Bright light therapy versus physical exercise to prevent co-occurring depression in adolescents and young adults with attention-deficit/hyperactivity disorder: a multicentre, three-arm, randomised controlled, pilot phase-IIa trial.

Depression is common in attention-deficit/hyperactivity disorder (ADHD), but preventive behavioural interventions are lacking. This randomised controlled, pilot phase-IIa trial aimed to study a physical exercise intervention (EI) and bright light therapy (BLT)-both implemented and monitored in an individual, naturalistic setting via a mobile health (m-health) system-for feasibility of trial design and interventions, and to estimate their effects on depressive symptoms in young people with ADHD. Two hundred seven participants aged 14-45 years were randomised to 10-week add-on intervention of either BLT (10,000 lx; daily 30-min sessions) (n = 70), EI (aerobic and muscle-strengthening activities 3 days/ week) (n = 69), or treatment-as-usual (TAU) (n = 68), of whom 165 (80%) were retained (BLT: n = 54; EI: n = 52; TAU: n = 59). Intervention adherence (i.e. ≥ 80% completed sessions) was very low for both BLT (n = 13, 22%) and EI (n = 4, 7%). Usability of the m-health system to conduct interventions was limited as indicated by objective and subjective data. Safety was high and comparable between groups. Changes in depressive symptoms (assessed via observer-blind ratings, Inventory of Depressive Symptomatology) between baseline and end of intervention were small (BLT: -0.124 [95% CI: -2.219, 1.971], EI: -2.646 [95% CI: -4.777, -0.515], TAU: -1.428 [95% CI: -3.381, 0.526]) with no group differences [F(2,153) = 1.45, p = 0.2384]. These findings suggest that the m-health approach did not achieve feasibility of EI and BLT in young people with ADHD. Prior to designing efficacy studies, strategies how to achieve high intervention adherence should be specifically investigated in this patient group. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03371810, 13 December 2017.

The ReCoDe addiction research consortium: Losing and regaining control over drug intake-Findings and future perspectives.

Substance use disorders (SUDs) are seen as a continuum ranging from goal-directed and hedonic drug use to loss of control over drug intake with aversive consequences for mental and physical health and social functioning. The main goals of our interdisciplinary German collaborative research centre on Losing and Regaining Control over Drug Intake (ReCoDe) are (i) to study triggers (drug cues, stressors, drug priming) and modifying factors (age, gender, physical activity, cognitive functions, childhood adversity, social factors, such as loneliness and social contact/interaction) that longitudinally modulate the trajectories of losing and regaining control over drug consumption under real-life conditions. (ii) To study underlying behavioural, cognitive and neurobiological mechanisms of disease trajectories and drug-related behaviours and (iii) to provide non-invasive mechanism-based interventions. These goals are achieved by: (A) using innovative mHealth (mobile health) tools to longitudinally monitor the effects of triggers and modifying factors on drug consumption patterns in real life in a cohort of 900 patients with alcohol use disorder. This approach will be complemented by animal models of addiction with 24/7 automated behavioural monitoring across an entire disease trajectory; i.e. from a naïve state to a drug-taking state to an addiction or resilience-like state. (B) The identification and, if applicable, computational modelling of key molecular, neurobiological and psychological mechanisms (e.g., reduced cognitive flexibility) mediating the effects of such triggers and modifying factors on disease trajectories. (C) Developing and testing non-invasive interventions (e.g., Just-In-Time-Adaptive-Interventions (JITAIs), various non-invasive brain stimulations (NIBS), individualized physical activity) that specifically target the underlying mechanisms for regaining control over drug intake. Here, we will report on the most important results of the first funding period and outline our future research strategy.

Modeling Heterogeneity in Temporal Dynamics: Extending Latent State-Trait Autoregressive and Cross-lagged Panel Models to Mixture Distribution Models.

Longitudinal models suited for the analysis of panel data, such as cross-lagged panel or autoregressive latent-state trait models, assume population homogeneity with respect to the temporal dynamics of the variables under investigation. This assumption is likely to be too restrictive in a myriad of research areas. We propose an extension of autoregressive and cross-lagged latent state-trait models to mixture distribution models. The models allow researchers to model unobserved person heterogeneity and qualitative differences in longitudinal dynamics based on comparatively few observations per person, while taking into account temporal dependencies between observations as well as measurement error in the variables. The models are extended to include categorical covariates, to investigate the distribution of encountered latent classes across observed groups. The potential of the models is illustrated with an application to self-esteem and affect data in patients with borderline personality disorder, an anxiety disorder, and healthy control participants. Requirements for the models' applicability are investigated in an extensive simulation study and recommendations for model applications are derived.

