Why do people call crisis helplines? Identifying taxonomies of presenting reasons and discovering associations between these reasons

Robin Turkington, Maurice Mulvenna, RR Bond, Siobhan O'Neill, Courtney Potts, Cherie Armour, Edel Ennis, Catherine Millman

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Abstract

The objective of this study is to identify the most common reasons for contacting a crisis helpline through analysing a large call log data set. Two taxonomies were identified within the call log data from a Northern Ireland telephone crisis helpline (Lifeline), categorising the cited reason for each call. One taxonomy categorised the reasons at a fine granular level; the other taxonomy used the relatively coarser International Classification of Diseases–10. Exploratory data analytic techniques were applied to discover insights into why individuals contact crisis helplines. Risk ratings of calls were also compared to assess the associations between presenting issue and of risk of suicide as assessed. Reasons for contacting the service were assessed across geolocations. Association rule mining was used to identify associations between the presenting reasons for client’s calls. Results demonstrate that both taxonomies show that calls with reasons relating to suicide are the most common reasons for contacting Lifeline and were a prominent feature of the discovered association rules. There were significant differences between reasons in both taxonomies concerning risk ratings. Reasons for calling helplines that are associated with higher risk ratings include those calling with a personality disorder, mental disorders, delusional disorders and drugs (legal). In conclusion, employing two differing taxonomy approaches to analyse call log data reveals the prevalence of main presenting reasons for contacting a crisis helpline. The association rule mining using each taxonomy provided insights into the associations between presenting reasons. Practical and research applications are discussed.

Original languageEnglish
Pages (from-to)1-17
Number of pages17
JournalHealth Informatics Journal
Early online date18 Apr 2020
DOIs
Publication statusE-pub ahead of print - 18 Apr 2020

Keywords

  • Telephone Crisis Helplines
  • Suicide
  • Association Rule Mining
  • Data Analytics
  • Computer Science
  • Public Health
  • ICD-10
  • Mental health and well-being helpline
  • Help-seeking behaviour
  • Telephony analysis
  • mental health
  • suicide
  • call data analytics
  • association rule mining
  • telephone crisis helplines

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