MétaCan
Menu
Back to cohort
Record W4323357039 · doi:10.9778/cmajo.20220083

Telemedicine perceptions and experiences of socially vulnerable households during the early stages of the COVID-19 pandemic: a qualitative study

2023· article· en· W4323357039 on OpenAlexaffvenueabout
Alayne M. Adams, Khandideh K.A. Williams, Jennifer C. Langill, Mylène Arsenault, Isabelle Leblanc, Kimberly Munro, Jeannie Haggerty

Bibliographic record

VenueCMAJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsMcGill UniversitySt Mary's Hospital Centre
Fundersnot available
KeywordsTelemedicineThematic analysisPandemicHealth careQualitative researchEquity (law)NursingTelehealthPerceptionExploratory researchMedicinePsychologyPublic relationsCoronavirus disease 2019 (COVID-19)Political scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Early in the COVID-19 pandemic, efforts to decrease risk of viral transmission triggered an abrupt shift from ambulatory health care delivery toward telemedicine. In this study, we explore the perceptions and experiences of telemedicine among socially vulnerable households and suggest strategies to increase equity in telemedicine access. METHODS: Conducted between August 2020 and February 2021, this exploratory qualitative study involved in-depth interviews with members of socially vulnerable households needing health care. Participants were recruited from a food bank and primary care practice in Montréal. Digitally recorded telephone interviews focused on experiences and perceptions related to telemedicine access and use. In our thematic analysis, we employed the framework method to facilitate comparison, and the identification of patterns and themes. RESULTS: Twenty-nine participants were interviewed, 48% of whom presented as women. Almost all sought health care in the early stages of the pandemic, 69% of which was received via telemedicine. Four themes emerged from the analysis: delays in seeking health care owing to competing priorities and perceptions that COVID-19-related health care took precedence; challenges with appointment booking and logistics given complex online systems, administrative inefficiencies, long wait times and missed calls; issues around quality and continuity of care; and conditional acceptance of telemedicine for certain health problems, and in exceptional circumstances. INTERPRETATION: Early in the pandemic, participants report telemedicine delivery did not accommodate the diverse needs and capacities of socially vulnerable populations. Patient education, logistical support and care delivery by a trusted provider are suggested solutions, in addition to policies supporting digital equity and quality standards to promote telemedicine access and appropriate use.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0100.007
Scholarly communication0.0030.004
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.156
GPT teacher head0.477
Teacher spread0.321 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations13
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueCMAJ OpenSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207