Momentary within-subject associations of affective states and physical behavior are moderated by weather conditions in real life: an ambulatory assessment study.

BACKGROUND: Physical behavior (PB) is a key lifestyle factor in regulating and preventing diseases across the lifespan. Researchers identified affective, cognitive, and contextual factors like weather conditions, as significant contributors in determining if individuals are physically active. However, there is scarce empirical evidence about potential associations between PB and affective states influenced by weather conditions in daily life. Therefore, we explored if weather conditions moderated the within-subject association between momentary affective states and subsequent PB. METHODS: Utilizing ambulatory assessment, 79 participants completed electronic diaries about their affective states (i.e., valence, energetic arousal, and calmness) up to six times a day over five days, and their PB (i.e., physical activity and sedentariness) was simultaneously recorded via accelerometers. Weather conditions (i.e., temperature and precipitation) recorded near participants' locations served as moderators in the multilevel analyses. RESULTS: We confirmed earlier findings associating affective states with PB. Increased valence and energetic arousal were positively associated with physical activity (ß = 0.007; p < .001), whereas calmness predicted lower levels of physical activity (ß = -0.006; p < .001). Higher levels of calmness showed a positive association with sedentary behavior (ß = 0.054; p = .003). In addition, we revealed a significant positive association between temperature, as a momentary weather condition, and physical activity (ß = 0.025; p = .015). Furthermore, we showed that the association of affective states and physical activity was moderated by temperature. Higher temperatures enhanced the positive effects of valence on physical activity (ß = .001, p = .023) and attenuated the negative effects of calmness on physical activity (ß = .001, p = .021). Moreover, higher temperatures enhanced the positive effects of valence on reduced sedentary behavior (ß = -0.011, p = .043). CONCLUSIONS: Temperature alterations appeared to have an impact on subsequent physical activity. Furthermore, temperature alterations moderated the influence of affective states on conducted physical activity. This might offer the opportunity for just-in-time adaptive interventions to intervene in individually appropriate environmental conditions for promoting physical activity.

Assessment of 24-hour physical behaviour in adults via wearables: a systematic review of validation studies under laboratory conditions.

BACKGROUND: Wearable technology is used by consumers and researchers worldwide for continuous activity monitoring in daily life. Results of high-quality laboratory-based validation studies enable us to make a guided decision on which study to rely on and which device to use. However, reviews in adults that focus on the quality of existing laboratory studies are missing. METHODS: We conducted a systematic review of wearable validation studies with adults. Eligibility criteria were: (i) study under laboratory conditions with humans (age ≥ 18 years); (ii) validated device outcome must belong to one dimension of the 24-hour physical behavior construct (i.e., intensity, posture/activity type, and biological state); (iii) study protocol must include a criterion measure; (iv) study had to be published in a peer-reviewed English language journal. Studies were identified via a systematic search in five electronic databases as well as back- and forward citation searches. The risk of bias was assessed based on the QUADAS-2 tool with eight signaling questions. RESULTS: Out of 13,285 unique search results, 545 published articles between 1994 and 2022 were included. Most studies (73.8% (N = 420)) validated an intensity measure outcome such as energy expenditure; only 14% (N = 80) and 12.2% (N = 70) of studies validated biological state or posture/activity type outcomes, respectively. Most protocols validated wearables in healthy adults between 18 and 65 years. Most wearables were only validated once. Further, we identified six wearables (i.e., ActiGraph GT3X+, ActiGraph GT9X, Apple Watch 2, Axivity AX3, Fitbit Charge 2, Fitbit, and GENEActiv) that had been used to validate outcomes from all three dimensions, but none of them were consistently ranked with moderate to high validity. Risk of bias assessment resulted in 4.4% (N = 24) of all studies being classified as "low risk", while 16.5% (N = 90) were classified as "some concerns" and 79.1% (N = 431) as "high risk". CONCLUSION: Laboratory validation studies of wearables assessing physical behaviour in adults are characterized by low methodological quality, large variability in design, and a focus on intensity. Future research should more strongly aim at all components of the 24-hour physical behaviour construct, and strive for standardized protocols embedded in a validation framework.

