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Cognitive behaviour therapy-enhanced (CBT-E) is an effective treatment for non-underweight patients with eating disorders. Its efficacy and effectiveness is investigated mostly among transdiagnostic samples and remains unknown for binge eating disorder. The aim of the present study was to assess several treatment outcome predictors and to compare effectiveness of CBT-E among adult out-patients with bulimia nervosa (n=370), binge eating disorder (n=113), and those with a restrictive food pattern diagnosed with other specified feeding and eating disorders (n=139). Effectiveness of CBT-E was assessed in routine clinical practice in a specialised eating disorders centre. Eating disorder pathology was measured with the EDEQ pre- and post-treatment, and at 20 weeks follow-up. Linear mixed model analyses with fixed effect were performed to compare treatment outcome among the eating disorder groups. Several predictors of treatment completion and outcome were examined with a regression analysis. No predictors for drop-out were found, except the diagnosis of bulimia nervosa. Eating disorder pathology decreased among all groups with effect sizes between 1.43 and 1.70 on the EDE-Q total score. There were no differences in remission rates between the three groups at end of treatment or at follow-up. Eating disorder severity at baseline affected treatment response. The results can be generalised to other specialised treatment centres. No subgroup of patients differentially benefited from CBT-E supporting the transdiagnostic perspective for the treatment of eating disorders. Longer-term follow-up data are necessary to measure persistence of treatment benefits. Key learning aims (1) What is the effectiveness of CBT-E among patients suffering from binge eating disorder? (2) Does any subgroup of patients suffering from an eating disorder differentially benefit from CBT-E? (3) What factors predict treatment response?

Background: Saudi Arabia is undergoing rapid sociocultural changes, which may have led to an increase of body mass index and eating disorder pathology. The aim of this study is to investigate whether body dissatisfaction, self-esteem, having lived abroad, cultural orientation, perceived stress, media use, and socioeconomic status are correlates of eating disorder pathology with body mass index as a covariate. Additional aims are to investigate if cultural orientation is associated with symptomatology and if stress is a covariate in the association between eating disorder pathology and Western orientation. Method: Self-report measures were administered in a convenience Saudi community sample (N = 1225) between April 2017 and May 2018. Hierarchical multiple linear regression analyses with eating disorder pathology as dependent variable were performed to establish the associations among the variables. Results: After adjusting for the effect of BMI, only body dissatisfaction and eating disorder pathology were moderately associated. Eating disorder pathology and body dissatisfaction were more severe among Saudi citizens with a higher BMI. Discussion: Several explanations for the lack of associations of westernization, self-esteem, and stress with eating disorder pathology are reviewed and discussed. The majority of this convenience sample existed of young unmarried Saudi females of high socioeconomic status. Of the total sample, 35% displayed eating disorder pathology which may be a reflection of the high rates of excess weight. Plain English summary: Eating disorders were assumed to be rare in Saudi Arabia, however, Saudi citizens report both, increased pressure to be thin and eating disorder pathology. Saudi Arabia is dealing with rapid sociocultural changes. Consequences of these sociocultural changes, which might be associated with eating disorder pathology, are an increase of BMI, body dissatisfaction, low self-esteem, westernization, perceived stress, media use, and socioeconomic status. In addition, the increase in BMI might strengthen the associations between eating disorder pathology and body dissatisfaction, low self-esteem, perceived stress, media use, and socioeconomic status. Alternative explanations might be that cultural values are associated with different eating disorder symptoms or that eating disorder pathology is associated with stress stemming from transformation that aims to empower women and modernize Saudi society. This study showed that only BMI and body dissatisfaction were associated with eating disorder pathology, and BMI was a covariate in the association between eating disorder pathology and body dissatisfaction. Preventative programs focused on avoidance of maladaptive weight loss strategies and the improvement of body satisfaction might be beneficial in Saudi Arabia.

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 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.

Purpose Previous studies of the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) interview version suggested a second-order model, with a general disability factor and six factors on a lower level. The goal of this study is to investigate if we can find support for a similar higher-order factor structure of the 36-item self-report version of the WHODAS 2.0 in a Dutch psychiatric outpatient sample. We aim to give special attention to the differences between the non-working group sample and the working group sample. Additionally, we intend to provide preliminary norms for clinical interpretation of the WHODAS 2.0 scores in psychiatric settings. Methods Patients seeking specialized ambulatory treatment, primarily for depressive or anxiety symptoms, completed the WHODAS 2.0 as part of the initial interview. The total sample consisted of 770 patients with a mean age of 37.5 years (SD = 13.3) of whom 280 were males and 490 were females. Several factorial compositions (i.e., one unidimensional model and two second-order models) were modeled using confirmatory factor analysis (CFA). Descriptive statistics, model-fit statistics, reliability of the (sub)scales, and preliminary norms for interpreting test scores are reported. Results For the non-working group, the second-order model with a general disability factor and six factors on a lower level, provided an adequate fit. Whereas, for the working group, the second-order model with a general disability factor and seven factors on a lower level seemed more appropriate. The WHODAS 2.0 36-item self-report form showed adequate levels of reliability. Percentile ranks and normalized T-scores are provided to aid clinical evaluations. Conclusion Our results lend support for a factorial structure of the WHODAS 2.0 36-item self-report version that is comparable to the interview version. While we conjecture that a seven-factor solution might give a better reflection of item content and item variance, further research is needed to assess the clinical relevance of such a model. At this point, we recommend using the second-order structure with six factors that matches past findings of the interview form.

