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Record W4308057530 · doi:10.1177/01939459221134374

A Scoping Literature Review of Rural Beliefs and Attitudes toward Telehealth Utilization

2022· article· en· W4308057530 on OpenAlexaboutno aff
Kristin Pullyblank

Bibliographic record

VenueWestern Journal of Nursing Research · 2022
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsTelehealthConfidentialityVariety (cybernetics)Inclusion (mineral)NursingQualitative researchRural areaPsychologyHealth careTelemedicineMedicinePublic relationsSociologyPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

The purpose of this scoping literature review was to understand what is known about how the rural profile influences beliefs regarding telehealth utilization. Rural nursing theory (RNT) provided a framework for the review. Search criteria were limited to peer-reviewed studies conducted in Europe, the United States, Canada, Australia, and New Zealand. A variety of search terms related to patient telehealth perceptions generated 213 unique articles, of which 10 met the inclusion criteria. Included studies incorporated qualitative methodologies and were from Australia, Canada, Sweden, or the United States. The review highlighted four themes related to the rural profile's influence on telehealth beliefs: importance of familiar relationships, concerns with privacy and confidentiality, acceptance of limited access to care, and resourcefulness and frugality. These themes echo concepts within RNT. Nurses and other health professionals must acknowledge the rural profile's influence on a person's decision to use telehealth in order to provide optimal care.

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)0.017
metaresearch head score (Gemma)0.084
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.084
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0270.024
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.227
GPT teacher head0.541
Teacher spread0.314 · 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 designSystematic review
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

Citations33
Published2022
Admission routes1
Has abstractyes

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