4.3.1 Design
This study utilised a survey research design, which involved a purposive sample of males recruited from factories, warehouses, garages, call centres and trade jobs in the Midlands. Purposive sampling was employed as participants were selected according to pre-determined criteria in relation to the research aims (as described below; Guest et al., 2006).
77 4.3.2 Participants
A purposive sample of males were recruited in order to validate the scales, with the intention of later using them as screening tools with male prisoners in the UK. According to the Ministry of Justice (MOJ; 2012a), 47% of prisoners had no qualifications, and of the 53% that had qualifications: 65% were educated to GCSE level or equivalent, with 8% being educated to higher than A levels. In terms of employment: 68% of prisoners were unemployed in the four weeks before custody, and 13% of prisoners had never had a job. When taking into account the last 12 months before custody, 52% were in paid employment, in which 49% of these prisoners were classed as working in routine and semi- routine occupations (i.e. postal worker, machine operative, van driver, packer, labourer etc.; MOJ, 2012a). Among prisoners, over 9,000 work in industrial workshops across the prison estate (MOJ, 2012b); therefore, a specific sample of males (with a broad age range; working in factories, warehouses, garages, call centres, and trade jobs) were chosen in order to try and gain a sample that may be representative of a male prisoner population.
Participants consisted of 203 males, with an age range of 18 – 81 years old (age M = 36.83, SD = 14.68), from Nottinghamshire and Derbyshire. According to the International Standard Classification of Occupations (ISCO-08; International Labour Office, 2012): 36.9% were Craft and Related Trade Workers (builders, electricians, mechanics), 24.6% were Plant and Machine Operators (machine/labelling/picking operator), 20.7% had Elementary Occupations (factory picker/stacker, waste collector), and 17.7% were Service and Sale Workers (call centre and customer contact centre staff). Concerning education attainment: 17.7% reported no qualifications, 37.9% reported GCSEs or NVQ equivalent, 34% reported A-levels or NVQ equivalent, and 10.4% reported degree level (BA/BSC) or NVQ equivalent. A large majority of participants were married/cohabiting (56.6%), with 36.5% being single, and 6.9% being divorced/separated/widowed.
4.3.3 Measures
4.3.3.1 Severity indices of personality problems – short form (SIPP-SF)
The SIPP-SF (Verhaul et al., 2008) is a 60-item self-report questionnaire which was designed to assess five core domains of (mal)adaptive personality functioning: self-control, identity integration, relational
capacities, responsibility, and social concordance. Within this study, the SIPP-SF was used to measure
personality functioning (criterion A of the DSM-5 AMPD). Each domain scale consists of 12 items. The SIPP-SF was derived from the SIPP-118, measuring the same domains with a reduced number of items. As in the SIPP-118, each SIPP-SF item is scored on a 4-point Likert scale (1 = fully disagree; 2 = partly disagree; 3 = partly agree; 4 = fully agree).
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Items are scored in both a positively and negatively keyed direction. The scales time frame is the ‘past 3 months’, with higher scores showing more adaptive (and thus less pathological) capacities, whereas, lower scores indicate more maladaptive personality functioning. Scores are converted to a Z-score and then a T-score in order to compare to normative data (general population and PD population; Verheul et al, 2008), whereby scores less than 40 indicate impaired adaptive functioning, and less than 30 indicate severely impaired adaptive functioning. Regarding internal consistency, excellent Cronbach’s alpha (α) values have been found in America (0.83-0.89; Ro & Clark, 2009) and Belgium (0.81-0.88; Rossi et al., 2016). The reliability of the SIPP-SF in the current sample will be discussed in the subsequent results section.
4.3.3.2 Personality inventory for DSM-5 brief form (PID-5-BF)
The PID-5-BF (APA, 2013b) is a 25-item self-report questionnaire which was designed to assess the five domains of the DSM-5 personality trait model: negative affectivity, detachment, antagonism,
disinhibition, and psychoticism. The PID-5-BF items come from the 220-item self-report PID-5 (Krueger
et al., 2012), which was developed to assess pathological personality traits as part of the DSM-5 AMPD. Each domain scale consists of five items, however, not all 25 pathological personality traits are represented by the 25 items in the scale. The scale consists of 21 of the most pure-loading facets, which means that restricted affectivity, rigid perfectionism, submissiveness and suspiciousness are not included in the brief form (however, these are not included when calculating the domain scores for the full version or short version either). Instead, the facets of withdrawal, impulsivity, eccentricity, and
cognitive and perceptual dysregulation are measured by two items each.
