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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. CONCLUSION: 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.
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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.
Subject(s)
Substance-Related Disorders , Humans , Animals , Germany , Behavior, Addictive , AlcoholismABSTRACT
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.
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BACKGROUND: The interplay of physical activity (PA) with affective well-being (AWB) is highly critical to both health behaviors and health outcomes. Current prominent theories presume AWB to be crucial for PA maintenance, and PA is evidenced to foster mental health. However, thus far, PA-AWB associations have mainly been researched in laboratory settings and with interventional designs, but the everyday life perspective had not been focused on, mostly due to technological limitations. In the course of digitization, the number of studies using device-based methods to research the within-subject association of physical activity and affective well-being (PA-AWB) under ecological valid conditions increased rapidly, but a recent comprehensive systematic review of evidence across populations, age groups, and distinct AWB components remained inconclusive. OBJECTIVES: Therefore, we aimed to firstly review daily-life studies that assessed intensive longitudinal device-based (e.g., electronic smartphone diaries and accelerometry) and real-time PA-AWB data, secondly to develop and apply a quality assessment tool applicable to those studies, and thirdly to discuss findings and draw implications for research and practice. METHODS: To this end, the literature was searched in three databases (Web of Science, PubMed, Scopus) up to November 2022. The systematic review followed the PRISMA guidelines and had been pre-registered (PROSPERO id: CRD42021277327). A modified quality assessment tool was developed to illustrate the risk of bias of included studies. RESULTS: The review of findings showed that, in general, already short PA bouts in everyday life, which clearly differ from structured exercise sessions, are positively associated with AWB. In particular, feelings of energy relate to incidental (non-exercise and unstructured) activity, and PA-AWB associations depend on population characteristics. The quality assessment revealed overall moderate study quality; however, the methods applied were largely heterogeneous between investigations. Overall, the reviewed evidence on PA-AWB associations in everyday life is ambiguous; for example, no clear patterns of directions and strengths of PA-AWB relationships depending on PA and AWB components (such as intensity, emotions, affect, mood) emerged. CONCLUSIONS: The reviewed evidence can fuel discussions on whether the World Health Organization's notion "every move counts" may be extended to everyday life AWB. Concurrently, the PA-AWB relationship findings endorse prominent theories highlighting the critical role of AWB in everyday PA engagement and maintenance. However, the review also clearly highlights the need to advance and harmonize methodological approaches for more fine-grained investigations on which specific PA/AWB characteristics, contextual factors, and biological determinants underly PA-AWB associations in everyday life. This will enable the field to tackle pressing challenges such as the issue of causality of PA-AWB associations, which will help to shape and refine existing theories to ultimately predict and improve health behavior, thereby feeding into precision medicine approaches.
Subject(s)
Affect , Exercise , Mental Health , Humans , Exercise/psychology , Accelerometry , Health Behavior , SmartphoneABSTRACT
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.
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BACKGROUND: Understanding the biological processes that underlie individual differences in emotion regulation and stress responsivity is a key challenge for translational neuroscience. The gene FKBP5 is a core regulator in molecular stress signaling that is implicated in the development of psychiatric disorders. However, it remains unclear how FKBP5 DNA methylation in peripheral blood is related to individual differences in measures of neural structure and function and their relevance to daily-life stress responsivity. METHODS: Here, we characterized multimodal correlates of FKBP5 DNA methylation by combining epigenetic data with neuroimaging and ambulatory assessment in a sample of 395 healthy individuals. RESULTS: First, we showed that FKBP5 demethylation as a psychiatric risk factor was related to an anxiety-associated reduction of gray matter volume in the ventromedial prefrontal cortex, a brain area that is involved in emotion regulation and mental health risk and resilience. This effect of epigenetic upregulation of FKBP5 on neuronal structure is more pronounced where FKBP5 is epigenetically downregulated at baseline. Leveraging 208 functional magnetic resonance imaging scans during a well-established emotion-processing task, we found that FKBP5 DNA methylation in peripheral blood was associated with functional differences in prefrontal-limbic circuits that modulate affective responsivity to daily stressors, which we measured using ecological momentary assessment in daily life. CONCLUSIONS: Overall, we demonstrated how FKBP5 contributes to interindividual differences in neural and real-life affect regulation via structural and functional changes in prefrontal-limbic brain circuits.
