Educational gaming and afterschool students’ science and drug prevention knowledge and 

attitudes 

!  

A program evaluation report for HTF community drug prevention coalition 

Conducted by Truman State University Student Research Team: 

Taylor Cichon, Truman State University  

15 S. Lincoln St. Batavia, IL, 60510; 630 205 4074; tcc3172@truman.edu 

Ben Lasser, Truman State University 

31799 E. 1800 N. Rd; Colfax, IL 61728; brl1512@truman.edu; 309-826-5976 

Nicole Dunseith, Truman State University 

2310 W. 184th St. Torrance, CA 90504; nad2322@truman.edu; 310-938-9081 

Angela Sas, Truman State University  

12453 W 105th St Overland Park, KS 66215; Als7533@truman.edu; 913 944 1103 

Hailee Baer, Truman State University 

6704 NW 102 Ct; Kansas City, MO 64145; hfb1486@truman.edu; 816 419 5329 

Haley Bylina, Truman State University 

3830 W 109th St; Chicago, IL 60655; hlb3347@truman.edu; 773 706 6470 

Marissa Leong, Truman State University 

4435 Conleth Dr; St Louis, MO 63129; mel8872@truman.edu; 314 620 1965 

Note: This community-based participatory research/evaluation project was done in conjunction 
with the Heartland Task Force C2000 Substance Abuse Prevention Coalition 

mailto:tcc3172@truman.edu
mailto:brl1512@truman.edu
mailto:nad2322@truman.edu
mailto:Als7533@truman.edu
mailto:hfb1486@truman.edu
mailto:hlb3347@truman.edu
mailto:mel8872@truman.edu


Educational gaming and afterschool students’ science and drug prevention knowledge and 

attitudes: A program evaluation for HTF community drug prevention coalition 

Abstract 

The Heartland Task Force C2000 Substance Abuse Prevention Coalition in rural 

Northeast Missouri purchased laptops for a local afterschool program and enthusiastically 

conducted a novel intervention for substance abuse prevention education. A digital educational 

game focused on science and drug prevention knowledge and attitudes was delivered on the 

laptop computers to at-risk elementary students in the school district’s afterschool program. After 

hour-long sessions for one day every week for six weeks, results of pre-post knowledge and 

attitude surveys noted the game neither significantly changed participants’ knowledge of science 

and drug prevention nor attitudes toward science and drug prevention. Results of the present 

evaluation study were inconsistent with other studies using technology in the classroom, possibly 

due to program delivery in the less formal afterschool setting.  Because elementary students’ 

attitudes toward drug use become more pro-use as they get older, consistent teaching about 

science and anti-drug education both during and after school is needed. 



Introduction   

The use of technology in K-12 education, especially when used as an educational support 

or resource, has demonstrated at least small to moderate positive effects on student learning. In a 

meta-analysis conducted by Lee, Waxman, Wu, Michko, and Lin, the use of technology in the 

classroom seemed to facilitate content knowledge and positive attitudes, particularly when the 

embedded tasks are challenging to the student (Lee et al. 2013, 133–146). Although teachers and 

students perceived technology-supported learning using computers and laptops as motivating and 

interesting (Godzicki et al. 2013), overall effects on learning outcomes were difficult to 

determine (Haßler, Major, and Hennessy 2015). In a synthesis, however, improvements in 

academic achievement in science as well as overall learning development were noted (Zheng et 

al. 2016). 

The use of technology tools like digital educational games on laptops and tablets have 

become more widespread and considered ‘serious’ games for training and education. For 

elementary-aged children, almost half have reported using mobile applications, especially for 

educational games (Rideout 2013). A recent literature review summarized that using digital 

educational games can be an effective teaching strategy (Backlund and Hendrix 2013). In other 



reviews, too, digital educational games improved K-16 student learning when compared to 

traditional strategies (Clark, Tanner-Smith, and Killingsworth 2016; Wouters et al. 2013); 

however, they were not more motivating. On the other hand, the effects on student learning have 

been summarized as limited (Abdul Jabbar and Felicia 2015). When additional instruction 

supplemented the educational games, though, effect increased (Wouters et al. 2013). 

