The ability to categorize information is essential to everyday tasks such as identifying the cause of an event given a set of likely explanations or pinpointing the correct from a set of possible diagnoses by sequentially probing questions. In three studies, we investigated how the level of inclusiveness at which objects are presented (basic-level vs. subordinate-level) influences children's (7- and 10-year-olds) and adults' performance in a sequential binary categorization task. Study 1 found a robust facilitating effect of basic-level objects on the ability to ask effective questions in a computerized version of the Twenty Questions game. Study 2 suggested that this facilitating effect might be due to the kinds of object-differentiating features participants generate when provided with basic-level as compared to subordinate-level objects. Study 3 ruled out the alternative hypothesis that basic-level objects facilitate the selection of the most efficient among a given set of features.

BackgroundOnline health information is of variable and often low scientific quality. In particular, elderly less-educated populations are said to struggle in accessing quality online information (digital divide). Little is known about (1) how their online behavior differs from that of younger, more-educated, and more-frequent Web users, and (2) how the older population may be supported in accessing good-quality online health information.ObjectiveTo specify the digital divide between skilled and less-skilled Web users, we assessed qualitative differences in technical skills, cognitive strategies, and attitudes toward online health information. Based on these findings, we identified educational and technological interventions to help Web users find and access good-quality online health information.MethodsWe asked 22 native German-speaking adults to search for health information online. The skilled cohort consisted of 10 participants who were younger than 30 years of age, had a higher level of education, and were more experienced using the Web than 12 participants in the less-skilled cohort, who were at least 50 years of age. We observed online health information searches to specify differences in technical skills and analyzed concurrent verbal protocols to identify health information seekers’ cognitive strategies and attitudes.ResultsOur main findings relate to (1) attitudes: health information seekers in both cohorts doubted the quality of information retrieved online; among poorly skilled seekers, this was mainly because they doubted their skills to navigate vast amounts of information; once a website was accessed, quality concerns disappeared in both cohorts, (2) technical skills: skilled Web users effectively filtered information according to search intentions and data sources; less-skilled users were easily distracted by unrelated information, and (3) cognitive strategies: skilled Web users searched to inform themselves; less-skilled users searched to confirm their health-related opinions such as “vaccinations are harmful.” Independent of Web-use skills, most participants stopped a search once they had found the first piece of evidence satisfying search intentions, rather than according to quality criteria.ConclusionsFindings related to Web-use skills differences suggest two classes of interventions to facilitate access to good-quality online health information. Challenges related to findings (1) and (2) should be remedied by improving people’s basic Web-use skills. In particular, Web users should be taught how to avoid information overload by generating specific search terms and to avoid low-quality information by requesting results from trusted websites only. Problems related to finding (3) may be remedied by visually labeling search engine results according to quality criteria.

Background Symptom checkers are digital tools assisting laypersons in self-assessing the urgency and potential causes of their medical complaints. They are widely used but face concerns from both patients and health care professionals, especially regarding their accuracy. A 2015 landmark study substantiated these concerns using case vignettes to demonstrate that symptom checkers commonly err in their triage assessment. Objective This study aims to revisit the landmark index study to investigate whether and how symptom checkers’ capabilities have evolved since 2015 and how they currently compare with laypersons’ stand-alone triage appraisal. Methods In early 2020, we searched for smartphone and web-based applications providing triage advice. We evaluated these apps on the same 45 case vignettes as the index study. Using descriptive statistics, we compared our findings with those of the index study and with publicly available data on laypersons’ triage capability. Results We retrieved 22 symptom checkers providing triage advice. The median triage accuracy in 2020 (55.8%, IQR 15.1%) was close to that in 2015 (59.1%, IQR 15.5%). The apps in 2020 were less risk averse (odds 1.11:1, the ratio of overtriage errors to undertriage errors) than those in 2015 (odds 2.82:1), missing >40% of emergencies. Few apps outperformed laypersons in either deciding whether emergency care was required or whether self-care was sufficient. No apps outperformed the laypersons on both decisions. Conclusions Triage performance of symptom checkers has, on average, not improved over the course of 5 years. It decreased in 2 use cases (advice on when emergency care is required and when no health care is needed for the moment). However, triage capability varies widely within the sample of symptom checkers. Whether it is beneficial to seek advice from symptom checkers depends on the app chosen and on the specific question to be answered. Future research should develop resources (eg, case vignette repositories) to audit the capabilities of symptom checkers continuously and independently and provide guidance on when and to whom they should be recommended.

Background Symptom checkers (SCs) are tools developed to provide clinical decision support to laypersons. Apart from suggesting probable diagnoses, they commonly advise when users should seek care (triage advice). SCs have become increasingly popular despite prior studies rating their performance as mediocre. To date, it is unclear whether SCs can triage better than those who might choose to use them. Objective This study aims to compare triage accuracy between SCs and their potential users (ie, laypersons). Methods On Amazon Mechanical Turk, we recruited 91 adults from the United States who had no professional medical background. In a web-based survey, the participants evaluated 45 fictitious clinical case vignettes. Data for 15 SCs that had processed the same vignettes were obtained from a previous study. As main outcome measures, we assessed the accuracy of the triage assessments made by participants and SCs for each of the three triage levels (ie, emergency care, nonemergency care, self-care) and overall, the proportion of participants outperforming each SC in terms of accuracy, and the risk aversion of participants and SCs by comparing the proportion of cases that were overtriaged. Results The mean overall triage accuracy was similar for participants (60.9%, SD 6.8%; 95% CI 59.5%-62.3%) and SCs (58%, SD 12.8%). Most participants outperformed all but 5 SCs. On average, SCs more reliably detected emergencies (80.6%, SD 17.9%) than laypersons did (67.5%, SD 16.4%; 95% CI 64.1%-70.8%). Although both SCs and participants struggled with cases requiring self-care (the least urgent triage category), SCs more often wrongly classified these cases as emergencies (43/174, 24.7%) compared with laypersons (56/1365, 4.10%). Conclusions Most SCs had no greater triage capability than an average layperson, although the triage accuracy of the five best SCs was superior to the accuracy of most participants. SCs might improve early detection of emergencies but might also needlessly increase resource utilization in health care. Laypersons sometimes require support in deciding when to rely on self-care but it is in that very situation where SCs perform the worst. Further research is needed to determine how to best combine the strengths of humans and SCs.