Background: In a previous study which made a comparison between disorder-specific and generic instruments to assess outcome of treatments for depression, the Beck Depression Inventory, Second Edition (BDI-II) seemed to be more sensitive to change than the Inventory of Depressive Symptoms- Self Rating (IDS-SR).Methods: A set with longitudinal data from Routine Outcome Monitoring (n=144) were analyzed with multilevel models with random intercepts. The sensitivity to change of two disorder-specific instruments, the BDI-II and the IDS-SR, were compared head to head.Results: The BDI-II was more sensitive to change when measuring treatment outcome compared to the IDS-SR. The BDI-II decreases significantly more over time than the IDS-SR: the average decrease per week for the IDS-SR is -.012 (95%CI -0.015, -0.009) and for the BDI-II it is -.017 (95%CI -0.021, -0.014).Limitations: Conclusions can only be preliminary due to a small sample size.Conclusions: Treatment outcomes measured with questionnaires may differ depending on the degree of sensitivity to change of the instruments.

Background Owing to the gap between treatment supply and demand, there are long waiting periods for patients with binge eating disorder, and there is an urgent need to increase their access to specialized treatment. Guided self-help cognitive behavioral therapy–enhanced (CBT-E) may have great advantages for patients if its efficacy can be established. Objective The aim of this study was to examine the efficacy of guided self-help CBT-E compared with that of a delayed-treatment control condition. Methods A single-blind 2-arm randomized controlled trial was designed to evaluate guided self-help CBT-E according to an intention-to-treat analysis. A total of 180 patients were randomly assigned to guided self-help CBT-E (n=90, 50%) or the delayed-treatment control condition (n=90, 50%) for which guided self-help CBT-E was provided after the initial 12-week delay. The primary outcome was reduction in binges. The secondary outcome was full recovery at the end of treatment, as measured using the Eating Disorder Examination during the last 4 weeks of treatment. A linear mixed model analysis was performed to compare treatment outcomes at the end of treatment. A second linear mixed model analysis was performed to measure between- and within-group effects for up to 24 weeks of follow-up. The Eating Disorder Examination–Questionnaire and clinical impairment assessment were conducted before and after treatment and during follow-up. In addition, dropout rates were assessed in both conditions. Results During the last 4 weeks of treatment, objective binges reduced from an average of 19 (SD 16) to 3 (SD 5) binges, and 40% (36/90) showed full recovery in the guided self-help CBT-E group. Between-group effect size (Cohen d) was 1.0 for objective binges. At follow-up, after both groups received treatment, there was no longer a difference between the groups. Of the 180 participants, 142 (78.9%) completed treatment. The overall treatment dropout appeared to be associated with gender, level of education, and number of objective binges at baseline but not with treatment condition. Conclusions This is the first study to investigate the efficacy of guided self-help CBT-E. Guided self-help CBT-E appeared to be an efficacious treatment. This study’s findings underscore the international guidelines recommending this type of treatment for binge eating disorder. Trial Registration Netherlands Trial Registry (NTR) NL7994; https://trialsearch.who.int/Trial2.aspx?TrialID=NL7994 International Registered Report Identifier (IRRID) RR2-10.1186/s12888-020-02604-1

BACKGROUND Owing to the gap between treatment supply and demand, there are long waiting periods for patients with binge eating disorder, and there is an urgent need to increase their access to specialized treatment. Guided self-help cognitive behavioral therapy–enhanced (CBT-E) may have great advantages for patients if its efficacy can be established. OBJECTIVE The aim of this study was to examine the efficacy of guided self-help CBT-E compared with that of a delayed-treatment control condition. METHODS A single-blind 2-arm randomized controlled trial was designed to evaluate guided self-help CBT-E according to an intention-to-treat analysis. A total of 180 patients were randomly assigned to guided self-help CBT-E (n=90, 50%) or the delayed-treatment control condition (n=90, 50%) for which guided self-help CBT-E was provided after the initial 12-week delay. The primary outcome was reduction in binges. The secondary outcome was full recovery at the end of treatment, as measured using the Eating Disorder Examination during the last 4 weeks of treatment. A linear mixed model analysis was performed to compare treatment outcomes at the end of treatment. A second linear mixed model analysis was performed to measure between- and within-group effects for up to 24 weeks of follow-up. The Eating Disorder Examination–Questionnaire and clinical impairment assessment were conducted before and after treatment and during follow-up. In addition, dropout rates were assessed in both conditions. RESULTS During the last 4 weeks of treatment, objective binges reduced from an average of 19 (SD 16) to 3 (SD 5) binges, and 40% (36/90) showed full recovery in the guided self-help CBT-E group. Between-group effect size (Cohen d) was 1.0 for objective binges. At follow-up, after both groups received treatment, there was no longer a difference between the groups. Of the 180 participants, 142 (78.9%) completed treatment. The overall treatment dropout appeared to be associated with gender, level of education, and number of objective binges at baseline but not with treatment condition. CONCLUSIONS This is the first study to investigate the efficacy of guided self-help CBT-E. Guided self-help CBT-E appeared to be an efficacious treatment. This study’s findings underscore the international guidelines recommending this type of treatment for binge eating disorder. CLINICALTRIAL Netherlands Trial Registry (NTR) NL7994; https://trialsearch.who.int/Trial2.aspx?TrialID=NL7994 INTERNATIONAL REGISTERED REPORT RR2-10.1186/s12888-020-02604-1

