European Journal of Health and Biology Education

Exploring the Impact of Knowledge and Social Environment on Influenza Prevention and Transmission in Midwestern United States High School Students
William L. Romine 1 * , Tanvi Banerjee 2, Lloyd H. Barrow 3, William R. Folk 4
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1 Missouri Valley College, Department of Math and Science, 500 E. College St., Marshall, MO 65340, UNITED STATES
2 University of Missouri, Department of Electrical and Computer Engineering, 329 Engineering Building West, Columbia, MO 65211, UNITED STATES
3 University of Missouri, Department of Curriculum and Instruction, 303 Townsend Hall, Columbia, MO 65211, UNITED STATES
4 University of Missouri, Department of Biochemistry, 117 Schweitzer Hall, Columbia, MO 65211, UNITED STATES
* Corresponding Author
Research Article

European Journal of Health and Biology Education, 2012 - Volume 1 Issue 1, pp. 75-115
https://doi.org/10.20897/lectito.201205

Published Online: 15 Jul 2012

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How to cite this article
APA 6th edition
In-text citation: (Romine et al., 2012)
Reference: Romine, W. L., Banerjee, T., Barrow, L. H., & Folk, W. R. (2012). Exploring the Impact of Knowledge and Social Environment on Influenza Prevention and Transmission in Midwestern United States High School Students. European Journal of Health and Biology Education, 1(1), 75-115. https://doi.org/10.20897/lectito.201205
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Romine WL, Banerjee T, Barrow LH, Folk WR. Exploring the Impact of Knowledge and Social Environment on Influenza Prevention and Transmission in Midwestern United States High School Students. European Journal of Health and Biology Education. 2012;1(1):75-115. https://doi.org/10.20897/lectito.201205
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Romine WL, Banerjee T, Barrow LH, Folk WR. Exploring the Impact of Knowledge and Social Environment on Influenza Prevention and Transmission in Midwestern United States High School Students. European Journal of Health and Biology Education. 2012;1(1), 75-115. https://doi.org/10.20897/lectito.201205
Chicago
In-text citation: (Romine et al., 2012)
Reference: Romine, William L., Tanvi Banerjee, Lloyd H. Barrow, and William R. Folk. "Exploring the Impact of Knowledge and Social Environment on Influenza Prevention and Transmission in Midwestern United States High School Students". European Journal of Health and Biology Education 2012 1 no. 1 (2012): 75-115. https://doi.org/10.20897/lectito.201205
Harvard
In-text citation: (Romine et al., 2012)
Reference: Romine, W. L., Banerjee, T., Barrow, L. H., and Folk, W. R. (2012). Exploring the Impact of Knowledge and Social Environment on Influenza Prevention and Transmission in Midwestern United States High School Students. European Journal of Health and Biology Education, 1(1), pp. 75-115. https://doi.org/10.20897/lectito.201205
MLA
In-text citation: (Romine et al., 2012)
Reference: Romine, William L. et al. "Exploring the Impact of Knowledge and Social Environment on Influenza Prevention and Transmission in Midwestern United States High School Students". European Journal of Health and Biology Education, vol. 1, no. 1, 2012, pp. 75-115. https://doi.org/10.20897/lectito.201205
ABSTRACT
We used data from a convenience sample of 410 Midwestern United States students from six secondary schools to develop parsimonious models for explaining and predicting precautions and illness related to influenza. Scores for knowledge and perceptions were obtained using two-parameter Item Response Theory (IRT) models. Relationships between outcome variables and predictors were verified using Pearson and Spearman correlations, and nested [student within school] fixed effects multinomial logistic regression models were specified from these using Akaike’s Information Criterion (AIC). Neural network models were then formulated as classifiers using 10-fold cross validation to predict precautions and illness. Perceived barriers against taking precautions lowered compliance with the CDC recommended preventative practices of vaccination, hand washing quality, and respiratory etiquette. Perceived complications from influenza illness improved social distancing. Knowledge of the influenza illness was a significant predictor for hand washing frequency and respiratory etiquette. Ethnicity and gender had varying effects on precautions and illness severity, as did school-level effects: enrollment size, proficiency on the state’s biology end-of-course examination, and use of free or reduced lunch. Neural networks were able to predict illness, hand hygiene, and respiratory etiquette with moderate success. Models presented may prove useful for future development of strategies aimed at mitigation of influenza in high school youths. As more data becomes available, health professionals and educators will have the opportunity to test and refine these models.
