Predictive Factors of Physicians’ Satisfaction and Quality of Work Under Teleconsultation Conditions: Structural Equation Analysis
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic contributed to an increase in teleconsultation adoption in the Polish primary health care system. It is expected that in the long run, teleconsultations will successfully replace a significant part of face-to-face visits. Therefore, a significant challenge facing primary health care facilities (PHCs) is the acceptance of teleconsultations by their users, especially physicians. OBJECTIVE: This study aimed to explore physicians' acceptance of teleconsultations during the COVID-19 pandemic in Poland. METHODS: A representative survey was conducted among 361 physicians of PHCs across Poland in 2021. For the purposes of the study, we developed a modified Technology Acceptance Model (TAM) model. Based on the modified TAM, we analyzed the impact of perceived usefulness (PU), perceived ease of use (PEU), and intention to use teleconsultation (INT) on physicians' satisfaction (SAT) and quality of work (Q). The psychometric properties of the research instrument were examined using exploratory factor analysis. Finally, structural equation modeling was used for data analysis. RESULTS: The results indicated a generally high level of PU (mean 3.85-4.36, SD 0.87-1.18), PEU (mean 3.81-4.60, SD 0.60-1.42), INT (mean 3.87-4.22, SD 0.89-1.12), and SAT (mean 3.55-4.13, SD 0.88-1.16); the lowest rated dimension in TAM was Q (mean 3.28-3.73, SD 1.06-1.26). The most important independent variable was PU. The influence of PU on INT (estimate=0.63, critical ratio [CR]=15.84, P<.001) and of PU on SAT (estimate=0.44, CR= 9.53, P<.001) was strong. INT was also a key factor influencing SAT (estimate=0.4, CR=8.57, P<.001). A weaker relationship was noted in the effect of PEU on INT (estimate=0.17, CR=4.31, P<.001). In turn, Q was positively influenced by INT (estimate=0.179, CR=3.64, P<.001), PU (estimate=0.246, CR=4.79, P<.001), PEU (estimate=0.18, CR=4.93, P<.001), and SAT (estimate=0.357, CR=6.97, P<.001). All paths between the constructs (PU, PEU, INT, SAT, and Q) were statistically significant, which highlights the multifaceted nature of the adoption of teleconsultations among physicians. CONCLUSIONS: Our findings provide strong empirical support for the hypothesized relationships in TAM. The findings suggest that the PU and PEU of teleconsultation have a significant impact on the intention of physicians to adopt teleconsultation. This results in an improvement in the satisfaction of Polish physicians with the use of teleconsultation and an increase in Q. The study contributes to both theory and practice by identifying important prognostic factors affecting physicians' acceptance of teleconsultation systems.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".