Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations

Evaluating psychometric properties of the Emotional Eating Scale Adapted for Children and Adolescents (EES-C) in a clinical sample of children seeking treatment for obesity: a case for the unidimensional model.

BackgroundThe Emotional Eating Scale - Adapted for Children and Adolescents (EES-C) assesses children's urge to eat in response to experiences of negative affect. Prior psychometric studies have demonstrated the high reliability, concurrent validity, and test-retest reliability of theoretically defined subconstructs among non-clinical samples of children and adolescents who were primarily healthy weight; however, no psychometric studies exist investigating the EES-C among clinical samples of children with overweight/obesity (OW/OB). Furthermore, studies conducted in different contexts have suggested a discordant number of subconstructs of emotions related to eating. The purpose of this study was to evaluate the validity of the EES-C in a clinical sample of children seeking weight-loss treatment.MethodUsing a hierarchical bi-factor approach, we evaluated the validity of the EES-C to measure a single general construct, a set of two separate correlated subconstructs, or a hierarchical arrangement of two constructs, and determined reliability in a clinical sample of treatment-seeking children with OW/OB aged 8-12 years (N = 147, mean age = 10.4 years.; mean BMI z = 2.0; female = 66%; Hispanic = 32%, White and other = 68%).ResultsComparison of factor-extraction methods suggested a single primary construct underlying EES-C in this clinical sample. The bi-factor indices provided clear evidence that most of the reliable variance in the total score (90.8 for bi-factor model with three grouping factors and 95.2 for bi-factor model with five grouping factors) was attributed to the general construct. After adjusting for relationships with the primary construct, remaining correlations among sets of items did not suggest additional reliable constructs.ConclusionResults suggest that the primary interpretive emphasis of the EES-C among treatment-seeking children with overweight or obesity should be placed on a single general construct, not on the 3- or 5- subconstructs as was previously suggested

Quality-of-life assessment in dementia: the use of DEMQOL and DEMQOL-Proxy total scores

Purpose There is a need to determine whether health-related quality-of-life (HRQL) assessments in dementia capture what is important, to form a coherent basis for guiding research and clinical and policy decisions. This study investigated structural validity of HRQL assessments made using the DEMQOL system, with particular interest in studying domains that might be central to HRQL, and the external validity of these HRQL measurements. Methods HRQL of people with dementia was evaluated by 868 self-reports (DEMQOL) and 909 proxy reports (DEMQOL-Proxy) at a community memory service. Exploratory and confirmatory factor analyses (EFA and CFA) were conducted using bifactor models to investigate domains that might be central to general HRQL. Reliability of the general and specific factors measured by the bifactor models was examined using omega (?) and omega hierarchical (? h) coefficients. Multiple-indicators multiple-causes models were used to explore the external validity of these HRQL measurements in terms of their associations with other clinical assessments. Results Bifactor models showed adequate goodness of fit, supporting HRQL in dementia as a general construct that underlies a diverse range of health indicators. At the same time, additional factors were necessary to explain residual covariation of items within specific health domains identified from the literature. Based on these models, DEMQOL and DEMQOL-Proxy overall total scores showed excellent reliability (? h > 0.8). After accounting for common variance due to a general factor, subscale scores were less reliable (? h < 0.7) for informing on individual differences in specific HRQL domains. Depression was more strongly associated with general HRQL based on DEMQOL than on DEMQOL-Proxy (?0.55 vs ?0.22). Cognitive impairment had no reliable association with general HRQL based on DEMQOL or DEMQOL-Proxy. Conclusions The tenability of a bifactor model of HRQL in dementia suggests that it is possible to retain theoretical focus on the assessment of a general phenomenon, while exploring variation in specific HRQL domains for insights on what may lie at the ‘heart’ of HRQL for people with dementia. These data suggest that DEMQOL and DEMQOL-Proxy total scores are likely to be accurate measures of individual differences in HRQL, but that subscale scores should not be used. No specific domain was solely responsible for general HRQL at dementia diagnosis. Better HRQL was moderately associated with less depressive symptoms, but this was less apparent based on informant reports. HRQL was not associated with severity of cognitive impairment