KEYWORDS
REFERENCES
  • American Society for Microbiology. (2000). America’s dirty little secret: our hands. Retrieved July 5, 2011 from http://www.washup.org/page03.htm
  • Allegranzi, B., Memish, Z., Donaldson, L. and Pittet, D. (2009). Religion and culture: Potential undercurrents influencing hand hygiene promotion in health care. American Journal of Infection Control, 37(1), 28-34.
  • Becker, M.H. and Maiman, L.A. (1975). Sociobehavioral determinants of compliance with health and medical care recommendations. Medical Care, 13(1), 10-24.
  • Bishop, C. (2006). Pattern Recognition and Machine Learning. Springer: New York.
  • Blendon, R., Koonin, L., Benson, J., Cetron, M., Pollard, W., Mitchell, E., Weldon, K. and Herrmann, M. (2008). Public response to community mitigation measures for pandemic influenza. Emerging Infectious Disease, 14(5), 778-786.
  • Brant, R. (1990). Assessing proportionality in the proportional odds model for ordinal logistic regression. Biometrics, 46, 1171-1178.
  • Burnham, K.P. and Anderson, D.R. (1998). Model Selection and Inference: A Practical Information-theoretic Approach. New York: Springer.
  • Carnegie Commission on Higher Education. (2010). The Carnegie Classification of Institutions on Higher Education. Retrieved August 7, 2012 from http://classifications.carnegiefoundation.org/
  • Cauchemez, S., Ferguson, N., Wachtel, C., Tegnell, A., Saour, G., Duncan, B. and Nicoll, A. (2009). Closure of schools during an influenza pandemic. Lancet Infect. Dis., 9, 473-481.
  • Center for Disease Control and Prevention. (2009) Seasonal Influenza: Flu. Retrieved November 3, 2010 from http://www.cdc.gov/flu/protect/habits.htm
  • Center for Disease Control and Prevention. (2010). H1N1 Flu Estimates. Retrieved November 3, 2010 from http://www.cdc.gov/h1n1flu/estimates_2009_h1n1.htm
  • Chen, J. Fox, S., Cantrell, C., Stockdale, S. and Kagawa-Singer, M. (2006). Health disparities and prevention: Racial/ethnic barriers to flu vaccinations. Journal of Community Health, 32(1), 5-20.
  • Cohen, J. (1988). Statistical Power and Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Cooper, C. and Pearson, P. (2012). A genetically optimized predictive system for success in general chemistry using a diagnostic algebra test. Journal of Science Education and Technology, 21(1), 197-205.
  • Curtis, V. and Biran, A. (2001). Dirt, disgust, and disease: is hygiene in our genes? Perspectives in Biology and Medicine, 44(1), 17-31.
  • Demuth, H. and Beale, H. (1998). Neural Network Toolbox for Use with Matlab. v 3, Mathworks, Natick, Mass.
  • Dubbert, P.M., Dolce, J., Richter, W., Miller, M. and Chapman, S. (1990). Increasing ICU staff handwashing: effects of education and group feedback. InfectControl Hosp Epidemiol, 11, 191–193.
  • Dumais, N. and Hasni, A. (2009). High school intervention for influenza biology and epidemics/pandemics: Impact on conceptual understanding among adolescents. Life Sciences Education, 8, 62-71.
  • Dushoff, J., Plotkin, J., Viboud, C., Earn, D. and Simonsen, L. (2006). Mortality due to influenza in the United States: An annualized regression approach using multiple-cause mortality data. American Journal of Epidemiology, 163(2), 181-187.
