Administering selected subscales of patient-reported outcome questionnaires to reduce patient burden and increase relevance: a position statement on a modular approach

Patient-reported outcome (PRO) questionnaires considered in this paper contain multiple subscales, although not all subscales are equally relevant for administration in all target patient populations. A group of measurement experts, developers, license holders, and other scientific-, regulatory-, payer-, and patient-focused stakeholders participated in a panel to discuss the benefits and challenges of a modular approach, defined here as administering a subset of subscales out of a multi-scaled PRO measure. This paper supports the position that it is acceptable, and sometimes preferable, to take a modular approach when administering PRO questionnaires, provided that certain conditions have been met and a rigorous selection process performed. Based on the experiences and perspectives of all stakeholders, using a modular approach can reduce patient burden and increase the relevancy of the items administered, and thereby improve measurement precision and eliminate wasted data without sacrificing the scientific validity and utility of the instrument. The panelists agreed that implementing a modular approach is not expected to have a meaningful impact on item responses, subscale scores, variability, reliability, validity, and effect size estimates; however, collecting additional evidence for the impact of context may be desirable. It is also important to recognize that adequate rationale and evidence (e.g., of fit-for-purpose status and relevance to patients) and a robust consensus process that includes patient perspectives are required to inform selection of subscales, as in any other measurement circumstance, is expected. We believe that the considerations discussed within (content validity, administration context, and psychometric factors) are relevant across multiple therapeutic areas.

Effectiveness of modular approach in ensuring data quality in large-scale surveys: Evidence from National Family Health Survey - 4 (2015-2016)

This study aims to examine the effect of administration of shorter and longer versions of questionnaires on key indicators such as age displacement, birth displacement, age heaping, and skipping questions on antenatal care (ANC) visits and use of contraceptive methods in India using National Family Health Survey (NFHS)-4 data. At the individual level, the effect of the adoption of the shorter and longer versions of the questionnaires on the age displacement of women and children and skipping of the key questions is insignificant. However, the results from the two-level logistic regression model reveal that at the primary sampling unit (PSU) level, work pressure, depending on the number of eligible women in a household, emerges as a confounder in skipping certain questions, namely ANC [1.18 (p < 0.09)] and contraceptive use [AOR = 1.17 (p < 0.05)]. To expand the coverage of NFHS in providing state- and district-level estimates since 2015, the overall sample size was increased from 88,562 households and 89,777 eligible women in 1992-93 to 6,01,509 households and 6,99,686 eligible women in 2015-16. As a strategy to reduce workload and non-sampling errors during the survey, a nested design and modular approach were adopted to provide estimates of maternal and child health indicators at the district/state level and sexual behaviour, HIV/AIDS, and women's empowerment at the state level. It was hypothesised that a longer version of the questionnaire canvassed in the state module may be detrimental to data quality issues. The findings of this study establish the effectiveness of adopting a modular approach in large-scale surveys, depending on the scale of investigation. However, the differential workload calls for expanding the duration of surveys in PSUs, where the number of eligible women is higher. State level variation in the key data quality indicators may be partially explained by differentials in the training of investigators by the agency and use of translators.

Design and synthesis of analogues of the sphingosine-1-phosphate receptor 1 agonist IMMH001 with improved phosphorylation rate in human blood

IMMH001, which is a prodrug for sphingosine-1-phosphate receptor 1 (S1P₁) agonist, is converted to the active form, its monophosphate ester (S)-IMMH001-P, by sphingosine kinase 1 (SphK1) and sphingosine kinase 2 (SphK2) in vivo. In this study, we designed head-piece-modified analogues of IMMH001 based on structural information and prepared them with an efficient modular synthetic strategy. The analogues showed higher phosphorylation rates in human blood than the parent compound. These results indicated that the pro-R hydroxymethyl in the head-piece-moiety of IMMH001 prevents the pro-S hydroxymethyl from being phosphorylated by the kinase and ATP. The analogues may have better therapeutic potential.

Evaluating Modular Approach to Therapy for Children with Anxiety, Depression, Trauma and Conduct Problems (MATCH-ADCT) in Norwegian child and adolescent outpatient clinics: Study protocol for a randomized controlled trial

BACKGROUND

Norwegian health, care, and welfare services are experiencing increased demands to deliver services that are safe, effective, of high quality, and that ensure user involvement. Yet, evidence-based treatment for common disorders such as depression, anxiety, trauma, and behavioral problems in children are not regularly used in clinical practice in Norway. Possible explanations for this are that many standard, evidence-based treatments may have difficulty addressing the complexity and comorbidity of referred children and the fact that children's treatment needs often shift during treatment. The Modular Approach to Therapy for children with Anxiety, Depression, Trauma and Conduct problems (MATCH-ADTC) was designed to address these challenges and reduce some of the barriers to therapists' use of evidence-based treatment in their practice.

METHODS/DESIGN

Participants will include 280 children (aged 6-14.5 years at intake) who receive treatment in child and adolescent mental health outpatient clinics in Norway, and their families. Families are randomly assigned to either the experimental group receiving treatment from therapists trained in MATCH, or to the comparison group receiving treatment from therapists delivering treatment as usual (TAU). Data on children's symptomology, child and family functioning, demographics, background information, and mental health outcomes are collected as well as frequent feedback on treatment response, plus video-recordings of treatment sessions and implementation quality scores from each participating clinic. Questionnaires are administered in six waves.

DISCUSSION

MATCH has been tested in the US with promising results, but we do not know whether this treatment approach will produce similar results in Norway. The implications of this study are 1. Possibly better treatment outcomes and/or more efficient improvements for children and families treated in mental health outpatient clinics in Norway 2. Clinicians learning to use more evidence-based practices in their treatment 3. Implementation of standard procedures for obtaining feedback from children and families and sharing the feedback with clinicians 4. Increased understanding, at the end of the trial, of whether introducing MATCH improves outcomes for children and families treated in mental health outpatient clinics TRIAL REGISTRATION: ISRCTN, registration number: ISRCTN24029895 . Registered on 8 August 2016.

A modular approach for item response theory modeling with the R package flirt

The new R package flirt is introduced for flexible item response theory (IRT) modeling of psychological, educational, and behavior assessment data. flirt integrates a generalized linear and nonlinear mixed modeling framework with graphical model theory. The graphical model framework allows for efficient maximum likelihood estimation. The key feature of flirt is its modular approach to facilitate convenient and flexible model specifications. Researchers can construct customized IRT models by simply selecting various modeling modules, such as parametric forms, number of dimensions, item and person covariates, person groups, link functions, etc. In this paper, we describe major features of flirt and provide examples to illustrate how flirt works in practice.