BACKGROUND: As digital media use has increasingly become a part of daily life for adolescents, it is critical to ascertain any potential link between digital media use and poorer mental health. Many studies have explored the relationship between screen time and psychiatric symptoms, but most of these studies have been limited by cross-sectional and participant recall. Moreover, many of these studies examine youth digital media use as a whole, rather than examining qualitative use. This study uses smartphone-based ecological momentary assessment to capture daily relationships between anxiety and depression symptoms and quality and quantity of smartphone use. METHODS: Youth aged 12 to 22 years-old were recruited from Cambridge Health Alliance’s outpatient psychiatry clinics to participate in the study. Participants were asked to use the mindLAMP app daily for six weeks to record depression and anxiety symptoms (via PHQ-8 and GAD-7 screeners), as well as provide daily screen time and three most frequently used apps obtained from their smartphone’s screen time report feature. Patient psychiatric diagnosis and demographic data were obtained from the medical record upon study enrollment. Multilevel mixed effects regression models were used to assess relationships between daily depression and anxiety symptoms and digital media use; linear regression models assessed relationships between psychiatric diagnoses and average screen and social media time over the course of the study. RESULTS: The study recruited a total of 51 youths. Frequent use of a specific type of digital media was not related to an increase in daily depression or anxiety symptoms. While no one category of psychiatric diagnosis was related to higher or lower average screen time, a statistically significant relationship was observed between daily GAD-7 score and daily time spent on social media (p=0.004) and percent of daily screen time that was spent on social media (p=0.01) with increased daily GAD-7 scores. Daily PHQ-8 scores were also positively correlated to daily time spent on social media (p=0.023). CONCLUSIONS: Our findings support those of prior studies that a significant relationship exists between anxiety, depression, and time spent on screens. It is less evident whether a specific type of digital media use may be more or less associated with these symptoms. More focused research with digital phenotyping or ecological momentary assessment may help to determine whether digital media use causes the worsening of psychiatric symptoms or alternatively, is being used to help manage them. Either way, mental health clinicians should educate their adolescent patients about these existing relationships and encourage patient self-awareness regarding personal patterns of digital media use. / 2025-02-20T00:00:00Z

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.

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La Dépression Post-AVC (DPAVC) constitue une des complications psychiatriques les plus fréquentes dans les suites d’un Accident Vasculaire Cérébral (AVC) avec des conséquences majeures en termes de récupération fonctionnelle et de qualité de vie. Il est nécessaire de disposer de critères permettant une identification précoce des patients à risque afin de leur proposer des aides adaptées. L’objectif de ce travail de thèse est d’étudier certains facteurs de risque et de protection de la DPAVC avec une approche en vie quotidienne chez des patients présentant un AVC peu invalidant. Dans une première partie, nous présentons l’étude du rôle exercé par le soutien social et la routinisation sur la sévérité des symptômes dépressifs trois mois après l’AVC par la méthode « Ecological Momentary Assessment ». Dans une seconde partie, nous explorons le rôle de la voix comme marqueur précoce de la DPAVC. Nous avons mis en évidence que la perception du soutien social initial influence l’intensité des symptômes dépressifs et les activités trois mois après. D’autre part, nous avons observé une dynamique temporelle unidirectionnelle entre l’augmentation des routines et la survenue de symptômes dépressifs plus intenses. Enfin, les analyses vocales nous ont permis d’identifier des marqueurs de DPAVC avec des modifications longitudinales de la fréquence fondamentale ainsi que des marqueurs précoces (shimmer et ruptures de voisement). Au-delà des facteurs cliniques traditionnellement reconnus, ce travail a mis en évidence de façon écologique de nouveaux marqueurs de risque de DPAVC dont la détection pourrait permettre d’élaborer de nouvelles stratégies de prévention et de prise en charge / Post-stroke depression (PSD) is one of the most common psychiatric complications following stroke with detrimental consequences in terms of functional recovery and quality of life. Its identification and treatment at the earliest stages of care remains a clinical challenge. The aim of this thesis is to study risk and protective factors for PSD based on data collected in the contexts of daily life. In the first section, we present a study of the role played by social support and routinization on the severity of depressive symptoms three months after stroke by Ecological Momentary Assessment (EMA). In the second section, we examine the voice as an early marker of PSD. We observed that patient perceptions of better support quality, and not quantity, immediately following mild stroke, are associated with better behavioral and emotional outcomes three months later. In addition, we observed a unidirectional pattern of association between mood and routines, whereby the occurrence of routines was associated with a higher level of depressive symptomatology over subsequent hours. Finally, voice analysis allowed us to identify PSD markers with longitudinal changes in fundamental voice frequency and discriminant analysis demonstrated that initial voice breaks coupled with shimmer are strongly predictive of subsequent PSD. Beyond commonly-recognized clinical risk factors such as stroke severity, these ecological investigations identified new markers for PSD whose detection could lead to new strategies for prevention and care

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Indiana University-Purdue University Indianapolis (IUPUI) / The research ideas included in this dissertation are motivated by a large sexually trans mitted infections (STIs) study (IU Phone study), which is also an ecological momentary assessment (EMA) study implemented by Indiana University from 2008 to 2013. EMA, as a group of methods used to collect subjects’ up-to-date behaviors and status, can increase the accuracy of this information by allowing a participant to self-administer a survey or diary entry, in their own environment, as close to the occurrence of the behavior as possible. IU Phone study’s high reporting level shows one of the benefits gain from introducing EMA in STIs study. As a prospective study lasting for 84 days, participants in IU Phone study undergo STI testing and complete EMA forms with project-furnished cellular telephones according to the predetermined schedules. At pre-selected eight-hour intervals, participants respond to a series of questions to identify sexual and non-sexual interactions with specific partners including partner name, relationship satisfaction and sexual satisfaction with this partner, time of each coital event and condom use for each event. etc. STIs lab results of all the participants are collected weekly as well. We are interested in several variables related to the risk of infection and sexual or non-sexual behaviors, especially the relationship among the longitudinal processes of those variables. New statistical models and applications are established to deal with the data with complex dependence and sampling data structures. The methodologies covers various of statistical aspect like generalized mixed models, mul tivariate models and autoregressive and cross-lagged model in longitudinal data analysis, misclassification adjustment in imperfect diagnostic tests, and variable-domain functional regression in functional data analysis. The contribution of our work is we bridge the meth ods from different areas with EMA data in the IU Phone study and also build up a novel understanding of the association among all the variables of interest from different perspec tives based on the characteristic of the data. Besides all the statistical analyses included in this dissertation, variety of data visualization techniques also provide informative support in presenting the complex EMA data structure.