Educational games for science and drug prevention knowledge/attitudes 

Science instruction has used digital educational games to support inquiry, problem-

solving, and knowledge acquisition. In a review by Li and Tsai, however, most games were 

focused on student learning of scientific concepts (Li and Tsai 2013). For elementary science 

students, technology applications in addition to other instructional methods showed promise as 

an effective teaching strategy (Slavin et al. 2014). Technology and internet access appeared to 

improve interest and motivation for science among at-risk students (Gillard 2010). In addition, 

using laptop computers with science learning software for at-risk elementary students motivated 

the students and individualized their instruction leading to standardized test score improvement 

(Zheng et al. 2014). 

Health instruction has also used digital educational games for health promotion. In an 

analysis, the games, with broad appeal to all ages and genders, demonstrated minor effects on 

knowledge and health risks (DeSmet et al. 2014). For example, in one study, a digital educational 



game with strong learning content was developed for elementary health students. Student 

motivation and knowledge improved as compared to control (Sung, Hwang, and Yen 2015). 

Specifically, for the health content area of drug prevention for adolescents, a review suggested 

that the games can improve student drug prevention knowledge but with limited effect on 

attitudes (Rodriguez, Teesson, and Newton 2013). 

For digital educational games to be most effective for knowledge and attitude change, 

they must engage the learner so they are cognitively and emotionally immersed in the game. 

Games should, therefore, include a variety of interactive tools and challenges appropriate to the 

student’s academic ability level, as well as appropriate feedback and support tools that may even 

include paper-pencil worksheets (Abdul Jabbar and Felicia 2015). In a review by Ravyse et al., 

guidelines for impactful game production included: backstory, realistic and adaptive interaction, 

as well as appropriate feedback (Ravyse et al. 2016). BrainTrain4Kids (BrainTrain4Kids n.d.) is 

a digital educational game designed to educate elementary-aged youth on the science and health 

topic of drug prevention. Students learn how drugs harm the brain and body using science-based 

educational lessons housed in interactive, online media ‘train stations’.  As students enter each 

virtual train station in sequence on the website, they are introduced to the concepts of: scientific 

inquiry, parts and functions of the brain, the nervous system, effect of drugs on the body, harmful 

effects of tobacco use, and how healthy lifestyle can improve brain function. Through interactive 



activities and games at each train station as well as supplemental printed worksheets and puzzles, 

positive attitudes and knowledge of science and health are promoted (BrainTrain4Kids n.d.). 

Elementary-aged students seem to be aware of alcohol, tobacco and other drugs, are 

knowledgeable enough to correctly identify many substances, and possess negative attitudes 

toward use (Hahn et al. 2000). A shift, however, seems to occur as students get older. For tobacco 

perceptions of upper elementary-aged students in one study, attitudes toward use became less 

negative as they progressed through the grades. Also, individual’s level of belief in the benefits 

of tobacco usage increased (Freeman, Brucks, and Wallendorf 2005). In addition, in a 

longitudinal study of elementary-aged students, intention to use substances increased as they 

progressed through elementary school grades (Andrews et al. 2003). 

In a rural Missouri county, the proportion of youth enrollment in free/reduced lunches, 

child abuse/neglect assessments, and out-of-home placements is higher than the state average 

(Adair County 2016), and juvenile court placements for parental drug use have increased since 

2010 (County Data 2015). The most current 30-day use rates show county youth using cigarettes, 

alcohol, over-the-counter drugs, hookah, and binge drinking at rates higher than the state average 

(Behavioral Health Profile 2015). Over half reported friends using alcohol and tobacco in the 

past year, and that both alcohol and tobacco would be easy to obtain. Average age of initiation 

for tobacco is 14 years old, and 13 for alcohol (County Reports 2014). The local drug prevention 



coalition, the Heartland Task Force C2000 Substance Abuse Prevention Coalition, wished to 

conduct a novel prevention intervention using recently-purchased laptops to interest and engage 

the at-risk students in drug prevention education.  

Because science and drug prevention education have had some success in using 

technology and digital educational games for learning, and students in a rural county were at 

high risk for substance abuse problems; the BrainTrain4Kids digital educational game was 

delivered by drug prevention coalition members. Conducted as a 6-week program (one day each 

week for an hour), it was held during the regularly-scheduled drug prevention session of an 

afterschool program for at-risk students in this county. Therefore, the purpose of this study was 

to determine if the game improved participants’ knowledge of science and drug prevention, and 

if the game improved participants’ attitudes toward science and drug prevention. 

