Lifestyle Modification Experiences of African American Breast Cancer Survivors: A Needs Assessment
Bibliographic record
Abstract
BACKGROUND: Little is known about the rates of obesity among African American (AA) breast cancer survivors (BCSs), the availability and use of lifestyle modification methods suitable for this population, and the impact of changes in dietary intake and physical activity on health-related quality of life (HR-QoL). OBJECTIVE: The objectives of the study were to describe obesity rates, dietary intake, and physical activity as lifestyle modification strategies; examine predictors of engagement in these strategies post diagnosis; and learn more about salient features of lifestyle interventions from AA BCSs participating in a breast cancer support group. METHODS: The needs assessment included four components: (1) a literature review to determine existing lifestyle modification strategies of AA BCSs; (2) secondary data analysis of the 2010 National Health Interview Survey, Cancer Control Supplement to examine HR-QoL; (3) administration, to 200 AA BCSs, of an assessment tool relating to weight and breast cancer history, dietary intake, and physical activity through a variety of approaches (eg, Internet, mail, in-person, and telephone); and (4) focus group discussions to frame lifestyle interventions. RESULTS: Preliminary findings indicate that AA BCSs are underrepresented in lifestyle intervention research, have disparities in HR-QoL outcomes, do not meet current cancer prevention guidelines, and have recommendations for effective strategies for lifestyle modification. CONCLUSIONS: As analyses of the needs assessment are completed, the research team is partnering with community coalitions and breast cancer support groups in Miami, Chicago, Houston, Los Angeles, and Philadelphia to develop community-engaged intervention approaches for promoting adherence to cancer prevention guidelines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".