Slater M D, Flora J A
Department of Technical Journalism, Colorado State University.
Health Educ Q. 1991 Summer;18(2):221-33. doi: 10.1177/109019819101800207.
This article is concerned with the application of market segmentation techniques in order to improve the planning and implementation of public health education programs. Seven distinctive patterns of health attitudes, social influences, and behaviors are identified using cluster analytic techniques in a sample drawn from four central California cities, and are subjected to construct and predictive validation: The lifestyle clusters predict behaviors including seatbelt use, vitamin C use, and attention to health information. The clusters also predict self-reported improvements in health behavior as measured in a two-year follow-up survey, e.g., eating less salt and losing weight, and self-reported new moderate and new vigorous exercise. Implications of these lifestyle clusters for public health education and intervention planning, and the larger potential of lifestyle clustering techniques in public health efforts, are discussed.
本文关注市场细分技术的应用，以改进公共卫生教育项目的规划与实施。运用聚类分析技术，从加利福尼亚州中部的四个城市抽取样本，识别出七种不同的健康态度、社会影响及行为模式，并进行了结构验证和预测验证：生活方式聚类可预测包括安全带使用、维生素C使用以及对健康信息的关注等行为。这些聚类还能预测在为期两年的随访调查中自我报告的健康行为改善情况，如减少盐的摄入量、减肥，以及自我报告的新的适度和剧烈运动。本文讨论了这些生活方式聚类对公共卫生教育和干预规划的意义，以及生活方式聚类技术在公共卫生工作中的更大潜力。
