Quality of life during occlusion therapy for amblyopia from the perspective of the children and from that of their parents, as proxy.

BACKGROUND: Parents pity their amblyopic child when they think that they suffer from occlusion therapy. We measured health-related quality of life during occlusion therapy. METHODS: We developed the Amblyopia Parents and Children Occlusion Questionnaire (APCOQ). It was designed by a focus group of patients, orthoptists and ophthalmologists and consisted of twelve items concerning skin contact of patch, activities, contact with other children, emotions and awareness of necessity to patch. Parents filled out the Proxy Version shortly before the Child Version was obtained from their child. Child Version item scores were compared with Proxy Version item scores and related to the child's age, visual acuity, refraction, angle of strabismus, and cause of amblyopia. RESULTS: 63 children were recruited by orthoptists, and their parents agreed to participate. Three children were excluded: one child with Down-syndrome, one child with cerebral palsy, and one child who had been treated by occlusion therapy. Included were 60 children (mean age 4.57 ± 1.34 SD) and 56 parents. Children had occluded 128 ± 45 SD days at interview. Prior to occlusion, 54 children had worn glasses. Cronbach's α was 0.74 for the Child Version and 0.76 for the Proxy Version. Children judged their quality of life better than their parents did, especially pertaining to skin contact and activities like games and watching TV. Notably, 13 children with initial visual acuity ≥ 0.6 logMAR in the amblyopic eye experienced little trouble with games during occlusion. Quality of life in eight children with strabismus of five years and older correlated negatively (Spearman rank mean rho = -0.43) with angle of strabismus. Children with amblyopia due to both refractive error and strabismus (n = 14) had, relatively, lowest quality of life, also according to their parents, as proxy. Several children did not know why they wore a patch, contrary to what their parents thought. CONCLUSIONS: Children's quality of life during occlusion therapy is affected less than their parents think, especially regarding skin contact, playing games and watching TV during occlusion. Quality of life correlates negatively with the angle of strabismus in children five years and older. Children do not know why they wear a patch, contrary to what their parents think. Notably, children with low visual acuity in the amblyopic eye, had little difficulty playing games.

Differences in quality-of-life dimensions of Adult Strabismus Quality of Life and Amblyopia & Strabismus Questionnaires.

PURPOSE: The Adult Strabismus Quality of Life Questionnaire (AS-20) and the Amblyopia & Strabismus Questionnaire (A&SQ) both measure health-related quality of life in strabismus patients. We evaluated to what extent these instruments cover similar domains by identifying the underlying quality-of-life factors of the combined questionnaires. METHODS: Participants were adults from a historic cohort with available orthoptic childhood data documenting strabismus and/or amblyopia. They had previously completed the A&SQ and were now asked to complete the AS-20. Factor analysis was performed on the correlation-matrix of the combined AS-20 and A&SQ data to identify common underlying factors. The identified factors were correlated with the clinical variables of angle of strabismus, degree of binocular vision, and visual acuity of the worse eye. RESULTS: One hundred ten patients completed both questionnaires (mean age, 44 years; range, 38-51 years). Six factors were found that together explained 78% of the total variance. The factor structure was dominated by the first four factors. One factor contained psychosocial and social-contact items, and another factor depth-perception items from both questionnaires. A third factor contained seven items-only from the AS-20-on eye strain, stress, and difficulties with reading and with concentrating. A fourth factor contained seven items-only from the A&SQ-on fear of losing the better eye and visual disorientation, specific for amblyopia. Current visual acuity of the worse eye correlated with depth-perception items and vision-related items, whereas current binocular vision correlated with psychosocial and social-contact items, in 93 patients. CONCLUSIONS: Factor analysis suggests that the AS-20 and A&SQ measure a similar psychosocial quality-of-life domain. However, functional problems like avoidance of reading, difficulty in concentrating, eye stress, reading problems, inability to enjoy hobbies, and need for frequent breaks when reading are represented only in the AS-20. During the development of the A&SQ, asthenopia items were considered insufficiently specific for strabismus and were excluded a priori. The patients who generated the items for the AS-20 had, in majority, adulthood-onset strabismus and diplopia and were, hence, more likely to develop such complaints than our adult patients with childhood-onset strabismus and/or amblyopia.

Construct validation of the Amblyopia and Strabismus Questionnaire (A&SQ) by factor analysis.

