Usability Factors Associated With Physicians’ Distress and Information System–Related Stress: Cross-Sectional Survey
Bibliographic record
Abstract
BACKGROUND: Constantly changing and difficult-to-use information systems have arisen as a significant source of stress in physicians' work. Physicians have reported several usability problems, system failures, and a lack of integration between the systems and have experienced that systems poorly support the documentation and retrieval of patient data. This stress has kept rising in the 21st century, and it seems that it may also affect physicians' well-being. OBJECTIVE: This study aimed to examine the associations of (1) usability variables (perceived benefits, technical problems, support for feedback, and user-friendliness), (2) the number of systems in daily use, (3) experience of using information systems, and (4) participation in information systems development work with physicians' distress and levels of stress related to information systems (SRIS) levels. METHODS: A cross-sectional survey was conducted among 4018 Finnish physicians (64.82%, 2572 out of 3968 women) aged between 24 and 64 years (mean 46.8 years) in 2017. The analyses of covariance were used to examine the association of independent variables with SRIS and distress (using the General Health Questionnaire) adjusted for age, gender, employment sector, specialization status, and the electronic health record system in use. RESULTS: High levels of technical problems and a high number of systems in daily use were associated with high levels of SRIS, whereas high levels of user-friendliness, perceived benefits, and support for feedback were associated with low levels of SRIS. Moreover, high levels of technical problems were associated with high levels of psychological distress, whereas high levels of user-friendliness were associated with low distress levels. Those who considered themselves experienced users of information systems had low levels of both SRIS and distress. CONCLUSIONS: It seems that by investing in user-friendly systems with better technical quality and good support for feedback that professionals perceive as being beneficial would improve the work-related well-being and overall well-being of physicians. Moreover, improving physicians' skills related to information systems by giving them training could help to lessen the stress that results from poorly functioning information systems and improve physicians' well-being.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".