Computing and Interpreting ANOVAs

Although heart-related deaths have declined over the last ten years (Rosamond et al., 2007), cardiovascular disease (CVD) remains the number one cause of mortality throughout the world. Much of the decline in deaths has been attributed to the identification of multiple risk factors associated with CVD. Risk factors for CVD are wide in scope and include physical (e.g., hypertension), behavioral (e.g., smoking), and psychosocial (e.g., social support) dimensions.

One of the more complex factors associated with CVD is social support. Research on CVD risk has consistently shown how social support is negatively associated with CVD-related mortality (e.g., Brummett et al., 2001). Psychologists and health researchers have long argued that receiving social support is beneficial to our well-being more generally. The more social support available to us, the more protected we are from disease and death (e.g., Broadhead et al., 1983). Those diagnosed with diseases such as cancer (e.g., Cassileth, Walsh, & Lusk, 1988) live longer the more social support they receive. What is less clear from this research is an understanding of why social support reduces the risk for diseases like CVD. One hypothesis that researchers have proposed is that social support reduces reactivity to stressful situations (Cohen & Wills, 1985). This stress-buffering model proposes that social support reduces the magnitude of cardiovascular reactivity, which is hypothesized to be essential for the development of CVD. Studies examining the role of social support in buffering stress reactivity however have been met with inconsistent support for the stress-buffering hypothesis. Some studies report buffering effects (e.g., Lepore, Allen, & Evans, 1993), others report no differences (e.g., Sheffield & Carroll, 1994), and still others have reported increases in reactivity (e.g., Allen, Blascovich, Tomaka, & Kelsey, 1991) when compared to no support conditions. One reason for these inconsistent findings may be a failure to distinguish among different forms of social support. According to Uchino (2009), social support can be emotional (comforting in times of stress) or instrumental (providing strategies for dealing with difficult tasks).

On the basis of the research outlined above, the present study seeks to examine the relationship between multiple known risk factors of CVD with a focus on experimentally addressing how different forms of social support help to reduce stress reactivity in stressful situations.

Method

• Participants: Participants (N = 95) were recruited from the southeastern United States using a variety of recruitment methods (e.g., Craigslist, flyers, local online message boards, and newspaper advertisements). Of these participants, 63% were female and 37% were male. 


• Procedure: Participants were first asked to complete a survey that included assessment of various risk factors theorized to be associated with CVD. These measures included: 


o General Happiness (Happy): General happiness was assessed using a single-item measure of participants’ perceived general happiness levels. Responses were collected on a scale of 0 (not at all) to 6 (very much) where higher values indicate more happiness.

o Frequency of Smoking (Smoke): Participants were also asked to indicate how often they smoke cigarettes on a single-item measure. Responses were collected on a scale of 0 (not at all) to 6 (often) where higher values indicate a greater frequency of smoking.

o Religious Belief (Religion): Participants rated the extent to which they believe in a religion using a single-item measure. Responses were collected on a scale of 0 (not at all) to 6 (very much) where higher values indicate more religiosity.

o Stress Level (StressLevel): After completing the religiosity measure, participants were asked to rate their overall stress levels using a single-item measure. Responses were collected on a scale of 0 (no stress) to 6 (very stressed) where higher values indicate more stress.

o General Health (GeneralHealth): General health was assessed using a thirty-six-item measure. The thirty-six items were summed to create a composite index of general health for each participant where higher numbers indicate better health.

o Self-Esteem (SelfEsteem): Self-esteem was assessed using the ten-item Rosenberg Self- Esteem Scale. The ten items were averaged together such that higher values indicate higher self-esteem.

o CVD: Finally, following participation in the present research, health data for participants was acquired to determine which participants had developed CVD. A score of “yes” indicates that the participant has been diagnosed with CVD.

Experimental Session: Social Support Manipulation

In order to manipulate social support, participants were randomly assigned to perform the speech to either two emotionally supportive evaluators, two instrumentally supportive evaluators, or two neutral evaluators. In the emotional support condition, evaluators were instructed to interrupt the participant’s speech and provide verbal praise for the participant’s performance (e.g., “You are doing a great job”) while also providing positive nonverbal feedback (e.g., smile or nod) throughout the task. In the instrumental support condition also, evaluators stopped participants but offered advice for successfully completing the speech (e.g., “Focus on using pauses to collect your thoughts while you speak”). In the neutral condition also, evaluators were instructed to interrupt after one minute; however, the evaluators simply restated the directions while maintaining flat, nonverbal feedback until the task was over.

Experimental Measures

Two measures were computed to examine the impact of each of the study conditions—respiratory sinus arrhythmia (RSA) and median blood pressure (MBP). RSA is a measure of resilience to stress and should drop under negatively stressful conditions. The MBP provides a measure of stress and is known to increase in conditions of stress. Each measure was computed by subtracting the stress period by a baseline. Thus, negative numbers mean reductions from baseline and positive numbers indicate increases from baseline.

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