JMIR FORMATIVE RESEARCHChampion et al

Original Paper

A Web-Based Intervention to Prevent Multiple Chronic Disease
Risk Factors Among Adolescents: Co-Design and User Testingof the Health4Life School-Based Program
Katrina Elizabeth Champion1,2*, BAPsych (Hons), BHealth, PhD; Lauren Anne Gardner1, BPsych (Hons), PhD;
Cyanna McGowan2, MPH; Cath Chapman1, BA (Hons), PhD; Louise Thornton1, BPsych (Hons), PhD; Belinda
Parmenter3, PhD; Nyanda McBride4, PhD; David R Lubans5, PhD; Karrah McCann1, BPsych (Hons), MCrim; Bonnie
Spring2, PhD; Maree Teesson1, BPsych (Hons), PhD; The Health4Life Team6*; Nicola Clare Newton1, BPsych (Hons),
PhD
1

The Matilda Centre for Research in Mental Health and Substance Use, The University of Sydney, Sydney, Australia

2

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States

3

Department of Exercise Physiology, School of Medical Sciences, Faculty of Medicine, UNSW Sydney, Sydney, Australia

4

National Drug Research Institute, Faculty of Health Sciences, Curtin University, Perth, Australia

5

Priority Research Centre for Physical Activity and Nutrition, Faculty of Education and Arts, University of Newcastle, Callaghan, Australia

6

See Authors' Contributions section*

these authors contributed equally

Corresponding Author:
Katrina Elizabeth Champion, BAPsych (Hons), BHealth, PhD
The Matilda Centre for Research in Mental Health and Substance Use
The University of Sydney
The Matilda Centre, Level 6, Jane Foss Russell Building (G02)
University of Sydney, NSW
Sydney, 2006
Australia
Phone: 61 286279006
Email: katrina.champion@sydney.edu.au

Abstract
Background: Chronic diseases are the leading cause of death worldwide. Addressing key lifestyle risk factors during adolescenceis critical for improving physical and mental health outcomes and reducing chronic disease risk. Schools are ideal intervention
settings, and electronic health (eHealth) interventions afford several advantages, including increased student engagement,
scalability, and sustainability. Although lifestyle risk behaviors tend to co-occur, few school-based eHealth interventions havetargeted multiple behaviors concurrently.
Objective: This study aims to summarize the co-design and user testing of the Health4Life school-based program, a web-based
cartoon intervention developed to concurrently prevent 6 key lifestyle risk factors for chronic disease among secondary school
students: alcohol use, smoking, poor diet, physical inactivity, sedentary recreational screen time, and poor sleep (the Big 6).
Methods: The development of the Health4Life program was conducted over 18 months in collaboration with students, teachers,
and researchers with expertise relevant to the Big 6. The iterative process involved (1) scoping of evidence and systematic literature
review; (2) consultation with adolescents (N=815) via a cross-sectional web-based survey to identify knowledge gaps, attitudes,
barriers, and facilitators in relation to the Big 6; (3) content and web development; and (4) user testing of the web-based programwith students (n=41) and teachers (n=8) to evaluate its acceptability, relevance, and appeal to the target audience.
Results: The co-design process resulted in a six-module, evidence-informed program that uses interactive cartoon storylines
and web-based delivery to engage students. Student and teacher feedback collected during user testing was positive in terms ofacceptability and relevance. Commonly identified areas for improvement concerned the length of modules, age appropriatenessof language and alcohol storyline, the need for character backstories and links to syllabus information, and feasibility of
implementation. Modifications were made to address these issues.

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Conclusions: The Health4Life school-based program is the first universal, web-based program to concurrently address 6
important chronic disease risk factors among secondary school students. By adopting a multiple health behavior change approach,it has the potential to efficiently modify the Big 6 risk factors within one program and to equip young people with the skills andknowledge needed to achieve and maintain good physical and mental health throughout adolescence and into adulthood.
(JMIR Form Res 2020;4(7):e19485) doi: 10.2196/19485
KEYWORDS
primary prevention; schools; eHealth; chronic disease; mobile phone; health promotion

Introduction
Background
Chronic diseases such as cardiovascular disease, type 2 diabetes,and mental disorders are the leading causes of death globally[1]. It is well established that major chronic diseases share 4
common lifestyle risk factors: poor diet, physical inactivity,
smoking, and alcohol use [1,2]. Emerging evidence has also
linked these established chronic disease risk factors with 2
additional risk behaviors: sedentary behavior (ie, sitting andrecreational screen time) [3,4] and poor sleep (ie, long or shortduration and/or poor quality) [5]. Together, these 6 risk factors(the Big 6) are important targets for prevention and earlyintervention programs to reduce chronic disease.
A life course approach to prevention includes intervening early
to reduce risk factors before the onset of chronic disease [6].
Early adolescence is a critical period to intervene, as it coincides
with the emergence of many health risk factors and is a time
when young people acquire greater autonomy over their lifestylechoices [7]. To date, most prevention approaches have focusedon changing single behaviors, despite risk factors commonly
co-occurring [8]. For example, watching television is associatedwith high-fat snacking [9], and young people who engage inrisky alcohol and other drug use are also more likely to eat
poorly and be sedentary [7]. In recognition of this clustering,
multiple health behavior change interventions [10] have beendeveloped to address risk factors together, rather than inisolation. These interventions are underpinned by the transfer
theory [11], whereby skills and knowledge learned about one
behavior are thought to transfer to other contexts [12], resulting
in improvements across multiple behaviors without additional
intervention [13]. For example, an intervention targeting
physical activity was also shown to improve eating habits [14].
Schools are ideal locations to deliver healthy lifestyleinterventions, as they provide an opportunity to engage large
numbers of students during this critical time period, and inAustralia, schools are mandated to teach health education.
Furthermore, outside of the family environment, the school is
the primary setting within which the development of children
and young people can be directed and shaped [15]. As teachingtime is often limited, multiple health behavior changeinterventions that can simultaneously address multiple risk
factors are particularly advantageous. However, evidence-based
prevention programs are typically poorly implemented, often
because of limited resources, a lack of teacher training andsupport, and program adaptations that undermine efficacy[16,17]. In fact, it has been estimated that only 14% of programs
delivered in schools have the correct content and modes of
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delivery [18], and more recently, that teachers adapt between
50% and 68% of content in prevention interventions [17,19].
This may help to explain why interventions targeting healthbehaviors, such as physical activity, among adolescents havebeen largely unsuccessful [20]. Web-based interventions havethe potential to overcome implementation barriers encounteredby face-to-face interventions and offer several advantages,
including increased student engagement, scalability, andprogram fidelity [21]. For example, core content ispreprogrammed on the web, and completion is self-directed by
students; therefore, delivery is not dependent on teacher trainingor skills, which promotes faithful delivery of key program
components [22,23]. Research indicates that web-based
interventions can be an effective means of preventing andreducing substance use among adolescents [21,24], andcomputer-based education has been shown to be superior to a
generic classroom curriculum in increasing physical activity
and improving diet [25]. Furthermore, schools are increasingly
looking for digital web-based platforms to deliver key
curriculum content as an alternative or adjunct to face-to-faceteaching. However, there are no existing web-based
interventions that adopt a multiple health behavior change
approach to address the Big 6 among school students.
The effective Climate Schools prevention programs [26-28] use
interactive, web-based cartoons about a group of teenagers toengage students; summaries and optional class activities toreinforce key content; and principles of social influence theory,
namely, information provision, normative education, andresistance skills training [29], to prevent risky substance use
and associated harms among adolescents [26-28]. Using the
Climate Schools programs as a model, we developed the
Health4Life school-based program to address gaps in the field.
Underpinned by a multiple health behavior change approach[10], Health4Life aims to empower adolescents to reducechronic disease risk and improve current physical and mental
health by providing simultaneous web-based education about
the Big 6 lifestyle risk factors. The intervention consists of 3components: (1) a school-based program delivered to all grade
7 students (aged approximately 12 years) during class time,
regardless of risk (universal prevention); (2) an accompanying
smartphone app, available to all students regardless of risk
(universal prevention); and (3) additional web and app content
delivered outside of school to students who remain at risk ofchronic disease 1 and 2 years after initial intervention delivery(selective prevention).

