Using Patient-Reported Outcome Measures for Quality Improvement in Clinical Genetics: an Exploratory Study

International advocacy of patient-centred healthcare delivery has led to emphasis on the (re)design and evaluation of healthcare processes and outcomes from a patient perspective. Patient-reported outcome measures (PROMs) have significant potential to inform such attempts. However there is limited understanding of the processes by which this can be achieved. This exploratory study followed attempts to utilise two different PROMs measures to support service quality improvement in clinical genetics. PROMs used were the Genetic Counseling Outcome Scale (GCOS-24), a well-validated clinical genetics-specific PROM and Euroqol (EQ-5D), a generic PROM favoured by the UK National Institute for Health and Excellence (NICE). Both of these PROMs enable pre/post intervention comparison. A service audit tool was also used, premised on a patient-reported experience measure. In addition, the study draws on interviews with clinical staff to identify challenges associated with the use of PROMs (response rate, data collection, analysis). Benefits are also explored and include the provision of insight into patients’ needs; complementing clinical judgement; identification of needs being met, evidencing the benefit of services provided; prompting consideration of areas requiring attention; and encouraging professional development.     

Nostalgia as a Linking Phenomenon

Immigrants and refugees who leave behind their countries, loved ones, and cultural environment experience loss and are obliged to go through a mourning process which may become complicated due to a variety of factors. Many such individuals create linking objects or linking phenomena that help them to continue to have contact with the past, while adjusting to their new environment. Nostalgia is the affect that accompanies linking objects and linking phenomena and at times functions itself as a linking phenomenon. The lack of nostalgia, poisoned nostalgia, and nostalgia in the service of adaptation are discussed with clinical examples.     

autoRasch: An R Package to Do Semi-Automated Rasch Analysis

The R package autoRasch has been developed to perform a Rasch analysis in a (semi-)automated way. The automated part of the analysis is achieved by optimizing the so-called in-plus-out-of-questionnaire log-likelihood (IPOQ-LL) or IPOQ-LL-DIF when differential item functioning (DIF) is included. These criteria measure the quality of fit on a pre-collected survey, depending on which items are included in the final instrument. To compute these criteria, autoRasch fits the generalized partial credit model (GPCM) or the generalized partial credit model with differential item functioning (GPCM-DIF) using penalized joint maximum likelihood estimation (PJMLE). The package further allows the user to reevaluate the output of the automated method and use it as a basis for performing a manual Rasch analysis and provides standard statistics of Rasch analyses (e.g., outfit, infit, person separation reliability, and residual correlation) to support the model reevaluation.     

Linking Disjoint Supermatrices and Criteria Clusters

An axiom of the Analytic Network Process (ANP) requires the elements being considered to be strongly connected in order to obtain a meaningful priority vector. A simple example demonstrates the issues that can arise when a decision contains disjoint clusters within the Supermatrix. From the example it can be observed that the necessary information to complete additional linking pin comparisons would have already been collected; and by performing linking pin comparisons a decision maker can convert a disjoint Supermatrix into a strongly connected Supermatrix. The linking process is summarized in five steps and provided in the general form. This linking comparison methodology exploits the fundamental advantages of pairwise comparisons and can also be used to weight the criteria clusters within a decision network. Linking pin comparisons performed at the level of a criterion of a single alternative with respect to another criterion of that same alternative can be used to obtain the criteria cluster weights. Linking pin comparisons at this level can reduce the decision maker's cognitive burden in comparison to totality comparisons. The ability to strongly connect an otherwise disjoint Supermatrix and reduce the decision maker's cognitive burden demonstrates the usefulness of linking pin comparisons in ANP decision models. Copyright © 2016 John Wiley & Sons, Ltd.     

