In a publication in BMC Psychiatry, researchers proposed an NIA to gain a better comprehension of the complexity of clinical phenotypes in MDD. The authors noted that their proposed NIA could assist in the recognition of risky behaviors, in primary and/or secondary prevention, as well as in monitoring treatment and confirming its effectiveness.
“To better explain the complexity of clinical phenotypes in MDD and the relationship between symptoms and pharmacological treatment in these patients, we propose Network Intervention Analysis, an extension of the network analysis model, which conceptualizes mental disorders as the product of interplay between symptoms,” the authors wrote.
The authors noted that their proposed NIA could assist in the recognition of risky behaviors, in primary and/or secondary prevention, as well as in monitoring the treatment and confirming its effectiveness.
The strength of the NIA noted by the authors is its ability to explain how efficacious a specific treatment is in improving the various symptoms and/or domains and how this result can be distributed throughout the network.
The authors wrote, “The paper aims to identify the interaction and changes in network nodes and connections of 14 continuous variables with nodes identified as ‘Treatment’ in a cohort of MDD patients recruited for their recent history of partial response to antidepressant drugs. The study analyzed the network of MDD patients at baseline and after 12 weeks of drug treatment.”
The results revealed that at baseline, the network showed separate dimensions for cognitive and psychosocial affective symptoms, with cognitive symptoms robustly affecting psychosocial functioning. Additionally, the Montreal Cognitive Assessment [MoCA] tool was recognized as a potential psychometric tool for assessing cognitive deficits and monitoring treatment response.
After drug treatment, the results also revealed that the NIA showed less interconnection between nodes. This, they wrote, suggests greater stability, with antidepressants taking a central role in driving the network and at follow-up, enhancing affective symptoms with the highest predictability for the Hamilton Depression Rating Scale.
The authors wrote, “Our results suggest that MoCA might represent a novel and interesting psychometric tool for a better evaluation of cognitive deficits in MDD and to monitor the clinical response to pharmacological and non-pharmacological treatments.
“NIA allows us to understand not only what symptoms enhance after pharmacological treatment, but especially the role it plays within the network and with which nodes it has stronger connections,” concluded the authors.
The authors also concluded that NIA could be instrumental in identifying specific symptoms targeted for intervention and possible pathways for clinical intervention that may have the optimal effect on overall symptom severity. Lastly, the authors indicated that NIA represents a promising, innovative approach to better comprehend and treat complex mental disorders like MDD.
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