Objectives
This study aims to describe the co-design and user testing of
the universal in-class school-based component of the
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Health4Life intervention to aid in the development of future
web-based prevention resources.

Methods
Co-Design
The Health4Life school-based program was developed using
an iterative co-design process consisting of 4 key stages (Figure1). A co-design approach was used to engage young people inthe co-creation and refinement of the program. Co-design allows
for a richer understanding of user needs and may be particularly
important in fostering the engagement and satisfaction needed
for web-based interventions to succeed among young people[30]. The Health4Life school-based program was co-designedwith youth and teachers, with development coordinated by aresearch team comprising experts in addiction, physical activity,
exercise physiology, sleep, dietetics, mental health, electronic
health (eHealth) interventions, and behavior change.

Figure 1. Co-design of the Health4Life school-based program.

Stage 1: Scoping of the Literature
Although guided by an overarching multiple health behavior
change approach [10], scoping of the literature was conducted
to identify evidence-based prevention principles and bestpractice for the prevention of each of the Big 6 behaviors.
Specifically, members of the research team with expertise ineach of the 6 health behaviors were consulted to identify key
behavioral theories and seminal school-based prevention papers

and systematic reviews concerning each behavior. In addition,
searches were conducted to identify national guidelines orrecommendations, along with any further school-based
prevention papers or systematic reviews and behavioral theories
that could guide development. The key behavioral theories andevidence-based prevention principles that were identified andembedded in the Health4Life school-based program are outlinedin Table 1.

Table 1. Key behavioral theories and evidence-based prevention principles for each of the Big 6 behaviors.
Big 6 behavior

Key behavioral theories

Evidence-based prevention principles

Alcohol use and smoking•••

Social influence theory
Social learning theory
Social cognitive theory

•
•
•
•
•
•

Normative education
Resistance skills training
Information and knowledge provision
Using peer leaders
Harm minimization
Life skills training, for example, decision making, problem-solving, coping
skills, refusal and assertion skills, self-esteem, and self-control

Physical activity••

Self-determination theory
Social cognitive theory••

Development of competence, relatedness and social connection, and autonomy
Promotion of autonomous motivation (engaging in behavior that is valued,
personally relevant, and enjoyable)
Self-regulatory skill development, for example, goal setting, self-monitoring,and decision making•

Sedentary recreational
screen time••Self-determination theory
Social cognitive theory••

Development of competence, relatedness and social connection, and autonomy
Self-regulatory skill development, for example, goal setting, self-monitoring,and decision making

Sleep

•
•

Two-process model of sleep
Social cognitive theory•••

Teaching biological contributing factors to sleep timing and duration
Maintaining regular sleep patterns and identifying sleep problems
Self-regulatory skill development, for example, goal setting, self-monitoring,and decision making

Diet

•

Social cognitive theory•

Self-regulatory skill development, for example, goal setting, self-monitoring,and decision making

In addition, to better understand the effectiveness ofinterventions targeting multiple risk behaviors, we conducteda systematic review and meta-analysis of eHealth school-based
multiple health behavior change interventions targeting two or
more of the Big 6 risk factors [31]. A total of 22 publications
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assessing 16 interventions were included in the review. Mostof the studies assessed interventions to prevent alcohol use andsmoking or improve diet and physical activity. Few studies
targeted screen or sitting time, and none addressed sleep. Pooled
findings supported the effectiveness of eHealth school-based
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multiple health behavior change interventions for improving
both accelerometer- (standard mean difference [SMD] 0.33;
95% CI 0.05 to 0.61) and self-report–(SMD 0.14; 95% CI 0.05
to 0.23) measured physical activity, screen time (SMD −0.09;
95% CI −0.17 to −0.01), and fruit and vegetable intake (SMD
0.11; 95% CI 0.03 to 0.19). However, the effects were smalland short lived. No effects were seen for alcohol or smoking,fat, or sugar-sweetened beverage or snack consumption.
Interventions varied greatly in their content and delivery. Few
studies described specific behavior change techniques, and noneof the studies referred to an established behavior change
taxonomy [32], making it difficult to tease apart effective
intervention components that could be embedded into future
programs. However, effective programs tended to use
computer-based tailored feedback, whereby students were
provided with individualized, normative, or stage-matchedfeedback based on self-reported responses to computer-based
assessments, suggesting that this may be an importantcomponent to include in future interventions.
Results from the systematic review highlighted the need todevelop multiple health behavior change interventions that
address sleep problems among youth, as none of the included
interventions addressed sleep. This is despite the growing
recognition that physical inactivity, sedentary behavior, andsleep are codependent [33,34] and the fact that many young
people report sleep problems [35]. Generally, ineffective
interventions for alcohol use and smoking were brief, primarily
used the transtheoretical model [36], and did not provide
sufficient opportunities for skill building. It was concluded that
future eHealth multiple health behavior change interventions
targeting alcohol and tobacco use alongside other risk behaviors
should be guided by principles of effective substance use
prevention (eg, normative education and life skills training).
Finally, the findings indicated that eHealth multiple behavior
change interventions were only effective in increasing physicalactivity among students aged 13 years or older, and boys had agreater increase in physical activity than girls. This suggeststhat such interventions might not adequately engage girls or
young teenagers (aged <13 years) and that formative researchis required to better understand the beliefs, attitudes, andmotivations of these groups regarding physical activity.

Stage 2: Web-Based Survey With Adolescents
A web-based self-report survey was conducted to understandyoung people’s knowledge about the Big 6, their current
engagement with health behaviors, their beliefs and attitudes
about health, and barriers and facilitators to achieving good
health.