Methods 

Sample 

All 77 elementary-aged youth in grades 3-5 enrolled in a school district’s afterschool 

program in a rural Missouri county were asked to participate in this study. Seventy-three (44 

girls, 31 boys; all White) of the 75 (97%) participated. No other demographics were collected 

due to school district policy. 



Instruments 

As part of the curricular package, the 21-question, paper-pencil BrainTrain4Kids 

Knowledge Assessment Instrument was used to measure participants’ pre-post program science 

and drug prevention content knowledge. The first 10 multiple-choice questions asked 

participants to identify the parts of the brain, the next six multiple-choice questions asked about 

the relationship between using drugs and effects on the brain, and the last five were true-false 

questions asking about the harmful effects of drugs. All multiple-choice questions included five 

potential answers and an option of marking “I don’t’ know”. All true-false questions included 

two potential answers and an option of marking ‘I don’t’ know’. 

Also as part of the curricular package, the 16-item, paper-pencil BrainTrain4Kids 

Attitude Assessment Instrument was used to measure participants’ pre-post program attitude 

toward science and drug prevention. All were Likert-style items to be rated on a scale of NO!=1, 

no=2, Sort of = 3, yes = 4, and YES!=5. The first 13 questions asked about level of agreement 

with pro-science and pro-health attitude statements. All 13 questions included an option of “I’m 

not sure what this question means”. The last three asked about how the participant would feel if 

someone was doing a negative health behavior. All three questions included and option of “I 

don’t understand the sentence” (BrainTrain4Kids n.d.).   



Both surveys contained questions aligned with the specific content covered in each of the 

six train stations.   

Procedure 

A one-way repeated measure design was used. After Institutional Review Board approval, 

principal and parent/guardian consent, and participant assent; participants completed the 

confidential pre-assessments one week before program start during the regularly-scheduled, 

weekly drug prevention session of the afterschool program. 

During the next six regularly-scheduled drug prevention sessions (one day each week for 

an hour) of the afterschool program, half of the participants were supervised by coalition 

members as they used laptop computers to navigate the BrainTrain4Kids website. The website 

consisted of six “train stations” or modules to teach participants about the science behind their 

brains, bodies, and drugs. During week 1/station 1, participants were shown the steps of 

scientific inquiry through the use of their senses to describe an object. Week 2/station 2 covered 

the parts of the brain and brain function. Week 3/station 3 introduced participants to the nervous 

system using interactive games, followed by week 4/station 4 which covered the harmful effects 

of drugs on the brain and body as well as why to take medication as prescribed. In week 5/station 

5, participants were shown the harmful effects of tobacco on the lungs through a controlled 



online experiment. During week 6/station 6, healthy lifestyle behaviors were encouraged in order 

to stay drug-free (BrainTrain4Kids n.d.). 

The other half of the group was also supervised by coalition members as participants 

completed the paper-pencil supportive worksheets and puzzles that accompanied the curriculum. 

After one-half hour, the two groups switched activities. Each week, the next train station and 

accompanying worksheets and puzzles were completed by participants. One week after the 

completion of the program, participants completed the confidential post-assessments also during 

the regularly-scheduled, weekly drug prevention session of the afterschool program. 

Analysis 

Responses to knowledge items were coded as correct or incorrect, with correct responses 

coded with a score of one and incorrect responses a score of zero.  All knowledge item scores 

were then summed to create a total knowledge score for each participant.  Possible scores ranged 

from 0 to 21.  The first 13 attitude items included five options that reflected participants’ 

attitudes and an additional option of “I’m not sure what this question means.”  Responses of “I’m 

not sure what this question means” were treated as missing data.   



Responses reflecting participants’ attitudes were coded from one to five with higher 

scores reflecting attitudes that were more positive.  The last three attitude items included three 

response choices that reflected participants’ attitudes and an additional option of “I don’t 

understand the sentence.”  Responses of “I don’t understand the sentence.” were treated as 

missing data.  Responses reflecting participants’ attitudes on the last three attitude items were 

coded from one to three with higher scores reflecting attitudes that were more positive.  All 

attitude items were summed to create a total attitude score.  Possible scores ranged from 16 to 

74.   

