Are Smokers with HIV Using Information and Communication Technology? Implications for Behavioral Interventions

Johns Hopkins Medical Institutions, Johns Hopkins University, Baltimore, MD 21287, USA.
AIDS and Behavior (Impact Factor: 3.49). 03/2011; 16(2):383-8. DOI: 10.1007/s10461-011-9914-1
Source: PubMed


Smoking is highly prevalent among persons living with HIV/AIDS (PLWHA) and associated with adverse outcomes including malignancy and cardiovascular disease. Information and communication technology (ICT) may be effective in disseminating cessation interventions among PLWHA. This study examines the prevalence of ICT use among 492 PLWHA attending an urban clinic and characteristics associated with ICT use. Participants completed a survey of demographics, smoking status, and ICT use. Factors associated with ICT use were examined with logistic regression. Overall, 63% of participants smoked with 73% of smokers owning their own cell phone. Use of other modalities was lower, with 48% of smokers reporting any internet use, 39% text messaging, and 31% using email. Higher education was associated with the use of all modalities. Cell phone interventions may have the broadest reach among PLWHA, though with almost half using the internet, this may also be a low-cost means of delivering cessation interventions.

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    • "We chose the topics based on the critical public health areas outlined by the 2009 Society for Academic Emergency Medicine Consensus Conference, “Public Health in the Emergency Department: Surveillance, Screening, & Intervention.”5 Questions regarding baseline technology-based use and behavioral intervention preferences were adapted, when possible, from validated questions administered to previous populations.23,28,30,32 Demographic questions were from the Behavioral Risk Factor Surveillance System.33 "
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    ABSTRACT: 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.
    Full-text · Article · Aug 2014 · The western journal of emergency medicine
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    • "The relationship between smoking and HIV/AIDS was brought to light in his presentation and elaborate evidence showed that smoking cessation indeed resulted in tangible health improvements including longevity. He also emphasized the importance of pharmacological interventions along with motivational intervention and drew attention to response prediction disparities between various ethnic groups.[8] AURORA, an initiative led by him with other co-investigators, is a culturally targeted smoking cessation intervention for Latinos with HIV. "
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    ABSTRACT: The Texas Center for Health Disparities, a National Institute on Minority Health and Health Disparities Center of Excellence, presents an annual conference to discuss prevention, awareness education and ongoing research about health disparities both in Texas and among the national population. The 2013 Texas Conference on Health Disparities brought together experts, in research, patient care and community outreach, on the "Intersection of Smoking, Human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and Cancer". Smoking, HIV/AIDS and cancer are three individual areas of public health concern, each with its own set of disparities and risk factors based on race, ethnicity, gender, geography and socio-economic status. Disparities among patient populations, in which these issues are found to be comorbid, provide valuable information on goals for patient care. The conference consisted of three sessions addressing "Comorbidities and Treatment", "Public Health Perspectives", and "Best Practices". This article summarizes the basic science, clinical correlates and public health data presented by the speakers.
    Full-text · Article · Oct 2013 · Journal of Carcinogenesis
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    ABSTRACT: To assess emergency department (ED) patients' preferences for technology-based behavioral interventions, and the demographic factors associated with these preferences. A cross-sectional survey of a random sample of urban ED patients (≥13 years) from a representative sample of shifts, with oversampling of adolescents/young adults (aged 13 to 24 years). Participants self-administered the survey about baseline technology use, concerns about technology-based interventions, and preferred intervention format for 7 behavioral health topics. We performed descriptive statistics and multivariate logistic regression (controlling for demographics and then additionally for baseline technology use) to identify factors differentially associated with technology preference for each behavioral topic. Of patients presenting during research assistant shifts, 1,429 (≈59%) were screened and 664 (68.2% of eligible) consented to participate. Mean age was 31 years (SD 0.69); 54.5% were female, 64.1% were white, 23.2% were Hispanic, and 46.6% reported low income. Baseline use of computers (91.2%), Internet (70.7%), social networking (66.9%), mobile phones (95.0%), and text messaging (73.8%) was high. Participants reported interest in receiving interventions on each behavioral topic. Ninety percent preferred a technology-based intervention for at least 1 topic. Patients expressed greatest concerns about Internet (51.5%) and social networking (57.6%), particularly about confidentiality. Adjusting for sex, race, ethnicity, and income, younger age associated with preference for technology-based interventions for unintentional injuries (odds ratio 0.63 for technology preference if adult versus youth; 95% confidence interval 0.45 to 0.89) and peer violence (odds ratio 0.63 if adult; 95% confidence interval 0.43 to 0.92). Additionally adjusting for baseline technology usage, only baseline usage was associated with preference for technology-based interventions. ED patients reported high baseline technology use, high interest in behavioral health interventions, and varying preferences for technology-based interventions. Future studies should address actual feasibility and acceptability of technology-based interventions in a more generalized population and ways to alleviate concerns about these interventions.
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