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The quality of physician-patient interaction is increasingly being recognized as an essential component of effective treatment. The present article reports on the development and validation of a brief patient self-report questionnaire (QQPPI) that assesses the quality of physician-patient interactions. Data were gathered from 147 patients and 19 physicians immediately after consultations in a tertiary care outpatient setting. The QQPPI displayed good psychometric properties, with high internal consistency and good item characteristics. The QQPPI total score showed variability between different physicians and was independent of patients' gender, age, and education. The QQPPI featured high correlations with other quality-related measures and was not influenced by social desirability, or patients' clinical characteristics. The QQPPI is a brief patient self-report questionnaire that allows assessment of the quality of physician-patient interactions during routine ambulatory care. It can also be used to evaluate physician communication training programs or for educational purposes.

Background: Therapy processes are complex dynamical systems where several variables are constantly interacting with each other. In general, the underlying mechanisms are difficult to assess. Our approach is to identify the dependency structure of relevant variables within the therapy process using interaction graphs. These are instruments for multivariate time series which are based on the analysis of partial spectral coherences. We used interaction graphs in order to investigate the therapy process of a multimodal therapy concept for fibromyalgia patients. Our main hypothesis was that self-efficacy plays a central role in the therapy process. Methods: Patients kept an electronic diary for 13 weeks. Pain intensity, depression, sleep quality, anxiety and self-efficacy were assessed via visual analogue scales. The resulting multivariate time series were aggregated over individuals, and partial spectral coherences between each pair of the variables were calculated. From the partial coherences, interaction graphs were plotted. Results: Within the resulting graphical model, self-efficacy was strongly related to pain intensity, depression and sleep quality. All other relations were substantially weaker. There was no direct relationship between pain intensity and sleep quality. Conclusions: The relations between two variables within the therapy process are mainly induced by self-efficacy. Interaction graphs can be used to pool time series data of several patients and thus to assess the common underlying dependency structure of a group of patients. The graphical representation is easily comprehensible and allows to distinguish between direct and indirect relationships.