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OBJECTIVE: Alcohol use disorder (AUD) constitutes a critical public health issue and has sex-specific characteristics. Initial evidence suggests that progesterone and estradiol might reduce or increase alcohol intake, respectively. However, there is a need for a better understanding of how the menstrual cycle in females and the ratio of progesterone to estradiol in females and males influence alcohol use patterns in individuals with AUD. METHODS: In this sex-separated multicenter longitudinal study, the authors analyzed 12-month data on real-life alcohol use (from 21,460 smartphone entries), menstrual cycle, and serum progesterone-to-estradiol ratios (from 667 blood samples at four individual study visits) in 74 naturally cycling females and 278 males with AUD between 2020 and 2022, using generalized and general linear mixed modeling. RESULTS: Menstrual cycle phases were significantly associated with binge drinking and progesterone-to-estradiol ratio. During the late luteal phase, females showed a lower predicted binge drinking probability of 13% and a higher predicted marginal mean of progesterone-to-estradiol ratio of 95 compared with during the menstrual, follicular, and ovulatory phases (binge drinking probability and odds ratios vs. late luteal phase, respectively: 17%, odds ratio=1.340, 95% CI=1.031, 1.742; 19%, odds ratio=1.523, 95% CI=1.190, 1.949; and 20%, odds ratio=1.683, 95% CI=1.285, 2.206; difference in progesterone-to-estradiol ratios, respectively: -61, 95% CI=-105.492, -16.095; -78, 95% CI=-119.322, -37.039; and -71, 95% CI=-114.568, -27.534). In males, a higher progesterone-to-estradiol ratio was related to lower probabilities of binge drinking and of any alcohol use, with a 10-unit increase in the hormone ratio resulting in odds ratios of 0.918 (95% CI=0.843, 0.999) and 0.914 (95% CI=0.845, 0.988), respectively. CONCLUSIONS: These ecologically valid findings suggest that high progesterone-to-estradiol ratios can have a protective effect against problematic alcohol use in females and males with AUD, highlighting the progesterone-to-estradiol ratio as a promising treatment target. Moreover, the results indicate that females with AUD may benefit from menstrual cycle phase-tailored treatments.
Subject(s)
Alcohol Drinking , Alcoholism , Estradiol , Menstrual Cycle , Progesterone , Humans , Female , Estradiol/blood , Progesterone/blood , Male , Adult , Menstrual Cycle/blood , Longitudinal Studies , Alcoholism/blood , Alcoholism/epidemiology , Alcohol Drinking/blood , Alcohol Drinking/epidemiology , Binge Drinking/blood , Binge Drinking/epidemiology , Sex Factors , Middle Aged , Young AdultABSTRACT
BACKGROUND: The use of mobile devices to continuously monitor objectively extracted parameters of depressive symptomatology is seen as an important step in the understanding and prevention of upcoming depressive episodes. Speech features such as pitch variability, speech pauses, and speech rate are promising indicators, but empirical evidence is limited, given the variability of study designs. OBJECTIVE: Previous research studies have found different speech patterns when comparing single speech recordings between patients and healthy controls, but only a few studies have used repeated assessments to compare depressive and nondepressive episodes within the same patient. To our knowledge, no study has used a series of measurements within patients with depression (eg, intensive longitudinal data) to model the dynamic ebb and flow of subjectively reported depression and concomitant speech samples. However, such data are indispensable for detecting and ultimately preventing upcoming episodes. METHODS: In this study, we captured voice samples and momentary affect ratings over the course of 3 weeks in a sample of patients (N=30) with an acute depressive episode receiving stationary care. Patients underwent sleep deprivation therapy, a chronotherapeutic intervention that can rapidly improve depression symptomatology. We hypothesized that within-person