In this study we report on our experiences with collecting large personal network data (25 alters) from a representative sample of Dutch women. We made use of GENSI, a recently developed tool for network data collection using interactive visual elements that has been shown to reduce respondent burden. A sample of 758 women between the ages of 18 and 40 were recruited through the LISS-panel; a longitudinal online survey of Dutch people. Respondents were asked to name exactly 25 alters, answer sixteen questions about these alters (name interpreter questions), and assess all 300 alter-alter relations. Nearly all (97%) respondents reported on 25 alters. Non-response was minimal: 92% of respondents had no missing values, and an additional 5% had fewer than 10% missing values. Listing 25 alters took 3.5 $\pm$ 2.2 (mean $\pm$ SD) minutes, and reporting on the ties between these alters took 3.6 $\pm$ 1.3 min. Answering all alter questions took longest with a time of 15.2 $\pm$ 5.3 min. The majority of respondents thought the questions were clear and easy to answer, and most enjoyed filling in the survey. Collecting large personal networks can mean a significant burden to respondents, but through the use of visual elements in the survey, it is clear that it can be done within reasonable time, with enjoyment and without much non-response.

在这项研究中，我们报告了我们从有代表性的荷兰妇女样本中收集大型个人网络数据（25个变更）的经验。我们使用了GENSI，这是一种最近开发的工具，它使用交互式视觉元素来收集网络数据，从而减轻了受访者的负担。通过LISS面板，招募了758名18至40岁的女性。对荷兰人的纵向在线调查。要求受访者准确地命名25个变更，回答有关这些变更的16个问题（名称解释者问题），并评估所有300个变更-变更关系。几乎所有受访者（97％）报告了25次更改。无回应的可能性很小：92％的回应者没有缺失值，另有5％的回应值小于10％。清单25的变更花费了3.5 $\pm$ 2.2（平均 $\pm$ SD）分钟，并且报告这些变更之间的联系花费了3.6 $\pm$ 1.3分钟 回答所有其他问题花费的时间最长，为15.2 $\pm$ 5.3分钟 大多数受访者认为问题很清楚且易于回答，并且大多数人喜欢填写调查表。收集大型个人网络可能对受访者构成沉重负担，但是通过在调查中使用视觉元素，很明显，可以在合理的时间内完成该过程，而且很愉快，而且没有太多响应。