How to select representative geographical areas in mental health service research: a method to combine different selection criteria.
BACKGROUND
Mental health service research can require the selection of representative geographical areas for data collection. This study designed and tested a new method of combining different relevant selection criteria within the context of a survey of housing services for people with mental health disorders in England.


METHODS
Six criteria were considered relevant to select areas for the survey: deprivation, urban-ness, provision of community mental health care, residential care provision, total mental health care spend and pressure on housing generally. A measure was identified for each criterion and established for each of 166 local areas. Variables were converted to standardised scores and multi-dimensional scaling undertaken to produce a single axis representing all six variables. Study sites were chosen from this. Identifying the spread of the constituent variables among the finally selected areas we established how successfully the resulting selection represented each of the selection criteria. Reliability analyses were performed on the rank positions of each area.


RESULTS
The measures were converted into one axis, and all areas were ranked according to the score on that specifically developed new axis. The scores on the axis showed good reliability when single criteria were eliminated from the equation. The finally selected six areas demonstrated a reasonable spread of scores of each of the constituent variables.


CONCLUSIONS
Converting several relevant criteria into one score is a feasible approach to ranking geographical areas to assist in identifying small samples that are arguably representative. The method may be used widely in similar research, but requires the availability of reliable data on relevant selection criteria.
Unit for Social and Community Psychiatry, Barts and the London School of Medicine, Queen Mary University of London, Newham Centre for Mental Health, London, UK. s.priebe@qmul.ac.uk
Stefan
S
Priebe
Marya
M
Saidi
John
J
Kennedy
Gyles
G
Glover
D002391:Catchment Area, Health; D016000:Cluster Analysis; D003155:Community Mental Health Centers; D003156:Community Mental Health Services / Q000379:methods; D004739:England; D005843:Geography; D006302:Health Services Research / Q000379:methods* / Q000592:standards; D006798:Housing; D006801:Humans; D014505:Urban Population