Longitudinal Digital Mood Charting in Bipolar Disorder: Experiences with ChronoRecord Over 20 Years.

INTRODUCTION: Longitudinal study is an essential methodology for understanding disease trajectories, treatment effects, symptom changes, and long-term outcomes of affective disorders. Daily self-charting of mood and other illness-related variables is a commonly recommended intervention. With the widespread acceptance of home computers in the early 2000s, automated tools were developed for patient mood charting, such as ChronoRecord, a software validated by patients with bipolar disorder. The purpose of this study was to summarize the daily mood, sleep, and medication data collected with ChronoRecord, and highlight some of the key research findings. Lessons learned from implementing a computerized tool for patient self-reporting are also discussed. METHODS: After a brief training session, ChronoRecord software for daily mood charting was installed on a home computer and used by 609 patients with affective disorders. RESULTS: The mean age of the patients was 40.3±11.8 years, a mean age of onset was 22±11.2 years, and 71.4% were female. Patients were euthymic for 70.8% of days, 15.1% had mild depression, 6.6% had severe depression, 6.6% had hypomania, and 0.8% had mania. Among all mood groups, 22.4% took 1-2 medications, 37.2% took 3-4 medications, 25.7 took 5-6 medications, 11.6% took 7-8 medications, and 3.1% took >8 medications. CONCLUSION: The daily mood charting tool is a useful tool for increasing patient involvement in their care, providing detailed patient data to the physician, and increasing understanding of the course of illness. Longitudinal data from patient mood charting was helpful in both clinical and research settings.

Measuring self-regulation in everyday life: Reliability and validity of smartphone-based experiments in alcohol use disorder.

Self-regulation, the ability to guide behavior according to one's goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test-retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures' construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks.

Mobile Data Collection of Cognitive-Behavioral Tasks in Substance Use Disorders: Where Are We Now?

INTRODUCTION: Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. METHOD: In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. RESULTS: Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that - although more systematic studies are necessary - task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. CONCLUSION: Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.

Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application.

BACKGROUND: Understanding which factors influence dietary intake, particularly in daily life, is crucial given the impact diet has on physical as well as mental health. However, a factor might influence whether but not how much an individual eats and vice versa or a factor's importance may differ across these two facets. Distinguishing between these two facets, hence, studying dietary intake as a dual process is conceptually promising and not only allows further insights, but also solves a statistical issue. When assessing the association between a predictor (e.g. momentary affect) and subsequent dietary intake in daily life through ecological momentary assessment (EMA), the outcome variable (e.g. energy intake within a predefined time-interval) is semicontinuous. That is, one part is equal to zero (i.e. no dietary intake occurred) and the other contains right-skewed positive values (i.e. dietary intake occurred, but often only small amounts are consumed). However, linear multilevel modelling which is commonly used for EMA data to account for repeated measures within individuals cannot be applied to semicontinuous outcomes. A highly informative statistical approach for semicontinuous outcomes is multilevel two-part modelling which treats the outcome as generated by a dual process, combining a multilevel logistic/probit regression for zeros and a multilevel (generalized) linear regression for nonzero values. METHODS: A multilevel two-part model combining a multilevel logistic regression to predict whether an individual eats and a multilevel gamma regression to predict how much is eaten, if an individual eats, is proposed. Its general implementation in R, a widely used and freely available statistical software, using the R-package brms is described. To illustrate its practical application, the analytical approach is applied exemplary to data from the Eat2beNICE-APPetite-study. RESULTS: Results highlight that the proposed multilevel two-part model reveals process-specific associations which cannot be detected through traditional multilevel modelling. CONCLUSIONS: This paper is the first to introduce multilevel two-part modelling as a novel analytical approach to study dietary intake in daily life. Studying dietary intake through multilevel two-part modelling is conceptually as well as methodologically promising. Findings can be translated to tailored nutritional interventions targeting either the occurrence or the amount of dietary intake.

Drivers of productivity: Being physically active increases yet sedentary bouts and lack of sleep decrease work ability.

