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Attachment 3 - Notes of various types done within the A in the class

Notes of various types done within the A in the class
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Hist & Historians (HIST 300)

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Medical cost analysis of a school district worksite wellness program

Ray M. Merrill

a,⁎

, James D. LeCheminant

b

aDepartment of Health Science, College of Life Sciences, Brigham Young University, Provo, UT, USA bDepartment of Exercise Sciences, College of Life Sciences, Brigham Young University, Provo, UT, USA

article info abstract

Available online 26 January 2016 Objective: To evaluate whether participation in a worksite wellness program differs by age and sex and is associated with frequency and average cost of medical claims: Healthcare cost data were available for school district employees during the academic years ending in 2009 through 2014. The wellness program was available in the later 3 years. The frequency and the average cost of medical claims were compared between the 3 years prior to and the 3 years during the wellness program: Wellness program participation increased from 65% 2011–2012 to 79% 2012–2013. The increase occurred within age-groups and for males and females. The average age of program participants was significantly lower in 2011–2012 (48 vs. 49, p= 0), but similar in the next 2 academic years. Participation in at least one behavior change campaign in each year was 52%, 53%, and 73% of all wellness program participants, respectively. Female employees were significantly more likely to complete one or more behavior change campaigns in each year of the wellness program (pb0). The percentage of employeesfiling at least one claim per time period was higher for those in the wellness program (pb0), but average medical claims payments were lower for those in the wellness program. After subtracting program costs, the cost savings from the wellness program was $3,612,402. The benefit-to-cost ratio was 3.6: Participation in the wellness program resulted in lower average medical claim costs than non-participation but number of claims were higher in program participants. © 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (creativecommons/licenses/by-nc-nd/4.0/).

Keywords: Cost-effectiveness Prevention Return on investment Worksite health promotion

Introduction

The cost of insurance premiums and employee medical claims costs have increased in recent years and are at an all-time high (The Henry J. Kaiser Family Foundation, 2014). According to the Kaiser Family Foundation and Health Research & Educational Trust, the average cost of health insurance premiums for a family of 4 has increased by 69% in the last 10 years (to $16,834) with employee contributions increasing by 81% (Trust, K. F. F. and H. R. E., 2014). Additionally, in the Western United States among companies consisting of 200 or more employees, premiums and worker contributions among employees covered by employer-sponsored coverage increased from $2194 in 1999 to $ in 2014 (The Henry J. Kaiser Family Foundation, 2014). In an attempt to curb rising costs, many employers are adopting worksite health promotion programs (Allen, 2015; Caloyeras et al., 2014; Liu et al., 2013; Merrill, 2013; LeCheminant and Merrill, 2012; Henke et al., 2011 ). Several studies have identified medical cost savings resulting from employee-based health promotion programs (Maeng et al., 2013; Merrill et al., 2011; Patel et al., 2011; Patel et al., 2010; Naydeck

et al., 2008; Aldana et al., 2005; Serxner et al., 2003; Serxner et al., 2001; Aldana, 2001). Reducing health care costs is not the only rationale for worksite wellness programs, but they can help employees be more responsible for their lifestyle choices, promote better general health, improve employee productivity, reduce absences and illness, shift the healthcare paradigm from treatment to prevention, improve productiv- ity, increase employee job satisfaction, increase retention, increase morale, and so on (Chen et al., 2015; CDC, 2014; Michaels and Greene, 2013; Niessen et al., 2012; Witt et al., 2013). Nevertheless, the effectiveness of worksite wellness programs has been questioned (Felter et al., 2013; Frakt, 2014; Mattke and Liu, 2015 ), particularly for their ability to produce afinancial return on investment (Baxter et al., 2014). In a systematic review of 33 methodo- logically rigorous peer-reviewed U. wellness program reports, the authors found evidence for positive effects on diet, smoking, alcohol use, exercise, physiologic markers, and health care costs but limited evidence for absenteeism and mental health (Mattke et al., 2012). A recent review of thefinancial return on investment associated with worksite health promotion programs showed that the quality of the study design was important; the return on investment ranged from 0 (high-quality study designs) to 2 (low-quality study designs) (Baxter et al., 2014). Notably, Baxter et al. also reported that the 12 ran- domized controlled trials included in this study produced, on average, a negativefinancial return on investment (Baxter et al., 2014). Other

Preventive Medicine Reports 3 (2016) 159– 165

⁎Corresponding author at: Department of Health Science, Brigham Young University, 2063 Life Sciences Building, Provo, UT 84602, USA. E-mail address:Ray_Merrill@byu(R. Merrill).

dx.doi/10.1016/j.pmedr.2016.01. 2211-3355/© 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CCBY-NC-ND license (creativecommons/licenses/by-nc-nd/4.0/).

