Self-monitoring: Appraisal and reappraisal.

Theory and research on self-monitoring have accumulated into a sizable literature on the impact of variation in the extent to which people cultivate public appearances in diverse domains of social functioning. Yet self-monitoring and its measure, the Self-Monitoring Scale, are surrounded by controversy generated by conflicting answers to the critical question, Is self-monitoring a unitary phenomenon? A primary source of answers to this question has been largely neglected—the Self-Monitoring Scale's relations with external criteria. The authors propose a quantitative method to examine the self-monitoring literature and thereby address major issues of the controversy. Application of this method reveals that, with important exceptions, a wide range of external criteria tap a dimension directly measured by the Self-Monitoring Scale. The authors discuss what this appraisal reveals about what self-monitoring is and is not. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On the nature of self-monitoring: Construct explication with Q-sort ratings.

To explicate M. Snyder's (1987) construct of self-monitoring (SM), a new Q-sort prototype is introduced. Analyses of Q-sorts by both observers and self demonstrated cross-method convergent validity for the revised 18-item Self-Monitoring Scale (SMS-R) and its Public Performing subscale; however, neither scale showed discriminant validity against measures of extraversion. The Other-Directedness items remaining on the SMS-R correlated neither with the other measures of SM nor with extraversion. These findings suggest that the scale revision led to a conceptual shift toward extraverted (and away from other-directed) features of self-presentation. To adequately assess the conceptual domain of SM phenomena, researchers should administer the original 25-item SMS (not the abbreviated 18-item SMS-R) and score Public Performing and Other-Directedness separately to examine their individual and joint effects. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Attributional style and attributional patterns among married couples.

Explored whether couples develop an attributional style in explaining marital behavior. Results demonstrate that spouses vary greatly in the extent to which they develop an attributional style in this area. Development of an attributional style is correlated with marital distress. Investigators have assumed that simultaneous attributional ratings across several attributional dimensions best characterize the attributions that spouses make for marital events. Yet almost all studies to date have considered each attributional dimension separately. The current investigation explored whether meaningful attributional patterns across dimensions were discernible for marital events. Findings indicate that such patterns do exist and are psychologically interpretable, and support the hypothesis that distressed spouses tend to maximize negative partner behaviors while minimizing positive partner behaviors. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The role of feedback, casual attributions, and self-efficacy in goal revision.

An important issue in work motivation is how, when, and why individuals revise their goals up or down over time. In the current study, the authors examine feedback, causal attributions, and self-efficacy in this process. Although self-efficacy has frequently been suggested as a key explanatory variable for goal revision, its role has yet to be directly evaluated. Additionally, although attributions have been shown to influence goal revision following failure, the extent to which attributions influence goal revision following success remains unclear. In the current study, the authors address these issues by experimentally manipulating goal progress via performance feedback and tracking the resulting changes in self-efficacy and goal revision over time. In so doing, the authors also address several interpretive ambiguities present in the existing research. Results support the hypothesized model, finding that performance feedback and attributions interactively influenced self-efficacy, which in turn influenced goal revision. These results suggest that interventions targeting attributions, and self-efficacy more directly, may have meaningful influences on goal setting and pursuit, particularly following feedback. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Self-monitoring and control in dyadic interactions.

Examined individual differences in the level of planning and monitoring involved in actual interpersonal interactions between pairs of friends and strangers, as measured by a self-monitoring scale (SMS) developed by M. Snyder (see record 1975-03047-001). 18 male–male, 18 male–female, and 18 female–female undergraduate dyads of friends or strangers conversed for 10 min and completed a questionnaire (rating their behavior and feelings in the interaction) and the SMS. Findings reveal that the original unitary SMS was a poor predictor of Ss' perceptions of the interaction, whereas an analysis based on 3 subscales suggested by previous research (e.g., S. R. Briggs et al [see PA, Vol 65:9212]) not only successfully predicted the Ss' perceptions but also explained the failure of the unitary scale. The subscales frequently operated in opposite directions to one another, so that although the individual subscales were able to predict aspects of Ss' perceptions quite well, when the scores were amalgamated into a single overall score this predictive power was lost. It is concluded that the subscales derived from the SMS provided a better explanation of Ss' perceptions of their interactions. (34 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effects of three psychological treatments and self-monitoring on the reduction of Type A behavior.

