We aimed to validate cross-culturally the Turkish, Moroccan Arabic and Moroccan Berber versions of the 48-item Symptom Questionnaire (SQ-48). Its psychometric properties were assessed in four... Show moreWe aimed to validate cross-culturally the Turkish, Moroccan Arabic and Moroccan Berber versions of the 48-item Symptom Questionnaire (SQ-48). Its psychometric properties were assessed in four samples: patients (n = 150) and controls (n = 103) with Turkish or Moroccan origins (n = 103) and patients (n = 189) and controls (n = 463) with native Dutch origins. Internal consistency and discriminatory power of SQ-48 subscales across groups were adequate to high. However, immigrant groups scored on average higher than Dutch native groups, but there was full configural, metric and partial scalar invariance in the immigrant groups. Although the SQ-48 is a valid measure of psychopathology in immigrant groups of Turkish and Moroccan origins, their cut-off values should likely be higher compared to natives. Show less
Beurs E. de; Blankers, M.; Peen, J.; Rademacher, C.; Podgorski, A.; Dekker, J. 2022
OBJECTIVE\nMETHOD\nRESULTS\nDISCUSSION\nThe uptake of digital interventions in mental health care (MHC) has been slow, as many therapists and patients believe that in-person contact is essential... Show moreOBJECTIVE\nMETHOD\nRESULTS\nDISCUSSION\nThe uptake of digital interventions in mental health care (MHC) has been slow, as many therapists and patients believe that in-person contact is essential for establishing a good working relationship and good outcomes in treatment. The public health policies regarding social distancing during the coronavirus disease-2019 (COVID-19) pandemic forced an abrupt transformation of MHC provisions for outpatients: Since mid-March 2020, nearly all in-person contact was replaced with videoconferencing. The COVID-19 crisis offered a unique opportunity to investigate whether MHC with videoconferencing yields inferior results as compared to in-person interventions.\nIn a large urban MHC facility in the Netherlands, measurement-based care is routine practice. Outcome data are regularly collected to support shared decision making and monitor patient progress. For this study, pretest and post-test data were used to compare outcomes for three cohorts: treatments performed prior to, partially during and entirely during the COVID-19 lockdown. Outcomes were compared in two large data sets: Basic MHC (N = 1392) and Specialized MHC (N = 1040).\nTherapeutic outcomes appeared robust for COVID-19 conditions across the three cohorts: No differences in outcomes were found between treatments that were conducted during lockdown compared to in-person treatments prior to COVID-19, or treatments which started in-person, but needed to be continued by means of videoconferencing.\nVideoconferencing care during the COVID-19 pandemic had similar outcomes compared to traditional in-person care. These real-world results corroborate findings of previous randomized controlled studies and meta-analyses in which videoconferencing and in-person care has been directly compared in terms of clinical effectiveness. Show less
Objective There is a great variety of measurement instruments to assess similar constructs in clinical research and practice. This complicates the interpretation of test results and hampers the... Show moreObjective There is a great variety of measurement instruments to assess similar constructs in clinical research and practice. This complicates the interpretation of test results and hampers the implementation of measurement-based care. Method For reporting and discussing test results with patients, we suggest converting test results into universally applicable common metrics. Two well-established metrics are reviewed: T scores and percentile ranks. Their calculation is explained, their merits and drawbacks are discussed, and recommendations for the most convenient reference group are provided. Results We propose to express test results as T scores with the general population as reference group. To elucidate test results to patients, T scores may be supplemented with percentile ranks, based on data from a clinical sample. The practical benefits are demonstrated using the published data of four frequently used instruments for measuring depression: the CES-D, PHQ-9, BDI-II and the PROMIS depression measure. Discussion Recent initiatives have proposed to mandate a limited set of outcome measures to harmonize clinical measurement. However, the selected instruments are not without flaws and, potentially, this directive may hamper future instrument development. We recommend using common metrics as an alternative approach to harmonize test results in clinical practice, as this will facilitate the integration of measures in day-to-day practice. Show less
The aim of this study was to examine cognitive emotion regulation strategies (CERS) of help-seeking adolescents diagnosed with personality disorders. At pre-treatment, patients (N = 116) were found... Show moreThe aim of this study was to examine cognitive emotion regulation strategies (CERS) of help-seeking adolescents diagnosed with personality disorders. At pre-treatment, patients (N = 116) were found to use some maladaptive but also some adaptive CERS more often than adolescents from the general population. Less than 4% of these pre-treatment CERS predicted treatment outcome. In patients whose treatment outcome according to the Symptom Checklist-90 (SCL-90) showed significant improvement (N = 75), a reduction of maladaptive CERS and an increase of adaptive CERS occurred. Patients that were unchanged or deteriorated (N = 41) showed no significant changes in CERS. In conclusion, pre-treatment CERS are not predictive for treatment outcome in this sample of adolescents diagnosed with personality disorders. Even though patients who use more adaptive and less maladaptive CERS have fewer symptoms, the relationship between these CERS and symptoms in this group of severe patients remains unclear. Show less
BackgroundObservational research based on routine outcome monitoring is prone to missing data, and outcomes can be biased due to selective inclusion at baseline or selective attrition at posttest.... Show moreBackgroundObservational research based on routine outcome monitoring is prone to missing data, and outcomes can be biased due to selective inclusion at baseline or selective attrition at posttest. As patients with complete data may not be representative of all patients of a provider, missing data may bias results, especially when missingness is not random but systematic.MethodsThe present study establishes clinical and demographic patient variables relevant for representativeness of the outcome information. It applies strategies to estimate sample selection bias (weighting by inclusion propensity) and selective attrition bias (multiple imputation based on multilevel regression analysis) and estimates the extent of their impact on an index of provider performance. The association between estimated bias and response rate is also investigated.ResultsProvider‐based analyses showed that in current practice, the effect of selective inclusion was minimal, but attrition had a more substantial effect, biasing results in both directions: overstating and understating performance. For 22% of the providers, attrition bias was estimated to be in excess of 0.05 ES. Bias was associated with overall response rate (r = .50). When selective inclusion and attrition bring providers' response below 50%, it is more likely that selection bias increased beyond a critical level, and conclusions on the comparative performance of such providers may be misleading.ConclusionsEstimates of provider performance were biased by selection, especially by missing data at posttest. Results on the extent and direction of bias and minimal requirements for response rates to arrive at unbiased performance indicators are discussed. Show less
Carlier, I.V.E.; Wiltens, D.H.A.; Rood, Y.R. van; Veen, T. van; Dekker, J.; Hemert, A.M. van 2018
