BACKGROUND: Ecological momentary assessment (EMA) is a measurement methodology that involves the repeated collection of real-time data on participants\' behavior and experience in their natural environment. While EMA allows researchers to gain valuable insights into dynamic behavioral processes, the need for frequent self-reporting can be burdensome and disruptive. Compliance with EMA protocols is important for accurate, unbiased sampling; yet, there is no \"gold standard\" for EMA study design to promote compliance.
OBJECTIVE: The purpose of this study was to use a factorial design to identify optimal study design factors, or combinations of factors, for achieving the highest completion rates for smartphone-based EMAs.
METHODS: Participants recruited from across the United States were randomized to 1 of 2 levels on each of 5 design factors in a 2×2×2×2×2 design (32 conditions): factor 1-number of questions per EMA survey (15 vs 25); factor 2-number of EMAs per day (2 vs 4); factor 3-EMA prompting schedule (random vs fixed times); factor 4-payment type (US $1 paid per EMA vs payment based on the percentage of EMAs completed); and factor 5-EMA response scale type (ie, slider-type response scale vs Likert-type response scale; this is the only within-person factor; each participant was randomized to complete slider- or Likert-type questions for the first 14 days or second 14 days of the study period). All participants were asked to complete prompted EMAs for 28 days. The effect of each factor on EMA completion was examined, as well as the effects of factor interactions on EMA completion. Finally, relations between demographic and socioenvironmental factors and EMA completion were examined.
RESULTS: Participants (N=411) were aged 48.4 (SD 12.1) years; 75.7% (311/411) were female, 72.5% (298/411) were White, 18.0% (74/411) were Black or African American, 2.7% (11/411) were Asian, 1.5% (6/411) were American Indian or Alaska Native, 5.4% (22/411) belonged to more than one race, and 9.6% (38/396) were Hispanic/Latino. On average, participants completed 83.8% (28,948/34,552) of scheduled EMAs, and 96.6% (397/411) of participants completed the follow-up survey. Results indicated that there were no significant main effects of the design factors on compliance and no significant interactions. Analyses also indicated that older adults, those without a history of substance use problems, and those without current depression tended to complete more EMAs than their counterparts. No other demographic or socioenvironmental factors were related to EMA completion rates. Finally, the app was well liked (ie, system usability scale score=82.7), and there was a statistically significant positive association between liking the app and EMA compliance.
CONCLUSIONS: Study results have broad implications for developing best practices guidelines for future studies that use EMA methodologies.
BACKGROUND: ClinicalTrials.gov number NCT05194228; https://clinicaltrials.gov/study/NCT05194228.

Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual\'s behavior. These measures involve the near-continuous and unobtrusive collection of data from smartphones without requiring active input from participants. For example, GPS sensors are used to determine the (social) context of a person, and accelerometers to measure movement. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers must make multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. The implementation of open science practices is only beginning to emerge in digital phenotyping studies and varies widely across studies. Well-intentioned researchers may fail to report on some decisions due to the variety of choices that must be made. To address this issue and enhance reproducibility in digital phenotyping studies, we propose the adoption of preregistration as a way forward. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Therefore, our objective was to develop a preregistration template that is easy to use and understandable for researchers. Additionally, we explain this template and provide resources to assist researchers in making informed decisions regarding data collection, cleaning, and analysis. Overall, we aim to make researchers\' choices explicit, enhance transparency, and elevate the standards for studies utilizing passive smartphone measures.

The cortisol awakening response (CAR) has been hypothesized to prepare the body for anticipated demands of the upcoming day. This pilot study investigates the influence of anticipated stress on the upcoming day on the CAR, using an intensive longitudinal design with ecological momentary assessments. Over a 30-day period, three healthy participants collected saliva samples each morning at three time points after awakening to measure cortisol levels and completed a questionnaire each evening on the anticipated stress for the following day. Additionally, they wore a smart headband to objectively determine the time point of awakening. There was high variability in the CAR magnitude within participants over time. A multi-level model was estimated to investigate the influence of anticipated stress on the CAR. Results indicated that anticipated stress is predictive of the CAR on the following morning, with higher anticipated stress being associated with increased cortisol levels at the post-awakening time points. These findings underscore the role of stress anticipation in modulating the CAR and highlight the importance of considering within-person variation and temporally lagged effects in biopsychological research.

