Using Qualitative Data-Mining for Practice Research in Child Welfare
Qualitative data-mining (QDM), using the narrative data contained in child welfare case records, enables researchers to examine child welfare practice using relatively non-intrusive methods. QDM can increase our understanding of client populations and problems, child welfare worker actions, and case...
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| Veröffentlicht in: | Child welfare 2014-01, Vol.93 (6), p.7-26 |
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| container_title | Child welfare |
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| creator | Henry, Colleen Carnochan, Sarah Austin, Michael J. |
| description | Qualitative data-mining (QDM), using the narrative data contained in child welfare case records, enables researchers to examine child welfare practice using relatively non-intrusive methods. QDM can increase our understanding of client populations and problems, child welfare worker actions, and case complexity. This paper reports on experiences from the Child Welfare Qualitative Data-Mining Project; outlines a seven-step guide to QDM methods; and describes how QDM can be used to enhance child welfare practice, research, and education. |
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| identifier | ISSN: 0009-4021 |
| ispartof | Child welfare, 2014-01, Vol.93 (6), p.7-26 |
| issn | 0009-4021 |
| language | eng |
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| source | Jstor Complete Legacy; Education Source; Sociological Abstracts |
| subjects | Academic Achievement Adoption Case Records Child Abuse Child Welfare Children Client Characteristics (Human Services) Confidentiality Consortia Content analysis Data mining Expertise Families & family life Federal Legislation Foster care Organizational change Practice research Qualitative Research Research Needs Researchers Resource Allocation Social Services Social work Teaching Methods |
| title | Using Qualitative Data-Mining for Practice Research in Child Welfare |
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