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Issues in Interdisciplinarity 2020-21/Evidence in the Research and Diagnosis of Depression

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Introduction edit

Depression is a mental illness that causes a constant feeling of dejection and low mood, which will strongly influence the daily lives of those affected.[1] Nearly 1 in 10 people suffer from it,[2] and the number of people touched increased considerably during the COVID-19 pandemic.[3] Consequently, it is an important societal issue that requires research to understand its causes and prescribe an effective treatment. To achieve this, one must understand the development of this disease: it can be triggered by many factors of different origins which vary from one person to another.[2]Thus, studying these evidences in the diagnosis of depression through the lens of different disciplines will allow us to obtain explanations on the implementation of the multiple treatments for this illness and to recognize how these evidences, while united, could result in a more accurate diagnosis.

Disciplines Perspectives edit

Biology edit

Biology as a discipline is concerned with the study of living organisms[4]. From this perspective, evidence relating to depression is collected at different levels: the molecular level, as well as the circuitry in neural systems.[5]

The study of depression concerning the circuity of neural systems often focus on the prefrontal cortex, amygdala and hippocampus which are considered to be responsible for maintaining emotional stability.[6] Malfunctions within these areas are seen to be key to understanding the neurochemistry of depression. Quantitative evidence is collected with neuroimaging techniques such as magnetic resonance imaging and functional fMRI.[6] These techniques provide visualisations both anatomically and functionally,[7] allowing for the connection of the aforementioned brain sections factors towards depression.

In regards to the study of molecular mechanisms, most have focused upon neurotransmitters, which act as chemical messengers.[8] Depression has often been connected towards imbalances concerning these neurotransmitters.[8] Evidence for their study is largely quantitative, with methods ranging from the measurement of levels to advanced imaging techniques involving radiolabelling.[9]

In regards to treatment, techniques are not yet sophisticated enough to diagnose on an individual case basis.[10] However, the study of neural interconnections has allowed for the creation of medical depression treatments.[11]For example, antidepressant medications to treat depression are known to act upon neurotransmitters to alleviate depression.[8]

Psychology edit

File:Beck test.png
Beck's depression questionnaire

Psychology is the study of the human mind and how it influences the behaviour of a person.[12] One of the approaches to collect evidences is through interviews based on open questions between a patient and a psychiatrist.[13] These qualitative evidences can then be used to build a coherent list of the depressive symptoms patients frequently exhibit. This list is found in the DSM-5, a renowned classification used for current diagnosis and future research.[14] The Beck Depression Inventory will also be created from these evidences and the theory of cognitive distortion. It is a questionnaire of 21 questions that will measure the severity of a patient’s depression.[15]

To validate newly observed symptoms, studies are conducted comparing patients diagnosed with depression to a control group.[16]
The information generated from such studies can then be statistically analysed in order to provide quantitative evidence on the prevalence of particular symptoms but also psychological causes of depression, such as stress. [17]This quantitative analysis is next combined with findings from the aforementioned forms of qualitative evidence. Connections are then made between the different forms of evidence. In turn, this enables the diagnosis of future patients to be done in a more accurate manner. 

These studies have also proven that the etiology of depression is largely defined by the diathesis–stress model. Some people are thereby more susceptible than others to depression.[18]

Sociology edit

 
Sociologist conducting a study using participant observation

Sociology is a discipline which studies the interactions between individuals and their environment.[19] According to the sociologist George Brown[20] "depression is essentially a social phenomenon in the sense of being usually the result of a person's thoughts about his or her world". Thus, sociology is concerned with depression as a disease that can be explained with aspects of social life.

There are two types of sociological studies that are relevant to depression. The first examines the social elements that cause or enhances the probability of developing a mental illness, and the second looks at how society responds to these illnesses.[21] In the course of their studies, sociologists use several methods. To obtain quantitative evidence, in order to better understand the social conditions that favor the appearance of these diseases, they will identify specific groups of individuals and question them through interviews or surveys. In addition, sociologists can also go into the field to obtain qualitative evidence through observations or by interacting with the group studied.[22] By analyzing the results, this will allow them to target social factors that are highly correlated with incidents of depression, and to know the responses of the population to depression, how they define the disease and whether they choose to be cured and in which ways, thereby, to be able to guide the search for treatments.[22] According to the evidence gathered, the best way to fight depression for sociologists would be to put in place social policies to reduce the pressure on the individuals concerned and to provide more support.[21]

Evaluation of Evidences edit

Given how severe depression is, the issue of its diagnosis extends beyond simply accurately diagnosing depression in a patient, due to the wide range of symptoms between patients and factors for the disorder. However, despite major studies being conducted on this subject, the diagnosis of depression is often misunderstood, with the need for more communication between related disciplines.