Physical behavior (ie, physical activity, sedentary behavior, and sleep) is a crucial lifestyle factor for preventing and managing diseases across the lifespan. However, less is known about potential work-related psychological and cognitive outcomes such as productivity. The present study examined within-person associations between physical behavior and self-perceived work ability. To investigate the degree to which physical behavior parameters influence self-perceived work ability in everyday life, we conducted an Ambulatory Assessment study in 103 university students over 5 days. Physical behavior was assessed continuously via a multi-sensor system. Self-perceived work ability was assessed repeatedly up to six times per day on smartphones. We employed multilevel modeling to analyze the within-person effects of physical behavior on self-perceived work ability. Physical activity intensity (MET) (ß = 0.15 ± 0.06, t = 2.59, p = 0.012) and sit-to-stand transitions (ß = 0.07 ± 0.03, t = 2.44, p = 0.015) were positively associated with self-perceived work ability. Sedentary bouts (≥20 min) (ß = -0.21 ± 0.08, t = -2.74, p = 0.006) and deviation from a recommended sleep duration (ie, 8 h) (ß = -0.1 ± 0.04, t = -2.38, p = 0.018) were negatively associated with self-perceived work ability. Exploratory analyses supported the robustness of our findings by comparing various time frames. Total sedentary time and sleep quality were not associated with self-perceived work ability. Regular sleep durations, breaking up sedentary time through sit-to-stand transitions, and higher intensities of physical activity may be important for the regulation of self-perceived work ability in university students' daily lives.

Studying Microtemporal, Within-Person Processes of Diet, Physical Activity, and Related Factors Using the APPetite-Mobile-App: Feasibility, Usability, and Validation Study.

BACKGROUND: Diet and physical activity (PA) have a major impact on physical and mental health. However, there is a lack of effective strategies for sustaining these health-protective behaviors. A shift to a microtemporal, within-person approach is needed to capture dynamic processes underlying eating behavior and PA, as they change rapidly across minutes or hours and differ among individuals. However, a tool that captures these microtemporal, within-person processes in daily life is currently not present. OBJECTIVE: The APPetite-mobile-app is developed for the ecological momentary assessment of microtemporal, within-person processes of complex dietary intake, objectively recorded PA, and related factors. This study aims to evaluate the feasibility and usability of the APPetite-mobile-app and the validity of the incorporated APPetite-food record. METHODS: The APPetite-mobile-app captures dietary intake event-contingently through a food record, captures PA continuously through accelerometers, and captures related factors (eg, stress) signal-contingently through 8 prompts per day. Empirical data on feasibility (n=157), usability (n=84), and validity (n=44) were collected within the Eat2beNICE-APPetite-study. Feasibility and usability were examined in healthy participants and psychiatric patients. The relative validity of the APPetite-food record was assessed with a subgroup of healthy participants by using a counterbalanced crossover design. The reference method was a 24-hour recall. In addition, the energy intake was compared with the total energy expenditure estimated from accelerometry. RESULTS: Good feasibility, with compliance rates above 80% for prompts and the accelerometer, as well as reasonable average response and recording durations (prompt: 2.04 min; food record per day: 17.66 min) and latencies (prompts: 3.16 min; food record: 58.35 min) were found. Usability was rated as moderate, with a score of 61.9 of 100 on the System Usability Scale. The evaluation of validity identified large differences in energy and macronutrient intake between the two methods at the group and individual levels. The APPetite-food record captured higher dietary intakes, indicating a lower level of underreporting, compared with the 24-hour recall. Energy intake was assessed fairly accurately by the APPetite-food record at the group level on 2 of 3 days when compared with total energy expenditure. The comparison with mean total energy expenditure (2417.8 kcal, SD 410) showed that the 24-hour recall (1909.2 kcal, SD 478.8) underestimated habitual energy intake to a larger degree than the APPetite-food record (2146.4 kcal, SD 574.5). CONCLUSIONS: The APPetite-mobile-app is a promising tool for capturing microtemporal, within-person processes of diet, PA, and related factors in real time or near real time and is, to the best of our knowledge, the first of its kind. First evidence supports the good feasibility and moderate usability of the APPetite-mobile-app and the validity of the APPetite-food record. Future findings in this context will build the foundation for the development of personalized lifestyle modification interventions, such as just-in-time adaptive interventions.

High-frequency ecological momentary assessment of emotional and interpersonal states preceding and following self-injury in female adolescents.

