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Record W2165119358 · doi:10.2196/jmir.3138

Medical Students and Personal Smartphones in the Clinical Environment: The Impact on Confidentiality of Personal Health Information and Professionalism

2014· article· en· W2165119358 on OpenAlexaffabout
Kim Tran, Dante Morra, Vivian Lo, Sherman Quan, Howard Abrams, Robert Wu

Bibliographic record

VenueJournal of Medical Internet Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsTrillium Health CentreUniversity Health Network
Fundersnot available
KeywordsConfidentialityMobile phonePhonePersonally identifiable informationInternet privacyPersonal careHealth careMedicinePsychologyApplied psychologyFamily medicineComputer scienceComputer security

Abstract

fetched live from OpenAlex

BACKGROUND: Smartphones are becoming ubiquitous in health care settings. The increased adoption of mobile technology such as smartphones may be attributed to their use as a point-of-care information source and to perceived improvements in clinical communication and efficiency. However, little is known about medical students' use of personal smartphones for clinical work. OBJECTIVE: The intent of the study was to examine final-year medical students' experience with and attitudes toward using personal mobile technology in the clinical environment, with respect to the perceived impact on patient confidentiality and provider professionalism. METHODS: Cross-sectional surveys were completed by final-year medical students at the University of Toronto. Respondents were asked about the type of personal mobile phone they use, security features on their personal phone, experiences using their personal phone during clinical rotations, and attitudes about using their personal phone for clinical work purposes. RESULTS: The overall response rate was 45.4% (99/218). Smartphone ownership was prevalent (98%, 97/99) with the majority (86%, 85/99) of participants using their personal phones for patient-related communication during clinical rotations. A total of 26% (26/99) of participants reported not having any type of security feature on their personal phone, 94% (90/96) of participants agreed that using their personal phone for clinical work makes them more efficient, and 86% (82/95) agreed that their personal phone allows them to provide better patient care. Although 68% (65/95) of participants believe that the use of personal phones for patient-related communication with colleagues poses a risk to the privacy and confidentiality of patient health information, 22% (21/96) of participants still use their personal phone to text or email identifiable patient data to colleagues. CONCLUSIONS: Our findings suggest that the use of personal smartphones for clinical work by medical students is prevalent. There is a need to more fully address the threat to patient confidentiality posed by the use of unsecured communication devices such as smartphones.

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)0.086
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient 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 score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0860.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.005
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 head0.177
GPT teacher head0.605
Teacher spread0.429 · 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

Citations85
Published2014
Admission routes2
Has abstractyes

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