Two paired samples t-tests were computed to determine if significant differences existed 

between pre-post knowledge and pre-post attitude scores.   

Results 

 For most knowledge items, participants more often answered incorrectly than correctly 

for both pre- and post-tests.  However, more participants did answer four of the five true/false 

questions correctly than incorrectly.  See Table 1.  A paired samples t-test revealed no statistically 

significant difference between pre-knowledge (M = 8.62, SD = 3.40) and post-knowledge (M = 

8.50, SD = 4.49) assessment scores, t(41) = 0.20, p = 0.85.    



For all attitude items on both the pre and post-tests except for one, participant attitudes 

were more positive than negative.  The one item that is the exception is, “People who exercise 

are cool.” with a post-test mean score of 2.96 (SD = 1.58).  See Tables 2 and 3. A paired samples 

t-test revealed no statistically significant difference between pre-attitude (M = 63.63, SD = 4.86) 

and post-attitude (M = 63.83, SD = 6.73) assessment scores, t(23) = -0.16, p = .87. The lower 

number of matched sets in the pre-post attitude scores as compared to the knowledge scores is 

due to response items of “I’m not sure what this question means.” being treated as missing data, 

which inhibited a total attitude scored from being computed. 

Discussion 

Science and health education have had some success in using technology and digital 

educational games for learning. A digital educational game focused on science and drug 

prevention knowledge was delivered on laptop computers to at-risk elementary students in a 

school district’s afterschool program by members of a drug prevention coalition. After hour-long 

sessions for one day every week for six weeks, the game neither significantly changed 

participants’ knowledge of science and drug prevention nor attitudes toward science and drug 

prevention. 

The use of laptop computers in schools to deliver instructional content has become a 

popular teaching strategy (Rideout 2013), and science and drug prevention content was delivered 



to participants in this current study using laptop computers. Although anecdotally, participants 

were observed by the researchers as enthusiastic about ‘playing the game’ on the laptops, the 

data indicated no significant changes. The effect of laptops on learning has been noted as 

positive for science but undetermined overall (Haßler, Major, and Hennessy 2015; Zheng et al. 

2016). Laptops were used in the district’s elementary classrooms but have never been used in the 

afterschool program. Although the use of digital games has been viewed as an effective teaching 

technique (Backlund and Hendrix 2013), participants in the present study may have been initially 

enthusiastic about a novel teaching technique in this setting, however, after six weeks; the 

novelty may have worn off.   

Many elementary students are familiar with playing educational games on devices 

(Rideout 2013). The present study, therefore, used a digital educational game to attempt to 

change participant science and drug prevention knowledge and attitudes. The use of digital 

educational games has demonstrated some positive (Backlund and Hendrix 2013; Clark, Tanner-

Smith, and Killingsworth 2016; Wouters et al. 2013) but also limited (Abdul Jabbar and Felicia 

2015) effects on academic achievement. In regard to science knowledge and attitudes, results of 

the present study are inconsistent with those of other studies where the use of technology and 

educational software demonstrated improvements in science knowledge and attitudes of at-risk 

elementary students (Gillard 2010; Zheng et al. 2014). In regard to drug prevention knowledge 



and attitudes, results of the present study are also inconsistent with those of other studies that 

demonstrated some improvements in health knowledge and attitudes (DeSmet et al. 2014; Sung, 

Hwang, and Yen 2015). 

 One possible reason for the unexpected knowledge findings is the setting in which the 

education took place may have not been the best possible learning environment. Participants 

used the laptops at cafeteria tables in a lobby as others completed their accompanying program 

worksheets at a group of adjacent cafeteria tables. Such an informal setting may have made 

participants feel that ‘learning’ science or drug prevention in the cafeteria was not as important as 

learning the subjects in the classroom. The true-false knowledge test items dealt specifically with 

the drug prevention content of the game. Although drug prevention knowledge did not change, 

more participants answered most of these true-false items correctly. With just two possible 

choices, participants may have had an easier time obtaining the correct answer.  They may have 

also had an easier time in understanding these questions than the more difficult multiple choice 

items that included pictures of different sections of the brain to identify.  The present study, 

however, was conducted in an afterschool setting in a community with high levels of substance 

abuse and poverty that limited its generalizability to other populations. Measurement of a total 

attitude score was also limited due to treating “I don’t know”-type responses as missing data. In 



addition, with no control group, any change in pre-post-scores could be attributed to learning 

from the test. 