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 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.

PURPOSE\nMETHOD\nRESULTS\nDISCUSSION\nLEVEL OF EVIDENCE\nThe aim of this study was to develop an Arabic version of the EDE-Q and to assess its psychometric properties and utility as a screener in the Saudi population. An additional aim was to establish EDE-Q norms for Saudis.\nEDE-Q data were collected in a convenience sample of the Saudi community (N = 2690), of which a subset was also subjected to the EDE interview (N = 98). Various models for the factor structure were evaluated on their fit by CFA. With ROC analysis, the AUC was calculated to test how well the EDE-Q discriminated between Saudis at high and low risk for eating disorders.\nThe original four factor model of the EDE-Q was not supported. Best fit was found for a three factor model, including the weight/shape concern scale, dietary restraint scale and eating concern scale. The ROC analysis showed that the EDE-Q could accurately discriminate between individuals at high and low risk for an eating disorder according to the EDE interview. Optimal cut off of 2.93 on the global score yielded a sensitivity of 82% and specificity of 80%. EDE-Q scores were fairly associated with BMI.\nPsychometric characteristics of the Saudi version of the EDE-Q were satisfactory and results support the discriminant and convergent validity. Severity level of eating disorder pathology can be determined by the EDE-Q global score. Global scores were high compared to what is found in Western community samples, leading to high prevalence estimates for Saudis at high risk for eating disorders.\nNot applicable, empirical psychometric study.

Background: There is a considerable gap between care provision and the demand for care for common mental disorders in low-and-middle-income countries. Screening for these disorders, e.g., in primary care, will help to close this gap. However, appropriate norms and threshold values for screeners of common mental disorders are lacking. Methods: We gathered data on frequently used screeners for alcohol use disorders, depression, and anxiety disorders in a representative sample from Suriname, a non-Latin American Caribbean country. Results: We established cut-off values, normsNorms and crosswalk tables were established for the conversion of raw scores into a common metric: T-scores. Furthermore, recommended cut-off values on the T-score metric for severity levels were compared with international cut-off values for raw scores on these screeners. The appropriateness of these cut-offs and the value of converting raw scores into T-scores are discussed. Conclusion: Cut-off values help with screening and early detection of those who are likely to have a common mental health disorder and may require treatment. Conversion to a common metric simplifies the interpretation of test results.

Public Significance Statement This study suggests that PROMIS CATs for Depression and Anxiety measure the same constructs as matching BSI subscales in Dutch adult patients treated for common mental disorders, are at least as able to detect change over time, and categorize the change scores of more patients as actually changed. Based on these findings, the PROMIS CATs may be considered a modest improvement as tools for reviewing treatment progress with patients.We evaluated construct validity, responsiveness, and utility of change indicators of the Dutch-Flemish PROMIS adult v1.0 item banks for Depression and Anxiety administered as computerized adaptive test (CAT). Specifically, the CATs were compared to the Brief Symptom Inventory (BSI) using pre- and re-test data of adult patients treated for common mental disorders (N = 400; median pre-to-re-test interval = 215 days). Construct validity was evaluated with Pearson's correlations and Cohen's ds; responsiveness with Pearson's correlations and pre-post effect sizes (ES); utility of change indicators with kappa coefficients and percentages of (dis)agreement. The results showed that the PROMIS CATs measure similar constructs as matching BSI scales. Under the assumption of measuring similar constructs, the CAT and BSI Depression scales were similarly responsive. For the Anxiety scales, we found a higher responsiveness for CAT (ES = 0.64) compared to the BSI (ES = 0.50). Finally, both CATs categorized the change scores of more patients as changed compared to matching BSI scales, indicating that the PROMIS CATs may be more able to detect actual change than the BSI. Based on these findings, the PROMIS CATs may be considered a modest improvement over matching BSI scales as tools for reviewing treatment progress with patients. We discuss several additional differences between the PROMIS CATs and the BSI to help test users choose instruments. These differences include the adopted measurement theory (Item Response Theory vs. Classical Test Theory), the mode of administration (CAT vs. fixed items), and the area of application (universal vs. predominantly clinical).

