Estimating a Preference-Based Value Set for the Mental Health Quality of Life Questionnaire (MHQoL).

BACKGROUND: Health economic evaluations using common health-related quality of life measures may fall short in adequately measuring and valuing the benefits of mental health care interventions. The Mental Health Quality of Life questionnaire (MHQoL) is a standardized, self-administered mental health-related quality of life instrument covering 7 dimensions known to be relevant across and valued highly by people with mental health problems. The aim of this study was to derive a Dutch value set for the MHQoL to facilitate its use in cost-utility analyses. METHODS: The value set was estimated using a discrete choice experiment (DCE) with duration that accommodated nonlinear time preferences. The DCE was embedded in a web-based self-complete survey and administered to a representative sample (N = 1,308) of the Dutch adult population. The matched pairwise choice tasks were created using a Bayesian heterogeneous D-efficient design. The overall DCE design comprised 10 different subdesigns, with each subdesign containing 15 matched pairwise choice tasks. Each participant was asked to complete 1 of the subdesigns to which they were randomly assigned. RESULTS: The obtained coefficients indicated that "physical health,""mood," and "relationships" were the most important dimensions. All coefficients were in the expected direction and reflected the monotonic structure of the MHQoL, except for level 2 of the dimension "future." The predicted values for the MHQoL ranged from -0.741 for the worst state to 1 for the best state. CONCLUSIONS: This study derived a Dutch value set for the recently introduced MHQoL. This value set allows for the generation of an index value for all MHQoL states on a QALY scale and may hence be used in Dutch cost-utility analyses of mental healthcare interventions. HIGHLIGHTS: A discrete choice experiment was used to derive a Dutch value set for the MHQoL.This allows the use of the MHQoL in Dutch cost-utility analyses.The dimensions physical health, mood, and relationships were the most important.The utility values range from -0.741 for the worst state to 1 for the best state.

Design and development of a digital intervention for workplace stress and mental health (EMPOWER).

Purpose: We describe the design and development of the European Platform to Promote health and wellbeing in the workplace (EMPOWER) digital intervention that provides an integrative user programme meeting the needs of employees and employers in addressing work stress. Results: A user-centred design process was followed from January 2020 until November 2021. A tailored algorithm was developed to provide support at the individual employee level and the company level. Each element of the digital intervention was developed in English and then translated in Spanish, English, Polish and Finnish. The digital intervention consists of a website and a mobile application (app) that provides algorithm-based personalised content after assessing a user's somatic and psychological symptoms, work functioning, and psychosocial risk factors for work stress. It has a public section and an employer portal that provides recommendations to reduce psychosocial risks in their company based upon clustered input from employees. Usability testing was conducted and showed high ease of use and completion of tasks by participants. Conclusion: The EMPOWER digital intervention is a tailored multimodal intervention addressing wellbeing, work stress, mental and physical health problems, and work productivity. This will be used in a planned RCT in four countries to evaluate its effectiveness.

Study protocol of EMPOWER: A cluster randomized trial of a multimodal eHealth intervention for promoting mental health in the workplace following a stepped wedge trial design.

Objective: This article describes the EMPOWER study, a controlled trial aiming to determine the effectiveness and cost-effectiveness of an eHealth intervention to prevent common health problems and reduce presenteeism and absenteeism in the workplace. Intervention: The EMPOWER intervention spans universal, secondary and tertiary prevention and consists of an eHealth platform delivered via a website and a smartphone app designed to guide employees throughout different modules according to their specific profiles. Design: A stepped-wedge cluster randomized trial will be implemented in four countries (Finland, Poland, Spain and UK) with employees from small and medium enterprises (SMEs) and public agencies. Companies will be randomly allocated in one of three groups with different times at which the intervention is implemented. The intervention will last 7 weeks. Employees will answer several questionnaires at baseline, pre- and post-intervention and follow-up. Outcome measures: The main outcome is presenteeism. Secondary outcomes include depression, anxiety, insomnia, stress levels, wellbeing and absenteeism. Analyses will be conducted at the individual level using the intention-to-treat approach and mixed models. Additional analyses will evaluate the intervention effects according to gender, country or type of company. Cost-effectiveness and cost-utility analyses [based on the use of quality-adjusted life-years (QALYS)] will consider a societal, employers' and employees' perspective.

Psychometric evaluation of the Mental Health Quality of Life (MHQoL) instrument in seven European countries.

