Digitale Phänotypisierung in der Psychologie – ein Quantensprung in der psychologischen Forschung?

Zusammenfassung. Digitale Phänotypisierung stellt einen neuen, leistungsstarken Ansatz zur Realisierung psychodiagnostischer Aufgaben in vielen Bereichen der Psychologie und Medizin dar. Die Grundidee besteht aus der Nutzung digitaler Spuren aus dem Alltag, um deren Vorhersagekraft für verschiedenste Anwendungsmöglichkeiten zu überprüfen und zu nutzen. Voraussetzungen für eine erfolgreiche Umsetzung sind elaborierte Smart Sensing Ansätze sowie Big Data-basierte Extraktions- (Data Mining) und Machine Learning-basierte Analyseverfahren. Erste empirische Studien verdeutlichen das hohe Potential, aber auch die forschungsmethodischen sowie ethischen und rechtlichen Herausforderungen, um über korrelative Zufallsbefunde hinaus belastbare Befunde zu gewinnen. Hierbei müssen rechtliche und ethische Richtlinien sicherstellen, dass die Erkenntnisse in einer für Einzelne und die Gesellschaft als Ganzes wünschenswerten Weise genutzt werden. Für die Psychologie als Lehr- und Forschungsdomäne bieten sich durch Digitale Phänotypisierung vielfältige Möglichkeiten, die zum einen eine gelebte Zusammenarbeit verschiedener Fachbereiche und zum anderen auch curriculare Erweiterungen erfordern. Die vorliegende narrative Übersicht bietet eine theoretische, nicht-technische Einführung in das Forschungsfeld der Digitalen Phänotypisierung, mit ersten empirischen Befunden sowie einer Diskussion der Möglichkeiten und Grenzen sowie notwendigen Handlungsfeldern.

It's Time to Think about Time in Health Psychology

This position paper addresses the need for stronger theorizing on temporal matters in health psychology. Too few theories in health psychology address temporal matters in the specified psychological phenomena, their relationships, and the explanation for these relationships. This might lead to underestimating existing relationships between constructs over time or missing out on opportunities for advancing our knowledge with regard to dynamic developments of the phenomena of interest. Examples of existing theories and approaches addressing temporal matters in health psychology are provided. Further, drawing from other disciplines, examples of methodological and conceptual approaches are outlined that offer directions on how to optimize our theories with regard to temporal matters. This might start with including time-related theoretical considerations to the definition of psychological concepts already in cross-sectional research and might reach as far as developing dynamic theories for capturing and changing phenomena of interest in real life. Challenges and opportunities of theorizing about temporal matters in health psychology are addressed.

Just DO(HaD) It! Testing the clinical potential of the DOHaD hypothesis to prevent mental disorders using experimental study designs

Optimal early cognitive and emotional development are vital to reaching one's full potential and represent our best chance to improve the mental health of the population. The developmental origins of health and disease (DOHaD) hypothesis posits that adverse perinatal exposures can alter physiology and increase disease risk. As physiological plasticity decreases with age, interventions applied during gestation may hold the most promise for reducing the impact of mental disorders across the lifespan. However, this vast clinical potential remains largely unrealized as the majority of human DOHaD research is observational in nature. The application of more rigorous experimental designs [e.g. Randomized Controlled Trials (RCTs)] not only represents a major step toward unlocking this potential, but are required to fully test the scientific validity of the DOHaD hypothesis as it pertains to mental illness. Here, we argue that the optimization of maternal diet and exercise during pregnancy represents our best chance to improve offspring neurodevelopment and reduce the burden of mental disorders. Follow-up studies of the offspring of pregnant women enrolled in new and existing RCTs of maternal gestational nutrition+exercise interventions are required to determine if acting during pregnancy can prevent and/or meaningfully reduce the prevalence and severity of mental disorders in the population.

The Acute Relationships Between Affect, Physical Feeling States, and Physical Activity in Daily Life: A Review of Current Evidence

Until recently, most studies investigating the acute relationships between affective and physical feeling states and physical activity were conducted in controlled laboratory settings, whose results might not translate well to everyday life. This review was among the first attempts to synthesize current evidence on the acute (e.g., within a few hours) relationships between affective and physical feeling states and physical activity from studies conducted in free-living, naturalistic settings in non-clinical populations. A systematic literature search yielded 14 eligible studies for review. Six studies tested the relationship between affective states and subsequent physical activity; findings from these studies suggest that positive affective states were positively associated with physical activity over the next few hours while negative affective states had no significant association. Twelve studies tested affective states after physical activity and yielded consistent evidence for physical activity predicting higher positive affect over the next few hours. Further, there was some evidence that physical activity was followed by a higher level of energetic feelings in the next few hours. The evidence for physical activity reducing negative affect in the next few hours was inconsistent and inconclusive. Future research in this area should consider recruiting more representative study participants, utilizing higher methodological standards for assessment (i.e., electronic devices combined with accelerometry), reporting patterns of missing data, and investigating pertinent moderators and mediators (e.g., social and physical context, intensity, psychological variables). Knowledge gained from this topic could offer valuable insights for promoting daily physical activity adoption and maintenance in non-clinical populations.

Metacognitions, worry and sleep in everyday life: Studying bidirectional pathways using Ecological Momentary Assessment in GAD patients

BACKGROUND

The metacognitive model of generalized anxiety disorder proposes that negative metacognitive beliefs are crucial in the maintenance of excessive worry. Furthermore, according to the cognitive model of insomnia, worry leads to problems falling or staying asleep and poor sleep quality. In order to test the assumed causal relationships, the present study examined the time-dependent course of negative metacognition and worry as well as worry and sleep quality, using Ecological Momentary Assessment (EMA).

