Cross-sectional studies of attitude-behavior relationships are vulnerable to the inflation of correlations by common method variance (CMV). Here, a model is presented that allows partial correlation analysis to adjust the observed correlations for CMV contamination and determine if conclusions about the statistical and practical significance of a predictor have been influenced by the presence of CMV. This method also suggests procedures for designing questionnaires to increase the precision of this adjustment.

This study examined the relationships of self-reported adoption of 12 seismic hazard adjustments (pre-impact actions to reduce danger to persons and property) with respondents' demographic characteristics, perceived risk, perceived hazard knowledge, perceived protection responsibility, and perceived attributes of the hazard adjustments. Consistent with theoretical predictions, perceived attributes of the hazard adjustments differentiated among the adjustments and had stronger correlations with adoption than any of the other predictors. These results identify the adjustments and attributes that emergency managers should address to have the greatest impact on improving household adjustment to earthquake hazard.

The commonly used form of r wg. (J) can display irregular behavior, so four variants of this index were examined. An alternative index, r* wg. J, is recommended. This index is an inverse linear function of the ratio of the average obtained variance to the variance of uniformly distributed random error. r* wg.Jis superficially similar to Cronbach’s α, but careful examination confirms that r* wg.Jis an index of agreement, not reliability. Based on an examination of the small-sample behavior of r wgand r* wg.J, sample sizes of 10 or more raters are recommended.

ObjectiveTo study the social determinants and cardiovascular risk factors for multimorbidity and the acquisition sequence of multimorbidity.DesignLongitudinal study based on anonymised primary care data.SettingGeneral practices in an urban multiethnic borough in London, UK.Participants332 353 patients aged ≥18 years.Main outcome measuresClinical and sociodemographic characteristics of patients with multimorbidity, defined as ≥3 of 12 long-term conditions (LTCs) selected according to high predicted healthcare use. Multilevel logistic regression was used to model social determinants and cardiovascular risk factors. Alluvial plots were constructed to illustrate multimorbidity acquisition sequences according to age, ethnicity and social deprivation.Results5597 (1.7%) patients had ≥3 selected LTCs, the ‘multimorbidity cohort’. The the most common LTCs were diabetes (63.0%) and chronic pain (CP) (42.8%). Social deprivation and ethnicity were independent determinants of multimorbidity: most compared with the least deprived quintile (adjusted OR (AOR) 1.56 (95% CI 1.41 to 1.72)); South Asian compared with white ethnicity (AOR 1.44 (95% CI 1.29 to 1.61)); and black compared with white ethnicity (AOR 0.86 (95% CI 0.80 to 0.92)). The included cardiovascular risk factors were relatively strong determinants of multimorbidity: hypertension (AOR 5.05 (95% CI 4.69 to 5.44)), moderate obesity (AOR 3.41 (95% CI 3.21 to 3.63)) and smoking (AOR 2.30 (95% CI 2.16 to 2.45)). The most common initial onset conditions were diabetes and depression; diabetes particularly in older and black ethnic groups; and depression particularly in younger, more deprived and white ethnicity groups. CP was less common as an initial condition.ConclusionOur findings confirm the importance of age, social deprivation and ethnicity as determinants of multimorbidity. Smoking, obesity and hypertension as cardiovascular risk factors were stronger determinants of multimorbidity than deprivation or ethnicity. The acquisition sequence of multimorbidity is patterned by sociodemographic determinants. Understanding onset conditions of multimorbidity and cardiovascular cardiovascular risk factors may lead to the development of interventions to slow the progression of multimorbidity.

This study extends previous work reviewing the cohesion-performance relationship by using meta-analytic techniques to assess the effects of level of analysis and task interdependence on the cohesion-performance relationship. A total of 51 effect sizesfmrom 46 empirical studies were obtainedfor the meta-analytic integration. Results suggest that level of analysis and task interdependence moderate the cohesion-performance relationship. Implications of the findingsforfuture research on group cohesion and performance are discussed