Identifying suicide prevention crisis-line caller behaviour using wavelet call volume analysis

Research output: Contribution to conferenceAbstract

Abstract

Study objectives: Crisis lines are vital to suicide prevention efforts and provide immediate emotional support to those struggling with loneliness and distress. A knowledge of call volume and caller behaviour patterns is of value in service and operational planning, and also help us under-stand how these lines may reflect, and impact upon, suicidal behaviour and helpseeking.
Methods and materials: This study analyses call data provided by Samaritans UK. Initially, the volume of ongoing calls were calculated with the frequency of 48 samples per day, by considering both number of call arrivals and duration of calls in each half an hour. The daily signals are decomposed using wavelet transform to obtain the approximation (trend-line) and coefficients of the signal.
Results: The preliminary results of this study represent the annual spectrogram of the wavelet approximation for 2015-2017. The spectrograms show that the Samaritans receive the highest volume of calls around 10pm to 2.30am, followed by a substantial reduction of call volume between 5am to 9am, particularly during the final days of the year, on a daily basis. Observation of weekly cycles indicate that the highest call volume throughout the week occurs between Sunday and Tuesday, with the lowest call volume between Thursday and Saturday. Accordingly, daily and weekly repetitive patterns are clearly detectable; however, there was no definite annual cyclic behaviour observed in this 3-year analysis.
Conclusion: Wavelet analysis of call volume can be applied to crisis line caller behaviour and provides insight to inform service planning. The caller behaviour patterns identified may illustrate the times at which people experience crisis.

Conference

Conference30th World Congress of the International Association for Suicide Prevention
Abbreviated titleIASP
CountryUnited Kingdom
CityDerry.Londonderry
Period17/10/1921/10/19
Internet address

Fingerprint

suicide
wavelet
wavelet analysis
analysis
transform

Keywords

  • helplines
  • Fourier
  • wavelet analysis
  • Log analysis
  • Calls
  • call centre
  • Mental Health

Cite this

Bond, RR., Biglarbeigi, P., McCallan, N., Finlay, D., Turkington, R., Mulvenna, M., & O'Neill, S. (2019). Identifying suicide prevention crisis-line caller behaviour using wavelet call volume analysis. Abstract from 30th World Congress of the International Association for Suicide Prevention, Derry.Londonderry, United Kingdom.
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title = "Identifying suicide prevention crisis-line caller behaviour using wavelet call volume analysis",
abstract = "Study objectives: Crisis lines are vital to suicide prevention efforts and provide immediate emotional support to those struggling with loneliness and distress. A knowledge of call volume and caller behaviour patterns is of value in service and operational planning, and also help us under-stand how these lines may reflect, and impact upon, suicidal behaviour and helpseeking.Methods and materials: This study analyses call data provided by Samaritans UK. Initially, the volume of ongoing calls were calculated with the frequency of 48 samples per day, by considering both number of call arrivals and duration of calls in each half an hour. The daily signals are decomposed using wavelet transform to obtain the approximation (trend-line) and coefficients of the signal.Results: The preliminary results of this study represent the annual spectrogram of the wavelet approximation for 2015-2017. The spectrograms show that the Samaritans receive the highest volume of calls around 10pm to 2.30am, followed by a substantial reduction of call volume between 5am to 9am, particularly during the final days of the year, on a daily basis. Observation of weekly cycles indicate that the highest call volume throughout the week occurs between Sunday and Tuesday, with the lowest call volume between Thursday and Saturday. Accordingly, daily and weekly repetitive patterns are clearly detectable; however, there was no definite annual cyclic behaviour observed in this 3-year analysis.Conclusion: Wavelet analysis of call volume can be applied to crisis line caller behaviour and provides insight to inform service planning. The caller behaviour patterns identified may illustrate the times at which people experience crisis.",
keywords = "helplines, Fourier, wavelet analysis, Log analysis, Calls, call centre, Mental Health",
author = "RR Bond and Pardis Biglarbeigi and Niamh McCallan and D Finlay and Robin Turkington and Maurice Mulvenna and Siobhan O'Neill",
year = "2019",
month = "10",
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language = "English",
note = "30th World Congress of the International Association for Suicide Prevention : Breaking Down Walls & Building Bridges, IASP ; Conference date: 17-10-2019 Through 21-10-2019",
url = "https://www.iasp2019.com",

}

Bond, RR, Biglarbeigi, P, McCallan, N, Finlay, D, Turkington, R, Mulvenna, M & O'Neill, S 2019, 'Identifying suicide prevention crisis-line caller behaviour using wavelet call volume analysis' 30th World Congress of the International Association for Suicide Prevention, Derry.Londonderry, United Kingdom, 17/10/19 - 21/10/19, .

