Ambulatory Assessment in Behavioral Science

BackgroundIt is well established that drastic declines in physical activity (PA) occur during young adults’ transition into university; however, our understanding of contextual and environmental factors as it relates to young adults’ PA is limited.ObjectiveThe purpose of our study was to examine the feasibility of using wrist-worn accelerometers and the use of ecological momentary assessment (EMA) to assess the context and momentary correlates of PA on multiple occasions each day during first-year university.MethodsFirst-year university students were asked to participate in the study. The participants completed a brief questionnaire and were subsequently asked to wear an ActiGraph GT9X-Link accelerometer and respond to a series of EMA prompts (7/day) via their phones for 5 consecutive days.ResultsA total of 96 first-year university students with smartphones agreed to participate in the study (mean age 18.3 [SD 0.51]; n=45 females). Overall, there was good compliance for wearing the accelerometers, with 91% (78/86) of the participants having ≥2 days of ≥10 hours of wear time (mean=3.53 valid days). Students were generally active, averaging 10,895 steps/day (SD 3413) or 1123.23 activity counts/min (SD 356.10). Compliance to EMA prompts was less desirable, with 64% (55/86) of the participants having usable EMA data (responding to a minimum of ≥3 days of 3 prompts/day or ≥4 days of 2 prompts/day), and only 47% (26/55) of these participants were considered to have excellent EMA compliance (responding to ≥5 days of 4 prompts/day or ≥ 4 days of 5 prompts/day).ConclusionsThis study represents one of the first studies to use an intensive real-time data capture strategy to examine time-varying correlates of PA among first-year university students. These data will aim to describe the physical and social contexts in which PA occurs and examine the relationships between momentary correlates of PA among the first-year university students. Overall, current results suggest that wrist-worn accelerometers and EMA are feasible methods for data collection among the young adult population; however, more work is needed to understand how to improve upon compliance to a real-time data capture method such as EMA.

In recent years, ecological momentary assessment (EMA) has been used to repeatedly assess eating disorder (ED) symptoms in naturalistic settings, which has allowed for increased understanding of temporal processes that potentiate ED behaviors. However, there remain notable limitations of self-report EMA, and with the rapid proliferation of technology there are ever-increasing possibilities to improve ambulatory assessment methods to further the understanding and treatment of EDs. Therefore, the purpose of this review was to (a) systematically review the studies in EDs that have utilized ambulatory assessment methods other than self-report, and (b) provide directions for future research and clinical applications. A systematic literature search of electronic databases was conducted, and data regarding study characteristics and methodological quality were extracted. The search identified 17 studies that used ambulatory assessment methods to gather objective data, and focused primarily on autonomic functioning, physical activity, and cognitive processes in ED and control groups. Together the literature demonstrates the promise of using a range of ecologically valid ambulatory assessment approaches in EDs, though there remains limited research that has utilized methods other than self-report (e.g., wearable sensors), particularly in recent years. Going forward, there are several technology-enhanced momentary assessment methods that have potential to improve the understanding and treatment of EDs.

BackgroundPrescription drug misuse and abuse is an established public health challenge, and young adults are particularly affected. There is a striking lack of real-time, naturalistic data collection assessing intentions to misuse and other precipitating factors at the time of actual misuse, leaving the conditions under which individuals are most likely to misuse prescription medications unknown. Ecological momentary assessment (EMA) apps and protocols designed to capture this information would accelerate and expand the knowledge base and could directly contribute to prevention and treatment efforts.ObjectiveThe objectives of this study are to describe the development and administration of a mobile app and the EMA protocol designed to collect real-time factors associated with college students’ prescription drug misuse intentions and behaviors in daily life; present completion rates, compliance, acceptability, and reactivity associated with the EMA protocol for participants who endorsed recent prescription drug misuse at screening (ie, risk group; n=300) and those who did not (ie, nonrisk group; n=55); and establish initial construct validity by linking the reports of misuse behaviors in daily life collected via the EMA app to prescription drug misuse reported on a standard survey.MethodsAn EMA data collection app and protocol were designed specifically to capture hypothesized contextual factors along with prescription drug misuse intentions and behaviors in daily life. Using this protocol, young adult college students (N=352) completed signal- and event-contingent reports over a 28-day period. When the intention to misuse a prescription drug was endorsed, a brief follow-up prompt was sent 15 min later to collect participants’ indications of whether or not misuse had occurred.ResultsRisk-group participants were significantly more likely than nonrisk counterparts to endorse any prescription drug misuse intentions in daily life (P<.001), to complete one or more follow-up reports (P<.001), and to endorse any prescription drug misuse behavior in daily life on the follow-ups (P<.001). Overall, participants demonstrated consistent engagement with the EMA procedures and returned an average of 74.5 (SD 23.82; range 10-122) reports. Participants in the risk and nonrisk groups did not differ in the number of reports they completed (P=.12), the number of their reporting days (P=.32), or their average completion rates (P=.14). The results indicated some evidence of reactivity to the momentary reporting procedure. Participants reported uniformly positive experiences and remained highly engaged throughout the reporting protocol and broader study.ConclusionsThe novel EMA app and protocol provide an effective way to assess real-time factors associated with prescription drug misuse intentions and behaviors in daily life. The resulting investigations offer the potential to provide highly translatable information for research and prevention efforts.

