Detecting changes in help seeker conversations on a suicide prevention helpline during the COVID- 19 pandemic: in-depth analysis using encoder representations from transformers

BMC Public Health. 2022 Mar 18;22(1):530. doi: 10.1186/s12889-022-12926-2.

Abstract

Background: Preventatives measures to combat the spread of COVID- 19 have introduced social isolation, loneliness and financial stress. This study aims to identify whether the COVID-19 pandemic is related to changes in suicide-related problems for help seekers on a suicide prevention helpline.

Methods: A retrospective cohort study was conducted using chat data from a suicide prevention helpline in the Netherlands. The natural language processing method BERTopic was used to detect common topics in messages from December 1, 2019 until June 1, 2020 (N = 8589). Relative topic occurrence was compared before and during the lock down starting on March 23, 2020. The observed changes in topic usage were likewise analyzed for male and female, younger and older help seekers and help seekers living alone.

Results: The topic of the COVID-19 pandemic saw an 808% increase in relative occurrence after the lockdown. Furthermore, the results show that help seeker increased mention of thanking the counsellor (+ 15%), and male and young help seekers were grateful for the conversation (+ 45% and + 32% respectively). Coping methods such as watching TV (- 21%) or listening to music (- 15%) saw a decreased mention. Plans for suicide (- 9%) and plans for suicide at a specific location (- 15%) also saw a decreased mention. However, plans for suicide were mentioned more frequently by help seekers over 30 years old (+ 11%) or who live alone and (+ 52%). Furthermore, male help seekers talked about contact with emergency care (+ 43%) and panic and anxiety (+ 24%) more often. Negative emotions (+ 22%) and lack of self-confidence (+ 15%) were mentioned more often by help seekers under 30, and help seekers over 30 saw an increased mention of substance abuse (+ 9%).

Conclusion: While mentions of distraction, social interaction and plans for suicide decreased, expressions of gratefulness for the helpline increased, highlighting the importance of contact to help seekers during the lockdown. Help seekers under 30, male or who live alone, showed changes that negatively related to suicidality and should be monitored closely.

Keywords: BERT; Machine learning; Natural language processing; Suicide chat counseling.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • COVID-19*
  • Communicable Disease Control
  • Female
  • Humans
  • Male
  • Pandemics / prevention & control
  • Retrospective Studies
  • Suicide Prevention*
  • Suicide* / psychology