评估印度人口的辅助技术需求、未满足的需求、障碍和差距:大型流行病学调查方案。

IF 1.9 Q3 REHABILITATION
Frontiers in rehabilitation sciences Pub Date : 2025-09-15 eCollection Date: 2025-01-01 DOI:10.3389/fresc.2025.1650693
Ashoo Grover, Hitesh K Sharma, Ravindra M Pandey, Ruchir Malik, Salaj Rana, Manisha Panda, Geeta Rani, Sunanda Deb, Shubhendu Singh, Akash, Daanish, Anjali Bajaj, Rupinder S Dhaliwal, Ravinder Singh
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引用次数: 0

摘要

背景:尽管辅助技术(AT)在支持有功能障碍的个人方面发挥着关键作用,但关于印度不同地区的辅助技术需求和障碍的信息有限。为了填补这一空白,我们设计了一份详细的调查方案,以收集关于辅助医疗需求、未满足需求和满意度的全国代表性数据。方法:将对印度北部、南部、东部、西部、中部和东北部六个地区的18万人(每个地区3万人)进行横断面调查。将有目的地选择地区,以体现地理多样性和机构能力;在每个选定的地区内,将按概率比例选择村庄和城区,然后通过系统随机抽样选择住户。在工作人员完成标准培训计划后,每个抽样家庭的所有成员将接受世卫组织快速辅助技术评估(rATA)数字工具的访谈;ICMR协调小组将通过实时数据库检查、监督交叉检查和每月审计来确保数据质量。分析:我们将使用单变量和多变量逻辑回归来确定相关因素,以95%的置信区间估计AT需求的患病率、未满足的需求和满意度。抽样权重和敏感性分析将调整和比较估计。讨论:本议定书描述了在东南亚进行的最大规模的辅助医疗需求调查。所产生的数据将为指导印度的国家AT战略提供关键证据。通过分享我们详细的方法,我们旨在提供一个实用的框架,供其他低收入和中等收入国家采用,以评估和加强其自身的自动检测服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing assistive technology needs, unmet demands, barriers, and gaps in the Indian population: a protocol for large epidemiological survey.

Background: Despite the critical role of assistive technologies (AT) in supporting individuals with functional impairments, there is limited information on AT needs and barriers across India's diverse regions. To fill this gap, we have designed a detailed survey protocol to gather nationally representative data on AT need, unmet need and satisfaction.

Methods: A cross-sectional survey of 180,000 individuals (30,000 per region) across six regions i.e., North, South, East, West, Central, and North-East India will be conduct. Districts will be purposively selected to capture geographic diversity and institutional capacity; within each selected district, villages and urban wards will be chosen with probability proportional to size and households will then be selected by systematic random sampling. All members of each sampled household will be interviewed with the digital WHO Rapid Assistive Technology Assessment (rATA) tool, after staff complete standard training program; data quality will be ensured through real-time database checks, supervisory cross-checks, and monthly audits by the ICMR coordinating team.

Analysis: We will estimate prevalence of AT need, unmet need, and satisfaction with 95 percent confidence intervals using univariate and multivariate logistic regression to identify associated factors. Sampling weights and sensitivity analyses will adjust and compare estimates.

Discussion: This protocol describes the largest AT needs survey ever conducted in South-East Asia. The data generated will provide crucial evidence to guide India's national AT strategy. By sharing our detailed methodology, we aim to offer a practical framework that other low and middle-income countries can adapt to assess and enhance their own AT services.

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