Health Outcome Measures for Diabetes Mellitus: A Review

To review selective health outcome measures for diabetes mellitus focussing on psychometric properties. Systematic literature search was carried out to identify the instruments using electronic databases and manual search from relevant journals. Health outcome measures were assessed with predefined inclusion and exclusion criteria. Each instrument was assessed for patient related information, instrument content, reliability, validity and responsiveness to change. The electronic and manual search generated 317 relevant references. Twenty seven instruments that met the inclusion criteria were included in the study. Among the 27 instruments, 20 were in English language. Out of these, 14 instruments were developed in USA and the majority of the remaining in UK. The time taken to complete the questionnaires varied from 3-40 minutes. Appraisal of Diabetes Scale and Audit of Diabetes-Dependent Quality of Life are single index instruments and the remaining instruments have dimension in a range of three to nine. Appraisal of Diabetes Scale and Diabetes Treatment Satisfaction Questionnaire are the shortest questionnaire whereas Diabetes Care Profile is the longest. The Diabetes Treatment Satisfaction Questionnaire has more translations followed by Diabetes Medication Satisfaction, Audit of Diabetes-Dependent Quality of Life, Diabetes Health profile, Problem area in diabetes scale and Insulin Treatment Appraisal Scale. All the instruments were assessed for psychometric properties. The Diabetes Care Profile, Diabetes-39, Diabetes Quality of life measure, Diabetes specific Quality of life scale, Diabetes Treatment Satisfaction Questionnaire, Diabetes symptom checklist-Revised and Diabetes Medication Satisfaction instruments have good psychometric properties and may be useful for the researcher interested in diabetes care. Most of the instruments were lacking in responsiveness evaluation and were developed and evaluated mainly in developed countries. There is a need, therefore, to focus future research on health outcome measures on the evaluation of responsiveness.     

A new goodness-of-fit measure for probit models: Surrogate R2

Probit models are used extensively for inferential purposes in the social sciences as discrete data are prevalent in a vast body of social studies. Among many accompanying model inference problems, a critical question remains unsettled: how to develop a goodness-of-fit measure that resembles the ordinary least square (OLS) R² used for linear models. Such a measure has long been sought to achieve ‘comparability’ of different empirical models across multiple samples addressing similar social questions. To this end, we propose a novel R² measure for probit models using the notion of surrogacy – simulating a continuous variable $S$ as a surrogate of the original discrete response (Liu & Zhang, Journal of the American Statistical Association, 113, 845 and 2018). The proposed R² is the proportion of the variance of the surrogate response explained by explanatory variables through a linear model, and we call it a surrogate R². This paper shows both theoretically and numerically that the surrogate R² approximates the OLS R² based on the latent continuous variable, preserves the interpretation of explained variation, and maintains monotonicity between nested models. As no other pseudo R², McKelvey and Zavoina's and McFadden's included, can meet all the three criteria simultaneously, our measure fills this crucial void in probit model inference.     

Concurrent Validation of the Treatment Outcome Package (TOP) for Children and Adolescents

The Treatment Outcome Package for children and adolescents (TOP) is a behavioral health and well-being assessment used widely in clinical and child welfare populations. The primary purpose of this study was to examine the concurrent validity of the Child and Adolescent versions of the TOP with the Child Behavior Checklist (CBCL) and the Strengths and Difficulties Questionnaire (SDQ) with a community sample. Children and adolescents (N = 203) 3–18 years of age from a community sample completed the CBCL, the SDQ, and the TOP. Significant correlations emerged between the TOP and theoretically similar scales on the SDQ and the CBCL. Analyses demonstrated that the TOP has excellent concurrent validity on most subscales with both the CBCL and the SDQ. These results provide additional evidence for the TOP’s utility and validity as a measure of psychological well-being and functioning.     

Research in Consultation: Toward Better Analogues and Outcome Measures

Recommendations for improving consultation research include (a) strengthening consultation analogue research by incorporating “boundary” conditions into research designs and (b) extending the outcome measures used.     

Linking serial residential burglary: comparing the utility of modus operandi behaviours,geographical proximity,and temporal proximity

Whilst case linkage is used with serious forms of serial crime (e.g. rape and murder), the potential exists for it to be used with volume crime. This study replicates and extends previous research on the behavioural linking of burglaries. One hundred and sixty solved residential burglaries were sampled from a British police force. From these, 80 linked crime pairs (committed by the same serial offender) and 80 unlinked crime pairs (committed by two different serial offenders) were created. Following the methodology used by previous researchers, the behavioural similarity, geographical proximity, and temporal proximity of linked crime pairs were compared with those of unlinked crime pairs. Geographical and temporal proximity possessed a high degree of predictive accuracy in distinguishing linked from unlinked pairs as assessed by logistic regression and receiver operating characteristic analyses. Comparatively, other traditional modus operandi behaviours showed less potential for linkage. Whilst personality psychology literature has suggested we might expect to find a relationship between temporal proximity and behavioural consistency, such a relationship was not observed. Copyright © 2010 John Wiley & Sons, Ltd.     

