Usability and Usefulness of Occupational Health Care Patient Portals: Patient-Based Cross-Sectional Study
Bibliographic record
Abstract
Background: Patient portals are a crucial part of modern health care services, as they provide patients with access to their personal information and enable communication with health care professionals. The usability and usefulness of these portals are decisive factors in their adoption. There is a lack of previous research on the use of patient portals in occupational health care (OHC). Objective: This study aims to examine patients' experiences with the usability and usefulness of OHC patient portals and to identify the factors that influence their perceived usability and usefulness. Methods: A cross-sectional study was conducted through a web-based survey in April 2024 in Finland. Of the 3072 respondents, usability was assessed using 12 statements, and usefulness was evaluated with 9 statements. Responses were collected on a 5-point Likert scale. The survey also gathered respondents' background information, including age, gender, education, information and communication technology (ICT) skills, satisfaction, frequency of use, and data privacy concerns. Data analysis was performed using SPSS Statistics (version 29; IBM Corp), applying frequency analysis and a general linear model. Results: The results showed that 75.1% (1895/2523) of respondents agreed that the portal was easy to learn and use, 70.5% (1774/2517) felt it supported collaboration with OHC, while 52.4% (1316/2511) reported that it provided a good overview of their work ability, and 35.5% (891/2505) felt it offered a good overview of their working conditions. The perceived usability of OHC patient portals was significantly associated with several factors in the adjusted model: fear of unauthorized access to data (F4=4.49, P=.001, η²=0.007), need for guidance (F4=52.2, P<.001, η²=0.080), frequency of use (F1=34.3, P<.001, η²=0.014), satisfaction with the portal (F1=577.1, P<.001, η²=0.193), perceived ICT skills (F1=12.2, P<.001, η²=0.005), and age (F1=10.8, P<.001, η²=0.004), with younger users (≤50 years) reporting better usability. Perceived usefulness was significantly influenced by frequency of use (F1=9.80, P=.002, η²=0.004) and satisfaction (F1=548.0, P<.001, η²=0.183), while other factors such as fear of unauthorized access (F4=0.41, P=.80), need for guidance (F4=1.52, P=.20), ICT skills, education, gender, and age were not statistically significant. Conclusions: OHC patient portals must enhance their capacity to provide information on work ability and working conditions. Improved documentation of work-related hazards, risks, and workload factors in medical records is needed. These enhancements could raise patient awareness of work well-being factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".