METHOD

Negative metacognitions, worry and sleep were assessed by self-report questionnaires as well as EMA in 56 GAD patients who carried a portable device for 1 week and logged sleep quality, negative metacognition and worry processes four times a day.

RESULTS

Metacognitions, worry and sleep were significantly correlated. Structural equation modeling using multilevel analyses showed a unidirectional relationship of negative metacognitions leading to prolonged worry processes and a bidirectional relationship of worry and sleep quality.

CONCLUSIONS

These findings support the theoretically derived assumptions on the relationship between negative metacognitions, worry and sleep. Implications for further research as well as clinical implications are discussed.

Using Personal Cell Phones for Ecological Momentary Assessment

Ecological Momentary Assessment (EMA) is a way of collecting data in people’s natural environments in real time and has become very popular in social and health sciences. The emergence of personal digital assistants has led to more complex and sophisticated EMA protocols but has also highlighted some important drawbacks. Modern cell phones combine the functionalities of advanced communication systems with those of a handheld computer and offer various additional features to capture and record sound, pictures, locations, and movements. Moreover, most people own a cell phone, are familiar with the different functions, and always carry it with them. This paper describes ways in which cell phones have been used for data collection purposes in the field of social sciences. This includes automated data capture techniques, for example, geolocation for the study of mobility patterns and the use of external sensors for remote health-monitoring research. The paper also describes cell phones as efficient and user-friendly tools for prompt manual data collection, that is, by asking participants to produce or to provide data. This can either be done by means of dedicated applications or by simply using the web browser. We conclude that cell phones offer a variety of advantages and have a great deal of potential for innovative research designs, suggesting they will be among the standard data collection devices for EMA in the coming years.

Using the time-varying effect model (TVEM) to examine dynamic associations between negative affect and self confidence on smoking urges: differences between successful quitters and relapsers

With technological advances, collection of intensive longitudinal data (ILD), such as ecological momentary assessments, becomes more widespread in prevention science. In ILD studies, researchers are often interested in the effects of time-varying covariates (TVCs) on a time-varying outcome to discover correlates and triggers of target behaviors (e.g., how momentary changes in affect relate to momentary smoking urges). Traditional analytical methods, however, impose important constraints, assuming a constant effect of the TVC on the outcome. In the current paper, we describe a time-varying effect model (TVEM) and its applications to data collected as part of a smoking-cessation study. Differentiating between groups of short-term successful quitters (N = 207) and relapsers (N = 40), we examine the effects of momentary negative affect and abstinence self-efficacy on the intensity of smoking urges in each subgroup in the 2 weeks following a quit attempt. Successful quitters demonstrated a rapid reduction in smoking urges over time, a gradual decoupling of the association between negative affect and smoking urges, and a consistently strong negative effect of self-efficacy on smoking urges. In comparison, relapsers exhibited a high level of smoking urges throughout the post-quit period, a time-varying and, generally, weak effect of self-efficacy on smoking urges, and a gradual reduction in the strength of the association between negative affect and smoking urges. Implications of these findings are discussed. The TVEM is made available to applied prevention researchers through a SAS macro.

Conceptualizing and Estimating Process Speed in Studies Employing Ecological Momentary Assessment Designs: A Multilevel Variance Decomposition Approach

Researchers have been making use of ecological momentary assessment (EMA) and other study designs that sample feelings and behaviors in real time and in naturalistic settings to study temporal dynamics and contextual factors of a wide variety of psychological, physiological, and behavioral processes. As EMA designs become more widespread, questions are arising about the frequency of data sampling, with direct implications for participants' burden and researchers' ability to capture and study dynamic processes. Traditionally, spectral analytic techniques are used for time series data to identify process speed. However, the nature of EMA data, often collected with fewer than 100 measurements per person, sampled at randomly spaced intervals, and replete with planned and unplanned missingness, precludes application of traditional spectral analytic techniques. Building on principles of variance partitioning used in the generalizability theory of measurement and spectral analysis, we illustrate the utility of multilevel variance decompositions for isolating process speed in EMA-type data. Simulation and empirical data from a smoking-cessation study are used to demonstrate the method and to evaluate the process speed of smoking urges and quitting self-efficacy. Results of the multilevel variance decomposition approach can inform process-oriented theory and future EMA study designs.

Enhancement of care through self-monitoring and tailored feedback via text messaging and their use in the treatment of childhood overweight

OBJECTIVE

This paper first illustrates the general potential of the short message service (SMS) for symptom and behavior monitoring and the provision of tailored feedback. Second, an SMS-based maintenance treatment (SMSMT) is introduced aimed at enhancing the treatment of childhood overweight.

METHODS

After a 12-week cognitive behavioral group treatment (CBGT), 40 children were assigned to the SMSMT for a period of 36 weeks. Children were asked to send weekly self-monitoring data on eating behavior, exercise behavior, and emotions and received tailored feedback. The adherence to SMSMT and changes in Body Mass Index Standard Deviation Scores (BMI-SDS) during the first and second treatment phase were analysed.

RESULTS

Children (mean age=10.05, SD=1.28) submitted 67% of the weekly SMS that they were expected to send in. During CBGT a significant reduction by 0.20 BMI-SDS was observed. The reduction by 0.07 BMI-SDS during the SMSMT did not reach statistical significance.

CONCLUSION

The results support the feasibility of SMSMT in the treatment of childhood overweight. The efficacy of the intervention needs to be demonstrated in an RCT.

PRACTICE IMPLICATIONS

SMSMT is a promising intervention that may extend the reach of treatment centers for childhood overweight at reasonable cost and effort.