  • Falomir-Pichastor, J., Toscani, L. and Despointes, S. (2009). Determinants of flu vaccination among nurses: The effects of group identification and personal responsibility. Applied Psychology: An International Review. 58(1), 42-58.
  • Foster, W.R., Collopy, F. and Ungar, L.H. (1992). Neural network forecasting of short, noisy time series. Computers & Chemical Engineering, 16(4), 293–297.
  • George, E.I. (2000). The variable selection problem. Journal of the American Statistical Association, 95(452), 1304-1308.
  • Granovetter, M. (1978). Threshold models for collective behavior. American Journal of Sociology, 83(6), 1420-1443.
  • Harbarth, S., Siegrist, C.A., Schira, J.C., Wunderli, W. and Pittet, D. (1998). Influenza immunization: improving compliance of healthcare workers. Infect Control Hosp Epidemiol, 19(5), 337–342.
  • Harbarth, S., Pittet, M., Grady, L. and Goldmann, D. (2001). Compliance with hygiene practice in pediatric intensive care. Pediatric Critical Care Medicine, 2(4), 311-314.
  • Harper, S.A., Fukuda, K., Uyeki, T.M., Cox, N.J. and Bridges, C.B. (2005). Prevention and control of influenza: recommendations of the Advisory Committee on Immunization Practices (ACIP). MMWR Recomm Rep, 54, 1–40.
  • Haykin, S. (1999). Neural Networks: A Comprehensive Foundation. 2nd ed., Englewood Cliffs, N.J.: Prentice Hall.
  • Inglesby, T.V., Nuzzo, J.B., O’Toole, T., and Henderson, D.A. (2006). Disease mitigation measures in the control of pandemic influenza. Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science, 4(4), 366-375.
  • Janz, N. and Becker, M. (1984). The Health Belief Model: a decade later. Health Education Quarterly, 11, 1-47.
  • Kendall, M.G. (1970). Rank correlation methods (4th ed.). London: Charles Griffin and Co.
  • Kiviniemi, M., Ram, P., Kozlowski, L. and Smith, K. (2011). Perceptions of and willingness to engage in public health precautions to prevent 2009 H1N1 transmission. BMC Public Health, 11, 152.
  • Kretzer, E.K. and Larson, E.L. (1998). Behavioural interventions to improve infection control practices. Am J Infect Control, 26, 245–253.
  • Kriesel, D. (2007). A brief introduction to neural networks. Retrieved August 15, 2011 from http://www.dkriesel.com.
  • Lee, E., Lim, C.P., Yuen, R.K. and Lo, S.M. (2004). A Hybrid Neural Network Model for Noisy Data Regression. IEEE Transactions on Systems, Man and Cybernetics, 34(2) 951-960.
  • Lindley, M., Wortley, P., Winston, C. and Bardenheier, B. (2006). The role of attitudes in understanding disparities in adult influenza vaccination. American Journal of Preventative Medicine, 31(4), 281-285.
  • Lord, F.M. and Novick, M.R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley: Reading, Mass.
  • Martinello, R.A., Jones, L. and Topal, J.E. (2003). Correlation between healthcare workers' knowledge of influenza vaccine and vaccine receipt. Infect Control Hosp Epidemiol, 24, 845-847.
  • Meers, G. (2009). Using the H1N1 outbreak as a learning tool: Curriculum and instructional implications and opportunities. Career Education Review, 19-27.
  • Molinari, N., Ortega-Sanchez, I., Messionnier, M., Thompson, W., Wortley, P., Weintraub, E. and Bridges, C. (2007). The annual impact of seasonal influenza in the US: Measuring disease burden and costs. Vaccine, 25(27), 5086-5096.
  • Nichol, K.L. and Hauge, M. (1997). Influenza vaccination of healthcare workers. Infect Control Hosp Epidemiol, 18(3), 189–194.
  • Nichol, K.L., Margolis, K.L., Wuorenma, J. and Von Sternberg, T. (1994). The efficacy and cost effectiveness of vaccination against influenza among elderly persons living in the community. N Engl J Med, 331, 778–784.
