International Food Policy Research Institute, Dhaka, Bangladesh.
New York University, New York, USA.
Sci Data. 2019 Jul 17;6(1):125. doi: 10.1038/s41597-019-0128-0.
High-frequency social data collection may facilitate improved recall, more inclusive reporting, and improved capture of intra-period variability. Although there are examples of small studies collecting particular variables at high frequency in the social science literature, to date there have been no significant efforts to collect a wide range of variables with high frequency. We have implemented the first such effort with a smartphone-based data collection approach, systematically varying the frequency of survey task and recall period, allowing the analysis of the relative merit of high-frequency data collection for different key variables in household surveys. This study of 480 farmers from northwestern Bangladesh over approximately one year of continuous data on key measures of household and community wellbeing could be particularly useful for the design and evaluation of development interventions and policies. While the data discussed here provide a snapshot of what is possible, we also highlight their strength for providing opportunities for interdisciplinary research in the household agricultural production, practices, seasonal hunger, etc., in a low-income agrarian society.
高频社会数据收集可能有助于改善回忆、更全面的报告，并更好地捕捉期间内的变化。虽然在社会科学文献中有一些小规模研究以高频收集特定变量的例子，但迄今为止，还没有进行重大努力以高频收集广泛的变量。我们通过基于智能手机的数据收集方法实现了首次此类尝试，系统地改变了调查任务和回忆期的频率，从而可以分析高频数据收集对于家庭调查中不同关键变量的相对优势。这项对孟加拉国西北部 480 名农民进行的研究，大约一年时间内持续收集了家庭和社区福祉的关键指标数据，对于发展干预措施和政策的设计和评估可能特别有用。虽然这里讨论的数据提供了一个可能的情况的快照，但我们也强调了它们的优势，即它们为在低收入农业社会中进行家庭农业生产、实践、季节性饥饿等跨学科研究提供了机会。
