Factors of Stress Among Young Adults

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Introduction

Stress among young adults is a topic of increased interest among sociologists and health professionals. Today, stress is caused by numerous factors, and young adults need to be aware of them to develop sufficient coping mechanisms. For instance, a popular health-related website, WebMD (n.d.), claims that stress can be caused by low job satisfaction, increased workloads, financial insecurity, family problems, chronic illnesses, injuries, fear of uncertainty, unrealistic expectations, and many other factors. The performance of a country’s economic system is also a possible predictor of stress, as it may create a feeling of insecurity among citizens of the country. According to Lindström and Rosvall (2018), economic stress causes suicidal thoughts in young adults, children, and adolescents. At the same time, the favorable economic situation in a country may decrease the amount of stress by giving a sense of stability to the citizens. Considering this, it is crucial to investigate the relationship between economics and stress in young adults to acquire a deeper understanding of the matter.

Statement of Problem

The study will assess the correlation between stress in adults aged 25-35 and the economic well-being of a country. Stress is known to have a severe impact on the human body, including headaches, insomnia, depression, high blood pressure, and stomach ache (Yaribeygi et al., 2017). Stress may also cause erectile dysfunction, weaken the immune system, and increase the risk of heart attack (Yaribeygi et al., 2017). Therefore, knowing the reasons for increased stress is crucial for predicting the possibility of its complications and applying preventative measures. Previous research has shown that the amount of stress on young adults increases after economic crises, which can negatively influence their emotional well-being. Since the world faces a new financial crisis associated with the COVID-19 pandemic, the knowledge of the correlation between the economy and emotional stress is of vital importance. The knowledge can be used to predict the number of stress-related conditions and develop preventative measures to address them.

Significance of the Study

The present research will provide a significant contribution to understanding the predictors of stress. It will adopt a broad approach to the problem by assessing how different economic variables affect the amount of stress put on young adults. The study will use only objective data provided by the official resources, such as the National Institute of Health (NIH), the US Bureau of Labor Statistics (BLS), and the Centers for Disease Control and Prevention (CDC). Therefore, it is expected to provide an assessment of the correlation between the matters of interest with minimal risk of bias. The study will provide healthcare professionals, sociologists, and young adults the opportunity to predict the possibility of increased stress based on the economic situation in the country and develop appropriate coping strategies to mitigate the effects of stress on emotional health and well-being.

Literature review

Emotional stress among young adults is a widely discussed topic in the current literature. A study by Yaribeygi et al. (2017) explains in detail how stress affects the human body. According to the study, stress can cause different reactions in the body ranging from alterations in homeostasis to life-threatening effects and death (Yaribeygi et al., 2017). In particular, stress can be the reason for brain function complications, immune system problems, cardiovascular diseases, gastrointestinal issues, and endocrine system conditions (Yaribeygi et al., 2017). Therefore, the reduction of stress and the development of applicable coping mechanisms is of extreme importance for young adults to sustain physical and mental health.

The factors that contribute to stress can be divided into three categories, which are health-related issues, social problems, and economic factors. Among health-related factors, chronic conditions are often named as the most common stressors. According to Karantzas and Gillath (2017), adults require social support from friends and family to cope with the stress associated with chronic conditions. The support from care providers can also be helpful; however, healthcare workers are often overloaded and cannot dedicate enough time and demonstrate the needed affection to help adults cope with stress (Karantzas & Gillath, 2017). At the same time, sleep deprivation is also known to be a significant predictor of psychological stress. According to Schwarz et al. (2018), even though one sleepless night does not significantly contribute to emotional stress, repeated sleep deprivation can cause severe problems with psychological well-being. In summary, there are different health conditions and habits that can increase stress in young adults.

Among social problems, the most frequent stressors are job-related issues, such as low job satisfaction and increased workload. For instance, Khamisa et al. (2016) state that nurses experience a high level of job-related stress, which leads to deterioration in their physical and psychological well-being. The central reason for stress is emotional exhaustion, lack of support from peers, increased workload, and lack of rest (Khamisa et al., 2016). These factors lead to decreased job satisfaction and burnout (Khamisa et al., 2016). At the same time, emotional problems associated with the loss of a partner or divorce can contribute to stress in young adults. The study by Karantzas and Gillath (2017) states that the death of an intimate partner is among the most frequent stressors in the life of adults. Considering this information, it is vital to mitigate the consequences of social problems to avoid additional stress.