Identifying suicide prevention crisis-line caller behaviour using wavelet call volume analysis. / Bond, RR; Biglarbeigi, Pardis; McCallan, Niamh; Finlay, D; Turkington, Robin; Mulvenna, Maurice; O'Neill, Siobhan.

2019. Abstract from 30th World Congress of the International Association for Suicide Prevention, Derry.Londonderry, United Kingdom.

Research output: Contribution to conferenceAbstract

TY - CONF

T1 - Identifying suicide prevention crisis-line caller behaviour using wavelet call volume analysis

AU - Bond, RR

AU - Biglarbeigi, Pardis

AU - McCallan, Niamh

AU - Finlay, D

AU - Turkington, Robin

AU - Mulvenna, Maurice

AU - O'Neill, Siobhan

PY - 2019/10/21

Y1 - 2019/10/21

N2 - Study objectives: Crisis lines are vital to suicide prevention efforts and provide immediate emotional support to those struggling with loneliness and distress. A knowledge of call volume and caller behaviour patterns is of value in service and operational planning, and also help us under-stand how these lines may reflect, and impact upon, suicidal behaviour and helpseeking.Methods and materials: This study analyses call data provided by Samaritans UK. Initially, the volume of ongoing calls were calculated with the frequency of 48 samples per day, by considering both number of call arrivals and duration of calls in each half an hour. The daily signals are decomposed using wavelet transform to obtain the approximation (trend-line) and coefficients of the signal.Results: The preliminary results of this study represent the annual spectrogram of the wavelet approximation for 2015-2017. The spectrograms show that the Samaritans receive the highest volume of calls around 10pm to 2.30am, followed by a substantial reduction of call volume between 5am to 9am, particularly during the final days of the year, on a daily basis. Observation of weekly cycles indicate that the highest call volume throughout the week occurs between Sunday and Tuesday, with the lowest call volume between Thursday and Saturday. Accordingly, daily and weekly repetitive patterns are clearly detectable; however, there was no definite annual cyclic behaviour observed in this 3-year analysis.Conclusion: Wavelet analysis of call volume can be applied to crisis line caller behaviour and provides insight to inform service planning. The caller behaviour patterns identified may illustrate the times at which people experience crisis.

AB - Study objectives: Crisis lines are vital to suicide prevention efforts and provide immediate emotional support to those struggling with loneliness and distress. A knowledge of call volume and caller behaviour patterns is of value in service and operational planning, and also help us under-stand how these lines may reflect, and impact upon, suicidal behaviour and helpseeking.Methods and materials: This study analyses call data provided by Samaritans UK. Initially, the volume of ongoing calls were calculated with the frequency of 48 samples per day, by considering both number of call arrivals and duration of calls in each half an hour. The daily signals are decomposed using wavelet transform to obtain the approximation (trend-line) and coefficients of the signal.Results: The preliminary results of this study represent the annual spectrogram of the wavelet approximation for 2015-2017. The spectrograms show that the Samaritans receive the highest volume of calls around 10pm to 2.30am, followed by a substantial reduction of call volume between 5am to 9am, particularly during the final days of the year, on a daily basis. Observation of weekly cycles indicate that the highest call volume throughout the week occurs between Sunday and Tuesday, with the lowest call volume between Thursday and Saturday. Accordingly, daily and weekly repetitive patterns are clearly detectable; however, there was no definite annual cyclic behaviour observed in this 3-year analysis.Conclusion: Wavelet analysis of call volume can be applied to crisis line caller behaviour and provides insight to inform service planning. The caller behaviour patterns identified may illustrate the times at which people experience crisis.

KW - helplines

KW - Fourier

KW - wavelet analysis

KW - Log analysis

KW - Calls

KW - call centre

KW - Mental Health

M3 - Abstract

ER -

Bond RR, Biglarbeigi P, McCallan N, Finlay D, Turkington R, Mulvenna M et al. Identifying suicide prevention crisis-line caller behaviour using wavelet call volume analysis. 2019. Abstract from 30th World Congress of the International Association for Suicide Prevention, Derry.Londonderry, United Kingdom.