 Scores on science and drug prevention attitude items were more positive than negative. 

Although there was no significant change, participants’ mostly positive drug prevention attitudes 

should be encouraging to the drug prevention coalition. Their level of drug prevention 

knowledge and attitudes may offer them some protection against health risks in their 

environment, at least for the present. 

 Unfortunately, though, as a student progresses through the grade levels, their drug 

prevention attitudes change to more pro-use (Freeman, Brucks, and Wallendorf 2005; Andrews et 

al. 2003). It is important to provide quality interventions at early ages to address this trend. 

Quality digital educational games should be interactive, realistic, and challenging; even 

including paper-pencil supplements (Abdul Jabbar and Felicia 2015; Ravyse et al. 2016). The 

intervention used in the present study did follow the guidelines for effective knowledge and 

attitude change with interactivity, feedback, and support provided.  The main science and drug 

prevention content and application, however, should come from the classroom curriculum and be 

supplemented in other programs such as afterschool or extra-curricular programs. When used to 

supplement or coordinated with classroom instructional methods, technology applications are 

more effective (Wouters et al. 2013; Slavin et al. 2014). It is recommended that digital 



educational games such as the one in the present study be integrated into the formal classroom 

setting as an educational supplement as well as used in the less formal afterschool and extra-

curricular settings to reinforce that learning. Future programming and research efforts for the 

drug prevention coalition could examine the impact of this digital educational game in the 

classroom as stand-alone, and/or integrated with classroom instruction, and/or reinforced in the 

afterschool setting to determine the best way to integrate it with science and health class lessons. 



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Table 1 

Pre and Post Correct and Incorrect Response Frequencies to Knowledge Items 

Variable
Pre 
Test  
n(%)

Post 
Test 
n(%)

You have found a new plant growing outside and you don't 
know what kind of plant it is. Which one of your senses can 
you safely use to find out what kind of plant it is?  
     Correct 
     Incorrect 
     Total 

Which step is “Make a guess or prediction” in scientific 
inquiry? 
          Correct 
          Incorrect 
          Total 

Which step is “Look it over -- use whatever senses you can 
safely use to find out about it” in scientific inquiry? 
          Correct 
          Incorrect 
          Total 

Which step is “Decide what you have learned” in scientific 
inquiry? 
           Correct  
           Incorrect 
           Total   

Which step is “Test or experiment” in scientific inquiry? 
         Correct 
         Incorrect 
         Total 

39(53.4) 
34(46.6) 
73(100) 

14(19.4) 
58(80.6) 
72(100) 

23(31.5) 
50(68.5) 
73(100) 

25(35.7) 
45(64.3) 
70(100) 

25(35.2) 
46(64.8) 
71(100)

41(71.9) 
16(28.1) 
57(100) 

10(17.9) 
46(82.1) 
56(100) 

12(21.8) 
43(78.2) 
55(100) 

20(37.0) 
34(63.0) 
54(100) 

16(29.6) 
38(73.4) 
54(100)



Here is a picture of the brain. What does this part of the brain 
help you do? 
     Correct 
     Incorrect 
     Total 

Here is another picture of the brain. What does this part of the 
brain help you do? 
     Correct 
     Incorrect 
     Total 

Here is another picture of the brain. What does this part of the 
brain help you do?           
     Correct          
     Incorrect          
     Total 

Here is a picture of the brain. What does this part of the brain 
help you do? 
     Correct 
     Incorrect 
     Total 

Here is a picture of the brain. What does this part of the brain 
help you do? 
     Correct 
     Incorrect 
     Total 

Your friend has a new cat. You decide to pet it. When you pet 
it, you feel how soft the cat's fur is. How do you know what 
the cat's fur feels like? 
     Correct 
     Incorrect 
     Total 

The messages that travel between your brain and your body 
are partly: 
     Correct 
     Incorrect 
     Total 

Smoking cigarettes over time can: 

1(1.4) 
72(98.6) 
73(100) 

