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迈向有效的健康干预设计:健康信念模型的扩展

Towards an effective health interventions design: an extension of the health belief model.

作者信息

Orji Rita, Vassileva Julita, Mandryk Regan

机构信息

Department of Computer Science, University of Saskatchewan, Canada.

出版信息

Online J Public Health Inform. 2012;4(3). doi: 10.5210/ojphi.v4i3.4321. Epub 2012 Dec 19.

DOI:10.5210/ojphi.v4i3.4321
PMID:23569653
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3615835/
Abstract

INTRODUCTION

The recent years have witnessed a continuous increase in lifestyle related health challenges around the world. As a result, researchers and health practitioners have focused on promoting healthy behavior using various behavior change interventions. The designs of most of these interventions are informed by health behavior models and theories adapted from various disciplines. Several health behavior theories have been used to inform health intervention designs, such as the Theory of Planned Behavior, the Transtheoretical Model, and the Health Belief Model (HBM). However, the Health Belief Model (HBM), developed in the 1950s to investigate why people fail to undertake preventive health measures, remains one of the most widely employed theories of health behavior. However, the effectiveness of this model is limited. The first limitation is the low predictive capacity (R(2) < 0.21 on average) of existing HBM's variables coupled with the small effect size of individual variables. The second is lack of clear rules of combination and relationship between the individual variables. In this paper, we propose a solution that aims at addressing these limitations as follows: (1) we extended the Health Belief Model by introducing four new variables: Self-identity, Perceived Importance, Consideration of Future Consequences, and Concern for Appearance as possible determinants of healthy behavior. (2) We exhaustively explored the relationships/interactions between the HBM variables and their effect size. (3) We tested the validity of both our proposed extended model and the original HBM on healthy eating behavior. Finally, we compared the predictive capacity of the original HBM model and our extended model.

METHODS

To achieve the objective of this paper, we conducted a quantitative study of 576 participants' eating behavior. Data for this study were collected over a period of one year (from August 2011 to August 2012). The questionnaire consisted of validated scales assessing the HBM determinants - perceived benefit, barrier, susceptibility, severity, cue to action, and self-efficacy - using 7-point Likert scale. We also assessed other health determinants such as consideration of future consequences, self-identity, concern for appearance and perceived importance. To analyses our data, we employed factor analysis and Partial Least Square Structural Equation Model (PLS-SEM) to exhaustively explore the interaction/relationship between the determinants and healthy eating behavior. We tested for the validity of both our proposed extended model and the original HBM on healthy eating behavior. Finally, we compared the predictive capacity of the original HBM model and our extended model and investigated possible mediating effects.

RESULTS

The results show that the three newly added determinants are better predictors of healthy behavior. Our extended HBM model lead to approximately 78% increase (from 40 to 71%) in predictive capacity compared to the old model. This shows the suitability of our extended HBM for use in predicting healthy behavior and in informing health intervention design. The results from examining possible relationships between the determinants in our model lead to an interesting discovery of some mediating relationships between the HBM's determinants, therefore, shedding light on some possible combinations of determinants that could be employed by intervention designers to increase the effectiveness of their design.

CONCLUSION

Consideration of future consequences, self-identity, concern for appearance, perceived importance, self-efficacy, perceived susceptibility are significant determinants of healthy eating behavior that can be manipulated by healthy eating intervention design. Most importantly, the result from our model established the existence of some mediating relationships among the determinants. The knowledge of both the direct and indirect relationships sheds some light on the possible combination rules.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee49/3615835/554a52822ccd/ojphi-04-27f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee49/3615835/af2e77f33ed4/ojphi-04-27f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee49/3615835/64c9816c476e/ojphi-04-27f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee49/3615835/554a52822ccd/ojphi-04-27f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee49/3615835/af2e77f33ed4/ojphi-04-27f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee49/3615835/64c9816c476e/ojphi-04-27f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee49/3615835/554a52822ccd/ojphi-04-27f3.jpg
摘要

引言

近年来,全球范围内与生活方式相关的健康挑战持续增加。因此,研究人员和健康从业者致力于通过各种行为改变干预措施来促进健康行为。这些干预措施大多是根据从不同学科改编而来的健康行为模型和理论设计的。几种健康行为理论已被用于指导健康干预设计,如计划行为理论、跨理论模型和健康信念模型(HBM)。然而,健康信念模型(HBM)是在20世纪50年代为研究人们为何不采取预防性健康措施而开发的,至今仍是应用最广泛的健康行为理论之一。然而,该模型的有效性有限。第一个局限性是现有健康信念模型变量的预测能力较低(平均R²<0.21),且单个变量的效应量较小。第二个局限性是各个变量之间缺乏明确的组合规则和关系。在本文中,我们提出了一个旨在解决这些局限性的方案:(1)我们通过引入四个新变量扩展了健康信念模型,这四个新变量分别是自我认同、感知重要性、对未来后果的考虑以及对外表的关注,它们可能是健康行为的决定因素。(2)我们详尽地探究了健康信念模型变量之间的关系/相互作用及其效应量。(3)我们测试了我们提出的扩展模型和原始健康信念模型在健康饮食行为方面的有效性。最后,我们比较了原始健康信念模型和我们扩展模型的预测能力。

方法

为实现本文的目标,我们对576名参与者的饮食行为进行了定量研究。本研究的数据收集历时一年(从2011年8月至2012年8月)。问卷由经过验证的量表组成,使用7点李克特量表评估健康信念模型的决定因素——感知益处、障碍、易感性、严重性、行动提示和自我效能感。我们还评估了其他健康决定因素,如对未来后果的考虑、自我认同、对外表的关注和感知重要性。为分析我们的数据,我们采用因子分析和偏最小二乘结构方程模型(PLS - SEM)来详尽探究这些决定因素与健康饮食行为之间的相互作用/关系。我们测试了我们提出的扩展模型和原始健康信念模型在健康饮食行为方面的有效性。最后,我们比较了原始健康信念模型和我们扩展模型的预测能力,并研究了可能的中介效应。

结果

结果表明,新添加的三个决定因素是健康行为的更好预测指标。与旧模型相比,我们扩展后的健康信念模型的预测能力提高了约78%(从40%提高到71%)。这表明我们扩展后的健康信念模型适用于预测健康行为并为健康干预设计提供参考。对我们模型中决定因素之间可能关系的研究结果带来了一个有趣发现,即健康信念模型的决定因素之间存在一些中介关系,因此,为干预设计者提供了一些可能的决定因素组合,可用于提高其设计的有效性。

结论

对未来后果的考虑、自我认同、对外表的关注、感知重要性、自我效能感、感知易感性是健康饮食行为的重要决定因素,可通过健康饮食干预设计加以调控。最重要的是,我们模型的结果证实了决定因素之间存在一些中介关系。直接和间接关系的知识为可能的组合规则提供了一些启示。

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