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基于图像的膳食评估依从性的定制提示:混合方法研究。

Tailored Prompting to Improve Adherence to Image-Based Dietary Assessment: Mixed Methods Study.

机构信息

Department of Medicine, University of Otago, Wellington, New Zealand.

Biostatistics Group, University of Otago, Wellington, New Zealand.

出版信息

JMIR Mhealth Uhealth. 2024 Apr 15;12:e52074. doi: 10.2196/52074.

DOI:10.2196/52074
PMID:38623738
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11034420/
Abstract

BACKGROUND

Accurately assessing an individual's diet is vital in the management of personal nutrition and in the study of the effect of diet on health. Despite its importance, the tools available for dietary assessment remain either too imprecise, expensive, or burdensome for clinical or research use. Image-based methods offer a potential new tool to improve the reliability and accessibility of dietary assessment. Though promising, image-based methods are sensitive to adherence, as images cannot be captured from meals that have already been consumed. Adherence to image-based methods may be improved with appropriately timed prompting via text message.

OBJECTIVE

This study aimed to quantitatively examine the effect of prompt timing on adherence to an image-based dietary record and qualitatively explore the participant experience of dietary assessment in order to inform the design of a novel image-based dietary assessment tool.

METHODS

This study used a randomized crossover design to examine the intraindividual effect of 3 prompt settings on the number of images captured in an image-based dietary record. The prompt settings were control, where no prompts were sent; standard, where prompts were sent at 7:15 AM, 11:15 AM, and 5:15 PM for every participant; and tailored, where prompt timing was tailored to habitual meal times for each participant. Participants completed a text-based dietary record at baseline to determine the timing of tailored prompts. Participants were randomized to 1 of 6 study sequences, each with a unique order of the 3 prompt settings, with each 3-day image-based dietary record separated by a washout period of at least 7 days. The qualitative component comprised semistructured interviews and questionnaires exploring the experience of dietary assessment.

RESULTS

A total of 37 people were recruited, and 30 participants (11 male, 19 female; mean age 30, SD 10.8 years), completed all image-based dietary records. The image rate increased by 0.83 images per day in the standard setting compared to control (P=.23) and increased by 1.78 images per day in the tailored setting compared to control (P≤.001). We found that 13/21 (62%) of participants preferred to use the image-based dietary record versus the text-based dietary record but reported method-specific challenges with each method, particularly the inability to record via an image after a meal had been consumed.

CONCLUSIONS

Tailored prompting improves adherence to image-based dietary assessment. Future image-based dietary assessment tools should use tailored prompting and offer both image-based and written input options to improve record completeness.

摘要

背景

准确评估个体的饮食对于个人营养管理和研究饮食对健康的影响至关重要。尽管其重要性不言而喻,但现有的饮食评估工具要么不够精确,要么过于昂贵或繁琐,不适合临床或研究使用。基于图像的方法提供了一种提高饮食评估可靠性和可及性的潜在新工具。尽管很有前景,但基于图像的方法容易受到依从性的影响,因为图像无法从已经食用的餐食中获取。通过短信适时提示可以提高对基于图像的方法的依从性。

目的

本研究旨在定量研究提示时间对基于图像的饮食记录依从性的影响,并定性探讨参与者的饮食评估体验,以为新型基于图像的饮食评估工具的设计提供信息。

方法

本研究采用随机交叉设计,检查 3 种提示设置对基于图像的饮食记录中拍摄图像数量的个体内影响。提示设置为对照组,不发送提示;标准组,为每位参与者在上午 7:15、上午 11:15 和下午 5:15 发送提示;定制组,根据每位参与者的习惯性用餐时间定制提示时间。参与者在基线时完成基于文本的饮食记录,以确定定制提示的时间。参与者随机分配到 6 种研究序列中的 1 种,每种序列都有 3 种提示设置的独特顺序,每个为期 3 天的基于图像的饮食记录之间间隔至少 7 天的洗脱期。定性部分包括半结构化访谈和问卷调查,以探索饮食评估体验。

结果

共招募了 37 人,其中 30 人(11 名男性,19 名女性;平均年龄 30 岁,标准差 10.8 岁)完成了所有基于图像的饮食记录。与对照组相比,标准设置下每天的图像数增加了 0.83 张(P=.23),与对照组相比,定制设置下每天的图像数增加了 1.78 张(P≤.001)。我们发现,21 名参与者中有 13 名(62%)更喜欢使用基于图像的饮食记录,而不是基于文本的饮食记录,但他们报告说每种方法都有特定的方法挑战,特别是在用餐结束后无法通过图像记录。

结论

定制提示可提高基于图像的饮食评估的依从性。未来的基于图像的饮食评估工具应使用定制提示,并提供基于图像和书面输入选项,以提高记录的完整性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06f/11034420/7e9e1ae5cf3a/mhealth-v12-e52074-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06f/11034420/b5265463c6b4/mhealth-v12-e52074-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06f/11034420/b33555b256ca/mhealth-v12-e52074-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06f/11034420/7e9e1ae5cf3a/mhealth-v12-e52074-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06f/11034420/b5265463c6b4/mhealth-v12-e52074-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06f/11034420/b33555b256ca/mhealth-v12-e52074-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06f/11034420/7e9e1ae5cf3a/mhealth-v12-e52074-g003.jpg

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