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Record W4380081708 · doi:10.2196/45384

Acceptance of Telemedicine Compared to In-Person Consultation From the Providers' and Users’ Perspectives: Multicenter, Cross-Sectional Study in Dermatology

2023· article· en· W4380081708 on OpenAlexvenueno aff
Lara Valeska Maul, Anna Sophie Jahn, Gustavo Santo Pedro Pamplona, Markus Streit, Lorena Gantenbein, Simon Müller, Mia‐Louise Nielsen, Christian Greis, Alexander A. Navarini, Julia‐Tatjana Maul

Bibliographic record

VenueJMIR Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsnot available
FundersFreiwillige Akademische GesellschaftUniversität Basel
KeywordsTeledermatologyTelemedicineMedicineReferralCross-sectional studyFamily medicineHealth careDemographicsPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Teledermatology is currently finding its place in modern health care worldwide as a rapidly evolving field. OBJECTIVE: The aim of this study was to investigate the acceptance of teledermatology compared to in-person consultation from the perspective of patients and professionals. METHODS: This multicenter, cross-sectional pilot study was performed at secondary and tertiary referral centers of dermatology in Switzerland from August 2019 to January 2020. A customized questionnaire addressing demographics and educational data, experience with telemedicine, and presumed willingness to replace in-patient consultations with teledermatology was completed by dermatological patients, dermatologists, and health care workers in dermatology. RESULTS: Among a total of 664 participants, the ones with previous telemedicine experience (171/664, 25.8%) indicated a high level of overall experience with it (patients: 73/106, 68.9%, dermatologists: 6/8, 75.0%, and health care workers: 27/34, 79.4%). Patients, dermatologists, and health care workers were most likely willing to replace in-person consultations with teledermatology for minor health issues (353/512, 68.9%; 37/45, 82.2%; and 89/107, 83.2%, respectively). We observed a higher preference for telemedicine among individuals who have already used telemedicine (patients: P<.001, dermatologists: P=.03, and health care workers, P=.005), as well as among patients with higher educational levels (P=.003). CONCLUSIONS: This study indicates that the preference for teledermatology has a high potential to increase over time since previous experience with telemedicine and a higher level of education were associated with a higher willingness to replace in-patient consultations with telemedicine. We assume that minor skin problems are the most promising issue in teledermatology. Our findings emphasize the need for dermatologists to be actively involved in the transition to teledermatology. TRIAL REGISTRATION: ClinicalTrials.gov NCT04495036; https://classic.clinicaltrials.gov/ct2/show/NCT04495036.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.032
GPT teacher head0.340
Teacher spread0.308 · 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 designObservational
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

Citations14
Published2023
Admission routes1
Has abstractyes

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