Examining the development of information needs assessment tools for use in the cancer context: A scoping and critical review
Bibliographic record
Abstract
Abstract Background Information needs are one of the most common unmet supportive care needs of those living with cancer. Little is known about how existing tools for assessing information needs in the cancer context have been created or the role those with lived cancer experience played in their development. Objectives This review aimed to characterize the development and intended use of existing cancer specific information needs assessment tools. Methods A systematic scoping review was conducted using a peer-reviewed protocol informed by recommendations from the Joanna Briggs Institute and the Prefered Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Results Twenty-one information needs assessment tools were included. Most tools were either breast cancer ( n = 8) or primary tumor nonspecific ( n = 8). Patients and informal carers participated in initial identification of questionnaire items in the minority of cases ( n = 6) and were more commonly involved in reviewing the final questionnaire before use or formal psychometric testing ( n = 9). Most questionnaires were not assessed for validity or reliability using rigorous quantitative psychometric testing. Significance of results Existing tools are generally not designed to provide a rigorous assessment of informational needs related to a specific cancer challenge and are limited in how they have been informed by those with lived cancer experience. Tools are needed that both rigirously address information needs for specific cancer challenges and that have been developed in partnership with those who have experienced cancer. Future directions should include understanding barriers and facilitators to developing such tools.
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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 | 0.324 | 0.590 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.045 | 0.035 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".