BACKGROUND: The Amblyopia and Strabismus Questionnaire (A&SQ) was previously developed to assess quality of life (QoL) in amblyopia and/or strabismus patients. Here, factor analysis with Varimax rotation was employed to confirm that the questions of the A&SQ correlated to dimensions of quality of life (QoL) in such patients. METHODS: Responses on the A&SQ from three groups were analyzed: healthy adults (controls) (n = 53), amblyopia and/or strabismus patients (n = 72), and a historic cohort of amblyopes born between 1962-1972 and occluded between 1968-1974 (n = 173). The correlations among the responses to the 26 A&SQ items were factor-analysed by Principal Component Analysis (PCA). As the development of the A&SQ was intuitive-deductive, it was expected that the pattern of correlation could be explained by the five a priori hypothesized dimensions: fear of losing the better eye, distance estimation, visual disorientation, diplopia, and social contact and cosmetic problems. Distribution of questions along the factors derived by PCA was examined by orthogonal Varimax rotation. RESULTS: Data from 296 respondents were analyzed. PCA provided that six factors (cutoff point eigenvalue >1.0) accumulatively explained 70.5% of the variance. All A&SQ dimensions but one matched with four factors found by Varimax rotation (factor loadings >0.50), while two factors pertained to the fifth dimension. The six factors explained 33.7% (social contact and cosmetic problems); 10.3% (near distance estimation); 8.7% (diplopia); 7.2% (visual disorientation); 6.3% (fear of losing the better eye); and 4.3% (far distance estimation), together 70.48% of the item variance. CONCLUSION: The highly explained variance in the A&SQ scores by the factors found by the PCA confirmed the a priori hypothesized dimensions of this QoL instrument.

Testing for response shift in treatment evaluation of change in self-reported psychopathology amongst secondary psychiatric care outpatients.

OBJECTIVES: If patients change their perspective due to treatment, this may alter the way they conceptualize, prioritize, or calibrate questionnaire items. These psychological changes, also called "response shifts," may pose a threat to the measurement of therapeutic change in patients. Therefore, it is important to test the occurrence of response shift in patients across their treatment. METHODS: This study focused on self-reported psychological distress/psychopathology in a naturalistic sample of 206 psychiatric outpatients. Longitudinal measurement invariance tests were computed across treatment in order to detect response shifts. RESULTS: Compared with before treatment, post-treatment psychopathology scores showed an increase in model fit and factor loading, suggesting that symptoms became more coherently interrelated within their psychopathology domains. Reconceptualization (depression/mood) and reprioritization (somatic and cognitive problems) response shift types were found in several items. We found no recalibration response shift. CONCLUSION: This study provides further evidence that response shift can occur in adult psychiatric patients across their mental health treatment. Future research is needed to determine whether response shift implies an unwanted potential bias in treatment evaluation or a desired cognitive change intended by treatment.

Psychometric properties of the Leiden Index of Depression Sensitivity (LEIDS).

The Leiden Index of Depression Sensitivity (LEIDS; Van der Does, 2002a) is a self-report measure of cognitive reactivity (CR) to sad mood. The LEIDS and its revised version, LEIDS-R (Van der Does & Williams, 2003), reliably distinguish between depression-vulnerable and healthy populations. They also correlate with other markers of depression vulnerability, but little is known about the other psychometric properties. Our aim was to examine the factor structure and validity of the LEIDS-R. We used data from the Netherlands Study of Depression and Anxiety (NESDA; N = 1,696) and a student sample (N = 811) for exploratory and confirmatory factor analysis (EFA and CFA, respectively). CFA showed that model fit of the 6-factor structure was satisfactory in the NESDA sample, but some factors were highly correlated. After removing 4 poor items, EFA yielded an alternative 5-factor structure and could not replicate the original 6-factor model. Testing for measurement invariance across recruitment groups of NESDA showed support for strong invariance. Due to high interfactor correlations, a bifactor model with 1 general factor and 5 specific factors was fitted in 2 samples. This model supported use of a general factor, but high factor loadings in specific factors supported retaining a 5-subscale structure. Higher scores on the general factor were associated with a history of depression, especially in participants with a history of comorbid anxiety. We concluded that the LEIDS-R has good psychometric properties. A modified version, LEIDS-RR, comprised of 5 subscales and a total CR score, is recommended for future research. One of the subscales is suitable as a short form. (PsycINFO Database Record

Stochastic Curtailment of Questionnaires for Three-Level Classification: Shortening the CES-D for Assessing Low, Moderate, and High Risk of Depression.

In clinical assessment, efficient screeners are needed to ensure low respondent burden. In this article, Stochastic Curtailment (SC), a method for efficient computerized testing for classification into two classes for observable outcomes, was extended to three classes. In a post hoc simulation study using the item scores on the Center for Epidemiologic Studies-Depression Scale (CES-D) of a large sample, three versions of SC, SC via Empirical Proportions (SC-EP), SC via Simple Ordinal Regression (SC-SOR), and SC via Multiple Ordinal Regression (SC-MOR) were compared at both respondent burden and classification accuracy. All methods were applied under the regular item order of the CES-D and under an ordering that was optimal in terms of the predictive power of the items. Under the regular item ordering, the three methods were equally accurate, but SC-SOR and SC-MOR needed less items. Under the optimal ordering, additional gains in efficiency were found, but SC-MOR suffered from capitalization on chance substantially. It was concluded that SC-SOR is an efficient and accurate method for clinical screening. Strengths and weaknesses of the methods are discussed.