variability in depressive and affective momentary states would be reflected in the following 3 speech features: pitch variability, speech pauses, and speech rate. We parametrized them using the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS) from open-source Speech and Music Interpretation by Large-Space Extraction (openSMILE; audEERING GmbH) and extracted them from a transcript. We analyzed the speech features along with self-reported momentary affect ratings, using multilevel linear regression analysis. We analyzed an average of 32 (SD 19.83) assessments per patient. RESULTS: Analyses revealed that pitch variability, speech pauses, and speech rate were associated with depression severity, positive affect, valence, and energetic arousal; furthermore, speech pauses and speech rate were associated with negative affect, and speech pauses were additionally associated with calmness. Specifically, pitch variability was negatively associated with improved momentary states (ie, lower pitch variability was linked to lower depression severity as well as higher positive affect, valence, and energetic arousal). Speech pauses were negatively associated with improved momentary states, whereas speech rate was positively associated with improved momentary states. CONCLUSIONS: Pitch variability, speech pauses, and speech rate are promising features for the development of clinical prediction technologies to improve patient care as well as timely diagnosis and monitoring of treatment response. Our research is a step forward on the path to developing an automated depression monitoring system, facilitating individually tailored treatments and increased patient empowerment.
Subject(s)
Depressive Disorder , Speech , Humans , Pilot Projects , Depression/therapy , Sleep DeprivationABSTRACT
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.
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Self Concept , Humans , Computer SimulationABSTRACT
OBJECTIVE: To examine the daily course of, and factors associated with, momentary fatigue after subarachnoid haemorrhage, and to explore subgroups of patients with distinct diurnal patterns of fatigue. DESIGN: Observational study using ecological momentary assessment. SUBJECTS: A total of 41 participants with subarachnoid haemorrhage. METHODS: Patients with fatigue were included within one year post-onset. Momentary fatigue (scale 1-7) was assessed with repeated measurements (10-11 times/day) during 7 consecutive days. Multilevel-mixed-model analyses and latent-class trajectory modelling were conducted. RESULTS: Mean (standard deviation; SD) age of the group was 53.9 (13.0) years, 56% female, and mean (SD) time post-subarachnoid haemorrhage onset was 9.3 (3.2) months. Mean (SD) momentary fatigue over all days was 3.22 (1.47). Fatigue increased significantly (p < 0.001) over the day, and experiencing more burden of fatigue and day type (working day vs weekend day) were significantly (p < 0.05) associated with higher momentary fatigue. Three subgroups could be distinguished based on diurnal patterns of fatigue. The largest group (n = 17, 41.5%) showed an increasing daily pattern of fatigue. CONCLUSION: Momentary fatigue in patients with subarachnoid haemorrhage increases over the day, and diurnal patterns of fatigue differ between participants. In addition to conventional measures, momentary measures of fatigue might provide valuable information for physicians to optimize personalized management of fatigue after subarachnoid haemorrhage.
Subject(s)
Ecological Momentary Assessment , Subarachnoid Hemorrhage , Female , Humans , Male , Middle Aged , Fatigue/etiology , Subarachnoid Hemorrhage/complications , Adult , AgedABSTRACT
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.
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Bipolar Disorder , Depressive Disorder , Humans , Female , Adult , Middle Aged , Child , Adolescent , Young Adult , Male , Bipolar Disorder/drug therapy , Longitudinal Studies , Mood Disorders , ManiaABSTRACT
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.
