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N A Gillespie

Publications and source records attributed to N A Gillespie.

3 recordsLinked to original sources

Perceived social support in a large community sample--age and sex differences.

BACKGROUND: The positive health and wellbeing effects of social support have been consistently demonstrated in the literature since the late 1970s. However, a better understanding of the effects of age and sex is required. METHOD: We examined the factor structure and reliability of Kessler's Perceived Social Support (KPSS) measure in a community-based sample that comprised younger and older adult cohorts from the Australian Twin Registry (ATR), totalling 11,389 males and females aged 18-95, of whom 887 were retested 25 months later. RESULTS: Factor analysis consistently identified seven factors: support from spouse, twin, children, parents, relatives, friends and helping support. Internal reliability for the seven dimensions ranged from 0.87 to 0.71 and test-retest reliability ranged from 0.75 to 0.48. Perceived support was only marginally higher in females. Age dependencies were explored. Across the age range, there was a slight decline (more marked in females) in the perceived support from spouse, parent and friend, a slight increase in perceived relative and helping support for males but none for females, a substantial increase in the perceived support from children for males and females and a negligible decline in total KPSS for females against a negligible increase for males. The perceived support from twin remained constant. Females were more likely to have a confidant, although this declined with age whilst increasing with age for males. CONCLUSIONS: Total scores for perceived social support conflate heterogeneous patterns on sub-scales that differ markedly by age and sex. Our paper describes these relationships in detail in a very large Australian sample.

Adolescent↗

Biometrical genetics.

Biometrical genetics is the science concerned with the inheritance of quantitative traits. In this review we discuss how the analytical methods of biometrical genetics are based upon simple Mendelian principles. We demonstrate how the phenotypic covariance between related individuals provides information on the relative importance of genetic and environmental factors influencing that trait, and how factors such as assortative mating, gene-environment correlation and genotype-environment interaction complicate such interpretations. Twin and adoption studies are discussed as well as their assumptions and limitations. Structural equation modeling (SEM) is introduced and we illustrate how this approach may be applied to genetic problems. In particular, we show how SEM can be used to address complicated issues such as analyzing the causes of correlation between traits or determining the direction of causation (DOC) between variables.

Biometry↗

The genetic aetiology of somatic distress.

BACKGROUND: Somatoform disorders such as neurasthenia and chronic fatigue syndrome are characterized by a combination of prolonged mental and physical fatigue. This study aimed to investigate the heritability of somatic distress and determine whether this dimension is aetiologically distinct from measures of depression and anxiety. METHOD: Measures of anxiety, depression, phobic anxiety, somatic distress and sleep difficulty were administered in a self-report questionnaire to a community-based sample of 3469 Australian twin individuals aged 18 to 28 years. Factor analysis using a Promax rotation, produced four factors: depression, phobic anxiety, somatic distress and sleep disturbance. Multivariate and univariate genetic analyses of the raw categorical data scores for depression, phobic anxiety and depression were then analysed in Mx1.47. RESULTS: Univariate genetic analysis revealed that an additive genetic and non-shared environmental (AE) model best explained individual differences in depression and phobic anxiety scores, for male and female twins alike, but could not resolve whether additive genes or shared environment were responsible for significant familial aggregation in somatic distress. However, multivariate genetic analysis showed that an additive genetic and non-shared environment (AE) model best explained the covariation between the three factors. Furthermore, 33 % of the genetic variance in somatic distress was due to specific gene action unrelated to depression or phobic anxiety. In addition, 74% of the individual environmental influence on somatic distress was also unrelated to depression or phobic anxiety. CONCLUSION: These results support previous findings that somatic symptoms are relatively aetiologically distinct both genetically and environmentally from symptoms of anxiety and depression.

Adolescent↗