Engaging in patient decision-making in multidisciplinary care for amyotrophic lateral sclerosis: the views of health professionals
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to explore clinician perspectives on patient decision-making in multidisciplinary care for amyotrophic lateral sclerosis (ALS), in an attempt to identify factors influencing decision-making. METHODS: Thirty-two health professionals from two specialized multidisciplinary ALS clinics participated in individual and group interviews. Participants came from allied health, medical, and nursing backgrounds. Interviews were audio recorded, and the transcripts were analyzed thematically. RESULTS: Respondents identified barriers and facilitators to optimal timing and quality of decision-making. Barriers related to the patient and the health system. Patient barriers included difficulties accepting the diagnosis, information sources, and the patient-carer relationship. System barriers were timing of diagnosis and symptom management services, access to ALS-specific resources, and interprofessional communication. Facilitators were teamwork approaches, supported by effective communication and evidence-based information. CONCLUSION: Patient-centered and collaborative decision-making is influenced by a range of factors that inhibit the delivery of optimal care. Decision-making relies on a fine balance between timing of information and service provision, and the readiness of patients to receive them. Health system restrictions impacted on optimal timing, and patients coming to terms with their condition. Clinicians valued proactive decision-making to prepare patients and families for inevitable change. The findings indicate disparity between patient choices and clinician perceptions of evidence, knowledge, and experience. To improve multidisciplinary ALS practice, and ultimately patient care, further work is required to bridge this gap in perspectives.
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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 | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| 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".