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Record W3046744576 · doi:10.1080/14992027.2020.1795281

An examination of clinical uptake factors for remote hearing aid support: a concept mapping study with audiologists

2020· article· en· W3046744576 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Audiology · 2020
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsWestern University
Fundersnot available
KeywordsAudiologistHearing aidMedical educationSample (material)PsychologyHealth careKnowledge managementProcess managementMedicineHearing lossComputer scienceBusinessAudiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop a conceptual framework around the factors that influence audiologists in the clinical uptake of remote follow-up hearing aid support services. DESIGN: A purposive sample of 42 audiologists, stratified according to client-focus of either paediatric or adult, were recruited from professional associations in Ontario, Canada, as members of the six-step, participatory-based concept mapping process. Analyses included multidimensional scaling and hierarchical cluster analysis. RESULTS: Six main themes emerged from this research according to overall level of importance: (1) technology and infrastructure; (2) audiologist-centred considerations; (3) hearing healthcare regulations; (4) client-centred considerations; (5) clinical implementation considerations; and (6) financial considerations. Subthemes were identified at the group-level and by subgroup. These highlight the importance of TECH factors (accessible Technology, Easy to use, robust Connection, and Help available), as well as the multi-faceted nature of the perceived attitudes/aptitudes across stakeholders. CONCLUSION: Findings can be utilised in tailored planning and development efforts to support future research, knowledge dissemination, best-practice protocol/guideline development, and related training to assist in the clinical uptake of remote follow-up hearing aid support services, across variable practice contexts.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.174
GPT teacher head0.414
Teacher spread0.240 · 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