Galanos A N, Strauss R P, Pieper C F
Duke University Medical Center, Durham, North Carolina.
Int J Aging Hum Dev. 1994;38(4):339-50. doi: 10.2190/62KA-FWN1-6XV5-PR2Q.
This study examined the hypothesis that sociodemographic characteristics such as age, education, race, and gender would be predictive of Multidimensional Health Locus of Control Subscale scores in a population-based sample of 342 community dwelling elderly individuals. Bivariate analysis revealed associations between black race, lower socioeconomic status, and lower education on the Chance and Powerful Others Subscales. While the multivariate analysis revealed no predictors for the Internal Subscale, a higher socioeconomic status, white race, and a higher level of education continued to predict low scores on the Chance Subscale when controlling for all other variables. Scores on the Powerful Others Subscale appeared to be a function of socioeconomic status and gender. Of note, the higher the education level for both men and women, the lower the scores on the Chance and Powerful Others Subscales. This sex by education interaction term reached statistical significance for the Chance Subscale. The results demonstrate the measurable influence of sociodemographic variables on the health beliefs of community dwelling elderly individuals.
在一个由342名社区居住的老年人组成的基于人群的样本中,年龄、教育程度、种族和性别等社会人口学特征将能够预测多维健康控制点子量表得分。双变量分析揭示了黑人种族、较低的社会经济地位以及在机遇和强大他人子量表上较低的教育程度之间的关联。虽然多变量分析未发现内部子量表的预测因素,但在控制所有其他变量时,较高的社会经济地位、白人种族以及较高的教育程度继续预测机遇子量表上的低分。强大他人子量表得分似乎是社会经济地位和性别的函数。值得注意的是,男性和女性的教育水平越高,机遇和强大他人子量表上的得分就越低。这种性别与教育的交互项在机遇子量表上达到了统计学显著性。结果表明社会人口学变量对社区居住老年人的健康信念具有可测量的影响。