31 Type A (coronary prone) individuals received either cognitive–behavioral treatment, values-clarification treatment in combination with anxiety management training (AMT), or AMT alone. Ss were also blocked on the variable of self-monitoring, which is the extent to which one plans and enacts social behavior by using situational cues. Reduction in Type A behavior was achieved by all Ss, with none of the treatment groups producing clearly superior reductions. Reduction of anxiety was significantly effected by treatment condition, self-monitoring, and the interaction of these 2 variables. Implications for treatment of the Type A behavior pattern as well as the possible effects of self-monitoring on response to more general cognitive–behavioral techniques are discussed. (47 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Simple minitheories of love.

Developed 2 causal models of love as alternatives to the A. Tesser and D. L. Paulhus (see record 1978-21448-001) theory. These models were tested for adequacy of fit using maximum-likelihood methods. While the Tesser-Paulhus models can be rejected empirically, the alternate models provide acceptable statistical representations of 4 variables measuring love at 2 times separated by 2 wks. One formulation is based on the idea of unidimensionality of interpersonal attraction. The 2nd formulation represents a refinement of the Tesser-Paulhus view of love. The formulation based on the idea that interpersonal attraction is primarily a unidimensional construct provides the more parsimonious and interpretable theory. (16 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Causal-Model Theory of Conceptual Representation and Categorization.

This article presents a theory of categorization that accounts for the effects of causal knowledge that relates the features of categories. According to causal-model theory, people explicitly represent the probabilistic causal mechanisms that link category features and classify objects by evaluating whether they were likely to have been generated by those mechanisms. In 3 experiments, participants were taught causal knowledge that related the features of a novel category. Causal-model theory provided a good quantitative account of the effect of this knowledge on the importance of both individual features and interfeature correlations to classification. By enabling precise model fits and interpretable parameter estimates, causal-model theory helps place the theory-based approach to conceptual representation on equal footing with the well-known similarity-based approaches. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Three Cs in measurement models: Causal indicators, composite indicators, and covariates.

In the last 2 decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that one can classify indicators into 2 categories: effect (reflective) indicators and causal (formative) indicators. We argue that the dichotomous view is too simple. Instead, there are effect indicators and 3 types of variables on which a latent variable depends: causal indicators, composite (formative) indicators, and covariates (the “Three Cs”). Causal indicators have conceptual unity, and their effects on latent variables are structural. Covariates are not concept measures, but are variables to control to avoid bias in estimating the relations between measures and latent variables. Composite (formative) indicators form exact linear combinations of variables that need not share a concept. Their coefficients are weights rather than structural effects, and composites are a matter of convenience. The failure to distinguish the Three Cs has led to confusion and questions, such as, Are causal and formative indicators different names for the same indicator type? Should an equation with causal or formative indicators have an error term? Are the coefficients of causal indicators less stable than effect indicators? Distinguishing between causal and composite indicators and covariates goes a long way toward eliminating this confusion. We emphasize the key role that subject matter expertise plays in making these distinctions. We provide new guidelines for working with these variable types, including identification of models, scaling latent variables, parameter estimation, and validity assessment. A running empirical example on self-perceived health illustrates our major points. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Temporal predictability facilitates causal learning.

[Correction Notice: An erratum for this article was reported in Vol 140(3) of Journal of Experimental Psychology: General (see record 2011-16270-001). Figure 2 (p. 759) contained an error. The corrected figure appears in the correction.] Temporal predictability refers to the regularity or consistency of the time interval separating events. When encountering repeated instances of causes and effects, we also experience multiple cause–effect temporal intervals. Where this interval is constant it becomes possible to predict when the effect will follow from the cause. In contrast, interval variability entails unpredictability. Three experiments investigated the extent to which temporal predictability contributes to the inductive processes of human causal learning. The authors demonstrated that (a) causal relations with fixed temporal intervals are consistently judged as stronger than those with variable temporal intervals, (b) that causal judgments decline as a function of temporal uncertainty, and (c) that this effect remains undiminished with increased learning time. The results therefore clearly indicate that temporal predictability facilitates causal discovery. The authors considered the implications of their findings for various theoretical perspectives, including associative learning theory, the attribution shift hypothesis, and causal structure models. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Interpretational confounding is due to misspecification, not to type of indicator: Comment on Howell, Breivik, and Wilcox (2007).

