A scoping review and intersectionality‐based analysis of heart failure telehealth interventions for vulnerable populations
Bibliographic record
Abstract
AIMS: To map the existing body of heart failure (HF) telehealth interventions for vulnerable populations, and to conduct an intersectionality-based analysis utilizing a structured checklist. DESIGN: A scoping review and intersectionality-based analysis. DATA SOURCES: The search was conducted in March 2022 in the following databases: MEDLINE, CINAHL, Scopus and the Cochrane Central Register of Controlled Trials, ProQuest Dissertations and Theses Global. REVIEW METHODS: First, the titles and abstracts were screened, and then the entire articles were screened against the inclusion criteria. Two of the investigators screened the articles independently in Covidence. The studies included and excluded at various stages of screening were depicted through a PRISMA flow diagram. The quality of the included studies was assessed based on the mixed methods appraisal tool (MMAT). Each study was read thoroughly and the intersectionality-based checklist by Ghasemi et al. (2021) was applied, whereby a yes/no response was marked for each question on the checklist and the relevant supporting data were extracted. RESULTS: A total of 22 studies were included in this review. About 42.2% of the responses indicated that studies incorporated the principles of intersectionality at the 'problem identification' stage, followed by 42.9% and 29.44% responses indicating incorporation of these principles at the 'design and implementation' and 'evaluation' stages respectively. CONCLUSIONS: The findings suggest that the research around HF telehealth interventions for vulnerable populations is not adequately grounded in appropriate theoretical underpinning. The principles of intersectionality have been applied mostly to the problem identification and the intervention development and implementation stages, and not so much at the evaluation stage. Future research must fill the identified gaps in this area of research. NO PATIENT OR PUBLIC CONTRIBUTION: Since this was a scoping, there was no patient contribution to this work; however, based on this study's findings, we are undertaking patient-centred studies with patient contribution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.118 | 0.279 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.016 |
| Bibliometrics | 0.090 | 0.060 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".