% CI -0.30 to -0.03, P=.02). Subgroup analyses for primary outcomes showed that several intervention features were supportive of self-management, including blood glucose, blood pressure, and medication monitoring, communication with health care providers, automated feedback, personalized goal setting, reminders, education materials, and data visualization. In addition, 8 objective secondary outcomes were meta-analyzed, which showed that the interventions had significant lowering effects on fasting blood glucose levels and waist circumference. A total of 42 secondary outcomes were narratively synthesized, and mixed results were found. CONCLUSIONS: Mobile app-assisted self-care interventions can be effective tools for managing blood glucose and blood pressure, likely because their use facilitates remote management of health issues and data, provision of personalized self-care recommendations, patient-care provider communication, and decision making. More studies are required to further determine which combinations of intervention features are most effective in improving the control of the diseases. Moreover, evidence regarding the effects of these interventions on the behavioral, knowledge, and psychosocial outcomes of patients is still scarce, which warrants further examination.

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.

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)0.025
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.830
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0680.005
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.193
GPT teacher head0.510
Teacher spread0.317 · 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