R. D. Howell, E. Breivik, and J. B. Wilcox (2007; see record 2007-07830-006) have argued that causal (formative) indicators are inherently subject to interpretational confounding. That is, they have argued that using causal (formative) indicators leads the empirical meaning of a latent variable to be other than that assigned to it by a researcher. Their critique of causal (formative) indicators rests on several claims: (a) A latent variable exists apart from the model when there are effect (reflective) indicators but not when there are causal (formative) indicators, (b) causal (formative) indicators need not have the same consequences, (c) causal (formative) indicators are inherently subject to interpretational confounding, and (d) a researcher cannot detect interpretational confounding when using causal (formative) indicators. This article shows that each claim is false. Rather, interpretational confounding is more a problem of structural misspecification of a model combined with an underidentified model that leaves these misspecifications undetected. Interpretational confounding does not occur if the model is correctly specified whether a researcher has causal (formative) or effect (reflective) indicators. It is the validity of a model not the type of indicator that determines the potential for interpretational confounding. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Strengths and weaknesses of the reading level design: A comment on Backman, Mamen, and Ferguson.

In an article on the design of studies of different reading abilities in children, J. E. Backman et al (see record 1985-13169-001) advocated using a combined method of comparing reading-disabled children with younger normal controls who are reading at the same level and comparing reading-disabled children with children of the same chronological age. The present authors argue that this design will produce interpretable results in some circumstances. Negative results in a reading-level comparison and positive results in an age comparison will be ambiguous. It is concluded that causal hypotheses are best tested by longitudinal studies combined with intervention. (13 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Correction to Greville and Buehner (2010).

Reports an error in "Temporal predictability facilitates causal learning" by W. James Greville and Marc J. Buehner (Journal of Experimental Psychology: General, 2010[Nov], Vol 139[4], 756-771). Figure 2 (p. 759) contained an error. The corrected figure appears in the correction. (The following abstract of the original article appeared in record 2010-22538-005.) Temporal predictability refers to the regularity or consistency of the time interval separating events. When encountering repeated instances of causes and effects, we also experience multiple cause–effect temporal intervals. Where this interval is constant it becomes possible to predict when the effect will follow from the cause. In contrast, interval variability entails unpredictability. Three experiments investigated the extent to which temporal predictability contributes to the inductive processes of human causal learning. The authors demonstrated that (a) causal relations with fixed temporal intervals are consistently judged as stronger than those with variable temporal intervals, (b) that causal judgments decline as a function of temporal uncertainty, and (c) that this effect remains undiminished with increased learning time. The results therefore clearly indicate that temporal predictability facilitates causal discovery. The authors considered the implications of their findings for various theoretical perspectives, including associative learning theory, the attribution shift hypothesis, and causal structure models. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Evidence that SMS 201-995 enhances the immunosuppressive effect of FK506

Somatostatin (SS) was originally described as a growth hormone release inhibiting factor synthesised in the hypothalamus. Recently, SS and its receptor (SSTR) have been demonstrated in lymphoid tissues and seem to play a regulatory, largely inhibitory, role in immune responses. The aim of the present study was to check the immunosuppressive effect of a SS derived peptide, the octreotide (SMS 201-995) and to verify whether this molecule acted synergistically with FK506. An immunosuppressive effect of SMS was observed on the proliferation of rat spleen cells induced in vitro, either by polyclonal mitogens such as PHA or by alloantigens. With PHA stimulation, 10(-14) M SMS significantly enhanced the immunosuppressive action of 0.00001 microg/ml FK506. The addition of SMS in MLR (10(-11)-10(-9)M) increased the antiproliferative effect of both 0.0001 microg/ml and 0.00001 microg/ml FK506. In consideration of the extremely low concentration of both drugs that was required to obtain a good immunosuppression in vitro, we verified the association of FK506 and SMS in vivo in an allogeneic skin graft model that used Lewis (Lew) rats as donors and Brown Norway (BN) rats as recipients. BN treated with 0.1 mg/kg FK506 and 0.5-10 microg/kg SMS showed a significant increase in mean skin allograft survival time when compared to either a monotherapy or control group. None of the animals died or showed signs of drug-related toxicity. In conclusion, a combined therapy of SMS and FK506, administered at lower dosages than those that are considered therapeutic, led to an effective immunosuppression without any undesirable side effects.     

On the nature of self-monitoring: Problems with assessment, problems with validity.

We investigated the evidence for a general factor of self-monitoring in six samples (N?=?3,615). The results indicate the presence of two, relatively orthogonal, major factors (General Factors A and B). General Factor A, which presumably accounts for most of the empirical validity of the scale, correlated strongly with measures of the traditional personality dimension of social surgency such as exhibitionism, social potency, and extraversion. General Factor B is a weakened version of an earlier identified Other-Directedness factor, and it correlated positively with shyness and negatively with self-esteem. Additional analyses examined the 18-item revision of the Self-Monitoring Scale in terms of the extent to which it strengthens General Factor A, its relationship to the original version, its factor structure, and correlations with other personality measures. We discuss three flaws in the construct of self-monitoring: its assumption of the bipolarity of social and personal orientations, its assumption of uniformity among those who score high on the Self-Monitoring Scale, and its lack of clarity concerning the role of intentionality in self-presentational processes. We suggest that it is time to move beyond the construct presented by Snyder (1987) toward a more comprehensive investigation of self-presentation and social behavior. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Focusing on the exterior and the interior: Two investigations of the initiation of personal relationships.