Contents lists available atScienceDirect

Preventive Medicine Reports

journal homepage:ees.elsevier/pmedr

published studies have reported similar unfavorablefindings (Rongen et al., 2013). However, it has been noted that some programs have better success than others, likely depending on the extent that best practices are utilized (Goetzel et al., 2014). Based on a systematic review of the literature,Kaspin et al. (2013)suggested that characteristics of success- ful health promotion programs often include (1) a corporate culture of wellness; (2) supportive company leadership; (3) participation- friendly corporate policy and physical environment; (4) programs adapted to employee needs; (5) community health organizations provided support, education, and treatment; (6) utilized technology to facilitate health risk assessments and health education; and (7) decreased health risks and lower healthcare costs. Nevertheless, it appears that additional research is needed to better understand the effectiveness of worksite health promotion, particularly when compre- hensive programs are implemented. Since the 2011–2012 academic year, the district has utilized a well- ness program provided by WellSteps, LLC. The program incorporated known practices thought to improve the health of employees, including several of the components of a successful program noted in the review cited above (Kaspin et al., 2013). The aim of the program was to improve employee health behaviors, lower elevated health risks, pre- vent chronic diseases, and consequently, curb increasing healthcare costs. Previous research has assessed health behaviors and outcomes in the district (LeCheminant et al., 2015; Merrill and Sloan, 2014). The district program is unique in that it was applied over 3 years to a multi-site school district with the majority of the employees being teachers. Little evidence is currently available showing the effect of the wellness program on healthcare costs over time for this population. The purpose of the current study was to extend previous research by evaluating the extent participation in the worksite wellness program was associated with frequency and average cost of submitted medical claims. Participation in the wellness program was also assessed by age and sex, and the association between wellness program participation and the primary outcome measures were adjusted for these variables. We hypothesized that wellness program participation would differ according to age and sex, and that it would be associated with the fre- quency and average cost of submitted medical claims, after adjusting for age and sex.

Methods

A retrospective cohort design was used that involved existing well- ness program participation status and healthcare claims data. Previous research has assessed the same employee population in terms of the effectiveness of the wellness program on decreasing health risks (LeCheminant et al., 2015; Merrill and Sloan, 2014). Each academic year employees were invited to complete a personal health assessment (PHA), biometric screening, and selected behavior change campaigns. The PHA and biometric screening were generally completed in the fall, and the behavior change campaigns were offered throughout the year. Participants were employed by the district. The school district included 6 high schools, 8 junior high schools, and 31 elementary schools. Only eligible employees for healthcare coverage were included in the current study. While data for this study cover the academic years 2008 – 2009 through 2013–2014, the wellness program was offered in the academic years 2011–2012, 2012–2013, and 2013–2014. The study was approved by the Institutional Review Board at Brigham Young University (IRB E1 5259). Data on healthcare medical claims costs were also used in this study. The district is fully insured with a retained-retention agreement that makes the plan act very much like a self-funded health plan. Each month the district pays a health insurance premium for the cost of med- ical care and a small premium for reinsurance of catastrophic claims. High cost (catastrophic) claims above $250,000 are reinsured by a stop loss policy and are not paid for by the school district. Therefore,

any annual per person claims above $250,000 are capped at $250,000. The annual medical claims data, as well as the biometric screening, PHA, and WellSteps campaign data reflect the academic calendar.

