The effects of mood and retrieval cues on semantic memory and metacognition

We investigated whether the previously established effect of mood on episodic memory generalizes to semantic memory and whether mood affects metacognitive judgments associated with the retrieval of semantic information. Sixty-eight participants were induced into a happy or sad mood by viewing and describing IAPS images. Following mood induction, participants saw a total of 200 general knowledge trivia items (50 open-ended and 50 multiple-choice after each of two mood inductions) and were asked to provide a metacognitive judgment about their knowledge for each item before providing a response. A sample trivia item is: Author – – To kill a mockingbird. Results indicate that mood affects the retrieval of semantic information, but only when the participant believes they possess the requested semantic information; furthermore, this effect depends upon the presence of retrieval cues. In addition, we found that mood does not affect the likelihood of different metacognitive judgments associated with the retrieval of semantic information, but that, in some cases, having retrieval cues increases accuracy of these metacognitive judgments. Our results suggest that semantic retrieval processes are minimally susceptible to the influence of affective state but does not preclude the possibility that affective state may influence encoding of semantic information.     

Enhancing social diffusion theory as a basis for prevention intervention: A conceptual and strategic framework

Social diffusion theory has recently been recognized as a promising approach for large-scale disease prevention and health promotion efforts. This paper describes how principles and tactics from social cognitive theory, operant psychology, social psychology, social marketing, and the overarching stages of change model can be used to further develop the conceptual and strategic (technological) bases of social diffusion theory. Within an integrative framework, we discuss in detail more effective ways to train peer mediators of behavior change as one example of how social diffusion theory can benefit from this conceptual and strategic reformulation. We then further illustrate the use of peer mediators of change in human immunodeficiency virus (HIV) and cancer prevention intervention studies with both interventions training peer mediators to diffuse information, norms, and risk reduction strategies. Although the results of these studies showed reductions in high-risk behaviors across population segments, more closely following the framework discussed in this article should further increase the behavior change potential of future interventions based on social diffusion theory.     

Remembering changes: repetition effects in face recollection.

Two experiments examined effects of repetition and change on states of awareness in face recognition. Participants studied repeatedly presented photographs of faces, with the second presentation following either immediately after the first presentation (massed repetition) or following six intervening items (spaced repetition). To manipulate perceptual change, each repeated face was either identical or a mirror image of the first presentation. Subsequently, when recognising a face, participants indicated whether they consciously recollected its prior occurrence ("remembering") or recognised it on the basis of familiarity ("knowing"). Changes in appearance between repeated faces enhanced remember, but not know, responses, and these effects were accentuated for spaced, rather than massed, repetition. These findings suggest that distinctiveness of encoding supports the phenomenological experience of conscious remembering.     

Personality characteristics as a function of frequency and type of substance use

Problematic and unhealthy personality characteristics have typically been the focus of researchers interested in the possible causes of substance use/abuse. Recent research has begun to identify differences between individuals based upon frequency of use, with indications that moderate users may have "healthier" characteristics than either abstainers or regular users. The present study was conducted in a rural setting and compared personality structure (based on the California Psychological Inventory) among three groups of college students: abstainers, experimenters, and regular users. The comparisons were conducted as a function of all illicit substance use (excluding alcohol) and for alcohol use only. Minimal support was obtained for the above hypothesis when comparing the three groups on illicit substance use. When comparing the three groups on alcohol use only, support for the theory was identified, with fewer differences found between the experimenters and the abstainers than between the experimenters and the regular users. It is suggested that rural use of psychoactive substances may be more limited to alcohol due to easier availability and less stigma. Data supporting the "healthier" personality structure of moderate users of alcohol would thus be more likely in rural settings even though such use would still be "risky" behavior given its illegality for individuals under age 21. The need for adaptations to current treatment approaches is suggested.     

On normal theory based inference for multilevel models with distributional violations

Data in social and behavioral sciences are often hierarchically organized though seldom normal, yet normal theory based inference procedures are routinely used for analyzing multilevel models. Based on this observation, simple adjustments to normal theory based results are proposed to minimize the consequences of violating normality assumptions. For characterizing the distribution of parameter estimates, sandwich-type covariance matrices are derived. Standard errors based on these covariance matrices remain consistent under distributional violations. Implications of various covariance estimators are also discussed. For evaluating the quality of a multilevel model, a rescaled statistic is given for both the hierarchical linear model and the hierarchical structural equation model. The rescaled statistic, improving the likelihood ratio statistic by estimating one extra parameter, approaches the same mean as its reference distribution. A simulation study with a 2-level factor model implies that the rescaled statistic is preferable.This research was supported by grants DA01070 and DA00017 from the National Institute on Drug Abuse and a University of North Texas faculty research grant. We would like to thank the Associate Editor and two reviewers for suggestions that helped to improve the paper.     

Concise formulas for the standard errors of component loading estimates

Concise formulas for the asymptotic standard errors of component loading estimates were derived. The formulas cover the cases of principal component analysis for unstandardized and standardized variables with orthogonal and oblique rotations. The formulas can be used under any distributions for observed variables as long as the asymptotic covariance matrix for sample covariances/correlations is available. The estimated standard errors in numerical examples were shown to be equivalent to those by the methods using information matrices.The author is indebted to anonymous reviewers for the corrections and suggestions on this study, which have led to improvements of earlier versions of this article.     

A unified approach to exploratory factor analysis with missing data,nonnormal data,and in the presence of outliers

Factor analysis is regularly used for analyzing survey data. Missing data, data with outliers and consequently nonnormal data are very common for data obtained through questionnaires. Based on covariance matrix estimates for such nonstandard samples, a unified approach for factor analysis is developed. By generalizing the approach of maximum likelihood under constraints, statistical properties of the estimates for factor loadings and error variances are obtained. A rescaled Bartlett-corrected statistic is proposed for evaluating the number of factors. Equivariance and invariance of parameter estimates and their standard errors for canonical, varimax, and normalized varimax rotations are discussed. Numerical results illustrate the sensitivity of classical methods and advantages of the proposed procedures.This project was supported by a University of North Texas Faculty Research Grant, Grant #R49/CCR610528 for Disease Control and Prevention from the National Center for Injury Prevention and Control, and Grant DA01070 from the National Institute on Drug Abuse. The results do not necessarily represent the official view of the funding agencies. The authors are grateful to three reviewers for suggestions that improved the presentation of this paper.