The Essay On Social Support's Influence On Health And Cardiovascular Reactivity: An Experimental Study.

Discuss about the impact of social support on the cardiovascular reactivity of participants. 
 

The evidence for the health benefits of social support

Evidence shows that social support may be an important determinant of human health, as measured by a wide variety of indices of mortality, morbidity, and psychological wellbeing (Kamarck, 1992; Orth-Gomér & Johnson, 1987; Uchino, Cacioppo, & Kiecolt-Glaser, 1996). Several reviews have reported social support to be inversely related to total mortality (Eriksen, 1994; Schwarzer & Leppin, 1989), total morbidity (Schwarzer & Leppin, 1989; Smith, Fernengel, Holcroft, Gerald, & Marien, 1994), cardiovascular mortality (Krantz & McCeney, 2002), cardiovascular morbidity (Krantz & McCeney, 2002; Orth-Gomér, 1994), and changes in cardiovascular reactivity based on the difference between task levels and baseline levels of cardiovascular indicators (Thorsteinsson & James, 1999).

It is important to understand how social support may influence health so that the effects of support on health can be optimized. Despite the evidence for the health benefits of social support, there is still limited knowledge about underlying physiological mechanisms (Orth-Gomér, 2000). Cardiovascular reactivity has been suggested as a potential underlying physiological mechanisms (mediator) of the benefits of social support on health such that social support affects reactivity that in turn affects health, and experimental studies have been conducted (e.g., Hilmert, Christenfeld, & Kulik, 2002; Kamarck, Manuck, & Jennings, 1990; Lepore, Allen, & Evans, 1993; Thorsteinsson, James, & Gregg, 1998). Much of this work derives from the "reactivity" hypothesis, which states that excessive cardiovascular reactivity and episodic psychological stress contributes to the development of hypertension and cardiovascular disease (Krantz et al., 1991; Krantz & Manuck, 1984; Lepore, 1998; Manuck, Kasprowicz, & Muldoon, 1990; Obrist, 1981). 

Participants in experimental studies have generally performed “active” laboratory challenges (e.g., public speaking, mental arithmetic), while receiving either supportive verbal (e.g., good, well done, you are doing fine) or silent supportive gestures (e.g., presence of a friend, smiles, nods) as compared with experiencing a neutral (no-support) silent presence of a confederate (i.e., an assistant to the researcher) or simply conducting the challenge alone. Generally, heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure (DBP) reactivity are monitored (see Lepore, 1998; Thorsteinsson & James, 1999), but findings have been mixed (Thorsteinsson & James, 1999). The trend has been for support to reduce HR, SBP, and DBP reactivity, but effect sizes have varied from small to large and some studies have reported that support increased HR reactivity (for a meta-analytic review see Thorsteinsson & James, 1999). These findings suggest that the effects of social support manipulations are dependent on several factors such as the type of challenge, type of support, and the relationship between the participant and the support provider. Little attention has been given to the effects of support on the subjective experience of stress during stressful situations and the possible effects stress and arousal may have on cardiovascular indicators, but there is some indication that subjective stress is affected by support (Thorsteinsson, James, & Gregg, 1996).

The potential underlying physiological mechanisms of social support on health through cardiovascular reactivity

Hypothesis 1: The stressful task increased the subjective stress rating above a score of 50.  This hypothesis was a check to see if the task did what it was supposed to do.

Hypothesis 2: The stressful task increased systolic blood pressure (SBP) of the participants.

Hypothesis 3: The support condition reduced HR reactivity compared with the no-support condition.

Hypothesis 4: The support condition reduced SBP reactivity compared with the no-support condition.

Hypothesis 5: There was a positive association between subjective stress levels and cardiovascular reactivity (change in HR, SBP, and DBP).