Electronic Health Literacy Across the Lifespan: Measurement Invariance Study

Background: Electronic health (eHealth) information is ingrained in the healthcare experience to engage patients across the lifespan. Both eHealth accessibility and optimization are influenced by lifespan development, as older adults experience greater challenges accessing and using eHealth tools as compared to their younger counterparts. The eHealth Literacy Scale (eHEALS) is the most popular measure used to assess patient confidence locating, understanding, evaluating, and acting upon online health information. Currently, however, the factor structure of the eHEALS across discrete age groups is not well understood, which limits its usefulness as a measure of eHealth literacy across the lifespan. Objective: The purpose of this study was to examine the structure of eHEALS scores and the degree of measurement invariance among US adults representing the following generations: Millennials (18-35-year-olds), Generation X (36-51-year-olds), Baby Boomers (52-70-year-olds), and the Silent Generation (71-84-year-olds). Methods: Millennials (N=281, mean 26.64 years, SD 5.14), Generation X (N=164, mean 42.97 years, SD 5.01), and Baby Boomers/Silent Generation (N=384, mean 62.80 years, SD 6.66) members completed the eHEALS. The 3-factor (root mean square error of approximation, RMSEA=.06, comparative fit index, CFI=.99, Tucker-Lewis index, TLI=.98) and 4-factor (RMSEA=.06, CFI=.99, TLI=.98) models showed the best global fit, as compared to the 1- and 2-factor models. However, the 4-factor model did not have statistically significant factor loadings on the 4th factor, which led to the acceptance of the 3-factor eHEALS model. The 3-factor model included eHealth Information Awareness, Search, and Engagement. Pattern invariance for this 3-factor structure was supported with acceptable model fit (RMSEA=.07, Δχ2=P>.05, ΔCFI=0). Compared to Millennials and members of Generation X, those in the Baby Boomer and Silent Generations reported less confidence in their awareness of eHealth resources (P<.001), information seeking skills (P=.003), and ability to evaluate and act on health information found on the Internet (P<.001). Results: Young (18-48-year olds, N=411) and old (49-84-year olds, N=419) adults completed the survey. A 3-factor model had the best fit (RMSEA=.06, CFI=.99, TLI=.98), as compared to the 1-factor, 2-factor, and 4-factor models. These 3-factors included eHealth Information Awareness (2 items), Information Seeking (2 items), and Information and Evaluation (4 items). Pattern invariance was supported with the acceptable model fit (RMSEA=.06, Δχ2=P>.05, ΔCFI=0). Compared with younger adults, older adults had less confidence in eHealth resource awareness (P<.001), information seeking skills (P<.01), and ability to evaluate and act upon online health information (P<.001). Conclusions: The eHEALS can be used to assess, monitor uniquely, and evaluate Internet users’ awareness of eHealth resources, information seeking skills, and engagement abilities. Configural and pattern invariance was observed across all generation groups in the 3-factor eHEALS model. To meet gold the standards for factor interpretation (ie, 3 items or indicators per factor), future research is needed to create and assess additional eHEALS items. Future research is also necessary to identify and test items for a fourth factor, one that captures the social nature of eHealth

The 12-item World Health Organization Disability Assessment Schedule II (WHO-DAS II): a nonparametric item response analysis

<p>Abstract</p> <p>Background</p> <p>Previous studies have analyzed the psychometric properties of the World Health Organization Disability Assessment Schedule II (WHO-DAS II) using classical omnibus measures of scale quality. These analyses are sample dependent and do not model item responses as a function of the underlying trait level. The main objective of this study was to examine the effectiveness of the WHO-DAS II items and their options in discriminating between changes in the underlying disability level by means of item response analyses. We also explored differential item functioning (DIF) in men and women.</p> <p>Methods</p> <p>The participants were 3615 adult general practice patients from 17 regions of Spain, with a first diagnosed major depressive episode. The 12-item WHO-DAS II was administered by the general practitioners during the consultation. We used a non-parametric item response method (Kernel-Smoothing) implemented with the TestGraf software to examine the effectiveness of each item (item characteristic curves) and their options (option characteristic curves) in discriminating between changes in the underliying disability level. We examined composite DIF to know whether women had a higher probability than men of endorsing each item.</p> <p>Results</p> <p>Item response analyses indicated that the twelve items forming the WHO-DAS II perform very well. All items were determined to provide good discrimination across varying standardized levels of the trait. The items also had option characteristic curves that showed good discrimination, given that each increasing option became more likely than the previous as a function of increasing trait level. No gender-related DIF was found on any of the items.</p> <p>Conclusions</p> <p>All WHO-DAS II items were very good at assessing overall disability. Our results supported the appropriateness of the weights assigned to response option categories and showed an absence of gender differences in item functioning.</p

Re-evaluation of the latent structure of common childhood disorders: is there a general psychopathology factor (P-factor)?