Why should researchers measure psychophysiological processes repeatedly over time? The study of psychophysiology inherently involves sampling biological processes as they manifest over time. The most common approach is to use a brief sample to make conclusions about how individuals or groups differ. Although these types of between-subject comparisons have utility for understanding individual and group differences, many of the important conceptual questions in the field involve processes that are dynamic, varying within individuals over time. Using examples from the literature on affect regulation, this conceptual review contrasts three types of study designs: the classic single-observation design and the aggregated and temporally linked repeated observation designs, which have great promise for measuring variables that fluctuate dynamically over time. Importantly, these designs can be integrated to elucidate research questions about risk (when and for whom will the likelihood of an unwanted outcome occurring increase?), mechanisms (how and why does a change in psychophysiology contribute to a change in another process of interest?), and interventions (how and when should interventions take place to modify an outcome?). Researchers are encouraged to implement intensive sampling in their research, which can be conducted in traditional laboratory settings (e.g., fMRI, event-related brain potentials, and heart rate variability) and in ecologically valid contexts in everyday life using ambulatory assessment.

Most of the scientific research on alcohol consumption behavior in humans is laboratory-based, as reflected by the ratio of laboratory vs. real-life contributions to this handbook. Studies in daily life, although having a long history in addiction research (Shiffman et al., Ann Behav Med 16:203-209, 1994), are in the minority. This is surprising, given that patients with substance use disorders are suffering in daily life and not in the laboratory setting. In other words, drinking patterns and symptoms of alcohol use disorder evolve not in the lab but in daily life, where patients show difficulties in limiting their alcohol intake accompanied with all kinds of related problems. The ultimate goal of all interventions, independent of being tailored toward restricted drinking or abstinence, is again an altered behavior in real life. Translated to practice, patients\' behavior in the lab may not translate to daily life, often showing minimal ecological validity. Therefore, we have to question to which degree lab-based research findings translate into daily life. Fortunately, the current digital revolution provided us with more and more tools, enabling us to monitor, analyze, and change behavior in human everyday life. Our chapter does not intend to give a comprehensive overview of the daily life research on alcohol consumption over the last few decades as others do (Morgenstern et al., Alcohol Res Curr Rev 36:109, 2014; Piasecki, Alcohol Clin Exp Res 43:564-577, 2019; Shiffman, Psychol Asses 21:486-497, 2009; Votaw and Witkiewitz, Clin Psychol Sci 9:535-562, 2021; Wray et al., Alcohol Res Curr Rev 36:19-27, 2014). Instead, we aim at the following: first, to highlight the key advantages of ecological momentary assessment to motivate scientists to add daily life research components to their laboratory research and, second, to provide some guidance on how to begin with daily life research.

Studying people in real-life situations, such as making music in a vocal group, requires flexible and integrative measurement technology. Therefore, a digital browser-based survey instrument was developed for this study. It was designed to seamlessly introduce questions on participants\' mobile devices through external control immediately after relevant events, aiming to achieve high accuracy in self-administered situational questions. In addition, chronological synchronization with supplementary measurements (here eye-tracking and audio recording) was incorporated. Digital features of this web app offer convenient integration into everyday situations, synchronous interviewing of multiple people, and gathering time-based data. Due to the numerous possibilities of the browser-based development interface, various other application areas can be opened up. The contribution of this article is:-App - explanation and offer for use-Feasibility report on the implementation of the app in an eye-tracking study with vocal groups.

Laboratory-based studies have shown that psychological stress caused by response to various stressors triggers acute changes in the cardiovascular system. A better understanding is needed of the emerging evidence on temporal associations between psychological stress and cardiovascular responses in natural settings. This study examined the association of psychological stress and heart rate variability (HRV) in daily life, at high resolution over 2 weeks, taking the effect of physical activity into account. Participants (n = 34) completed ecological momentary assessments (EMA) 6 times per day, reporting levels of perceived stress, low-arousal negative affect (LNA), and high-arousal negative affect. Chest-mounted heart-rate monitors were worn to assess HRV. Multilevel models were used to examine the association between psychological stress levels and preceding/subsequent HRV. Reduced time domain HRV measures (mean and standard deviation of R-wave to R-wave intervals) during the prior hour predicted higher levels of perceived stress. Frequency domain HRV measures higher low to high frequency (LF/HF) and lower HF to total power (HF nu) ratios during the preceding 10 min predicted higher perceived stress levels, suggesting the dominance of sympathetic nervous system activity. EMA reports of higher perceived stress levels were associated with reduced time domain HRV measures during the following 10 min. On the other hand, higher LNA were related to increased HRV measures, such as lower LF/HF and higher HF nu during the following hour. The dynamic associations observed may have therapeutic implications for \'just-in-time\' interventions in the management of daily stress and cardiovascular health.