Participants and Procedure
A total of 7 independent secondary schools in New South Walesand the Australian Capital Territory of Australia were invited
to participate. Of the 7 schools, 3 agreed to participate.
Participating schools were asked to distribute information andconsent forms to the parents or guardians of their grade 7 to 9
students. Passive parental consent and active student consent
were required for youth to be eligible to participate in the study(99% consent rate). Students completed an anonymous
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Champion et al
web-based survey in a supervised classroom setting between
August 2018 and September 2018. Participants who completed
the survey were entered into the draw to win a Fitbit valued at
Aus $450 (US $315), with one prize given per school. Ethics
approval was obtained from the University of New South Wales
Human Research Ethics Committee (HREC; HC180224).

Measures
Demographic data collected included age, sex, self-reported
height and weight, and postcode. Self-reported health status
was measured using a single item, “How would you rate yourown health?,” with responses made on a 5-point Likert scaleranging from “Poor” to “Excellent.”
Physical Activity
To assess moderate-to-vigorous physical activity (MVPA)
students were asked, “Over the past 7 days, how many days did
you do moderate or vigorous intensity physical activity for atleast 60 minutes per day?” [37]. Participants were provided
with a written description of what constitutes MVPA.
Screen Time
Using a modified version of the Adolescent Sedentary Activity
Questionnaire [38], students were asked to recall the amount oftime (hours and minutes) typically spent on recreational screen
time on weekdays and weekend days.
Fruit and Vegetable Consumption
Using validated short items commonly used in health research[39,40], fruit intake was assessed via a single item: “About how
many serves of fruit do you usually have each day?” (“don’t
eat fruit” to “6 serves or more”). A similar item measured
vegetable intake. Participants were provided with information
about what constitutes one serve of fruit or vegetables.
Sleep
Students were asked to report their usual bedtime and waketime on school nights and weekend nights. Sleep duration (inhours) was calculated as the difference between wake time andbedtime. Self-reported estimates of bedtime, wake time, andsleep duration have been shown to be reliable and valid [41].
Alcohol and Tobacco Use
Students were asked to report if they had ever tried alcohol or
tobacco, based on validated items used in previous school-based
trials [28,42].
Attitudes, Knowledge, Barriers, and Facilitators
A series of open-ended questions were asked to understandattitudes toward health, for example, “What does good healthmean to you?” Students were asked 5 multiple-choice questions
to test their knowledge about age-appropriate national
recommendations for the Big 6 risk behaviors. These items werebased on national guidelines for each behavior [34,43-45]. As
there are no official national guidelines for smoking,participants’ knowledge could not be assessed. Open-ended
questions were used to assess key motivational factors, barriers,and facilitators of health, for example, “What gets in the way,or stops you, from being more physically active?”

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Analysis
Data were collated and analyzed using IBM SPSS Statistics 24(IBM Corp). Descriptive analyses were conducted to illustrate
the sample characteristics, prevalence rates of the Big 6, andknowledge. For the collected open-ended data, we selected a
subsample of student responses (20%-25%) and carried out aqualitative analysis on these responses until no new themes
emerged (ie, data saturation was reached). The sample wasstratified by age and year group, and a random subsample wasselected to ensure balanced representation across age and year
groups. Using an inductive approach, one author (LG) coded
responses from the subsample, examined the data for frequentor significant responses, and grouped them according to key
themes or categories.

Findings
Health Behaviors and Knowledge
A total of 815 students (mean age 13.89 years, SD 0.89; 84.3%[687/815] female) from 3 schools (2 coeducational and 1 female
only) completed the survey. The majority of participants

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perceived their health to be “very good” (334/801, 41.7%) or“good” (274/801, 34.2%); however, adherence to nationalguidelines for the Big 6 was mixed. Only 12.9% (101/784) ofparticipants achieved the recommended amount of MVPA, andonly 11.8% (92/779) of participants reported eating enoughvegetables per day. The majority of students (622/779, 79.8%)
reported eating sufficient fruit serves, and approximately halfof the participants (382/779, 49.0%) met guidelines for screen
time on weekdays; however, only 23.0% (179/779) ofparticipants met guidelines on the weekend. A small proportionof students (29/778, 3.7%) had tried tobacco in their lifetime,and 64.0% (498/779) of students had used alcohol in their
lifetime (including a taste or sip). Among students aged 14 years
or older, 70.1% (262/374) met the guidelines of sleeping 8 to
10 hours; however, only 53.0% (222/419) of students aged 12
to 13 years met their guideline of 9 to 11 hours. Knowledge ofthe recommended guidelines was poor for physical activity,
diet, and sleep (Table 2); however, most students (719/786,
91.5%) correctly identified that for adolescents, the safest option
is not to drink alcohol at all, and 98.1% (771/786) of students
agreed that smoking is harmful.

Table 2. Percentage of students who correctly identified national guidelines.
Risk behavior and Australian guidelines for young people

Value, n (%)

Physical activity (n=798)
Accumulate 60 min or more of moderate-to-vigorous physical activity per day

212 (26.6)

Sedentary recreational screen time (n=792)
No more than 2 hours per day

394 (49.7)

Sleep
9-11 hours of uninterrupted sleep per night for those aged 5-13 years (n=405)

77 (19.0)

8-10 hours per night for those aged 14-17 years (n=351)

210 (59.8)

Diet (n=789)
Minimum of 2 serves of fruit per day

279 (35.4)

Minimum of 5 serves of vegetables per day

266 (33.7)

Alcohol use (n=786)
For children and young people aged younger than 18 years, not drinking alcohol is the safest option

Attitudes, Barriers, and Facilitators
The key themes extracted from the open-ended responses areillustrated in Table 3. Many of the student responses alignedwith the key behavioral theories and prevention principles
outlined in stage 1. For example, consistent with
self-determination theory, key facilitators of physical activity

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719 (91.5)

included social connection and intrinsic motivation. In addition,in line with social influence and social learning theories, therole of peers and older influences was prominent when
considering reasons to drink alcohol and smoke cigarettes. Thesefindings further shaped the storylines and guided the corecontent in the Health4Life program (more information isprovided in the Stage 3: Content and Web Development section).

