Hunter Caouette’s research while affiliated with Worcester Polytechnic Institute and other places

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Publications (1)


StudentSADD: Rapid Mobile Depression and Suicidal Ideation Screening of College Students during the Coronavirus Pandemic
  • Article

July 2022

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45 Reads

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14 Citations

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies

ML Tlachac

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Miranda Reisch

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The growing prevalence of depression and suicidal ideation among college students further exacerbated by the Coronavirus pandemic is alarming, highlighting the need for universal mental illness screening technology. With traditional screening questionnaires too burdensome to achieve universal screening in this population, data collected through mobile applications has the potential to rapidly identify at-risk students. While prior research has mostly focused on collecting passive smartphone modalities from students, smartphone sensors are also capable of capturing active modalities. The general public has demonstrated more willingness to share active than passive modalities through an app, yet no such dataset of active mobile modalities for mental illness screening exists for students. Knowing which active modalities hold strong screening capabilities for student populations is critical for developing targeted mental illness screening technology. Thus, we deployed a mobile application to over 300 students during the COVID-19 pandemic to collect the Student Suicidal Ideation and Depression Detection (StudentSADD) dataset. We report on a rich variety of machine learning models including cutting-edge multimodal pretrained deep learning classifiers on active text and voice replies to screen for depression and suicidal ideation. This unique StudentSADD dataset is a valuable resource for the community for developing mobile mental illness screening tools.

Citations (1)


... In the next step, they screened the 103 potentially relevant full texts and resolved any conflicts with an independent researcher, revealing 27 eligible articles. This included eleven studies investigating the predictive value of passive sensing for the prediction of STB [26][27][28][29][30][31][32][33][34][35][36] , ten trials focusing on the feasibility of passive sensing 28,[37][38][39][40][41][42][43][44][45] , and seven study protocols [46][47][48][49][50][51][52] . One article reported on two studies: a feasibility investigation and a prediction study 28 . ...

Reference:

A systematic review on passive sensing for the prediction of suicidal thoughts and behaviors
StudentSADD: Rapid Mobile Depression and Suicidal Ideation Screening of College Students during the Coronavirus Pandemic
  • Citing Article
  • July 2022

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies