Exploring the emotional dynamics of subclinically depressed individuals with and without anhedonia: An experience sampling study.

BACKGROUND: Anhedonia has been linked to worse prognosis of depression. The present study aimed to construct personalized models to elucidate the emotional dynamics of subclinically depressed individuals with versus without symptoms of anhedonia. METHODS: Matched subclinically depressed individuals with and without symptoms of anhedonia (N = 40) of the HowNutsAreTheDutch sample completed three experience sampling methodology assessments per day for 30 days. For each individual, the impact of physical activity, stress experience, and high/low arousal PA/NA on each other was estimated through automated impulse response function analysis (IRF). These individual IRF associations were combined to compare anhedonic versus non-anhedonic individuals. RESULTS: Physical activity had low impact on affect in both groups. In non-anhedonic individuals, stress experience increased NA and decreased PA and physical activity more strongly. In anhedonic individuals, PA high arousal showed a diminished favorable impact on affect (increasing NA/stress experience, decreasing PA/physical activity). Finally, large heterogeneity in the personalized models of emotional dynamics were found. LIMITATIONS: Stress experience was measured indirectly by assessing level of distress; the timeframe in between measurements was relatively long with 6h; and only information on one of the two hallmarks of anhedonia, loss of interest, was gathered. CONCLUSIONS: Our results suggest different pathways of emotional dynamics underlie depressive symptomatology. Subclinically depressed individuals with anhedonic complaints are more strongly characterized by diminished favorable impact of PA high arousal and heightened NA reactivity, whereas subclinically depressed individuals without these anhedonic complaints seem more characterized by heightened stress reactivity. The automatically generated personalized models may offer patient-specific insights in emotional dynamics, which may show clinical relevance.

Let's get Physiqual - An intuitive and generic method to combine sensor technology with ecological momentary assessments.

The emergence of wearables and smartwatches is making sensors a ubiquitous technology to measure daily rhythms in physiological measures, such as movement and heart rate. An integration of sensor data from wearables and self-report questionnaire data about cognition, behaviors, and emotions can provide new insights into the interaction of mental and physiological processes in daily life. Hitherto no method existed that enables an easy-to-use integration of sensor and self-report data. To fill this gap, we present 'Physiqual', a platform for researchers that gathers and integrates data from commercially available sensors and service providers into one unified format for use in Ecological Momentary Assessments (EMA) or Experience Sampling Methods (ESM), and Quantified Self (QS). Physiqual currently supports sensor data provided by two well-known service providers and therewith a wide range of smartwatches and wearables. To demonstrate the features of Physiqual, we conducted a case study in which we assessed two subjects by means of data from an EMA study combined with sensor data as aggregated and exported by Physiqual. To the best of our knowledge, the Physiqual platform is the first platform that allows researchers to conveniently aggregate and integrate physiological sensor data with EMA studies.