Measuring recovery in deaf, hard-of-hearing, and tinnitus patients in a mental health care setting:validation of the I.ROC

This study was aimed at validating the Individual Recovery Outcomes Counter (I.ROC) for deaf, hard-of-hearing, and tinnitus patients in a mental health care setting. There is a need for an accessible instrument to monitor treatment effects in this population. The I.ROC measures recovery, seeing recovery as a process of experiencing a meaningful life, despite the limitations caused by illness or disability. A total of 84 adults referred to 2 specialist mental health centers for deaf, hard-of-hearing, and tinnitus adults in the Netherlands completed the Dutch version of I.ROC and 3 other instruments. A total of 25 patients refused or did not complete the instruments: 50% of patients using sign language and 18% of patients using spoken language. Participants completed the measures at intake and then every 3 months. In this sample I.ROC demonstrated good internal consistency and convergent validity. Sensitivity to change was good, especially over a period of 6 or 9 months. This study provides preliminary evidence that the I.ROC is a valid instrument measuring recovery for hard-of-hearing and tinnitus patients using spoken language. For deaf patients using sign language, specifically those with limited language skills in spoken and written Dutch, more research is needed.</p

Effects and side-effects of integrating care: the case of mental health care in the Netherlands

Contains fulltext : 56200.pdf ( ) (Open Access)Purpose: Description and analysis of the effects and side-effects of integrated mental health care in the Netherlands. Context of case: Due to a number of large-scale mergers, Dutch mental health care has become an illustration of integration and coherence of care services. This process of integration, however, has not only brought a better organisation of care but apparently has also resulted in a number of serious side-effects. This has raised the question whether integration is still the best way of reorganising mental health care. Data sources: Literature, data books, patients and professionals, the advice of the Dutch Commission for Mental Health Care, and policy papers. Case description: Despite its organisational and patient-centred integration, the problems in the Dutch mental health care system have not diminished: long waiting lists, insufficient fine tuning of care, public order problems with chronic psychiatric patients, etc. These problems are related to a sharp rise in the number of mental health care registrations in contrast with a decrease of registered patients in first-level services. This indicates that care for people with mental health problems has become solely a task for the mental health care services (monopolisation). At the same time, integrated institutions have developed in the direction of specialised medical care (homogenisation). Monopolisation and homogenisation together have put the integrated institutions into an impossible divided position. Conclusions and discussion: Integration of care within the institutions in the Netherlands has resulted in withdrawal of other care providers. These side-effects lead to a new discussion on the real nature and benefits of an integrated mental health care system. Integration requires also a broadly shared vision on good care for the various target groups. This would require a radicalisation of the distinction between care providers as well as a recognition of the different goals of mental health care.11 p

Psychometric properties of the Dutch version of the Evidence-Based Practice Attitude Scale (EBPAS).

BackgroundThe Evidence-Based Practice Attitude Scale (EBPAS) was developed in the United States to assess attitudes of mental health and welfare professionals toward evidence-based interventions. Although the EBPAS has been translated in different languages and is being used in several countries, all research on the psychometric properties of the EBPAS within youth care has been carried out in the United States. The purpose of this study was to investigate the psychometric properties of the Dutch version of the EBPAS.MethodsAfter translation into Dutch, the Dutch version of the EBPAS was examined in a diverse sample of 270 youth care professionals working in five institutions in the Netherlands. We examined the factor structure with both exploratory and confirmatory factor analyses and the internal consistency reliability. We also conducted multiple linear regression analyses to examine the association of EBPAS scores with professionals' characteristics. It was hypothesized that responses to the EBPAS items could be explained by one general factor plus four specific factors, good to excellent internal consistency reliability would be found, and EBPAS scores would vary by age, sex, and educational level.ResultsThe exploratory factor analysis suggested a four-factor solution according to the hypothesized dimensions: Requirements, Appeal, Openness, and Divergence. Cronbach's alphas ranged from 0.67 to 0.89, and the overall scale alpha was 0.72. The confirmatory factor analyses confirmed the factor structure and suggested that the lower order EBPAS factors are indicators of a higher order construct. However, Divergence was not significantly correlated with any of the subscales or the total score. The confirmatory bifactor analysis endorsed that variance was explained both by a general attitude towards evidence-based interventions and by four specific factors. The regression analyses showed an association between EBPAS scores and youth care professionals' age, sex, and educational level.ConclusionsThe present study provides strong support for a structure with a general factor plus four specific factors and internal consistency reliability of the Dutch version of the EBPAS in a diverse sample of youth care professionals. Hence, the factor structure and reliability of the original version of the EBPAS seem generalizable to the Dutch version of the EBPAS

Predicting Undesired Treatment Outcomes With Machine Learning in Mental Health Care: Multisite Study

Background:It remains a challenge to predict which treatment will work for which patient in mental healthcare.Objective:The aims of this multi-site study were two-fold: 1) to predict patient’s response to treatment, during treatment, in Dutch basic mental healthcare using commonly available data from routine care; and 2) to compare the performance of these machine learning models across three different mental healthcare organizations in the Netherlands by using clinically interpretable models.Methods:Using anonymized datasets from three different mental healthcare organizations in the Netherlands (n = 6,452), we applied three times a lasso regression to predict treatment outcome. The algorithms were internally validated with cross-validation within each site and externally validated on the data from the other sites.Results:The performance of the algorithms, measured by the AUC of the internal validations as well as the corresponding external validations, were in the range of 0.77 to 0.80.Conclusions:Machine learning models provide a robust and generalizable approach in automated risk signaling technology to identify cases at risk of poor treatment outcome. Results of this study hold substantial implications for clinical practice by demonstrating that model performance of a model derived from one site is similar when applied to another site (i.e. good external validation)

