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Stay Engaged in Society And Remaining Active: Problem of Loneliness

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“Loneliness is a prevalent social problem with serious physiological and health implications” (Hawkley et al., 2010). By staying engaged in society and remaining active, one can improve their mental and physical health (National Center, 2018). Although multiple studies have been conducted on the physcological and physical effects of loneliness, most of the research was based on cross-sectional data (Hawkley et al., 2010). In the study “Loneliness Predicts Increased Blood Pressure,” the research group questioned how loneliness affects systolic blood pressure over a four year period. Because of the researcher’s previous studies, which found that loneliness was associated with elevated blood pressure, they hypothesized that loneliness would increase a person’s SBP over a four-year period (Hawkley et al., 2010).

The researchers chose this question because of the severity of this public health problem. Loneliness affects 32% of all Americans over the age of 55, and 5-7% of those people report feeling persistent loneliness (Hawkley et al., 2010). Studies have found that loneliness often leads to depressive symptoms, such as: impaired sleep dysfunction, impaired mental health, and mortality (Hawkley et al., 2010). Additionally, loneliness has been connected to an increased vascular resistance, increased SBP, and altered immunity (Hawkley et al., 2010). In order to understand the serious physical effects of loneliness, it is important to understand how it affects the body, which is why the research group questioned how loneliness affects blood pressure.

In order to understand this article, it is helpful to have a background in science and medicine. A lot of the scientific vernacular used, I had never seen before, so I referenced a dictionary while reading this study. I also referenced another research article, which supported this research, and it provided me with other facts and results. This study was done in Switzerland, and it found that it was important to consider “loneliness for physical and mental health and lifestyle factors, not only in older and younger, but also in middle-aged adults” (Richard et al., 2017). In addition, this article pointed out that “little is known about the prevalence of loneliness in different age groups” (Richard et al., 2017). By reading these texts, the findings of the study, “Loneliness Predicts Increased Blood Pressure,” will make more sense.

In the study, the researchers used “longitudinal data to examine the degree to which loneliness explains increases in blood pressure over a four-year follow-up period in the same sample of adults” (Hawkley et al., 2010). The results of the study showed that the presence of loneliness increased SBP 2 to 4 years later. It was also found that “higher initial levels of loneliness were associated with greater increases in SBP over a 4-year period” (Hawkley et al., 2010). Additionally, the researchers noticed that the lonelinesses effect on SBP was independent of “age, gender, race/ethnicity, … health conditions, and the effects of depressive symptoms” (Hawkley et al., 2010). The general overview of the findings and purpose can be found in the Abstract of the research article. Although the abstract sufficiently summarizes the majority of the study, the analysis of the study’s findings could be more in depth. The abstract seems short for the length of the study and article, as this research study took over four years to complete.

The study began in 2002 and ended in 2006, because the researchers wanted to examine how SBP changed over a four year period. In order to retrieve reliable data that could be used, the methods for conducting this study needed to be precise. The Chicago Health, Aging, and Social Relations Study (CHAIRS) was used to select participants (Hawkley et al., 2010). The CHAIR study was population-based, and conducted on “non-Hispanic White, African American, and non-Black Latino American persons born between 1935 and 1952,” who were living in Cook County, IL (Hawkley et al., 2010). In order to select the participants, a multistage probability design was used to select a household of a certain race (Hawkley et al., 2010).

Then a quota sampling strategy was used for each household to achieve an equal distribution of participants all along the six racial and gender combinations (Hawkley et al., 2010). These methods were used to select 229 participants between the ages of 50-68, all with varied backgrounds, genders, and races. Therefore, allowing the study to examine the changes of SBP in a wide variety of people. The procedural method was kept the same for all four years, as participants received the same “standard psychological surveys, health and medication interviews, anthropometric measurements,” and BP measurement (Hawkley et al., 2010).