Non-suicidal self-injury (NSSI) is a considerable health problem among adolescents. Affect regulation by means of self-injury may promote the maintenance of NSSI. However, existing findings have limited ecological validity. The present study aimed to assess emotional and interpersonal states preceding and following incidents of NSSI in female adolescents. Adolescents with NSSI-disorder completed ecological momentary assessments of affective and interpersonal states on an hourly basis for multiple days. Multilevel mixed-effect regression analyses were conducted to assess antecedences and consequences of acts of self-injury. Data from n = 73 female adolescents covering a total of 52 acts of self-injury were available for analyses. The urge to self-injure on the between subject-level and negative affect on the within-level were best predictors of self-injury. Surprisingly, self-injury increased negative affect and decreased feelings of attachment (mother only) in the following hour. In line with findings in adults, results illustrate the important association between negative affect and self-injury in female adolescents. However, the occurrence of NSSI itself was related to concurrent increases in negative affect, and even prospectively predicted a consecutive increase in negative affect. Therefore, improvements of negative affect following (or during) self-injury, as previously reported, are at best short-lived (< 1 h).

Addiction Research Consortium: Losing and regaining control over drug intake (ReCoDe)-From trajectories to mechanisms and interventions.

One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12-year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism-based interventions. These goals will be achieved by: (i) using mobile health (m-health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real-life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal-directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake.

Momentary mood predicts upcoming real-life sedentary behavior.

Humans in the industrialized world spend a large amount of daily time in sedentary behavior. Since sedentariness negatively impacts a variety of psychophysiological outcomes, the identification of antecedents that lead to sedentary behavior is an important public health issue. In this context, mood, a central indicator for both psychological well-being and mental health, is severely understudied. To investigate whether mood dimensions influence subsequent sedentary behavior, we assessed both constructs at baseline via questionnaires and via ambulatory assessment (AA) over 5 days in 92 university employees. We continuously measured sedentary behavior using accelerometers and assessed mood repeatedly 10 times each day on smartphone diaries. We employed multiple regression analyses to analyze between-subject effects and multilevel modeling to analyze within-subject effects. Higher momentary ratings of valence (P < .05) and energetic arousal (P < .01) predicted lower amounts of subsequent sedentary behavior, whereas higher ratings of calmness (P < .01) predicted higher amounts of subsequent sedentary behavior. The context moderated the effect of energetic arousal and calmness on sedentary behavior with increased effects in the home compared to the work context. Mood significantly predicted sedentary behavior on a within-subject level but not on a between-subject level. Preliminary evidence suggests that mood regulates sedentary behavior in everyday life. Time-sensitive analyses, such as from moment to moment revealed an association between mood and sedentary behavior (within-subject), whereas analyses between different individuals revealed no associations (between-subject). These preliminary findings may inform multicomponent intervention strategies that target mood, to reduce sedentary behavior in daily life.

Relationships between incidental physical activity, exercise, and sports with subsequent mood in adolescents.

Physical activity is beneficial for human physical health and well-being. Accordingly, the association between physical activity and mood in everyday life has been a subject of several Ambulatory Assessment studies. This mechanism has been studied in children, adults, and the elderly, but neglected in adolescents. It is critical to examine this mechanism in adolescents because adolescence plays a key role in human development and adolescents' physical activity behavior translates into their behavior in adulthood. We investigated adolescents' mood in relation to distinct physical activities: incidental activity such as climbing stairs; exercise activity, such as skating; and sports, such as playing soccer. We equipped 134 adolescents aged 12-17 years with accelerometers and GPS-triggered electronic diaries to use in their everyday life. Adolescents reported on mood repeatedly in real time across 7 days, and these data were analyzed using multilevel-modeling. After incidental activity, adolescents felt better and more energized. After exercise, adolescents felt better but less calm. After sports, adolescents felt less energized. Analyses of the time course of the effects confirmed our findings. Physical activity influences mood in adolescents' everyday life, but has distinct effects depending on the kind of physical activity. Our results suggest incidental and exercise activities entail higher post-bout valence compared to sports in competitive settings. These findings may serve as an important empirical basis for the targeted application of distinct physical activities to foster well-being in adolescence.

Ambulatory Assessment for Physical Activity Research: State of the Science, Best Practices and Future Directions.

