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75,000 severely disabled children.

J Bradshaw, D Lawton

    Developmental Medicine and Child Neurology
    |February 1, 1985
    PubMed
    Summary
    This summary is machine-generated.

    The Family Fund computerised record offers valuable epidemiological insights into 75,000 UK children with severe disabilities. Analysis reveals variations in child and family characteristics based on primary handicapping conditions.

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    Area of Science:

    • Epidemiology
    • Public Health
    • Disability Studies

    Background:

    • The Family Fund provides financial assistance to families in the UK raising severely disabled children.
    • A comprehensive computerised record of applications exists, detailing 75,000 children.
    • Understanding the characteristics of this population is crucial for public health and policy.

    Purpose of the Study:

    • To explore the epidemiological potential of the Family Fund computerised record.
    • To analyze the strengths and weaknesses of this data source for research.
    • To examine variations in child and family characteristics by principal handicapping conditions.

    Main Methods:

    • Utilized the computerised record of applications to the Family Fund.
    • Conducted a descriptive analysis of the demographic and disability-related data.

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  • Examined variations in characteristics stratified by principal handicapping conditions.

    • Main Results:

    • The Family Fund record is a rich resource for epidemiological research on childhood disability.
    • Identified specific variations in family and child characteristics across different disability types.
    • Highlighted the strengths (e.g., sample size, detail) and limitations (e.g., potential biases) of the record.

    Conclusions:

    • The Family Fund computerised record has significant epidemiological potential for studying severe childhood disability in the UK.
    • Further research can leverage this dataset to inform targeted interventions and support services.
    • Awareness of the record's characteristics is essential for accurate interpretation of findings.