I deserve more A's: A report on the development of a measure of academic entitlement.

This paper reports the results of a multi-stage effort to develop a measure of Academic Entitlement. An empirical/rational approach was taken to develop items and reduce the item set for a final version of the Academic Entitlement Scale (AES). The measure includes seven dimensions: Accommodation, Reward for Effort, Responsibility Avoidance, Grade Haggling, Customer Orientation, Customer Service Expectations, and General Academic Entitlement. Fit, using Confirmatory Factor Analysis, for the seven-factor correlated model and a bifactor model including General AE and the six specific factors, was good. The full measure is reported along with descriptive statistics for the scale and preliminary validation evidence.

Pre-drinking motives in Canadian undergraduate students: Confirmatory factor analysis of the Prepartying Motivations Inventory and examination of new themes.

INTRODUCTION: Pre-drinking is a risky, yet common activity among college students whereby they consume alcohol prior to going to an event where more alcohol may be consumed (LaBrie, Hummer, Pederson, Lac, & Chithambo, 2012). While general drinking motives have been studied extensively, attention to pre-drinking is recent, and deserves more attention. This study assessed the reliability, validity, and factor structure of the Prepartying Motivations Inventory (PMI), and identified novel motivations through a thematic analysis. METHOD: A sample of 276 Canadian undergraduate students completed an online survey consisting of open-ended questions, drinking and pre-drinking questions, the PMI, and a brief demographic questionnaire. RESULTS: It was demonstrated that a four-factor model, similar to that of the initial PMI, fits well, but that improvements are made by eliminating an item related to being under the legal drinking age. Further, five new themes emerged that warrant further investigation, and possible inclusion in the current PMI. CONCLUSIONS: Findings suggest that the PMI could be refined to further understand students' motivations for pre-drinking, and might inform alcohol intervention programs on post-secondary campuses.

A meta-analysis of cognitive functioning in nondemented adults with type 2 diabetes mellitus.

OBJECTIVE: The current investigation sought to determine the pattern and magnitude of cognitive functioning deficits in persons with type 2 diabetes mellitus without dementia using meta-analysis to consolidate findings in the literature. METHODS: MedLine and PsychInfo databases were searched to identify studies of cognitive functioning in persons with type 2 diabetes. Effect sizes (Cohen's d) were calculated for the differences in cognitive functioning between subjects with type 2 diabetes and controls without diabetes on classified cognitive abilities. Average d values were calculated for all cognitive abilities across studies. RESULTS: Twenty-five studies meeting the inclusion criteria were identified. Persons with type 2 diabetes performed significantly lower than controls without diabetes (p<0.05) on all cognitive abilities evaluated, with effect sizes ranging from -0.14 to -0.37. The largest effect sizes were processing speed (with motor task demands), M -0.37 (95% CI, -0.41 to -0.32), and divided attention/shifting, M -0.36 (95% CI, -0.42 to -0.31). CONCLUSIONS: Type 2 diabetes leads to mild to moderate deficits in all measured cognitive abilities. There was a lack of published studies investigating type 2 diabetes-associated variables; therefore, additional meta-analyses investigating the impact of these variables on cognitive functioning in type 2 diabetes could not be performed. As such, data from individual studies must be reported consistently to allow for investigation of variables that may affect the relationship between type 2 diabetes and cognitive functioning. Given the present findings, clinicians working with patients with type 2 diabetes should be alerted to the possibility of cognitive changes that could impact type 2 diabetes treatment management or require referral for neuropsychological assessment.

The role of belief in occurrence within autobiographical memory.

This article examines the idea that believing that events occurred in the past is a non-memorial decision that reflects underlying processes that are distinct from recollecting events. Research on autobiographical memory has often focused on events that are both believed to have occurred and remembered, thus tending to overlook the distinction between autobiographical belief and recollection. Studying event representations such as false memories, believed-not-remembered events, and non-believed memories shows the influence of non-memorial processes on evaluations of occurrence. Believing that an event occurred and recollecting an event may be more strongly dissociated than previously stated. The relative independence of these constructs was examined in 2 studies. In Study 1, multiple events were cued, and then each was rated on autobiographical belief, recollection, and other memory characteristics. In Study 2, participants described a nonbelieved memory, a believed memory, and a believed-not-remembered event, and they made similar ratings. In both studies, structural equation modeling techniques revealed distinct belief and recollection latent variables. Modeling the predictors of these factors revealed a double dissociation: Perceptual, re-experiencing, and emotional features predicted recollection and not belief, whereas event plausibility strongly predicted belief and weakly predicted recollection. The results show that judgments of autobiographical belief and recollection are distinct, that each is influenced by different sources of information and processes, and that the strength of their relationship varies depending on the type of event under study. The concept of autobiographical belief is elaborated, and implications of the findings are discussed in relation to decision making about events, social influence on memory, metacognition, and recognition processes.

Reporting results of latent growth modeling and multilevel modeling analyses: some recommendations for rehabilitation psychology.

OBJECTIVE: There has been a general increase in interest and use of modeling techniques that treat data as nested, whether it is people nested within larger units, such as families or treatment centers, or observations nested under people. The popularity can be witnessed by noting the number of new textbooks and articles related to latent growth curve modeling and multilevel modeling. This paper discusses both of these techniques in the context of longitudinal research designs, with the main purposes of highlighting some benefits and issues related to the use of these models and outlining guidelines for reporting results from studies using multilevel modeling or latent growth modeling. IMPLICATIONS: These longitudinal analytic techniques can be greatly beneficial to researchers conducting rehabilitation studies, but there are several issues related to their use and reporting that need to be taken into consideration.

Reporting practices in confirmatory factor analysis: an overview and some recommendations.

Reporting practices in 194 confirmatory factor analysis studies (1,409 factor models) published in American Psychological Association journals from 1998 to 2006 were reviewed and compared with established reporting guidelines. Three research questions were addressed: (a) how do actual reporting practices compare with published guidelines? (b) how do researchers report model fit in light of divergent perspectives on the use of ancillary fit indices (e.g., L.-T. Hu & P. M. Bentler, 1999; H. W. Marsh, K.-T., Hau, & Z. Wen, 2004)? and (c) are fit measures that support hypothesized models reported more often than fit measures that are less favorable? Results indicate some positive findings with respect to reporting practices including proposing multiple models a priori and near universal reporting of the chi-square significance test. However, many deficiencies were found such as lack of information regarding missing data and assessment of normality. Additionally, the authors found increases in reported values of some incremental fit statistics and no statistically significant evidence that researchers selectively report measures of fit that support their preferred model. Recommendations for reporting are summarized and a checklist is provided to help editors, reviewers, and authors improve reporting practices.