An alternative multi‐language structure for personality attributes

A scientific taxonomy of human personality attributes should optimally be based on studies from multiple languages and cultures. Study 1 demonstrates convergence between seven‐factor structures found in previous studies of Filipino and Hebrew languages. Study 2 shows that this ‘Multi‐Language Seven’ (ML7) factor model overlaps partially with the Big Five model, but includes four rather than three affective–interpersonal factors, replicates in American English lexical data nearly as well as the Big Five, and has close correspondences to the structure upon which two Italian lexical studies have converged. Correlates were used to clarify interpretation of ML7 factors labelled Gregariousness, Self‐Assurance, Even Temper ‘versus Temperamentalness’, Concern for Others, Conscientiousness, Originality/Virtuosity, and Negative Valence ‘or Social Unacceptability’. These studies indicate the viability of a lexically derived ‘etic’ alternative to the Big Five. Copyright © 2003 John Wiley & Sons, Ltd.     

Perceptions of Training-Related Factors and Personal Variables as Predictors of Transfer Implementation Intentions

A number of factors influence the outcomes of computer skills training and the likelihood of successful transfer. The first empirical test of a conceptual model of training transfer sought to explain how trainees' perceptions of various in-training transfer-enhancing activities such as overlearning, fidelity, stimulus variability, principles-meaningfulness, self-management activities, relapse prevention, and goal setting would predict the self-efficacy and implementation intentions (rather than actual transfer outcomes) of computer skills trainees. As expected, posttraining self-efficacy and transfer enhancing activities both predicted transfer implementation intentions. Pretraining self-efficacy also significantly predicted posttraining self-efficacy, trainees' level of learning during training and transfer enhancing activities, providing support for the conceptual model of training transfer.     

Social networks and partner stress as predictors of adherence to medication, rehabilitation attendance, and quality of life following acute coronary syndrome.

OBJECTIVE: This study examined whether social network size and partner stress predicted medication adherence, cardiac rehabilitation attendance, and quality of life 12 months following hospitalization for an acute coronary syndrome (ACS). DESIGN: ACS patients (N = 193, M age = 60.6 years, SD = 11.4 years, 23% female) were recruited shortly following admission to 4 local hospitals. A prospective design was employed with follow-up data collected 12 months following hospital admission. MAIN OUTCOME MEASURES: Data were gathered on social network size and partner stress. The main outcomes assessed at 12 months were medication adherence, cardiac rehabilitation attendance, and quality of life (Short Form 36). RESULTS: Partner stress predicted medication nonadherence, odds ratio: 2.89, (95% CI = 1.21, 6.95). ACS patients with large social networks were more likely to attend rehabilitation, odds ratio: 3.42, (95% CI = 1.42, 8.25). Analyses were adjusted for age, gender, clinical risk scores, readmission/recurrence, and negative affectivity. Both partner stress and smaller social network size were associated with poorer quality of life. CONCLUSION: Social network size and partner stress may partly exert their influence on coronary heart disease morbidity and mortality through recovery behaviors and maintenance of quality of life.     

SSRAT: The processing of rating scales for the determination of two-dimensional sociometric status

SSRAT is an MS-DOS computer program for two-dimensional sociometric status determination with rating scales. It classifies members of a population into five sociometric status groups, using 3-, 5-, 7-, or 9-point ratings in matrices of assessors and assessed. The processing of rating scales instead of nominations offers several advantages, including increased variability and reliability of the resulting scores. SSRAT is built on the null hypothesis of conditional random attribution of ratings, according to the particular probability distribution of an assessor. Output is available in the form of an ASCII SPSS data file for further statistical processing. Recent studies show that SSRAT, in comparison with nomination methods, (1) is superior in determining popular persons while it detects rejected persons as well, and (2) probably yields classifications that have a higher temporal stability.     

A study of the near-miss involving Weber’s law and pure-tone intensity discrimination

A study of pure-tone intensity discrimination is presented in which amplitude changes are detected in 1000 Hz tone bursts 15–20 msec in duration. The masking function (log detectable increment vs log background intensity) is found to have a slope of 9/10 when calculations are carried out via energy measurements. This near-miss to Weber’s law is in agreement with other data reported in the literature. The masking slope proves to be essentially independent of stimulus duration between 15 msec and 1.5 sec. Our stable slope parameter is interpreted as a detectability restriction generated by “mass-flow” phenomena in the auditory channel. These phenomena are thought to be similar to the fluctuations accompanying a noisy or turbulent stream of events. Pure-tone intensity discrimination is then analyzed as a special case of energy detection.