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Construct validity and psychosocial correlates of the Italian version of the 21-item Medical Interview Satisfaction Scale in primary care

Published online by Cambridge University Press:  18 February 2021

Matteo Balestrieri*
Affiliation:
Unit of Psychiatry, Department of Medicine, University of Udine, Italy
Giovanni de Girolamo
Affiliation:
Unit of Psychiatric Epidemiology and Evaluation, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Italy
Paola Rucci
Affiliation:
Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum, University of Bologna, Italy
*
Correspondence: Matteo Balestrieri. Email: matteo.balestrieri@uniud.it
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Abstract

Background

Satisfaction with the medical interview has been rarely explored in primary care outside the UK, despite evidence suggesting that a trustful doctor–patient relationship is a key ingredient to facilitate treatment adherence and relief from illness-related distress.

Aims

The aims of this study are to analyse the construct validity of the Italian version of the Medical Interview Satisfaction Scale (MISS-21) and its correlations with two outcome measures, the Inventory of Depressive Symptomatology – Self-Report and World Health Organization Quality Of Life Brief Version, in patients with mild-to-moderate depression, recruited in primary care practices.

Method

The factor structure underlying the MISS-21 was investigated with principal component analysis, and the internal consistency of the factors was evaluated with Cronbach's alpha. Network analysis was used to investigate the interrelationships among items. The importance of individual items in the network structure was determined with centrality analyses. Correlations of MISS-21 scores with changes in depression and quality of life were analysed with Spearman's correlation coefficient.

Results

The MISS-21 proved to have a robust four-dimensional factor structure. Cronbach's alpha for the factors ranged from 0.77 to 0.93, suggesting good to excellent internal consistency. The four factors identified were positively correlated with improvement in depressive symptoms and three quality-of-life domains.

Conclusions

The MISS-21 has sound psychometric properties, and comprises four factors related to clinical outcomes, which makes it suitable for clinical and research applications. The central items in the network should be considered as possible targets for quality improvement interventions in primary care.

Information

Type
Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists
Figure 0

Table 1 Characteristics and depression scores at baseline of study participants assigned to the telemedicine group (n = 42) and the control group (n = 22)

Figure 1

Table 2 Descriptive statistics of the 21 items of the Italian version of the Medical Interview Satisfaction Scale

Figure 2

Table 3 Results of principal component analysis of the items of the Italian version of the Medical Interview Satisfaction Scale (item loadings are arranged in decreasing order)

Figure 3

Fig. 1 Network structure of the Italian version of the Medical Interview Satisfaction Scale. Items with a suffix ‘i’ have been inverted for the analysis. For the meaning of the items, see Table 2. Edges denoting direct associations are in violet, those denoting inverse associations are in red.

Figure 4

Fig. 2 Centrality plot for the Italian version of the Medical Interview Satisfaction Scale network. Betweenness indicates the number of times a node lies on the shortest path length between any two other nodes. Closeness indicates the average distance of a node from all other nodes in the network. Degree quantifies the extent to which a certain node influences other nodes in the network. For each index, higher values reflect greater centrality in the network.

Figure 5

Fig. 3 Edge weights (x-axis) sorted in increasing order (red line). The black line is the mean of 1000 bootstrap replications. The grey areas are the 95% confidence intervals. In the y-axis, the edge labels are omitted to avoid cluttering. The accuracy of edge weights was measured by the mean and 95% confidence intervals of 1000 bootstrap samples drawn from the study population: the narrower the confidence interval, the more accurate is the estimate of the edge weight. The black line in the figure shows that the average weights from the bootstrap samples overlap to large extent with edge weights of the sample (red line). Moreover, the edges with the highest absolute partial correlation are significantly different from those with the lowest absolute partial correlation (confidence intervals do not overlap), but the confidence intervals of many edge weight estimates are quite large. Thus, the edge weight estimations are partly accurate.

Figure 6

Table 4 Spearman's correlation coefficients of the MISS-21 factor scores with changes in severity of depression (ΔIDS-SR) and in the quality-of-life domains

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