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Attitudes towards the collection and linkage of maltreatment data for research: A qualitative study
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In: Int J Popul Data Sci (2022)
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Abstract:
INTRODUCTION: Factors that affect public and professionals’ attitudes towards the collection and linkage of health and other data have been explored in the literature. Thus far there has been no study exploring attitudes towards the collection of child maltreatment data. OBJECTIVES: Our aim is to explore attitudes regarding the collection and linkage of maltreatment data for research. METHODS: Participants included younger mothers, older mothers, care-experienced young people, and professionals who were responsible for recording child maltreatment data. Four face-to-face focus groups were conducted, one with younger mothers (n = 6), one with older mothers (n = 10), and two with care-experienced young people (n = 6 and n = 5). An online focus group was conducted with professionals (n = 10), two of whom additionally participated in telephone interviews. Transcribed audio-recorded data were inductively coded, a portion were double-coded by a second researcher, and thematically analysed. RESULTS: Three major themes were identified. The first concerned issues of consent, specifically the conditions for providing consent and factors influencing this. The second concerned trust in data security and validity, the organisations and individuals providing and using the data, and how the information provided shapes attitudes. The third theme explored the benefits of research and the researchers’ role in child protection. Participants wanted the choice of providing consent for data collection, especially when consenting on behalf of another, but there were concerns that maltreated children were unidentifiable in anonymised datasets. Care-experienced young people were concerned about data collection from Social Services records due to their sensitivity. There was a general lack of understanding about how research data is viewed and the accuracy of records. CONCLUSIONS: Novel findings in the study were strongly related to the sensitive nature of the topic. The findings may be particularly useful when designing research studies and participant materials and a co-productive approach to this should be taken.
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Keyword:
Population Data Science
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URL: https://doi.org/10.23889/ijpds.v6i1.1693 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8793841/
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23 |
Maastricht University’s Multilingual Speech Translation System for IWSLT 2021
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25 |
Toward Multilingual Neural Machine Translation with Universal Encoder and Decoder
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26 |
The Karlsruhe Institute of Technology Systems for the News Translation Task in WMT 2017
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27 |
Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation
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In: Transactions of the Association for Computational Linguistics, 7, 313–325 ; ISSN: 2307-387X (2022)
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30 |
Adapting End-to-End Speech Recognition for Readable Subtitles
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32 |
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning
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33 |
The Karlsruhe Institute of Technology Translation Systems for the WMT 2012
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34 |
Robust and Scalable Differentiable Neural Computer for Question Answering
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35 |
Lecture Translator Speech translation framework for simultaneous lecture translation
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36 |
The Universität Karlsruhe Translation System for the EACL-WMT 2009
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38 |
Incremental processing of noisy user utterances in the spoken language understanding task
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39 |
Improving Zero-shot Translation with Language-Independent Constraints
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40 |
Lexical Translation Model Using A Deep Neural Network Architecture
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