Editorial Perspective: Prescribing measures: unintended negative consequences of mandating standardized mental health measurement

Polygenic Analyses Show Important Differences Between Major Depressive Disorder Symptoms Measured Using Various Instruments

BACKGROUND

Symptoms of major depressive disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire-9 (PHQ-9) (current symptoms) and the Composite International Diagnostic Interview Short-Form (CIDI-SF) (worst-episode symptoms). We performed a systematic comparison between them for their genetic architecture and utility in investigating MDD heterogeneity.

METHODS

Using data from the UK Biobank (n = 41,948-109,417), we assessed the single nucleotide polymorphism heritability and genetic correlation (rg) of both sets of MDD symptoms. We further compared their rg with non-MDD traits and used Mendelian randomization to assess whether either set of symptoms has more genetic sharing with non-MDD traits. We also assessed how specific each set of symptoms is to MDD using the metric polygenic risk score pleiotropy. Finally, we used genomic structural equation modeling to identify factors that explain the genetic covariance between each set of symptoms.

RESULTS

Corresponding symptoms reported through the PHQ-9 and CIDI-SF have low to moderate genetic correlations (rg = 0.43-0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip structure in the CIDI-SF. Both Mendelian randomization and polygenic risk score pleiotropy analyses showed that PHQ-9 symptoms are more associated with traits that reflect general dysphoria, whereas the skip structure in the CIDI-SF allows for the identification of heterogeneity among likely MDD cases. Finally, the 2 sets of symptoms showed different factor structures in genomic structural equation modeling, reflective of their genetic differences.

CONCLUSIONS

MDD symptoms assessed using the PHQ-9 and CIDI-SF are not interchangeable; the former better indexes general dysphoria, while the latter is more informative about within-MDD heterogeneity.

Heterogeneity of outcome measures in depression trials and the relevance of the content of outcome measures to patients: a systematic review

Research waste occurs when randomised controlled trial (RCT) outcomes are heterogeneous or overlook domains that matter to patients (eg, relating to symptoms or functions). In this systematic review, we reviewed the outcome measures used in 450 RCTs of adult unipolar and bipolar depression registered between 2018 and 2022 and identified 388 different measures. 40% of the RCTs used the same measure (Hamilton Depression Rating Scale [HAMD]). Patients and clinicians matched each item within the 25 most frequently used measures with 80 previously identified domains of depression that matter to patients. Seven (9%) domains were not covered by the 25 most frequently used outcome measures (eg, mental pain and irritability). The HAMD covered a maximum of 47 (59%) of the 80 domains that matter to patients. An interim solution to facilitate evidence synthesis before a core outcome set is developed would be to use the most common measures and choose complementary scales to optimise domain coverage. TRANSLATIONS: For the French and Dutch translations of the abstract see Supplementary Materials section.

Mental Health and Well-being Measures for Mean Comparison and Screening in Adolescents: An Assessment of Unidimensionality and Sex and Age Measurement Invariance

Adolescence is a period of increased vulnerability for low well-being and mental health problems, particularly for girls and older adolescents. Accurate measurement via brief self-report is therefore vital to understanding prevalence, group trends, screening efforts, and response to intervention. We drew on data from the #BeeWell study (N = 37,149, aged 12-15) to consider whether sum-scoring, mean comparisons, and deployment for screening were likely to show bias for eight such measures. Evidence for unidimensionality, considering dynamic fit confirmatory factor models, exploratory graph analysis, and bifactor modeling, was found for five measures. Of these five, most showed a degree of non-invariance across sex and age likely incompatible with mean comparison. Effects on selection were minimal, except sensitivity was substantially lower in boys for the internalizing symptoms measure. Measure-specific insights are discussed, as are general issues highlighted by our analysis, such as item reversals and measurement invariance.

Measuring the active elements of cognitive-behavioral therapies

Understanding how and for whom cognitive-behavioral therapies work is central to the development and improvement of mental health interventions. Suboptimal quantification of the active elements of cognitive-behavioral therapies has hampered progress in elucidating mechanisms of change. To advance process research on cognitive-behavioral therapies, we describe a theoretical measurement framework that focuses on the delivery, receipt, and application of the active elements of these interventions. We then provide recommendations for measuring the active elements of cognitive-behavioral therapies aligned with this framework. Finally, to support measurement harmonization and improve study comparability, we propose the development of a publicly available repository of assessment tools: the Active Elements of Cognitive-Behavioral Therapies Measurement Kit.

