Inferential statistics were then used to check for relationships between outcome measures and risk factors (e.g. alcohol use and smoking status), sociodemographics (borough, gender, age, marital status, ethnicity, educational qualification and socioeconomic classification) as well as health behaviours (e.g. visiting the GP, visiting the Dentist and the reason for Dental visit).
As Speybroeck et al. (2006) note, the qualifications, training, classification and roles of health workers vary widely from country to country.
Predictor variables included demographic information (such as age, years of experience, profession and higher degree qualification) and the baseline measures such as compliance classification (compliant vs non compliant), biomedical belief score, behavioural belief score, and knowledge score.
We are not hung up on categories, rules and classification.
● clustering and classification.
Chapter 17 Summary And Classification.
In the context of the RANZCOG FSEP target practitioner population, several population subgroup classifications can be made based on qualification and or professional experience (for example, trainee midwife, midwife, registrar, general practitioner, obstetrician).
It seems then that the level of qualification and training required to carry out substitution requires yet a better definition of practice boundaries including a classification of tasks.