Various populations with chronic conditions are at risk for decreased cognitive performance, making assessment of their cognition important. Formal mobile cognitive assessments measure cognitive performance with greater ecological validity than traditional laboratory-based testing but add to participant task demands. Given that responding to a survey is considered a cognitively demanding task itself, information that is passively collected as a by-product of ecological momentary assessment (EMA) may be a means through which people's cognitive performance in their natural environment can be estimated when formal ambulatory cognitive assessment is not feasible. We specifically examined whether the item response times (RTs) to EMA questions (eg, mood) can serve as approximations of cognitive processing speed. This study aims to investigate whether the RTs from noncognitive EMA surveys can serve as approximate indicators of between-person (BP) differences and momentary within-person (WP) variability in cognitive processing speed. Data from a 2-week EMA study investigating the relationships among glucose, emotion, and functioning in adults with type 1 diabetes were analyzed. Validated mobile cognitive tests assessing processing speed (Symbol Search task) and sustained attention (Go-No Go task) were administered together with noncognitive EMA surveys 5 to 6 times per day via smartphones. Multilevel modeling was used to examine the reliability of EMA RTs, their convergent validity with the Symbol Search task, and their divergent validity with the Go-No Go task. Other tests of the validity of EMA RTs included the examination of their associations with age, depression, fatigue, and the time of day. Overall, in BP analyses, evidence was found supporting the reliability and convergent validity of EMA question RTs from even a single repeatedly administered EMA item as a measure of average processing speed. BP correlations between the Symbol Search task and EMA RTs ranged from 0.43 to 0.58 (P<.001). EMA RTs had significant BP associations with age (P<.001), as expected, but not with depression (P=.20) or average fatigue (P=.18). In WP analyses, the RTs to 16 slider items and all 22 EMA items (including the 16 slider items) had acceptable (>0.70) WP reliability. After correcting for unreliability in multilevel models, EMA RTs from most combinations of items showed moderate WP correlations with the Symbol Search task (ranged from 0.29 to 0.58; P<.001) and demonstrated theoretically expected relationships with momentary fatigue and the time of day. The associations between EMA RTs and the Symbol Search task were greater than those between EMA RTs and the Go-No Go task at both the BP and WP levels, providing evidence of divergent validity. Assessing the RTs to EMA items (eg, mood) may be a method of approximating people's average levels of and momentary fluctuations in processing speed without adding tasks beyond the survey questions.

Digital phenotyping using wearable devices and ecological momentary assessment (EMA) enables continuous, real-world monitoring of physiological and emotional states, but identifying high-risk stress states in real time remains challenging. We examined day-level associations between emotional distress and heart rate variability (HRV), and assessed whether daily physical activity modifies this relationship using longitudinal wearable and EMA data. The Smart Momentary Interactive Longitudinal Evaluation Study (SMILES) was a prospective cohort study conducted among STEM graduate students in the U.S. in 2025. Participants wore an Oura Ring Generation 3 continuously for five months and completed daily EMA surveys assessing emotional distress. The primary outcome was nightly HRV measured as the root mean square of successive differences and log-transformed for analysis. Quantile regression within a quadratic inference function framework was used to estimate associations at the 25th, 50th, and 75th percentiles of HRV, accounting for within-participant correlation and time-varying covariates. Thirty-one participants contributed 1,724 person-days of observation. High emotional distress was associated with lower HRV across the HRV distribution, with the strongest association observed at the lower HRV quantile (β = -0.094, 95\% CI: [-0.111, -0.078]). A significant interaction between daily step count and emotional distress was observed across quantiles, such that higher physical activity was associated with higher HRV on high emotional distress days but not on low-to-moderate distress days. Integration of wearable-derived physiological data with EMA enables real-time identification of high-risk stress states in naturalistic settings. The observed buffering effect of physical activity during periods of elevated emotional distress suggests that wearable-guided, personalized just-in-time adaptive interventions, such as physical activity prompts, could be deployed to improve autonomic regulation and mental health.

