170 Chapter 7 The perspectives of professionals can thus provide deeper insights, not only into their own perceived gains and drawbacks but also into their clients’ perceptions. Our findings bear two more important EMA-related implications for daily practice that require further research. First, about half of the participants and their care professionals in Chapter 4 chose to include personalized items that inquired after (potentially) positive experiences of that day. I believe this speaks volumes, both about what clients want to report on and about the value daily practice places on amplifying what goes well. This stands in stark contrast to the vast majority of empirical research that focuses solely on problems and symptoms. Future research should explicitly focus on what constitutes daily positivity in the lives of people with a mild intellectual disability, how to measure it, and how to enhance it. EMA is an ideal method to obtain ecologically valid information about their daily experiences, while the field of positive psychology provides a framework for such a line of inquiry (Stone, 2022). Second, in Chapter 6 we assessed the extent to which instability in EMA data can serve as an early warning signal for phase transitions between different attractor states. Our results were promising but did not imply conclusive evidence of instability as an early warning signal for this case, as there were several instability peaks without transitions and transitions without instability peaks. Nevertheless, improving the detection of warning signals has the ultimate relevance for clinical practice, because for professionals it is crucial to be able to anticipate and prevent undesirable change and promote desirable change. Future research is recommended to explore the potential of warning indicators for phase transitions in different cases. Physiological data, when combined with EMA, presents an intriguing yet complex potential for clinical practice. While wearables can capture physiological changes such as heart rate and skin conductance, these measures often face non-specificity issues (e.g., difficulties distinguishing between stress and physical exercise). Interestingly, de Looff et al. (2019) found that patterns of heart rate and skin contained predictive value for aggressive incidents within the next 30 minutes. However, this short time window might mean it is too late for professionals to anticipate and intervene timely. Implementing fully data-driven approaches in daily practice is premature. Currently, human behavior, particularly in the context of specialized care for people with mild intellectual disability, is too complex to be predicted with high precision using only data-driven methods. Nonetheless, improving the detection of warning signals holds significant relevance for clinical practice.
RkJQdWJsaXNoZXIy MTk4NDMw