HADS

As previously discussed, mood was assessed using the Hospital Anxiety and Depression Scale (HADS). The HADS is a 14 item questionnaire that documents common depressive and anxiety symptoms (7 items for each). The two scales are correlated but the two factor structure of the scales has been confirmed [Spinhoven 1997]. Each item is scored with a 4-point verbal rating scale and hence a maximum score for either anxiety or depressive symptoms is 21. Individuals are asked to fill the form so as to reflect their feelings over the previous week.

This assessment was designed specifically for individuals with medical illness and physical limitations by Zigmond and Snaith in 1983 [Zigmond 1983]. It avoids over-dependence on physical symptoms of depression and focuses on the psychological manifestations [Mykletun 2001]. It has been used extensively in many studies across different population and illness groups and been translated into several languages.

Although its name may suggest use within hospitals, in fact the HADS was designed with a view to use in community settings as well and has been validated in a large number of different population groups including many different conditions, such as cancer, heart failure and a number of neurological disorders. It has been used and validated in TBI [Dawkins 2006, Al-Adawi 2007, Whelan- Goodinson 2008]. Comprehensive reviews of the HADS are available [Hermann 1997, Bjellend 2002].

The form can be self-filled by an individual in a matter of a few minutes. A small number of patients may require some assistance by a relative or by the clinician to help e.g. patients unable to read or who require further explanation of the question items. A particular advantage of the HADS, apart from the short time taken to fill in is that it has been shown to be equally effective as more detailed or time-consuming tools in the diagnosis of depression [Whelan-Goodinson 2008]. It also minimises the confounding factor of somatic symptoms, many of which will overlap with the diagnosis of TBI, e.g. poor sleep, weight loss. Only one of the responses in the HADS (“I feel that I am slowed down”) would correspond to a somatic symptom or be common in individuals with a TBI alone, quite apart

from an added diagnosis of depression. A common problem with many of the other tools used to evaluate mood is that they have a high proportion of trans-diagnostic symptoms which make evaluation of mood over and above the presence of TBI very difficult. Other depression measures suffer from this “floor” effect as discussed in Chapter 1.

A number of different cut-offs have been used by studies but the original paper used a cut-off score above 8 [Zigmond 1983]. This has also been shown to have the best discriminant value and trade-off between specificity and sensitivity [Bjellend 2002, Hermann 1997]. Using this cut-off, Lowe found a sensitivity of 0.85 and specificity of 0.76 [Lowe 2004]. Some have used a higher level of cut-off (10/11) to define severe depression [Crawford 2001, Cameron 2008]. Use of this cut-off would undoubtedly improve specificity but has to be balanced against the lower sensitivity that would result. It is likely that many true cases would be missed at a higher cut-off.

The test can be easily repeated at intervals allowing monitoring of changes; this is particularly useful in assessing changes caused by intervention such as medication [Crawford 2008].

The internal consistency of the anxiety score varies from 0.8-0.93 and 0.81-0.9 for the depression score across a wide range of studies encompassing more than 60000 patients [Bjelland 2002]. The re-test value is very high and quoted as 0.91 after one month. This reduces with time but is probably due to changes in mood rather than the test reliability [Bjelland 2002, Lowe 2004].

A review of over 600 English publications found that the sensitivity and specificity were >0.8 for both. In TBI it was found that use of a cut-off at 8/9 results in a sensitivity of 0.66 and specificity of 0.88. For reference, this is comparable to the value of exercise ECG testing for the presence of coronary heart disease [Bjelland 2002]. The HADS has been noted to be better at diagnosing depression than non-psychiatrist physicians [Cosco 2012].

The accuracy of any test at diagnosing a condition depends on the presence of a “gold standard” test to compare against. The closest test in depression that approximates to this gold standard is the Structured Clinical Interview for DSM. In using this standard, Receiver Operated Characteristics curves indicated a best cut-off at 8/9 on the HADS for which the area under curve was 0.887 (95%

Confidence Intervals 0.84-0.91). The predictive power was 83% which compares very favourably to any other tests of depression [Herrero 1983].

The HADS has also been correlated positively to other measures of depression including PHQ-9 and BDI [Kroenke 2001, Cameron 2008, Revicki 2008].

There were two possible options for analysis of the HADS. Firstly, depression could be analysed as a linear outcome using the crude HADS scores (range 0-21). The advantage of such an analysis is that by preserving the whole score, analysis theoretically preserves the absolute scores allowing for better characterisation of the extent of depression an individual experiences. The alternative is to use a cut-off score to signify a case. For example, using a cut-off between 8 and 9, an individual with a HADS score of 9 would be considered depressed; at the same time an individual with a score of 17 would also be considered as depressed but presumably the much high score of the latter suggests that the extent of depression is much more significant. In a similar vein, a score of 8 would not be a case but the distinction between individuals with scores of 8 and 9 is likely to be small. Preserving the absolute scores would allow for this dimension of the data to be preserved in the analysis. Nevertheless it was felt that the use of a binary method would be more realistic and akin to clinical practice. This was after all, the aim of the project. This is because in a clinical setting, the decision as to whether an individual is depressed or not, is essentially a binary one. Subsequent decisions to treat follow a yes or no pattern. This was the rationale for classing depression as a binary outcome.