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Health-related Behaviors (health-related + behavior)
Selected AbstractsThe relationship between education and health behavior: some empirical evidenceHEALTH ECONOMICS, Issue 2 2006Alexander J. Cowell Abstract Although researchers agree that more educated people typically engage in healthier behaviors, they have not uncovered the reason why. This paper considers several explanations, including future opportunity costs. Future opportunity costs represent any utility-improving future outcome that is affected by currently engaging in health-related behavior. This paper also examines whether there are degree effects in the health behaviors of binge drinking and smoking. Results suggest that future opportunity costs may affect smoking, although other interpretations cannot be ruled out. The results also find degree effects with regard to binge drinking. Copyright © 2005 John Wiley & Sons, Ltd. [source] Individual trajectories of substance use in lesbian, gay and bisexual youth and heterosexual youthADDICTION, Issue 6 2009Michael P. Marshal ABSTRACT Aims Several decades of research have shown that lesbian, gay and bisexual (LGB) adults are at high risk for substance use and substance use disorders, and a recent meta-analysis shows that these disparities most probably begin in adolescence; however, no studies to date have examined longitudinal growth in substance use in LGB youth and heterosexual youth to determine if they follow different trajectories into young adulthood. The primary aims of this paper were to estimate individual trajectories of substance use in youth and examine differences between self-identified LGB and heterosexual subsamples. Method A school-based, longitudinal study of health-related behaviors of adolescents and their outcomes in young adulthood was used to test our hypotheses (The National Longitudinal Study of Adolescent Health). Participants were included if they were interviewed at all three waves and were not missing information regarding self-identified sexual orientation (n = 10 670). Results Latent curve models (LCMs) showed that LGB identity was associated significantly with individual variability in substance use intercepts and slopes, above and beyond age, race and gender. Self-identified LGB youth reported higher initial rates of substance use and on average their substance use increased over time more rapidly than did substance use by heterosexual youth. Two other indicators of sexual orientation (same-sex romantic attraction and same-sex sexual behavior) were also associated with substance use trajectories, and differential results were found for youth who identified as ,mostly heterosexual' and bisexual compared with youth who identified as completely heterosexual or homosexual. Conclusions Sexual orientation is an important risk marker for growth in adolescent substance use, and the disparity between LGB and heterosexual adolescents increases as they transition into young adulthood. More research is needed in order to examine: causal mechanisms, protective factors, important age-related trends (using a cohort-sequential design), the influence of gay-related developmental milestones, curvilinear effects over time and long-term health outcomes. [source] Challenges and Opportunities for Developing and Implementing Incentives to Improve Health-Related Behaviors in Older AdultsJOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 9 2010Eran Klein MD There is growing interest in using patient-directed incentives to change health-related behaviors. Advocates of incentive programs have proposed an ambitious research agenda for moving patient incentive programs forward. The unique cognitive and psychological features of older adults, however, present a challenge to this agenda. In particular, age-related changes in emotional regulation, executive function, and cognitive capacities, and a preference for collaborative decision-making raise questions about the suitability of these programs, particularly the structure of current financial incentives, for older adults. Differences in decision-making in older adults need to be accounted for in the design and implementation of financial incentive programs. Financial incentive programs adjusted to characteristics of older adult populations may be more likely to improve the lives of older persons and the economic success of programs that serve them. [source] Characterizing and Reaching High-Risk Drinkers Using Audience SegmentationALCOHOLISM, Issue 8 2009Howard B. Moss Background:, Market or audience segmentation is widely used in social marketing efforts to help planners identify segments of a population to target for tailored program interventions. Market-based segments are typically defined by behaviors, attitudes, knowledge, opinions, or lifestyles. They are more helpful to health communication and marketing planning than epidemiologically defined groups because market-based segments are similar in respect to how they behave or might react to marketing and communication efforts. However, market segmentation has rarely been used in alcohol research. As an illustration of its utility, we employed commercial data that describes the sociodemographic characteristics of high-risk drinkers as an audience segment, including where they tend to live, lifestyles, interests, consumer behaviors, alcohol consumption behaviors, other health-related behaviors, and cultural values. Such information can be extremely valuable in targeting and planning public health campaigns, targeted mailings, prevention interventions, and research efforts. Methods:, We described the results of a segmentation analysis of those individuals who self-reported to consume 5 or more drinks per drinking episode at least twice in the last 30 days. The study used the proprietary PRIZMÔ (Claritas, Inc., San Diego, CA) audience segmentation database merged with the Center for Disease Control and Prevention's (CDC) Behavioral Risk Factor Surveillance System (BRFSS) database. The top 10 of the 66 PRIZMÔ audience segments for this risky drinking pattern are described. For five of these segments we provided additional in-depth details about consumer behavior and the estimates of the market areas where these risky drinkers resided. Results:, The top 10 audience segments (PRIZM clusters) most likely to engage in high-risk drinking are described. The cluster with the highest concentration of binge-drinking behavior is referred to as the "Cyber Millenials." This cluster is characterized as "the nation's tech-savvy singles and couples living in fashionable neighborhoods on the urban fringe." Almost 65% of Cyber Millenials households are found in the Pacific and Middle Atlantic regions of the United States. Additional consumer behaviors of the Cyber Millenials and other segments are also described. Conclusions:, Audience segmentation can assist in identifying and describing target audience segments, as well as identifying places where segments congregate on- or offline. This information can be helpful for recruiting subjects for alcohol prevention research as well as planning health promotion campaigns. Through commercial data about high-risk drinkers as "consumers," planners can develop interventions that have heightened salience in terms of opportunities, perceptions, and motivations, and have better media channel identification. [source] Cross-Validation and Discriminant Validity of Adolescent Health Promotion Scale Among Overweight and Nonoverweight Adolescents in TaiwanPUBLIC HEALTH NURSING, Issue 6 2006Mei-Yen Chen ABSTRACT This study used cross-validation and discriminant analysis to evaluate the construct and discriminant validity of Adolescent Health Promotion (AHP) scale between the overweight and nonoverweight adolescents in Taiwan. A cross-sectional survey method was used and 660 adolescents participated in this study. Cluster and discriminant analyses were used to analyze the data. Our findings indicate that the AHP is a valid and reliable scale to discriminate between the health-promoting behaviors of overweight and nonoverweight adolescents. For the total scale, cluster analyses revealed two distinct patterns, which we designated the healthy and unhealthy groups. Discriminate analysis supported this clustering as having good discriminant validity, as nonoverweight adolescents tended to be classified as healthy, while the overweight tended to be in the unhealthy group. In general, overweight adolescents practiced health-related behaviors at a significantly lower frequency than the nonoverweight. These included exercise behavior, stress management, life appreciation, health responsibility, and social support. These findings can be used to further develop and refine knowledge of adolescent overweight and related strategies for intervention. [source] | ||||||||||