Nutrition and Health Program, CSIRO Health & Biosecurity, Adelaide, Australia.
The Australian eHealth Research Center, CSIRO Health & Biosecurity, Sydney, Australia.
JMIR Mhealth Uhealth. 2020 Apr 17;8(4):e14726. doi: 10.2196/14726.
Large-scale initiatives to improve diet quality through increased vegetable consumption have had small to moderate success. Digital technologies have features that are appealing for health-related behavior change interventions.
This study aimed to describe the implementation and evaluation of a mobile phone app called VegEze, which aims to increase vegetable intake among Australian adults.
To capture the impact of this app in a real-world setting, the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework was utilized. An uncontrolled, quantitative cohort study was conducted, with evaluations after 21 and 90 days. The app was available in the Apple App Store and was accompanied by television, radio, and social media promotion. Evaluation surveys were embedded into the app using ResearchKit. The primary outcomes were vegetable intake (servings per day) and vegetable variety (types per day). Psychological variables (attitudes, intentions, self-efficacy, and action planning) and app usage were also assessed. Descriptive statistics and multiple linear regression were used to describe the impact of the app on vegetable intake and to determine the characteristics associated with the increased intake.
Data were available from 5062 participants who completed the baseline survey; 1224 participants completed the 21-day survey, and 273 completed the 90-day survey. The participants resided across Australia and were mostly women (4265/5062, 84.3%) with a mean age of 48.2 years (SD 14.1). The mean increase in intake was 0.48 servings, from 3.06 servings at baseline to 3.54 servings at the end of the 21-day challenge (t=8.71; P<.001). The variety of vegetables consumed also increased by 0.35 types per day (t=9.59; P<.001). No changes in intake and variety were found from day 21 to the 90-day follow-up. Participants with the highest app usage increased their vegetable intake by 0.63 (SD 2.02) servings per day compared with 0.32 (SD 1.69) servings per day for those with the lowest app usage. On the basis of multiple linear regression, gender; age; BMI; psychological variables of self-efficacy, attitudes, intentions, and action planning specific to vegetable intake; baseline vegetable intake; and active days of app usage accounted for 23.3% of the variance associated with the change in intake (F=42.09; P<.001). Baseline vegetable intake was the strongest predictor of change in intake (beta=-.495; P<.001), with lower baseline intake associated with a greater change in intake. Self-efficacy (beta=.116; P<.001), action planning (beta=.066; P=.02), BMI (beta=.070; P=.01), and app usage (beta=.081; P=.002) were all significant predictors of the change in intake.
The VegEze app was able to increase intake by half a serving in a large sample of Australian adults. Testing the app in a real-world setting and embedding the consent process allowed for greater reach and an efficient, robust evaluation. Further work to improve engagement is warranted.
通过增加蔬菜摄入量来改善饮食质量的大规模举措收效甚微。数字技术具有吸引健康相关行为改变干预的特点。
本研究旨在描述一种名为 VegEze 的手机应用程序的实施和评估，该应用程序旨在增加澳大利亚成年人的蔬菜摄入量。
为了在真实环境中捕捉该应用程序的影响，利用了 Reach、Effectiveness、Adoption、Implementation 和 Maintenance 框架。进行了一项无对照、定量的队列研究，在 21 天和 90 天后进行评估。该应用程序可在 Apple App Store 中使用，并辅以电视、广播和社交媒体宣传。使用 ResearchKit 在应用程序中嵌入评估调查。主要结果是蔬菜摄入量（份/天）和蔬菜种类（每天的类型）。还评估了心理变量（态度、意图、自我效能感和行动计划）和应用程序使用情况。使用描述性统计和多元线性回归来描述该应用程序对蔬菜摄入量的影响，并确定与摄入量增加相关的特征。
共有 5062 名参与者完成了基线调查，其中 5062 名完成了基线调查；1224 名参与者完成了 21 天调查，273 名参与者完成了 90 天调查。参与者分布在澳大利亚各地，大多数是女性（4265/5062，84.3%），平均年龄为 48.2 岁（SD 14.1）。摄入量的平均增加量为 0.48 份，从基线时的 3.06 份增加到 21 天挑战结束时的 3.54 份（t=8.71；P<.001）。每天消耗的蔬菜种类也增加了 0.35 种（t=9.59；P<.001）。从第 21 天到 90 天的随访，摄入量和种类均无变化。与使用最少应用程序的参与者相比，使用最多应用程序的参与者每天增加 0.63 份（SD 2.02）蔬菜摄入量，而每天增加 0.32 份（SD 1.69）蔬菜摄入量。基于多元线性回归，性别；年龄；BMI；自我效能感、态度、意图和特定于蔬菜摄入量的行动计划等心理变量；基线蔬菜摄入量；以及应用程序使用的活跃天数解释了与摄入量变化相关的 23.3%的方差（F=42.09；P<.001）。基线蔬菜摄入量是摄入量变化的最强预测因素（β=-.495；P<.001），较低的基线摄入量与摄入量的较大变化相关。自我效能感（β=.116；P<.001）、行动计划（β=.066；P=.02）、BMI（β=.070；P=.01）和应用程序使用（β=.081；P=.002）都是摄入量变化的显著预测因素。
VegEze 应用程序能够在澳大利亚大量成年人中增加半份的摄入量。在真实环境中测试该应用程序并嵌入同意过程，实现了更大的覆盖范围和高效、强大的评估。需要进一步改进参与度。
