Computerized adaptive testing in primary care: CATja

In this dissertation, research is described that has been conducted to develop an online test battery (named CATja) that supports general practitioners and mental health assistants (MHAs) in deciding which level of care suits their clients that experience diverse psychological complaints best. Would treatment in general practices be sufficient, or is referral to generalist or specialist mental health care required? For this, CATja generates a profile of complaints (e.g. depression) and strengths (e.g. emotional support). In order to incorporate the valuable experience, knowledge and wishes of the intended users, CATja has been developed in close collaboration with MHAs from the beginning. The innovative feature of CATja is its adaptive character, making it very efficient in practice. Adaptive means that follow-up questions during test administration are tailored to answers given to preceding questions. After each answer provided, the extent to which a certain domain (e.g. fear) is present in a client is newly computed and it is determined which follow-up question yields most information given this level of fear. Questions that provide little information are skipped. One could say that 'the behavior' of a 'computerized adaptive test' (CAT, hence the name CATja), as it were, mimics the behavior of an experienced interviewer. The first version of CATja includes five psychopathology domains: anxiety, depression, distress (general stress symptoms), and negative and positive symptoms of psychosis. In addition, MHAs can map the quality of clients’ social networks by use the domains emotional support and friendship. First results of our implementation study are promising

A Step Towards a Better Understanding of Pain Phenotypes: Latent Class Analysis in Chronic Pain Patients Receiving Multimodal Inpatient Treatment

Purpose: The number of non-responders to treatment among patients with chronic pain (CP) is high, although intensive multimodal treatment is broadly accessible. One reason is the large variability in manifestations of CP. To facilitate the development of tailored treatment approaches, phenotypes of CP must be identified. In this study, we aim to identify subgroups in patients with CP based on several aspects of self-reported health. Patients and Methods: A latent class analysis (LCA) was carried out in retrospective data from 411 patients with CP of different origins. All patients experienced severe physical and psychosocial consequences and were therefore undergoing multimodal inpatient pain treatment. Self-reported measures of pain (visual analogue scales for pain intensity, frequency, and impairment; Pain Perception Scale), emotional distress (Patient Health Questionnaire, PHQ-9; Generalized Anxiety Disorder Scale, GAD-7) and physical health (Short Form Health Survey; SF-8) were collected immediately after admission and before discharge. Instruments assessed at admission were used as input to the LCA. Resulting classes were compared in terms of patient characteristics and treatment outcome. Results: A model with four latent classes demonstrated the best model fit and interpretability. Classes 1 to 4 included patients with high (54.7%), extreme (17.0%), moderate (15.6%), and low (12.7%) pain burden, respectively. Patients in class 4 showed high levels of emotional distress, whereas emotional distress in the other classes corresponded to the levels of pain burden. While pain as well as physical and mental health improved in class 1, only the levels of depression and anxiety improved in patients in the other groups during multimodal treatment. Conclusion: The specific needs of these subgroups should be taken into account when developing individualized treatment programs. However, the retrospective design limits the significance of the results and replication in prospective studies is desirable

Reprint of:Negative symptoms predict high relapse rates and both predict less favorable functional outcome in first episode psychosis, independent of treatment strategy

Background: In first episode psychosis (FEP) baseline negative symptoms (BNS) and relapse both predict less favorable functional outcome. Relapse-prevention is one of the most important goals of treatment. Apart from discontinuation of antipsychotics, natural causes of relapse are unexplained. We hypothesized that BNS, apart from predicting worse functional outcome, might also increase relapse risk. Methods: We performed a post-hoc analysis of 7-year follow-up data of a FEP cohort (n = 103) involved in a dose-reduction/discontinuation (DR) vs. maintenance treatment (MT) trial. We examined: 1) what predicted relapse, 2) what predicted functional outcome, and 3) if BNS predicted relapse, whether MT reduced relapse rates compared to DR. After remission patients were randomly assigned to DR or MT for 18 months. Thereafter, treatment was uncontrolled. Outcomes: BNS and duration of untreated psychosis (DUP) predicted relapse. Number of relapses, BNS, and treatment strategy predicted functional outcome. BNS was the strongest predictor of relapse, while number of relapses was the strongest predictor of functional outcome above BNS and treatment strategy. Overall and within MT, but not within DR, more severe BNS predicted significantly higher relapse rates. Treatment strategies did not make a difference in relapse rates, regardless of BNS severity. Interpretation: BNS not only predicted worse functional outcome, but also relapses during follow-up. Since current low dose maintenance treatment strategies did not prevent relapse proneness in patients with more severe BNS, resources should be deployed to find optimal treatment strategies for this particular group of patients. (C) 2019 Elsevier B.V. All rights reserved

