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PURPOSE: Unmet social needs pose barriers to cancer care, contributing to adverse outcomes and health inequities. A better understanding of how social needs change after cancer diagnosis can inform more effective, equity-focused interventions. METHODS: In this study, we examined self-reported social needs at 0, 3, and 6 months after a breast cancer diagnosis in a racially diverse, multilingual sample (n = 222) enrolled in patient navigation intervention at an urban safety-net hospital. At each timepoint, respondents completed surveys about social needs related to employment, disability benefits, housing and utilities, and personal and family stability. RESULTS: Over three-quarters (78%, n = 175) reported ≥ 1 social need, and 46% (n = 102) reported ≥ 3 social needs. The most frequently reported need was housing and utilities (64%, n = 142), followed by employment (40%, n = 90). Individuals from minoritized groups more frequently reported an increased number of social needs over time, compared with their White counterparts (p = 0.02). CONCLUSION: Our findings suggest that despite navigation, many cancer patients from historically underrepresented populations continue to experience social concerns over the first 6 months of treatment. Further research, conducted with historically underrepresented populations in research, is needed to better understand the social needs of breast cancer patients to inform effective and equitable interventions.
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OBJECTIVE: This paper evaluates ChatGPT's accuracy and consistency in providing information on ankyloglossia, a congenital oral condition. Assessing alignment with expert consensus, the study explores potential implications for patients relying on AI for medical information. METHODS: Statements from the 2020 clinical consensus statement on ankyloglossia were presented to ChatGPT, and its responses were scored using a 9-point Likert scale. The study analyzed the mean and standard deviation of ChatGPT scores for each statement. Statistical analysis was conducted using Excel. RESULTS: Among the 63 statements assessed, 67 % of ChatGPT responses closely aligned with expert consensus mean scores. However, 17 % (11/63) were statements in which the ChatGPT mean response was different from the CCS mean by 2.0 or greater, raising concerns about ChatGPT's potential influence in disseminating uncertain or debated medical information. Variations in mean scores highlighted discrepancies, with some statements showing significant deviations from expert opinions. CONCLUSION: While ChatGPT mirrored medical viewpoints on ankyloglossia, alignment with non-consensus statements raises caution in relying on it for medical advice. Future research should refine AI models, address inaccuracies, and explore diverse user queries for safe integration into medical decision-making. Despite potential benefits, ongoing examination of ChatGPT's power and limitations is crucial, considering its impact on health equity and information access.