Self-control: An integrative framework

Research on self-control has flourished within the last two decades, with many researchers trying to answer one of the most fundamental questions regarding human behaviour—how do we successfully regulate desires in the pursuit of long-term goals? While recent research has focused on different strategies to enhance self-control success, we still know very little about how strategies are implemented or where the need for self-control comes from in the first place. Drawing from parallel fields (e.g., emotion regulation, health) and other theories of self-regulation, we propose an integrative framework that describes self-control as a dynamic, multi-stage process that unfolds over time. In this review, we first provide an overview of this framework, which poses three stages of regulation: the identification of the need for self-control, the selection of strategies to regulate temptations, and the implementation of chosen strategies. These regulatory stages are then flexibly monitored over time. We then expand this framework by outlining a series of growth points to guide future research. By bridging across theories and disciplines, the present framework improves our understanding of how self-control unfolds in everyday life.     

The factor structure of the Multiple Affect Adjective Check List-Revised (MAACL-R): Some statistical considerations

In response to Zuckerman's comments on my factor analyses of the MAACL-R, I focus on the statistical issues of the cutoff criterion for factor loadings and the evidence for the discriminant validity of the five-factor solution. Based upon the conclusions I draw in these two areas, I recommend that researchers either (a) use the two factor solution to the MAACL-R represented in the summary scores of Dysphoria and Positive Affect + Sensation Seeking or (b) include all MAACL-R scales in their studies and analyze their data to determine whether it is statistically appropriate to report results from a single scale (A, D, H, PA, or SS) rather than from the summary scores.     

Factor structure of the mobility inventory for agoraphobia: A validational study with australian samples of agoraphobic patients

This study examines the factor structure of the Mobility Inventory for Agoraphobia and attempts to validate the inventory, using an Australian sample of agoraphobic patients, by comparison with other scales. One hundred twentyfour panic disorder with agoraphobia patients were studied. Factor analysis showed that a two-factor solution was the most suitable both when subjects were accompanied (accompanied condition) and when alone (alone condition). Factor I represented public, crowded, or social situations including department stores, supermarkets, restaurants, theaters, and panics and social gatherings. Factor II reflected enclosed or riding situations such as elevators, parking garages, enclosed spaces, and riding in subways or airplanes. These two factors accounted for 46.6% and 44.3% of the variance on the accompanied condition and the alone condition, respectively. The Mobility Inventory was significantly correlated with the Agoraphobia factor of the Fear Questionnaire and the Social Avoidance and Distress scale. These results indicated that the Mobility Inventory is a valid instrument to measure agoraphobic behavior.     

Psychometric properties and factor structure of the Fear Questionnaire phobia subscale items in two normative samples

Normative data for the Fear Questionnaire (Marks & Mathews, 1979), a popular self-report instrument measuring phobic concerns, were collected from both a community and a collegiate sample. The covariation and internal consistency of the blood-injury phobia (BI), social phobia (SO), and agoraphobia (AG) subscales were assessed in each sample, and the factor structure of the items from these three subscales was examined. Results indicated that, in general, community subjects reported more phobic concerns than did collegiate subjects, and females reported greater phobic concerns than did males. Results from confirmatory factor analyses suggest that the three factors of BI, SO, and AG did not emerge from either data set. Follow-up exploratory factor analyses did identify the general factors of blood-injury phobia and agoraphobia. Normative data from the present study are compared to those obtained previously, and directions for future research are provided.     

Testing a stochastic foraging model in an operant simulation: Agreement with qualitative but not quantitative predictions

An operant simulation of foraging through baited and empty patches was studied with 4 pigeons. On a three-key panel, side keys were designated as patches, and successive opportunities to complete 16 fixed-ratio 10 schedules on side keys were defined as encounters with feeders. In a random half of the patches in any session, some of the fixed-ratio 10 schedules yielded reinforcement (baited feeders) and the other schedules yielded nonreinforcement (empty feeders). In the other half of the patches, all feeders were empty. Pigeons could travel between patches at any time by completing a fixed-ratio schedule on the center key. An optimal foraging model was tested in Experiments 1 and 2 by varying center-key travel time and number of baited feeders in baited patches. The ordinal predictions that number of feeders visited in empty patches would increase with travel time and decrease as number of baited feeders increased were supported, but pigeons visited far more feeders in empty patches than the optimal number predicted by the model to maximize energy/time. In Experiment 3, evidence was found to suggest that the number of empty feeders encountered before the first baited feeder in baited patches is an important factor controlling leaving empty patches.     