Connecting clinical and actuarial prediction with rule-based methods.

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods.

Weak measurement invariance with respect to unmeasured variables: an implication of strict factorial invariance.

Measurement bias refers to systematic differences across subpopulations in the relation between observed test scores and the latent variant underlying the test scores. Comparisons of subpopulations with the same score on the latent variable can be expected to have the same observed test score. Measurement invariance is therefore one of the key issues in psychological testing. It has been established that strict factorial invariance (SFI) with respect to a selection variable V almost certainly implies weak measurement invariance with respect to V: given SFI, means and variances of observed scores do not depend on V. It is shown that this result can be extended. SFI in groups derived by selection on V has implications not only for V but also for potentially biasing variables W, if W and the selection variable V and/or if W and the factor underlying the observed test scores are statistically dependent. Given SFI with respect to V and prior knowledge concerning these dependencies, it is not necessary to measure and model variables W in order to exclude them as potentially biasing variables if the investigation focuses on groups selected on V.

Curtailment: a method to reduce the length of self-report questionnaires while maintaining diagnostic accuracy.

Minimizing the respondent burden and maximizing the classification accuracy of tests is essential for efficacious screening for common mental health disorders. In previous studies, curtailment of tests has been shown to reduce average test length considerably, without loss of accuracy. In the current study, we simulate Deterministic (DC) and Stochastic (SC) Curtailment for three self-report questionnaires for common mental health disorders, to study the potential gains in efficiency that can be obtained in screening for these disorders. The curtailment algorithms were applied in an existing dataset of item scores of 502 help-seeking participants. Results indicate that DC reduces test length by up to 37%, and SC reduces test length by up to 46%, with only very slight decreases in diagnostic accuracy. Compared to an item response theory based adaptive test with similar test length, SC provided better diagnostic accuracy. Consequently, curtailment may be useful in improving the efficiency of mental health self-report questionnaires.

Response shifts in mental health interventions: an illustration of longitudinal measurement invariance.

The efficacy of treatments for depression is often measured by comparing observed total scores on self-report inventories, in both clinical practice and research. However, the occurrence of response shifts (changes in subjects' values, or their standards for measurement) may limit the validity of such comparisons. As most psychological treatments for depression are aimed at changing patients' values and frame of reference, response shifts are likely to occur over the course of such treatments. In this article, we tested whether response shifts occurred over the course of treatment in an influential randomized clinical trial. Using confirmatory factor analysis, measurement models underlying item scores on the Beck Depression Inventory (Beck & Beamesderfer, 1974) of the National Institute of Mental Health Treatment of Depression Collaborative Research Program (Elkin, Parloff, Hadley, & Autry, 1985) were analyzed. Compared with before treatment, after-treatment item scores appeared to overestimate depressive symptomatology, measurement errors were smaller, and correlations between constructs were stronger. These findings indicate a response shift, in the sense that participants seem to get better at assessing their level of depressive symptomatology. Comparing measurement models of patients receiving psychotherapy and medication suggested that the aforementioned effects were more apparent in the psychotherapy groups. Consequently, comparisons of observed total scores on self-report inventories may yield confounded measures of treatment efficacy.

Improvement in Detection of Differential Item Functioning Using a Mixture Item Response Theory Model.

Usually, methods for detection of differential item functioning (DIF) compare the functioning of items across manifest groups. However, the manifest groups with respect to which the items function differentially may not necessarily coincide with the true source of the bias. It is expected that DIF detection under a model that includes a latent DIF variable is more sensitive to this source of bias. In a simulation study, it is shown that a mixture item response theory model, which includes a latent grouping variable, performs better in identifying DIF items than DIF detection methods using manifest variables only. The difference between manifest and latent DIF detection increases as the correlation between the manifest variable and the true source of the DIF becomes smaller. Different sample sizes, relative group sizes, and significance levels are studied. Finally, an empirical example demonstrates the detection of heterogeneity in a minority sample using a latent grouping variable. Manifest and latent DIF detection methods are applied to a Vocabulary test of the General Aptitude Test Battery (GATB).

Latent-Trait Latent-Class Analysis of Self-Disclosure in the Work Environment.

Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of self-disclosure. The model was used to analyze the data of 1,113 subjects, tested on extraversion and with respect to their degree of self-disclosure toward different categories of people in the work environment. A model with one latent trait and a latent class variable with three categories was identified. Subjects belonging to the different latent classes differ in their general tendency to self-disclose, in their choice to whom they will show self-disclosure and in the degree to which they are selective in their self-disclosure. The collateral variable extraversion was associated with both latent variables. The association of extraversion with selectivity in self-disclosure was not significant.