Abstract
Past research has relied on normative analyses for establishing the positive relationship between psychological flexibility (PF) process and well-being. These analyses, however, assume that aggregate-level effects (i.e., this positive relationship) also apply to most individuals, limiting our ability to explore the dynamic and complex nature of PF processes that interact with individual factors. Idionomic analyses, which use idiographic effects as a foundation from which to draw normative conclusions, provide a possible solution. This study used idionomic analysis to assess the degree of non-random individual heterogeneity in the relationship between each PF process and mood, how this relationship changes over time, and the unique effects of each process. From a pre-existing dataset, we analysed data from 103 psychiatric patients (M age = 37 years, SD = 11.7 years; 47% male) who completed an ACT intervention. Experience sampling methods were used to repeatedly measure PF processes and mood at pre- and post-intervention. Traditional normative analyses showed an average positive relationship between each PF process and mood. However, idionomic analyses uncovered significant person-specific heterogeneity for several PF processes. The strength and direction of each relationship varied depending on the person, the specific PF process, and the temporal effects that were masked in the aggregate findings. We highlight the value of idionomic analyses in capturing, with greater depth and precision, within-person heterogeneity in the PF process-mood relationship. Idionomics has the potential to advance our development of empirically-based and personalised interventions, thus going beyond the general statement of “it depends” to a specification of how it does so.
| Original language | English |
|---|---|
| Article number | 100993 |
| Journal | Journal of Contextual Behavioral Science |
| Volume | 40 |
| DOIs | |
| State | Published - Apr 2026 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2026 The Authors.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Autoregressive integrated moving average (ARIMA)
- Experience sampling method
- Idionomic analysis
- Process-based therapy
- Processes of change
- Psychological flexibility
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