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Table 3. Summary of key themes extracted from the open-ended responses of students.
Theme

ExampleThe meaning of good health
Physical health factors such as being physically fit or “Eating well and just keeping active.” (Male, 14 years)
active and having a good diet
Mental health factors such as having a positive mental “Being active and eating healthy, but also to have a positive and healthy mindset.” (Female,state and feeling well
13 years)
Emotional health factors such as feeling happy“Good health to me means being happy. It also means being healthy by exercising andeating the right foods. But mainly I think it means being happy.” (Female, 13 years)

Physical activity motivators
Outcomes of being active such as the positive emotions “I know that when I do exercise it puts me in a better mood which motivates me because
felt afterward and maintenance of fitness and health who doesn't want to be in a good mood.” (Female, 14 years)
Social factors such as friends, family, and teammates“My friends and family. They help encourage me to take part in sport and also get meoutside of the house for a run.” (Female, 12 years)

Enjoyment and fun derived from physical activity and “What motivates me is my liking and love for sports. I find most sports extremely fun tosportsplay.” (Female, 12 years)
Physical activity barriers
Lack of time because of school, homework, or assign- “My schedule is full with other work [homework, study for exams] and also I havements and other commitments
commitments like family and community work so I don’t always have enough time towork out.” (Male, 14 years)
Laziness or a lack of motivation and feeling tired“Things such as not having enough sleep, not being motivated enough and being too tired
can contribute.” (Female, 13 years)

Reasons for young people smoking
To look or feel cool

“It is seen as the cool thing to do or a way to make you seem older than you are.” (Male,
14 years)Peer pressure or to fit in“Peer pressure from people either older than them or their age.” (Female, 12 years)

Curiosity or just to try it“Some people my age smoke probably because they want to seem like a ‘cool’ kid andalso try to experience what it tastes like.” (Female, 14 years)

No reason as people do not smoke at that age“I don’t think they smoke.” (Female, 12 years)

Reasons for young people drinking alcohol
To look or feel cool“I think people my age drink alcohol because they want to seem cool and mature, as alcohol is an adult thing to do.” (Female, 13 years)

Peer pressure or to fit in“Because of peer pressure, thinks it’s cool and will achieve friends loyalty.” (Male, 13
years)

Curiosity“People my age drink alcohol mostly out of curiosity and because they want to see what
it tastes like.” (Female, 12 years)

No reason as people do not drink alcohol at that age“I don't think people my age drink alcohol.” (Female, 13 years)

Barriers to getting enough sleep
Using technology and devices“...because they are on their technology just before bed, making it hard to get to sleep.”(Female, 13 years)

Other commitments taking their time such as homework or extracurricular activities“I think that people my age do not sleep because they stay awake doing homework or
schoolwork. Assignments, projects.” (Male, 14 years)

Stage 3: Content and Web Development
Background and Content Development
The development of the Health4Life school-based program wasbased on the effective Climate Schools substance use prevention
programs [26-28], which use web-based cartoon storylines abouta group of teenagers to deliver key prevention messages andhttp://formative.jmir.org/2020/7/e19485/

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engage students. Underpinned by a multiple health behavior
change approach [10] and guided by the key behavioral theories
and prevention principles for each of the Big 6 behaviors
identified in stage 1, the findings from the web-based youth
survey conducted in stage 2, and consultation with researcherswith expertise in the Big 6, the core content areas weredeveloped, which formed the basis for the 6-module Health4Life
program (Table 4).

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Table 4. Summary of Health4Life program content.
ModuleKey messages

1

•
•
•
•

Guidelines for eating healthily and benefits of a healthy dietTips for increasing water intake
Sleep needs of adolescents and the benefits of sleeping well
Guidelines for recreational screen time and the benefits of limiting screen use

2

•
•
•
•
•

Prevalence and patterns of alcohol and tobacco use among adolescents
Australian guidelines to reduce health risks from drinking alcohol
Identifying reasons why teenagers choose to, or not to, drink alcohol
Benefits of being physically active
Finding physical activities that you enjoy

3

•
•
•
•

Short- and long-term consequences of alcohol and tobacco use
Consequences of excessive sedentary recreational screen time
Strategies for reducing sedentary recreational screen time
Responsible use of social media

4

•
•
•
•

Social, financial, and legal consequences of alcohol and tobacco use
Assertive communication skills and refusal skills
Australian guidelines for physical activity and sedentary behavior
Tips for setting specific, measurable, achievable, relevant, time-bound (SMART) goals

5

•
•
•
•

Understanding food labels
Limiting sugar-sweetened beverage consumption
Improving sleep hygiene
Avoiding too much sleep on weekends (“social jet lag”)

6

•
•
•
•

Associations and interrelations between health habits
Relationships between the Big 6 and mental health
Physical, social, and emotional benefits of health and well-being
The Big 6 and long-term healthCharacter Development and Script Writing
The first step in designing the cartoon modules was to develop
character profiles. The characters were purposely designed to
be of similar age to the target audience (ie, grade 7 students,
aged approximately 12 years) and to have different strengths
and weaknesses and various health behavior clusters. Basiccharacter profiles were developed with and reviewed by young
people (n=7; aged 12-15 years; 2 males and 5 females) recruited
via personal and professional networks. The youth reviewers
were asked to make suggestions about character names,
appearance, personalities, and health habits and to provide ideas
for age-appropriate scenarios to be embedded into the storylines.
Next, based on these characters and the findings from the
web-based youth survey (stage 2), initial cartoon scripts for the
6 modules were written by members of the research team. The
scripts aimed to provide students with information and skills
about the Big 6 through the context of a teenage drama. The
script writing was an iterative process, undergoing review by
the expert researchers (n=22) and young people (n=9) before
being sent for animation. Youth reviewers were asked tocomment on the language used and relevance of the storylines,
whereas expert reviewers commented on the accuracy of thecontent and prevention messages. Scripts were modified
accordingly and then sent to animators to develop into thecartoon animations.

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Module Summaries and Activities
Consistent with the Climate Schools programs [26-28], teacher
and student summaries and optional class activities weredeveloped, in addition to the cartoon storylines, for each of the
6 modules. Module summaries were developed to reinforce thekey content taught within the cartoons. The summaries were
written by members of the research team, drawing on the latest
available evidence, including national prevalence data, forexample [46,47], national guidelines, for example [48], andrecent scientific literature relating to the Big 6 risk factors, forexample, benefits of engaging in healthy behaviors andconsequences of engaging in risky behaviors. In addition, a setof 4 to 5 activities was developed for each module, including
points for class discussions, worksheets, quizzes, and homeworktasks. Activities were designed to develop key self-management
and interpersonal skills, such as communication, decision
making, and problem-solving, and to meet key outcomes fromthe stage 4 New South Wales Personal Development, Healthand Physical Education syllabus, the Western Australian Year
7 Health and Physical Education syllabus, and the years 7 and
8 Australian Health and Physical Education curriculum (forQueensland). Each module includes one web-based activity,
such as interactive worksheets, games, or quizzes, to provide
an engaging and immersive learning experience. Summaries
and activities for each module were reviewed by members of
the wider Health4Life team, including those with expertise
relevant to the Big 6 behaviors.

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Stage 4: User Testing
User testing was conducted in 2019 with year 7 students andteachers to gain feedback on the acceptability and feasibility of
the Health4Life school-based program before implementation.
Ethical approval was obtained from the University of Sydney
HREC (2018/882).