Technological and digital progress benefits physical activity (PA) research. Here we compiled expert knowledge on how Ambulatory Assessment (AA) is utilized to advance PA research, i.e., we present results of the 2nd International CAPA Workshop 2019 "Physical Activity Assessment - State of the Science, Best Practices, Future Directions" where invited researchers with experience in PA assessment, evaluation, technology and application participated. First, we provide readers with the state of the AA science, then we give best practice recommendations on how to measure PA via AA and shed light on methodological frontiers, and we furthermore discuss future directions. AA encompasses a class of methods that allows the study of PA and its behavioral, biological and physiological correlates as they unfold in everyday life. AA includes monitoring of movement (e.g., via accelerometry), physiological function (e.g., via mobile electrocardiogram), contextual information (e.g., via geolocation-tracking), and ecological momentary assessment (EMA; e.g., electronic diaries) to capture self-reported information. The strengths of AA are data assessment that near realtime, which minimizes retrospective biases in real-world settings, consequentially enabling ecological valid findings. Importantly, AA enables multiple assessments across time within subjects resulting in intensive longitudinal data (ILD), which allows unraveling within-person determinants of PA in everyday life. In this paper, we show how AA methods such as triggered e-diaries and geolocation-tracking can be used to measure PA and its correlates, and furthermore how these findings may translate into real-life interventions. In sum, AA provides numerous possibilities for PA research, especially the opportunity to tackle within- subject antecedents, concomitants, and consequences of PA as they unfold in everyday life. In-depth insights on determinants of PA could help us design and deliver impactful interventions in real-world contexts, thus enabling us to solve critical health issues in the 21st century such as insufficient PA and high levels of sedentary behavior.

Sedentary behavior in everyday life relates negatively to mood: An ambulatory assessment study.

Empirical evidence shows that physical behavior positively impacts human health. Recently, researchers have started to differentiate between physical activity and sedentary behavior showing independent effects on somatic health. However, whether this differentiation is also relevant for mood dimensions is largely unknown. For investigating the dynamic relationships between sedentary behavior and mood dimensions in daily life, ambulatory assessment (AA) has become the state-of-the-art methodology. To investigate whether sedentary behaviors influence mood dimensions, we conducted an AA study in the everyday life of 92 university employees over 5 days. We continuously measured sedentary behavior via accelerometers and assessed mood repeatedly 10 times each day on smartphone diaries. To optimize our sampling strategy, we used a sophisticated sedentary-triggered algorithm. We employed multilevel modeling to analyze the within-subject effects of sedentary behavior on mood. Sedentary time (15-minute intervals prior to each e-diary assessment) and sedentary bouts (30-minute intervals of uninterrupted sedentary behavior) negatively influenced valence and energetic arousal (all Ps < 0.015). In particular, the more participants were sedentary in their everyday life, the less they felt well and energized. Exploratory analyses of the temporal course of these effects supported our findings. Sedentary behavior can be seen as a general risk factor because it impacts both somatic and mental health. Most importantly, physical activity and sedentary behavior showed independent effects on mood dimensions. Accordingly, future studies should consider the two sides of the physical behavior coin: How should physical activity be promoted? and How can sedentary behavior be reduced?

Effectiveness of smartphone-based ambulatory assessment (SBAA-BD) including a predicting system for upcoming episodes in the long-term treatment of patients with bipolar disorders: study protocol for a randomized controlled single-blind trial.