15(20.8) 
57(79.2) 
72(100) 

17(23.6) 
55(76.4) 
72(100) 

9(12.5) 
63(87.5) 
72(100) 

6(8.2) 
67(91.8) 
73(100) 

36(49.3) 
37(50.7) 
73(100) 

9(12.3) 
64(87.7) 
73(100) 

5(8.8) 
52(91.2) 
57(100) 

8(14.0) 
49(86.0) 
57(100) 

11(19.3) 
46(80.7) 
57(100) 

9(15.8) 
48(84.2) 
57(100) 

8(14.0) 
49(86.0) 
57(100) 

32(56.1) 
25(43.9) 
57(100) 

11(19.3) 
46(80.7) 
57(100) 



Table 2  

Frequencies and Measures of Central Tendency for Attitude Items 1-13  

True or False: Alcohol doesn’t do anything to your brain 
         Correct 
         Incorrect 
         Total

52(74.3) 
18(25.7) 
70(100)

37(69.8) 
15(28.3) 
53(100)

Item n NO! 
n (%)

no 
n (%)

Sort of 
n (%)

yes 
n (%)

YES! 
n (%)

Mean Std 
Dev

I think that science 
can help me solve 
problems. 
     Pre  
     Post 

64 
50

5(7.2) 
8(16.0)

2(2.9) 
2(4.0) 

6(8.7) 
14(28.0)

21(30.4) 
6(12.0)

35(50.7) 
20(40.0)

3.56 
3.56

1.26 
1.46

I think doing science 
is fun. 
     Pre  
     Post 

67 
52

10(14.9) 
8(15.4)

2(3.0) 
2(3.8)

16(23.9) 
14(26.9)

18(26.9) 
10(19.2)

21(31.3) 
18(34.6)

3.57 
3.54

1.36 
1.41

I think that learning 
about science is 
important.  
     Pre  
     Post 

64 
52

3(4.7) 
5(9.6)

0(0.0) 
1(1.9)

11(17.2) 
5(9.6)

11(17.2) 
9(17.3)

39(60.9) 
32(61.5)

4.30 
4.19

1.06 
1.28 



Doing science upsets 
me.* 
     Pre  
     Post 

67 
49

39(58.2) 
29(59.2)

17(25.4) 
8(16.3)

7(7.4) 
7(14.3)

1(1.5) 
2(4.1)

3(4.5) 
3(6.1)

4.31 
4.18

1.03 
1.20

Science can help me 
learn about my body. 
     Pre 
     Post 69 

50
5(7.2) 
6(12.0)

2(2.9) 
1(2.0)

6(8.7) 
6(12.0)

21(30.4) 
7(14.0)

35(50.7) 
30(60.0)

4.14 
4.00

1.17 
1.38



I think science is 
hard to do.*  
     Pre 
     Post 

I think that scientists 
do important work. 
     Pre 
     Post 

People who exercise 
are cool. 
     Pre  
     Post 

I think exercise is 
fun. 
     Pre  
     Post 

Smoking cigarettes 
can be helpful to 
your body.* 
     Pre 
     Post 

Smoking cigarettes is 
good for your 
health.*  
      Pre  
      Post 

Drinking alcohol can 
be harmful to your 
body. 
      Pre  
      Post

68 
51 

67 
51 

63 
48 

69 
50 

67 
51 

69 
50 

69 
49

18(26.5) 
21(41.2) 

1(1.5) 
8(15.7) 

8(12.7) 
16(33.3) 

8(11.6) 
7(14.0) 

61(91.0) 
44(86.3) 

62(89.9) 
46(92.0) 

4(5.8) 
6(12.2)

12(17.6) 
6(11.8) 

1(1.5) 
1(2.0) 

7(11.1) 
1(2.1) 

2(2.9) 
1(2.0) 

4(6.0) 
1(2.0) 

4(5.8) 
1(2.0) 

1(1.4) 
0(0.0) 

30(44.1) 
14(27.5) 

3(4.5) 
5(9.8) 

25(39.7) 
11(22.9) 

18(26.1) 
12(24.0) 

1(1.5) 
0(0.0) 

1(1.4) 
0(0.0) 

9(13.0) 
1(2.0) 

4(5.9) 
4(7.8) 

12(17.9) 
1(2.0) 

