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BackgroundPhysical inactivity increases the risk of chronic disease and reduces life expectancy, yet adherence to physical activity (PA) guidelines remains low. SMS text messages are promising for promoting PA, but it is not clear what type of messaging is most effective. Messages with causal information, which explain why a recommendation is being made, may be more persuasive than messages containing only recommendations. ObjectiveThis study aims to compare the effectiveness of causal versus noncausal SMS text messages for promoting PA in US adults. MethodsIn this pilot study, we randomized US adults (n=28 in the analytic sample) aged 18-64 years to receive causal or noncausal SMS text messages roughly every other day for 2 weeks, following a 1-week baseline. PA was measured using Empatica wristbands during intervention and baseline periods, and the International Physical Activity Questionnaire – Short Form (IPAQ-SF) at baseline, postintervention, and 4 weeks later. The primary outcome was the change in mean metabolic equivalent of tasks (METs) per minute from baseline to intervention. The secondary outcomes were (1) PA differences on intervention and nonintervention days (mean METs/min), (2) changes in self-reported METs per week between surveyed periods, and (3) participant satisfaction. We used a linear mixed model to analyze our primary outcome, the Mann-Whitney U test and the chi-square test of independence to analyze quantitative secondary outcomes, and qualitative coding to analyze survey data. ResultsThe causal message group had a greater increase in mean METs per minute from baseline to intervention compared to the noncausal group with a moderate effect size (P=.01; Cohen d=0.54). In the causal group, PA was significantly higher on SMS text message days (mean 2.46, SD 0.12 METs/min) compared to nonmessage days (mean 2.25, SD 0.15 METs/min; P=.02), while there was no difference in the noncausal group (P=.54). No significant between-group difference was found in self-reported PA or satisfaction. ConclusionsCausal information that links suggested PA to health outcomes can increase the effectiveness of SMS text messages promoting PA, indicating the value of incorporating causal information into intervention design. Our results provide further basis for just-in-time interventions, as activity was higher on message days. Further work is needed to better personalize message content and timing to maintain participant engagement. 

Background People’s health-related knowledge influences health outcomes, as this knowledge may influence whether individuals follow advice from their doctors or public health agencies. Yet, little attention has been paid to where people obtain health information and how these information sources relate to the quality of knowledge. Objective We aim to discover what information sources people use to learn about health conditions, how these sources relate to the quality of their health knowledge, and how both the number of information sources and health knowledge change over time. Methods We surveyed 200 different individuals at 12 time points from March through September 2020. At each time point, we elicited participants’ knowledge about causes, risk factors, and preventative interventions for 8 viral (Ebola, common cold, COVID-19, Zika) and nonviral (food allergies, amyotrophic lateral sclerosis [ALS], strep throat, stroke) illnesses. Participants were further asked how they learned about each illness and to rate how much they trust various sources of health information. Results We found that participants used different information sources to obtain health information about common illnesses (food allergies, strep throat, stroke) compared to emerging illnesses (Ebola, common cold, COVID-19, Zika). Participants relied mainly on news media, government agencies, and social media for information about emerging illnesses, while learning about common illnesses from family, friends, and medical professionals. Participants relied on social media for information about COVID-19, with their knowledge accuracy of COVID-19 declining over the course of the pandemic. The number of information sources participants used was positively correlated with health knowledge quality, though there was no relationship with the specific source types consulted. Conclusions Building on prior work on health information seeking and factors affecting health knowledge, we now find that people systematically consult different types of information sources by illness type and that the number of information sources people use affects the quality of individuals’ health knowledge. Interventions to disseminate health information may need to be targeted to where individuals are likely to seek out information, and these information sources differ systematically by illness type.