  • Pittet, D. (2000). Improving compliance with hand hygiene in hospitals. Infect Control Hosp Epidemiol, 21, 381–386.
  • Pittet, D., Hugonnet, S., Harbarth, S., Mourouga, P., Sauvan, V., Touveneau, S. and Perneger, T. (2000). Effectiveness of a hospital-wide programme to improve compliance with hand hygiene. The Lancet, 356, 1307-1312.
  • Principi, N., Esposito, S., Marchisio, P., Gasparini, R. and Crovari, P. (2003). Socioeconomic impact of influenza on healthy children and their families. Pediatric Infectious Disease Journal, 22(10), S207-S210.
  • Rogers, R.W. (1975). A protection motivation theory of fear appeals and attitude change. Journal of Psychology: Interdisciplinary and Applied. 91(1), 93-114.
  • Romine, W. (2011). Development and validation of two influenza assessments: Exploring the impact of knowledge and social environment on health behaviors. Doctoral Dissertation, University of Missouri: Columbia.
  • Romine, W., Barrow, L. and Folk, W. (2012). Development and validation of an assessment of understanding of influenza for high school students using the Rasch model, and analysis of students’ knowledge of influenza. Paper presentation at the National Association for Research in Science Teaching annual meeting: Indianapolis, IN.
  • Rosenstock, I. (1966). Why people use health services. Milbank Memorial Fund Quarterly, 44, 94-124.
  • Rosenstock, I. (1974). Historical origins of the Health Belief Model. Health Education Monographs, 2, 328-335.
  • Rosenthal, R. (1994). Parametric measures of effect size. In H. Hooper and L.V. Hedges (Eds.), Handbook of Research Synthesis (pp. 213-244). New York: Russell Sage Foundation.
  • Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement, No. 17.
  • Samejima, F. (1972). A general model for free response data. Psychometrika Monograph, No. 18.
  • Shepard, L. (2000). The role of assessment in a learning culture. Educational Researcher, 29(7), 4-14.
  • Steyerberg, E. W., Eijkemans, M. and Habbema, D. (1999). Stepwise selection in small data sets: A simulation study of bias in logistic regression analysis. Journal of Clinical Epidemiology, 52(10), 935-942.
  • Theodoridis, S. and Koutroumbas, K. (2006). Pattern Recognition, 3rd ed. New York: Academic Press.
  • Thompson, W., Shay, D., Weintraub, E., Brammer, L., Bridges, C., Cox, N. and Fukuda, K. (2004). Influenza-associated hospitalizations in the United States. JAMA, 292(11), 1333-1340.
  • Thompson, W., Shay, D.K., Weintraub, E., Brammer, L., Cox, N., Anderson, L. and Fukuda, K. (2003). Mortality associated with influenza and respiratory syncytial virus in the United States. JAMA, 289(2), 179–186.
  • Wallace, J. and Louden,W. (1992). Science teaching and teachers' knowledge: Prospects for reform of elementary classrooms. Science Education, 76, 507-521.
  • Weinstein, N. D., McCaul, K., Gerrard, M., Gibbons, F. X. Kwitel, A. and Magnan, R. (2004). Risk perceptions: Assessment and relationship to influenza vaccination. Health Psychology, 26(2), 146-151.
  • Wensing, M., Van der Weijden, T. and Grol, R. (1998). Implementing guidelines and innovations in general practice: Which interventions are effective? British Journal of General Practice, 48(427), 991-997.
  • White, T., Lavoie, S. and Nettleman, M. (1999). Potential cost savings attributable to influenza vaccination of school-aged children. Pediatrics, 103(6), 1-5.
  • White, C., Koble, R., Carlson, R., Lipson, N., Dolan, M., Ali, Y. and Cline, M. (2003). The effect of hand hygiene on illness rate among students in university residence halls. American Journal of Infection Control, 31, 364-370.
  • Zadeh L.A. (1996). Fuzzy logic = computing with words. IEEE Trans. on Fuzzy Systems, 4, 103-111.
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