Predicting Return to Work in Employees Sick-Listed Due to Minor Mental Disorders

Objective To investigate which factors predict return to work (RTW) after 3 and 6 months in employees sick-listed due to minor mental disorders. Methods Seventy GPs recruited 194 subjects at the start of sick leave due to minor mental disorders. At baseline (T0), 3 and 6 months later (T1 and T2, respectively), subjects received a questionnaire and were interviewed by telephone. Using multivariate logistic regression analyses, we developed three prediction models to predict RTW at T1 and T2. Results The RTW rates were 38% after 3 months (T1) and 61% after 6 months (T2). The main negative predictors of RTW at T1 were: (a) a duration of the problems of more than 3 months before sick leave; and (b) somatisation. The main negative predictors of RTW at T2 were: (a) a duration of the problems of more than 3 months before sick leave; (b) more than 3 weeks of sick leave before inclusion in the study; and (c) anxiety. The main negative predictors of RTW at T2 for those who had not resumed work at T1 were: (a) more than 3 weeks of sick leave before inclusion in the study; and (b) depression at T1. The predictive power of the models was moderate with AUC-values between 0.695 and 0.763. Conclusions The main predictors of RTW were associated with the severity of the problems. A long duration of the problems before the occurrence of sick leave and a long duration of sick leave before seeking help predict a relatively small probability to RTW within 3–6 months. High baseline somatisation and anxiety, and high depression after 3 months make the prospect even worse. Since these predictors are readily assessable with just a few questions and a symptom questionnaire, this opens the opportunity to select high-risk employees for a targeted intervention to prevent long-term absenteeism

Red ROM als kwaliteitsinstrument

In het recent verschenen rapport over de bekostiging van de curatieve ggz concludeert de Algemene Rekenkamer (2017): ‘informatie die met ROM [routine outcome monitoring] wordt verkregen, heeft beperkingen en is van onvoldoende kwaliteit om te dienen als sturingsinformatie bij de zorginkoop’ (p. 14). Dit rapport is door een groep psychiaters en psychologen aangegrepen om de petitie ‘Stop benchmark met ROM’ (www.stoprom.com) in het leven te roepen, die inmiddels door ruim 6000 mensen getekend is. In dit artikel reageren wij op deze petitie. Wij onderschrijven dat ROM geen basis mag zijn voor zorginkoop, maar vinden dat ROM en benchmarking van grote waarde kunnen zijn voor het verbeteren van de kwaliteit van de behandeling en pleiten daarom voor inhoudelijke doorontwikkeling van benchmarking in plaats van deze te stoppen

Improving long-term outcome of depression in primary care:a review of RCTs with psychological and supportive interventions

Background and objectives: Depression is often a recurrent or persistent disorder. Since the majority of depressed patients are treated in primary care, it is clear that to improve long-term outcomes more effective treatments in this setting are needed. The goal of this study was to review the strategies used for improvement of routine treatment in terms of their effects on patient outcome. Methods: We conducted a systematic literature search to identify improvement strategies tested in randomized controlled trials in primary care, reporting at least six months effects on depression course and outcome. Results: Four strategies were identified: (1) training primary care physicians (PCPs) - this appears ineffective (2) supporting PCPs by other professionals - this produces better short term outcomes but does not prevent recurrence (3) organisational quality improvement - this shows improved outcomes at 6 months, and there is some evidence of longer term effectiveness; and (4) recurrence - and chronicity prevention strategies - these have not been shown to be effective. Conclusion: Since effects of the reviewed strategies generally do not seem to persist over time and no clear superiority over usual care has been demonstrated, we conclude that for improving long-term outcome of depression in primary care new directions or even a novel paradigm is needed

Improving long-term outcome of depression in primary care:a review of RCTs with psychological and supportive interventions

Background and objectives: Depression is often a recurrent or persistent disorder. Since the majority of depressed patients are treated in primary care, it is clear that to improve long-term outcomes more effective treatments in this setting are needed. The goal of this study was to review the strategies used for improvement of routine treatment in terms of their effects on patient outcome. Methods: We conducted a systematic literature search to identify improvement strategies tested in randomized controlled trials in primary care, reporting at least six months effects on depression course and outcome. Results: Four strategies were identified: (1) training primary care physicians (PCPs) - this appears ineffective (2) supporting PCPs by other professionals - this produces better short term outcomes but does not prevent recurrence (3) organisational quality improvement - this shows improved outcomes at 6 months, and there is some evidence of longer term effectiveness; and (4) recurrence - and chronicity prevention strategies - these have not been shown to be effective. Conclusion: Since effects of the reviewed strategies generally do not seem to persist over time and no clear superiority over usual care has been demonstrated, we conclude that for improving long-term outcome of depression in primary care new directions or even a novel paradigm is needed