Participants

The study progressed with 40 healthy volunteers, where males and females were equal in numbers (N = 20). The participants were selected from the university students who volunteered to participate in the research. Ethics approval was given by the University's human ethics committee. The debrief sheets were also provided to the selected candidates. The average age of male participants was 21.95 years (SD = 2.50), and that for the female participants was 20.21 years (SD = 2.54). Average BMI for all the participants was 21.77 kg/m², where males (M = 21.33, SD =2.22) were found to have higher BMI compared to females (M = 21.06, SD = 2.46). Participants were all healthy and non-smokers based on a screening of general health and health-behavior status using a questionnaire. Average systolic blood pressure of the partakers during the screening task was 134.48 mmHg, which ranged from 115 mmHg to 160 mmHg. Hence, participants were normotensive during screening. Each participant was paid AU$10 on completion of the laboratory session. 

Apparatus 

Finapres Continuous Blood Pressure NIBP Monitor; model 2300E (Ohmeda, Ohmeda House, Hertfordshire, England) in combination with dedicated data-processing software (‘Modelflo’, FAST -mf system, TNO Biomedical Instrumentation Research Unit, Amsterdam, The Netherlands) was used to measure HR, SBP, and DBP. A modified version of self-report stress and arousal inventory (Mackay, Cox, Burrows, & Lazzerini, 1978) was employed. Stress during task had a Cronbach’s alpha of .81.

Experimental Design

Participants were randomly assigned to one of two conditions: support or no support. Participants in the support and no-support conditions were told that a confederate who had considerable experience in dealing with a computer task would appear on the monitor. In the support condition, the confederate made positive comments on the participant's performance while in the no support condition the confederate made no comments. The confederate was shown sitting in front of a computer screen on which the participant's responses appeared to be displayed, ostensibly allowing the confederate to monitor the participant's performance. A pre-recording of the confederate was employed to maintain consistency in the support and no-support conditions across participants.

Experimental studies conducted to explore the effects of social support on cardiovascular reactivity

Tasks/Challenges 

The task involved the Fire Chief Computer challenge which is a computerized microworld generator used to create an interactive fire-fighting simulation. This challenge was intended to capture a different type of real-life stress, namely, complex decision making, not captured by tasks such as mental arithmetic or public speaking that are commonly used as stressors in this area. Participants used a computer mouse to manipulate computer icons representing a fire truck and a fire-fighting helicopter to extinguish fires that ignited spontaneously and spread inexorably throughout a large, sparsely populated forest.  

Descriptive Statistics and Assumption Testing

Average task Stress rating score was 58.49 (SD = 12.16). There was not enough evidence to reject the null hypothesis of Shapiro-Wilk test that the variable was normally distributed (W = 0.97, p = 0.34), with skewness S = 0.43 and Kurtosis K = 1.2. An outlier value of 95 was observed outside the “1.5 IQR “rule.

Figure 1: Distribution of Task Stress Scores

Before task (M = 113.10, SD = 12.03) and during experiment SBP (M = 134.48, SD = 10.31) were both found to be normally distributed. The null hypothesis regarding the supposition of normality failed to get rejected at 5% level of significance. Pre-task SBP (W = 0.98, p = 0.74) and during task SBP (W = 0.98, p = 0.75) both were found to be normally distributed by Shapiro-Wilk test. No outlier observation was there in pre-task SBP, but, during the task, a participant had SBP of 160 mmHg, and it was found to be an outlier observation.

Figure 2: Systolic Blood Pressure in pre-task and duration screening

The change in heart rate (HR), Systolic (SBP) and Diastolic blood pressure (DBP) corresponding to the two experimental conditions. The Shapiro-Wilk test confirmed that change in SBP was the only variable, which was normally distributed (W = 0.97, p = 0.16). Hear rate change was significantly not normal (W = 0.87, p < 0.05), and, so was change in diastolic pressure (W = 0.92, p = 0.01), at 5% level of significance.

Figure 3: Comparative analysis of HR, SBP, and DBP change

Relative to two experimental conditions

Hypotheses testing 

To estimate whether the stressful task increased the subjective stress rating above a score of 50, and to check if the task did what it was supposed to do, a one-sample t-test was performed. Mean difference in subjective stress due to stressful task was measured to be 8.49 mmHg (95% CI: 4.6, 12.38). The researcher found a statistically significant increase in subjective stress above 50 (M = 58.49, SD = 12.16), t (39) = 4.42, p < 0.05, d = 0.7 (95% CI: 0.25, 1.15).

