Impact of Gender on Patient Preferences for Technology-Based Behavioral Interventions

INTRODUCTION: Technology-based interventions offer an opportunity to address high-risk behaviors in the emergency department (ED). Prior studies suggest behavioral health strategies are more effective when gender differences are considered. However, the role of gender in ED patient preferences for technology-based interventions has not been examined. The objective was to assess whether patient preferences for technology-based interventions varies by gender. METHODS: This was a secondary analysis of data from a systematic survey of adult (≥18 years of age), English-speaking patients in a large urban academic ED. Subjects were randomly selected during a purposive sample of shifts. The iPad survey included questions on access to technology, preferences for receiving health information, and demographics. We defined “technology-based” as web, text message, e-mail, social networking, or DVD; “non-technology-based” was defined as in-person, written materials, or landline. We calculated descriptive statistics and used univariate tests to compare men and women. Gender-stratified multivariable logistic regression models were used to examine associations between other demographic factors (age, race, ethnicity, income) and technology-based preferences for information on specific risky behaviors. RESULTS: Of 417 participants, 45.1% were male. There were no significant demographic differences between men and women. Women were more likely to use computers (90.8% versus 81.9%; p=0.03), Internet (66.8% versus 59.0%; p=0.03), and social networks (53.3% versus 42.6%; p=0.01). 89% of men and 90% of women preferred technology-based formats for at least type of health information; interest in technology-based for individual health topics did not vary by gender. Concern about confidentiality was the most common barrier to technology-based use for both genders. Multivariate analysis showed that for smoking, depression, drug/alcohol use, and injury prevention, gender modified the relationship between other demographic factors and preference for technology-based health information; e.g., older age decreases interest in technology-based information for smoking cessation in women but not in men (aOR 0.96, 95% CI 0.93-0.99 versus aOR 1.00, 95% CI 0.97-1.03). CONCLUSION: Our findings suggest ED patients' gender may affect technology preferences. Receptivity to technology-based interventions may be a complex interaction between gender and other demographic factors. Considering gender may help target ED patient populations most likely to be receptive to technology-based interventions.