Negative symptoms predict high relapse rates and both predict less favorable functional outcome in first episode psychosis, independent of treatment strategy

BACKGROUND: In first episode psychosis (FEP) baseline negative symptoms (BNS) and relapse both predict less favorable functional outcome. Relapse-prevention is one of the most important goals of treatment. Apart from discontinuation of antipsychotics, natural causes of relapse are unexplained. We hypothesized that BNS, apart from predicting worse functional outcome, might also increase relapse risk. METHODS: We performed a post-hoc analysis of 7-year follow-up data of a FEP cohort (n = 103) involved in a dose-reduction/discontinuation (DR) vs. maintenance treatment (MT) trial. We examined: 1) what predicted relapse, 2) what predicted functional outcome, and 3) if BNS predicted relapse, whether MT reduced relapse rates compared to DR. After remission patients were randomly assigned to DR or MT for 18 months. Thereafter, treatment was uncontrolled. OUTCOMES: BNS and duration of untreated psychosis (DUP) predicted relapse. Number of relapses, BNS, and treatment strategy predicted functional outcome. BNS was the strongest predictor of relapse, while number of relapses was the strongest predictor of functional outcome above BNS and treatment strategy. Overall and within MT, but not within DR, more severe BNS predicted significantly higher relapse rates. Treatment strategies did not make a difference in relapse rates, regardless of BNS severity. INTERPRETATION: BNS not only predicted worse functional outcome, but also relapses during follow-up. Since current low dose maintenance treatment strategies did not prevent relapse proneness in patients with more severe BNS, resources should be deployed to find optimal treatment strategies for this particular group of patients

A Smart Screening Device for Patients with Mental Health Problems in Primary Health Care:Development and Pilot Study

BACKGROUND: Adequate recognition of mental health problems is a prerequisite for successful treatment. Although most people tend to consult their general practitioner (GP) when they first experience mental health problems, GPs are not very well equipped to screen for various forms of psychopathology to help them determine clients' need for treatment. OBJECTIVE: In this paper, the development and characteristics of CATja, a computerized adaptive test battery built to facilitate triage in primary care settings, are described, and first results of its implementation are reported. METHODS: CATja was developed in close collaboration with GPs and mental health assistants (MHAs). During implementation, MHAs were requested to appraise clients' rankings (N=91) on the domains to be tested and to indicate the treatment level they deemed most appropriate for clients before test administration. We compared the agreement between domain score appraisals and domain score computed by CATja and the agreement between initial (before test administration) treatment level advice and final treatment level advice. RESULTS: Agreements (Cohen kappas) between MHAs' appraisals of clients' scores and clients' scores computed by CATja were mostly between .40 and .50 (Cohen kappas=.10-.20), and the agreement between "initial" treatment levels and the final treatment level advised was .65 (Cohen kappa=.55). CONCLUSIONS: Using CATja, caregivers can efficiently generate summaries of their clients' mental well-being on which decisions about treatment type and care level may be based. Further validation research is needed

Searching for the optimal number of response alternatives for the distress scale of the four-dimensional symptom questionnaire

BACKGROUND: The Four-Dimensional Symptom Questionnaire (4DSQ) is a self-report questionnaire designed to measure distress, depression, anxiety, and somatization. Prior to computing scale scores from the item scores, the three highest response alternatives ('Regularly', 'Often', and 'Very often or constantly present') are usually collapsed into one category to reduce the influence of extreme responding on item- and scale scores. In this study, we evaluate the usefulness of this transformation for the distress scale based on a variety of criteria. METHODS: Specifically, by using the Graded Response Model, we investigated the effect of this transformation on model fit, local measurement precision, and various indicators of the scale's validity to get an indication on whether the current practice of recoding should be advocated or not. In particular, the effect on the convergent- (operationalized by the General Health Questionnaire and the Maastricht Questionnaire), divergent- (operationalized by the Neuroticism scale of the NEO-FFI), and predictive validity (operationalized as obtrusion with daily chores and activities, the Biographical Problem list and the Utrecht Burnout Scale) of the distress scale was investigated. RESULTS: Results indicate that recoding leads to (i) better model fit as indicated by lower mean probabilities of exact test statistics assessing item fit, (ii) small (<.02) losses in the sizes of various validity coefficients, and (iii) a decrease (DIFF (SE's) = .10-.25) in measurement precision for medium and high levels of distress. CONCLUSIONS: For clinical applications and applications in longitudinal research, the current practice of recoding should be avoided because recoding decreases measurement precision for medium and high levels of distress. It would be interesting to see whether this advice also holds for the three other domains of the 4DSQ