Biological evidence is crucial for diagnosis as well as the development of treatments. However this approach to depression includes several limits. Firstly, the existence of certain anomalies within the brain do not necessarily imply they were involved in the development of depression within patients. Therefore, it can be difficult to draw causal relationships between particular brain structures and incidents of depression. Moreover, there are multiple types of depression and levels of severity which are not distinguishable at the biological scale.[23] The distinction between them can only result from a psychological approach. Nevertheless, the psychological studies are based on the patient’s word which can not be completely reliable and objective. Some people tend to self-diagnose, resulting in their responses to questionnaires being biased by their own interpretation of their condition.[24] Concerning quantitative evidences in psychology or sociology, an issue also lies in how they tend to result in wide spread generalisations which do not take account  the specificity of individual experiences within the area of mental health which can be a hindrance to the progress of research and diagnosis.[21]

With each discipline having difficulties in tackling the diagnosis of depression, it is important for interdisciplinary dialogue to be conducted by combining the different forms of evidence within each discipline in order to build complex models to group biological and demographic parameters which can create diagnosis subjects and connect them to different treatments. For example, evidence of biological predispositions and demographic correlations are helpful in determining subtypes within depression. However, while these models have been attempted, there have been inadequate or unsuccessful replication studies.[25] This can potentially be attributed to the different areas of focus within each discipline, making it hard to integrate all forms of evidence into one cohesive model.

References edit

  1. ↑ Mayo Clinic, 2018. Depression (major depressive disorder). [Online]. Available from: https://www.mayoclinic.org/diseases-conditions/depression/symptoms-causes/syc-20356007
  2. ↑ a b Parker C, Depression: clinical features and diagnosis. Clinical Pharmacist. 2012; 4(1): 222-226
  3. ↑ Robinson j. Mental health conditions Rate of depression in Great Britain doubled during COVID-19 pandemic, ONS figures reveal. The Pharmaceutical Journal. 2020[Online] Available from: https://www.pharmaceutical-journal.com/news-and-analysis/news/rate-of-depression-in-great-britain-doubled-during-covid-19-pandemic-ons-figures-reveal/20208279.article?firstPass=false
  4. ↑ Rogers K., Britannica. [Online]. Available from: https://www.britannica.com/science/biology.
  5. ↑ Carter M., Jennifer c shieh. Guide to Research Techniques in Neuroscience.Academic Press; 2010.
  6. ↑ a b Palazidou, E. The neurobiology of depression. British Medical Bulletin. 2012;101(1): 127–145.
  7. ↑ Wang J, Yang T, Thompson P, Ye J. Sparse models for imaging genetics. Machine learning and medical imaging. 2016:129-151.
  8. ↑ a b c Nemade, R. Gracepoint Wellness. Biology of Depression-Neurotransmitters [Online]. Available from: https://www.gracepointwellness.org/5-depression-depression-related-conditions/article/12999-biology-of-depression-neurotransmitters
  9. ↑ Gryglewski, G, Lanzenberger, R, Kranz, G, Cumming, P. Meta-Analysis of Molecular Imaging of Serotonin Transporters in Major Depression. Journal of Cerebral Blood Flow & Metabolism. 2014; 34(7).
  10. ↑ Saggar, M, Uddin, L. Pushing the Boundaries of Psychiatric Neuroimaging to Ground Diagnosis in Biology. ENeuro. 2019;6(6).
  11. ↑ Harvard health publishing. What causes depression? [Online]. Available from: https://www.health.harvard.edu/mind-and-mood/what-causes-depression.
  12. ↑ Oxford Learner's Dictionaries [Internet]. Oxfordlearnersdictionaries.com. 2020. Available from: https://www.oxfordlearnersdictionaries.com/
  13. ↑ Williams C., Rittman M., Boylstein C., Fairloth C., Haijing Q. Qualitative and quantitative measurement of depression in veterans recovering from stroke. Journal of Rehabilitation Reasearch & Development. 2005;42(3):277-290
  14. ↑ Kupfer D, Regier D, Kuhl E. On the road to DSM-5 and ICD-11. European Archives of Psychiatry and Clinical Neuroscience. 2008;258(5):2-6.
  15. ↑ Jackson-Koku G. Beck Depression Inventory. Occupational Medicine. 2016;66(2):174-175.
  16. ↑ Weingartner H, Cohen R, Murphy D, Martello J, Gerdt C. Cognitive Processes in Depression. Archives of General Psychiatry. 1981;38(1):42.
  17. ↑ Van Praag H. Can stress cause depression?. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2004;28(5):891-907.
  18. ↑ Arnau-Soler A, Adams M, Clarke T. A validation of the diathesis-stress model for depression in Generation Scotland. Translational Psychiatry. 2019;9(25)
  19. ↑ Geneso. The Sociological Perspective. Sociology. [Online] Available from: https://www.geneseo.edu/sociology/about
  20. ↑ George W Brown. Depression — a sociologist's view. Trends in Neurosciences. 1979; 2(1): 253-256
  21. ↑ a b c Horwitz A. An Overview of Sociological Perspectives on the Definitions, Causes, and Responses to Mental Health and Illness. A Handbook for the Study of Mental Health.Cambridge University Press. 2012:6-19.
  22. ↑ a b Course Lumenlearning. Research Methods. Introduction to Sociology. 2020[Online] Available from: https://courses.lumenlearning.com/sociology/chapter/research-methods/
  23. ↑ Gotlib I, Hamilton J. Neuroimaging and Depression. Current Directions in Psychological Science. 2008;17(2):159-163.
  24. ↑ Kessler D, Lloyd K, Lewis G, Gray D, Heath I. Cross sectional study of symptom attribution and recognition of depression and anxiety in primary care. BMJ. 1999;318(7181):436-440.
  25. ↑ Dunlop, B, Mayberg, H. Neuroimaging Advances for Depression. Cerebrum : the Dana forum on brain science. 2017;1(1).
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