Capturing Community Perspectives in a Statewide Cancer Needs Assessment: Online Focus Group Study
Bibliographic record
Abstract
BACKGROUND: Kentucky has the highest all-site cancer incidence and mortality rates in the United States. Conducting needs assessments in a large geographic area, such as an entire state, poses challenges in collecting qualitative data from diverse rural and urban contexts. In 2021, a steering committee was formed to drive a multimethod, statewide cancer needs assessment (CNA) to identify the future priorities for all cancer-related care in Kentucky. OBJECTIVE: We aimed to report on the online focus group component of the CNA by documenting existing community resources and perceived needs across the cancer care continuum. In addition, we aimed to explore the impacts of social determinants of health among populations experiencing health disparities. METHODS: Through existing partnerships and a national research registry, we recruited adult Kentucky residents who were not employed in health occupations to participate in 11 online 60-minute focus groups, stratified to include multiple target populations and geographic areas. We based our semistructured discussion guide on the cancer care continuum and focused on social determinants of health, health equity, and factors affecting cancer diagnoses and outcomes. We conducted a qualitative line-by-line analysis of the recorded transcripts to identify themes. RESULTS: The participants (N=51; mean 4.63, SD 2.26 per group) lived in 25 different counties, including 35% (18/51) from rural communities, 14% (7/51) from the Appalachian area of Kentucky, and 31% (16/51) who self-identified with a racial or ethnic minority group. We identified 17 primary themes representing community-perceived needs and potential solutions across the cancer care continuum, including novel approaches to make information accessible; messaging not interpreted as blaming or shaming; messaging from individuals who engender trust; screening efforts to reach individuals where they are; ways to address practical barriers to screening and treatment, such as cost and transportation; and ways to increase knowledge about insurance coverage. In addition, we found 83 emergent subthemes specific to race, ethnicity, rural and urban residence, sexual orientation and gender identity, and age. The participants described the need to promote positive, culturally sensitive patient-health care provider communication and to create safe care spaces that consider the ways in which social norms affect cancer care, fight stigma, and improve health equity. CONCLUSIONS: By conducting statewide qualitative data collection online, we provided valuable depth of understanding for future programs and research to address cancer incidence and mortality in Kentucky. The findings pointed to several potential actions to address community-perceived needs across the cancer care continuum, including increasing accessible risk reduction information, expanding ways to overcome challenges to screening and treatment, building patient navigation resources, and increasing positive patient-health care provider communication. The findings also suggest that online focus groups can be a valuable component of CNAs to capture cancer-related needs and solutions across large geographic areas and diverse populations.
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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 | 0.019 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".