Oliffe John L, Black Nick, Yiu Jeffrey, Flannigan Ryan K, McCreary Donald R, Goldenberg S Larry
School of Nursing, Faculty of Applied Science, University of British Columbia, Vancouver, BC, Canada.
Department of Nursing, University of Melbourne, Melbourne, Australia.
J Med Internet Res. 2020 May 15;22(5):e16174. doi: 10.2196/16174.
Although evaluation studies confirm the strong potential of men's electronic health (eHealth) programs, there have been calls to more fully understand acceptability, engagement, and behavior change to guide future work. Relatedly, mapping of behavior changes using health promotion theories including the transtheoretical model (or stages of change) has been recommended to build a translatable empirical base to advance design and evaluation considerations for men's eHealth programs.
This study aimed to use a benchmark sample as a reference group to map the recent and intended health behavior changes in Canadian men who use the Don't Change Much (DCM) eHealth program. The hypothesis being tested was that increased exposure to DCM would be positively associated with men's recent and intended health behavior changes.
DCM users (n=863) were sampled for demographic data and self-reported recent and intended health behavior changes. Respondents also reported their usage (frequency and duration) for each of the 3 DCM components (web, newsletter, and social media) and were allocated to limited exposure (257/863, 29.8%), low exposure (431/863, 49.9%), and high exposure (175/863, 20.3%) subgroups. A benchmark sample (n=2000), comprising respondents who had not accessed DCM provided a reference group. Bivariate analysis of recent and intended health behavior changes and DCM exposure levels were used to compute the strength of association between the independent variables (exposure levels) and the 10 categorical dependent variables (recent and intended health behavior changes). Binary logistic regression models were computed for each of the 10 recent and intended health behavior changes. Linear regression was used to model the association between the number of recent and intended changes and the level of exposure to DCM.
Compared with the benchmark reference group, DCM high-exposure respondents had significantly increased odds for 9 of the 10 health behavior changes, with the largest effect size observed for Changed diet or Improved eating habits (odds ratio [OR] 5.628, 95% CI 3.932-8.055). High-exposure respondents also had significantly increased odds for 9 intended health changes, with the largest effect sizes observed for Reduce stress level (OR 4.282, 95% CI 3.086-5.941). Moderate effect size (goodness of fit) was observed for increased total number of recent (F=25.52; P.001; adjusted R=.093) and intended health behavior changes (F=36.30; P.001; adjusted R=.129) among high-exposure respondents.
DCM respondents contrasted the predominately precontemplative benchmark sample mapping across the contemplative, preparation, and action stages of the transtheoretical health behavior change model. Almost 10% of variation in the recent and 13% of variation in the intended health behavior changes can be explained by DCM exposure and demographic factors, indicating the acceptability of this men's eHealth resource.
尽管评估研究证实了男性电子健康（eHealth）项目的巨大潜力，但仍有人呼吁更全面地了解其可接受性、参与度和行为改变，以指导未来的工作。相关地，有人建议使用包括跨理论模型（或改变阶段）在内的健康促进理论来描绘行为改变，以建立一个可转化的实证基础，推进男性eHealth项目的设计和评估考量。
本研究旨在使用一个基准样本作为参照组，描绘使用“变化不大”（DCM）eHealth项目的加拿大男性近期和预期的健康行为改变。所检验的假设是，增加对DCM的接触将与男性近期和预期的健康行为改变呈正相关。
对DCM用户（n = 863）进行抽样，收集人口统计学数据以及自我报告的近期和预期的健康行为改变。受访者还报告了他们对DCM三个组成部分（网络、时事通讯和社交媒体）各自的使用情况（频率和时长），并被分配到有限接触组（257/863，29.8%）、低接触组（431/863，49.9%）和高接触组（175/863，20.3%）亚组。一个由未使用DCM的受访者组成的基准样本（n = 2000）提供了一个参照组。对近期和预期的健康行为改变与DCM接触水平进行双变量分析，以计算自变量（接触水平）与10个分类因变量（近期和预期的健康行为改变）之间的关联强度。针对10种近期和预期的健康行为改变分别计算二元逻辑回归模型。使用线性回归对近期和预期改变的数量与DCM接触水平之间的关联进行建模。
与基准参照组相比，DCM高接触组受访者在10种健康行为改变中的9种上显著增加了几率，在“改变饮食或改善饮食习惯”方面观察到最大效应量（优势比[OR] 5.628，95%置信区间3.932 - 8.055）。高接触组受访者在9种预期健康改变方面也显著增加了几率，在“降低压力水平”方面观察到最大效应量（OR 4.282，95%置信区间3.086 - 5.941）。在高接触组受访者中，观察到近期（F = 25.52；P <.001；调整后R =.093）和预期健康行为改变总数增加的中等效应量（拟合优度）（F = 36.30；P <.001；调整后R =.129）。
DCM受访者与跨理论健康行为改变模型中沉思、准备和行动阶段主要处于前沉思阶段的基准样本形成对比。近期健康行为改变中近10%的变异以及预期健康行为改变中13%的变异可由DCM接触和人口统计学因素解释，表明这种男性eHealth资源的可接受性。