As in the PID-5, each PID-5-BF item is scored on a 4-point Likert scale (0 = very false or often false; 1 = sometimes or somewhat false; 2 = sometimes or somewhat true; 3 = very true or often true). All items are scored in a positively keyed direction, which is different to the full PID-5 version, which contains negatively keyed items. Higher scores on the domains of the PID-5-BF indicate greater dysfunction. The PID-5-BF differs from other versions of the PID-5 as it yields a score for the overall measure, providing a score for the overall personality disturbance (APA, 2013b). In terms of internal consistency, there is no published report available that describes the psychometric properties of the scale, however, acceptable α values have been found in America (ranging from 0.68 - 0.78 across three samples: Anderson et al., 2018), Denmark (0.74 - 0.81; Bach et al., 2015), and Italy (0.64 - 0.77; Fossati et al., 2017). The reliability of the PID-5-BF in the current sample will be discussed in the subsequent results section.
79 4.3.3.3 Personality diagnostic questionnaire – 4
The PDQ-4 (Hyler, 1994) is a 99-item self-report questionnaire which was designed to assess DSM-IV PDs. It is a true-false instrument, consisting of items that correspond directly to criteria for the DSM-IV PDs. The measure produces 12 scales, which index the 10 PDs included in Section II of the DSM-IV (Paranoid, Schizoid, Schizotypal, Histrionic, Narcissistic, Antisocial, Borderline, Avoidant, Dependent, and Obsessive Compulsive) and the two PDs in the appendix of the DSM-IV (Passive-aggressive and
Depressive). The PDQ-4 can be used to create individual PD diagnoses according to the number of DSM-
IV criteria endorsed, or, it can generate a total score of the number of pathological traits endorsed. Similar to Hopwood et al. (2012) and Anderson et al. (2018) this study used continuous symptom counts rather than categorical PDs, as continuous psychopathology scales are generally more reliable and valid than categorical markers (Markon, Chmielewski, & Miller, 2011). The PDQ-4 has been widely used and demonstrates reasonable convergence with other PD measures (Bagby & Farvolden, 2004). It has been found to be valid and reliable in various countries (Ling, Qian, & Yang, 2010; Calvo et al., 2012), including the UK (Davison, Leese, & Taylor, 2001; Whyte, Fox, & Coxell, 2006).
In the current sample, the overall Cronbach’s alpha coefficient (α) for the whole scale was excellent, with a value of 0.94. Cronbach’s alpha coefficients for the subscales ranged from 0.53 (Obsessive-
Compulsive) to 0.78 (Avoidant), with a mean of 0.65. Some of these values indicate poor internal
consistency (< .60; Streiner, 2003), however, they are similar to α values found in comparable studies (Anderson et al., 2018; Hopwood et al., 2012; Samuel, Hopwood, Krueger, Thomas, & Ruggero, 2013), which is thought to be due to the heterogeneous compositions of symptoms that comprise Section II PDs. Despite this, the PDQ-4 has been used in previous research to compare Section II and Section III models (Anderson et al., 2018; Hopwood et al., 2012).
Due to the PDQ-4 having a dichotomous scoring system, it may be argued that the Ordinal alpha should be calculated, rather than Cronbach’s alpha. Conceptually, the two are the same; however, the Ordinal alpha performs well for dichotomous data (Zumbo, Gadermann & Zeisser, 2007). Therefore, the Ordinal alpha was also calculated for the overall scale (.97), and individual subscales (ranging from 0.59 [Obsessive-Compulsive] to .90 [Avoidant], with a mean of .80), demonstrating good internal consistency.
