IDEAS home Printed from https://ideas.repec.org/a/gam/jscscx/v12y2023i4p239-d1125312.html
   My bibliography  Save this article

A Delphi Study to Develop Items for a New Tool for Measuring Child Neglect for Use by Multi-Agency Practitioners in the UK

Author

Listed:
  • Simon Haworth

    (Department of Social Work & Social Care, School of Social Policy, University of Birmingham, Birmingham B15 2TT, UK)

  • Paul Montgomery

    (Department of Social Policy, Sociology and Criminology, University of Birmingham, Birmingham B15 2TT, UK)

  • Jason Schaub

    (Department of Social Work & Social Care, School of Social Policy, University of Birmingham, Birmingham B15 2TT, UK)

Abstract

Social work and allied professions can struggle to accurately assess child neglect. Our research project is developing a new child neglect measurement tool for use by multi-agencies to address this issue. Phase two of this project employed a Delphi study to gather the views of a range of experts to help develop it. There were two important stages to inform the Delphi study: a systematic review of child neglect measures, and three online focus groups with a purposive sample of 16 participants with expertise in child neglect (academics, practitioners, and experts by experience). We then conducted a three-round modified online Delphi study with a purposive sample of 60 international panellists with expertise in child neglect. We followed the CREDES guidelines for the rigorous application of the Delphi technique. The panel generated salient items for the tool and scaled these for importance. The panel reached consensus for 18 items and 15 elements for the tool. The items included neglect type, chronicity, and severity. The elements included hyperlinks to research and the use of 10-point scales. The draft tool is short and may be useable by a range of practitioners in multi-agency settings. It is inclusive of social harms, such as poverty and social isolation. It will now be piloted.

Suggested Citation

  • Simon Haworth & Paul Montgomery & Jason Schaub, 2023. "A Delphi Study to Develop Items for a New Tool for Measuring Child Neglect for Use by Multi-Agency Practitioners in the UK," Social Sciences, MDPI, vol. 12(4), pages 1-20, April.
    • Handle: RePEc:gam:jscscx:v:12:y:2023:i:4:p:239-:d:1125312
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2076-0760/12/4/239/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2076-0760/12/4/239/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Meijering, Jurian V. & Tobi, Hilde, 2016. "The effect of controlled opinion feedback on Delphi features: Mixed messages from a real-world Delphi experiment," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 166-173.
    2. Cynthia Chew & Gunther Eysenbach, 2010. "Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-13, November.
    3. Carter, Vernon & Myers, Miranda R., 2007. "Exploring the risks of substantiated physical neglect related to poverty and parental characteristics: A national sample," Children and Youth Services Review, Elsevier, vol. 29(1), pages 110-121, January.
    Full references (including those not matched with items on IDEAS)