BACKGROUND: Digital phenotyping and monitoring tools are the most promising approaches to automatically detect upcoming depressive episodes. Especially, linguistic style has been seen as a potential behavioral marker of depression, as cross-sectional studies showed, for example, less frequent use of positive emotion words, intensified use of negative emotion words, and more self-references in patients with depression compared to healthy controls. However, longitudinal studies are sparse and therefore it remains unclear whether within-person fluctuations in depression severity are associated with individuals\' linguistic style.
METHODS: To capture affective states and concomitant speech samples longitudinally, we used an ambulatory assessment approach sampling multiple times a day via smartphones in patients diagnosed with depressive disorder undergoing sleep deprivation therapy. This intervention promises a rapid change of affective symptoms within a short period of time, assuring sufficient variability in depressive symptoms. We extracted word categories from the transcribed speech samples using the Linguistic Inquiry and Word Count.
RESULTS: Our analyses revealed that more pleasant affective momentary states (lower reported depression severity, lower negative affective state, higher positive affective state, (positive) valence, energetic arousal and calmness) are mirrored in the use of less negative emotion words and more positive emotion words.
CONCLUSIONS: We conclude that a patient\'s linguistic style, especially the use of positive and negative emotion words, is associated with self-reported affective states and thus is a promising feature for speech-based automated monitoring and prediction of upcoming episodes, ultimately leading to better patient care.

BACKGROUND: The racial/ethnic and gender disparities in cardiovascular disease (CVD) morbidity and mortality in the United States are evident. Across nearly every metric, non-Hispanic Black women have poorer overall cardiovascular health. Emerging evidence shows a disproportionately high burden of increased CVD risk factors in Black women of childbearing age, which has a far-reaching impact on both maternal and child outcomes, resulting in premature onset of CVD and further widens the racial disparities in CVD. There is growing recognition that the fundamental driver of persistent racial/ethnic disparities in CVD, as well as disparities in behavioral risk factors such as physical activity and sleep, is structural racism. Further, the lived personal experience of racial discrimination not only has a negative impact on health behaviors, but also links to various physiological pathways to CVD risks, such as internalized stress resulting in a pro-inflammatory state. Limited research, however, has examined the interaction between daily experience and health behaviors, which are influenced by upstream social determinants of health, and the downstream effect on biological/physiological indicators of cardiovascular health in non-pregnant Black women of childbearing age.
METHODS: The BLOOM Study is an observational study that combines real-time ambulatory assessments over a 10-day monitoring period with in-depth cross-sectional lab-based physiological and biological assessments. We will use a wrist-worn actigraphy device to capture 24-h movement behaviors and electronic ecological momentary assessment to capture perceived discrimination, microaggression, and stress. Blood pressure will be captured continuously through a wristband. Saliva samples will be self-collected to assess cortisol level as a biomarker of psychological stress. Lab assessments include a fasting venous blood sample, and assessment of various indices of peripheral and cerebral vascular function/health. Participants\' address or primary residence will be used to obtain neighborhood-level built environmental and social environmental characteristics. We plan to enroll 80 healthy Black women who are between 18 and 49 years old for this study.
CONCLUSIONS: Results from this study will inform the development of multilevel (i.e., individual, interpersonal, and social-environmental levels) lifestyle interventions tailored to Black women based on their lived experiences with the goal of reducing CVD risk.
RESULTS:
UNASSIGNED: NCT06150989.

OBJECTIVE: Schizotypy is a useful and unifying construct for examining the etiology, development, and expression of schizophrenia-spectrum psychopathology. The positive, negative, and disorganized schizotypy dimensions are associated with distinct patterns of schizophrenia-spectrum symptoms and impairment. Furthermore, they are differentiated by mean levels of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, and by temporal dynamics of affect. The schizotypy dimensions were thus hypothesized to be differentiated by the temporal dynamics of schizotypic experiences in daily life.
METHODS: The present study employed experience sampling methodology in a large nonclinically ascertained sample (n = 693) to examine the associations of multidimensional schizotypy with psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, as well as with their temporal dynamics (variability, reactivity, inertia, and instability).
RESULTS: We replicated the mean-level associations between multidimensional schizotypy and schizotypic experiences in daily life. Furthermore, positive, negative, and disorganized schizotypy demonstrated hypothesized, differential patterns of temporal dynamics of schizotypic experiences. Disorganized schizotypy demonstrated the most robust associations, including intensity, variability, and inertia of disorganized schizotypic experiences. Disorganized schizotypy also moderated reactivity of psychotic-like and disorganized schizotypic experiences following previously reported stress. Positive schizotypy was associated with intensity and variability of psychotic-like experiences. Negative schizotypy was associated with intensity and variability of negative schizotypic experiences.
CONCLUSIONS: The findings indicate that schizotypy dimensions can be differentiated by both mean levels and temporal patterns of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, with disorganized schizotypy uniquely characterized by stress reactivity.