Background Suriname is a Low-middle income country consisting of diverse population groups. Epidemiological studies concerning mental disorders like depression and anxiety had not been conducted until 2015. The treatment gap for mental disorders in Low and middle-income countries (LMICs) may reach 76-80% as treatment is not always readily available. In this study, we estimate and compare the prevalence of potential cases of depression and anxiety, as well as the size of the treatment gap in a rural (Nickerie) and urban (Paramaribo) region of Suriname, a lower middle-income country. Methods Subjects were selected by a specific sampling method of the national census bureau. The Center for Epidemiological Studies-Depression (CES-D) was used to assess depression. Generalized anxiety disorder was assessed with the Generalized Anxiety Disorder 7 (GAD-7) and The Agoraphobic Cognitions Questionnaire (ACQ), the Body Sensations Questionnaire (BSQ) were used to assess Panic disorder. The treatment gap was calculated by estimating the percentage of subjects with depression or anxiety that did not seek out professional help. Results About 18% of the respondents from Nickerie and 16% from Paramaribo were at risk of depression and the established cut-off values of the instruments used indicate that about 3-4% in both regions may suffer from Generalized Anxiety Disorder. Women in both samples were most at risk of high anxiety about body sensations and maladaptive thoughts about panic. The treatment gap varies between 78 and 100% for the two disorders. Conclusions A high depression rate has been found in both areas, especially among young females. In addition, a high treatment gap is noted which insinuates that more therapeutic strategies are required to tackle depression and anxiety in Suriname.

We used the Dutch–Flemish version of the USA PROMIS adult V1.0 item bank for Anxiety as input for developing a computerized adaptive test (CAT) to measure the entire latent anxiety continuum. First, psychometric analysis of a combined clinical and general population sample ( N = 2,010) showed that the 29-item bank has psychometric properties that are required for a CAT administration. Second, a post hoc CAT simulation showed efficient and highly precise measurement, with an average number of 8.64 items for the clinical sample, and 9.48 items for the general population sample. Furthermore, the accuracy of our CAT version was highly similar to that of the full item bank administration, both in final score estimates and in distinguishing clinical subjects from persons without a mental health disorder. We discuss the future directions and limitations of CAT development with the Dutch–Flemish version of the PROMIS Anxiety item bank.

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. 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.

Aim: The aim of this paper is to compare single-level and multilevel regression analysis to obtain risk-adjusted outcomes from mental health care providers. Subject and methods: The study population consisted of adult patients receiving treatment for common mental health disorders. The outcome was self-reported symptom level at post-test. Risk adjustment models were developed using single- and multilevel regression analysis. In the multilevel approach, a random intercept for each provider was included. The intraclass correlation coefficient was used to estimate the proportion of variability in treatment outcome between providers. Spearman correlation coefficient of ranks was used to compare results between the two approaches. Results: The effects of most casemix variables on outcomes were similar for the two models. The ranking of providers in both methods was also quite similar (ρ =.99). The multilevel model estimated that 5.4% of total variability in adjusted post-test scores was explained by the provider factor. Conclusions: The findings of risk adjustment of mental health outcomes are quite robust for the use of single-level or multilevel regression analysis in the current study. However, given the small but significant amount of variation in outcomes that is attributable to providers, the multilevel approach is recommended for dealing with outcomes when patients are clustered within providers.

BackgroundThe prevalence of eating disorders has been assumed to be low in the Arab world, due to the alleged absence of the thin ideal. However, the Arab world is undergoing rapid sociocultural changes, and there are reports of an increase of the desire to be thin. This literature review therefore provides point-prevalence of Arabs at high risk for eating disorders, and a comprehensive synthesis of correlates of eating disorder symptoms, eating disorder-related variables and of a high risk for eating disorders.MethodSeveral electronic databases were searched for published, peer-reviewed studies between 1986 and 2019 involving several key terms. From 317 screened studies, 81, mainly cross-sectional, were included. Preferred Reporting Items for Systematic reviews and meta-analyses was used as guidance and the quality of studies were assessed using the Newcastle-Ottawa scale.ResultsEstimates of individuals at high risk for eating disorders ranged from 2 to 54.8%. The eating disorder-related variables identified were desire to be thin, body dissatisfaction, disturbed-, and dieting- eating behavior. Identified correlates were increased affluence, media use, western influences, and obesity. An additional finding was that in some cases eating disorders were expressed somatically rather than psychiatrically.DiscussionIn the Arab world, females were most at risk for eating disorders and eating disorder symptoms. Sociocultural changes gave rise to the thin ideal and the prevalence of obesity, increasing the risk for the development of eating disorder-related variables and eating disorders. The literature on eating disorders in the Arab world suffers from potential limitations due to the use of non-validated assessment tools. Further research is necessary, particularly on the development and validation of a culturally sensitive assessment tool. Improved knowledge is likely to increase the number of people seeking treatment and decrease the stigma of psychotherapy.

