User:Kylie McGilvray/sandbox

Depression has been found to play a major role in the onset of many cognitive disorders, such as vascular dementia and Alzheimer’s disease, which generally occur in people over the age of 65 (de la Vega, Pina, Peralta, Kelly, and Giner, 2018). It has also been shown to have a connection to disorders that are generally diagnosed at a young age, such as attention deficit hyperactivity disorder (ADHD), as 17.6% of bipolar patients also meet the criteria for ADHD, with there also being a greater risk for the diagnosis of bipolar disorder when major depressive disorder is comorbid with ADHD (Vega et al, 2018). The specificity hypothesis, which identifies the perception of definitive, unavoidable loss as the main factor that distinguishes mood disorders from other emotional disorders, has largely lined up with the research, as depressed individuals have been found to think less of themselves and be much more pessimistic about life than non-depressed individuals (Haaga, Ernst, and Dyck, 1991). While the majority of this research on clinical depression has not tested the extent to which negative cognitions occur automatically, subclinical dysphoria research has suggested that the processing of negative information about the self is indeed automatic (Haaga et al, 1991).

Neuroscientists Julia O. Linke and Nancy E. Adleman constructed the White Matter Microstructure in Pediatric Bipolar Disorder and Disruptive Mood Dysregulation Disorder and evaluated two hypotheses that addressed abnormalities in WM microstructure presented in youth characterized by chronic irritability which compared healthy and bipolar patients along with abnormalities in WM microstructure with associating the symptom dimension within BD and DMDD (Linke & Adleman,etc., 2020, p. 1136). Variables consisted of age and sex as indepdent variables and a calculation of a ANCOVA analysis across three groups were analyzed when calculating the patients data with covariance (Linke & Adleman,etc., 2020, p. 1138). By extracting and evaluating these values across the peak voxels of the data clusters found from the post HOC tests, findings were then related to the symptom dimension of irritability which lead to discovering a mean each participant's Spearman correlation and coefficients (Linke & Adleman,etc., 2020, p. 1138). Researchers found within the first goal that there was significantly lower FA in the corticospinal tract in BP vs. DMDD; significantly lower FA values within the anterior corpus callosum that were derived mainly by increased RD in BD vs  healthy volunteers; as well as a widespread reduction in FA from radial diffusivity in BD vs healthy volunteers (Linke & Adleman,etc., 2020, p. 1138). Researchers as well discovered that within their second hypothesis, FA values within the patients anterior corpus callosum were evaluated to be negatively associated with the irritability for both comparing patient groups whereas researchers as well observed a positive link between FA in the posterior corpus callosum and irritability within the DMDD strictly (Linke & Adleman,etc., 2020, p. 1139).

Different factors of mood disorders affect different aspects of the social life. (Vega, Pina, Peralta, Kelly, and Giner, 2018). People experience different behaviors in different stages of mood disorders which includes the inability to function, sleep, developing depression, weight changes, irritability, mania and more (Vega et al. 2018). In Bipolar Disorder (BD) and Borderline Personality Disorder (BPD) a person may face suicidal thoughts and different mood symptoms (Vega et al 2018). Then in Seasonal Anxiety Disorder (SAD) an individual may be abusing alcohol (Waraich, Goldner, Somers, and Lorena, 2004). Most mood disorders deal with major depression and instability that causes people to behave in ways that they would not normally (ADHD, DMDD, MDD, MADD) (Vega et al 2018). All mood disorders are associated with cognitive, perceptual disturbance, and a few that also deals with delusions, hallucination that affects the daily life of a patient (Vega et al. 2018).

Social media use has been affecting mood disorders for decades, especially within the millennial generation. Instead of social media fulfilling and enhancing human need for social connection, it has produced a fairly new type of stressor, FOMO, the abbreviation for, fear of missing out, which is the anxiety of missing out on an exciting events are currently happening, seen through social media posts or websites. Although FOMO is not a disorder listened in the DSM V, it contributes to individuals experiences with anxiety and depression (Watson and Sawson, 2017). The term FOMO was first mentioned in 1966, by Dr, Dan Herman, later being defined by Patrick James McGinnis in 2004 (Divya and Mandeep, 2019). Over time this disorder seems continuously impacted the mental health of many, and is not limited to millennials like many assume, producing increased rates of depression, loneliness, anxiety, social media use, distracted driving, and has lowered levels of life productivity and satisfaction (Watson et al, 2017). The symptoms of FOMO consist of, the anxiety of not being part of a group, a fear of rejection and loneliness, comparing oneself with others, and jealousy of others successes (Luca, Linian et al., 2020). FOMO becomes more intense for individual who are predisposed to lower levels of ability, autonomy and integrity. In 2012 a study was performed, concluding that over 56% of the individuals felt effects affiliated with FOMO (Divya et al., 2019). To help avoid and limit FOMO, doctors encourage individuals to unplug or limit social media use; which numerus apps can help with. Other solutions such as serotonin reuptake inhibitors treatments and behavioral therapy are also options for individuals struggling from FOMO (Watson et al., 2017)

Divya, Arora, and Kaur Mandeep. “Detach out to Attach on Everything: A Study on Relationship between Personality and Fear of Missing out (FoMO).” Indian Journal of Health & Wellbeing, vol. 10, no. 10-12, 2019, pp. 317–323.

Luca, Liliana, et al. “The FOMO Syndrome and the Perception of Personal Needs in Contemporary Society.” Brain. Broad Research In Artificial Intelligence And Neuroscience, vol. 11, no. 1Sup1, 2020, pp. 38–46., doi:10.18662/brain/11.1sup1/27.

Watson, K., & Slawson, D. C. (2017). Social Media Use and Mood Disorders: When Is It Time to Unplug? American Family Physician, 96(8), 537–539.

de la Vega, D., Piña, A., Peralta, F.J. et al. (2018). A Review on the General Stability of Mood Disorder Diagnoses Along the Lifetime. Current Psychiatry Reports 20:29, 1-10.

Haaga, D. A., Dyck, M. J., & Ernst, D. (1991). Empirical status of Cognitive Theory of Depression. Psychological Bulletin,110 (2), 215-236.

Linke, J. O., PhD, Adleman, N. E., PhD, Sarlls, J., PhD, Ross, A., BA, Perlstein, S., BA, Frank, H. R., BA,. . . Brotman, M. A., PhD. (2020, October). White Matter Microstructure in Pediatric Bipolar Disorder and Disruptive Mood Dysregulation Disorder. Retrieved 2020, from https://keene.illiad.oclc.org:2052/illiad/illiad.dll?Action=10&Form=75&Value=72126