Understanding bariatric patients' experiences of <scp>self‐management post‐surgery</scp>: A qualitative study
Bibliographic record
Abstract
Although most bariatric patients achieve significant weight loss and improvements in both physical and mental health-related quality of life (HRQoL) in the short-term, there is wide variability in weight and long-term HRQoL outcomes. The role of bariatric patients' self-management style in explaining variability in long-term outcomes is unclear. This qualitative study examined bariatric patients' self-management experiences after bariatric surgery in relation to long-term outcomes. A qualitative study was conducted using semi-structured individual interviews with post-surgery patients (n = 23) at a Canadian bariatric surgery program. A constant comparative approach was used to systematically analyse the data and identify overarching themes. Variation in patients' experiences and follow-up time were the two primary units of analysis. Patients were predominantly female (n = 19; 82.6%) and had a mean age of 50 ± 8.49 years. The median time post-surgery was 2 years (range: 6 months-7 years). Three distinct phases described the process of self-management post-bariatric surgery: (1) rediscovering self-esteem and confidence in one's ability to self-manage (1-month to 1.5-years post-surgery), (2) achieving weight maintenance and addressing emotion dysregulation (1.5-3-years post-surgery) and (3) embracing a flexible balanced lifestyle (beyond 3-years). Bariatric surgery patients experience distinct challenges relative to their post-surgery time course. Facilitating access to interprofessional bariatric care after surgery allowed patients to acquire the self-management knowledge and skills necessary to address challenges to following the bariatric guidelines in the long-term.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".