Module 5: Effective Health Education

Defining Health Education

The formulation of a concrete, comprehensive definition of health education and its multi-faceted variances has been noted as a problematic area for educators. Nevertheless, a number of models have been proposed throughout the years, including Hornsey’s framework that lists the major role of health education as encompassing four separate components(1):

• medical components;

• educational components;

• developmental components; and

• socio-political components

In this framework, the medical component of health education involves the dissemination of medical information and preventative measures in the context of health and well-being. The educational component of health education includes various participatory methods, including discussion, group interaction and group support. Likewise, the developmental component focuses on the development of skills that enable citizens to look after themselves while the socio-political component examines the various social-economic and political determinants of health such as social demographics, behavioral change and availability of resources and materials.(2) Regardless of the model used, effective health education requires the integration and utilization of a wide range of factors.

Designing Health Education

Research has demonstrated that effective health education design begins with the identification of various important psychosocial determinants that govern health behavior in individuals and populations. These behavior models can range from the theory of planned behavior – which equates behavioral intentions, social norms, and perceived behavioral controls with predictions in a subject’s behavior – to the social cognitive theory – which suggests that people learn by watching other people’s actions.(3)(4)

One means of designing effective health education is the modification of materials using an understanding of these psychosocial principles, thereby providing the best conditions for which a student can learn. Indeed, one study done by Whittingham et al. demonstrated that certain cognitive psychological theories could be adapted for improving knowledge transfer and comprehension; their modified materials regarding alcohol abuse resulted in significantly higher knowledge uptake by the study participants, as compared to those participants using the non-modified materials.(5) Some of the principles they used could be readily adapted for other workers involved in the generation of health education materials, including:

• Text coherence – designing information in such a way that information logically follows from one passage to the next, as well as from one topic to the next;

• Illustrations – presenting information in a visual manner has been shown to increase comprehension and recall;

• Pop-out effects – drawing attention to specific information by displaying the important information differently than the rest of the text, i.e., through the use of color, shapes, font, size, etc.

Used in conjunction, these techniques noticeably improve the efficacy of health education materials.

It is vital to recognize that the best material for content uptake varies widely among readers. In other words, learning about the target demographic and customizing the presentation of information to best suit this demographic is a crucial step towards effective health education; generic information may greatly benefit one group, but do little to nothing for another group. A study by Kreuter et al. provided proof for this principle. In it, tailored messages created by clinicians, behavioral scientists and weight loss experts crafted specific weight loss messages to address individual differences among the study participants; compared to the non-tailored generic weight-loss brochures, the tailored information was not only seen as having a significantly greater attractiveness in general, but also yielded more positive self-assessment thoughts, positive behavioral intentions and greater long-term behavioral changes.(6) Furthermore, efforts should be made to work with local organizations and local community members. These local partnerships have been shown to facilitate overall communication, minimize logistical issues, and legitimize the educational efforts.(7) The empowering of local people with knowledge beyond the span of the educational program(s) is vital as well.(8)

Lastly, attention must be given to the cultural contexts of the target demographic. An example stems from Thailand in the early 1990s, where Peace Corps volunteers attempted to educate villagers about the importance of condoms in the reduction and prevention of HIV/AIDS transmission. “In the old days volunteers used bananas in the demonstration but switched to wooden replicas when they discovered that some participants went home and actually put condoms on bananas thinking it had some sort of power to keep them safe.”(9)

In Papua New Guinea, however, researchers used both wooden replicas and bananas in their condom demonstrations. In this situation, the researched concluded that: “We found that bananas worked better than wooden penis models, because the women were less embarrassed handling them.”(10) This startling difference in situation between health workers and villagers draws attention to the necessity of health educators to thoroughly examine the people, culture, methods, materials and society that they wish to impact.

Evaluating the Outcomes of Health Education

Perhaps the most important thing about health education is that one should never simply assume that the educational materials, information and procedures used are effective. A lecture or intervention that appears to be efficacious may yield completely unexpected results – and even be detrimental - as the Thailand example mentioned above demonstrated. Effective health education relies heavily on continual testing to ensure compliance and knowledge comprehension, to generate data that can be used to measure the efficacy of the health care work and to improve future health care education, as well as to rectify and address areas of concern as soon as they occur. Furthermore, this educational data-gathering and continual testing requires the presence of baseline “pre-testing” to establish the impact of the developed materials; educators need to gauge a student’s prior knowledge in order to measure the effectiveness of the education. This prior knowledge has been shown to have a substantial influence on a student’s observations, learning receptiveness, and perceptive beliefs.(11) Therefore, the vast majority of health education programs should implement some means of testing a student’s prior knowledge, such as through the use of non-leading questionnaires, surveys, conversation, etc. After adequate pre-testing is achieved, educators should begin their proposed health education program. Learner follow-up should then be performed. In regards to this, there are various measures that researchers and educators can adopt to evaluate the outcomes of their health education, including:

• Changes in Knowledge – Demonstrated changes in a student responses towards non-leading pre-determined questions, surveys, questionnaires, and/or other measures that relate to the specific material addressed by the health educational program. Ideally, an effective health program will result in changes that demonstrate increased factual accuracy and knowledge about specific medical and health-related issues for a prolonged period of time.(12)

• Changes in Behavior – Effective health education will yield both short-term and long-term changes in behavior that reduce risky behavior and/or improve quality-of-life. These changes in behavior can be recorded through evaluator observations and learner feedback, or through more formal means, such as questionnaires and surveys. Importantly, the extent of a student’s behavioral change and maintenance depends heavily on the learner’s beliefs, specifically in regard to the expectations of the outcomes stemming from behavioral change as well as personal expectations about one’s ability to undergo behavioral change.(13)

• Learner/Participant Satisfaction – A subjective measure based on the learner’s perceived expectations regarding their overall experience and the actual outcome. Generally, learner/participant satisfaction data is gathered through questionnaires or surveys; the data can be used to improve health education programs through the targeting of specific changes noted by the prior participants.(14)

• Cost-Effectiveness Analysis (CEA) – Strictly speaking, CEA is the estimation of the net costs and effects of any action. In health education, CEA provides a way for program developers to quantitatively illustrate the “opportunity cost” of a decision: the possible socio-educational-medical benefits lost in exchange for the execution of another program. In this sense, it provides an additional metric for health workers to make informed judgments in creating an effective health educational program.(15)

Only programs that show statistically significant benefits should continue to be used in future educational cycles. Taken together, program outcome evaluation maximizes the effectiveness, efficiency, and impact that best characterizes effective health education.

Case Studies on Health Education in the Context of HIV/AIDS

In 2002, Donald Bundy, the World Bank’s Lead Health Specialist for Health, Nutrition and Population in the Africa Region, noted that in regards to HIV/AIDS in Africa: “The Window of Hope is the school children. School-aged children, even in the worst affected countries, are uninfected in general. And school-aged children need never become infected. There is no cure; there is no biological vaccine, but this is a condition which is entirely preventable. There is no reason why these children, uninfected today, should not grow up to be uninfected adults.”(16) Spurred by these words, Duflo et al. conducted a three-pronged study beginning in 2003 on HIV/AIDS health education programs in Kenya. In the study, they examined and executed three separate school-based interventions aimed at reducing the incidence of HIV/AIDS in school children: 1) teacher training using the Kenyan Government’s HIV/AIDS-education curriculum; 2) classroom essays and student debates on HIV/AIDS prevention and the use of condoms; and 3) a reduction in the cost of schooling. Through the use of many of the methodologies, techniques, and evaluation methods outlined above, Duflo et al. uncovered surprising results in each of the three interventions, including:

• In general, the teacher training intervention resulted in greater integration of HIV/AIDS education into the curriculum, more time spent on HIV/AIDS education, and the creation of school-based HIV prevention health clubs. Surprisingly, however, the intervention yielded no change in practical knowledge among students, excluding knowledge regarding the use of abstinence as one method of HIV/AIDS prevention. Moreover, the teacher training had no bearing on the incidence of teen pregnancy, but increased the probability that teen pregnancies occur within marriage.(17)

• Both boys and girls who engaged in debates about condom use were substantially more likely to state that condoms could prevent pregnancy and provide protection against HIV infection. Furthermore, the study found that only females were statistically more likely to state that condoms could prevent HIV transmission, while only males were statistically more likely to have self-reported the use of a condom the last time that they had sex. The overall frequency of self-reported sexual activity remained unchanged after the condom debate intervention.(18)

• A reduction in the cost of schooling was achieved by providing a free school uniform – the main financial barrier to educational access - to each student enrolled in the sixth grade. Duflo et al. discovered that this intervention not only reduced school dropout rates, but also reduced teen pregnancies and the likelihood that boys and girls would be married between grades 5-8. It has been speculated that reducing the cost of education raises the opportunity cost of pregnancy and unprotected sex.(19)

Study author Patricia Dupas of UCLA aptly noted that the risk of contracting HIV/AIDS is highly dependent on the sexual relationship: “…The prevalence of HIV is at least three times higher among teenage girls than among teenage boys. Multiple studies have suggested that this discrepancy is due, in part, to the high incidence of unsafe cross-generational sexual relationships – that is, unprotected sex between teenage girls and adult men more than five years their senior. Men involved in these relationships, often called “sugar daddies”, are more likely to be infected with HIV than teenage boys since they have been sexually active for longer. Thus, compared to relationships with teen boys, cross-generational relationships pose a higher risk of HIV infection for teenage girls.”(20) Consequently, a change in marriage rates could either signal an increase or decrease in HIV/AIDS incidence, as early marriage with older partners raises the risk of HIV infection while early marriage with younger or similarly-aged partners would reduce the risk of HIV infection within a marriage.

