Preliminary investigation of the Kitchen Picture Test (KPT): A new screening test of practical judgment for older adults

Judgment is widely recognized as an important executive function, and deficits in judgment can lead to health risks, safety concerns, and hospitalizations. Surprisingly, relatively few tests of judgment have been developed specifically for older adults—a population particularly vulnerable to executive and functional declines. The Kitchen Picture Test (KPT) is a new screening measure of practical judgment. In two independent studies (Study 1, N = 99 nursing home patients; Study 2, N = 163 nursing home and assisted living patients), psychometric analyses confirmed strong evidence for reliability, construct validity, and predictive validity. A receiver operating characteristic (ROC) curve was calculated from sensitivity and 1-specificity values for diagnoses of dementia versus no dementia. A KPT cut score can be used for identifying persons to be referred to appropriate health-care professionals who have specific expertise in the evaluation and treatment of cognitive impairment.     

Mind-Wandering and Childhood ADHD: Experimental Manipulations across Laboratory and Naturalistic Settings

Research on Child and Adolescent Psychopathology - The conceptual overlap between mind-wandering and attention-deficit/hyperactivity disorder (ADHD)-related impairments is considerable, yet little...     

Anticipatory looks reveal expectations about discourse relations

Previous research provides evidence for expectation-driven processing within sentences at phonological, lexical, and syntactic levels of linguistic structure. Less well-established is whether comprehenders also anticipate pragmatic relationships between sentences. To address this, we evaluate a unit of discourse structure that comprehenders must infer to hold between sentences in order for a discourse to make sense—the intersentential coherence relation. In a novel eyetracking paradigm, we trained participants to associate particular spatial locations with particular coherence relations. Experiment 1 shows that the subset of listeners who successfully acquired the location∼relation mappings during training subsequently looked to these locations during testing in response to a coherence–signaling intersentential connective. Experiment 2 finds that listeners’ looks during sentences containing coherence-biasing verbs reveal expectations about upcoming sentence types. This work extends existing research on prediction beyond sentence-internal structure and provides a new methodology for examining the cues that comprehenders use to establish relationships at the discourse level.     

Spiritual Versus Religious Identity: A Necessary Distinction in Understanding Clinicians’ Behavior and Attitudes Toward Clinical Practice and Medical Student Teaching in This Realm

Social sciences view spirituality and religion separately; medicine views them together. We identified distinctions regarding clinical practice and teaching among clinician educators based on their self-identified spirituality versus religiosity. We emailed a 24-item survey on spiritual/religious (S/R) issues to clinician educators (n = 1,067) at our institution. Three summary scales were created. Responses to statements, ‘I consider myself to be spiritual’ and ‘I consider myself to be religious’ generated four comparison groups: ‘spiritual only,’ ‘religious only,’ ‘both spiritual and religious’ and ‘neither.’ Analyses employed ANOVA and T tests. A total of 633 (59 %) surveys were completed. Four percentage self-identified as ‘religious only’; remaining respondents divided evenly, about 30 % into each of the other categories. Groups differed from one another on all summary scales (p < .0001). Using T tests, the ‘spiritual only’ group differed from the ‘religious only’ group regarding teaching. The ‘spiritual and religious’ group had the highest mean ratings for all summary scales. The ‘neither’ and ‘religious only’ group had the lowest mean ratings. Clinicians’ spiritual versus religious identity is associated with differences in behavior/attitudes regarding S/R toward clinical practice and medical student teaching. These findings elucidate opportunities for faculty development to explore effects of beliefs on behavior and attitudes within this realm.     

Using generalized additive (mixed) models to analyze single case designs

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R.     

School System Evaluation by Value Added Analysis Under Endogeneity

Value added is a common tool in educational research on effectiveness. It is often modeled as a (prediction of a) random effect in a specific hierarchical linear model. This paper shows that this modeling strategy is not valid when endogeneity is present. Endogeneity stems, for instance, from a correlation between the random effect in the hierarchical model and some of its covariates. This paper shows that this phenomenon is far from exceptional and can even be a generic problem when the covariates contain the prior score attainments, a typical situation in value added modeling. Starting from a general, model-free definition of value added, the paper derives an explicit expression of the value added in an endogeneous hierarchical linear Gaussian model. Inference on value added is proposed using an instrumental variable approach. The impact of endogeneity on the value added and the estimated value added is calculated accurately. This is also illustrated on a large data set of individual scores of about 200,000 students in Chile.