影响产品体积知觉的形状效应研究

产品包装是现代营销的重要手段之一,也是消费与广告心理学领域的研究热点之一。产品包装的形状、尺寸和体积大小都会影响到消费者的判断、购买决策和消费行为。本文就影响产品体积知觉的高径比效应(elongation),从其概念、形状消费错觉与形重错觉的关系、实际消费中的体积知觉效应,以及注意对形状效应的影响等方面进行了阐述,并作了简要的评论。     

测验链接中的锚题代表性研究

本文旨在以“锚题代表性”这一研究命题切入,探索在非等组锚测验设计下,作为实现测验链接的重要载体,锚题和相关的测验试卷/水平之间究竟应该有什么关系。本文首先指出锚题代表性这一概念在等值和垂直量尺化领域中具有不同的含义,并给出其在垂直量尺化中的含义。通过考察测验链接中有关锚题代表性的既有研究,系统总结相关研究成果,本文概括出了当前锚题构建实践的可能优化方案,分析了锚题代表性研究的未来方向。     

结果的接近性对正性结果评价影响的电生理证据

结果的接近性是指对已发生事件的实际结果与在心理上的理想结果或期待结果之间差距的接近程度。实验采用事件相关电位技术和类老虎机赌博任务探讨了结果的接近性对正性结果评价的影响。(1)行为评定结果表明, 结果的接近性不同水平诱发了不同的情绪体验, “差一点输”的赢钱使被试更多感到庆幸, “最理想”的赢钱使被试感到高兴; 结果的接近性也影响了随后trial的反应时, 与“一般”的赢钱和“最理想”的赢钱相比, “差一点输的”赢钱后的下一个trial中被试的反应时明显变长。(2)脑电结果表明, 结果的接近性不同水平诱发了不同的FRN和P300, 与“一般”的赢钱和“最理想”的赢钱相比, “差一点输”的赢钱诱发了波幅更大的FRN和波幅更大潜伏期更长的P300。这说明结果的接近性明显地影响了正性结果的认知评价加工。     

TreeBUGS: An R package for hierarchical multinomial-processing-tree modeling

Multinomial processing tree (MPT) models are a class of measurement models that account for categorical data by assuming a finite number of underlying cognitive processes. Traditionally, data are aggregated across participants and analyzed under the assumption of independently and identically distributed observations. Hierarchical Bayesian extensions of MPT models explicitly account for participant heterogeneity by assuming that the individual parameters follow a continuous hierarchical distribution. We provide an accessible introduction to hierarchical MPT modeling and present the user-friendly and comprehensive R package TreeBUGS, which implements the two most important hierarchical MPT approaches for participant heterogeneity—the beta-MPT approach (Smith & Batchelder, Journal of Mathematical Psychology 54:167-183, 2010) and the latent-trait MPT approach (Klauer, Psychometrika 75:70-98, 2010). TreeBUGS reads standard MPT model files and obtains Markov-chain Monte Carlo samples that approximate the posterior distribution. The functionality and output are tailored to the specific needs of MPT modelers and provide tests for the homogeneity of items and participants, individual and group parameter estimates, fit statistics, and within- and between-subjects comparisons, as well as goodness-of-fit and summary plots. We also propose and implement novel statistical extensions to include continuous and discrete predictors (as either fixed or random effects) in the latent-trait MPT model.     