Common measures in mental health: a joint initiative by funders and journals

There is notable heterogeneity in how clinical and phenotypic data are measured by mental health researchers. There is a proliferation of self-report measures (eg, over 280 for depression alone), meaning it is challenging for researchers to compare findings across different studies from different laboratories. To begin to address this issue, a consortium of mental health research funders and journals has launched the Common Measures in Mental Health Science Initiative. The purpose of this endeavour is to identify common measures for mental health conditions that funders and journals can require all researchers to collect, in addition to any other measures they require for their specific study. These measures would not necessarily capture the full range of experiences of a given condition but could be used to link and compare across studies with different designs in different contexts. This Health Policy outlines the rationale, objectives, and potential challenges of this initiative, which aims to enhance the rigour and comparability of mental health research by promoting the adoption of standardised measures.

Gaining consensus on clinical quality outcomes for eating disorders: Framework for the development of an Australian national minimum dataset

OBJECTIVES

Eating disorders (EDs) are complex psychiatric illnesses requiring multidisciplinary care across both mental and medical healthcare settings. Currently, no nationally comprehensive, consistent, agreed on or mandated data set or data collection strategy exists for EDs in Australia: thus, little is known about the outcomes of care nor treatment pathways taken by individuals with EDs. InsideOut Institute was contracted by the Australian Government Department of Health to develop a minimum dataset (MDS) for the illness group with consideration given to data capture mechanisms and the scoping of a national registry.

DESIGN

A four-step modified Delphi methodology was used, including national consultations followed by three rounds of quantitative feedback by an expert panel.

SETTING

Due to social distancing protocols throughout the global SARS-CoV-2 pandemic, the study was conducted online using video conferencing (Zoom and Microsoft Teams) (Step 1), email communication and the REDCap secure web-based survey platform (Steps 2-4).

PARTICIPANTS

14 data management organisations, 5 state and territory government departments of health, 2 Aboriginal and Torres Strait Islander advising organisations and 28 stakeholders representing public and private health sectors across Australia participated in consultations. 123 ED experts (including lived experience) participated in the first quantitative round of the Delphi survey. Retention was high, with 80% of experts continuing to the second round and 73% to the third.

MAIN OUTCOME MEASURES

Items and categories endorsed by the expert panel (defined a priori as >85% rating an item or category 'very important' or 'imperative').

RESULTS

High consensus across dataset items and categories led to the stratification of an identified MDS. Medical status and quality of life were rated the most important outcomes to collect in an MDS. Other items meeting high levels of consensus included anxiety disorders, depression and suicidality; type of treatment being received; body mass index and recent weight change.

CONCLUSIONS

Understanding presentation to and outcomes from ED treatment is vital to drive improvements in healthcare delivery. A nationally agreed MDS has been defined to facilitate this understanding and support improvements.

Polygenic analyses show important differences between MDD symptoms collected using PHQ9 and CIDI-SF

Symptoms of Major Depressive Disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire 9 (PHQ9, for current symptoms), and the Composite International Diagnostic Interview Short-Form (CIDI-SF, for lifetime worst-episode symptoms). Using data from the UKBiobank, we show that corresponding symptoms endorsed through PHQ9 and CIDI-SF have low to moderate genetic correlations (rG=0.43-0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip-structure in CIDI-SF. Through a combination of Mendelian Randomization (MR) and polygenic prediction analyses, we find that PHQ9 symptoms are more associated with traits which reflect general dysphoria, while the skip-structure in CIDI-SF allows for the identification of heterogeneity among likely MDD cases. This has important implications on factor analyses performed on their respective genetic covariance matrices for the purpose of identification of genetic factors behind MDD symptom dimensions and heterogeneity.

Choice and Partnership Approach to community mental health and addiction services: a realist-informed scoping review

OBJECTIVES

The Choice and Partnership Approach (CAPA) was developed to create an accessible, child-centred and family-centred model of child and adolescent mental health service delivery that is adaptable to different settings. We sought to describe the state of evidence regarding the extent, outcomes and contextual considerations of CAPA implementation in community mental health services.

DESIGN

Scoping review.

DATA SOURCES

Published and grey literature were searched using MEDLINE, Embase, CINAHL, PsycINFO, Scopus and Google to 13 and 20 July 2022, respectively.

ELIGIBILITY CRITERIA

We included reports focused on the implementation, outcomes (clinical, programme or system) or a discussion of contextual factors that may impact CAPA implementation in either child and adolescent or adult mental health services.