Wellness program

Enrollment in the wellness program was voluntary. The overall program included the following components: administrative planning, evaluation, culture change and communication strategy analysis, screenings for biometric measures, and health campaigns focused on changing behavior (LeCheminant et al., 2015; Merrill and Sloan, 2014). Thebiometric screenings (BMI, blood pressure, cholesterol, and glucose) were available to all employees at no cost to them. Participants had the option to be screened on location and have a health nurse review the results, or receive screening and review of results through their family physician. The 36-question PHA was written at a 6th-grade level, available to all employees, and assessed nutrition, physical activity, health status, life-satisfaction, sleep quality, smoking, demographics, productivity, absenteeism, and job satisfaction outcomes. The survey questions were based on the 2006 Behavioral Risk Factor Surveillance System (BRFSS) survey (Centers for Disease Control and Prevention, 2006), combined with several nutrition questions from another validated instrument (Block et al., 1990). Upon completion, employee PHA data were used to generate behavior specific health scores. For each behavior and each biometric category, a letter grade (A–E) was assigned based on established risk categories. Hence, a summary health report card was generated for each employee. High grades were recognized and individ- uals were givenideas on how to maintain correspondingbehaviors grades wereflagged and used to create individualized programs for change. Poor health behaviors and elevated risks were also used to cre- ate achievable goals that each person can choose to pursue. The summa- ry health report card was reviewed with the employee by a nurse or physician in order to evaluate and improve the employee's health. Details of the WellSteps campaigns are presented inTable 1. Each campaign typically lasted about 5 weeks and covered topics related to health, such as diet, physical activity, weight loss, posture and balance, and health maintenance. Three tofive campaigns were available to employees each year.

Benefits-based incentive plan requirements

Program participation was promoted using incentives. In the academic year ending in 2012, employees who completed the PHA and biometric screening had a $20 lower copay on doctor's office visits and their deductible was $350 versus $700. In the academic year ending in 2013, employees who completed the PHA and biometric screening had up to a $20 lower copay on doctor's office visits, their deductible was $350 versus $700, and they also received a $40 monthly premium discount. In the academic year ending in 2014, the same incentives were applied, but now employees needed to complete the PHA, biomet- ric screening, and one or more WellSteps campaign, or submit a form that had options such as a communityfitness event, proof of gym membership attendance, meeting with a dietician, completing a course to quit smoking, or any class where the focus was to improve health or relieve stress. In this study, completion of the wellness program in any given year means the participant completed the PHA and biometric screening. The behavior change campaigns were optional.

Statistical techniques

Analyses were based on 4133 eligible employees of the district during the academic years ending in 2009 through 2014. Of this num- ber, 2438 (59%) were employed continuously over these 6 years. Data were analyzed using the statistical software package PC-SAS (version 9; SAS Institute, Inc., 2014) and Microsoft® EXCEL 2013.

Means, standard deviations, and percentages characterize the data. Medical costs were adjusted for medical cost inflation usingTom's Inflation Calculator's's (2015). Average dollar ($) payment per eligible employee was derived and presented according to wellness program participant status by year. The yearly payment for the nonwellness participants was also adjusted for the same distribution of age and sex as the wellness participants. A number of claimsfiled were compared between wellness and nonwellness program participants using the chi-square statistic. Average annual $ payment per eligible employees was compared between wellness and nonwellness program partici- pants using thetstatistic. Statistical significant was based on the 0. level of significance.

Results

The number of employees in any given time period ranged from 3089 to 3283 (Table 2). Approximately 73% of employees were female and the mean age increased 2% over the study period. The number of employees who were employed all 6 years was 2438. Approximately 73% of these employees were female. The percentage that completed the PHA, biometric screening, and one or more behavior change campaigns increased each academic year (Table 3). Participation in one or more behavior change campaigns in each time period reflected 52%, 53%, and 73% of all wellness plan participants, respectively. In 2011–2012, age was significantly lower for those involved in the wellness program (48 vs. 49,p= 0), but not in the next two academic years. The increase in wellness participa- tion over the three academic years occurred in each age-group (Fig. 1). Wellness programparticipation was similar betweenmales and females in each time period. The greatest level of participation was among employees aged 40–49 years. Similar results were seen for PHA, biomet- ric screening, and behavior change campaign participation, except fe- male employees were significantly (pb0) more likely to complete one or more behavior change campaigns each year (37% vs. 24% in 2011–2012, 43% vs. 29% in 2012–2013, 62% vs. 47% in 2013–2014). For employeesin thewellnessprogramthatfileda claim, themedian payment was $795 in 2011–2012, $800 in 2012–2013, and $753 in 2013 – 2014. Corresponding median payments for those not in the well- ness program were $824, $832, and $816. The percentage of employeesfiling at least one claim per time period was higher for those in the wellness program (Table 4). However, average medical claims payments were significantly lower each of the 3 years for those in the wellness program (tstatisticp= 0, 0, 0,