Subject(s)
Affect , Emotions , Humans , Affect/physiology , Exercise/psychology , Sedentary Behavior , WeatherABSTRACT
BACKGROUND: Increasing attention is being paid to lifestyle factors, such as nutrition and physical activity (PA), as potential complementary treatment options in attention-deficit/hyperactivity disorder (ADHD). Previous research indicates that sugar and saturated fat intake may be linked to increased impulsivity, a core symptom of ADHD, whereas protein intake and PA may be related to reduced impulsivity. However, most studies rely on cross-sectional data that lack microtemporal resolution and ecological validity, wherefore questions of microtemporal dynamics (eg, is the consumption of foods high in sugar associated with increased impulsivity within minutes or hours?) remain largely unanswered. Ecological momentary assessment (EMA) has the potential to bridge this gap. OBJECTIVE: This study is the first to apply EMA to assess microtemporal associations among macronutrient intake, PA, and state impulsivity in the daily life of adults with and without ADHD. METHODS: Over a 3-day period, participants reported state impulsivity 8 times per day (signal-contingent), recorded food and drink intake (event-contingent), and wore an accelerometer. Multilevel 2-part models were used to study the association among macronutrient intake, PA, and the probability to be impulsive as well as the intensity of impulsivity (ADHD: n=36; control: n=137). RESULTS: No association between macronutrient intake and state impulsivity was found. PA was not related to the intensity of impulsivity but to a higher probability to be impulsive (ADHD: ß=-.09, 95% CI -0.14 to -0.04; control: ß=-.03, 95% CI -0.05 to -0.01). No evidence was found that the combined intake of saturated fat and sugar amplified the increase in state impulsivity and that PA alleviated the positive association between sugar or fat intake and state impulsivity. CONCLUSIONS: Important methodological considerations are discussed that can contribute to the optimization of future EMA protocols. EMA research in the emerging field of nutritional psychiatry is still in its infancy; however, EMA is a highly promising and innovative approach as it offers insights into the microtemporal dynamics of psychiatric symptomology, dietary intake, and PA in daily life.
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In the last two decades, e-diary studies have gained increasing interest, with a dominant focus on mood and affect. Although requested in current guidelines, psychometric properties are rarely reported, and methodological investigations of factor structure, model fit, and the reliability of mood and affect assessment are limited. We used a seven-day e-diary dataset of 189 adolescent participants (12-17 years). The e-diary affect assessments revealed a considerable portion of within-person variance. The six-factor model showed the best model fit compared to the less complex models. Factor loadings also improved with the complexity of the models. Accordingly, we recommend that future e-diary studies of adolescents use the six-factor model of affect as well as reporting psychometric properties and model fit. For future e-diary scale development, we recommend using a minimum of three items per scale to enable the use of confirmatory multilevel factor analyses.
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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.
Subject(s)
Wearable Electronic Devices , Humans , Adult , Adolescent , Fitness Trackers , Monitoring, Physiologic , Posture , Sedentary BehaviorABSTRACT
Digital innovations in mental health offer great potential, but present unique challenges. Using a consensus development panel approach, an expert, international, cross-disciplinary panel met to provide a framework to conceptualise digital mental health innovations, research into mechanisms and effectiveness and approaches for clinical implementation. Key questions and outputs from the group were agreed by consensus, and are presented and discussed in the text and supported by case examples in an accompanying appendix. A number of key themes emerged. (1) Digital approaches may work best across traditional diagnostic systems: we do not have effective ontologies of mental illness and transdiagnostic/symptom-based approaches may be more fruitful. (2) Approaches in clinical implementation of digital tools/interventions need to be creative and require organisational change: not only do clinicians and patients need training and education to be more confident and skilled in using digital technologies to support shared care decision-making, but traditional roles need to be extended, with clinicians working alongside digital navigators and non-clinicians who are delivering protocolised treatments. (3) Designing appropriate studies to measure the effectiveness of implementation is also key: including digital data raises unique ethical issues, and measurement of potential harms is only just beginning. (4) Accessibility and codesign are needed to ensure innovations are long lasting. (5) Standardised guidelines for reporting would ensure effective synthesis of the evidence to inform clinical implementation. COVID-19 and the transition to virtual consultations have shown us the potential for digital innovations to improve access and quality of care in mental health: now is the ideal time to act.