Background Binge eating disorder is characterized by recurrent episodes of binge eating accompanied by a sense of lack of control. Of the different treatments available, Cognitive Behavioral Therapy-Enhanced and guided self-help treatment are recommended. As online treatment offers several additional advantages, we have developed a CBT-Enhanced online guided self-help intervention. The aim of this study is to determine whether this intervention reduces eating disorder pathology and increases the amount of binge free days in adults classified with binge eating disorder or other specified feeding or eating disorder- binge eating disorder, compared to an untreated waiting list condition. The experimental condition is hypothesized to be superior to the waiting list condition. Methods The efficacy of an online guided self-help intervention for binge eating disorder will be assessed by conducting a randomized controlled trial. The trial will target adult individuals classified with binge eating disorder or other specified feeding or eating disorder- binge eating disorder with a body mass index between 19.5 and 40, referred to an eating disorder treatment center. Dual arm allotment will be performed in a 1:1 ratio stratified for BMI above or below 30. Randomization will be blinded to the online intervention (n = 90), or to the control waiting list condition (n = 90). Assessors will be blinded and assessments will be administered at baseline, week 5, at end-of-treatment, and at 12 and 24 weeks follow-up. Primary outcome will be eating disorder pathology, operationalized as number of days on which binge eating occurred between the two conditions during the period of the intervention. Secondary outcome measures will be differences in other eating disorder pathology, clinical impairment and in quality of life, while therapeutic alliance, demographic characteristics and followed treatment module will serve as effect moderators. Several types of costs will be assessed. Discussion This paper presents an online guided self-help Cognitive Behavioral Therapy- Enhanced study protocol for individuals classified with binge eating disorder or other specified feeding or eating disorder. Efficacy will be examined through a Randomized Controlled Trial. Trial registration The study protocol is registered with the Netherlands Trial Registry NTR (NTR 7994) since 6 September 2019.

Purpose: Decisional conflict refers to the degree to which patients are engaged in and feel comfortable about important clinical decisions. Until now, the concept has received little attention in mental health care. We investigate the level of decisional conflict in mental health care and whether this is influenced by socio-demographics, treatment setting, diagnoses, and locus of control.Methods: Cross-sectional study among 186 patients in Dutch specialist mental health care using the Decisional Conflict Scale, which measures five dimensions of decisional conflict: information, support, clarification of values, certainty, and decisional quality. Descriptive statistics and forward stepwise linear regression analyses were used.Results: Patients report relatively high levels of decisional conflict, especially those with more external locus of control. Having a personality disorder and higher education also increases decisional conflict on the dimensions support and clarification of values, respectively. Less decisional conflict was experienced by patients with psychotic disorders on the dimension certainty and by women on the information domain.Conclusions: Decisional conflict is common among patients in specialist mental health care and is very useful for assessing the quality of clinical decision making. Measuring decisional conflict and knowledge about influencing factors can be used to improve patients' participation in clinical decision making, adherence to treatment and clinical outcomes.

We developed a Dutch-Flemish version of the patient-reported outcomes measurement information system (PROMIS) adult V1.0 item bank for depression as input for computerized adaptive testing (CAT). As item bank, we used the Dutch-Flemish translation of the original PROMIS item bank (28 items) and additionally translated 28 U.S. depression items that failed to make the final U.S. item bank. Through psychometric analysis of a combined clinical and general population sample ( N = 2,010), 8 added items were removed. With the final item bank, we performed several CAT simulations to assess the efficiency of the extended (48 items) and the original item bank (28 items), using various stopping rules. Both item banks resulted in highly efficient and precise measurement of depression and showed high similarity between the CAT simulation scores and the full item bank scores. We discuss the implications of using each item bank and stopping rule for further CAT development.

A meaningful comparison of clinical outcomes of mental health care providers requires risk adjustment of case mix variables that affect treatment outcome. The first goal of the present study was to describe the risk adjustment method we applied to routine outcome monitoring data in The Netherlands. Second, the consequences of risk adjustment for the ranking of providers were investigated. Using an observational study design, pre- and posttest self-report assessments of symptoms were obtained for 31,849 adults with common mental health problems, such as mood and anxiety disorders. Regression analyses were performed to predict the posttest symptom level using socio-demographics and clinical characteristics as predictors. Results showed that the posttest level of symptoms was best predicted by the symptom level at baseline, followed by the baseline level of functioning, age, socioeconomic status and some diagnoses. For the majority of the providers, risk adjustment did not markedly change their ranking. The baseline level of symptoms is the best predictor of the posttest level. The other investigated case mix variables only have a modest influence on the performance of providers. Risk adjustment is particularly necessary when consequences are related to the performance of an individual provider. These results contribute to the limited literature on risk adjustment in mental health care by using a large national data set.