BACKGROUND: The detection of early warning signs is essential in the long-term treatment of bipolar disorders. However, in bipolar patients' daily life and outpatient treatment the assessment of upcoming state changes faces several difficulties. In this trial, we examine the effectiveness of a smartphone based automated feedback about ambulatory assessed early warning signs in prolonging states of euthymia and therefore preventing hospitalization. This study aims to assess, whether patients experience longer episodes of euthymia, when their treating psychiatrists receive automated feedback about changes in communication and activity. With this additional information an intervention at an earlier stage in the development of mania or depression could be facilitated. We expect that the amount of time will be longer between affective episodes in the intervention group. METHODS/DESIGN: The current study is designed as a randomized, multi-center, observer-blind, active-control, parallel group trial within a nationwide research project on the topic of innovative methods for diagnostics, prevention and interventions of bipolar disorders. One hundred and twenty patients with bipolar disorder will be randomly assigned to (1) the experimental group with included automated feedback or (2) the control group without feedback. During the intervention phase, the psychopathologic state of all participants is assessed every four weeks over 18 months. Kaplan-Meier estimators will be used for estimating the survival functions, a Log-Rank test will be used to formally compare time to a new episode across treatment groups. An intention-to-treat analysis will include data from all randomized patients. DISCUSSION: This article describes the design of a clinical trial investigating the effectiveness of a smartphone-based feedback loop. This feedback loop is meant to elicit early interventions at the detection of warning signs for the prevention of affective episodes in bipolar patients. This approach will hopefully improve the chances of a timely intervention helping patients to keep a balanced mood for longer periods of time. In detail, if our hypothesis can be confirmed, clinical practice treating psychiatrists will be enabled to react quickly when changes are automatically detected. Therefore, outpatients would receive an even more individually tailored treatment concerning time and frequency of doctor's appointments. TRIAL REGISTRATION: ClinicalTrials.gov : NCT02782910 : Title: "Smartphone-based Ambulatory Assessment of Early Warning Signs (BipoLife_A3)". Registered May 25 2016. Protocol Amendment Number: 03. Issue Date: 26 March 2018. Author(s): ES.

Classical conditioning in borderline personality disorder: an fMRI study.

Previous research suggests disturbed emotional learning and memory in borderline personality disorder (BPD). Studies investigating the neural correlates of aversive differential delay conditioning in BPD are currently lacking. We aimed to investigate acquisition, within-session extinction, between-session extinction recall, and reacquisition. We expected increased activation in the insula, amygdala, and anterior cingulate, and decreased prefrontal activation in BPD patients. During functional magnetic resonance imaging, 27 medication-free female BPD patients and 26 female healthy controls (HC) performed a differential delay aversive conditioning paradigm. An electric shock served as unconditioned stimulus, two neutral pictures as conditioned stimuli (CS+/CS-). Dependent variables were blood-oxygen-level-dependent response, skin conductance response (SCR), and subjective ratings (valence, arousal). No significant between-group differences in brain activation were found [all p(FDR) > 0.05]. Within-group comparisons for CS+unpaired > CS- revealed increased insula activity in BPD patients but not in HC during early acquisition; during late acquisition, both groups recruited fronto-parietal areas [p(FDR) < 0.05]. During extinction, BPD patients rated both CS+ and CS- as significantly more arousing and aversive than HC and activated the amygdala in response to CS+. In contrast, HC showed increased prefrontal activity in response to CS+ > CS during extinction. During extinction recall, there was a trend for stronger SCR to CS+ > CS in BPD patients. Amygdala habituation to CS+paired (CS+ in temporal contingency with the aversive event) during acquisition was found in HC but not in patients. Our findings suggest altered temporal response patterns in terms of increased vigilance already during early acquisition and delayed extinction processes in individuals with BPD.

Does a 20-week aerobic exercise training programme increase our capabilities to buffer real-life stressors? A randomized, controlled trial using ambulatory assessment.

PURPOSE: The cross-stressor adaptation hypothesis suggests that regular exercise leads to adaptations in the stress response systems that induce decreased physiological responses to psychological stressors. Even though an exercise intervention to buffer the detrimental effects of psychological stressors on health might be of utmost importance, empirical evidence is mixed. This may be explained by the use of cross-sectional designs and non-personally relevant stressors. Using a randomized controlled trial, we hypothesized that a 20-week aerobic exercise training does reduce physiological stress responses to psychological real-life stressors in sedentary students. METHODS: Sixty-one students were randomized to either a control group or an exercise training group. The academic examination period (end of the semester) served as a real-life stressor. We used ambulatory assessment methods to assess physiological stress reactivity of the autonomic nervous system (heart rate variability: LF/HF, RMSSD), physical activity and perceived stress during 2 days of everyday life and multilevel models for data analyses. Aerobic capacity (VO2max) was assessed pre- and post-intervention via cardiopulmonary exercise testing to analyze the effectiveness of the intervention. RESULTS: During real-life stressors, the exercise training group showed significantly reduced LF/HF (ß = -0.15, t = -2.59, p = .01) and increased RMSSD (ß = 0.15, t = 2.34, p = .02) compared to the control group. CONCLUSIONS: Using a randomized controlled trial and a real-life stressor, we could show that exercise appears to be a useful preventive strategy to buffer the effects of stress on the autonomic nervous system, which might result into detrimental health outcomes.