Supplemental Material for Perceived Criticism Predicts Outcome of Psychotherapy for Panic Disorder: Replication and Extension

Summary: Background: This article reports on a study of the concurrent validity between the standard expressed emotion instrument, the Camberwell Family Interview (CFI), and two alternative EE measures, the Level of Expressed Emotion (LEE) and the Perceived Criticism Scale (PCS). Methods: The research sample consisted of 56 schizophrenic clients, who were residing in sheltered residences, and 56 professionals. Results: Based on the results of the correlation matrix between all the subscales of the instruments, a significantly positive relationship was found between the criticism scale of the CFI, the total score of the LEE, and the client version of the PCS. These correlations, however, were rather weak, which implies that the three instruments have little in common with each other. The professionals' version of the PCS does not appear to be an EE instrument. Conclusions: The results suggest that the CFI still remains the best instrument for assessing EE in a therapeutic relationship (between a professional and a client). If there is insufficient time to administer the CFI, then the client version of the PCS and the LEE can be used with the qualification that the PCS and LEE also measure other aspects and thus cannot completely replace the CFI. Nevertheless, the research indicates that asking the clients would seem to provide a better indication of the level of the professionals' criticism rather than asking the professionals themselves directly.

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Identifying Patterns in Complex Field Data

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000310 ◽

2017 ◽

Vol 225 (3) ◽

pp. 268-284 ◽

Cited By ~ 1

Author(s):

Andrew J. White ◽

Dieter Kleinböhl ◽

Thomas Lang ◽

Alfons O. Hamm ◽

Alexander L. Gerlach ◽

...

Keyword(s):

Heart Rate ◽

Panic Disorder ◽

Latent Class ◽

Treatment Protocol ◽

Situational Factors ◽

Self Report ◽

Complex Field ◽

Cluster Assignment ◽

Experimental Conditions ◽

Conventional Analysis

Abstract. Ambulatory assessment methods are well suited to examine how patients with panic disorder and agoraphobia (PD/A) undertake situational exposure. But under complex field conditions of a complex treatment protocol, the variability of data can be so high that conventional analytic approaches based on group averages inadequately describe individual variability. To understand how fear responses change throughout exposure, we aimed to demonstrate the incremental value of sorting HR responses (an index of fear) prior to applying averaging procedures. As part of their panic treatment, 85 patients with PD/A completed a total of 233 bus exposure exercises. Heart rate (HR), global positioning system (GPS) location, and self-report data were collected. Patients were randomized to one of two active treatment conditions (standard exposure or fear-augmented exposure) and completed multiple exposures in four consecutive exposure sessions. We used latent class cluster analysis (CA) to cluster heart rate (HR) responses collected at the start of bus exposure exercises (5 min long, centered on bus boarding). Intra-individual patterns of assignment across exposure repetitions were examined to explore the relative influence of individual and situational factors on HR responses. The association between response types and panic disorder symptoms was determined by examining how clusters were related to self-reported anxiety, concordance between HR and self-report measures, and bodily symptom tolerance. These analyses were contrasted with a conventional analysis based on averages across experimental conditions. HR responses were sorted according to form and level criteria and yielded nine clusters, seven of which were interpretable. Cluster assignment was not stable across sessions or treatment condition. Clusters characterized by a low absolute HR level that slowly decayed corresponded with low self-reported anxiety and greater self-rated tolerance of bodily symptoms. Inconsistent individual factors influenced HR responses less than situational factors. Applying clustering can help to extend the conventional analysis of highly variable data collected in the field. We discuss the merits of this approach and reasons for the non-stereotypical pattern of cluster assignment across exposures.

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