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Record W2010561441 · doi:10.1089/tmj.2005.11.137

The Essence of Telehealth Readiness in Rural Communities: An Organizational Perspective

2005· article· en· W2010561441 on OpenAlexafffundabout
Penny Jennett, Andora Jackson, Kendall Ho, Theresa Healy, Arminée Kazanjian, Robert Woollard, Susan Haydt, Joanna Bates

Bibliographic record

VenueTelemedicine Journal and e-Health · 2005
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of British ColumbiaUniversity of Northern British ColumbiaUniversity of Calgary
FundersHealth Canada
KeywordsTelehealthPerspective (graphical)Knowledge managementPublic relationsQualitative researchPsychologyBusinessNursingHealth careTelemedicineSociologyMedicinePolitical scienceComputer science

Abstract

fetched live from OpenAlex

This paper examines telehealth readiness from an organizational perspective and explores the essence of telehealth readiness among four domains, namely, patients, practitioners, the public, and organizations in rural Canadian communities. Because readiness is a necessary requirement for the successful implementation of an innovation, it is important to identify and ensure core factors of readiness before costly investments are made. The findings presented here derive from a qualitative phenomenological research approach involving semistructured telephone interviews with four key informants (respondents). The data identified four categories of readiness in an organizational setting: core readiness, engagement, structural readiness, and nonreadiness. Understanding organizational readiness within rural and remote communities is an important step for the successful implementation of telehealth services into existing systems of health 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)0.002
metaresearch head score (Gemma)0.004
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 score0.159
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.009
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.381
Teacher spread0.347 · 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

Citations64
Published2005
Admission routes3
Has abstractyes

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