Anxiety disorders are among the most prevalent mental disorders. In panic disorder, panic attacks often occur at unpredictable times, making it difficult to study these episodes in the laboratory. In specific phobias, symptoms occur in very circumscribed situations and specific triggers are sometimes difficult to reproduce in the laboratory. Ambulatory assessment, or ecological momentary assessment, can further the understanding of the natural course and scope of symptoms under ecologically valid circumstances. Because bodily symptoms are integral to the diagnosis of anxiety disorders, the objective assessment of physiological responses in the patients' natural environment is particularly important. On the one hand, research has highlighted intriguing discrepancies between the experience of symptoms and physiology during panic attacks. On the other hand, it has validated symptom reporting during therapeutic exposure to phobic situations. Therefore, ambulatory assessment can yield useful information about the psychopathology of anxiety disorders, and it can be used to monitor change during clinical interventions.

The study compared the utility of two approaches for collecting real-world listening experiences to predict hearing-aid preference: a retrospective questionnaire (Speech, Spatial, and Qualities of Hearing Scale [SSQ]) and in-situ Ecological Momentary Assessment (EMA). The rationale being that each approach likely provides different and yet complementary information. In addition, it was examined how self-reported listening activity and hearing-aid data-logging can augment EMAs for individualized and contextualized hearing outcome assessments. Experienced hearing-aid users (N = 40) with mild-to-moderate symmetrical sensorineural hearing loss completed the SSQ questionnaire and gave repeated EMAs for two wear periods of 2-weeks each with two different hearing-aid models that differed mainly in their noise reduction technology. The EMAs were linked to a self-reported listening activity and sound environment parameters (from hearing-aid data-logging) recorded at the time of EMA completion. Wear order was randomized by hearing-aid model. Linear mixed-effects models and Random Forest models with five-fold cross-validation were used to assess the statistical associations between listening experiences and end-of-trial preferences, and to evaluate how accurately EMAs predicted preference within individuals. Only 6 of the 49 SSQ items significantly discriminated between responses made for the end-of-trial preferred versus nonpreferred hearing-aid model. For the EMAs, questions related to perception of the sound from the hearing aids were all significantly associated with preference, and these associations were strongest in EMAs completed in sound environments with predominantly low SNR and listening activities related to television, people talking, nonspecific listening, and music listening. Mean differences in listening experiences from SSQ and EMA correctly predicted preference in 71.8% and 72.5% of included participants, respectively. However, a prognostic classification of single EMAs into end-of-trial preference with a Random Forest model achieved a 93.8% accuracy when contextual information was included. SSQ and EMA predicted preference equally well when considering mean differences, however, EMAs had a high prognostic classifications accuracy due to the repeated-measures nature, which make them ideal for individualized hearing outcome investigations, especially when responses are combined with contextual information about the sound environment.

Stress is omnipresent in our everyday lives and a key risk factor for our physical and mental health. Yet little is known about the impact of geographic life environments, linked to our daily activities and mobility patterns, on our momentary and daily stress levels.We propose this review to gather evidence on the spatio-temporal determinants of momentary or daily stress in studies using ecological momentary assessment (EMA) or experience sampling methods (ESM) in addition to global positioning systems (GPS) tracking. We will focus on the spatio-temporal definition and modelling of environmental exposures accounting for participant daily activities and mobility patterns and their association with stress. This scoping review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework for scoping reviews (2018). We will search the PubMed/Medline, Web of Science, PsycInfo and Scopus databases. We will include papers using EMA or ESM and GPS measuring chronic, daily or momentary stress as an outcome; these methods are also referred to as geographically-explicit ecological momentary assessment.Articles published from January 2000-June 2025 will be screened. Two independent reviewers will screen titles and abstracts to agree on the inclusion of articles. No geographical or population limitation will be imposed. This study is a scoping review based on previously published and publicly available literature. It does not involve the collection of primary data, human participants, or the processing of personal or sensitive information. Therefore, ethical approval is not required in accordance with institutional and international research ethics guidelines. The results will be submitted in peer-reviewed journals and presented at international conferences.

