Factors Associated with Meeting the Psychosocial Needs of Cancer Survivors in Nova Scotia, Canada
Bibliographic record
Abstract
Purpose: The purpose of this study is to describe the psychosocial needs of cancer survivors and examine whether sociodemographic factors and health care providers accessed are associated with needs being met. Methods: All Nova Scotia survivors meeting specific inclusion and exclusion criteria are identified from the Nova Scotia Cancer Registry and sent an 83-item survey to assess psychosocial concerns and whether and how their needs were met. Descriptive statistics (frequencies, percentages) and Chi-square analyses are used to examine associations between sociodemographic and provider factors and outcomes. Results: Anxiety and fear of recurrence, depression, and changes in sexual intimacy are major areas of concern for survivors. Various sociodemographic factors, such as immigration status, education, employment, and internet use, are associated with reported psychosocial health and having one’s needs met. Having both a specialist and primary care provider in charge of follow-up care is associated with a significantly (p < 0.05) higher degree of psychosocial and informational needs met compared to only one physician or no follow-up physician in charge. Accessing a patient navigator also is significantly associated with a higher degree of needs met. Conclusions: Our study identifies the most prevalent psychosocial needs of cancer survivors and the factors associated with having a higher degree of needs met, including certain sociodemographic factors, follow-up care by both a primary care practitioner and specialist, and accessing a patient navigator.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".