Abstract
This study combines the fever model with communication privacy management to examine the conditions under which military wives are likely to disclose their family stressors or engage in protective buffering with their deployed husbands. Military wives (N =105) whose husbands were deployed and who had at least one child completed a web-based survey about the communication of family stressors during deployment. Protective buffering was associated with negative health symptoms, and disclosure was related to marital satisfaction. Wives' perceptions that their husbands were in dangerous situations as well as their perceptions that husbands were supportive of their disclosures were both related to protective buffering and disclosure.
Acknowledgements
This study is based on the first author's Master's thesis, which was conducted under the direction of the second author. An earlier version of this paper was presented at the 2009 Annual Meeting of the National Communication Association, Chicago, IL. The authors would like to thank the military wives who participated in this study for their openness and generosity. We also thank Walid Afifi and Robin Nabi for their valuable insights on various versions of the manuscript. Funding for this research was provided by the Graduate Research Award for Social Science Surveys (GRASSS) at the University of California, Santa Barbara.
Notes
1. Originally, we did not ask participants about the location of their husbands’ deployment. However, as we conducted the analyses, we realized the importance of this variable. We contacted our participants again and asked them where their husbands were deployed when they completed the survey. We could not locate 25 of the participants (24% of the total sample) and 14 participants (13% of the total sample) refused to disclose their husbands’ deployment locations for security reasons.
2. To test the distribution of the variables of interest, we conducted a Shapiro-Wilk test. The Shapiro-Wilk test tests the null hypothesis that a sample comes from a normally distributed population. Therefore, a variable is normally distributed if the p-value is greater than .05 because the null hypothesis cannot be rejected. Disclosure, perceived risk to husband, marital satisfaction, husband social support, military social support, and control all had p-values less than .05, signifying a nonnormal distribution.
To overcome nonnormality, we tested several transformations. In particular, we calculated square root, logarithm, inverse, and Blom transformations. Neither square root, logarithm, nor inverse transformations resulted in nonsignificant Shapiro-Wilk tests. However, the Blom transformation did increase the p-values of all variables except husband social support. When we reran the analyses, the Blom transformations did not change the outcome of any statistical test. Therefore, for ease of interpretability, we kept the variables in their original form.