Moving Forward With Telehealth in Cancer Rehabilitation: Patient Perspectives From a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic accelerated the use of telehealth in cancer care and highlighted the potential of telehealth as a means of delivering the much-needed rehabilitation services for patients living with the side effects of cancer and its treatments. OBJECTIVE: This mixed methods study aims to explore patients' experiences of telehealth and their preferences regarding the use of telehealth for cancer rehabilitation to inform service development. METHODS: The study was completed in 2 phases from October 2020 to November 2021. In phase 1, an anonymous survey (web- and paper-based) exploring the need, benefits, barriers, facilitators, and preferences for telehealth cancer rehabilitation was distributed to survivors of cancer in Ireland. In phase 2, survivors of cancer were invited to participate in semistructured interviews exploring their experiences of telehealth and its role in cancer rehabilitation. Interviews were conducted via telephone or video call following an interview guide informed by the results of the survey and transcribed verbatim, and reflexive thematic analysis was performed using a qualitative descriptive approach. RESULTS: A total of 48 valid responses were received. The respondents were at a median of 26 (range 3-256) months after diagnosis, and 23 (48%) of the 48 participants had completed treatment. Of the 48 respondents, 31 (65%) reported using telehealth since the start of the pandemic, 15 (31%) reported having experience with web-based cancer rehabilitation, and 43 (90%) reported a willingness for web-based cancer rehabilitation. A total of 26 (54%) of the 48 respondents reported that their views on telehealth had changed positively since the start of the pandemic. Semistructured interviews were held with 18 survivors of cancer. The mean age of the participants was 58.9 (SD 8.24) years, 56% (10/18) of the participants were female, and 44% (8/18) of the participants were male. Reflexive thematic analysis identified 5 key themes: telehealth improves accessibility to cancer rehabilitation for some but is a barrier for others, lived experiences of the benefits of telehealth in survivorship, the value of in-person health care, telehealth in cancer care and COVID-19 (from novelty to normality), and the future of telehealth in cancer rehabilitation. CONCLUSIONS: Telehealth is broadly welcomed as a mode of cancer rehabilitation for patients living with and beyond cancer in Ireland. However, issues regarding accessibility and the importance of in-person care must be acknowledged. Factors of convenience, time savings, and cost savings indicate that telehealth interventions are a desirable patient-centered method of delivering care when performed in suitable clinical contexts and with appropriate populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".