Gaps in knowledge: Tracking and explaining gender differences in health information seeking
Section snippets
The sex gap and health information seeking behavior
While a wide array of different datasets are equipped to look at sex differences in HISB, few studies have thought of sex as anything other than a control variable. The routine inclusion of sex in regressions and bivariate analysis has yielded a strikingly consistent association between sex and HISB. Studies usually find that females are more likely to look for health information by a margin of ten to twenty percent, with adjusted odds ratios falling between 1.4 and 2.0 (e.g.(Weaver et al., 2009
Data
This study leverages repeated waves of data from the Health Information National Trends Survey (HINTS) to look at trends in HISB while also using a single wave of HINTS data to take advantage of more specific items that were asked that wave. The repeated dataset is comprised of six cross sectional waves of data ranging from 2003 to 2013. The first two iterations of HINTS utilized a RDD sample, while HINTS 3 was mixed mode with both an RDD (n = 4081) and mail sample (n = 3593). All HINTS cycles
Results
Table 3 presents odds ratios for sex, wave and their interaction, controlling for all other trending items unless specified. Each of these models indicates a significant gap in predicted probabilities of health information seeking by sex. The strongest coefficients were in the cancer information seeking model, where females were expected to have 111% higher odds of looking for cancer information than males. However, in 2008, 2012, and 2013 the interaction between sex and time was statistically
Discussion
The current study analyzed two key questions. The first of these asked if the sex gap is a persistent phenomenon over time once consistent measurement strategies are employed across multiple waves of data. The results presented confirm that there is a persistent sex gap in searching for health information in some contexts. Unlike Lorence and Park's (2007) results that suggested that the sex gap was expanding for Internet users, when looked at over the course of thirteen years it appears that
Limitations
These results must be taken with limitations in mind. First, the current study uses sex to operationalize gender. While an array of interactions and mediators are used to try to capture gender differences rather than sex, ultimately this is only a step in the right direction rather a perfect quantification of an extremely complex construct. Second, relevant measures such as social capital, health literacy, and attitudes towards HISB could not be accounted for. These measures have been found to
Conclusion
The current study sought to correct several limitations in the current literature by attempting to identify the underlying processes that may be driving the sex differences in HISB. While it was found that sex gaps are substantial and, except for one case, persistent, efforts to explain the sex gap in more substantive theoretical terms were not always successful. Explanations rooted in gendered reactivity to illness and gendered division of labor received little support. Perceived cancer risk
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