11(17.5) 
9(18.8) 

14(20.3) 
8(16.0) 

1(1.5) 
0(0.0) 

0(0.0) 
0(0.0) 

9(13.0) 
3(6.1)

4(5.9) 
6(11.8) 

50(74.6) 
36(70.6) 

12(19.0) 
11(22.9) 

27(39.1) 
22(44.0) 

0(0.0) 
6(11.8) 

2(2.9) 
3(6.0) 

46(66.7) 
39(79.6)

3.53 
3.63 

4.63 
4.10 

3.19 
2.96 

3.72 
3.74 

4.87 
4.51 

4.80 
4.74 

4.33 
4.41

1.23 
1.40 

0.78 
1.53 

1.24 
1.58 

1.33 
1.41 

0.49 
1.30 

0.74 
0.86 

1.13 
1.34



*Denotes items that were reverse coded. 

Table 3  
Frequencies and Measures of Central Tendency for Attitude Items 14-16 

Drinking alcohol can 
be harmful to your 
brain. 
      Pre 
      Post

65 
67

2(3.1) 
6(12.8)

0(0.0) 
0(0.0)

8(12.3) 
4(8.5)

10(15.4) 
2(4.3)

45(69.2) 
35(74.5)

4.48 
4.28

0.34 
1.39

Note: 5 = YES!; 4 = yes; 3 = Sort of; 2 = no; 1 = NO!

Item n Not at all 
worried 
n (%)

Little 
worried 
n (%)

Very 
worried 
n (%)

Mean Std 
Dev

If someone I knew 
exercised every day, I 
would feel:*  
     Pre 
     Post 

63 
42

43(68.3) 
28(66.7)

16(25.4) 
12(28.6)

4(6.3) 
2(4.8)

2.62 
2.62

0.61 
0.58

If someone I knew was 
smoking cigarettes, I 
would feel: 
     Pre 
     Post 

66 
42

4(6.1) 
1(2.4)

10(15.2) 
8(19.0) 

52(78.8)    
33(78.6)     

2.73 
2.76

0.57 
0.48



*Denotes items that were reverse coded 

If someone I knew drank 
a lot of alcohol each day, 
I would feel: 
     Pre 
     Post 

66 
40

3(4.5) 
3(7.5)

5(7.6) 
3(7.5)

58(87.9) 
34(85.0)    

2.83 
2.28

0.48 
0.58

Note: 1 = Not at all worried; 2 = Little worried; 3 = Very worried 



Educational Gaming and Afterschool Students’ Science and Drug Prevention 
Knowledge and Attitudes Project Reflective Analysis 

Haley Bylina 
Truman State University  

Community-based participatory research (CBPR) is an all-encompassing approach to 
address inequities among vulnerable populations by involving community members in the 
research process (Holkup 2009). Researchers work with and for our communities! We as 
researchers target needs assessed by local organizations and combine resources at all levels to 
achieve desired changes within a community regarding substance abuse, domestic violence, 
family negligence, food insecurity, and more. The methodology of CPBR is dependent on the 
audience but is based on inter-professionalism and community commitment (CDC).  A key 
feature of CPBR is the focus on creating long-standing partnerships with community resources 
such as businesses, agencies, or local drug abuse prevention coalitions like the one in our 
evaluation report. Our research team has been working with our local drug prevention coalition 
for many years. Our drug prevention coalition’s partnership and participation with us using 
CBPR symbolizes their interest in working together over time to decrease substance abuse in an 
evidence-based fashion. Data obtained through our partnership in collecting information and 
analyzing it using statistics allows us as researchers to evaluate the progress and efficiency of the 
coalition’s approach. 