The economic factors of stress are also widely discussed in the current literature. Lindström and Rosvall (2018) claim that economic stress in childhood, which is identified as a decreased ability to pay the bills and buy groceries, is associated with increased stress in children and young adults. As a result, economic factors may cause suicidal thoughts, which is a sign of mental health problems. Kokaliari (2016) studied the amount of stress in citizens of Greece after the economic crisis in 2008. The research concluded that economic factors increase the amount of stress experienced by citizens (Kokaliari. 2016). The effect was most evident in single citizens, females, unemployed, and people with low income (Kokaliari. 2016). Gudmundsdóttir et al. (2016) conducted a population-based survey to determine how economic crisis affects adolescents. The results revealed that adolescents that do not have access to emotional support from their parents experience a significantly increased amount of stress, which can negatively affect their health.

Mucci et al. (2016) conducted a systematic review of articles that studied the impact of the economy on the amount of stress. The results revealed that “a rise in unemployment, increased workload, staff reduction, and wages reduction were linked to an increased rate of mood disorders, anxiety, depression, dysthymia, and suicide” (Mucci et al., 2016, p. 983). Therefore, it can be stated that an abrupt change in financial well-being contributes to stress and stress-related conditions mentioned by Yaribeygi et al. (2017).

In summary, the current body of knowledge provides extensive information on the correlation between stress and various social, economic, and health-related factors. However, even though contemporary literature found a significant correlation between macro-economics and stress among citizens, the body of knowledge lacks specific information about young adults in the US. At the same time, all the overviewed studies were cohort studies that included self-reported data, which may be biased. The literature review revealed no studies based on official objective data published by the US government, on CDC, NIH, and BLS websites. Therefore, the present research will close a considerable gap in knowledge concerning the correlation between economics and stress and improve the generalizability of findings of previous studies.

After reviewing the literature, it became evident that there should be a significant correlation between stress and economics. In the reviewed studies, common indicators of stress were depression, sleep disorders, and anxiety, while the indicators of economic well-being were unemployment rates, household incomes, and poverty rate. Higher unemployment rates and poverty rates are expected to lead to an increased number of cases of depression, anxiety, and insomnia. At the same time, a higher median household income is expected to correlate with the aforementioned conditions negatively.

Theoretical framework

The theoretical framework of the present paper is the cognitive activation theory of stress (CATS). The theory views stress as a unity of four aspects that can be measured separately. The four elements of stress are stress stimuli, stress experience, stress response, and feedback from the stress response (Ursin & Eriksen, 2004). According to the theory, a stress stimulus is an object or an action that can potentially cause alarm or arousal of the nervous system (Ursin & Eriksen, 2004). In the present paper, the stimulus is the economy of the country measured in unemployment rates, median family income, and poverty rates. CATS claims that all the stimuli are processed by the human brain, which filters all the outside information and decides to which of the stimuli it needs to respond (Ursin & Eriksen, 2004). Therefore, not all stress stimuli cause stress experience, which is a realization of the importance of a stimulus (Ursin & Eriksen, 2004). The general response to stress experience is “a non-specific alarm response, eliciting a general increase in wakefulness and brain arousal, and specific responses to deal with the reasons for the alarm” (Ursin & Eriksen, 2004, p. 571). The final link is the realization of stress, which is called feedback from stress experience, which adds to the feeling of being stressed.

CATS supposes that stress response and feedback from stress experience are healthy reactions to stress stimuli. The alarm occurs when there is a discrepancy between what is expected, or the set value, and the reality, or the actual value (Ursin & Eriksen, 2004). The unpleasantness of the alarm is not a health threat in its nature, as it encourages a person to act to eliminate the stress factor. However, sustained exposure to the alarm caused by stress response may lead to physical and psychological complications, such as depression, anxiety, and insomnia, which are measured in the present research as response variables.

The theory has the potential to explain how economics affects the prevalence of stress in young adults in the US. The economic situation in a country is a continuous stress stimulus that may cause sustained arousal of the nervous system. As explained by CATS, repeated exposure to stress stimuli causes discomfort and poses a significant threat to the emotional and physical well-being of young adults. The theory is also helpful for defining coping mechanisms to fight depression, anxiety, and sleeping disorders. In particular, it proposes distortion of expectations (the set value) so that it does not differ with the actual value. In summary, CATS seems to be an appropriate theory to guide the present research.

