MétaCan
Menu
Back to cohort
Record W3198424320 · doi:10.2196/29941

Pediatric Clinicians’ Use of Telemedicine: Qualitative Interview Study

2021· article· en· W3198424320 on OpenAlexvenueno aff
Julia B. Finkelstein, Elise Schlissel Tremblay, Melissa Van Cain, Aaron Farber-Chen, Caitlin Schumann, Christina Brown, Ankoor S. Shah, Erinn T. Rhodes

Bibliographic record

VenueJMIR Human Factors · 2021
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
FundersU.S. National Library of MedicineNational Institute of Diabetes and Digestive and Kidney DiseasesAgency for Healthcare Research and QualityNational Institutes of Health
KeywordsTelemedicineFocus groupQualitative researchMedical educationPreparednessMedicineTelehealthHealth careNursingPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Bedside manner describes how clinicians relate to patients in person. Telemedicine allows clinicians to connect virtually with patients using digital tools. Effective virtual communication or webside manner may require modifications to traditional bedside manner. OBJECTIVE: This study aims to understand the experiences of telemedicine providers with patient-to-provider virtual visits and communication with families at a single large-volume children's hospital to inform program development and training for future clinicians. METHODS: A total of 2 focus groups of pediatric clinicians (N=11) performing virtual visits before the COVID-19 pandemic, with a range of experiences and specialties, were engaged to discuss experiential, implementation, and practice-related issues. Focus groups were facilitated using a semistructured guide covering general experience, preparedness, rapport strategies, and suggestions. Sessions were digitally recorded, and the corresponding transcripts were reviewed for data analysis. The transcripts were coded based on the identified main themes and subthemes. On the basis of a higher-level analysis of these codes, the study authors generated a final set of key themes to describe the collected data. RESULTS: Theme consistency was identified across diverse participants, although individual clinician experiences were influenced by their specialties and practices. A total of 3 key themes emerged regarding the development of best practices, barriers to scalability, and establishing patient rapport. Issues and concerns related to privacy were salient across all themes. Clinicians felt that telemedicine required new skills for patient interaction, and not all were comfortable with their training. CONCLUSIONS: Telemedicine provides benefits as well as challenges to health care delivery. In interprofessional focus groups, pediatric clinicians emphasized the importance of considering safety and privacy to promote rapport and webside manner when conducting virtual visits. The inclusion of webside manner instructions within training curricula is crucial as telemedicine becomes an established modality for providing 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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.264
GPT teacher head0.506
Teacher spread0.242 · 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 teacher head, not a consensus.

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

Citations18
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Human FactorsSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207