洞察尼日利亚哈科特港 2 型糖尿病护理的社会人口影响因素以及数字健康推广的机遇:定量研究。

Q2 Medicine
JMIR Diabetes Pub Date : 2024-08-21 DOI:10.2196/56756
Oritsetimeyin Arueyingho, Jonah Sydney Aprioku, Paul Marshall, Aisling Ann O'Kane
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引用次数: 0

摘要

背景:尼日利亚人口中有相当大比例的人患有 2 型糖尿病(T2D),其中相当一部分患者还伴有并发症。尽管由于不良饮食和运动习惯等因素,2 型糖尿病在尼日利亚的发病率越来越高,但关于其在哈科特港等大城市的发病率以及社会人口因素对当前自我护理和利用技术合作护理 2 型糖尿病方法的影响,却没有足够可靠的数据。这一点,再加上针对 T2D 护理的数字健康干预措施严重缺乏,是我们开展这项研究的主要动机:本研究旨在:(1) 探索 T2D 患者的社会人口学特征,了解该特征如何直接影响他们的护理工作;(2) 准确了解协作护理实践,重点关注 T2D 护理工作中的细微差别;(3) 根据目前对技术使用和 T2D 护理工作的了解,确定改进数字医疗技术应用的机会:我们设计了与研究目标相一致的调查问卷,通过 WhatsApp(Meta Platforms, Inc)和面对面互动获取定量数据。社交媒体活动旨在接触难以接触到的受众,这为通过 WhatsApp 发送问卷提供了便利,同时也让我们能够探索其作为数据收集工具的可行性。与此同时,我们还亲自分发了调查问卷。我们共收集到 110 份回复:其中 83 份(75.5%)来自现场发放,27 份(24.5%)来自 WhatsApp。数据分析使用 SPSS Premium(29 版;IBM 公司)和 JASP(0.16.4 版;阿姆斯特丹大学)软件的描述性和推论性统计方法进行。这种双重方法确保了我们的研究能够收集和分析全面的数据:针对我们的研究目标,研究结果被分为三组。我们发现,与女性相比,患有 T2D 的男性年龄明显较大(平均 61 岁),家庭收入较高,学历普遍较高(P=.03)。性别与到医院就诊的频率(P=.60)或到药房就诊的频率(P=.48)之间没有统计学意义上的明显关系,文化差异也不会影响疾病的发病率。在管理方法方面,75.5%(83/110)的人依靠处方药;60%(66/110)的人依靠饮食调节;35.5%(39/110)和 20%(22/110)的人依靠传统药物和精神疗法。大多数参与者(82/110,74.5%)不熟悉糖尿病护理技术,使用技术的参与者中有 89.2%(98/110)只熟悉血糖仪。最后,与数字方式相比,参与者更愿意亲自寻求健康信息(96/110,87.3%):通过确定社会人口因素对糖尿病护理和健康或信息寻求行为的影响,我们能够识别出促进数字健康技术应用的特定环境机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Insights Into Sociodemographic Influences on Type 2 Diabetes Care and Opportunities for Digital Health Promotion in Port Harcourt, Nigeria: Quantitative Study.

Background: A significant percentage of the Nigerian population has type 2 diabetes (T2D), and a notable portion of these patients also live with comorbidities. Despite its increasing prevalence in Nigeria due to factors such as poor eating and exercise habits, there are insufficient reliable data on its incidence in major cities such as Port Harcourt, as well as on the influence of sociodemographic factors on current self-care and collaborative T2D care approaches using technology. This, coupled with a significant lack of context-specific digital health interventions for T2D care, is our major motivation for the study.

Objective: This study aims to (1) explore the sociodemographic profile of people with T2D and understand how it directly influences their care; (2) generate an accurate understanding of collaborative care practices, with a focus on nuances in the contextual provision of T2D care; and (3) identify opportunities for improving the adoption of digital health technologies based on the current understanding of technology use and T2D care.

Methods: We designed questionnaires aligned with the study's objectives to obtain quantitative data, using both WhatsApp (Meta Platforms, Inc) and in-person interactions. A social media campaign aimed at reaching a hard-to-reach audience facilitated questionnaire delivery via WhatsApp, also allowing us to explore its feasibility as a data collection tool. In parallel, we distributed surveys in person. We collected 110 responses in total: 83 (75.5%) from in-person distributions and 27 (24.5%) from the WhatsApp approach. Data analysis was conducted using descriptive and inferential statistical methods on SPSS Premium (version 29; IBM Corp) and JASP (version 0.16.4; University of Amsterdam) software. This dual approach ensured comprehensive data collection and analysis for our study.

Results: Results were categorized into 3 groups to address our research objectives. We found that men with T2D were significantly older (mean 61 y), had higher household incomes, and generally held higher academic degrees compared to women (P=.03). No statistically significant relationship was found between gender and the frequency of hospital visits (P=.60) or pharmacy visits (P=.48), and cultural differences did not influence disease incidence. Regarding management approaches, 75.5% (83/110) relied on prescribed medications; 60% (66/110) on dietary modifications; and 35.5% (39/110) and 20% (22/110) on traditional medicines and spirituality, respectively. Most participants (82/110, 74.5%) were unfamiliar with diabetes care technologies, and 89.2% (98/110) of those using technology were only familiar with glucometers. Finally, participants preferred seeking health information in person (96/110, 87.3%) over digital means.

Conclusions: By identifying the influence of sociodemographic factors on diabetes care and health or information seeking behaviors, we were able to identify context-specific opportunities for enhancing the adoption of digital health technologies.

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来源期刊
JMIR Diabetes
JMIR Diabetes Computer Science-Computer Science Applications
CiteScore
4.00
自引率
0.00%
发文量
35
审稿时长
16 weeks
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