Student Testing: Participants and Procedure
A selection of secondary schools in Sydney that had previously
expressed interest in participating in research were invited toparticipate in user testing of the Health4Life program, of which
2 agreed to participate. A total of 2 focus groups (45-60 min)were conducted with grade 7 students in 2 independent
secondary schools in Sydney: one all male (n=21; mean age
12.05 years, SD 0.38) and one all female (n=20; mean age 12.10
years, SD 0.31). Consent forms were distributed to parent or
guardians, with passive parental consent and active student
consent required. Facilitated by 2 researchers, the focus groupconsisted of students watching a video presentation of modules
1 and 2 cartoons as a group. Following each cartoon, thefacilitators led a class discussion, prompting students withquestions regarding the likability and relatability of thecharacters, storylines, and language used in the cartoons. The
focus groups were audio recorded and later transcribed. At theend of the discussion, students were also asked to complete a
brief, 10-min questionnaire to provide their written feedback
about the acceptability and relevance of the Health4Life
modules. Students were remunerated a Aus $30 (US $20) gift
voucher for their time spent in the focus group. Students werealso invited to provide feedback on the remaining 4 modules
via a web-based survey for an additional reimbursement of one
Aus $15 gift (US $10) voucher per module.

Teacher Testing: Participants and Procedure
All grade 7 health education teachers at the same 2 participating
schools were invited to participate in the user testing process.

Additional teachers were recruited via social media and personal
and professional networks. A total of 8 teachers from 5 schools
agreed to participate. After providing informed consent, teachers
were invited to view 2 Health4Life modules (including cartoons,module summaries, and activities) and asked to complete a
web-based survey to comment on the acceptability andsuitability of the Health4Life school-based program. The
teachers were reimbursed Aus $50 (US $35) for each module
they reviewed. In addition, health education curriculum experts(n=6) from New South Wales, Western Australia, andQueensland were engaged to provide expert advice on thealignment of the Health4Life content with the national- andstate-based health education curricula.

AnalysisStudent and teacher questionnaire data were analyzed using
IBM SPSS Statistics 24. Descriptive statistics were conductedto calculate the percentage agreement for each survey item. The
focus group data were transcribed by one researcher (EH).
Individual comments and specific recommendations wereextracted to inform refinements and modifications to the
Health4Life program.

Results
User Testing Results
A total of 41 students (mean age 12 years, SD 0.35; 49% [20/41]
female) provided feedback about the Health4Life school-based
program. As the review of modules 3 to 6 occurred outside of
the classroom and was optional, the response rate ranged from39% (16/41) to 100% (41/41) across modules. Overall, students
rated the cartoon modules favorably, providing positive feedback
about the likability and believability of the storylines andcharacters (Table 5). An example of open-ended feedback
provided by students is summarized in Multimedia Appendix
1.

Table 5. Summary of student questionnaire data.

aQuestion

Module 1(n=41), n (%)

Module 2(n=41), n (%)

Module 3(n=31), n (%)

Module 4(n=26), n (%)

Module 5(n=18), n (%)

Module 6(n=16), n (%)

Overall rating (% good/very good)

36 (88)37 (90)30 (97)24 (92)16 (89)14 (88)How much did you like the storylines? (% 35 (85)
liked a little/lot)

38 (93)30 (97)24 (92)18 (100)

13 (81)

How much did you like the characters?
(% liked a little/lot)

29 (71)34 (83)28 (90)24 (92)17 (94)

12 (75)How believable and realistic were thestorylines? (% completely/somewhat)

31 (78)32 (82)26 (87)23 (88)16 (89)13 (81)

Do you think that other year 7 students
will understand the information in thelessons? (% strongly agree/agree)

30 (77)—a22 (73)22 (85)

14 (78)14 (88)Do you think other year 7 students will
like the characters? (% strongly
agree/agree)

28 (72)—20 (67)20 (77)14 (78)11 (69)Do you think that other students will find 32 (82)the cartoons an engaging way to learn? (%strongly agree/agree)—

21 (70)20 (77)

11 (61)10 (63)Students were asked to respond to questions 5-7 about both modules 1 and 2, so separate data for each module were not available.

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A total of 8 teachers (75% male) participated in user testing: 7
taught at coeducational schools and 1 taught at a single-sex
school. On average, participants had been teaching for 11.5 (SD10.09) years. Table 6 summarizes the feedback provided byteachers via the web-based questionnaire. Overall, the teachers
rated the Health4Life program positively, with the percentageof teachers rating the modules as good or very good ranging
from 88% to 100%. The vast majority of teachers also indicatedthat the modules were a good fit with the health education
syllabus and that the storylines were believable, age appropriate,
and understandable to students. However, some teachers hadconcerns about the modules adequately covering content, having
sufficient lesson time, and feasibility of implementation.
Multimedia Appendix 2 provides key themes and examples
extracted from the open-ended teacher feedback.

Table 6. Summary of teacher questionnaire feedback.
Feedback item

Module 1(n=8), n (%)

Module 2(n=8), n (%)

Module 3(n=7), n (%)

Module 4(n=7), n (%)

Module 5(n=7), n (%)

Module 6(n=7), n (%)

Overall rating (% good/very good)

7 (88)

7 (88)

7 (100)7 (100)7 (100)7 (100)

Fit with syllabus (% very well/extremely well)

6 (75)

6 (75)

6 (86)

6 (86)

7 (100)7 (100)Believable and valid storylines (% yes)

7 (88)

8 (100)7 (100)7 (100)6 (86)

7 (100)Age-appropriate content (% yes)

8 (100)7 (88)

7 (100)7 (100)7 (100)7 (100)Concepts understood/remembered by students (% 8 (100)yes)

8 (100)6 (86)

6 (86)

7 (100)7 (100)Lesson length adequately covers content (% yes) 4 (50)

5 (63)

3 (43)

4 (57)

4 (57)

3 (43)

Language acceptable to youth (% yes)

8 (100)7 (88)

7 (100)7 (100)7 (100)7 (100)Concerns about language used (% yes)

1 (13)

1 (13)

1 (14)

1 (14)

0 (0)

0 (0)

Effectiveness of program improving students’
health behaviors (% somewhat effective/very effective)

8 (100)8 (100)7 (100)7 (100)7 (100)7 (100)Likely to have implementation problems (% yes) 5 (63)

5 (63)

4 (57)

4 (57)

1 (14)

1 (14)

Sufficient time to deliver modules (% yes)

6 (75)

6 (75)

4 (57)

4 (57)

4 (57)

4 (57)

Sufficient computers for students (% yes)

7 (88)

7 (88)

6 (86)

6 (86)

5 (71)

5 (71)Key Changes Made to the Health4Life Program After
User TestingOn the basis of feedback obtained from students and teachers,
several modifications were made to the Health4Life program,

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including changes to the language, a reduction in cartoon text
and slides, the addition of a backstory module and links tosyllabus overviews, and the provision of alternate delivery
methods (Table 7).

