a national depression index
for
This site complements the article published in the Medical Journal of
Australia which describes the development of a national depression
index for
The NDI has been developed to track changes in the
population and groups over time and to enable groups within the population to
be compared and groups who may be at elevated risk of depression to be
identified.
Unlike other serious illness, there is no register of
cases of depression or any other mental health disorder. Many people with the condition do not seek
help. Also, many people who have
symptoms of depression but whose symptoms fall below the cutoff level for a
formal diagnosis may be significantly disabled by their problems. These factors mean that the only reliable
statistics on the mental health of the entire population must come from
surveys. However few surveys have the
resources to collect the information required to make formal, clinical
diagnoses of mental health disorders.
The NDI attempts to bridge this gap.
It is based on only six short questions but is calibrated against
diagnoses of clinical depression in a large sample representative of the
Australian population. Using another,
independent sample of the population, it has been scaled so that the value of
100 is the benchmark value for
Confirmatory factor analysis was used to identify
items from the Australian version of the Kessler ‘K-10’
scale most strongly related to depression.
This scale had been administered in the large (N>10,000) National
Survey of Health and Wellbeing. This survey
included also an interview that yielded diagnoses of depression according to
DSM-IV criteria so the chosen items could be ‘calibrated’ against clinical
diagnoses. Factor scores were calculated
for each respondent, locating them on a depression ‘dimension.’ A problem with these scores is that they have
no intuitive meaning – it would difficult to look at the mean factor score of a
group and say whether it represented high or low levels of depression. To overcome this limitation, a transformation
was developed that yielded values that can be readily interpreted. Using a logistic regression model relating
factor scores to the diagnosis of depression, estimated probability of being a
‘case’ of depression was estimated.
These values were calculated for respondents from another large sample
representative of the Australian population – the ABS National Health Survey
(2001). Individual probabilities were
then divided by the average for this sample (0.048) and multiplied by 100. This means that individual values can be
interpreted as risk of depression relative to the Australian population. Values of 100 are ‘average’ risk, values
greater than 100 represent higher risk of depression. The value of the index for a group is simply
the average of the individual values.
Although the steps may seem convoluted and complicated, they make maximum use of a very small amount of information and produce an index that, we hope, everyone will be able have an intuitive feel for.
The NDI has been developed to track changes in the
population and groups over time and to enable groups within the population to
be compared and groups who may be at elevated risk of depression to be
identified. Below are two examples of
its use.
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NDI values for income groups |
NDI values employment status |
The graph on the left shows NDI for men and women grouped according to income. The NDI declines as income increases. For women the NDI is generally higher than for men in all but the lowest income groups. The graph on the right shows that people who are employed have a better (lower) NDI than the unemployed and those not in the labour force. These patterns correspond to the established epidemiology of depression – while they may not tell us much that is new about depression, they demonstrate that the NDI behaves as it should.
The National Depression Index describes the status of the population or groups of people. It is not a method of diagnosing depression in an individual. It is certainly true that people with high values on the NDI items are likely to be depressed, but the information collected to calculate the NDI is not detailed enough to make an assessment of the status of someone who may be suffering from depression. For more information about depression and diagnosis, see the beyondblue web site.
The
Kessler K-10 is a brief instrument and easy to administer. Full details of the
We hope
that researchers will include it in projects so that the NDI will be available
from many samples and in many situations.
Although it is necessary to administer only six of the 10 items in the
K-10 to calculate the NDI, we recommend including all 10 items whenever
possible. It will then be possible to
calculate values for the full scale and to compare these with other research
using this scale.
NDI scores are based on a transformation of factor scores calculated from the six K-10 items on which the index is based. Factor scores are used in preference to simply summing items. While the factor score and item sum are highly correlated, the former takes into account the discriminatory power of each item and its location on the underlying factor or dimension and is thus able to achieve finer degrees of discrimination between individuals (see graphs below).
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Histogram of NDI Item Sum Scores |
Histogram of NDI Factor Scores |
A substantial problem with using factor scores is that special software is required to estimate them for each respondent. In the article, we used Mplus, a program designed to undertake factor analysis of ordinal data. As few potential users of the NDI will have access to this program, we have devised a method of obtaining factor scores and NDI values that is very simple and requires only the use of SPSS. Instructions, syntax and data files are contained in the file NDI.zip.
Once NDI values
have been calculated for individuals in a group, the value of the Index for the
group is simply the average of the individual values.
Because
individual NDI values were constructed to be interpretable as relative risk of
depression compared to the Australian population, their distribution can be
expected to be highly skewed in many groups: people who respond highly
positively to multiple items on the K-10 are many, many times more likely than
average to suffer from depression and thus their relative risk will be
correspondingly high. When the NDI is
calculated for a small sample, the presence of one or two frankly depressed
individuals may dramatically influence the value of the index. Thus, care is required in interpreting index
values in small samples. This is no
different to the calculation of prevalence estimates in small samples. Because of the extreme values that may occur,
individual index values are not recommended for use in statistical
analyses. It would be reasonable and
preferable to use the factor scores.
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