Nithya Ramanathan

Reliability and Validity of Daily Self-Monitoring by Smartphone Application for Health-Related Quality-of-Life, Antiretroviral Adherence, Substance Use, and Sexual Behaviors Among People Living with HIV

This paper examines inter-method reliability and validity of daily self-reports by smartphone application compared to 14-day recall web-surveys repeated over 6xa0weeks with people living with HIV (PLH). A participatory sensing framework guided participant-centered design prioritizing external validity of methods for potential applications in both research and self-management interventions. Inter-method reliability correlations were consistent with prior research for physical and mental health quality-of-life (rxa0=xa00.26–0.61), antiretroviral adherence (rxa0=xa00.70–0.73), and substance use (rxa0=xa00.65–0.92) but not for detailed sexual encounter surveys (rxa0=xa00.15–0.61). Concordant and discordant pairwise comparisons show potential trends in reporting biases, for example, lower recall reports of unprotected sex or alcohol use, and rounding up errors for frequent events. Event-based reporting likely compensated for modest response rates to daily time-based prompts, particularly for sexual and drug use behaviors that may not occur daily. Recommendations are discussed for future continuous assessment designs and analyses.

Time series visualizations for daily diary reports of health behaviors: a case study of mobile phone-based reports of stress, physical activity, and diet quality in mostly ethnic minority mothers (Preprint)

Background Health behavior patterns reported through daily diary data are important to understand and intervene upon at the individual level in N-of-1 trials and related study designs. There is often interest in relationships between multiple outcomes, such as stress and health behavior. However, analyses often utilize regressions that evaluate aggregate effects across individuals, and standard analyses target single outcomes. Objective This paper aims to illustrate how individuals’ daily reports of stress and health behavior (time series) can be explored using visualization tools. Methods Secondary analysis was conducted on 6 months of daily diary reports of stress and health behavior (physical activity and diet quality) from mostly ethnic minority mothers who pilot-tested a self-monitoring mobile health app. Time series with minimal missing data from 14 of the 44 mothers were analyzed. Correlations between stress and health behavior within each time series were reported as a preliminary step. Stress and health behavior time series patterns were visualized by plotting moving averages and time points where mean shifts in the data occurred (changepoints). Results Median correlation was small and negative for associations of stress with physical activity (r=−.14) and diet quality (r=−.08). Moving averages and changepoints for stress and health behavior were aligned for some participants but not for others. A third subset of participants exhibited little variation in stress and health behavior reports. Conclusions Median correlations in this study corroborate prior findings. In addition, time series visualizations highlighted variations in stress and health behavior across individuals and time points, which are difficult to capture through correlations and regression-based summary measures.