respectively). The total reduction in total payments was calculated by taking the difference between the total dollar payment assuming that everyone had the same age and sex distributions as those not in the in- centive wellness program and the total dollar payment inTable 4and then summing the differences over the three academic years, which yielded $5,025,138. The total cost of the wellness program over the three academic years was $1,412,736. Hence, the cost savings from the wellness program was $3,612,402. The benefit-to-cost ratio was 3. The remaining results apply to 2438 individuals who were continu- ously employed over the 6-year study period. Among these individuals, there were 277 (11%) who did not participate in the wellness program any of the years, 114 (4%) who participated once, 181 (7%) who participated twice, and 1866 (76%) who participated all 3 years. With respect to the behavior change campaigns, which are optional in the wellness program, there were 763 (31%) who did not participate in the campaigns in any of these years, 591 (24%) who participated in thecampaigns(1or more) campaigns1 year,298 (12%) whopartic- ipated in the campaigns 2 years, and 786 (32%) who participated in the campaigns all 3 years. Of those employees continuously employed throughout the 6-year study, average medical claims payments are shown according to well- ness program and behavior change campaign participation (Fig. 2). For those who participated in the wellness program one or more years during its offering (2011–2012, 2012–2013, 2013–2014), their average medical claims payments increased 3% over the prior 3-year period (2008–2009, 2009–2010, 2010–2011). For those who did not partici- pate in the wellness program, their average medical claims payments increased 16%. For those who participated in the behavior change campaigns one or more years during their offering, their average medi- cal claims payments increased 4%. For those who did not participate in any of the behavior change campaigns, their average medical claims payments increased 27%.

Discussion

Participation in the wellness program increased over the three academic years they were offered and likely reflects the increased requirements and incentives associated with the program. Wellness program participation was highest among 40–49 year olds; however, there was no difference in the percentage of males and females in the program, although more females than malesparticipated in theoptional behavior change campaigns. The primary aim of this study was to examine the association between participation in the wellness program and medical claims

Table 2 Eligible employees by sex, age, and continuous employment.

Academic year Eligible employees Females Age Eligible employees employed all 6 years Females Age No. % Mean Standard deviation No. % Mean Standard deviation 2008 – 2009 3118 73 47 10 2438 73 46 10. 2009 – 2010 3089 73 48 11 2438 73 47 10. 2010 – 2011 3094 73 48 11 2438 73 48 10. 2011 – 2012 3269 73 49 11 2438 73 49 10. 2012 – 2013 3202 73 49 11 2438 73 50 10. 2013 – 2014 3283 72 49 11 2438 73 51 10.

Table 3 Level of participation in the wellness program by academic year.

Academic year Number of eligible employees Wellness programa Personal health assessment Biometric screening Behavior change campaign≥ 1 No. % % % % 2011 – 2012 3269 65 65 65 34. 2012 – 2013 3202 73 74 73 39. 2013 – 2014 3283 79 79 81 58. aCompleted the PHA and biometric screening. The behavior change campaigns were optional.

among the sample population. We note that among those that partici- pated in the wellness program, the average medical claim cost was not reduced during the pre and post intervention periods. This may be due to the year-over-year increases in medical costs experienced across the United States (National Center for Health Statistics, 2015). However, there was a difference in the change in medical claim costs between the participants and non-participants of the program. As noted above, the difference in medical claim costs between wellness partici- pants and non-participants during the years the wellness program and behavior change campaign plans were offered was $3,612,402, with a benefit-to-cost ratio of 3. Both participation in the wellness program or the wellness program with the optional behavior change campaigns resulted in lower average medical claim payments. Specifically, there was a 3% increase in average medical claims payments from pre to post periods for those participating in the wellness program while a 16% increase in average medical claims payments from pre to post periods for those not participating in the wellness program. Corre- sponding increases in the average medical claims payments for those also participating or not participating in the behavior change campaigns were 4% and 27%, respectively. Importantly, those participating in the wellness program had a higher percentage of 1 or more medical claims per year than those who did not participate, even though the average cost of the claims was lower for those participating in the program. In other words, those in the program utilized the system more often but their specific claims did not tend to be as expensive as those not participating in the program. We do not know the exact reason for this. However, it may be that those on the wellness program had medical visits focused on

