Lloyd, Shaffer, Christy, Widome, Repke, Weitekamp, Eslinger, Bargainnier, and Paul: Health Knowledge Among the Millennial Generation

Health Knowledge Among the Millennial Generation

Abstract

The Millennial Generation, also known as Generation Y, is the demographic cohort following Generation X, and is generally regarded to be composed of those individuals born between 1980 and 2000. They are the first to grow up in an environment where health-related information is widely available by internet, TV and other electronic media, yet we know very little about the scope of their health knowledge. This study was undertaken to quantify two domains of clinically relevant health knowledge: factual content and ability to solve health related questions (application) in nine clinically related medical areas. Study subjects correctly answered, on average, 75% of health application questions but only 54% of health content questions. Since students were better able to correctly answer questions dealing with applications compared to those on factual content contemporary US high school students may not use traditional hierarchical learning models in acquisition of their health knowledge.




Significance for public health

Understanding how health knowledge is acquired by young people is a necessary first step to the creation of all health care programs. This study is a small step towards this understanding.

Introduction

Human disease is often complex, as are treatments. Thus, effective communication between healthcare providers and patients is ever more important in our efforts to improve healthcare as is a basic level of health knowledge by patients and it is founded upon adequate health knowledge and health literacy. We are aware that a large percentage of Americans have low health literacy skills,1-6 which restricts their acquisition of health knowledge yet we are less knowledgeable about where young adult Americans acquire their health knowledge and the extent of their actual depth of understanding. In the past most Americans received the majority of their health education in high school yet in the 21st century health knowledge can now be acquired from many non-school sources, and particularly from the internet and other media. As health topics are being presented with increasing frequency on TV and web programs, the population is inundated with health-related information such as advertisements for drugs to treat diseases, to lose weight and to have greater energy. Although we know that many adult Americans use the Internet to search for health information including the Millennials,7-13 it is unclear what the impact of this mix of sources of health-related information has been on health knowledge acquisition among young adults and how it will impact their health care in the future.

Numerous assessments of adolescents’ health behaviors have been made,9,14-16 and mass media has been shown to be an effective tool to change health behavior in adolescents.16 However, quantitative studies to assess clinically relevant health knowledge among young adults have not been reported. Prior to the explosion of media-based health information, health education classes in middle and high school were the primary sources of health information to the public. The curricula in the US has been based upon theory that learning is hierarchical and that acquisition of content is a necessary base structure upon which comprehension, application and synthesis are sequentially built.17,18 Some assessments of the use of the internet for health information have been performed yet this does not inform us as to the level of working health knowledge by the users.19

The present study was undertaken in an effort to learn the level of clinically related health knowledge possessed by 18 year old American high school students. In this context clinically relevant refers to knowledge that can be directly linked to physical health. Thus our goal is distinct from assessments of school health programs in the US over the past two decades which have placed increasing emphasis on promotion of healthy behaviors. As the instruments for assessment of these programs are not appropriate for our study we developed a health knowledge survey appropriate for high school seniors because high school is the last period of formal health education for most Americans. The survey we developed focuses on two domains of clinically relevant health knowledge, namely health content, which encompasses factual information, and health application, namely the ability to use health information in real-world situations.

Design and Methods

Study subjects

All high school seniors enrolled in five Central Pennsylvania public schools were invited to participate. The catchment areas for the schools included urban, suburban, and rural areas. Participation was voluntary, and students were provided with written information about the study to share with parents or guardians before participating. No identifying personal information was obtained. The study was approved by the Institutional Review Board of the Penn State Hershey Medical Center and by appropriate officials at each of the participating high schools.

Questionnaire

Although there are many health assessment questionnaires and surveys of use of online health information there are few validated instruments to evaluate health information.15 Because no contemporary survey instruments were available for the assessment of health knowledge of clinically related questions appropriate for high school seniors, we constructed and tested a new survey instrument. The anonymous, multiple choice, questionnaire was designed to take not more than 25 minutes to complete and to be taken during school hours under supervision. The questionnaire was designed by a team of senior primary care physicians, epidemiologists, and health educators at Penn State to obtain information on study subject demographics, health content knowledge and health application knowledge in nine clinically relevant areas: nutrition, cancer, obesity, diabetes, risk-taking behaviors, physical activity, sexuality, cardiovascular health, and HIV/AIDS. Selection of the final questions was based on the criteria that each question was clinically relevant and would be on a subject and at a level that a clinician would expect a reasonably informed patient to be able to answer. There were correct, unambiguous answers for each question. For each of the nine topic areas we had at least one question in each of the two domains. All questions were multiple-choice, other than those for age, height, and weight. A second team of primary care physicians established the degree of difficulty for the survey by selecting questions which they believed could be correctly answered by 75% of public high school seniors. Prototypes of the questionnaire were piloted with three healthcare groups to identify and revise problematic questions. The three groups were: 12 physicians in a graduate course on Clinical Research Methods, the 60 person staff of the Department of Public Health Sciences, and 45 second-year medical students taking the Elements of Clinical Research course at Penn State College of Medicine. Overall, the three groups who pilot tested the questionnaire (Appendix) answered correctly 80-85% of both the content and application questions. Questionnaires were distributed in regular high school classes by a health or home room teacher, completed by the students, and collected by the teacher. Questionnaires were collected by study staff at each school and returned to Penn State University for scanning and data management.

