Numeracy, Information Seeking, and Self-Efficacy in Managing Health: An Analysis Using the 2007 Health Information National Trends Survey (HINTS)

Abstract

This study examined the unique effects of numeracy on self-efficacy in managing health and on information-seeking experience, and explored the mediating role of information-seeking experience. The proposed model was tested using a national random-digit-dial sample (n = 4,092) of adults participating in the 2007 Health Information National Trends Survey. Findings from multiple regression analyses revealed that higher numeracy was associated with higher self-efficacy in managing health and better (i.e., more positive) health information-seeking experience, and that better information-seeking experience partially mediated the association between higher numeracy and higher self-efficacy. Findings indicated that communication factors (e.g., information seeking) partially mediated the relationship between cognitive abilities (e.g., numeracy) and self-efficacy. Theoretical implications are discussed, along with practical implications for individuals, health care providers, and public health professionals.

ACKNOWLEDGMENTS

Yixin Chen is a doctoral student and Thomas Hugh Feeley is Professor and Chair in the Department of Communication at the University at Buffalo, The State University of New York. The authors thank the National Cancer Institute for conducting the Health Information National Trends Survey (HINTS) and making the data available online. The authors are also grateful to two anonymous reviewers and Editor Teresa Thompson for their insightful comments and suggestions.

Notes

1. ¹The STAT-confidence scale contains three items: (1) In general, how easy or hard do you find it to understand medical statistics?; (2) I am confident that I can make sense of medical statistics; and (3) I feel like I do not know how to interpret medical statistics (Woloshin et al., 2005). The responses for the first item ranged from 1 = very easy to 4 = very hard. The responses for the second and third items ranged from 0 = strongly disagree to 4 = strongly agree.

2. ²The ISEE scale (Arora et al., 2007) has another two items that were not implemented in the 2007 HINTS and thus were not included in the present study. These two items are as follows: You wanted more information but did not know where to find it. You did not have the time to get all the information you needed.

3. ³The 2007 HINTS also has a single-item measurement about confidence in getting health information. We consider that this single item should be included in the measure for the information-seeking construct in our model, because this single item is highly correlated with the four items that we used for the information-seeking construct. However, the reliability for the information-seeking construct did not improve (i.e., remained .77), when this single item and the four items that we used were combined into a scale. Thus, we decided to remove this single item from the measure for information seeking.

4. ⁴The item’s stem “Overall, how confident are you about your ability … ,” is a standard approach to assessing self-efficacy, and the context “to take good care of your health” was added, so the whole item became a measure for self-efficacy in managing health (N. K. Arora, personal communication, February 4, 2013).

5. ⁵At this stage, SPSS does not have the ability to incorporate replicate weights for inferential statistics (National Cancer Institute [NCI], 2009). If the replicate weights are not incorporated in the analysis, the standard errors of coefficients will probably be underestimated; therefore, the p values will be smaller than they “ought to” be, and a type I error is more likely to occur (NCI, 2009). That is why the present study used STATA rather than SPSS for data analysis.

6. ⁶Interested readers can access the response frequencies for the items of the main measures on the HINTS Website (http://hints.cancer.gov). For example, here is the link for the response frequency for the item “In general, how easy or hard do you find it to understand medical statistics”: http://hints.cancer.gov/question-details.aspx?dataset=2007&qid=785&qdid=2372&method=Combined

7. ⁷Interested readers can contact the corresponding author for the standard deviations (based on the weighted sample) of all variables in each regression equation of Tables 2 and 3.