DATA EXTRACTION AND SYNTHESIS

Data were extracted using a codebook that reflected the five domains of the Consolidated Framework for Implementation Research (CFIR) and reviewed for agreement and accuracy. Data were synthesised according to the five CFIR domains.

RESULTS

Forty-eight reports describing 36 unique evaluations were included. Evaluations were observational in nature; 10 employed pre-post designs. CAPA implementation, regardless of setting, was largely motivated by long wait times. Characteristics of individuals (eg, staff buy-in or skills) were not reported. Processes of implementation included facilitative leadership, data-informed planning and monitoring and CAPA training. Fidelity to CAPA was infrequently measured (n=9/36) despite available tools. Health system outcomes were most frequently reported (n=28/36); few evaluations (n=7/36) reported clinical outcomes, with only three reporting pre/post CAPA changes.

CONCLUSIONS

Gaps in evidence preclude a systematic review and meta-analysis of CAPA implementation. Measurement of clinical outcomes represents an area for significant improvement in evaluation. Consistent measurement of model fidelity is essential for ensuring the accuracy of outcomes attributed to its implementation. An understanding of the change processes necessary to support implementation would be strengthened by more comprehensive consideration of contextual factors.

Better together: Advancing life course research through multi-cohort analytic approaches

Longitudinal cohorts can provide timely and cost-efficient evidence about the best points of health service and preventive interventions over the life course. Working systematically across cohorts has the potential to further exploit these valuable data assets, such as by improving the precision of estimates, enhancing (or appropriately reducing) confidence in the replicability of findings, and investigating interrelated questions within a broader theoretical model. In this conceptual review, we explore the opportunities and challenges presented by multi-cohort approaches in life course research. Specifically, we: 1) describe key motivations for multi-cohort work and the analytic approaches that are commonly used in each case; 2) flag some of the scientific and pragmatic challenges that arise when adopting these approaches; and 3) outline emerging directions for multi-cohort work in life course research. Harnessing their potential while thoughtfully considering limitations of multi-cohort approaches can contribute to the robust and granular evidence base needed to promote health and wellbeing over the life span.

Health literacy measurement: embracing diversity in a strengths-based approach to promote health and equity, and avoid epistemic injustice

Definitions of health literacy have evolved from notions of health-related literacy to a multidimensional concept that incorporates the importance of social and cultural knowledge, practices and contexts. This evolution is evident in the development of instruments that seek to measure health literacy in different ways. Health literacy measurement is important for global health because diverse stakeholders, including the WHO, use these data to inform health practice and policy, and to understand sources of inequity. In this Practice paper, we explore the potential for negative consequences, bias and epistemic injustice to occur when health literacy instruments are used across settings without due regard for the lived experiences of people in various contexts from whom data are collected. A health literacy measurement approach that is emic-sensitive, strengths based and solution oriented is needed to minimise biased data interpretation and use and to avoid epistemic injustice.

A multi-group confirmatory factor analysis of the revised children's anxiety and depression scale (RCADS) in Spain, Chile and Sweden

BACKGROUND

There is a need for a measure that can be used across countries and cultures to advance cross-cultural research about internalizing mental health symptoms in children and adolescents. The Revised Children's Anxiety and Depression Scale (RCADS) is a potential candidate, but no study has examined whether its scales are measured similarly in youth populations from different countries.

METHODS

In this study, we use confirmatory factor analysis (CFA) and multi-group CFA to examine the cross-cultural properties of a short and free to use 30-item version of RCADS that assesses social, generalized, panic, and separation anxiety alongside depression and obsessive-compulsive symptoms. We tested the factor structure of RCADS in children and adolescents from Chile, Spain, and Sweden, recruited using different research designs (i.e., school-based studies and an anonymous web survey), and whether the factor structure showed measurement invariance across the three countries.

RESULTS

The proposed factor structure of RCADS showed good model/data fit in all three countries and was superior to a unidimensional model in which correlations among scale items were explained by a single broad internalizing factor. Each RCADS subscale showed adequate to excellent internal consistency in all three countries and multi-group CFA supported scalar invariance across the three countries.

LIMITATIONS

No clinical sample was included.

CONCLUSIONS

This study provides an important first step in supporting the use of RCADS in cross-cultural research on depression, anxiety and obsessive-compulsive symptoms in children and adolescents, but more work on validity aspects of the scale across cultures is needed.

