Patients’ experiences of telenursing follow‐up care after bariatric surgery
Bibliographic record
Abstract
AIM: To explore the postsurgical management experiences of bariatric patients after receiving telenursing follow-up care, using a telemonitoring platform for approximately 1 month. BACKGROUND: Obesity prevalence rates among adult Canadians are increasing, and as such the number of bariatric surgeries. Adapting to life following bariatric surgery is challenging, and patients are often experiencing difficulties to adhere to the postsurgical behavioural recommendations. The use of technology has been introduced in bariatric aftercare programmes, yet patients voiced a desire to communicate with a clinician between routine visits to improve continuity of care. To our knowledge, there is a lack of research on emerging practice of telenursing to provide monitoring, support and aftercare to bariatric patients remotely. DESIGN: A qualitative descriptive design was used. METHODS: A total of 22 semi-structured interviews were thematically analysed. The SRQR checklist was used. RESULTS: Participants embraced the idea of integrating telenursing care in bariatric aftercare programmes, as they viewed this novel approach to care as a way to overcome the current challenges of accessing bariatric services. The most salient benefit reported by participants was the timely advice and care provided by the telenurse. The provision of tailored nursing care and the accessibility to a first-line professional empowered participants to exercise greater control over their recovery process, which promotes self-management and enhances feelings of security and reassurance. Lastly, participants voiced areas of improvement to better the system and to render it most accessible and user-friendly. CONCLUSION: Despite its novelty in bariatric aftercare, our findings indicated that patients are eager to integrate telenursing in mainstream services. Discussions are needed regarding patient adherence to telemonitoring, and the need to develop clinical follow-up protocols. RELEVANCE TO CLINICAL PRACTICE: Results provide new insights into the importance of a telenurse in providing individualised care to bariatric patients.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".