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Table 7. Examples modifications made to the Health4Life program.
Key issues identified

Modifications

Lesson length

•

•
•
•

•

Text-heavy cartoons
Too many cartoon slides
Concern over fitting the cartoons and activities into
one lesson

Cartoon content

•

•
•
•

•

Age appropriateness of language
Need for a backstory
Relatability of alcohol storyline for year 7 students•

Linking content to the health and physical education curric- •ula•

Implementation feasibility for schools with limited access •to computer rooms or devices

Scripts were revised to make wording more succinct, and cartoon slides were removed
where possible.
It was made clear to teachers that the class activities are optional and that a rangeof activities are provided so that the most suitable and feasible options can be selected.

Language was refined based on student suggestions (eg, changing “okay” to “kk”
in text messages).
An introductory cartoon module was added to provide a backstory for each of themain characters.
The script was adapted to make it clear that, aside from Xavier (year 7), the only
other characters drinking alcohol are older (year 10).
Expert curriculum consultants were engaged to develop or review unit overviews
that map the cartoon content and activities to the relevant syllabus outcomes anddescriptors for each state.
An outline of how the components of the Health4Life program align with the different
stages of learning (knowledge, understanding, skills, and application) and the 5
propositions (taking a strengths-based approach, focusing on educative purposes,
valuing movement, developing health literacy, and including a critical inquiry approach) that shape the health and physical education curricula was provided.
Teachers were provided with alternative delivery options, such as using a smart
board to go through the modules as a class or using hard copies of the cartoons andactivities.

The Final Health4Life School-Based Program
The Health4Life school-based program is underpinned by amultiple health behavior change approach [10]. It is anticipatedthat by providing students with concurrent education about the
Big 6, while also highlighting the associations and interrelations
between health behaviors, the program will efficiently facilitatechange across multiple behaviors. The program uses principles
of social influence [29], social cognitive [49], social learning[50] and self-determination theories [51], and the two-processmodel of sleep [52,53] (Table 1 and Figure 2), with key behavior
change components and mechanisms for change woven into thestoryline and accompanying activities. The Health4Life
school-based program was developed to meet outcomes fromthe stage 4 New South Wales Personal Development, Health

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and Physical Education syllabus, the Western Australian Year
7 Health and Physical Education syllabus, and the years 7 and
8 Australian Health and Physical Education curriculum (forQueensland). Teachers are provided with unit overviews that
map the cartoon content and activities to the state-based syllabus
outcomes and descriptors, along with an outline of how thecomponents of the Health4Life program align with the different
stages of learning (knowledge, understanding, skills, andapplication) and the 5 propositions (taking a strengths-based
approach, focusing on educative purposes, valuing movement,
developing health literacy, and including a critical inquiry
approach) that shape the health and physical education
curriculum. An overview of the program content is provided inTable 4.

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JMIR FORMATIVE RESEARCHChampion et al

Figure 2. Health4Life Conceptual model.

The Health4Life school-based program consists of 6 modules,
ideally delivered once per week, each comprising the following:
1.

2.

3.

A 20-min web-based cartoon completed individually by
students (Figure 3): The cartoons follow the story of a groupof teenagers, of similar ages to grade 7 students, to impart
key prevention messages while engaging students andmaintaining interest. The cartoon modules aim to provide
evidence-based information about the Big 6, improve
resistance skills, modify existing norms, and increaseautonomous motivation. Short web-based quizzes areembedded at the end of each cartoon module to test
knowledge.
Module summaries: teachers and students are provided with
PDF factsheets for each module to provide additional details
and reinforce key messages.
Optional activities: teachers are provided with a selectionof 4 activities (eg, worksheets, group discussions, andhomework tasks) to implement with their students after the
cartoon in remaining lesson time (approximately 20 min).
Teachers can select which and how many activities they

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implement to best suit the needs of their class. A
self-directed interactive web-based activity (eg, web-based
worksheet and game) is also included after each cartoon
module to accommodate students completing the cartoon
component at different speeds.
On the basis of the findings of the systematic review conductedin stage 1, the final component of the Health4Life school-based
program is web-based tailored feedback. Students are provided
color-coded strengths-based feedback about their adherence tonational health guidelines for each of the Big 6 immediately
after completing a self-report web-based assessment, via thestudy website (Figure 4). The feedback aims to help students
identify behaviors to increase, decrease, or maintain. Using a
traffic light system, green notifications are provided to students
who are currently meeting national guidelines (Going Strong),orange notifications are given to students who are not yetmeeting guidelines but are close (Needs some work), and red
notifications are provided to students who are not meeting
guidelines (Action needed).

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JMIR FORMATIVE RESEARCHChampion et al

Figure 3. Example cartoons from the Health4Life modules.

Figure 4. Example web-based tailored feedback.

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JMIR FORMATIVE RESEARCH

Program Implementation
The Health4Life school-based program is a universal
intervention designed to be delivered to all grade 7 students,
regardless of their level of risk for chronic disease. It was
designed for delivery during health education classes
approximately once per week over 6 weeks. All materials areavailable on the web and accessed via student and teacher
portals. Teachers are provided with implementation guidelines
and links to the syllabus; however, no teacher training isrequired.

Discussion
Principal Findings
This study aimed to describe the comprehensive, formative
research and development process of the school-based
component of the Health4Life initiative. The program wasdeveloped in collaboration with students, teachers, and healthprofessionals and is grounded in theory and the best available
scientific evidence and is aligned closely with the latest healtheducation curricula in Australia.

Strengths and Limitations
A key strength of the Health4Life school-based program is that
it is the first eHealth intervention to concurrently address the
Big 6 lifestyle risk factors for chronic disease—physicalinactivity, poor diet, smoking, alcohol use, poor sleep, andsedentary recreational screen time—among school students. By
adopting a multiple health behavior change approach, it has thepotential to efficiently modify the Big 6 within one program
and to equip young people with the skills and knowledge needed
to maintain good physical and mental health throughout
adolescence and into adulthood. Although not the focus of thispaper, the Health4Life school-based program is supplemented
by a universal smartphone app that prompts students to monitor
their behaviors, track their progress, and set goals. In addition,a selective intervention based on cognitive behavioral andmotivational enhancement principles provides youth who remainChampion et alat risk of chronic disease when they are in grades 8 and 9, withadditional web and app content to assist them in developing
coping strategies and skills to facilitate healthy behavior change.
Detailed information about these additional components has
been published elsewhere [54]. Together, these 3 components
span both universal and selective prevention, maximizing
outcomes for students throughout their secondary school years.
Finally, as the Health4Life program is delivered to students via
web-based technology with interactive components and noteacher training is required for implementation, student
engagement and program fidelity is likely to be increased [21](assessment of these outcomes is reported on elsewhere [54]).
Importantly, web-based interventions also typically lead to
improved scalability and sustainability, which enhances thedissemination potential and reach of the Health4Life program.
A notable limitation of the co-design process is that students
and teachers were only recruited from independent schools in
Sydney for user testing and, although the web-based survey
sample in stage 2 spanned across 2 states, participants werepredominantly female. Nonetheless, this study was successful
in engaging end users at various stages of the development
process, and the final program was rated favorably and deemed
acceptable and relevant by young people.

