Ronald M. Rapee’s research while affiliated with Macquarie University and other places

Three decades of research indicate that intolerance of uncertainty (IU) plays a role in the maintenance of mental health conditions. In particular, the relationship between IU and worry is especially strong. The current study aimed to conduct a partial examination of the Intolerance of Uncertainty Model (IUM) of GAD as well as the Transdiagnostic Model of Intolerance of Uncertainty (TMIU), in a clinical sample of adults with GAD using path analysis. Participants with a primary diagnosis of GAD (N = 112) completed a range of measures that assessed IU, cognitive avoidance (CA), positive beliefs about worry (PBW), threat estimates, worry, and anxiety, with two path analysis models constructed for the IUM and TMIU. In a preliminary analysis of the IUM, path analysis found that CA and PBW did not have an indirect effect the relationship between IU and worry, however, CA (and not PBW) had an indirect effect on the relationship between IU and anxiety. For the TMIU, the first model demonstrated a poor fit. In an alternative model, threat estimates were found to indirect effect the relationship between IU and worry as well as anxiety. This suggests that threat appraisals do play a role in the relationship between IU, worry and anxiety in individuals with GAD.

The Penn State Worry Questionnaire (PSWQ) is a 16-item self-report measure designed to assess pathological worry. The PSWQ has, however, demonstrated inconsistent factor structure in adults and older adults leading to the development of the 8-item PSWQ-A and the ultra-brief 3-item PSWQ-3. The PSWQ is yet to be compared to the PSWQ-A and PSWQ-3 in adults with generalised anxiety disorder (GAD). Thus, the current study aimed to evaluate the psychometric properties of these three versions. Participants were screened using the Anxiety Disorders Interview Schedule for DSM-IV-TR to ascertain clinical principal diagnosis of GAD (n = 140) or non-clinical status (n = 76). Four different confirmatory factor models were fit to the 16-item PSWQ, with a unidimensional model fit to the 8-item PSWQ-A and to the PSWQ-3. A bifactor model fitted the data best for the PSWQ, and a unidimensional PSWQ-A model fitted the data best for the GAD sample. Results found that all three versions of the PSWQ demonstrated good construct validity, moderate test-retest reliability, and excellent criterion validity. ROC curve analysis indicated that all three versions demonstrated comparable levels of sensitivity and specificity for screening GAD. Both the PSWQ-A and PSWQ demonstrated no floor or ceiling effects and good internal consistency, whereas the PSWQ-3 demonstrated floor effects with adequate internal consistency. Overall, all three versions of the PSWQ share comparable psychometric properties. As such, the brevity of the PSWQ-A and its comparable performance to the 16-item PSWQ, warrant recommendations for use of this version to researchers and clinicians.

Objective Life interference is a key diagnostic feature for anxiety and depressive disorders. Measures focusing on life interference caused by anxiety and depressive disorders in children and adolescents have received minimal attention. This study evaluated the psychometric properties of the Child Anxiety and Depression Life Interference Scale (CADLIS), a brief child (CADLIS-C) and parent-report (CADLIS-P) measure designed to assess life interference from anxiety and depressive disorders in both the child and parent’s life. Method A total of 672 parents of children aged 4–18 years completed the CADLIS-P, and 627 children aged 7–18 years completed the CADLIS-C. Results The proposed two-factor CADLIS-C model was not supported, instead, due to high inter-factor covariance a one-factor model of life interference was proposed. The one-factor model demonstrated better model fit. The proposed three-factor model for the CADLIS-P was not supported, instead, an exploratory factor analysis found a two-factor model differentiating life interference into child and parent life interference a better model fit. The CADLIS demonstrated excellent internal consistency, good convergent and divergent validity, interrater correlations and was able to differentiate between children with and without clinical levels of anxiety and depressive symptoms. Limitations Limitations of the study included the sample population which consisted of a small clinical sample, an over-representation of high-income families and the use of a panel provider. Conclusions Overall, the CADLIS demonstrated sound psychometric properties. The CADLIS is a reliable measure that demonstrates evidence of convergent validity for the assessment of life interference associated with anxiety and depressive symptoms in children.

There are few psychometrically sound measures of overprotection designed for the caregiver and focusing largely on overt behaviours and actions. The Parental Overprotection Measure (POM) was developed for research with preschool aged children and has been used in a range of research projects and translated into several languages. However, its full psychometric properties have not previously been reported. The aim of the current paper was to evaluate the psychometric properties of the original, English-language version of the POM. Mothers (N = 288) of children aged between 36 and 71 months completed the POM along with measures assessing validity. A subsample (n = 86) also repeated the POM after approximately 5 weeks. Exploratory factor analysis of the present sample, did not show very clear factor structure and we therefore recommend use of the full scale at this stage. However, two, potentially interpretable factors related to restriction and comfort. Reliability for both factors and the total was strong (alphas and omegas .74 to .90) and the (sub)scales all showed good retest reliability (.72 to .75). Correlations with other measures of overprotection were moderate for the total and restriction scales but smaller for comfort and the two subscales correlated differently from each other with other aspects of parenting. The total and restriction subscale correlated moderately with child anxiety but the comfort subscale failed to relate significantly. Overall, the POM shows solid psychometric properties and could be used as a self-report measure of caregiver overprotection.

Background The identification of predictors of treatment response is crucial for improving treatment outcome for children with anxiety disorders. Machine learning methods provide opportunities to identify combinations of factors that contribute to risk prediction models. Methods A machine learning approach was applied to predict anxiety disorder remission in a large sample of 2114 anxious youth (5–18 years). Potential predictors included demographic, clinical, parental, and treatment variables with data obtained pre-treatment, post-treatment, and at least one follow-up. Results All machine learning models performed similarly for remission outcomes, with AUC between 0.67 and 0.69. There was significant alignment between the factors that contributed to the models predicting two target outcomes: remission of all anxiety disorders and the primary anxiety disorder. Children who were older, had multiple anxiety disorders, comorbid depression, comorbid externalising disorders, received group treatment and therapy delivered by a more experienced therapist, and who had a parent with higher anxiety and depression symptoms, were more likely than other children to still meet criteria for anxiety disorders at the completion of therapy. In both models, the absence of a social anxiety disorder and being treated by a therapist with less experience contributed to the model predicting a higher likelihood of remission. Conclusions These findings underscore the utility of prediction models that may indicate which children are more likely to remit or are more at risk of non-remission following CBT for childhood anxiety.