prevention while those not in the wellness program were more likely receiving treatment for illness. These data and results are meaningful and unique to the population studied. The majority of the employees consists of teachers. Teachers provide an extremely valuable service to the children they teach and their families. However, recent evidence indicates that teachers experi- ence similar risks for poor health behaviors as the students they teach, such as poor diet, prolonged sedentary time, and stress (Eaton et al., 2007; Woynarowska-Soldan and Tabak, 2013). There is also evidence that stress has increased in many teachers compared with previous years (MetLife, 2013). These indicators are likely associated with medi- cal claims costs. The results of this study indicate that various compo- nents of worksite wellness programs, including incentives and behavior change campaigns, are associated with lower average medical costs. In theory, better health would be associated with lower medical claims and hopefully, better productivity and engagement in the classroom. This study has certain strengths but also weaknesses. Strengths include a large sample size, the inclusion of medical claims data, a multi-site employee population, and a retrospective cohort design. However, the design is not a randomized controlled trial and there is a possibility of selection bias. As noted in the introduction, recent studies have indicated that stronger study designs (specifically, randomized controlled trials) do not always show a positive or robust return on in- vestment while weaker study designs tend to show a stronger return on investment. In addition, this study is able to report medical claims (an important outcome but rarely reported in the literature) by participa- tion in the wellness program. However, the claims data are not linked

0

10

20

30

40

50

60

70

80

90

100

< 30 30-39 40-49 50-59 60 +

Percentage

2011-12 2012-13 2013-

Fig. 1 participation according to age and academic year.

Table 4 Employeesfiling claims and average payment per academic year according to participation status in the wellnessprogram.

Wellness program

No wellness program

No wellness programa Academic year

Number Employees filing≥ 1 claims, %

Average annual $ payment per eligible employee

Number Employees filing≥ 1 claims, %

Average annual $ payment per eligible employee

Employees filing≥ 1 claims, %

Average annual $ payment per eligible employee

Total annual $ payment

Total annual $ paymentb 2011 – 2012 2218 91 3752 1051 68 3960 67 4094 12,484,324 13,244, 2012 – 2013 2391 91 3160 811 79 4822 76 4635 11,466,264 14,993, 2013 – 2014 2729 90 3153 554 72 3569 68 3423 10,582,863 11,320,

Note: The number of employeesfiling≥1 claims per year was significantly greater (Chi-squarepb0) for those in the wellness program compared with those not in the program. Average annual $ payment per eligible employee was significantly lower each year for those in the wellness program compared with those not in the program (tstatisticp= 0, 0, 0, respectively). aAdjusted for the age and sex distribution of the incentive plan participants. bBased on the assumption that everyone had the same age and sex distributions as those not in the incentive plan.

The Henry J. Kaiser Family Foundation, 1999-2014. Premiums and worker contributions among workers covered by employer-sponsored coverage. Retrieved fromhttp:// kff/interactive/premiums-and-worker-contributions/. Tom's Inflation Calculator. Available athalfhill/inflation_js.html. Accessed May 29, 2015. Trust, K. F. F. and H. R. E., 2014. Employer Health Benefits 2014 Summary of Findings. Re- trieved fromfiles.kff/attachment/ehbs-2014-abstract-summary-of-findings.

Witt, L., Olsen, D., Ablah, E., 2013 factors for small and midsized businesses to implement worksite health promotion. Health Promot. Pract. 14 (6), 876–884. Woynarowska-Soldan, M., Tabak, I., 2013 enhancing behaviors of teachers and other school staff. Med. Pr. 64 (5), 659–670.

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Attachment 3 - Notes of various types done within the A in the class

Course: Hist & Historians (HIST 300)

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University: Indiana State University

