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The revised Psychosis Attachment Measure: Measuring disorganized attachment.

ABSTRACT: OBJECTIVES:The Psychosis Attachment Measure (PAM) is currently the most widely used and validated measure of attachment in psychosis. However, the PAM does not assess disorganized attachment, the type of attachment that has been most closely linked with vulnerability to psychosis. This study aimed to expand the PAM to capture the concept of disorganized attachment and to examine its psychometric properties in a psychosis sample. METHODS:Clinical and academic experts in the field of psychosis and service user representatives were asked to assess the comprehensiveness and comprehensibility of the pool of disorganized items. This process resulted in 12 items hypothesized to capture disorganized attachment that were included with the original items of the PAM. A sample of 144 individuals with either a self-reported diagnosis of, or treatment for, a psychosis-related condition completed a battery of online measures comprising the revised PAM, existing measures of adult disorganized attachment and constructs hypothesized to be conceptually related to disorganized attachment. RESULTS:An exploratory factor analysis was conducted with three factors retained; these were labelled anxious, avoidant and disorganized attachment. The factors displayed good internal consistency and test-retest reliability and the disorganized factor displayed good construct validity with related measures and constructs. CONCLUSIONS:These results provide preliminary evidence that the revised PAM captures the concept of disorganized attachment. However, confirmatory psychometric evaluation of the revised PAM is required, within a separate psychosis sample, to confirm its factor structure. The relationship between these results and the current literature, in addition to the clinical and research implications, are discussed. PRACTITIONER POINTS:We present an expanded version of the Psychosis Attachment Measure (PAM), revised to capture the concept of disorganised attachment in adulthood. This expanded measure showed good reliability and the new disorganized subscale demonstrated construct validity. These results provide preliminary evidence that disorganized attachment can be measured using a simple self-report measure with individuals with psychosis. Further research is required to confirm the structural dimensionality of the revised PAM within a new sample using confirmatory factor analysis. Following further psychometric validation the use of this measure has the potential to be expanded to other mental health conditions in which disorganized attachment has been implicated in the development and maintenance of difficulties, for example, trauma-related conditions and borderline personality disorder.

SUBMITTER: Pollard C

PROVIDER: S-EPMC7496745 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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The revised Psychosis Attachment Measure: Measuring disorganized attachment.

Pollard Catherine C Bucci Sandra S MacBeth Angus A Berry Katherine K

The British journal of clinical psychology 20200515 3

<h4>Objectives</h4>The Psychosis Attachment Measure (PAM) is currently the most widely used and validated measure of attachment in psychosis. However, the PAM does not assess disorganized attachment, the type of attachment that has been most closely linked with vulnerability to psychosis. This study aimed to expand the PAM to capture the concept of disorganized attachment and to examine its psychometric properties in a psychosis sample.<h4>Methods</h4>Clinical and academic experts in the field o ...[more]

PMID: 32415698

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Project description:Importance:There is urgent need to improve the limited prognostic accuracy of clinical instruments to predict psychosis onset in individuals at clinical high risk (CHR) for psychosis. As yet, no reliable biological marker has been established to delineate CHR individuals who will develop psychosis from those who will not. Objectives:To investigate abnormalities in a graph-based gyrification connectome in the early stages of psychosis and to test the accuracy of this systems-based approach to predict a transition to psychosis among CHR individuals. Design, Setting, and Participants:This investigation was a cross-sectional magnetic resonance imaging (MRI) study with follow-up assessment to determine the transition status of CHR individuals. Participants were recruited from a specialized clinic for the early detection of psychosis at the Department of Psychiatry (Universitäre Psychiatrische Kliniken [UPK]), University of Basel, Basel, Switzerland. Participants included individuals in the following 4 study groups: 44 healthy controls (HC group), 63 at-risk mental state (ARMS) individuals without later transition to psychosis (ARMS-NT group), 16 ARMS individuals with later transition to psychosis (ARMS-T group), and 38 antipsychotic-free patients with first-episode psychosis (FEP group). The study dates were November 2008 to November 2014. The dates of analysis were March to November 2017. Main Outcomes and Measures:Gyrification-based structural covariance networks (connectomes) were constructed to quantify global integration, segregation, and small-worldness. Group differences in network measures were assessed using functional data analysis across a range of network densities. The extremely randomized trees algorithm with repeated 5-fold cross-validation was used to delineate ARMS-T individuals from ARMS-NT individuals. Permutation tests were conducted to assess the significance of classification performance measures. Results:The 4 study groups comprised 161 participants with mean (SD) ages ranging from 24.0 (4.7) to 25.9 (5.7) years. Small-worldness was reduced in the ARMS-T and FEP groups and was associated with decreased integration and increased segregation in both groups (Hedges g range, 0.666-1.050). Using the connectome properties as features, a good classification performance was obtained (accuracy, 90.49%; balanced accuracy, 81.34%; positive predictive value, 84.47%; negative predictive value, 92.18%; sensitivity, 66.11%; specificity, 96.58%; and area under the curve, 88.30%). Conclusions and Relevance:These findings suggest that there is poor integration in the coordinated development of cortical folding in patients who develop psychosis. These results further suggest that gyrification-based connectomes might be a promising means to generate systems-based measures from anatomical data to improve individual prediction of a transition to psychosis in CHR individuals.

Dataset Information

The revised Psychosis Attachment Measure: Measuring disorganized attachment.

Publications

The revised Psychosis Attachment Measure: Measuring disorganized attachment.

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