Statistical methods

Demographic characteristics were summarized by percentages. The average content and application scores were compared between different demographic groups using analysis of variance. Nonparametric analyses of variance also were conducted to test the sensitivity of the results to the assumption of normality. The nonparametric analyses are not shown, as the results were consistent with the original analysis of variance models. An extension of logistic regression, generalized estimating equations with a logic link, was used to compute the predicted probability of answering questions correctly, while accounting for the multiple questions answered by each student. The distributions of the percentages of content and application questions answered correctly were compared by adding an indicator variable to this analysis to identify if a response was to a content or application question. A P-value of less than 0.05 was considered significant for all hypothesis testing. SAS version 9 (SAS Institute, Inc., Cary, NC) was used to perform all analyses.

Results

Of the 839 students enrolled at the five participating high schools, 802 completed questionnaires (95.6%). 13 questionnaires were unusable due to having more than one missing answer or to having been defaced leaving 789 usable questionnaires. The demographic characteristics of the study population are presented in Table 1. The study subjects were evenly divided by gender, were predominantly White, and two-thirds lived with both parents. This cohort reported that 46% of their health knowledge came from school sources, 29% from parents, 20% from media, and 4% from friends.

Overall, the study population answered 54% of the health knowledge content questions correctly and 75% of the health knowledge application questions correctly with no significant differences between schools. As shown by Figure 1, the data for correct responses are similarly distributed with the two curves being displaced one from another by about 20 percentage points. The distributions are skewed left so the means, reported above, are slightly lower than the medians (58% and 77% for content and application, respectively).

Table 2 displays the health content and health application scores as percentages as well as the relationships between the subjects’ demographics and their health knowledge scores in the two domains of content and application. We observed that females had higher scores than males, and significant differences in scores were associated with ethnicity, the level of education attained by the respondents’ parents, family income, parents’ exercise habits, subject’s body type and the subjects’ smoking habits. In contrast, neither the students’ exercise habits, nor their living arrangements, nor their reported sources of health information were significantly associated with differences in health content or health application scores. Regarding specific health areas, questions most likely to be answered correctly were in the areas of HIV/AIDS, risky behaviors, sexuality, and obesity and areas least likely to be answered correctly were cancer and nutrition (data not shown).

