Acceptance, Satisfaction, and Preference With Telemedicine During the COVID-19 Pandemic in 2021-2022: Survey Among Patients With Chronic Pain
Bibliographic record
Abstract
Background The COVID-19 pandemic has forced many health care providers to make changes in their treatment, with telemedicine being expanded on a large scale. An earlier study investigated the acceptance of telephone calls but did not record satisfaction with treatment or patients’ preferences. This warranted a follow-up study to investigate acceptance, satisfaction, and preferences regarding telemedicine, comprising of phone consultations, among health care recipients. Objective The primary aim was to assess the acceptance and satisfaction of telemedicine during the subsequent months of 2021-2022, after the initial wave of the COVID-19 pandemic in Switzerland. Furthermore, we aimed to assess patients’ preferences and whether these differed in patients who had already experienced telemedicine in the past, as well as correlations between acceptance and satisfaction, pain intensity, general condition, perception of telemedicine, and catastrophizing. Finally, we aimed to investigate whether more governmental restrictions were correlated with higher acceptance. Methods An anonymous cross-sectional web-based survey was conducted between January 27, 2021, and February 4, 2022, enrolling patients undergoing outpatient pain therapy in a tertiary university clinic. We conducted a descriptive analysis of acceptance and satisfaction with telemedicine and investigated patients’ preferences. Further, we conducted a descriptive and correlational analysis of the COVID-19 stringency index. Spearman correlation analysis and a chi-square test for categorical data were used with Cramer V statistic to assess effect sizes. Results Our survey was completed by 60 patients. Telemedicine acceptance and satisfaction were high, with an average score of 7.6 (SD 3.3; on an 11-point Numeric Rating Scale from 0=not at all to 10=completely), and 8.8 (SD 1.8), respectively. Respondents generally preferred on-site consultations to telemedicine (n=35, 58% vs n=24, 40%). A subgroup analysis revealed that respondents who already had received phone consultation, showed a higher preference for telemedicine (n/N=21/42, 50% vs n/N=3/18, 17%; χ22 [N=60]=7.5, P=.02, Cramer V=0.354), as well as those who had been treated for more than 3 months (n/N=17/31, 55% vs n/N=7/29, 24%; χ22 [N=60]=6.5, P=.04, Cramer V=0.329). Acceptance of telemedicine showed a moderate positive correlation with satisfaction (rs{58}=0.41, P<.05), but there were no correlations between the COVID-19 stringency index and the other variables. Conclusions Despite high acceptance of and satisfaction with telemedicine, patients preferred on-site consultations. Preference for telemedicine was markedly higher in patients who had already received phone consultations or had been treated for longer than 3 months. This highlights the need to convey knowledge of eHealth services to patients and the value of building meaningful relationships with patients at the beginning of treatment. During the COVID-19 pandemic, the modality of patient care should be discussed individually.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".