INTRODUCTION: To make efficient use of available resources, decision-makers in healthcare may assess the costs and (health) benefits of health interventions. For interventions aimed at improving mental health capturing the full health benefits is an important challenge. The Mental Health Quality of Life (MHQoL) instrument was recently developed to meet this challenge. Evaluating the pyschometric properties of this instrument in different contexts remains important. METHODS: A psychometric evaluation of the MHQoL was performed using existing international, cross-sectional data with 7155 respondents from seven European countries (Denmark, France, Germany, Italy, Portugal, The Netherlands, Portugal and the United Kingdom). Reliability was examined by calculating Cronbach's alpha, a measure of internal consistency of the seven MHQoL dimensions, and by examining the association of the MHQoL sum scores with the MHQoL-VAS scores. Construct validity was examined by calculating Spearman's rank correlation coefficients between the MHQoL sum scores and EQ-5D index scores, EQ-VAS scores, EQ-5D anxiety/depression dimension scores, ICECAP-A index scores and PHQ-4 sum scores. RESULTS: The MHQoL was found to have good internal consistency for all seven countries. The MHQoL sum score and the MHQoL-VAS had a high correlation. Spearman's rank correlation coefficients were moderate to very high for all outcomes. CONCLUSION: Our results, based on data gathered in seven European countries, suggest that the MHQoL shows favourable psychometrical characteristics. While further validation remains important, the MHQoL may be a useful instrument in measuring mental health-related quality of life in the Western European context.

Estimating an anchored utility tariff for the well-being of older people measure (WOOP) for the Netherlands.

OBJECTIVE: Health economic evaluations using common health-related quality of life measures may fall short in adequately incorporating all relevant benefits of health and social care interventions targeted at older people. The Well-being of Older People measure (WOOP) is a broader well-being measure that comprises nine well-being domains. The objective of this study was to estimate a utility tariff for the WOOP, to facilitate its application in cost-utility analyses. METHODS: A discrete choice experiment (DCE) with duration approach was set up and fielded among 2,012 individuals from the Netherlands aged 65 years and above. Matched pairwise choice tasks, colour-coding and level overlap were used to reduce the cognitive burden of the DCE. The choice tasks were created using a Bayesian heterogeneous D-efficient design. The estimation procedure accommodated for nonlinear time preferences via an exponential discounting function. RESULTS: The estimation results showed that 'physical health', 'mental health', and 'making ends meet' were the most important well-being domains for older people, followed by 'independence' and 'living situation'. Of somewhat lesser importance were domains like 'social life', 'receiving support' and 'feeling useful'. The generated utility tariffs can be used to translate well-being states described with the WOOP to a utility score between -0.616 and 1. CONCLUSIONS: This study established a tariff for the WOOP, which will facilitate its use in economic evaluations of health and social care interventions targeted at older people, first of all in the Netherlands.

Development and psychometric evaluation of the Decision Tool Anxiety Disorders, OCD and PTSD (DTAOP): Facilitating the early detection of patients in need of highly specialized care.

BACKGROUND: Early identification of patients with an anxiety disorder, obsessive-compulsive disorder (OCD), or post-traumatic stress disorder (PTSD) in need of highly specialized care could facilitate the selection of the optimal initial treatment in these patients. This paper describes the development and psychometric evaluation of the Decision Tool Anxiety Disorders, OCD and PTSD (DTAOP), which aims to aid clinicians in the early identification of patients with an anxiety disorder, OCD, or PTSD in need of highly specialized mental healthcare. METHODS: A systematic literature review and a concept mapping procedure were carried out to inform the development of the DTAOP. To evaluate the psychometric properties of the DTAOP, a cross-sectional study in 454 patients with a DSM-IV-TR anxiety disorder was carried out. Feasibility was evaluated by the completion time and the content clarity of the DTAOP. Inter-rater reliability was assessed in a subsample of 87 patients. Spearman's rank correlation coefficients between the DTAOP and EuroQol five-dimensional questionnaire (EQ-5D-5L) scores were computed to examine the convergent validity. Criterion validity was assessed against independent clinical judgments made by clinicians. RESULTS: The average time required to complete the eight-item DTAOP was 4.6 min and the total DTAOP was evaluated as clear in the majority (93%) of the evaluations. Krippendorff's alpha estimates ranged from 0.427 to 0.839. Based on the qualitative feedback, item wording and instructions were improved. As hypothesized, the DTAOP correlated negatively with EQ-5D-5L scores. The area under the curve was 0.826 and the cut-off score of ≥4 optimized sensitivity (70%) and specificity (71%). CONCLUSIONS: The DTAOP demonstrated excellent feasibility and good validity, but weak inter-rater reliability. Based on the qualitative feedback and reliability estimates, revisions and refinements of the wording and instructions were made, resulting in the final version of the DTAOP.

Development and psychometric evaluation of the Transdiagnostic Decision Tool: matched care for patients with a mental disorder in need of highly specialised care.