80 4.3.4 Procedure
The purpose of this study was to validate the SIPP-SF and PID-5-BF in a sample of UK males in the community, in order to later use these scales to screen for PD among prisoners (as demonstrated in the subsequent chapters of the thesis), therefore, as described above in section 4.3.2, a specific sample of males were recruited to participate in this study. The main researcher contacted and distributed questionnaires to several factories, warehouses, garages, call centres and trade jobs in and around Nottinghamshire and Derbyshire. Participants were provided with an information sheet, consent form, battery of tests and debrief form, which were placed within a sealable envelope (please see appendices 5 - 7 for examples of the information sheet, consent form and debrief form). Participants were able to complete the questionnaires on their lunch break at work or could take it home to complete in their own time, returning it to the researcher via a pre-paid envelope. The debrief form contained contact details for the researcher, as well as contact details for any support services if required.
4.3.5 Analysis
4.3.5.1 Analytical procedures
Throughout the whole thesis, all analyses were conducted using SPSS Version 23, Mplus version 7.2 (Muthen & Muthen, 2015) or R (R Core Team, 2017). The psychometric properties of the PID-5-BF and SIPP-SF were investigated by examining the factor structure, internal consistency, discriminant validity and convergent validity of the scales. All variables were examined for normality by assessing skewness and kurtosis, whereby a value between -2 and +2 indicates normality of distributions (George & Mallery, 2010). Additionally, variables were assessed for extreme outliers using boxplots, as extreme outliers may introduce bias into statistical estimates (Kwak & Kim, 2017). In the current study, no variables exceeded the range for skewness and kurtosis, and no extreme outliers were identified, therefore, all cases were used for analytical purposes. All assumptions were met before any of the further analytical techniques were conducted.
Cronbach’s alpha coefficient (α) and mean item-total correlations (MIT) were used to assess the internal consistency of the scales. Internal reliability coefficients should be above 0.6 (Streiner, 2003), and MIT values should be above 0.3 (Nunnally & Bernstein, 1994). Due to the brevity of the PID-5-BF (25 items), mean inter-item (MII) correlations were also conducted to assess internal consistency (optimal range between 0.2-0.4; Briggs & Cheek, 1986). Descriptive statistics were examined, and one sample t-tests were conducted to compare the means of the current sample to previous population means. Discriminant validity among trait domains was assessed by means of divergent intercorrelations. Correlations were interpreted according to Cohen’s guidelines (Cohen, 1988; .10 - .29 = small, .30 - .49 = medium, and .50 – 1.0 = large).
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To explore the factor structure of the questionnaires, a ratio of participants-to-variables of 4:1 or larger is advised (MacCallum, Widaman, Preacher, & Hong, 2001), meaning 100 participants would be required for 25 PID-5-BF items, and 240 participants for 60 SIPP-SF items. Therefore, confirmatory factor analysis (CFA) was only conducted on the PID-5-BF, using robust weighted least squares estimation. In order to assess model fit, the comparative fit index (CFI; Bentler, 1990), Tucker-Lewis Index (TLI; Tucker & Lewis, 1973), and root mean square error of approximation (RMSEA; Browne & Cudeck, 1993) were calculated, in addition to the goodness-of-fit chi-square (χ2) test.
A CFI/TLI value of ≥ .90 is indicative of adequate fit, and a value of ≥ .95 is considered a good fit (Hu & Bentler, 1999). Consistent with Hu and Bentler’s (1999) suggestions, an RMSEA value ≤ .08 is interpreted as adequate fit, with values ≤ .05 being considered good fit. Confidence intervals (CI) were calculated for the RMSEA to provide more information than a point estimate, in which the upper bound of the CI should be ≤ .10 (Chen, Curran, Bollen, Kirby, & Paxton, 2008) for acceptable model fit. A non- significant χ2 value indicates that the model has excellent fit, however, there are various issues with the χ2, including: the assumption of multivariate normality (McIntosh, 2007), and its sensitivity to sample size (Jöreskog & Sörbom, 1993). When considering factor loadings, items with a factor loading of 0.32 and above were considered to significantly load on a factor (Tabachnick & Fidell, 2013).
Discriminant validity was also assessed between the PID-5-BF and SIPP-SF by conducting bivariate correlations, in order to differentiate between personality functioning and personality traits. Finally, convergent validity of the PID-5-BF and SIPP-SF was evaluated by means of bivariate correlations with DSM-IV PD criterion counts (as measured by the PDQ-4).
4.3.5.2 Missing data
No missing data were reported for this study, therefore, all data points were used in the analysis. Although this study involved completing self-report questionnaires, for the majority of participants the main researcher was present at their workplace so was able to offer any help or advice if required.
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