Interviewers for the APMS asked questions using the PTSD Checklist – Civilian (PCL-C), a 17-item questionnaire based on the Diagnostic Statistical Manual (DSM-IV) symptoms of post-traumatic stress disorder (PTSD).
Each survey involved interviewing a large stratified probability sample of the general population, covering people living in private households. The full adult age range was covered, with the youngest participants aged 16 and the oldest over 100.
While a positive screen for PTSD isn’t a diagnosis, it does suggest the person probably has PTSD and warrants a clinical assessment. The ‘Methods’ chapter of the Adult Psychiatric Morbidity Survey 2014 (PDF) sets out the specific methodology of the PCL-C.
The prevalence of PTSD is determined here by dividing the number of respondents with a score of 50 or more on the PCL-C by the total number of respondents.
The resulting statistics for PTSD have been age-standardised. This is because the prevalence of common mental disorders is related to age and the age profile can differ considerably between ethnic groups. (An age profile shows the number of people of different ages within an ethnic group.) This adjustment allows comparisons to be made between ethnic groups as if they had the same age profile.
The survey covers people who live in private households. It doesn’t include those who live in institutional settings (such as hospitals or prisons) or in temporary housing (such as hostels or bed and breakfasts) or those who sleep rough. People living in such settings are likely to have worse mental health than those living in private households (Gill et al. 1996; cited in APMS 2014).
Where a selected participant could not take part in a long interview due to a physical or mental health condition, some information about this was recorded by the interviewer on the doorstep. This information may be biased due to it having been collected from another household member.
Socially undesirable or stigmatised feelings and behaviours may be underreported. While this is a risk for any study based on self-report data, the study goes some way to minimising this by collecting particularly sensitive information in a self-completion format.
Some people selected for the survey could not be contacted or refused to take part. The achieved response rate (57%) is in line with that of similar surveys (Barnes et al. 2010; cited in APMS 2014). Weighting helps take account of those who were selected for the survey but didn’t take part.
Statisticians rebalance or ‘weight’ the survey results to more accurately represent the general population. This helps to make them more reliable. Survey weights are usually applied to make sure the survey sample has broadly the same sex, age, ethnic and geographic make up as the general population.
Biases in sample selection for the phase 1 interviews were addressed through weighting so that the results were representative of the English household population aged 16 and over. Weights for phase 2, the follow-up of some respondents, were calculated through a process of modelling the probability of being selected and responding, then relating the result to the phase 1 weighting figure.
Confidence intervals for each ethnic group are available in the ‘download the data’ section.
Based on survey results, it’s estimated that 4.9% of White British women screened positive for probable PTSD.
This estimate is based on a random sample of adults rather than the whole population of England. The measure makes an estimate of the percentage of different groups who would screen positive for probable PTSD, but it’s impossible to be 100% certain of the true percentage.
It’s 95% certain, however, that somewhere between 4.1% and 5.9% of all White British women in England would have screened positively for probable PTSD. In statistical terms, this is a 95% confidence interval. This means that if 100 random samples were taken, then 95 times out of 100 the estimate would fall between the lower and upper bounds of the confidence interval. But 5 times out of 100 it would fall outside this range.
The smaller the survey sample, the more uncertain the estimate and the wider the confidence interval. For example, fewer Black/Black British women responded to the survey than White British women, so we can be less certain about the estimate for the smaller group. This greater uncertainty is expressed by a wider confidence interval, for example of between 5.6% and 20.3% for Black/Black British women.
All the differences noted in the text are statistically significant. The statistical significance of differences are approximate because they are determined where the 95% confidence intervals for 2 groups or time periods don't overlap.
An example of non-overlapping confidence intervals would be the results for White British men, which had a confidence interval of between 2.7% and 4.5%, and the results for Black women, which had a confidence interval of between 5.6% and 20.3%.
Suppression rules and disclosure control
Risk to disclosure has been accounted for with limitations of the level of disaggregation, size of category groupings, and the maintaining of large underlying populations for each level. No further suppression or other disclosure control has been applied.
Percentages have been rounded to one decimal point.
Full references for other sources cited in this commentary can be found in the report this information has been sourced from Adult Psychiatric Morbidity Survey: Survey of Mental Health and Wellbeing, England, 2014.Quality and methodology information