Factor structure, measurement invariance, and concurrent validity of the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder scale-7 in a Norwegian psychiatric outpatient sample

OBJECTIVE

The aim of this study was to test factor structure, measurement invariance, and concurrent validity of the nine item Patient Health Questionnaire-9 (PHQ-9) and the seven item Generalized Anxiety Disorder scale-7 (GAD-7) in a heterogeneous outpatient sample.

METHOD

Outpatients completed the PHQ-9, GAD-7, and the Working Social Adjustment Scale (WSAS) before starting treatment. Study design was cross-sectional, with convenience sampling. The total sample consisted of 831 participants (61% women).

RESULTS

Both PHQ-9 and GAD-7 demonstrated better fit statistics with two-factor and bifactor solutions consisting of a cognitive and somatic factor. Omega hierarchical was .78 for PHQ-9 and .81 for GAD-7. Both instruments achieved scalar invariance across gender, diagnosis, and comorbidity. However, the somatic factors demonstrated poor discriminant validity. These factors are not well separatable and risks being too similar if used together. The general factors of both instruments were most associated with functional impairment, although PHQ-9 demonstrated a stronger association with WSAS (γ = .74, r² = .62) than GAD-7 (γ = .54, r² = .32). Using latent mean difference, women and patients with comorbidity had significantly higher scores of both depression and anxiety.

CONCLUSION

This study shows that the PHQ-9 and GAD-7 may be used as one-dimensional instruments in clinical settings. Tests for measurement invariance supported that both measures are understood and interpreted comparably across gender and diagnostic subgroups.

Revisiting the theoretical and methodological foundations of depression measurement

Depressive disorders are among the leading causes of global disease burden, but there has been limited progress in understanding the causes and treatments for these disorders. In this Perspective, we suggest that such progress crucially depends on our ability to measure depression. We review the many problems with depression measurement, including limited evidence of validity and reliability. These issues raise grave concerns about common uses of depression measures, such as diagnosis or tracking treatment progress. We argue that shortcomings arise because depression measurement rests on shaky methodological and theoretical foundations. Moving forward, we need to break with the field's tradition that has, for decades, divorced theories about depression from how we measure it. Instead, we suggest that epistemic iteration, an iterative exchange between theory and measurement, provides a crucial avenue for depression measurement to progress.

Measurement practices in hallucinations research

Introduction: In several sub-fields of psychology, there has been a renewed focus on measurement practices. As far as we are aware, this has been absent in hallucinations research. Thus, we investigated (a) cross-study variation in how hallucinatory experiences are measured and (b) the reliability of measurements obtained using two tasks that are widely employed in hallucinations research.Method: In Study 1, we investigated to what extent there was variation in how the Launay-Slade Hallucination Scale (LSHS) has been used across 100 studies. In Study 2, we investigated the reliability of the measurements obtained through source monitoring and signal detection tasks, using data from four recent publications. Materials/data are available at doi: 10.17605/osf.io/d3gnk/.Results: In Study 1, we found substantial variation in how hallucinatory experiences were assessed using the LSHS and that descriptions of the LSHS were often incomplete in important ways. In Study 2, we reported a range of reliability estimates for the measurements obtained using source monitoring and signal discrimination tasks. Some measurements obtained using source monitoring tasks had unacceptably low levels of reliability.Conclusions: Our findings suggest that suboptimal measurement practices are common in hallucinations research and we suggest steps researchers could take to improve measurement practices.

A Systematic Review of Psychobiotic Interventions in Children and Adolescents to Enhance Cognitive Functioning and Emotional Behavior

This systematic review brings together human psychobiotic interventions in children and adolescents (aged 6-25 years) to evaluate the efficacy of pre- and probiotic supplements on stress, anxiety, and cognitive outcomes. Psychobiotic interventions in animal studies highlighted sensitivity to effects during development and maturation in multiple domains from emotion to cognitive processing. Several translational psychobiotic interventions in humans have been carried out to assess effects on emotion and cognition during childhood and into adulthood. The findings illustrate that there are limited consistent psychobiotic effects in developing human populations, and this is proposed to be due to heterogeneity in the trials conducted. Consequentially, it is recommended that three specific factors are considered in future psychobiotic trials: (1) Specificity of population studied (e.g., patients, developmental age), (2) specificity of intervention, and (3) homogeneity in outcome measures.

Common measures or common metrics? A plea to harmonize measurement results

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.

