92 Chapter 4 daily self-evaluations in the app. This finding is highly promising for participants, as it suggests that the method itself can empower them in the process of ‘getting to know yourself’. Benefits are optimized when the daily diary data are integrated in their clinical trajectories, by routinely providing daily diary input in treatment sessions. This finding echoes other clinical studies that reported advantages of daily diaries (Fartacek et al., 2016; Schiepek et al., 2016) and EMA research in general (Bos et al., 2019; Riese et al., 2021). In our study, care professionals received weekly overviews of raw diary data with visualizations (Figure 2) which they could discuss with the participant. Future research could explore other ways in which clinicians can benefit from diary feedback. That is, in addition to visualizations of raw diary, diary data can also be analyzed statistically to unravel underlying patterns. For example, timeseries analysis of diary data, when channeled back to a clinician, can provide insights into potential causes and consequences of specific behaviors for groups of clients or individual cases (Daniëls et al., 2022). Statistical timeseries analyses have aided the identification of treatment needs of psychotic patients, after they participated in a 6-day EMA protocol with 10 prompts per day (van Os et al., 2014). In other studies, individual clients' daily diary patterns were analyzed with non-linear dynamic systems analyses (Fartacek et al., 2016; Schiepek et al., 2016). Their results had real-life predictive value about the chances of meaningful clinical change occurring on the short-term. Diary items are ideally used to capture fluctuations over time. This study showed that, of the eight standardized items to assess internalizing and externalizing symptoms, ‘feeling happy’ and ‘feeling unrest’ were most sensitive to day-to-day changes. The items ‘doing things without thinking’, ‘doing things that you later regret’ and ‘doing things for kicks’, on the other hand, demonstrated the lowest overall MSSD. This may indicate that items measuring impulsivity may be more trait-like (i.e., patterns that are relatively similar across situations) than state-like emotional experiences such as happiness or unrest (cf. Baumeister et al., 2007). In other words, although there was some variation over time in impulsivity, a person's level of happiness or unrest seemed to depend more on the circumstances of a particular day and therefore demonstrated more fluctuations over time. The descriptive statistics of day-to-day fluctuations, and additionally the notion that the care professional and client attributed meaning to them in treatment settings, seems to indicate that the daily self-ratings reflected overall good face validity. That is, the fact that items indeed captured the dayto-day fluctuations that one would expect and the benefits that participants reported from keeping the diaries, give us no reason to suspect that the selfratings somehow did not correspond to reality.
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