The knowledge that cross-generational relationships were risky was the crux of Patricia Dupas’s own interventional study in the area – a targeted health education program that informed students about the relative risk of “sugar daddies” and the distribution of HIV infections by age and gender. Accordingly, the intervention was found to have reduced incidences of both “sugar daddies” and “sugar mammies” relationships; however, overall sexual activity among teenagers increased.(21) Interestingly enough, Jeremy Magruder of Yale University noted earlier that the overall intervention may not be beneficial: “The total amount of sexual activity might increase, however, if teenage girls who learn that sex with teenage boys is relatively safe increase their sexual activity with teenage boys. This might have negative public health consequences, both in terms of teen pregnancies and in terms of lifetime HIV risk and its epidemiological implications.”(22)

These interventions and their results highlight the importance of constant evaluation backed by science and statistics; health education programs can generate unexpected results that should be taken into consideration when determining overall program efficacy and cost-effectiveness. Furthermore, careful comparisons should be made between prior health education programs and existing programs to evaluate the best course-of-action for organizations and governments. Interventions such as the ones demonstrated show promising venues for future investigation and may yield substantial benefits in the reduction of HIV/AIDS prevalence in Africa for the short- and long-term.

Additional Information

For a more in-depth look into Health Education Strategies in the context of Global Health Delivery, look into the Certificate Program in Health Education Strategies.

Footnotes

(1) Hornsey, E. “Health education in pre-retirement education – a question of relevance.” Health Education Journal. 41(4)(1982):107-113.

(2) Piper, S. Health Promotion for Nurses: Theory and practice. United Kingdom: Taylor & Francis, 2009.

(3) Ajzen, I. “The Theory of Planned Behavior.” Organizational Behavior and Human Decision Processes 50(1991):179-211.

(4) Bandura, A. Social foundations of thought and action: A social cognitive theory. Ed. Englewood Cliffs. Prentice-Hall, 1986.

(5) Whittingham J.R.D., Ruiter R.A.C., Castermans D., Huiberts A., and Gerjo Kok. “Designing effective health education materials: experimental pre-testing of a theory-based brochure to increase knowledge.” Health Education Research. 23(3)(2007):414-426.

(6) Kreuter M.W., Oswald D.L., Bull F.C., and Eddie M. Clark. “Are tailored health education materials always more effective than non-tailored materials?” Health Education Research. 15(3)(2000):305-315.

(7) Gillies, P. “Effectiveness of alliances and partnerships for health promotion.” Health Promotion International. 13(2)(1998):99-120.

(8) Wallerstein, N, & Bernstein, E. “Empowerment Education: Freire’s Ideas Adapted to Health Education.” Health Education & Behavior. 15(4)(1988):379-394

(9) Schimmelpfennig, S. “Mosquito nets, condoms and recycling.” Good Intentions Are Not Enough: An honest conversation about the impact of aid. Posted on 22 September 2009. https://informationincontext.typepad.com/good_intentions_are_not_e/2009/09/mosquito-nets-condomns-and-recycling.html.

(10) Lupiwa S., Suve N., Horton K., and Megan Passey. “Knowledge about sexually transmitted diseases in rural and periurban communities of the Asaro Valley of Eastern Highlands Province: the health education component of an STD study.” Papua New Guinea Medical Journa.l 39(1996):243-247.

(11) Heit, Evan. “Models on the Effects of Prior Knowledge on Category Learning.” Journal of Experimental Psychology: Learning, Memory, and Cognition. 20(6)(1994):1264-1282.

(12) Estabrooks C.A., Wallin L., and Margaret Milner. “Measuring Knowledge Utilization in Health Care.” Evaluation & Management. 1(1)(2003):3-36.

(13) Strecher V.J., DeVellis B.M., Becker M.H., and Irwin M. Rosenstock. “The Role of Self-Efficacy in Achieving Health Behavior Change.” Health Education Quarterly. 13(1)(1986):73-91.

(14) Appleton-Knapp, S. L., & Krentler, K. “Measuring Student Expectations and Their Effects on Satisfaction: The Importance of Managing Student Expectations.” Journal of Marketing Education. 31(2009):160-172.

(15) Gold, M. Cost-effectiveness in health and medicine. New York: Oxford University Press, 1996.

(16) Bundy, D. Education and HIV/AIDS: A Window of Hope. The World Bank. Presented on 7 May 2002.

(17) Duflo E., Dupas P., Kremer M., and Samuel Sinei. “Education and HIV/AIDS Prevention: Evidence from a randomized evaluation in Western Kenya.” World Bank Policy Research Working Paper 4024(2006).

(18) Ibid.

(19) Ibid.

(20) Dupas, P. “Do Teenagers Respond to HIV Risk Information? Evidence from a Field Experiment in Kenya.” American Economic Journal: Applied Economics. 3(1)(2011):1-36

(21) Ibid.

(22) Magruder, J. R. (2011). Marital shopping and epidemic AIDS. Demography, 48(4), 1401-1428.