Dementia Care Mapping (DCM): initial validation of DCM 8 in UK field trials

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Dementia Care Mapping (DCM): initial validation of DCM 8 in UK field trials.

OBJECTIVES This paper describes DCM 8 and reports on the initial validation study of DCM 8. METHODS Between 2001-2003, a series of international expert working groups were established to examine various aspects of DCM with the intention of revising and refining it. During 2004-2005 the revised tool (DCM 8) was piloted in seven service settings in the UK and validated against DCM 7th edition. ...

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Exploring the potential for secondary uses of Dementia Care Mapping (DCM) data for improving the quality of dementia care.

The reuse of existing datasets to identify mechanisms for improving healthcare quality has been widely encouraged. There has been limited application within dementia care. Dementia Care Mapping is an observational tool in widespread use, predominantly to assess and improve quality of care in single organisations. Dementia Care Mapping data have the potential to be used for secondary purposes to...

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Optimising intervention implementation in the DCM™ epic trial (dementia care mapping™: to enable person-centred care in care homes)

The DCMTM EPIC trial requires participating care homes to identify two staff members willing to be trained in the DCMTM intervention and thereafter implement three DCM ‘mapping cycles’ during the trial. These staff are known as ‘mappers’. This is no small undertaking, and early pilot work highlighted the need to include additional measures to enhance adherence to some elements of intervention u...

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N-hydroxysuccinimide Dcm, Edc

Additional Acknowledgements Magnetic resonance imaging work was performed at the Northwestern University Center for Advanced Molecular Imaging generously supported by NCI CCSG P30 CA060553 awarded to the Robert H Lurie Comprehensive Cancer Center. Metal analysis was performed at the Northwestern University Quantitative Bioelemental Imaging Center generously supported by NASA Ames Research Cente...

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Network discovery with DCM

This paper is about inferring or discovering the functional architecture of distributed systems using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity. This network discovery uses Bayesian model selection to identify the sparsity structure (absence of edges or connections) in a g...

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ژورنال

عنوان ژورنال: International Journal of Geriatric Psychiatry

سال: 2006

ISSN: 0885-6230,1099-1166

DOI: 10.1002/gps.1600