IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0175580.html
   My bibliography  Save this article

Media effects on suicide methods: A case study on Hong Kong 1998-2005

Author

Listed:
  • Qijin Cheng
  • Feng Chen
  • Paul S F Yip

Abstract

Background: Previous studies have suggested that mass media’s reports of new suicide methods will increase suicides using the same method. The same pattern seems not to apply to a conventional suicide method, unless it was used by a celebrity. Objective: 1) to examine media effects on both new and non-new suicide methods during 1998 and 2005 in Hong Kong (HK), when a new method by burning charcoal (CB suicide) was spreading in the region. 2) to examine how CB competed with non-CB methods in terms of media coverage and “recruiting” suicidal persons in the socio-economic context. Methods: A self- and mutual- exciting process model was fitted to the data, adjusting for divorce rate, unemployment rate, and property price index. Breaking the whole period into onset, peak, and post-peak stages, the model was fitted again to examine the differences. Results: Comparable copycat effects were found on both CB and non-CB suicide news. The only cross-method media effects were found in the onset stage when non-CB suicide news showed suppressing effect on CB suicides. CB suicides reported a significant self-excitation effect. A higher divorce rate and lower property price index were associated with significantly more suicides incidences and more suicide news. Conclusions: The emerging of CB suicide method did not substitute media coverage of non-CB suicide in HK. Media effects in this case were not limited to new suicide method or celebrity suicide. The effects were further fueled by adverse socio-economic conditions.

Suggested Citation

  • Qijin Cheng & Feng Chen & Paul S F Yip, 2017. "Media effects on suicide methods: A case study on Hong Kong 1998-2005," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-12, April.
  • Handle: RePEc:plo:pone00:0175580
    DOI: 10.1371/journal.pone.0175580
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0175580
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0175580&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0175580?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Claudia Czado & Tilmann Gneiting & Leonhard Held, 2009. "Predictive Model Assessment for Count Data," Biometrics, The International Biometric Society, vol. 65(4), pages 1254-1261, December.
    2. Ying-Yeh Chen & Feng Chen & David Gunnell & Paul S F Yip, 2013. "The Impact of Media Reporting on the Emergence of Charcoal Burning Suicide in Taiwan," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-6, January.
    3. Brockwell, A.E., 2007. "Universal residuals: A multivariate transformation," Statistics & Probability Letters, Elsevier, vol. 77(14), pages 1473-1478, August.
    4. Qijin Cheng & Shu-Sen Chang & Yingqi Guo & Paul S F Yip, 2015. "Information Accessibility of the Charcoal Burning Suicide Method in Mainland China," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-15, October.
    5. Florentine, Julia Buus & Crane, Catherine, 2010. "Suicide prevention by limiting access to methods: A review of theory and practice," Social Science & Medicine, Elsevier, vol. 70(10), pages 1626-1632, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emmanuel Nii-Boye Quarshie & Johnny Andoh-Arthur & Kwaku Oppong Asante & Winifred Asare-Doku, 2021. "Online media reporting of suicidal behaviour in Ghana: Analysis of adherence to the WHO guidelines," International Journal of Social Psychiatry, , vol. 67(3), pages 251-259, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    2. Qijin Cheng & Shu-Sen Chang & Yingqi Guo & Paul S F Yip, 2015. "Information Accessibility of the Charcoal Burning Suicide Method in Mainland China," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-15, October.
    3. Cui, Yunwei & Wu, Rongning, 2016. "On conditional maximum likelihood estimation for INGARCH(p,q) models," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 1-7.
    4. Vasiliki Christou & Konstantinos Fokianos, 2014. "Quasi-Likelihood Inference For Negative Binomial Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 55-78, January.
    5. James Mitchell & Martin Weale, 2023. "Censored density forecasts: Production and evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 714-734, August.
    6. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    7. Lu, Ye & Suthaharan, Neyavan, 2023. "Electricity price spike clustering: A zero-inflated GARX approach," Energy Economics, Elsevier, vol. 124(C).
    8. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    9. Zhan, Xiu-Xiu & Liu, Chuang & Sun, Gui-Quan & Zhang, Zi-Ke, 2018. "Epidemic dynamics on information-driven adaptive networks," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 196-204.
    10. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    11. Diebold, Francis X. & Shin, Minchul & Zhang, Boyuan, 2023. "On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates," Journal of Econometrics, Elsevier, vol. 237(2).
    12. Nicholas G. Reich & Justin Lessler & Krzysztof Sakrejda & Stephen A. Lauer & Sopon Iamsirithaworn & Derek A. T. Cummings, 2016. "Case Study in Evaluating Time Series Prediction Models Using the Relative Mean Absolute Error," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 285-292, July.
    13. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    14. Antonio Bracale & Pasquale De Falco, 2015. "An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power," Energies, MDPI, vol. 8(9), pages 1-22, September.
    15. Tsyplakov, Alexander, 2013. "Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments," MPRA Paper 45186, University Library of Munich, Germany.
    16. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
    17. Birgit Schrödle & Leonhard Held, 2011. "A primer on disease mapping and ecological regression using $${\texttt{INLA}}$$," Computational Statistics, Springer, vol. 26(2), pages 241-258, June.
    18. Xueli Wang & Moqin Zhou & Jinzhu Jia & Zhi Geng & Gexin Xiao, 2018. "A Bayesian Approach to Real-Time Monitoring and Forecasting of Chinese Foodborne Diseases," IJERPH, MDPI, vol. 15(8), pages 1-13, August.
    19. repec:hum:wpaper:sfb649dp2010-055 is not listed on IDEAS
    20. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2014. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121.
    21. Moritz Berger & Gerhard Tutz, 2021. "Transition models for count data: a flexible alternative to fixed distribution models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(4), pages 1259-1283, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0175580. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.