The implications of the present research suggest there may be other factors associated with memory that are impacting on relationships between depression and memory for both younger and older adults. The advantage of studying both age-groups together is the differing effects of depression on memory can be observed and compared. There were trends towards age-based interactions for some tasks in which factors such as depression, anxiety, stress, and visual processing speed had different effects for the younger and older adults. Research focussing on these differences is important as it cannot be assumed changes seen over adulthood apply in later life.
Far more pressing than the implications of the ageing process and their contributions to memory functioning in depression, are the implications pertaining to the theoretical constructs of depression, anxiety, and stress. Quite clearly, these constructs are not independent of one another; in fact, they are strongly correlated. The considerable overlap among these constructs coupled with the somewhat weak effects each has on some types of memory, resulted in a highly complex and sometimes confusing set of results. High correlations between measures of these constructs are not new to the present study. As noted earlier (see Chapter 5), two common measures of depression and anxiety, the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI) have correlations ranging from r = .48 to .63 (Beck et al., 1988; Fydrich et al., 1992; Hewitt & Norton, 1993). The State-Trait Anxiety Inventory (STAI) is well known for inadvertently measuring depression, especially the trait scale (Balon, 2005). Bieling et al. (1998) compared the STAI-T to other measures of depression and anxiety. A higher correlation was found between the STAI-T and the BDI than for the BAI (r = .72 and .42, respectively).
In order to start accounting for the high correlation between depression and anxiety, Clark and Watson (1991) argued for a tripartite model consisting of depression, anxiety, and an element they called general affective distress. They
looked at different measures of both depression and anxiety, including self- report measures and clinical rating scales. In reviewing studies of the psychometric properties of depression and anxiety measures, they found the presence of anhedonia (for depression) or physiological hyperarousal (for anxiety) discriminated between depression and anxiety. What they also found was the general affective distress component contributed towards depressive and anxious syndromes, but did not differentiate either condition from the other.
The results from the present study support a move back towards models such as the tripartite model, to explore a higher order construct, such as that of general affective distress, which may link depression, anxiety, and stress. Without such a theoretical shift, research into the cognitive impact of depression, anxiety, and stress will continue to be inconsistent and somewhat futile. At present, when one is considering depression as an independent variable, one cannot be sure the outcomes obtained are purely a function of depression level. The present results strongly suggest results will be due in part to anxiety and stress levels. Methods such as multiple regression could be employed to partial out the effects of anxiety and stress to give an experimentally “clear” picture of depression and its relationship to memory. However, this would have no ecological validity or clinical applicability because of the strong relationships between these three factors. By partialling out anxiety and stress, elements of the effect of depression may also be partialled out.
Sitting alongside the issue of related constructs and high correlations between measures of depression, anxiety, and stress, are the sometimes weak correlations among test instruments purporting to be measures of the same construct, for example, depression. If two depression tests correlate, say, at r = 0.7 only approximately 50 % of the variance is shared by the two tests. Such differences in scales may yield big enough differences to delete a small effect, or make a barely significant result non-significant. Future research needs to come
to grips with the overlap between tests of differing constructs, as well as the potential effects of using different tests and comparing the effects to previous research. Research and reviews need a greater level of stringency in how constructs such as depression are defined, and what tests are used to measure depression (or anxiety, stress, etc.). One way forward would be to compare results across studies only when the same scale (test instrument) is used to assess the level of depression.
In a similar vein, there exist multiple tests of, for example, working memory. These tests share the same problem as the constructs discussed above; that is, the correlations among the different measures can be quite low, suggesting that the tests are not necessarily assessing the same thing (Conway et al., 2002). Thus, it is quite possible that using one particular test of working memory and one particular test of depression will yield a set of results markedly different from what would have been obtained with different tests of depression and working memory. Added to this confusion is the fact that depression may contain elements of stress and anxiety. When one considers previous research on memory and depression, taking into account such difficulties, it is easy to understand why results have been so inconsistent.