The predictive value of personality disorder (PD) on treatment length of offenders detained in high security psychiatric hospitals in the Netherlands was studied on 536 male patients (mean age 34.0 years, SD = 10.5, range: 18.0–68.8) with a 76.5% PD prevalence. Results showed that PD did not independently predict length of enforced treatment. A subgroup of patients with only PD and no comorbid major mental disorder had a shorter treatment length. This study has isolated separate factors that can shorten or prolong treatment and can provide a focus for both policy and (clinical) decision makers in the enforced treatment process.

BackgroundAlthough the importance and advantages of measurement-based care in mental healthcare are well established, implementation in daily practice is complex and far from optimal.AimsTo accelerate the implementation of outcome measurement in routine clinical practice, a government-sponsored National Quality Improvement Collaborative was initiated in Dutch-specialised mental healthcare.MethodTo investigate the effects of this initiative, we combined a matched-pair parallel group design (21 teams) with a cluster randomised controlled trial (RCT) (6 teams). At the beginning and end, the primary outcome ‘actual use and perceived clinical utility of outcome measurement’ was assessed.ResultsIn both designs, intervention teams demonstrated a significant higher level of implementation of outcome measurement than control teams. Overall effects were large (parallel group d=0.99; RCT d=1.25).ConclusionsThe National Collaborative successfully improved the use of outcome measurement in routine clinical practice.

We investigated longitudinal measurement invariance in the Dutch-Flemish PROMIS adult v1.0 item banks for Depression and Anxiety using two clinical samples with mood and anxiety disorders (n = 640 and n = 528, respectively). Factor analysis was used to evaluate whether the item banks were sufficiently unidimensional at two test-occasions and whether the measured constructs remained the same over time. The results indicated that the item banks were sufficiently unidimensional, but the thresholds and residual variances of the constructs changed over time. However, using tentative rules of thumb, these invariance violations did not substantially affect the endorsement of a specific response category of a specific item at a specific test-occasion. Furthermore, the impact on the mean latent change scores of the item banks remained below the proposed cutoff value for substantial bias. These findings suggest that the invariance violations lacked practical significance for test-users, meaning that the item banks provide sufficiently invariant latent factor scores for use in clinical practice.

ObjectivesThe authors of a previous study proposed a statistically based approach to denote treatment outcome, translating pretest and posttest scores into clinically relevant categories, such as recovery and reliable improvement. We assessed the convergent validity of the Jacobson–Truax (JT) approach, using T‐score based cutoff values, with ratings by an independent evaluator.MethodsPretest and retest scores on the Brief Symptom Inventory (BSI) and clinical global impression improvement (CGI‐I) ratings were collected repeatedly through routine outcome monitoring from 5,900 outpatients with common mental disorders. Data were collected in everyday practice in a large mental health care provider.ResultsContinuous pretest‐to‐retest BSI change scores had a stronger association with CGI‐I than the categorical variable based on JT. However, JT categorization and improvement according to CGI converged substantially with association indices (Somers' D) ranging from D = .50 to .56. Discordance was predominantly due to a more positive outcome according to JT than on CGI‐I ratings.ConclusionConverting continuous outcome variables into clinically meaningful categories comes at the price of somewhat diminished concurrent validity with CGI‐I. Nevertheless, support was found for the proposed threshold values for reliable change and recovery, and the outcome denoted in these terms corresponded with CGI improvement for most patients.

Careless responding by mental health patients on self-report assessments is rarely investigated in routine care despite the potential for serious consequences such as faulty clinical decisions. We investigated validity indices most appropriate for detecting careless responding in routine outcome monitoring (ROM) in mental health-care. First, we reviewed indices proposed in previous research for their suitability in ROM. Next, we evaluated six selected indices using data of the Brief Symptom Inventory and the Mood and Anxiety Symptom Questionnaire from 3,483 outpatients. Simulations showed that for typical ROM scales the L max Lmax index, Mahalanobis distance, and inter-item standard deviation may be too strongly confounded with the latent trait value to compare careless responding across patients with different symptom severity. Application of two different classification methods to the validity indices did not converge in similar prevalence estimates of careless responding. Finally, results suggest that careless responding does not have a substantial biasing effect on scale-score statistics. We recommend the l p z lzp person-fit index to screen for random careless responding in large ROM data sets. However, additional research should further investigate methods for detecting repetitive responding in typical ROM data and assess whether there are specific circumstances in which simpler validity statistics or direct screening methods perform similarly as the l p z lzp index.

