Benefits in using a dimensional approach also become to light when discussing diagnostic utility. Diagnostic utility can be defined as the extent to which a model is useful or helpful in assisting clinical treatment decisions (Verheul, 2005). Utility is extremely low when only considering a categorical anxiety diagnosis. In the context of treatment, each individual requires specific tailored treatments to target differing symptoms and underlying etiological causes. As mentioned earlier, a categorical approach may be useful for providing diagnoses, however, accurate placement into a disorder category does not include sufficient information or enough guide lines for treatment.
Particular anxiety disorder categories may have specific therapies that work better, however due to missing information, treatments cannot be tailored to suit the differences of each individual. Not only is there an absence of knowledge on symptoms and severity, categorical approaches also doesn't take into account different etiological factors underpinning the development of symptoms or course of anxiety. A variety of different underlying mechanisms may be involved in the pathogenesis of symptoms. For example, anxiety disorders can develop as a result of trauma, such as for those who have endured abuse or witnessed traumatic events.
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Stress may be involved, including work stress, financial stress, or the stress that comes with health conditions and illnesses. Biological factors including changes in brain functioning can contribute, as well as family history and genetics, or psychological factors; specific personality types can be more prone to anxiety disorders than others. Dimensional model, such as RDoC, can be used to assess anxiety disorders in a different way, and find underlying causes based on dimensions of observable behaviour and neurobiological measures. Through RDoC, anxiety symptoms are seen as falling along different dimensions, such as cognitive processes and reward systems. Mood, social interactions, memory and attention, etc, are also analysed with traits ranging from ‘normal’ to ‘extreme/abnormal’.
To clarify or pinpoint underlying causes of anxiety, imaging is often done, as well as genetic and neuroscientific analysis, and behavioural and clinical studies. Rather than categorically labelling the disorder, dimensional approaches can create a whole symptom profile. However, limitations exist when only using a dimensional model as well. As anxiety is viewed as distributed along a continuum, it is hard to determine one point or a specific score to place the cut-off where normal anxiety becomes abnormal enough to diagnose as an anxiety disorder. Moreover, there may be frequent or extreme changes to scores in dimensional measures, either as a part of the natural course of anxiety disorders, or in response to treatment. Therefore it may not be appropriate to use dimensional measures for diagnosis.
Thus, there are both benefits and limitations when utilising dimensional approaches to assess anxiety disorders. In regards to the pros and cons of both categorical and dimensional approaches, as well as the reliability, validity and utility of an anxiety disorder diagnosis, there are a few recommendations that could be made in regards to future treatment. As categorical and dimensional approaches to conceptualising and assessing anxiety disorders can work complementarily to each other, with benefits making up for each other’s limitations, rather than just using one or the other, the two approaches should be used in tandem to tailor the most effective treatment for each individual. Categorical analysis can tell gist of each patient’s situation through reliable diagnosis, while dimensional assessments increase diagnostic validity and clinical utility through detailed information about symptoms, severity and underlying etiological causes.
For example, within the DSM-5 category, there are different types of anxiety disorders, including panic disorder, specific phobias, generalised anxiety disorder, agoraphobia, social anxiety disorder, etc. All disorders share features of fear, anxiety and related symptoms, however are all slightly different, with differing situations or objects that can trigger an anxious response, therefore need different treatments with specific targets. Many therapies exist in order to help people deal with the varying symptoms and long ranging effects of different anxiety disorders. As categorical diagnosis gives an idea of the gist of problem, it also provides an idea for which treatment may be more suited. However, dimensional details are necessary to help customise treatments to suit each person. For instance, different forms of psychosocial therapies such as cognitive behavioural therapy (CBT) counselling sessions, motivational therapies and cognitive restructuring of dysfunctional thoughts may suit some disorders but not others. For example, a form of exposure therapy CBT may work best for specific phobias however are not so helpful in treating generalised anxiety. However, those are just ideas, without much utility.
As mentioned earlier, dimensional details must be combined with categorical diagnoses. Varying severities of disorder impact require different speeds of treatment, as well as different amounts and intensities of treatment, determined through dimensional assessments. Where needed, psychopharmacological measures, such as the use of antidepressant medication including selective serotonin reuptake inhibitors (SSRIs) or serotonin and noradrenaline reuptake inhibitors (SNRIs), depressant medication such as benzodiazepines, or beta blockers, can be combined with psychosocial talking treatments, or used on its own, to help with various physiological impacts from anxiety.
Thus categorical and dimensional approaches should be used in tandem to provide the most effective and customised treatment. There are benefits and limitations in both categorical and dimensional approaches to anxiety disorders. Approaching anxiety disorders categorically through models such as the DSM-5 allow the accurate sorting of disorders, as well as consistent, reliable diagnoses and efficient communication between clinicians, however lacks the validity and utility for effective clinical practice. While approaching with dimensional models such as RDoC produce potentially inconsistent and unreliable diagnoses, the diagnostic analysis of symptoms, severity and underlying etiological causes of disorder pathogenesis supply necessary details to provide better diagnostic validity and clinical utility, as well as come up with a specific treatment plan tailored for each individual.
Therefore pros and cons exist in both categorical and dimensional approaches. Recommendations were then subsequently made on how categorical and dimensional approaches can used in tandem to increase the reliability, validity and utility of future anxiety disorder assessment and treatment.
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