Our community partner, the Heartland Task Force (HTF), is a coalition formed to combat 
the abuse of alcohol, tobacco, and other substances in a rural, Northeast Missouri county that 
reports a median household income of about $37,967 (Data USA 2015). Drugs pose the most 
predominant threat to families living in the county and have serious implications regarding 
family structure and child endangerment. In order to address these issues of household support, 
HTF implements CBPR and recruits local community members to join the Task Force to conduct 
interventions and events that promote healthy social change. For example, the Mother-Son 
Stampede, an annual event hosted in September attended by over 500 families, is a day full of 
various activities that promote mother-son bonding among area families. The event is accessible 
to the entire community and inclusive of all ages by including activities sponsored by local 
businesses and organizations in the form of crafts, sports, or food. With the purpose of promoting 
health education, each adult guardian is given a free tote with informational pamphlets regarding 
youth health. Additionally, strengthening that community tie, all profits made from the event 
support local high schools, scholarships, and more. Another example of an impactful HTF event 
is the Daddy Daughter Dance that promotes the same family bonding intended by the Mother 
Son Stampede. Hosted annually in April, the dance features crafts, free refreshments, cookies, 
balloons, a photo booth, and a DJ. The event hosted over 800 participants. The HTF also 
implements weekly educational programming in the form of after-school lessons to youth 
regarding bullying and substance abuse prevention. 

As we as researchers process and reflect on what we learned, we view CBPR as an 
attractive form of research due to its sustainability (Policylink 2012) and how it allows all parties 



of the partnership to see direct results. This aids in a better understanding of the target population 
and promotes long-lasting relationships that continue beyond the research process (Detroit URC 
Board 2011). With CBPR, we feel a real sense of belonging to our community and are proud of 
doing our part in making  improvements to the community and to address those vulnerable 
populations in need. With the researcher being a part of the community, they are able to adapt to 
the culture and environmental obstacles. We as researchers, therefore, are now coalition members 
and partners, we identify as townspeople in our local community, and we will continue to work 
with and for this and other community organizations.  

By participating in this study and future CBPR studies, we will not only be improving the 
health of our community but we will also be developing skills that will later translate into career 
assets. The work we do by engaging with the community members and striving to improve the 
lives of the families truly embodies the mission of public health for us as Health Education 
majors. The work done with and for the HTF allows us to really put into practice the 
expectations of a public health educator. By gaining this experience, we are better equipped for 
any potential future careers we may pursue in the public health sector.  

Reflecting on the perceptions of the other side of the partnership, we hope the coalition 
members are able to see the researchers as people who genuinely care about them and the 
community that we share. The community, hopefully, sees how it is benefiting from the 
implementation of the community programs and research results and will offer more support to 
ensure that the work continues. The support is vital for the success of community maintenance 
because it is not enough for us to care about the work being done to better the community - the 
community members themselves have to care in order to truly make it successful. Especially in 
this instance where we are working together for youth substance abuse prevention, we hope the 
younger generation sees our partnership and research efforts as enriching and helpful. Now that 
the study has been completed, there is sense of accomplishment as well as hope. The hope of the 
HTF is that through the success (or even lack of success as noted in this report) of their programs 
and events, the community will continue to be receptive to any new health-promoting endeavors 
of the HTF.  

References  

Adair County, MO. (n.d.). Retrieved May 21, 2018, from https://datausa.io/profile/geo/adair-
county-mo/ 

Community-Based Participatory Research Principles. (2011, January 20). Retrieved May 21, 
2018, from http://www.detroiturc.org/about-cbpr/cbpr-principles.html 

Faridi, Z., Grunbaum, J., Sajor Gray, B., Franks, A., & Simoes, E. (2007, July). Preventing 
Chronic Disease: July 2007: 06_0182. Retrieved May 21, 2018, from https://
www.cdc.gov/pcd/issues/2007/jul/06_0182.htm 

Holkup, P. A., Tripp-Reimer, T., Salois, E. M., & Weinert, C. (2004). Community-based 
Participatory Research An Approach to Intervention Research With a Native American 



Community. Retrieved May 21, 2018, from https://www.ncbi.nlm.nih.gov/pmc/articles/
PMC2774214/ 

Johnson Kirksville Daily Express, & Maria Johnson Kirksville Daily Express. (2017, 
September 29). Mother-Son Stampede brings old-fashioned fun. Retrieved May 21, 2018, 
from http://www.kirksvilledailyexpress.com/news/20170929/mother-son-stampede-brings-
old-fashioned-fun 

Minkler, M., Garcia, A. P., Rubin, V., & Wallerstein, N. (n.d.). Community-Based 
Participatory Research: A Strategy for Building Healthy Communities and Promoting 
Health through Policy Change. Retrieved May 21, 2018, from http://www.policylink.org/
sites/default/files/CBPR.pdf 


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