This article reviews the Electronically Activated Recorder (EAR) as an ambulatory ecological momentary assessment tool for the real-world observation of daily behavior. Technically, the EAR is an audio recorder that intermittently records snippets of ambient sounds while participants go about their lives. Conceptually, it is a naturalistic observation method that yields an acoustic log of a person’s day as it unfolds. The power of the EAR lies in unobtrusively collecting authentic real-life observational data. In preserving a high degree of naturalism at the level of the raw recordings, it resembles ethnographic methods; through its sampling and coding, it enables larger empirical studies. This article provides an overview of the EAR method; reviews its validity, utility, and limitations; and discusses it in the context of current developments in ambulatory assessment, specifically the emerging field of mobile sensing.

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.

Cette thèse vise à expliquer les fluctuations du bien-être momentané tout au long de la journée et de la semaine, en tenant compte de l'influence de l'environnement construit et social sur ces variations. Cette étude a évalué l'impact du moment de la journée, des interactions sociales, de la météo et des environnements bâtis et sociaux, sur le bien-être momentané à l’aide d’un devis longitudinal par évaluation écologique momentanée géographique (GEMA). Un total de 899 participants résident dans le Grand Montréal, âgés de 18 à 80 ans (Âge : M = 41,71, md = 39 ; femmes = 55,7%) ont rempli une échelle brève de l'humeur trois fois par jour pendant sept jours consécutifs sur leurs téléphones intelligents (application EthicaData). Lors des réponses, la coordonnée GPS de leur localisation a également été captée, et a servi à mesurer diverses expositions environnementales dans un système d’information géographique. Un modèle à effets mixtes à trois niveaux avec des effets aléatoires a montré une corrélation positive entre le bien-être et l'âge, les après-midis, les week-ends et les interactions sociales impliquant la famille et les amis. En revanche, le bien-être était négativement associé aux soirées. Quelques variables de l’environnement bâti et social étaient significativement associées au bien-être. Ces liens ont persisté après contrôle des facteurs de confusion potentiels. De plus, un effet d'interaction a révélé que l'influence des interactions sociales momentanées différait entre les hommes et les femmes. Cette étude met en lumière le rôle des facteurs environnementaux et sociaux dans la compréhension du bien-être momentané. L'intégration de la technologie géospatiale et des évaluations écologiques momentanées offre des perspectives précieuses pour l'urbanisme et la santé publique dans l’exploration des liens entre contexte et santé. / This thesis aims to explain the fluctuations of momentary well-being throughout the day and week, taking into consideration how the built and social environment affects these variations. In this seven-day longitudinal study using GPS-enabled smartphones and EthicaData software with a geographic ecological momentary assessment (GEMA) approach, the real-time impact of built and social environments on self-reported momentary well-being of residents of Greater Montreal between 2018 and 2021 was investigated. A total of 889 participants aged 18–80 years (Age: M=41.71, md=39; females = 55.7%) completed the Short Mood Scale three times daily for seven consecutive days. A three-level mixed-effects model with random effects showed a positive correlation between well-being and age, afternoons, weekends, and social interactions involving family and friends. On the other hand, well-being was negatively associated with evenings. Only a few built and social environmental variables were found to be significantly associated with well-being. These links remained after controlling for potential confounding factors. Moreover, an interaction effect revealed that the influence of momentary social interactions differed for men and women. This study highlights the significance of environmental and social factors in comprehending momentary well-being, which has important implications for urban planning and public health initiatives. Integrating geospatial technology and EMA provides valuable insights into this intricate relationship.