RESUMO
BACKGROUND: Sleep, or a lack thereof, is strongly related to mood dysregulation. Although considerable research uses symptom scales to examine this relation, few studies use longitudinal, real-time methods focused on pediatric irritability. This study leveraged an ecological momentary assessment (EMA) protocol, assessing bidirectional associations between momentary irritability symptoms and daily sleep duration in a transdiagnostic pediatric sample enriched for irritability. METHODS: A total of N = 125 youth (Mage = 12.58 years, SD = 2.56 years; 74% male; 68.8% White) completed digital, in vivo surveys three times a day for 7 days. For a subset of youth, their parents also completed the EMA protocol. Trait irritability was measured using youth-, parent-, and clinician-report to test its potential moderating effect on the association between sleep duration and momentary irritability. RESULTS: Results from multilevel modeling dynamically linked sleep to irritability. Specifically, according to youth- and parent-report, decreased sleep duration was associated with increased morning irritability (bs ≤ -.09, ps < .049). A bidirectional association between parent-reported nightly sleep duration and anger was found-increased evening anger related to decreased nightly sleep duration, and decreased sleep duration related to increased morning anger (bs ≤ -.17, ps < .019). Trait irritability moderated this association, which was stronger for more irritable youth (b = -.03, p < .027). CONCLUSIONS: This study adds to the literature and suggests sleep-irritability dynamics as a potential treatment target.
RESUMO
BACKGROUND: Although ecological momentary assessment (EMA) has been applied in psychological research for decades, delivery methods have evolved with the proliferation of digital technology. Technological advances have engendered opportunities for enhanced accessibility, convenience, measurement precision, and integration with wearable sensors. Notwithstanding, researchers must navigate novel complexities in EMA research design and implementation. OBJECTIVE: In this paper, we aimed to provide guidance on platform selection for clinical scientists launching EMA studies. METHODS: Our team includes diverse specialties in child and adolescent behavioral and mental health with varying expertise on EMA platforms (eg, users and developers). We (2 research sites) evaluated EMA platforms with the goal of identifying the platform or platforms with the best fit for our research. We created a list of extant EMA platforms; conducted a web-based review; considered institutional security, privacy, and data management requirements; met with developers; and evaluated each of the candidate EMA platforms for 1 week. RESULTS: We selected 2 different EMA platforms, rather than a single platform, for use at our 2 research sites. Our results underscore the importance of platform selection driven by individualized and prioritized laboratory needs; there is no single, ideal platform for EMA researchers. In addition, our project generated 11 considerations for researchers in selecting an EMA platform: (1) location; (2) developer involvement; (3) sample characteristics; (4) onboarding; (5) survey design features; (6) sampling scheme and scheduling; (7) viewing results; (8) dashboards; (9) security, privacy, and data management; (10) pricing and cost structure; and (11) future directions. Furthermore, our project yielded a suggested timeline for the EMA platform selection process. CONCLUSIONS: This study will guide scientists initiating studies using EMA, an in vivo, real-time research tool with tremendous promise for facilitating advances in psychological assessment and intervention.
