Most depression assessment tools are based on self-report questionnaires, such as the Patient Health Questionnaire (PHQ-9). These psychometric instruments can be easily adapted to an online setting by means of electronic forms. However, this approach lacks the interacting and engaging features of modern digital environments. With the aim of making depression screening more available, attractive and effective, we developed Perla, a conversational agent able to perform an interview based on the PHQ-9. We also conducted a validation study in which we compared the results obtained by the traditional self-report questionnaire with Perla's automated interview. Analyzing the results from this study we draw two significant conclusions: firstly, Perla is much preferred by Internet users, achieving more than 2.5 times more reach than a traditional form-based questionnaire; secondly, her psychometric properties (Cronbach's alpha of 0.81, sensitivity of 96% and specificity of 90%) are excellent and comparable to the traditional well-established depression screening questionnaires.

翻译：大多数抑郁症评估工具都基于自我报告调查表,如病人健康问卷(PHQ-9),这些心理计量工具可以通过电子形式很容易地适应在线环境,然而,这一方法缺乏现代数字环境的相互作用和互动特点;为了让抑郁症筛查更容易获得、更有吸引力和更加有效,我们开发了Perla,这是一个能够根据PHQ-9进行访谈的谈话代理机构;我们还进行了一项鉴定研究,将传统自我报告问卷获得的结果与Perla的自动访谈进行比较;分析这项研究的结果,我们得出两个重要结论:第一,Perla为互联网用户所偏爱,比传统的基于表格的问卷高出2.5倍以上;第二,她的心理测量特征(Cronbach的0.81阿尔法,敏感度为96%,特殊度为90%)优异,与传统的完善的抑郁症筛查问卷相当。