In the field of psychopathology, there is high comorbidity between different disorders. Traditionally, support for two broad correlated dimensions of internalizing and externalizing symptoms has consistently emerged for children and adolescents. To date, oblique 2 and 3 first-order factor models (factors for externalizing and internalizing, and fear, distress, and externalizing) and bi-factor models with the corresponding two and three group factors have been suggested for common internalizing and eternalizing child and adolescent disorders. The present study used confirmatory factor analyses to examine the relative support for these models in adolescents (≥ 12 to 18 years; N = 866) and children (6 to < 12 years; N = 1233) and the reliability and convergent and divergent validities of the psychopathology factor (P-factor) and group factors in the optimum bi-factor model. All participants were from a clinic and underwent Diagnostic and Statistical Manual of Mental Disorders, 4th Edition clinical diagnosis. The findings showed that the bi-factor model with two group factors (internalizing and externalizing) was the optimum model for both children and adolescents. For both groups, findings showed relatively higher reliability for the P-factor than the group factors, although the externalizing group factor showed substantial reliability in adolescents, and both the externalizing and internalizing group factors also showed substantial reliability in children. The factors of the optimum bi-factor model also showed good convergent and discriminant validities. The implications for theory and clinical and research practice related to psychopathology are discussed

A Rasch analysis of the Person-Centred Climate Questionnaire – staff version

Background: Person-centred care is the bedrock of modern dementia services, yet the evidence-base to support its implementation is not firmly established. Research is hindered by a need for more robust measurement instruments. The 14-item Person-Centred Climate Questionnaire - Staff version (PCQ-S) is one of the most established scales and has promising measurement properties. However, its construction under classical test theory methods leaves question marks over its rigour and the need for evaluation under more modern testing procedures. Methods: The PCQ-S was self-completed by nurses and other care staff working across nursing homes in 35 Swedish municipalities in 2013/14. A Rasch analysis was undertaken in RUMM2030 using a partial credit model suited to the Likert-type items. Three subscales of the PCQ-S were evaluated against common thresholds for overall fit to the Rasch model; ordering of category thresholds; unidimensionality; local dependency; targeting; and Differential Item Functioning. Three subscales were evaluated separately as unidimensional models and then combined as subtests into a single measure. Due to large number of respondents (n = 4381), two random sub-samples were drawn, with a satisfactory model established in the first ('evaluation') and confirmed in the second ('validation'). Final item locations and a table converting raw scores to Rasch-transformed values were created using the full sample. Results: All three subscales had disordered thresholds for some items, which were resolved by collapsing categories. The three subscales fit the assumptions of the Rasch model after the removal of two items, except for subscale 3, where there was evidence of local dependence between two items. By forming subtests, the 3 subscales were combined into a single Rasch model which had satisfactory fit statistics. The Rasch form of the instrument (PCQ-S-R) had an adequate but modest Person Separation Index (&lt; 0.80) and some evidence of mistargeting due to a low number of `difficult-to-endorse' items. Conclusions: The PCQ-S-R has 12 items and can be used as a unidimensional scale with interval level properties, using the nomogram presented within this paper. The scale is reliable but has some inefficiencies due to too few high-end thresholds inhibiting discrimination amongst populations who already perceive that person-centred care is very good in their environment

Bifactor analysis of motivation for charity sport event participation

The purpose of this study was to examine the utility of the existing subscales of charity sport events (CSEs) participation motivation by adopting both a second-order modeling and a bifactor modeling approaches. The results with 488 college students revealed that the bifactor model provided a better interpretation of the data compared to second-order model. The five-factor CSE motivation significantly predict the intention to participate in CSEs along with two domain-specific motivations, namely ‘sport and event’ and ‘cause’ while other three domain-specific motivations including ‘philanthropic’, ‘social interaction’, and ‘reference group’ are not statistically significant predictors. The results suggest that the bifactor model is more useful in predicting this group’s participation in charity sport events. © 2015, Springer-Verlag Berlin Heidelberg

Development of a Patient-Report Measure of Psychotherapy for Depression

Despite clear indications of need to improve depression treatment, practical tools that efficiently measure psychotherapy are not available. We developed a patient-report measure of psychotherapy for depression that assesses Cognitive Behavioral (CBT), Interpersonal (IPT), and Psychodynamic therapies. 420 patients with depression from a large managed behavioral health care organization completed the measure. The three subscales measuring CBT, IPT, and Psychodynamic Therapy showed good internal consistency, appropriate item-total correlations, and were supported by a 3-factor structure. Our results suggest that a patient questionnaire is a promising approach for assessing psychotherapy in quality improvement interventions