Fiorani, C. and Poggioli, M., 2011. The PSQ Italian Standardisation. Reformulation, Winter, pp.49-52.
The PSQ was devised as a measure of deficits in personality integrity and represents an assessment measure of the multiple self states model of Cognitive Analytic Therapy (MSSM). It has been found to be a reliable and valid psychometrically sound measure associated with facets of identity disturbance (Pollock et al 2001, Bedford et al 2009).
The PSQ has a clinical use in identifying dissociation and in opening up a discussion of states and state shifts.
It is quick to administer and score.
A total of 270 controls and 266 clinical cases were administered an Italian translation of the PSQ Questionnaire which was designed to measure deficits in personality integrity and was designed as an assessment measure of the multiple self states model in CAT (MSSM). Broadbent et al. constructed a self report measure termed a measure of integration “the PSQ”. Items were generated to reflect BDP (Borderline Personality Disorder) as conceptualised by the MSSM Model and refer to identity disturbance rather than criteria such as self harm or aggression. There are eight items on a Likert scale, a high score is achieved by ticking the items on the right side of the page which are indicative of an unstable sense of self and of variation in subjective experience. The PSQ items on the right hand of the scale are divided into: presence of different self states (items 1 - 4), changeability in mood (items 5 - 6) and behavioural loss of control (items 7 - 8).
The controls were acquired by going to Piazza Duomo in Milan and asking a roughly equivalent number of men and women of various age groups to complete the questionnaire. Some questionnaires were also given to people we knew to give to other people they knew. There was no significant difference between the scores of these two samples so both were used. The controls were not matched to the clinical cases for age, marital status, or other demographic variables.
The patient group were referred to the Neuropsychiatry Service in Piacenza AUSL (The Italian Public Health Service) where they were diagnosed according to ICD-10 Criteria. Psychiatrists and psychologists and doctors in the Service were asked to administer the questionnaire to their patients.
In order to compare our result to those obtained by Pollock in 2001, initially we ran parametric statistics and we had comparable results. However since the raw scores are in fact an ordinal variable and not a continuum variable, we thought it more appropriate to use non parametric statistics.
Table 1 shows the means, the standard deviations, the quartiles and the ranks for total scores for controls and for the clinical cases. The clinical cases have a higher mean score than the controls and higher median and quartiles. This is confirmed by the Mann-Whitney non-parametric test in which the value of the statistic U was = 28938.000 and the p-value was 0.000. This means that there is a significant difference between the ranks of the total scores for cases and controls. Therefore the clinical cases have answered in a significantly different way to the control sample, in that in the clinical sample the score was higher.
Table 2 shows the analysis done by gender. It is interesting to note that within the clinical sample males have higher scores when compared with females. This could be owing to the unequal sample size with regards to gender. Because there are only 33 males compared to 213 females, standard error is much larger (1.152), even though the standard deviation is similar. In the control group there are no significant differences between the males and females.
Table 3 shows the Spearman’s rho correlation between age and scores for clinical cases and controls. For clinical cases there is a negative rank correlation (-0,263) which is not high but significant (p-value=0,000 between age and score. As the age increases the score diminishes and this is statistically significant. This does not apply to the control group where there is no significant statistical difference. It is important to notice that we ran also Pearson’s correlation index and we obtained similar results.
This finding is similar to that found by Bedford et al. 2009, Clinical psychology and Psychotherapy 16, 77-81 (2009), however Pollock et al. (2001) did not report the same finding.
The Italian standardisation figures for the non clinical sample in Milan are similar to those of Pollock et al Clinical Psychology and Psychotherapy 8, 59-72 (2001) in their London Bridge Station sample (although in our analysis we employed non parametric approaches), because the clinical sample scored consistently higher than control cases.
The sample was gathered in order to compare the non clinical population to the clinical for the purpose of Standardisation. On the clinical sample we found that clinicians had given a diagnosis. Since we had this information we also ran some descriptive statistics to see if there is a difference in the scores of patients allocated to different diagnostic categories. We found that there was a statistical difference but at the moment we have not reached any clinical conclusions.
Table 4 shows the mean scores for each diagnostic category and all the other statistics (standard deviation, the minimum and maximum, quartiles) it highlights that the value of the scores changes according to diagnostic categories. We also ran the non parametric Kruskal Wallis Test and we obtained the value 42,982 with 5 degrees of freedom. The p-value 0.000 evidences that the mean rank of the score is different between different diagnostic categories. Similar results were initially obtained with F parametric statistics based on one-way ANOVA.
The Bulimics have the highest scores (31) and the Anorectics come close with (27.02). The lowest score come with Metabolic Disorders (19.85). Scores very near to this are found with the EDNOS (eating disorder not otherwise classified) and the Obese patients, both categories score at around 20. Clinical cases with a gastric bypass operation have a score which is very similar to the general mean (23) of the patient sample.
Figures 1, represent the box-plot of the scores by diagnostic categories. We found that the PSQ discriminated between different diagnostic groups but as yet we have not reached any conclusion what this means. We can think about this in future.
Discussion in a nutshell
Pollock H.P. et al, (2001). “Assessment The Personality Structure Questionnaire (PSQ) A Measure of the Multiple Self States Model of Identity Disturbance in Cognitive Analytic Therapy”. Clin. Psychol. Psychother. 8, 59-72 (2001)
Bedford et al (2009). “Assessment The personality Structure Questionnaire (PSQ): A Cross-Validation with a Large Clinical Sample”. Clin. Psychol. Psychother. 16, 77-81
CRISTINA FIORANI is the Vice President and founder member of the Italian CAT Association (ITA-CAT). She is a Clinical and Psychotherapeutic Psychologist. She has Worked in the Italian AUSL (NHS) for over 25 years and now works in Piacenza in the Child and Adolescent Psychiatric Service. For the past 12 years she has increasingly used CAT in her practice and is keen to further the development of CAT in Italy. She works mainly in Eating Disorders.
MARISA POGGIOLI - CAT Practitioner and Supervisor, and HPC Practitioner Psychologist. She worked in the UK in Adult Primary Care and with forensic populations. She is a founder member of the Italian CAT Association (ITA-CAT). She now supervises an Eating Disorder service, and works as a Counsellor in a college, and in private practice. She has been collaborating with Cristina Fiorani for more than 11 years in bringing CAT ideas to Italy.
Statistical analysis by Dr. SILVIA SALINI - University of Milan, Department of Economics Business and Statistics, Mathematical and Statistics Section
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