Discussion

Assessing clinically relevant health knowledge of young Americans is a logical initial step as we attempt to improve American health literacy and improve the ability of physicians and patients to understand one another in clinical settings. The education and healthcare communities are deeply engaged in trying to understand not only what but also how students in the Millennial generation learn.9,10,14,20-25 The fact that 18 year old high school seniors are better able to answer health application questions than health content questions emphasizes our need to understand how young Americans are acquiring their health knowledge. Their access to information is unprecedented and it may be useful to consider a model for their knowledge accumulation as multiple domains with overlapping intersections as shown in Figure 2. The study subjects, most of whom were 18 years of age, are in the middle of the Millennial Generation, namely those born between 1980 and 2000. Studies to date on the attitudes and behaviors of the Millennials portray them as being optimistic, team-oriented achievers who embrace user-generated and user-controlled technology and are comfortable navigating complex multimodal digital environments.22,26,27 Many US school districts continue to provide most of their health education in a single semester class in the 10th or 11th grade. However, high school students in contemporary America live among sound bites and fleeting images where much health related information is presented to them as health advice bullets, such as, don’t smoke, do exercise, practice safe sex, wear sunscreen, and don’t drink the tap water in Mexico. The result is that they often do not know or understand the content from which the advice was derived. This type of advice-driven knowledge is likely to restrict and limit problem solving when faced with new or complex situations involving behavioral choices that impact health. For example, they may know not to drink the water in Mexico, but not realize that the ice in their soft drink in Mexico may be just as dangerous as the tap water. Although the Internet is being widely used to deliver health behavior change interventions aimed at adolescents and young adults, generalizable effective strategies are in their infancy.4,7,10,13,16 Due to the increasingly complex medical therapies that are in place today a minimum level of understanding is necessary to grasp what healthcare providers are asking their patients to do. The present study has limitations. First, our results apply to 18 year old high school seniors living in the United States, and specifically, in Central Pennsylvania. There were many areas of interest in addition to the nine we used and several other knowledge domains, in addition to those of content and application, as used in this study. However, we were constrained by time limitations at the participating high schools which required that the questionnaire not take more than 25 minutes to complete. We constructed the two domains of questions with a similar range of difficulty. The fact that we did not observe any differences in the scores between the two domains of questions when the survey was piloted among two groups of healthcare professionals and one group of medical students indicates that there was a similar level of difficulty for the two domains of questions. The subjects in this study reported that their schools were their largest source of health information, followed by media and parents. The fact that the questionnaire was completed at school and during school hours may have influenced their choice. Additional studies of Millennials in other countries are needed to understand their most important sources of health information. The major finding of this study, namely, that high school seniors have higher levels of applied health knowledge compared to health content knowledge challenges the idea that a hierarchical learning model applies today in the acquisition of clinically relevant health knowledge. One of the logical next steps is to determine not only how Millennials acquire health knowledge but also if this knowledge becomes static or remains dynamic. Given what we now know about both the increasing amount of health information available to Millennials and their different patterns of knowledge acquisition, it is timely that the stakeholders in health education adapt teaching methods to confront the reality that the Millennial Generation and their successors will soon obtain the majority of their health information using new learning patterns and from ever evolving sources.

References

1. 

MA Abrams, P Klass, B P Dreyer. Health literacy and children: introduction. Pediatrics 2009;124 Suppl 3:S262-4.

2. 

DW Baker, JA Gazmararian, MV Williams. Functional health literacy and the risk of hospital admission among Medicare man aged care enrollees. Am J Public Health. 2002;92:1278-83.

3. 

DA DeWalt, A Hink. Health literacy and child health outcomes: a systematic review of the literature. Pediatrics 2009;124 Suppl 3:S265-74.

4. 

JA Manganello. Health literacy and adolescents: a framework and agenda for future research. Health Educ Res 2008;23:840-7.

5. 

HS Yin, M Johnson, AL Mendelsohn. The health literacy of parents in the United States: a nationally representative study. Pediatrics 2009;124 Suppl 3:S289-98.

6. 

PJ Schulz, K Nakamoto. Health literacy and patient empowerment in health communication: the importance of separating conjoined twins. Patient Educ Couns 2012;90:4-11.

7. 

LS Suggs, C McIntyre. Are we there yet? An examination of online tailored health communication. Health Educ Behav 2009;36:278-88.

8. 

L Baker, TH Wagner, S Singer, MK Bundorf. Use of the internet and email for health care information. JAMA 2003;289:2400-6.

9. 

TR Eng, A Maxfield, K Patrick. Access to health information and support. JAMA 1998;280:1371-5.

10. 

NJ Gray, JD Klein, PR Noyce. Health information-seeking behaviour in adolescence: the place of the internet. Soc Sci Med 2005;60:1467.

11. 

DE Nelson, GL Kreps, BW Hesse. The health information national trends survey (HINTS): development, design, and dissemination. J Health Commun 2004;9:443-60.

12. 

N Tustin. The role of patient satisfaction in online health information seeking. J Health Commun 2010;15:3-17.

13. 

S Zhao. Parental education and children’s online health information seeking: beyond the digital divide debate. Soc Sci Med 2009;69:1501-5.

14. 

C Dziuban, P Moskal, J Hartman. Higher education, blended learning and the generations: knowledge is power - no more. Elements of quality online education: Engaging communities. Needham, MA: Sloan Center for Online Education, 2005.

15. 

A Luk, P Aslani. Tools used to evaluate written medicine and health information document and user perspectives. Health Educ Behav 2011;38:389-403.

16. 

LJ Solomon, JY Bunn, BS Flynn. Mass media for smoking cessation in adolescents. Health Educ Behav 2009;36:642-59.

17. 

EJ Furst. Bloom’s taxonomy of educational objectives for the cognitive domain: Philosophical and educational issues. Rev Educ Res 1981;51:441-53.

18. 