The many null distributions of person fit indices

This paper deals with the situation of an investigator who has collected the scores ofn persons to a set ofk dichotomous items, and wants to investigate whether the answers of all respondents are compatible with the one parameter logistic test model of Rasch. Contrary to the standard analysis of the Rasch model, where all persons are kept in the analysis and badly fittingitems may be removed, this paper studies the alternative model in which a small minority ofpersons has an answer strategy not described by the Rasch model. Such persons are called anomalous or aberrant. From the response vectors consisting ofk symbols each equal to 0 or 1, it is desired to classify each respondent as either anomalous or as conforming to the model. As this model is probabilistic, such a classification will possibly involve false positives and false negatives. Both for the Rasch model and for other item response models, the literature contains several proposals for a person fit index, which expresses for each individual the plausibility that his/her behavior follows the model. The present paper argues that such indices can only provide a satisfactory solution to the classification problem if their statistical distribution is known under the null hypothesis that all persons answer according to the model. This distribution, however, turns out to be rather different for different values of the person's latent trait value. This value will be called ability parameter, although our results are equally valid for Rasch scales measuring other attributes.As the true ability parameter is unknown, one can only use its estimate in order to obtain an estimated person fit value and an estimated null hypothesis distribution. The paper describes three specifications for the latter: assuming that the true ability equals its estimate, integrating across the ability distribution assumed for the population, and conditioning on the total score, which is in the Rasch model the sufficient statistic for the ability parameter.Classification rules for aberrance will be worked out for each of the three specifications. Depending on test length, item parameters and desired accuracy, they are based on the exact distribution, its Monte Carlo estimate and a new and promising approximation based on the moments of the person fit statistic. Results for the likelihood person fit statistic are given in detail, the methods could also be applied to other fit statistics. A comparison of the three specifications results in the recommendation to condition on the total score, as this avoids some problems of interpretation that affect the other two specifications.The authors express their gratitude to the reviewers and to many colleagues for comments on an earlier version.     

Interpreting canonical correlation analysis through biplots of structure correlations and weights

This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate regression and canonical correlation analysis/redundancy analysis is exploited for producing an optimal biplot that displays a matrix of regression coefficients. This plot can be made from the canonical weights of the predictors and the structure correlations of the criterion variables. An example is used to show how the proposed biplots may be interpreted.     

New lower and upper bounds for communality in factor analysis

We derive several relationships between communalities and the eigenvalues for ap ×p correlation matrix under the usual factor analysis model. For suitable choices ofj, _j (), where _j () is thej-th largest eigenvalue of , provides either a lower or an upper bound to the communalities for some of the variables. We show that for at least one variable, 1 - _p () improves on the use of squared mulitiple correlation coefficient as a lower bound.This research was done while the second author was at Tokyo Institute of Technology.     

Type A behaviour in pre-school children: Interrater reliability, stability over six months and subcomponents

Type A behaviour was measured in 250 boys and 245 girls (ages 3-7) using a Swedish version of Matthews' Youth Test for Health (MYTH). In addition, speech and voice characteristics (speed, loudness, response latency) were measured. Each child was independently rated by two play group leaders and measurements were repeated after a six month interval. Interrater reliability (first session) was 0.76 for both sexes and did not change with the age of the child. Boys obtained significantly (p less than 0.0001) higher scores than girls. Correlations over the six month period were 0.64 and 0.60 (p less than 0.001) for the two possible combinations of different raters and slightly higher (0.75 and 0.68, p less than 0.001) when the same rater was used. Two components of Type A behaviour were identified from a factor analysis of the data: impatience and competitiveness, and they accounted for 57% of the total variance. As for the total scale, boys obtained significantly higher scores than girls on both subscales. Scores on the competitiveness scale increased systematically with age. Speech and voice characteristics correlated significantly with Type A scores (total Type A behaviour: r = 0.50, using different raters, and 0.71, using the same raters, p less than 0.001) and, once again, boys obtained significantly (p less than 0.001) higher scores than girls. The results are in close agreement with the American findings from the original scale. It was concluded that the scale provides a reliable and valid instrument for measuring Type A or Type A-like behaviours in pre-school children.