Respiratory Interoception and Pathological Illness Anxiety: Disentangling Bias
Timo Slotta, Carolin Wolters, Zeynep Marx, Michael Witthöft, Alexander L. Gerlach, Anna Pohl- Psychiatry and Mental health
- Applied Psychology
Abstract
Objective
Biased interoception decoupled from physiology might be relevant in the etiology of pathological illness anxiety. Empirical evidence for interoceptive deviations in illness anxiety is scarce but potentially informative to optimize treatments. We hypothesized that persons with pathological illness anxiety differ fundamentally in the classification of bodily sensations from those without pathological illness anxiety.
Methods
In a respiratory categorization task, participants breathed into a pulmonary training device. Inspiration effort was varied by eight resistive loads. The lower/higher four loads were introduced as belonging to arbitrary categories ‘A’/‘B’, respectively. Participants memorized respiratory sensations in a first experimental block and were asked to label the resistances in a second block. We calculated the sensitivity of resistance classification according to category, and response bias in terms of categorical misclassification. Data of 39 participants with pathological illness anxiety and 35 controls were compared with regard to sensitivity and response bias by group, resistive load, and their interaction in a multiple regression.
Results
With similar sensitivity, patients more often labelled loads above the categorical border erroneously as belonging to category A, thus underestimating their resistance (β = -.06,
Conclusion
Individuals with PIA showed a systematic “wait and see” approach. Altered respiroception in PIA might stem from biased perception during training phase, the recognition phase, biased memory or a combination of these. Its exact characteristics remain unknown and future research must address the challenge of developing reliable and valid paradigms accounting for the variability of interoceptive biases.
Registration: This work was preregistered on OSF (https://osf.io/9shcw).