DR Krathwohl. A revision of Bloom’s taxonomy: an overview. Theory Into Practice 2002;41:212-8.

19. 

SM Lee, CR Burgeson, JE Fulton, CG Spain. Physical education and physical activity: results from the School Health Policies and Programs Study 2006. J Sch Health 2007;77:435-63.

20. 

D Marks. Literacy, instruction, and technology: meeting millennials on their own turf. AACE 2009;17:363-77.

21. 

AP McGlyn. Teaching millennials, our newest cultural cohort. Education Digest: Essential Readings Condensed for Quick Review 2005;71:12-6.

22. 

D Oblinger. Boomers gen-xers millennials. EDUCAUSE review 2003;500:36.

23. 

TC Reeves. How do you know they are learning? The importance of alignment in higher education. Int J Learn Technol 2006;2:294-309.

24. 

C DiLullo, P McGee, RM Kriebel. Demystifying the Millennial student: a reassessment in measures of character and engagement in professional education. Anatomic Sci Educ 2011;4:214-26.

25. 

M Monaco, M Martin. The millennial student: a new generation of learners. Athlet Train Educ J 2007;2:42-6.

26. 

PM Valkenburg, J Peter. Preadolescents’ and adolescents’ online communication and their closeness to friends. Dev Psychol 2007;43:267.

27. 

PM Valkenburg, J Peter. Online communication among adolescents: an integrated model of its attraction, opportunities, and risks. J Adolesc Health 2011;48:121-7.

Figure 1.

Data analysis: numbers of subjects/percentage of health knowledge questions answered correctly by 18 year-old American students.

jphr-2013-1-e8-g001.jpg
Figure 2.

Knowledge relationship for Millennial students.

jphr-2013-1-e8-g002.jpg
Table 1.

Demographics of the high school senior study population.

Variables %
Gender
  Male 50
  Female 50
Ethnicity
  African American 3
  Caucasian 85
  Asian American 3
  Indian native 1
  Hawaiian other 17
Living with
  Both parents 67
  Mother 22
  Father 6
  Other 5
Mother’s highest level of education
  Some High School 6
  High School graduate 35
  Some College 17
  College graduate 28
  Graduate degree 14
Father’s highest level of education
  Some High School 8
  High School graduate 37
  Some College 12
  College graduate 26
  Graduate degree 17
Family’s total annual income
  <$25,000 3
  $25,000 to $50,000 11
  $50,000 to $100,000 27
  >$100,000 17
  Don’t know 42
Student’s exercise habits
  Little or none 17
  1-2 times per week 21
  3 or more times per week 33
  Play on a high school or recreational athletic team 29
Student’s smoking habit
  Never 78
  Occasionally 12
  Every day 10
Student’s body type
  About average 33
  Slender 19
  Athletic 40
  Full-figured 8
Mother’s exercise habits
  None - occasionally 39
  1-2 times per week 29
  3 or more times per week 21
  Don’t know 11
Father’s exercise habits
  None - occasionally 32
  1-2 times per week 25
  3 or more times per week 28
  Don’t know
Mother’s body type
  About average 52
  Slender 19
  Athletic 5
  Full-figured 24
Father’s body type
  About average 47
  Slender 11
  Athletic 20
  Full-figured 22
Student’s largest source of health information
  School 46
  Media 20
  Parents 29
  Friends 5
Table 2.

Relationships between the subjects’ demographics and health knowledge content and health knowledge application scores.

Variables Content P-value Application P-value
Mean SD Mean SD
Gender
  Males 52 17 0.0002 71 19 ≤ 0.0001
  Females 57 15 78 14
Ethnicity
  Black 45 15 63 21
  White 55 16 0.001 76 16 0.001
  Asian 54 19 74 17
  Other 50 16 72 18
Smoking
  Never 55 15 76 15
  Occasionally 51 17 0.009 72 20 ≤ 0.0001
  Daily 51 18 69 22
Subject’s body type
  About average - - - 77 15
  Slender - - - 76 17 0.03
  Athletic - - - 73 17
  Full-figured - - - 73 19

[i]   SD, standard deviation.

Abstract views:
2427

Views:
PDF
520
HTML
434

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM


Copyright (c) 2013 Tom Lloyd, Michele L. Shaffer, Christy Stetter, Mark D. Widome, John Repke, Michael R. Weitekamp, Paul J. Eslinger, Sandra S. Bargainnier, Ian M. Paul

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
 
© PAGEPress 2008-2017     -     PAGEPress is a registered trademark property of PAGEPress srl, Italy.     -     VAT: IT02125780185