Future Directions
The next important step is to evaluate the effectiveness of the
Health4Life intervention. A large cluster randomized controlled
trial is currently underway in 71 Australian schools (>6600
students) to evaluate whether Health4Life is more effective thanhealth education as usual in delaying the uptake of alcohol andtobacco use, reducing sedentary recreational screen time,
reducing the decline in MVPA, reducing consumption ofsugar-sweetened beverages, and improving sleep [54].

Conclusions
Ultimately, this study has the potential to make a substantial
public health impact by concurrently addressing 6 key risk
factors, thereby reducing the incidence of chronic disease andminimizing the associated costs, disability, and early mortality.

Acknowledgments
The authors acknowledge Professor Michael Gradisar, the Association of Independent Schools of New South Wales, and Dominque
Sidaros for providing expert advice and feedback throughout the development process. The authors would also like to thank
Evelyn Heap and Courtney Maher for their assistance with data collection and the many students and teachers who participatedin the development and testing process. Finally, the authors acknowledge Warren Salley and John Horvarth at Big Q productions
for producing the cartoon animations and Netfront Pty Ltd for programming and web development. This study was funded by
the Paul Ramsay Foundation and the Australian National Health and Medical Research Council via Fellowships (KC, APP1120641;
MT, APP1078407; and NN, APP1166377) and via the Centre of Research Excellence in the Prevention and Early Intervention
in Mental Illness and Substance Use (APP11349009). The funders had no role in the study design, data collection and analysis,
decision to publish, or preparation of the manuscript.

Authors' Contributions
The Health4Life Team includes: Frances Kay-Lambkin, Tim Slade, Katherine Mills, Matthew Sunderland, Steve Allsop, LeanneHides, Emma Barrett, Louise Mewton, Lexine Stapinski, and Louise Birrell.

Conflicts of Interest
None declared.

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JMIR FORMATIVE RESEARCHChampion et alMultimedia Appendix 1
Student open-ended feedback.
[DOCX File , 17 KB-Multimedia Appendix 1]

Multimedia Appendix 2
Teacher open-ended feedback.
[DOCX File , 18 KB-Multimedia Appendix 2]

References
1.
2.
3.

4.
5.

6.

7.
8.
9.

10.
11.

12.

13.

14.

15.

16.

17.

Understanding Health and Illness. Australian Institute of Health and Welfare. 2014. URL: https://www.aihw.gov.au/getmedia/
d2946c3e-9b94-413c-898c-aa5219903b8c/16507.pdf.aspx?inline=true [accessed 2020-04-20]
Ezzati M, Riboli E. Behavioral and dietary risk factors for noncommunicable diseases. N Engl J Med 2013 Sep
5;369(10):954-964. [doi: 10.1056/NEJMra1203528] [Medline: 24004122]
Ding D, Rogers K, van der Ploeg H, Stamatakis E, Bauman AE. Traditional and emerging lifestyle risk behaviors andall-cause mortality in middle-aged and older adults: evidence from a large population-based Australian cohort. PLoS Med
2015 Dec;12(12):e1001917 [FREE Full text] [doi: 10.1371/journal.pmed.1001917] [Medline: 26645683]
Lynch BM, Owen N. Too much sitting and chronic disease risk: steps to move the science forward. Ann Intern Med 2015
Jan 20;162(2):146-147. [doi: 10.7326/M14-2552] [Medline: 25599352]
Cappuccio FP, Cooper D, D'Elia L, Strazzullo P, Miller MA. Sleep duration predicts cardiovascular outcomes: a systematic
review and meta-analysis of prospective studies. Eur Heart J 2011 Jun;32(12):1484-1492. [doi: 10.1093/eurheartj/ehr007][Medline: 21300732]
Wilcox S. Chronic Diseases in Australia: Blueprint For Preventive Action. Victoria University: Melbourne Australia. 2015.
URL: https://www.vu.edu.au/sites/default/files/AHPC/pdfs/Chronic-Diseases-in-Australia-Blueprint-for-preventive-action.
pdf [accessed 2020-04-20]
de la Haye K, D'Amico EJ, Miles JN, Ewing B, Tucker JS. Covariance among multiple health risk behaviors in adolescents.
PLoS One 2014;9(5):e98141 [FREE Full text] [doi: 10.1371/journal.pone.0098141] [Medline: 24858838]
Spring B, Moller AC, Coons MJ. Multiple health behaviours: overview and implications. J Public Health (Oxf) 2012
Mar;34(Suppl 1):i3-10 [FREE Full text] [doi: 10.1093/pubmed/fdr111] [Medline: 22363028]
Marsh S, Ni Mhurchu C, Maddison R. The non-advertising effects of screen-based sedentary activities on acute eating
behaviours in children, adolescents, and young adults. A systematic review. Appetite 2013 Dec;71:259-273. [doi:10.1016/j.appet.2013.08.017] [Medline: 24001394]
Prochaska JJ, Spring B, Nigg CR. Multiple health behavior change research: an introduction and overview. Prev Med 2008
Mar;46(3):181-188 [FREE Full text] [doi: 10.1016/j.ypmed.2008.02.001] [Medline: 18319098]
Lippke S, Nigg CR, Maddock JE. Health-promoting and health-risk behaviors: theory-driven analyses of multiple healthbehavior change in three international samples. Int J Behav Med 2012 Mar;19(1):1-13 [FREE Full text] [doi:10.1007/s12529-010-9135-4] [Medline: 21234735]
Fleig L, Lippke S, Pomp S, Schwarzer R. Intervention effects of exercise self-regulation on physical exercise and eating
fruits and vegetables: a longitudinal study in orthopedic and cardiac rehabilitation. Prev Med 2011 Sep;53(3):182-187.
[doi: 10.1016/j.ypmed.2011.06.019] [Medline: 21784096]
Johnson SS, Paiva AL, Mauriello L, Prochaska JO, Redding C, Velicer WF. Coaction in multiple behavior changeinterventions: consistency across multiple studies on weight management and obesity prevention. Health Psychol 2014
May;33(5):475-480 [FREE Full text] [doi: 10.1037/a0034215] [Medline: 24274806]
Mata J, Silva MN, Vieira PN, Carraça EV, Andrade AM, Coutinho SR, et al. Motivational 'spill-over' during weight control:increased self-determination and exercise intrinsic motivation predict eating self-regulation. Health Psychol 2009
Nov;28(6):709-716. [doi: 10.1037/a0016764] [Medline: 19916639]
National Research Council (US) and Institute of Medicine (US) Committee on the Prevention of Mental Disorders andSubstance Abuse Among Children, Youth, and Young Adults: Research Advances and Promising Interventions. Family,
School, and Community Interventions. In: O'Connell ME, Boat T, Warner KE, editors. Preventing Mental, Emotional, andBehavioral Disorders Among Young People: Progress and Possibilities. Washington, DC: National Academies Press;
2009:157-190.
Dusenbury L, Brannigan R, Hansen WB, Walsh J, Falco M. Quality of implementation: developing measures crucial tounderstanding the diffusion of preventive interventions. Health Educ Res 2005 Jun;20(3):308-313. [doi: 10.1093/her/cyg134][Medline: 15522898]
Miller-Day M, Pettigrew J, Hecht ML, Shin Y, Graham J, Krieger J. How prevention curricula are taught under real-world
conditions: types of and reasons for teacher curriculum adaptations. Health Educ (Lond) 2013;113(4):324-344 [FREE Fulltext] [doi: 10.1108/09654281311329259] [Medline: 26290626]

http://formative.jmir.org/2020/7/e19485/

XSL• FO
RenderX

JMIR Form Res 2020 | vol. 4 | iss. 7 | e19485 | p. 14(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
18.