The challenge of ensuring affordability, sustainability, consistency, and adaptability in the common metrics agenda

Mental health research grapples with research waste and stunted field progression caused by inconsistent outcome measurement across studies and clinical settings, which means there is no common language for considering findings. Although recognising that no gold standard measures exist and that all existing measures are flawed in one way or another, anxiety and depression research is spearheading a common metrics movement to harmonise measurement, with several initiatives over the past 5 years recommending the consistent use of specific scales to allow read-across of measurements between studies. For this approach to flourish, however, common metrics must be acceptable and adaptable to a range of contexts and populations, and global access should be as easy and affordable as possible, including in low-income countries. Within a measurement landscape dominated by fixed proprietary measures and with competing views of what should be measured, achieving this goal poses a range of challenges. In this Personal View, we consider tensions between affordability, sustainability, consistency, and adaptability that, if not addressed, risk undermining the common metrics agenda. We outline a three-pronged way forward that involves funders taking more direct responsibility for measure development and dissemination; a move towards managing measure dissemination and adaptation via open-access measure hubs; and transitioning from fixed questionnaires to item banks. We argue that now is the time to start thinking of mental health metrics as 21st century tools to be co-owned and co-created by the mental health community, with support from dedicated infrastructure, coordinating bodies, and funders.

Embracing Scientific Humility and Complexity: Learning "What Works for Whom" in Youth Psychotherapy Research

Clinical psychological scientists have spent decades attempting to understand "what works for whom" in the context of youth psychotherapy, toward the longstanding goal of personalizing psychosocial interventions to fit individual needs and characteristics. However, as the articles in this Special Issue jointly underscore, more than 50 years of psychotherapy research has yet to help us realize this goal. In this introduction to the special issue, we outline how and why "aspiration-method mismatches" have hampered progress toward identifying moderators of youth psychotherapy; emphasize the need to embrace etiological complexity and scientific humility in pursuing new methodological solutions and propose individual and structural strategies for better-aligning clinical research methods with the goal of personalizing mental health care for youth with diverse identities and treatment needs.

[Student's mental health: better measurement and considereration of the challenges]

Mental health represents a high cost for society, estimated at 109 billion euros per year in France, 80 % of which are indirect costs. Mental diseases start before the age of 24 for 75 % of patients. Students, whose age is predominantly between 18 and 25, are a particularly high-risk population and for whom mental illness can have very serious consequences. The Observatoire de la vie Etudiante surveys from 2016 found a 12 month prevalence of depression of 15 % with suicidal thoughts in 8 % of the students higher than what is observed in the French general population, respectively 10 % and 5 %. The confinement itself and its consequences both economic (unemployment, difficulty for young people to find a job…) and social (isolation) could have a very bad effect on their mental health. The survey made by a governmental organization (Santé Publique France) revealed a significant increase in the prevalence of anxiety disorders at the start of confinement in the general population. This prevalence decreased during confinement but remained significantly higher than in 2017. Economic simulated data indicate that prevention in mental health could not only be effective but also profitable. In France, reimbursement by national health insurance of 12 sessions of psychologists for young people (between 11 to 21) is being tested in order to further and widely implement psychological prevention strategies rather than relying on already widely reimbursed pharmacological treatments. There are, however, several issues to discuss. First of all, is the need to define what psychopathology is considered to be. Then, it should be understood how measures of these concepts are created, how tools are constructed and how they operate in their environment. For depression, many different scales exist and even if the most used one are taken into account, they have very little content or symptoms in common. In addition, for the same scale, many different cut-offs exist to define whether a case should be considered as pathological or not, and so it is with the period of time studied being considered that may vary, both leading to consequences such as the differences observed in prevalence. Other biases should also be considered such as the age of the participants, the gender, the size of the sample, the response rate, the method of assessment and recruitment. Finally, it is necessary to question the assumptions and models used concerning the causes of psychic pathologies. Biological hypotheses on the origin of depression involve genetics and inflammation, but sociological and psychological factors must also be considered as well as the underlying complexity both in their nature and interactions at different structural levels of space and time. We should avoid drifting towards a biological or a sociological reductionism and move forward through complex systems approaches and models. With regard to student mental health in France, unfortunately, quality data are still lacking, and existing studies are difficult to compare as some may also have methodological issues. This article leads to the conclusion that there is a need for policies to assess student mental health at both local and national levels with a reflexional thinking on the tools and scales to use as measurements of these phenomena. This approach does not require being too assertive, but should have full transparency on the way the measures were designed and obtained. Measures are as much needed as are the needs for coordinated prevention and care in mental health.