BackgroundRoutine outcome monitoring (ROM) may enhance individual treatment and is also advocated as a means to compare the outcome of different treatment programs or providers. There is debate on the optimal instruments to be used for these separate tasks.MethodsThree sets with longitudinal data from ROM were analyzed with correlational analysis and repeated measures ANOVAs, allowing for a head-to-head comparison of measures regarding their sensitivity to detect change. The responsiveness of three disorder-specific instruments, the Beck Depression Inventory, the Inventory of Depressive Symptoms, and the Mood and Anxiety Symptoms Questionnaire, was compared to three generic instruments, the Symptom Checklist (SCL-90), the Outcome Questionnaire (OQ-45), and the Brief Symptom Inventory, respectively.ResultsIn two of the three datasets, disorder-specific measures were more responsive compared to the total score on generic instruments. Subscale scores for depression embedded within generic instruments are second best and almost match disorder-specific scales in responsiveness. No evidence of a desynchronous response on outcome measures was found.LimitationsThe present study compares measures head-to-had, and responsiveness is not assessed against an external criterion, such as clinical recovery.DiscussionDisorder-specific measures yield the most precise assessment for individual treatment and are recommended for clinical use. Generic measures may allow for comparisons across diagnostic groups and their embedded subscales approach the responsiveness of disorder-specific measures.

De Stichting Benchmark GGZ brengt behandeluitkomsten voor ggz-instellingen in kaart. Casemixcorrectie is nodig als de patientenpopulatie van ggz-instellingen verschilt op patientkenmerken die de behandeluitkomsten beinvloeden. Hiervoor is het belangrijk te onderzoeken welke patientkenmerken de behandeluitkomsten beinvloeden. Bij patienten met een angst- en/of depressieve stoornis van zes ggz-instellingen is via een observationele studie onderzocht welke patientkenmerken de behandeluitkomst beinvloeden.

PurposeTo investigate the effects of Shared Decision-Making (SDM) using Routine Outcome Monitoring (ROM) primary on patients’ perception of Decisional Conflict (DC), which measures patients’ engagement in and satisfaction with clinical decisions, and secondary on working alliance and treatment outcomes.MethodMulti-centre two-arm matched-paired cluster randomised-controlled trial in Dutch specialist mental health care. SDM using ROM (SDMR) was compared with Decision-Making As Usual (DMAU). Outcomes were measured at baseline (T0) and 6 months (T1). Multilevel regression and intention-to-treat analyses were used. Post hoc analyses were performed on influence of subgroups and application of SDMR on DC.ResultsSeven teams were randomised to each arm. T0 was completed by 186 patients (51% intervention; 49% control) and T1 by 158 patients (51% intervention, 49% control). DC, working alliance, and treatment outcomes reported by patients did not differ significantly between two arms. Post hoc analyses revealed that SDMR led to less DC among depressed patients (p = 0.047, d =− 0.69). If SDMR was applied well, patients reported less DC (SDM: p = 0.000, d = − 0.45; ROM: p = 0.021, d = − 0.32), which was associated with better treatment outcomes.ConclusionExcept for patients with mood disorders, we found no difference between the arms for patient-reported DC. This might be explained by the less than optimal uptake of this generic intervention, which did not support patients directly. Regarding the positive influence of a higher level of applying SDM and ROM on less DC and better treatment outcomes, the results are encouraging for further investments in patient-oriented development and implementation of SDMR.

Contains fulltext : 194109.pdf (Publisher’s version ) (Open Access) Background: The present study investigates the suitability of various treatment outcome indicators to evaluate performance of mental health institutions that provide care to patients with severe mental illness. Several categorical approaches are compared to a reference indicator (continuous outcome) using pretest-posttest data of the Health of Nation Outcome Scales (HoNOS). Methods: Data from 10 institutions and 3189 patients were used, comprising outcomes of the first year of treatment by teams providing long-term care. Results: Findings revealed differences between continuous indicators (standardized pre-post difference score ES and delta T) and categorical indicators (SEM, JTRCI, JTCS, JTRCI&CS, JTrevised) on their ranking of institutions, as well as substantial differences among categorical indicators; the outcome according to the traditional JT approach was most concordant with the continuous outcome indicators. Conclusions: For research comparing group averages, a continuous outcome indicator such as ES or delta T is preferred, as this best preserves information from the original variable. Categorical outcomes can be used to illustrate what is accomplished in clinical terms. For categorical outcome, the classical Jacobson-Truax approach is preferred over the more complex method of Parabiaghi et al. with eight outcome categories. The latter may be valuable in clinical practice as it allows for a more detailed characterization of individual patients. 10 p.

The hazard ratio (HR) is a measure of instantaneous relative risk of an increase in one unit of the covariate of interest, which is widely reported in clinical researches involving time-to-event data. However, the measure fails to capture absolute risk reduction. Other measures such as number needed to treat (NNT) and risk difference (RD) provide another perspective on the effectiveness of an intervention, and can facilitate clinical decision making. The article aims to provide a step-by-step tutorial on how to compute RD and NNT in survival analysis with R. For simplicity, only one measure (RD or NNT) needs to be illustrated, because the other measure is a reverse of the illustrated one (NNT=1/RD). An artificial dataset is composed by using the survsim package. RD and NNT are estimated with Austin method after fitting a Coxproportional hazard regression model. The confidence intervals can be estimated using bootstrap method. Alternatively, if the standard errors (SEs) of the survival probabilities of the treated and control group are given, confidence intervals can be estimated using algebraic calculations. The pseudo-value model provides another method to estimate RD and NNT. Details of R code and its output are shown and explained in the main text.

