Health Information Seeking From an Intelligent Web-Based Symptom Checker: Cross-sectional Questionnaire Study.

BACKGROUND: The ever-growing amount of health information available on the web is increasing the demand for tools providing personalized and actionable health information. Such tools include symptom checkers that provide users with a potential diagnosis after responding to a set of probes about their symptoms. Although the potential for their utility is great, little is known about such tools' actual use and effects. OBJECTIVE: We aimed to understand who uses a web-based artificial intelligence-powered symptom checker and its purposes, how they evaluate the experience of the web-based interview and quality of the information, what they intend to do with the recommendation, and predictors of future use. METHODS: Cross-sectional survey of web-based health information seekers following the completion of a symptom checker visit (N=2437). Measures of comprehensibility, confidence, usefulness, health-related anxiety, empowerment, and intention to use in the future were assessed. ANOVAs and the Wilcoxon rank sum test examined mean outcome differences in racial, ethnic, and sex groups. The relationship between perceptions of the symptom checker and intention to follow recommended actions was assessed using multilevel logistic regression. RESULTS: Buoy users were well-educated (1384/1704, 81.22% college or higher), primarily White (1227/1693, 72.47%), and female (2069/2437, 84.89%). Most had insurance (1449/1630, 88.89%), a regular health care provider (1307/1709, 76.48%), and reported good health (1000/1703, 58.72%). Three types of symptoms-pain (855/2437, 35.08%), gynecological issues (293/2437, 12.02%), and masses or lumps (204/2437, 8.37%)-accounted for almost half (1352/2437, 55.48%) of site visits. Buoy's top three primary recommendations split across less-serious triage categories: primary care physician in 2 weeks (754/2141, 35.22%), self-treatment (452/2141, 21.11%), and primary care in 1 to 2 days (373/2141, 17.42%). Common diagnoses were musculoskeletal (303/2437, 12.43%), gynecological (304/2437, 12.47%) and skin conditions (297/2437, 12.19%), and infectious diseases (300/2437, 12.31%). Users generally reported high confidence in Buoy, found it useful and easy to understand, and said that Buoy made them feel less anxious and more empowered to seek medical help. Users for whom Buoy recommended "Waiting/Watching" or "Self-Treatment" had strongest intentions to comply, whereas those advised to seek primary care had weaker intentions. Compared with White users, Latino and Black users had significantly more confidence in Buoy (P<.05), and the former also found it significantly more useful (P<.05). Latino (odds ratio 1.96, 95% CI 1.22-3.25) and Black (odds ratio 2.37, 95% CI 1.57-3.66) users also had stronger intentions to discuss recommendations with a provider than White users. CONCLUSIONS: Results demonstrate the potential utility of a web-based health information tool to empower people to seek care and reduce health-related anxiety. However, despite encouraging results suggesting the tool may fulfill unmet health information needs among women and Black and Latino adults, analyses of the user base illustrate persistent second-level digital divide effects.

Beyond fatalism: Information overload as a mechanism to understand health disparities.

BACKGROUND: Fatalism - beliefs about the causes and controllability of disease - has been negatively associated with prevention behaviors. Fatalism has been suggested as a mechanism for health disparities because ethnic minorities are especially likely to hold fatalistic beliefs. However, the construct has been criticized: Fatalism fails to account for structural barriers to health faced by vulnerable populations that also score highly on measures of fatalism. Another critique suggests that operationalizations of fatalism expose communication failures: "Fatalism" rather reflects information overload from an environment riddled with misinformation and contradictions. This study aimed to expand understanding of one mechanism through which communication may contribute to disparities by considering the context of nutrition among bicultural Latinas, who face increased risk from dietary acculturation. METHOD: Mixed-methods (semi-structured in-depth interview, survey) with Mexican-American women ages 18-29 (n = 24) in rural California. RESULTS: Contrary to previous studies, the majority of this sample of Mexican-American women did not endorse fatalistic beliefs; most demonstrated clear understanding of the link between diet and risk of diseases: Diabetes and heart disease were understood to result from behaviors within one's control. Yet despite articulating links between diet and disease, participants felt overloaded and confused about conflicting information from public and interpersonal sources. Moreover, despite reporting feeling inundated with information, participants noted critical information gaps, distinguishing between information available and information needed. CONCLUSIONS: We found minimal support for fatalistic beliefs among a sample of Mexican-American women, but considerable information overload and confusion, together with a desire for specific knowledge and skills. Results extend understanding of how communication may influence disparities: Information overload may be conflated with fatalism, challenging the notion that fatalism is a cultural belief. Moreover, inequalities in access to and ability to process information compound overload effects. We discuss opportunities to improve the clarity of communication about nutrition science and dietary recommendations.