Tested the hypothesis that the construct of self-monitoring would identify individuals who characteristically adopt distinctly different orientations when initiating dating relationships. In each of 2 studies, low and high self-monitoring men chose a female partner for a date. In Study 1, attentional differences in the initial information-seeking stage of relationship initiation in an open-field setting were examined with 19 high- and 20 low-scoring Ss on a self-monitoring scale. In Study 2, actual choices of dating partners were examined where one type of desirable attribute in a partner had to be sacrificed in order to obtain another type of desirable attribute. 16 high- and 16 low-scoring Ss on a self-monitoring scale participated. Behavioral and self-report evidence revealed that in both the initial information-gathering stage and the actual choice of whom to date, low self-monitoring Ss paid a greater amount of attention to and placed greater weight on information about interior personal attributes than did high self-monitoring Ss; by contrast, high self-monitoring Ss paid more attention to and put greater weight on exterior physical appearance than did low self-monitoring Ss. (28 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Causal inference and related statistical methods

Statistical approaches for evaluating causal effects and for discovering causal networks are discussed in this paper.A causal relation between two variables is different from an association or correlation between them.An association measurement between two variables and may be changed dramatically from positive to negative by omitting a third variable,which is called Yule-Simpson paradox.We shall discuss how to evaluate the causal effect of a treatment or exposure on an outcome to avoid the phenomena of Yule-Simpson paradox. Surrogates and intermediate variables are often used to reduce measurement costs or duration when measurement of endpoint variables is expensive,inconvenient,infeasible or unobservable in practice.There have been many criteria for surrogates.However,it is possible that for a surrogate satisfying these criteria,a treatment has a positive effect on the surrogate,which in turn has a positive effect on the outcome,but the treatment has a negative effect on the outcome,which is called the surrogate paradox.We shall discuss criteria for surrogates to avoid the phenomena of the surrogate paradox. Causal networks which describe the causal relationships among a large number of variables have been applied to many research fields.It is important to discover structures of causal networks from observed data.We propose a recursive approach for discovering a causal network in which a structural learning of a large network is decomposed recursively into learning of small networks.Further to discover causal relationships,we present an active learning approach in terms of external interventions on some variables.When we focus on the causes of an interest outcome, instead of discovering a whole network,we propose a local learning approach to discover these causes that affect the outcome.     

Overestimating causality: Attributional effects of confirmatory processing.

People may routinely overestimate the strength of a hypothesized cause of an outcome. In 4 experiments, Ss exaggerated the extent to which an outcome resulted from a focal cause. The tendency was attenuated when Ss were prompted to explain the outcome or consider alternative causes before the judgment. Surprisingly, stronger causal inferences were drawn when Ss were highly accountable for their judgments. The results indicate that causal inferences are often mediated by the confirmatory processes that have been delineated in previous hypothesis testing research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Measurement and statistics: An examination of construct validity.

Uses principles of latent trait theory to derive conditions under which mean differences on an observed variable are indicative of mean differences on an underlying construct, focusing on the logistic curve as a model for describing the relation between the observed variable and construct. In this situation, and with normally distributed scores on the construct, a t test comparing groups on the observed variable produces correct inferences at the construct level only if group variances on the construct are homogeneous or the difficulty level of the test equals the mean ability level of the examinees. (27 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Orientations toward personnel selection: Differential reliance on appearance and personality.

In two studies we examined the hypothesis that the psychological construct of self-monitoring would identify people who adopt distinctly different strategies in personnel selection. In both experiments, undergraduates examined information about the physical appearance and personalities of two applicants for a specific job and then decided which applicant should receive a job offer. In Study 1, information about the applicants' physical attractiveness and job-appropriate dispositions was varied. In Study 2, job appropriateness of the applicants' physical appearance and of their personalities were both varied. In each study, high self-monitoring individuals placed greater weight on information about physical appearance than did low self-monitoring individuals. By contrast, low self-monitoring individuals put greater weight on information about personal dispositions than did high self-monitoring individuals. We discuss the implications for understanding personnel selection as well as for decision making in interpersonal contexts. (PsycINFO Database Record (c) 2010 APA, all rights reserved)