Approaches based on continuous indicators (the size of the pre-to-post-test change; effect size or ΔT) and on categorical indicators (Percentage Improvement and the Jacobson–Truax approach to Clinical Significance) are evaluated to determine which has the best methodological and statistical characteristics, and optimal performance, in comparing outcomes of treatment providers. Performance is compared in two datasets from providers using the Brief Symptom Inventory or the Outcome Questionnaire. Concordance of methods and their suitability to rank providers is assessed. Outcome indicators tend to converge and lead to a similar ranking of institutes within each dataset. Statistically and conceptually, continuous outcome indicators are superior to categorical outcomes as change scores have more statistical power and allow for a ranking of providers at first glance. However, the Jacobson–Truax approach can complement the change score approach as it presents outcome information in a clinically meaningful manner. Copyright © 2015 John Wiley & Sons, Ltd. Key Practitioners Messages When comparing various indicators or treatment outcome, statistical considerations designate continuous outcomes, such as the effect size of the pre–post change (effect size or ΔT) as the optimal choice. Expressing outcome in proportions of recovered, changed, unchanged or deteriorated patients has supplementary value, as it is more easily interpreted and appreciated by clinicians, managerial staff and, last but not the least, by patients. If categorical outcomes are used with small datasets, true differences in institutional performance may get obscured due to diminished power to detect differences. With sufficient data, outcome according to continuous and categorical indicators converge and lead to similar rankings of institutes' performance.

Purpose National initiatives, such as the UK Improving Access to Psychological Therapies program (IAPT), demonstrate the feasibility of conducting empirical mental health assessments on a large scale, and similar initiatives exist in other countries. However, there is a lack of international consensus on which outcome domains are most salient to monitor treatment progress and how they should be measured. The aim of this project was to propose (1) an essential set of outcome domains relevant across countries and cultures, (2) a set of easily accessible patient-reported instruments, and (3) a psychometric approach to make scores from different instruments comparable. Methods Twenty-four experts, including ten health outcomes researchers, ten clinical experts from all continents, two patient advocates, and two ICHOM coordinators worked for seven months in a consensus building exercise to develop recommendations based on existing evidence using a structured consensus-driven modified Delphi technique. Results The group proposes to combine an assessment of potential outcome predictors at baseline (47 items: demographics, functional, clinical status, etc.), with repeated assessments of disease-specific symptoms during the treatment process (19 items: symptoms, side effects, etc.), and a comprehensive annual assessment of broader treatment outcomes (45 items: remission, absenteeism, etc.). Further, it is suggested reporting disease-specific symptoms for depression and anxiety on a standardized metric to increase comparability with other legacy instruments. All recommended instruments are provided online (www.ichom.org). Conclusion An international standard of health outcomes assessment has the potential to improve clinical decision making, enhance health care for the benefit of patients, and facilitate scientific knowledge. Electronic supplementary material The online version of this article (doi:10.1007/s11136-017-1659-5) contains supplementary material, which is available to authorized users.

Background: Enhancing patient participation is becoming increasingly important in mental health care as patients use to have a dependent, inactive role and nonadherence to treatment is a regular problem. Research shows promising results of initiatives stimulating patient participation in partnership with their clinicians. However, few initiatives targeting both patients' and clinicians' behaviour have been evaluated in randomised trials (RCT). Therefore, in GGz Breburg, a specialized mental health institution, a digital intake approach was developed aimed at exploring treatment needs, expectations and preferences of patients intended to prepare patients for the intake consultations. Subsequently, patients and clinicians discuss this information during intake consultations and make shared decisions about options in treatment. The aim of this trial is to test the efficacy of this new digital intake approach facilitated by Routine Outcome Monitoring (ROM), peer support and training of clinicians as compared to the intake as usual. The primary outcome is decisional conflict about choices in treatment. Secondary outcomes focus on patient participation, shared decision making, working alliance, adherence to treatment and clinical outcomes. Methods: This article presents the study protocol of a cluster-randomised controlled trial in four outpatient departments for adults with depression, anxiety and personality disorders, working in two different regions. Randomisation is done between two similar intake-teams within each department. In the four intervention teams the new intake approach is implemented. The four control teams apply the intake as usual and will implement the new approach after the completion of the study. In total 176 patients are projected to participate in the study. Data collection will be at baseline, and at two weeks and two months after the intake. Discussion: This study will potentially demonstrate the efficacy of the new digital intake approach in mental health care in terms of the primary outcome the degree of decisional conflict about choices in treatment. The findings of this study may contribute to the roll out of such eHealth initiatives fostering patient involvement in decision making about their treatment. Trial registration: Trial registration: Dutch Trial Register NTR5677. Registered 17th January 2016.