Accurate, timely information can be a powerful tool to mitigate harmful effects of air pollution. While national guidelines for environmental risk communication – based on risk and crisis communication principles – exist, little is known how these are operationalized, nor about the effectiveness of existing communication efforts. Moreover, a growing literature on environmental health literacy suggests that communication about environmental risks must move beyond individual behavior education to empower communities to mobilize to reduce environmental threats. This study aimed to identify and critically evaluate public sources of information about the causes and controllability of air pollution and its health effects, and potential disparities in information reach and utility. The case study triangulated data from three sources: Systematic analysis of the public information environment, interviews with regional expert stakeholders, and interviews with community residents. Three themes emerged: 1) Lack of clarity about responsibility for communicating about air quality (information sources), 2) Existing air quality communication strategies lack critical information including risk mitigation behaviors and long-term health impacts (information quality), and 3) Existing air quality communications fail to reach vulnerable populations (information reach). This study demonstrates that air quality communication is lacking yet crucially needed. Information about air pollution and health risks focuses on individual risk behaviors but is disseminated using channels that are unlikely to reach the most vulnerable populations. We discuss opportunities to improve the reach and impact of communication of air quality health risks, an increasingly important global priority, situating our argument within a critical environmental health literacy perspective.

The San Joaquin Valley of California has poor air quality and high rates of asthma. Surveys were collected from 744 residents of the San Joaquin Valley from November 2014 to January 2015 to examine the public’s views about air quality. The results of this study suggest that participants exposed to high PM_2.5 (particulate matter less than 2.5 microns in size) concentrations perceived air pollution to be of the worst quality. Air quality in the San Joaquin Valley was primarily perceived as either moderate or unhealthy for sensitive groups. Females perceived air pollution to be of worse quality compared to males. Participants perceived unemployment, crime, and obesity to be the top three most serious community problems in the San Joaquin Valley. Participants viewed cars and trucks, windblown dust, and factories as the principle contributors to air pollution in the area. There is a need to continue studying public perceptions of air quality in the San Joaquin Valley with a more robust survey with more participants over several years and seasons.

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.

Patients report persisting impairment in quality of life (QoL) after treatment for pituitary disease. At present, there is no questionnaire to assess (a) whether patients with pituitary disease are bothered by these consequences, and (b) their needs for support.