BackgroundAttrition is one of the major methodological problems in longitudinal studies. It can deteriorate generalizability of findings if participants who stay in a study differ from those who drop out. The aim of this study was to examine the degree to which attrition leads to biased estimates of means of variables and associations between them.MethodsMothers of 18-month-old children were enrolled in a population-based study in 1993 (N=913) that aimed to examine development in children and their families in the general population. Fifteen years later, 56% of the sample had dropped out. The present study examined predictors of attrition as well as baseline associations between variables among those who stayed and those who dropped out of that study. A Monte Carlo simulation study was also performed.ResultsThose who had dropped out of the study over 15 years had lower educational level at baseline than those who stayed, but they did not differ regarding baseline psychological and relationship variables. Baseline correlations were the same among those who stayed and those who later dropped out. The simulation study showed that estimates of means became biased even at low attrition rates and only weak dependency between attrition and follow-up variables. Estimates of associations between variables became biased only when attrition was dependent on both baseline and follow-up variables. Attrition rate did not affect estimates of associations between variables.ConclusionsLong-term longitudinal studies are valuable for studying associations between risk/protective factors and health outcomes even considering substantial attrition rates.

Objective The authors sought to clarify the structure of the genetic and environmental risk factors for 22 DSM-IV disorders: 12 common axis I disorders and all 10 axis II disorders. Method The authors examined syndromal and subsyndromal axis I diagnoses and five categories reflecting number of endorsed criteria for axis II disorders in 2,111 personally interviewed young adult members of the Norwegian Institute of Public Health Twin Panel. Results Four correlated genetic factors were identified: axis I internalizing, axis II internalizing, axis I externalizing, and axis II externalizing. Factors 1 and 2 and factors 3 and 4 were moderately correlated, supporting the importance of the internalizing-externalizing distinction. Five disorders had substantial loadings on two factors: borderline personality disorder (factors 3 and 4), somatoform disorder (factors 1 and 2), paranoid and dependent personality disorders (factors 2 and 4), and eating disorders (factors 1 and 4). Three correlated environmental factors were identified: axis II disorders, axis I internalizing disorders, and externalizing disorders versus anxiety disorders. Conclusions Common axis I and II psychiatric disorders have a coherent underlying genetic structure that reflects two major dimensions: internalizing versus externalizing, and axis I versus axis II. The underlying structure of environmental influences is quite different. The organization of common psychiatric disorders into coherent groups results largely from genetic, not environmental, factors. These results should be interpreted in the context of unavoidable limitations of current statistical methods applied to this number of diagnostic categories.

A study was conducted to explore (a) the dimensional structure of perceived behavioural control (PBC), (b) the conceptual basis of perceived difficulty items, and (c) how PBC components and instrumental and affective attitudes, respectively, relate to intention and behaviour. The material stemmed from a two-wave study of Norwegian graduate students (N = 227 for the prediction of intention and N = 110 for the prediction of behaviour). Data were analysed using confirmatory factor analysis (CFA) and multiple regression by the application of structural equation modelling (SEM). CFA suggested that PBC could be conceived of as consisting of three separate but interrelated factors (perceived control, perceived confidence and perceived difficulty), or as two separate but interrelated factors representing self-efficacy (measured by perceived difficulty and perceived confidence or by just perceived confidence) and perceived control. However, the perceived difficulty items also overlapped substantially with affective attitude. Perceived confidence was a strong predictor of exercise intention but not of recycling intention. Perceived control, however, was a strong predictor of recycling intention but not exercise intention. Affective attitudes but not instrumental attitudes were identified as substantial predictors of intentions. The findings suggest that at least under some circumstances it may be inadequate to measure PBC by means of perceived difficulty. One possible consequence may be that the role of PBC as a predictor of intention is somewhat overestimated, whereas the role of (affective) attitude may be similarly underestimated.

Context Although both genetic and environmental factors affect risk of individual personality disorders (PDs), we know little of how they contribute to the pattern of comorbidity between the PDs in the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV). Objective To clarify the structure of the genetic and environmental risk factors for the 10 DSM-IV PDs. Design Assessment of PDs at personal interview and multivariate twin modeling with the Mx program. Setting General community. Participants A total of 2794 young adult members of the Norwegian Institute of Public Health Twin Panel. Main Outcome Measure Number of endorsed criteria for the 10 DSM-IV PDs. Results The best-fit multivariate twin model required 3 genetic and 3 individual-specific environmental factors and genetic and individual-specific factors unique to each PD. The first genetic factor had high loadings on PDs from all 3 clusters including paranoid, histrionic, borderline, narcissistic, dependent, and obsessive-compulsive. The second genetic factor had substantial loadings only on borderline and antisocial PD. The third genetic factor had high loadings only on schizoid and avoidant PD. Several PDs had substantial disorder-specific genetic risk factors. The first, second, and third individual-specific environmental factors had high loadings on the cluster B, A, and C PDs, respectively, with 1 exception: obsessive-compulsive PD loaded with cluster B and not cluster C PDs. Conclusions Genetic risk factors for DSM-IV PDs do not reflect the cluster A, B, and C typology. Rather, 1 genetic factor reflects a broad vulnerability to PD pathology and/or negative emotionality. The 2 other genetic factors are more specific and reflect high impulsivity/low agreeableness and introversion. Unexpectedly, the cluster A, B, and C typology is well reflected in the structure of environmental risk factors, suggesting that environmental experiences may be responsible for the tendency of cluster A, B, and C PDs to co-occur.