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Medical cost analysis of a school district worksite wellness program
Ray M. Merrill
a,
⁎, James D. LeCheminant
b
a
Department of Health Science, College of Life Sciences, Brigham Young University, Provo, UT, USA
b
Department of Exercise Sciences, College of Life Sciences, Brigham Young University, Provo, UT, USA
abstractarticle info
Available online 26 January 2016 Objective: To evaluate whether participation in a worksite wellness program differs by age and sex and is
associated with frequency and average cost of medical claims. Methods: Healthcare cost data were available for
school district employees during the academic years ending in 2009 through 2014. The wellness program was
available in the later 3 years. The frequency and the average cost of medical claims were compared between
the 3 years prior to and the 3 years during the wellness program. Results: Wellness program participation
increased from 65.6% 2011–2012 to 79.7% 2012–2013. The increase occurred within age-groups and for males
and females. The average age of program participants was significantly lower in 2011–2012 (48.2 vs. 49.4,
p= 0.0099), but similar in the next 2 academic years. Participation in at least one behavior change campaign
in each year was 52.1%, 53.7%, and 73.7% of all wellness program participants, respectively. Female employees
were significantly more likely to complete one or more behavior change campaigns in each year of the wellness
program (pb0.0001). The percentage of employees filing at least one claim per time period was higher for those
in the wellness program (pb0.0001), but average medical claims payments were lower for those in the wellness
program. After subtracting program costs, the cost savings from the wellness program was $3,612,402. The
benefit-to-cost ratio was 3.6. Conclusion: Participation in the wellness program resulted in lower average medical
claim costs than non-participation but number of claims were higher in program participants.
© 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords:
Cost-effectiveness
Prevention
Return on investment
Worksite health promotion
Introduction
The cost of insurance premiums and employee medical claims costs
have increased in recent years and are at an all-time high (The Henry J.
Kaiser Family Foundation, 2014). According to the Kaiser Family
Foundation and Health Research & Educational Trust, the average cost
of health insurance premiums for a family of 4 has increased by 69% in
the last 10 years (to $16,834) with employee contributions increasing
by 81% (Trust, K. F. F. and H. R. E., 2014). Additionally, in the Western
United States among companies consisting of 200 or more employees,
premiums and worker contributions among employees covered by
employer-sponsored coverage increased from $2194 in 1999 to $6353
in 2014 (The Henry J. Kaiser Family Foundation, 2014). In an attempt
to curb rising costs, many employers are adopting worksite health
promotion programs (Allen, 2015; Caloyeras et al., 2014; Liu et al.,
2013; Merrill, 2013; LeCheminant and Merrill, 2012; Henke et al.,
2011). Several studies have identified medical cost savings resulting
from employee-based health promotion programs (Maeng et al.,
2013; Merrill et al., 2011; Patel et al., 2011; Patel et al., 2010; Naydeck
et al., 2008; Aldana et al., 2005; Serxner et al., 2003; Serxner et al.,
2001; Aldana, 2001). Reducing health care costs is not the only rationale
for worksite wellness programs, but they can help employees be more
responsible for their lifestyle choices, promote better general health,
improve employee productivity, reduce absences and illness, shift the
healthcare paradigm from treatment to prevention, improve productiv-
ity, increase employee job satisfaction, increase retention, increase
morale, and so on (Chen et al., 2015; CDC, 2014; Michaels and Greene,
2013; Niessen et al., 2012; Witt et al., 2013).
Nevertheless, the effectiveness of worksite wellness programs has
been questioned (Felter et al., 2013; Frakt, 2014; Mattke and Liu,
2015), particularly for their ability to produce a financial return on
investment (Baxter et al., 2014). In a systematic review of 33 methodo-
logically rigorous peer-reviewed U.S. wellness program reports, the
authors found evidence for positive effects on diet, smoking, alcohol
use, exercise, physiologic markers, and health care costs but limited
evidence for absenteeism and mental health (Mattke et al., 2012). A
recent review of the financial return on investment associated with
worksite health promotion programs showed that the quality of the
study design was important; the return on investment ranged from
0.26 (high-quality study designs) to 2.32 (low-quality study designs)
(Baxter et al., 2014). Notably, Baxter et al. also reported that the 12 ran-
domized controlled trials included in this study produced, on average, a
negative financial return on investment (Baxter et al., 2014). Other
Preventive Medicine Reports 3 (2016) 159–165
⁎Corresponding author at: Department of Health Science, Brigham Young University,
2063 Life Sciences Building, Provo, UT 84602, USA.
E-mail address: Ray_Merrill@byu.edu (R.M. Merrill).
http://dx.doi.org/10.1016/j.pmedr.2016.01.002
2211-3355/© 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Contents lists available at ScienceDirect
Preventive Medicine Reports
journal homepage: http://ees.elsevier.com/pmedr

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