Predictors of Self-Management Behaviors in Older Adults with Hypertension.

Advances in Preventive Medicine Pub Date : 2015-01-01 Epub Date: 2015-08-12 DOI:10.1155/2015/960263
Brenda M Douglas, Elizabeth P Howard
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引用次数: 19

Abstract

The purpose of this study was to develop a prediction model of demographic and sociobehavioral characteristics common among older adults with hypertension (HTN) who engage in self-management behavior. A descriptive, correlational predictive design was used to collect data at 14 faith-based and senior citizen organizations in a major urban northeastern city. Participants ranged in age from 63 to 96 with a mean age of 77 (SD 6.9). A 33-item questionnaire was used to gather data on 15 explanatory and 5 outcome variables. Instruments were the Perceived Stress Scale, the Duke Social Support Index, the stage of change for physical activity scale, and the DASH Food Frequency Questionnaire. Correlation and regression analyses were used to test the hypothesis. Results indicate there is a common set of characteristics such as higher stage of change, reading food labels, and higher self-rated health that can predict the older adult's likelihood to engage in hypertension self-management behavior. The significant correlations found in this preliminary study warrant further study and validation. Findings are clinically relevant as knowledge of demographic and sociobehavioral characteristics associated with engagement in self-management behavior enables health care clinicians to support and encourage older adults to improve management of this common, chronic condition.

老年高血压患者自我管理行为的预测因素。
本研究的目的是建立一个参与自我管理行为的老年高血压患者(HTN)的人口学和社会行为特征的预测模型。采用描述性、相关性预测设计对东北某主要城市的14个信仰组织和老年人组织进行数据收集。参与者的年龄从63岁到96岁不等,平均年龄为77岁(SD 6.9)。采用33项问卷收集15个解释变量和5个结果变量的数据。工具为感知压力量表、杜克社会支持指数、体育活动变化阶段量表和DASH食物频率问卷。采用相关分析和回归分析对假设进行检验。结果表明,有一系列共同的特征,如较高的变化阶段、阅读食品标签和较高的自评健康,可以预测老年人参与高血压自我管理行为的可能性。本初步研究中发现的显著相关性值得进一步研究和验证。研究结果具有临床相关性,因为与参与自我管理行为相关的人口统计学和社会行为特征的知识使卫生保健临床医生能够支持和鼓励老年人改善对这种常见慢性疾病的管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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6
审稿时长
15 weeks
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