Extant literature has indicated that the experience of defeat confers risk for experiencing conceptions of entrapment, which in turns increases one’s risk of experiencing suicidal ideation. In addition, certain cognitive processes are hypothesized to increase or decrease the likelihood of feelings of entrapment emerging when one feels defeated. One such cognitive process is mindfulness, defined as present moment awareness with an orientation of openness and acceptance. Better understanding the interplay of defeat, entrapment, mindfulness, and suicidal thinking will contribute to intervention strategies aimed at reducing the severity of suicidal thinking; however, said research should be conducted with consideration that one’s suicidal thoughts vary greatly over different temporal scales (e.g., ambulatory assessment). The purpose of this study was to analyze the relations between state defeat, state entrapment, state mindfulness, and state severity of suicidal ideation using ecological momentary assessment over a ten-day data collection period. Participants (N=50) were college students with a history of suicidal thinking. Results indicated that (1) defeat predicted entrapment concurrently but not prospectively, (2) although mindfulness was inversely predictive of entrapment, it did not interact with defeat to predict entrapment, (3) entrapment was significantly predictive of SI severity both concurrently and prospectively. Findings provide partial support for contemporary theories of suicide and highlight the highly dynamic nature of SI severity and related risk factors.

BackgroundWe present a digital phenotyping protocol designed to continuously and objectively measure behavioral, physiological, and contextual data during pregnancy and the postpartum period using passive sensing from Garmin smartwatches and smartphones, along with active ecological momentary assessments (EMAs). This novel protocol uniquely adapts to the unpredictable timing of childbirth, spanning from the third trimester through 6 weeks post partum, to accurately capture critical temporal changes and maternal-infant outcomes. By providing high-frequency real-time data, this methodology offers comprehensive insights into pregnancy-related behaviors and physiological processes, overcoming the limitations of traditional retrospective self-report methods.ObjectiveWe aim to develop a protocol for longitudinal data collection supporting digital phenotyping that is optimized for pregnancy and the postpartum period. This protocol leverages the pregnant population’s heightened interest in health and tracking. It aims to minimize the burden on the participants, increase retention, and assess the value of wearables compared to smartphones to determine the appropriate data collection methods.MethodsData will be collected from 30 nulliparous participants from the start of the third trimester through 6 weeks post partum. This protocol uses 3 distinct 1-time surveys, alongside daily and weekly EMAs, to capture real-time maternal experience data. Passive maternal data—such as activity, vitals, sleep, and location—are collected via smartphones and Garmin smartwatches. Participants are expected to log data about the newborn after delivery through the mobile app Huckleberry. This protocol was developed in collaboration with the Northeastern University Sath Laboratory, which focuses on digital phenotyping and longitudinal data collection, and the Tufts Medical Center’s obstetrics and gynecology department, which has expertise in working with the pregnant population.ResultsThis study was funded in August 2024. Data collection is projected to run from October 2025 to July 2026. As of September 2025, the study has been approved, and recruitment and data collection are to begin. The results are expected to be published by August 2026. We plan to assess the retention rates, survey and EMA completion rates, wear time of the smartwatch without intervention, and data volume logged in the Huckleberry app. In addition, we will perform digital phenotyping to determine whether the data collected during pregnancy can be used to predict breastfeeding outcomes, delivery outcomes, and maternal-infant well-being.ConclusionsThis protocol integrates the use of digital phenotyping in pregnancy and postpartum research, providing a novel method for capturing real-time indicators of maternal well-being. It will determine the expected rates of data completion and appropriate sample size using a power analysis for a more extensive future study. By integrating smartphone and wearable sensor data, this protocol has the potential to transform the way maternal health clinical interventions are designed and implemented in the future.International Registered Report Identifier (IRRID)PRR1-10.2196/77175

This study examines patterns of physical activity and sedentary behavior in individuals aged 65 years and older in the Beira Baixa region of Portugal with the aim of identifying differences between rural and urban settings. We analyzed data from 40 participants, including 19 rural residents (mean age = 74.7 years, SD = 8.5 years) and 21 urban residents (mean age = 70.1 years, SD = 5.2 years), using a retrospective cross-sectional design complemented by an ecological momentary assessment to capture real-time behavior. The thematic analysis revealed that both cohorts were predominantly sedentary, especially in terms of television consumption. Physical activities were mainly limited to tasks such as housework, gardening and occasional walking, with minimal social interactions. Urban participants, in particular, reported meeting more frequently with family at home and in the neighborhood. Both groups primarily used indoor spaces and nearby streets for physical activity. Our findings highlight the urgent need for tailored weekend physical activity programs to improve sedentary lifestyles among older adults in both rural and urban areas. This study contributes to the literature by highlighting the specific leisure-time preferences and activity patterns of older Portuguese adults, providing a basis for the development of adaptive, age-appropriate interventions. Keywords: Movement behaviors, ageing, observational study, real-time data capture

