Do patient and clinician goals align in a prehabilitation setting? A mixed methods study
Bibliographic record
Abstract
Background.Engaging patients in healthcare can empower them to take an active role in their treatment, improve their understanding of medical decisions, and foster better communication with healthcare providers, ultimately improving treatment adherence, outcomes, and satisfaction.To enhance patient engagement in an Enhanced Recovery After Surgery setting, at the PeriOperative Program (POP) prehabilitation clinic, we co-developed (with patients) a handout that invited patients to outline their preoperative goals and its significance.We explored the following research questions: (1) What are the goals of patients receiving prehabilitation?(2) How well do these goals align with the surgeons' reasons for referral to prehabilitation? ( 3) To what extent does goal alignment influence attainment of surgeons' referral aim. Methods.Using a mixed methods sequential exploratory design, all engagement handouts from September 2021-2023 were evaluated without exclusion.Qualitative responses were transcribed verbatim, and quantitative data on the alignment of patient goals with clinician referrals were collected.Quantitative data on the proportion of patient goals that were completely, partially, or misaligned with surgeon referral were collected concurrently.Qualitative data were analyzed with summative content analysis (NVivo).Quantitative data were analyzed descriptively. Results.A total of 191 patient handouts were reviewed.Surgical indications were lung (38%, n=72) and gastrointestinal diseases (26%, n=49), hernia (19%, n=37), and orthopedic/spinal procedures (17%, n=33).The goal section of the handout was completed by 178 patients and the most frequently reported goals included improving physical health (27%, n=86), simply feeling prepared for surgery (18%, n=56), and improving nutrition (15%, n=49).Rationale for these goals included personal well-being (39%, n=93), to recover well from surgery (20%, n=47), and the well-being of others such as family and friends (15%, n=36).Complete data for alignment were available for 167 patients.Forty-nine percent of patient goals (n=81) partially aligned with their surgeon's referral, 32% (n=55) fully aligned, and 19% (n=31) did not align (P<0.001).Of the goals that did not align with referrals, smoking cessation and weight loss were the most mismatched.When surgeon and patient goals completely aligned, 85% (n=47) of patients met the referral aim, compared to only 16% (n=5) when goals were misaligned (P<0.001). Conclusion.The top patient goals in a prehabilitation program were to improve physical health, feel prepared for surgery, and enhance nutrition, but only a third of these goals completely aligned with clinician referrals.Patients whose goals aligned with their surgeon's showed significantly higher prehabilitation success compared with patients whose goals did not align.Future research should explore ways to better align clinician goals with patient priorities.
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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 | 0.067 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".