Subject(s)
COVID-19 , Mental Disorders , Humans , Mental Health , COVID-19/epidemiology , Mental Disorders/diagnosisABSTRACT
BACKGROUND: Childhood trauma exposures (CTEs) are frequent, well-established risk factor for the development of psychopathology. However, knowledge of the effects of CTEs in healthy individuals in a real life context, which is crucial for early detection and prevention of mental disorders, is incomplete. Here, we use ecological momentary assessment (EMA) to investigate CTE load-dependent changes in daily-life affective well-being and psychosocial risk profile in n = 351 healthy, clinically asymptomatic, adults from the community with mild to moderate CTE. FINDINGS: EMA revealed significant CTE dose-dependent decreases in real-life affective valence (p = 0.007), energetic arousal (p = 0.032) and calmness (p = 0.044). Psychosocial questionnaires revealed a broad CTE-related psychosocial risk profile with dose-dependent increases in mental health risk-associated features (e.g., trait anxiety, maladaptive coping, loneliness, daily hassles; p values < 0.003) and a corresponding decrease in factors protective for mental health (e.g., life satisfaction, adaptive coping, optimism, social support; p values < 0.021). These results were not influenced by age, sex, socioeconomic status or education. CONCLUSIONS: Healthy community-based adults with mild to moderate CTE exhibit dose-dependent changes in well-being manifesting in decreases in affective valence, calmness and energy in real life settings, as well as a range of established psychosocial risk features associated with mental health risk. This indicates an approach to early detection, early intervention, and prevention of CTE-associated psychiatric disorders in this at-risk population, using ecological momentary interventions (EMI) in real life, which enhance established protective factors for mental health, such as green space exposure, or social support.
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The coronavirus pandemic has brought about dramatic restrictions to real-life social interactions and a shift towards more online social encounters. Positive social interactions have been highlighted as an important protective factor, with previous studies suggesting an involvement of the amygdala in the relationship between social embeddedness and well-being. The present study investigated the effect of the quality of real-life and online social interactions on mood, and explored whether this association is affected by an individual's amygdala activity. Sixty-two participants of a longitudinal study took part in a one-week ecological momentary assessment (EMA) during the first lockdown, reporting their momentary well-being and their engagement in real-life and online social interactions eight times per day (N ~ 3000 observations). Amygdala activity was assessed before the pandemic during an emotion-processing task. Mixed models were calculated to estimate the association between social interactions and well-being, including two-way interactions to test for the moderating effect of amygdala activity. We found a positive relationship between real-life interactions and momentary well-being. In contrast, online interactions had no effect on well-being. Moreover, positive real-life social interactions augmented this social affective benefit, especially in individuals with higher amygdala being more sensitive to the interaction quality. Our findings demonstrate a mood-lifting effect of positive real-life social interactions during the pandemic, which was dependent on amygdala activity before the pandemic. As no corresponding effect was found between online social interactions and well-being, it can be concluded that increased online social interactions may not compensate for the absence of real-life social interactions.
Subject(s)
COVID-19 , Humans , Pandemics , Longitudinal Studies , Social Interaction , Communicable Disease ControlABSTRACT
The COVID-19 pandemic strongly impacted people's daily lives. However, it remains unknown how the pandemic situation affects daily-life experiences of individuals with preexisting severe mental illnesses (SMI). In this real-life longitudinal study, the acute onset of the COVID-19 pandemic in Germany did not cause the already low everyday well-being of patients with schizophrenia (SZ) or major depression (MDD) to decrease further. On the contrary, healthy participants' well-being, anxiety, social isolation, and mobility worsened, especially in healthy individuals at risk for mental disorder, but remained above the levels seen in patients. Despite being stressful for healthy individuals at risk for mental disorder, the COVID-19 pandemic had little additional influence on daily-life well-being in psychiatric patients with SMI. This highlights the need for preventive action and targeted support of this vulnerable population.