Enhancing access to sustainable cancer supportive modalities: the roles of interactive health communication and trained volunteers
Bibliographic record
Abstract
Abstract Background: Addressing the unmet needs of individuals with cancer in a timely manner is imperative for true implementation of person-centered care. Interactive health communication (ie, people's interactions with health information technologies) and more sustainable forms of support (eg, trained volunteers), are increasingly recognized as promising means to address the many barriers to accessing cancer-related support. This pilot study is timely as it tested an accessible cancer supportive approach that included e-handouts on 25 cancer distress-related topics and supportive phone calls by trained volunteers. The study objectives were to document participants’ preferences for the types of support offered, assess changes in distress pre and post, and determine the usability of the approach. Methods: Individuals with various types and stages of cancer (N = 88), diagnosed within the past 6 months were recruited from a university-affiliated cancer center in Montreal, Quebec, Canada. Participants completed the Cancer Support Community Distress measure at baseline, and they were prompted to request different types of support. Participants completed a follow-up questionnaire including the distress measure one to four weeks post support provision. Results: Of the 88 participants who filled out baseline questionnaires, 68 completed the follow up measures. Of the former, 76% (n = 67) made at least one request (e-handouts/phone calls/or both). The most frequently requested e-handout addressed pain/physical discomfort (37 requests) and phone calls were requested mostly for sleep problems (8 requests). Participants who requested both support modalities reported significantly lower distress [F (3,64) = 3.52, P = .02] at follow-up compared to those who made no requests. Ninety-two percent of participants who requested e-handouts reported that other patients would benefit from these. Participants who requested phone calls agreed or strongly agreed that volunteers were knowledgeable. The usability score was excellent (mean = 85.5/100; SD = 16.36). Conclusion: Preliminary findings indicate that this supportive approach is promising. Future work would document the differential contributions of supportive modalities that compare, for instance, professional versus lay (trained) support.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".