Assessing and Preparing Patients for Hematopoietic Stem Cell Transplant in Canada: An Environmental Scan of Psychosocial Care
Bibliographic record
Abstract
Recipients and caregivers of Hematopoietic Stem Cell Transplant (HCT) have extensive physical and psychosocial needs. HCT programs recognize the need to support psychosocial wellbeing. However, evidence-based guidance for pre-HCT psychosocial services is sparse. We conducted a qualitative environmental scan of programs across Canada to better understand how programs evaluate and support patients and caregivers prior to HCT. METHODS: HCT programs across Canada were contacted with a list of questions about their psychosocial assessment and preparation process with patients and caregivers. They could respond via email or participate in an interview over the phone. Descriptive qualitative content analysis was conducted, using steps outlined by Vaismoradi and colleagues (2013). RESULTS: Most participants were social workers from hospitals (64%). Four qualitative themes arose: (a) Psychosocial Team Composition. Psychosocial assessment for HCT patients was often provided by social workers, with limited availability of psychologists and psychiatrists. (b) Criteria for assessing select HCT patients. Participants prioritized psychosocial assessments for patients with higher perceived psychosocial needs or risk, and/or according to transplant type. Limited time and high psychosocial staff demands also played into decision-making. (c) Components and Practices of Pre-HCT Psychosocial Assessment. Common components and differences of assessments were identified, as well as a lack of standardized tools. (d) Patient Education Sessions. Many sites provided adjunct patient education sessions, of varying depth. CONCLUSION: Significant variation exists in the way programs across the country assess their patients' psychosocial pre-transplant needs and assist in preparing patients for the psychosocial aspects of HCT. This environmental scan identified several strategies used in diverse ways. Further in-depth research on program outcomes across Canada could help to identify which strategies are the most successful.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 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".