Methodology

Research Design

The present research will use only secondary data sources without gathering any primary data from surveys or interviews. The secondary data sources are databases of governmental services, such as CDC, BLS, and NIH. The research will also use scholarly journal articles, books, and governmental reports. The central idea behind the experiment will be to synthesize historical data about the number of depression, anxiety, and sleeping disorder cases and analyze it against unemployment rates, median family income, and poverty rates in the US. The data is expected to provide significant insights into the correlation between stress and the economy.

Data Collection

As the research design does suppose the use of primary data, the data collection procedure will include internet search for relevant historical data. As all the information is expected to be in open access, no special permission is required to access the databases. At the same time, as the research is not expected to use the information received from human subjects, no informed consent is required. The approval of IRB is also not needed as the study is not expected to experience difficulties with ethical questions. After gathering all the relevant data, it will be edited to a unified format in a Microsoft Excel spreadsheet or other data analysis tools, such as MiniTab or SPSS. The data will be cleared of all the unneeded information to include only the data about adults aged 25-35. After that, data analysis will be performed.

Data Analysis

The data analysis procedure will include the creation of three regression models to understand the influence of independent variables on the dependent variables. The independent variables will be associated with the economic performance of the country, which are unemployment rates, median family income, and poverty rates in the USA. The dependent variables will be the indicators of stress in young adults, which are depression, sleep disorders, and anxiety. The first regression model will assess how the independent variable will influence the number of depression cases in adults aged between 25 and 35. The second regression model will establish correlations between the number of anxiety cases and the independent variables. The third regression model will determine if there is a statistically significant correlation between the independent variables and the number of sleep disorder cases.

The chosen tools of data analyses allow for investigating a multifaceted nature of relationships between numerous variables and test their respective influence on the dependent variable. The data analysis process is relevant and consistent with the study goals. Data analysis is expected to answer the primary research question. The interpretation of the results will help to identify the relationship between the economic well-being of a country and the amount of stress experienced by its citizens.

References

Gudmundsdóttir, D., Ásgeirsdóttir, B., Huppert, F., Sigfúsdóttir, I., Valdimarsdóttir, U., & Hauksdóttir, A. (2016). How does the economic crisis influence adolescents’ happiness? Population-based surveys in Iceland in 2000–2010. Journal of Happiness Studies, 17(3), 1219-1234. Web.

Karantzas, G., & Gillath, O. (2017). Stress and well-being during chronic illness and partner death in later-life: The role of social support. Current Opinion in Psychology, 13, 75-80. Web.

Khamisa, N., Peltzer, K., Ilic, D., & Oldenburg, B. (2016). Work related stress, burnout, job satisfaction and general health of nurses: A follow-up study. International Journal of Nursing Practice, 22(6), 538-545. Web.

Kokaliari, E. (2016). Quality of life, anxiety, depression, and stress among adults in Greece following the global financial crisis. International Social Work, 61(3), 410-424. Web.

Lindström, M., & Rosvall, M. (2018). Economic stress in childhood and suicide thoughts and suicide attempts: a population-based study among adults. Public Health, 163, 42-45. Web.

Mucci, N., Giorgi, G., Roncaioli, M., Fiz Perez, J., & Arcangeli, G. (2016). The correlation between stress and economic crisis: a systematic review. Neuropsychiatric Disease and Treatment, 12, 983-992. Web.

Schwarz, J., Gerhardsson, A., van Leeuwen, W., Lekander, M., Ericson, M., Fischer, H., Kecklundac, G., & Åkerstedtac, T. (2018). Does sleep deprivation increase the vulnerability to acute psychosocial stress in young and older adults? Psychoneuroendocrinology, 96, 155-165. Web.

Ursin, H., & Eriksen, H. R. (2004). The cognitive activation theory of stress. Psychoneuroendocrinology, 29(5), 567–592. Web.

WebMD. (n.d.). Causes of stress. Web.

Yaribeygi, H., Panahi, Y., Sahraei, H., Johnston, T. P., & Sahebkar, A. (2017). The impact of stress on body function: A review. EXCLI Journal, 16, 1057–1072. Web.

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