BACKGROUND: Early identification of patients with mental health problems in need of highly specialised care could enhance the timely provision of appropriate care and improve the clinical and cost-effectiveness of treatment strategies. Recent research on the development and psychometric evaluation of diagnosis-specific decision-support algorithms suggested that the treatment allocation of patients to highly specialised mental healthcare settings may be guided by a core set of transdiagnostic patient factors. AIMS: To develop and psychometrically evaluate a transdiagnostic decision tool to facilitate the uniform assessment of highly specialised mental healthcare need in heterogeneous patient groups. METHOD: The Transdiagnostic Decision Tool was developed based on an analysis of transdiagnostic items of earlier developed diagnosis-specific decision tools. The Transdiagnostic Decision Tool was psychometrically evaluated in 505 patients with a somatic symptom disorder or post-traumatic stress disorder. Feasibility, interrater reliability, convergent validity and criterion validity were assessed. In order to evaluate convergent validity, the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) and the ICEpop CAPability measure for Adults (ICECAP-A) were administered. RESULTS: The six-item clinician-administered Transdiagnostic Decision Tool demonstrated excellent feasibility and acceptable interrater reliability. Spearman's rank correlations between the Transdiagnostic Decision Tool and ICECAP-A (-0.335), EQ-5D-5L index (-0.386) and EQ-5D-visual analogue scale (-0.348) supported convergent validity. The area under the curve was 0.81 and a cut-off value of ≥3 was found to represent the optimal cut-off value. CONCLUSIONS: The Transdiagnostic Decision Tool demonstrated solid psychometric properties and showed promise as a measure for the early detection of patients in need of highly specialised mental healthcare.

The decision tool unipolar depression (DTUD): a new measure to facilitate the early identification of patients with major depressive disorder in need of highly specialized care.

BACKGROUND: Selection of the optimal initial treatment in patients with major depressive disorder (MDD) in need of highly specialized care has the potential to benefit treatment outcomes and cost-effectiveness of treatment strategies. However, to date, there is a paucity of measures that could guide the selection of the initial treatment, in particular to indicate which patients with MDD are in need of highly specialized care. Recognizing this gap, this paper reports on the development and psychometric evaluation of the Decision Tool Unipolar Depression (DTUD), aimed to facilitate the early identification of patients with MDD in need of highly specialized care. METHODS: The DTUD was developed using a mixed-methods approach, consisting of a systematic review and a concept mapping study. To evaluate the psychometric features of the DTUD, a cross-sectional multicenter study was conducted. A total of 243 patients with MDD were evaluated with the DTUD. Feasibility was operationalized as the time required to complete the DTUD and the content clarity of the DTUD. Inter-rater reliability was evaluated using Krippendorf's alpha. The Maudsley Staging Method (MSM) and the Dutch Measure for quantification of Treatment Resistance in Depression (DM-TRD) were administered to assess the convergent validity. A receiver operator characteristic curve was generated to evaluate the criterion validity and establish the optimal cut-off value. RESULTS: The mean administration time was 4.49 min (SD = 2.71), and the content of the total DTUD was judged as clear in 94.7% of the evaluations. Inter-rater reliability values ranged from 0.69 to 0.91. Higher scores on the DTUD were associated with higher scores on the MSM (rs = 0.47) and DM-TRD (rs = 0.53). Based on the maximum Youden index (0.494), maximum discrimination was reached at a cut-off score of ≥5 (sensitivity 67%, specificity 83%). CONCLUSION: The DTUD demonstrated to be a tool with solid psychometric properties and, therefore, is a promising measure for the early identification of patients with MDD in need of highly specialized care. Use of the DTUD has the potential to facilitate the selection and initiation of the optimal initial treatment in patients with MDD, which in turn may improve the clinical effectiveness and cost-effectiveness of treatment strategies.

Indicators of patients with major depressive disorder in need of highly specialized care: A systematic review.

OBJECTIVES: Early identification of patients with major depressive disorder (MDD) that cannot be managed by secondary mental health services and who require highly specialized mental healthcare could enhance need-based patient stratification. This, in turn, may reduce the number of treatment steps needed to achieve and sustain an adequate treatment response. The development of a valid tool to identify patients with MDD in need of highly specialized care is hampered by the lack of a comprehensive understanding of indicators that distinguish patients with and without a need for highly specialized MDD care. The aim of this study, therefore, was to systematically review studies on indicators of patients with MDD likely in need of highly specialized care. METHODS: A structured literature search was performed on the PubMed and PsycINFO databases following PRISMA guidelines. Two reviewers independently assessed study eligibility and determined the quality of the identified studies. Three reviewers independently executed data extraction by using a pre-piloted, standardized extraction form. The resulting indicators were grouped by topical similarity, creating a concise summary of the findings. RESULTS: The systematic search of all databases yielded a total of 7,360 references, of which sixteen were eligible for inclusion. The sixteen papers yielded a total of 48 unique indicators. Overall, a more pronounced depression severity, a younger age of onset, a history of prior poor treatment response, psychiatric comorbidity, somatic comorbidity, childhood trauma, psychosocial impairment, older age, and a socioeconomically disadvantaged status were found to be associated with proxies of need for highly specialized MDD care. CONCLUSIONS: Several indicators are associated with the need for highly specialized MDD care. These indicators provide easily measurable factors that may serve as a starting point for the development of a valid tool to identify patients with MDD in need of highly specialized care.