Background/objectivesInsulin resistance (IR)-related disorders and cognitive impairment lead to reduced quality of life and cause a significant strain on individuals and the public health system. Thus, we investigated the effects of insulin resistance (IR), and blood glucose fluctuations on cognitive function under laboratory and free-living conditions, using ecological momentary assessment (EMA).Subjects/methodsBaseline assessments included neuropsychological tests and blood analysis. Individuals were classified as either insulin-sensitive (<2) or insulin-resistant (≥2), based on their Homeostatic Model Assessment (HOMA-IR) values. Continuous glucose monitoring (CGM) using a percutaneous sensor was performed for 1 week. Using multiple linear regression, we examined the effects of HOMA-IR and CGM metrics on cognitive domains. Working memory (WM) performance, which was assessed using EMA, 4 times a day for 3 consecutive days, was matched to short-term pre-task CGM metrics. Multilevel analysis was used to map the within-day associations of HOMA-IR, short-term CGM metrics, and WM.ResultsAnalyses included 110 individuals (mean age 48.7 ± 14.3 years, 59% female, n = 53 insulin-resistant). IR was associated with lower global cognitive function (b = −0.267, P = 0.027), and WM (b = −0.316; P = 0.029), but not with executive function (b = −0.216; P = 0.154) during baseline. EMA showed that higher HOMA-IR was associated with lower within-day WM performance (β = −0.20, 95% CI −0.40 to −0.00). CGM metrics were not associated with cognitive performance.ConclusionsThe results confirm the association between IR and decrements in global cognitive functioning and WM, while no effects of CGM metrics were observed, making IR a crucial time point for intervention. Targeting underlying mechanisms (e.g., inflammation) in addition to glycemia could be promising to minimize adverse cognitive effects. Registered under https://drks.de/register/de identifier no. DRKS00022774.

Social functioning in schizophrenia: Comparing laboratory-based assessment with real-world measures

BACKGROUND We present a digital phenotyping protocol designed to continuously and objectively measure behavioral, physiological, and contextual data during pregnancy and postpartum periods using passive sensing from Garmin smartwatches and smartphones, along with active ecological momentary assessments (EMAs). This novel protocol uniquely adapts to the unpredictable timing of childbirth, spanning from the third trimester through six weeks postpartum, to accurately capture critical temporal changes and maternal-infant outcomes. By providing high-frequency real-time data, this methodology offers comprehensive insights into pregnancy-related behaviors and physiological processes, overcoming limitations of traditional retrospective self-report methods. OBJECTIVE The objective is to develop a protocol for longitudinal data collection supporting digital phenotyping that is optimized for pregnancy and postpartum. This protocol leverages the pregnant population’s heightened interest in health and tracking with over 50% using mobile health apps [1]. This protocol aims to minimize burden on the participants, increase retention, and assess the value of wearables compared to smartphones to determine appropriate data collection methods. METHODS Data will be collected on 30 nulliparous participants from the start of the third trimester through 6 weeks postpartum. This protocol utilizes three distinct one-time surveys, alongside daily and weekly Ecological Momentary Assessments (EMA), to capture real-time maternal experience data. Passive maternal data - such as activity, vitals, sleep, location - are collected via smartphone and Garmin smartwatch. Participants are expected to log data about the newborn after delivery through the mobile application Huckleberry. This protocol was developed in collaboration between the Northeastern University SATH Lab who focus on digital phenotyping and longitudinal data collection and Tufts Medical Center Obstetrics and Gynecology who have expertise working with the pregnant population. RESULTS The planned completion date is December 2026, with a manuscript published afterward. We plan to assess retention rates, survey and EMA completion rates, track wear time of smartwatch without intervention, and data volume logged in Huckleberry. CONCLUSIONS This protocol integrates the use of digital phenotyping in pregnancy and postpartum research, providing a novel method for capturing real-time maternal well-being indicators. It will determine expected rates of data completion and appropriate sample size using a power analysis for a more extensive future study. By integrating smartphone and wearable sensor data, this protocol has the potential to transform the way maternal health clinical interventions are designed and implemented in the future.

Experience sampling and ecological momentary assessment studies in psychopharmacology: A systematic review