Hypotheses tested related to task-induced subjective stress, systolic blood pressure, HR reactivity, SBP reactivity, and the relationship between subjective stress levels and cardiovascular reactivity

The inference on increase in SBP due to the stressful task was tested with a paired t-test at 5% level of significance. Decrease (M = -21.38, SD = 10.92, 95% CI:-24.87, -17.88) in SBP was found to due to the task performed. The researcher found a statistically significant increase in average SBP during task (M = 134.48, SD = 10.31) compared to SBP before task (M = 113.10, SD = 12.03) to, t (39) = 12.38, p < 0.05, d = 1.96 (95% CI: 1.52, 2.39).

An independent sample t-test was conducted to review the between-subjects design, that whether the support condition reduced HR reactivity compared with the no-support condition. Average difference in HR reactivity score was calculated as 5.15 bpm, and Levene’s test (F = 14.67, p < 0.05) produced enough statistical evidence for unequal variances of HR change for two experimental conditions. No statistically significant difference was found between HR change score for support (M = 12.20, SD = 4.63) and non-support experimental conditions (M = 17.35, SD = 19.65), t (38) = -1.14, p = 0.27, d = -0.36 (95% CI: -0.99, 0.26). 

An independent t-test was used to check the hypothesis whether the support condition reduced SBP reactivity compared with the no-support condition. The difference in systolic blood pressure between the pre-task and during task conditions was measured. Levene’s test confirmed statistically significant evidence for equality of variances of SBP change in two experimental conditions (F = 0.13, p = 0.72). The scholar failed to find a statistically significant difference in SBP change between random allocation to support (M = 18.25, SD = 10.74) and non-support experimental condition (M = 24.5, SD = 10.42), t (38) = -1.87, p = 0.07, d = - 0.59 (95% CI: -1.22, 0.04).  

Pearson’s correlation was used to draw an inference about the positive association between subjective stress levels and cardiovascular reactivity (change in HR, SBP, and DBP). The study found that there was no statistically significant correlation between changes in subjective stress levels and HR change score (r = 0.29, p = 0.07). Stress task rating was also found to have a statistically non-significant positive correlation with change in SBP (r = 0.19, p = 0.24). Change in diastolic blood pressure score was also positively correlated with SBP change, but the correlation was not statistically significant (r = 0.18, p = 0.26) at 5% level of significance. Hence, none of the independent factors were significantly correlated to change in systolic blood pressure.

Table 1: Correlation matrix of experiment variables

The present research failed to find any significant impact of social support on cardiovascular reactivity of the participants. Social support also failed to add any benefit to the hypertension sensitivity for the subjects in the sample. Neither heart rate nor SBP was affected by social support in the present research. These conclusions contradict with the outcome of previous research works (Krantz et al., 1991; Obrist, 1981). Alteration in Heart rate, diastolic blood pressure, and stress task level failed to have a significant correlation with the change in systolic blood pressure of the subjects. The correlations were found to be positive, but for significant support, the sample size needs to be increased (Thorsteinsson & James, 1999). Interestingly, stress full atmosphere or pressure task environment was able to increase the SBP to a statistically significant level compared to the pre-task condition. This conclusion was again in line with the results of Thorsteinsson, James, & Gregg (1996). 

The study also had its limitations. In most cases, the effect size was not large enough for statistically significant results. The measures of SBP and DBP were found to have less sample size, especially when the comparison analysis with social support was done. For each group of experimental conditions, the sample size was 20, which created problems for assumptions of normality. Sample size greater than 30 for each experimental condition would have been a desired criterion. 

References

Eriksen, W. (1994). The role of social support in the pathogenesis of coronary heart disease. A literature review. Family Practice, 11, 201-209.