Each year, the participants also went through the same health interview and cardiovascular measurements, which allowed for the researchers to only take into account the effects of loneliness on SBP (Hawkley et al., 2010). SBP was selected for this study because it’s considered superior to diastolic blood pressure (DBP) when it comes to predicting cardiovascular disease in adults over the age of 50 (Hawkley et al., 2010). For monitoring and measuring blood pressure, a Colin Vital Statistics Monitor was used, as this method is fairly accurate in defining SBP (Hawkley et al., 2010). This measurement method was chosen for this study because it found the SBP accurately, and it wasn’t a challenging test for the participants (Hawkley et al., 2010).

The method for measuring loneliness involved the UCLA Loneliness Scale-Revised, which required participants to rate certain statements, in order to determine their loneliness. This method is known for constructing “validity as a measure of general loneliness and degree of satisfaction with one’s social network,” which creates a reliable data set (Hawkley et al., 2010). Because there were multiple covariates, in the final model, the researchers used the covariates to assess whether or not the relationships between covariates and loneliness affected the SBPs of the participants (Hawkley et al., 2010). The UCLA scale was used because loneliness does relate to the covariates; however, it was found that loneliness was distinct from the psychological covariates (Hawkley et al., 2010). The method for data analysis was a “cross-lagged panel model approach” (Hawkley et al., 2010). This method was chosen because it can concurrently address lonelinesses influence on SBP, which helped determine trends in the data tables (Hawkley et al., 2010).

Data Table #3 was the figure I chose to analyze and explain, because it answers and explains how the covariates related to the study. Table 3 shows how the participant’s SBP and UCLA loneliness scores were affected by each coverity (Hawkley et al., 2010). The covariates of the study were: “age, sex, race, education, income, social network size, current smoker or drinker, BMI, exercise, current medications, depressive symptoms, perceived stress, hostility, social support” (Hawkley et al., 2010). In order to determine the SBP of participants with certain covariates, the Colin Vital Statistics Monitor calculated beat-by-beat systolic blood pressure reading (Hawkley et al., 2010). The UCLA loneliness reading was determined by calculating the reverse scores from the UCLA loneliness scale-revised (Hawkley et al., 2010). By comparing the covariates to SBP and loneliness scores, the researchers were able to determine how certain covariates, such as age and BMI, affected the overall change in SBP. Years of education predicted a decrease in SBP, and the demographic variables predicted no change in SBP (Hawkley et al., 2010).

Additionally, cardiovascular medication use and chronic health conditions predicted increases in SBP in the first two years (Hawkley et al., 2010) No other covariates predicted increases or decreases in SBP (Hawkley et al., 2010). These tests were statistically significant because the relationships between the variables were caused by more than chance, as SBP was affected by both loneliness and the covariates (Gallo, 2016). A statistical hypothesis test can also be used to determine if data is statistically significant (Gallo, 2016). In this study, the statistical test used resulted in a reasonably fit “χ2(2515) = 4796.569, p < .001; RMSEA = .063, 90% CI: .060, .066” (Hawkley et al., 2010). This test showed that loneliness doesn’t have a significant short-term effect on SBP; however, when loneliness is constant and long-term, there were “larger increases in SBP over a four-year period” (Hawkley et al., 2010). Both of these findings supported the original hypothesis.

I feel as though this study answered the question as accurately as it could have been. The brain is full of surprises, and sometimes psychological variables affect our bodies in ways we couldn’t have predicted. The participants are all aging and their social lives are most likely slowing down for a variety of reasons (National Center, 2018). Additionally, because everyone has a different definition of loneliness, it is hard to accurately measure the effects on the body. There were too many psychological limitations that could have influenced the data. Even though the researchers discussed the covariates and how they may have influenced the data with their predictions, the psyche of every person is different. Because of these limitations, the increases in SBP weren’t always homogeneous for every category (Hawkley et al., 2010).

Although the study was very thorough, and the researchers included a section on the covariates, I don’t believe that the study satisfactorily answered the question. There just isn’t a way to know exactly what each of these participants felt everyday, and precisely how each of these psychological variables affected the SBP of everyone. In the future, a follow-up study could focus on how exactly loneliness affects SBP, by using participants similar to one another. Therefore, making it easier to determine why and how the feeling of loneliness increases SBP, which would build off of this paper’s conclusion and answer a lot of my questions.

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