Abstract
Background and aims
Understanding associations between constructs such as personality, depression, stress, and quality of life is central to psychosomatic research. These constructs are typically assessed using questionnaires that often include similar symptoms, such as fatigue or emotional distress. Although such measurement overlap is widely recognized, its consequences for interpreting associations are rarely made explicit. This work aims to clarify how symptom overlap influences observed associations and to provide a practical way to distinguish construct-level relationships from overlapping measurement items.
Methods
We developed a framework to distinguish different forms of symptom or item overlap in psychosomatic questionnaires and show how such overlap can inflate observed associations, even when constructs do not directly share symptoms. We introduce a method that allows previously reported associations to be reinterpreted by separating construct-level relationships from shared symptom content. An empirical illustration using psychosomatic questionnaire data demonstrates the clinical relevance of this approach.
Results
Observed associations among psychosomatic constructs were frequently inflated when measurement overlap was present. Findings show that our novel method accurately clarifies how much of an association reflects meaningful relationships between constructs versus shared symptom content. We implemented our method in a user-friendly online tool.
Discussion
Our findings highlight that commonly reported associations between psychosomatic constructs may partly reflect shared symptom content rather than distinct psychosomatic mechanisms. Making this distinction explicit can improve clinical interpretation and theory development.
Conclusion
This work provides psychosomatic researchers with a practical framework and tool for valid interpretation of associations among constructs measured with overlapping items.
Understanding associations between constructs such as personality, depression, stress, and quality of life is central to psychosomatic research. These constructs are typically assessed using questionnaires that often include similar symptoms, such as fatigue or emotional distress. Although such measurement overlap is widely recognized, its consequences for interpreting associations are rarely made explicit. This work aims to clarify how symptom overlap influences observed associations and to provide a practical way to distinguish construct-level relationships from overlapping measurement items.
Methods
We developed a framework to distinguish different forms of symptom or item overlap in psychosomatic questionnaires and show how such overlap can inflate observed associations, even when constructs do not directly share symptoms. We introduce a method that allows previously reported associations to be reinterpreted by separating construct-level relationships from shared symptom content. An empirical illustration using psychosomatic questionnaire data demonstrates the clinical relevance of this approach.
Results
Observed associations among psychosomatic constructs were frequently inflated when measurement overlap was present. Findings show that our novel method accurately clarifies how much of an association reflects meaningful relationships between constructs versus shared symptom content. We implemented our method in a user-friendly online tool.
Discussion
Our findings highlight that commonly reported associations between psychosomatic constructs may partly reflect shared symptom content rather than distinct psychosomatic mechanisms. Making this distinction explicit can improve clinical interpretation and theory development.
Conclusion
This work provides psychosomatic researchers with a practical framework and tool for valid interpretation of associations among constructs measured with overlapping items.
| Original language | English |
|---|---|
| Article number | 112771 |
| Pages (from-to) | 36-37 |
| Number of pages | 2 |
| Journal | Journal of Psychosomatic Research |
| Volume | 207, Supplement |
| DOIs | |
| Publication status | Published - Aug 2026 |
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