    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. Nisar, Sobia & Shafiq, Muhammad, 2019. "Framework for efficient utilisation of social media in Pakistan's healthcare sector," Technology in Society, Elsevier, vol. 56(C), pages 31-43.
    2. Luis-Millán González & José Devís-Devís & Maite Pellicer-Chenoll & Miquel Pans & Alberto Pardo-Ibañez & Xavier García-Massó & Fernanda Peset & Fernanda Garzón-Farinós & Víctor Pérez-Samaniego, 2021. "The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis," IJERPH, MDPI, vol. 18(9), pages 1-20, April.
    3. Han, Chunjia & Yang, Mu & Piterou, Athena, 2021. "Do news media and citizens have the same agenda on COVID-19? an empirical comparison of twitter posts," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    4. Boonyanit Mathayomchan & Viriya Taecharungroj & Walanchalee Wattanacharoensil, 2023. "Evolution of COVID-19 tweets about Southeast Asian Countries: topic modelling and sentiment analyses," Place Branding and Public Diplomacy, Palgrave Macmillan, vol. 19(3), pages 317-334, September.
    5. Elanor Colleoni & Nuccio Ludovico & Illia Laura & Ravindran Kiron, 2021. "Does Sharing Economy Have a Moral Capital? Comparing Semantic Networks in Social Media and News Media," Journal of Management and Sustainability, Canadian Center of Science and Education, vol. 11(2), pages 1-1, December.
    6. Nanath, Krishnadas & Balasubramanian, Sreejith & Shukla, Vinaya & Islam, Nazrul & Kaitheri, Supriya, 2022. "Developing a mental health index using a machine learning approach: Assessing the impact of mobility and lockdown during the COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    7. Cindy Cheng & Joan Barceló & Allison Spencer Hartnett & Robert Kubinec & Luca Messerschmidt, 2020. "COVID-19 Government Response Event Dataset (CoronaNet v.1.0)," Nature Human Behaviour, Nature, vol. 4(7), pages 756-768, July.
    8. Bruce Forrester, 2020. "Authentic chatter," Computational and Mathematical Organization Theory, Springer, vol. 26(4), pages 382-411, December.
    9. Greyling, Talita & Rossouw, Stephanie & Adhikari, Tamanna, 2020. "Happiness-lost: Did Governments make the right decisions to combat Covid-19?," GLO Discussion Paper Series 556, Global Labor Organization (GLO).
    10. Belton, Ian & Wright, George & Sissons, Aileen & Bolger, Fergus & Crawford, Megan M. & Hamlin, Iain & Taylor Browne Lūka, Courtney & Vasilichi, Alexandrina, 2021. "Delphi with feedback of rationales: How large can a Delphi group be such that participants are not overloaded, de-motivated, or disengaged?," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    11. Hongzhou Shen & Yue Ju & Zhijing Zhu, 2023. "Extracting Useful Emergency Information from Social Media: A Method Integrating Machine Learning and Rule-Based Classification," IJERPH, MDPI, vol. 20(3), pages 1-20, January.
    12. Gaspar, Rui & Yan, Zheng & Domingos, Samuel, 2019. "Extreme natural and man-made events and human adaptive responses mediated by information and communication technologies' use: A systematic literature review," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 125-135.
    13. David A Broniatowski & Michael J Paul & Mark Dredze, 2013. "National and Local Influenza Surveillance through Twitter: An Analysis of the 2012-2013 Influenza Epidemic," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
    14. Jiayin Pei & Guang Yu & Xianyun Tian & Maureen Renee Donnelley, 2017. "A new method for early detection of mass concern about public health issues," Journal of Risk Research, Taylor & Francis Journals, vol. 20(4), pages 516-532, April.
    15. Kawamoto, Carlos Tadao & Wright, James Terence Coulter & Spers, Renata Giovinazzo & de Carvalho, Daniel Estima, 2019. "Can we make use of perception of questions' easiness in Delphi-like studies? Some results from an experiment with an alternative feedback," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 296-305.
    16. Zeynep Ertem & Dorrie Raymond & Lauren Ancel Meyers, 2018. "Optimal multi-source forecasting of seasonal influenza," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-16, September.
    17. Meijering, Jurian Vincent & Tobi, Hilde, 2018. "The effects of feeding back experts’ own initial ratings in Delphi studies: A randomized trial," International Journal of Forecasting, Elsevier, vol. 34(2), pages 216-224.
    18. Jose L Herrera & Ravi Srinivasan & John S Brownstein & Alison P Galvani & Lauren Ancel Meyers, 2016. "Disease Surveillance on Complex Social Networks," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-16, July.
    19. Ibrahim Musa & Hyun Woo Park & Lkhagvadorj Munkhdalai & Keun Ho Ryu, 2018. "Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization," Sustainability, MDPI, vol. 10(10), pages 1-20, September.
    20. Helton, Jesse J., 2016. "Food neglect and maltreatment re-report," Children and Youth Services Review, Elsevier, vol. 71(C), pages 77-83.

    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:gam:jscscx:v:12:y:2023:i:4:p:239-:d:1125312. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.