{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T23:20:05Z","timestamp":1782256805782,"version":"3.54.5"},"reference-count":13,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2018,9,17]],"date-time":"2018-09-17T00:00:00Z","timestamp":1537142400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"National Office for Suicide Prevention, Republic of Ireland"},{"name":"Samaritans Ireland"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health Informatics J"],"published-print":{"date-parts":[[2019,12]]},"abstract":"<jats:p>This work presents an analysis of 3.5 million calls made to a mental health and well-being helpline, seeking to answer the question, what different groups of callers can be characterised by specific usage patterns? Calls were extracted from a telephony informatics system. Each call was logged with a date, time, duration and a unique identifier allowing for repeat caller analysis. We utilized data mining techniques to reveal new insights into help-seeking behaviours. Analysis was carried out using unsupervised machine learning (K-means clustering) to discover the types of callers, and Fourier transform was used to ascertain periodicity in calls. Callers can be clustered into five or six caller groups that offer a meaningful interpretation. Cluster groups are stable and re-emerge regardless of which year is considered. The volume of calls exhibits strong repetitive intra-day and intra-week patterns. Intra-month repetitions are absent. This work provides new data-driven findings to model the type and behaviour of callers seeking mental health support. It offers insights for computer-mediated and telephony-based helpline management.<\/jats:p>","DOI":"10.1177\/1460458218792668","type":"journal-article","created":{"date-parts":[[2018,9,17]],"date-time":"2018-09-17T11:56:06Z","timestamp":1537185366000},"page":"1722-1738","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":23,"title":["Data analytics of call log data to identify caller behaviour patterns from a mental health and well-being helpline"],"prefix":"10.1177","volume":"25","author":[{"given":"Siobhan","family":"O\u2019Neill","sequence":"first","affiliation":[{"name":"Ulster University, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raymond R","family":"Bond","sequence":"additional","affiliation":[{"name":"Ulster University, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4820-0322","authenticated-orcid":false,"given":"Alexander","family":"Grigorash","sequence":"additional","affiliation":[{"name":"Ulster University, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Colette","family":"Ramsey","sequence":"additional","affiliation":[{"name":"Ulster University, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cherie","family":"Armour","sequence":"additional","affiliation":[{"name":"Ulster University, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maurice D","family":"Mulvenna","sequence":"additional","affiliation":[{"name":"Ulster University, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2018,9,17]]},"reference":[{"key":"bibr1-1460458218792668","doi-asserted-by":"publisher","DOI":"10.1186\/s13033-016-0076-4"},{"key":"bibr2-1460458218792668","unstructured":"Pollock K, Armstrong S, Coveney C, et al. 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