Estimating Complex Measurement and Growth Models Using the R Package PLmixed

Measurement models, such as factor analysis and item response theory models, are commonly implemented within educational, psychological, and behavioral science research to mitigate the negative effects of measurement error. These models can be formulated as an extension of generalized linear mixed models within a unifying framework that encompasses various kinds of multilevel models and longitudinal models, such as partially nonlinear latent growth models. We introduce the R package PLmixed, which implements profile maximum likelihood estimation to estimate complex measurement and growth models that can be formulated within the general modeling framework using the existing R package lme4 and function optim. We demonstrate the use of PLmixed through two examples before concluding with a brief overview of other possible models.     

Linking Individual Value Orientations to Employee Attitudes: An Exploratory Analysis

This study tested the relationships of individualism, power distance, and mastery orientation to 2 employee attitudes (organizational trust and organizational commitment) that are associated with employees’ psychological benefits within the organization. Results from university employees (N = 706) showed that individualism negatively, whereas mastery positively, related to trust and commitment. Power distance positively related to trust only. The moderating role of mastery was also identified. These findings can help employment or organizational counselors to appreciate value‐related factors that facilitate employees in psychologically integrating into the organization and to explore new ways for employers to foster employees’ positive attitudes.     

RMediation: An R package for mediation analysis confidence intervals

This article describes the RMediation package,which offers various methods for building confidence intervals (CIs) for mediated effects. The mediated effect is the product of two regression coefficients. The distribution-of-the-product method has the best statistical performance of existing methods for building CIs for the mediated effect. RMediation produces CIs using methods based on the distribution of product, Monte Carlo simulations, and an asymptotic normal distribution. Furthermore, RMediation generates percentiles, quantiles, and the plot of the distribution and CI for the mediated effect. An existing program, called PRODCLIN, published in Behavior Research Methods, has been widely cited and used by researchers to build accurate CIs. PRODCLIN has several limitations: The program is somewhat cumbersome to access and yields no result for several cases. RMediation described herein is based on the widely available R software, includes several capabilities not available in PRODCLIN, and provides accurate results that PRODCLIN could not.     

An R package for state-trace analysis

State-trace analysis (Bamber, Journal of Mathematical Psychology, 19, 137-181, 1979) is a graphical analysis that can determine whether one or more than one latent variable mediates an apparent dissociation between the effects of two experimental manipulations. State-trace analysis makes only ordinal assumptions and so, is not confounded by range effects that plague alternative methods, especially when performance is measured on a bounded scale (such as accuracy). We describe and illustrate the application of a freely available GUI driven package, StateTrace, for the R language. StateTrace automates many aspects of a state-trace analysis of accuracy and other binary response data, including customizable graphics and the efficient management of computationally intensive Bayesian methods for quantifying evidence about the outcomes of a state-trace experiment, developed by Prince, Brown, and Heathcote (Psychological Methods, 17, 78-99, 2012).     

The Effectiveness of Coping Power Program for ADHD: An Observational Outcome Study

The present study evaluates the implementation of the Coping Power Program (CPP)-Child Component in a group of patients with attention deficit/hyperactivity disorder (ADHD), and explores the effects of this treatment on changes in the primary and associated symptoms of ADHD. A clinical sample of 50 children and preadolescents (8–13 years) with ADHD was involved. The clinical sample was split into a treatment group (TG; N?=?26), which was included in the child training program (CPP), and a control group (CG; N?=?24), which was placed on a waiting list. The Clinical Global Impression-Severity (CGI-S) and the Child Behavior Checklist 6–18 (CBCL 6–18) were assessed at baseline and at the end of treatment. The outcomes were assessed as a CBCL-subscale response rate and a CGI-S shift. Our results showed a significant improvement in children’s global functioning and in emotional and behavioral symptoms. The children in the TG were more likely to shift from a more severe functional impairment class to a less severe one (69.2% of TG vs. 20.8% of CG). Further, the CGI-S scores diminished significantly in the TG (p?<?0.01). There were significant differences in the changes in Social Problems (p?<?0.05), Attention Problems (p?<?0.05) and Rule-Breaking Behavior Scales (p?<?0.05). CPP seemed to be effective in children and adolescents with ADHD without comorbidity for ODD or CD. Our study revealed an improved outcome, not only in the core symptoms of ADHD, but also in global functioning and social adjustment. Possible improvements to the present formulation of CPP-C are discussed.