Factors Explaining the Use of Web-Based Consultations With Physicians by Young and Middle-Aged Individuals in China: Qualitative Comparative Analysis
Bibliographic record
Abstract
BACKGROUND: It was only upon the occurrence of the COVID-19 pandemic that the demand for web-based consultations with physicians grew at unprecedented rates. To meet the demand, the service environment developed rapidly during the pandemic. OBJECTIVE: This study aimed to identify the current status of the use of web-based consultations with physicians among young and middle-aged Chinese individuals and explore users' perspectives on key factors that influence its use in terms of optimizing benefits and compensating for disadvantages. METHODS: We conducted semistructured interviews with 65 individuals (aged 18 to 60 years) across China between September and October 2022. The interviewees were selected through snowball sampling. They described their experiences of using web-based physician consultations and the reasons for using or not using the service. Based on the Andersen Behavioral Model, a qualitative comparative analysis was used to analyze the factors associated with the use of web-based physician consultations and explore the combinations of these factors. RESULTS: In all, 31 (48%) of the 65 interviewees used web-based consultation services. The singular necessary condition analysis revealed that the complementary role of the service and perceived convenience are necessary conditions for the use of web-based consultation services, and user's confidence in the service was a sufficient condition. Based on the Andersen Behavioral Model, the configuration analysis uncovered 2 interpretation models: an enabling-oriented model and a need-oriented model. The basic combination of the enabling-oriented model included income and perceived convenience. The basic combination of the need-oriented model included complementary role and user's confidence. CONCLUSIONS: Among the factors associated with the use of web-based consultations, perceived convenience, complementary role, and user's confidence were essential factors. Clear instructions on the conduct of the service, cost regulations, provider qualifications guarantee, privacy and safety supervision, the consultations' application in chronic disease management settings, and subsequent visits can promote the positive development of web-based consultations.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".