Hilmert, C. J., Christenfeld, N., & Kulik, J. A. (2002). Audience status moderates the effects of social support and self-efficacy on cardiovascular reactivity during public speaking. Annals of Behavioral Medicine, 24, 122-131.

Kamarck, T. W. (1992). Recent developments in the study of cardiovascular reactivity: Contributions from psychometric theory and social psychology. Psychophysiology, 29, 491-503.

Kamarck, T. W., Manuck, S. B., & Jennings, J. R. (1990). Social support reduces cardiovascular reactivity to psychological challenge: A laboratory model. Psychosomatic Medicine, 52, 42-58.

Krantz, D. S., & Manuck, S. B. (1984). Acute psychophysiologic reactivity and risk of cardiovascular disease: A review and methodologic critique. Psychological Bulletin, 96, 435-464.

Krantz, D. S., & McCeney, M. K. (2002). Effects of psychological and social factors on organic disease: A critical assessment of research on coronary heart disease. Annual Review of Psychology, 53, 341-369.

Krantz, D. S., Helmers, K. F., Bairey, C. N., Nebel, L. E., Hedges, S. M., & Rozanski, A. (1991). Cardiovascular reactivity and mental stress-induced myocardial ischemia in patients with coronary artery disease. Psychosomatic Medicine, 53, 1-12.

Lepore, S. J. (1998). Problems and prospects for the social support reactivity hypothesis. Annals of Behavioral Medicine, 20, 257-269.

Lepore, S. J., Allen, K. A. M., & Evans, G. W. (1993). Social support lowers cardiovascular reactivity to an acute stressor. Psychosomatic Medicine, 55, 518-524.

Mackay, C., Cox, T., Burrows, G., & Lazzerini, T. (1978). An inventory for the measurement of self-reported stress and arousal. British Journal of Social and Clinical Psychology, 17, 283-284.

Manuck, S. B., Kasprowicz, A. L., & Muldoon, M. F. (1990). Behaviorally-evoked cardiovascular reactivity and hypertension: Conceptual issues and potential associations. Annals of Behavioral Medicine, 12, 17-29.

Obrist, P. A. (1981). Cardiovascular psychophysiology: A perspective. New York: Plenum.

Orth-Gomér, K. (1994). International epidemiological evidence for a relationship between social support and cardiovascular disease. In S. A. Shumaker & S. M. Czajkowski (Eds.), Social support and cardiovascular disease (pp. 97-117). New York: Plenum press.

Orth-Gomér, K. (2000). Stress and social support in relation to cardiovascular health. In P. M. McCabe & N. Schneiderman (Eds.), Stress, coping, and cardiovascular disease. Stress and coping (pp. 229-240). Mahwah, NJ, US: Lawrence Erlbaum Associates, Publishers.

Schwarzer, R., & Leppin, A. (1989). Social support and health: A meta-analysis. Psychology & Health, 3, 1-15.

Smith, C. E., Fernengel, K., Holcroft, C., Gerald, K., & Marien, L. (1994). Meta-analysis of the associations between social support and health outcomes. Annals of Behavioral Medicine, 16, 352-362.

Thorsteinsson, E. B., & James, J. E. (1999). A meta-analysis of the effects of experimental manipulations of social support during laboratory stress. Psychology & Health, 14, 869-886.

Thorsteinsson, E. B., James, J. E., & Gregg, M. E. (1996). [Effects of Video-relayed Social Support on Hemodynamic and Salivary Cortisol Activity During Passive and Active Behavioural Challenge]. Unpublished raw data.

Thorsteinsson, E. B., James, J. E., & Gregg, M. E. (1998). Effects of video-relayed social support on hemodynamic reactivity and salivary cortisol during laboratory stress. Health Psychology, 17, 436-444.

Uchino, B. N., Cacioppo, J. T., & Kiecolt-Glaser, J. K. (1996). The relationship between social support and physiological processes: A review with emphasis on underlying mechanisms and implications for health. Psychological Bulletin, 119, 488-531.