19.

20.

21.

22.

23.

24.

25.

26.
27.

28.

29.
30.
31.

32.
33.

34.

35.
36.
37.

38.

Ennett ST, Ringwalt CL, Thorne J, Rohrbach LA, Vincus A, Simons-Rudolph A, et al. A comparison of current practicein school-based substance use prevention programs with meta-analysis findings. Prev Sci 2003 Mar;4(1):1-14. [doi:10.1023/a:1021777109369] [Medline: 12611415]
Pettigrew J, Graham JW, Miller-Day M, Hecht ML, Krieger JL, Shin YJ. Adherence and delivery: implementation quality
and program outcomes for the seventh-grade keepin' it REAL program. Prev Sci 2015 Jan;16(1):90-99 [FREE Full text][doi: 10.1007/s11121-014-0459-1] [Medline: 24442403]
Borde R, Smith JJ, Sutherland R, Nathan N, Lubans DR. Methodological considerations and impact of school-based
interventions on objectively measured physical activity in adolescents: a systematic review and meta-analysis. Obes Rev
2017 Apr;18(4):476-490. [doi: 10.1111/obr.12517] [Medline: 28187241]
Champion KE, Newton NC, Barrett EL, Teesson M. A systematic review of school-based alcohol and other drug prevention
programs facilitated by computers or the internet. Drug Alcohol Rev 2013 Mar;32(2):115-123. [doi:10.1111/j.1465-3362.2012.00517.x] [Medline: 23039085]
Backer TE. Finding the Balance: Program Fidelity and Adaptation in Substance Abuse Prevention: A State-of-the-Art
Review. California State University, Northridge (CSUN). 2001. URL: https://www.csun.edu/sites/default/files/
FindingBalance1.pdf [accessed 2020-07-09]
Pankratz MM, Jackson-Newsom J, Giles SM, Ringwalt CL, Bliss K, Bell ML. Implementation fidelity in a teacher-led
alcohol use prevention curriculum. J Drug Educ 2006;36(4):317-333. [doi: 10.2190/H210-2N47-5X5T-21U4] [Medline:
17533804]
Champion KE, Newton NC, Teesson M. Prevention of alcohol and other drug use and related harm in the digital age: what
does the evidence tell us? Curr Opin Psychiatry 2016 Jul;29(4):242-249. [doi: 10.1097/YCO.0000000000000258] [Medline:
27153124]de Bourdeaudhuij I, van Cauwenberghe E, Spittaels H, Oppert J, Rostami C, Brug J, et al. School-based interventions
promoting both physical activity and healthy eating in Europe: a systematic review within the HOPE project. Obes Rev
2011 Mar;12(3):205-216. [doi: 10.1111/j.1467-789X.2009.00711.x] [Medline: 20122137]
Newton NC, Teesson M, Vogl LE, Andrews G. Internet-based prevention for alcohol and cannabis use: final results of theclimate schools course. Addiction 2010 Apr;105(4):749-759. [doi: 10.1111/j.1360-0443.2009.02853.x] [Medline: 20148791]
Newton NC, Vogl LE, Teesson M, Andrews G. CLIMATE schools: alcohol module: cross-validation of a school-based
prevention programme for alcohol misuse. Aust N Z J Psychiatry 2009 Mar;43(3):201-207. [doi:10.1080/00048670802653364] [Medline: 19221908]
Teesson M, Newton NC, Slade T, Carragher N, Barrett EL, Champion KE, et al. Combined universal and selective prevention
for adolescent alcohol use: a cluster randomized controlled trial. Psychol Med 2017 Jul;47(10):1761-1770. [doi:10.1017/S0033291717000198] [Medline: 28222825]
Botvin GJ. Preventing drug abuse in schools: social and competence enhancement approaches targeting individual-level
etiologic factors. Addict Behav 2000;25(6):887-897. [doi: 10.1016/s0306-4603(00)00119-2] [Medline: 11125777]
Thabrew H, Fleming T, Hetrick S, Merry S. Co-design of ehealth interventions with children and young people. Front
Psychiatry 2018;9:481 [FREE Full text] [doi: 10.3389/fpsyt.2018.00481] [Medline: 30405450]
Champion KE, Parmenter B, McGowan C, Spring B, Wafford QE, Gardner LA, et al. Effectiveness of school-based eHealthinterventions to prevent multiple lifestyle risk behaviours among adolescents: a systematic review and meta-analysis. Lancet
Digit Health 2019 Sep;1(5):e206-e221. [doi: 10.1016/s2589-7500(19)30088-3]
Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health Psychol 2008
May;27(3):379-387. [doi: 10.1037/0278-6133.27.3.379] [Medline: 18624603]
Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, SBRN Terminology Consensus Project
Participants. Sedentary behavior research network (SBRN) - terminology consensus project process and outcome. Int J
Behav Nutr Phys Act 2017 Jun 10;14(1):75 [FREE Full text] [doi: 10.1186/s12966-017-0525-8] [Medline: 28599680]
Australian 24-Hour Movement Guidelines For Children and Young People (5 to 17 Years). Australian Government
Department of Health. 2019. URL: https://www1.health.gov.au/internet/main/publishing.nsf/Content/
AC46EFBE3130BC97CA2583D00023E7B0/$File/
Australian%2024-Hour%20Movement%20Guidelines%20for%20Children%20and%20Young%20People%205-17%20years.
pdf [accessed 2020-04-20]
Matricciani L, Olds T, Petkov J. In search of lost sleep: secular trends in the sleep time of school-aged children andadolescents. Sleep Med Rev 2012 Jun;16(3):203-211. [doi: 10.1016/j.smrv.2011.03.005] [Medline: 21612957]
Prochaska JO, DiClemente CC. Stages and processes of self-change of smoking: toward an integrative model of change.
J Consult Clin Psychol 1983 Jun;51(3):390-395. [doi: 10.1037//0022-006x.51.3.390] [Medline: 6863699]
Ridgers ND, Timperio A, Crawford D, Salmon J. Validity of a brief self-report instrument for assessing compliance withphysical activity guidelines amongst adolescents. J Sci Med Sport 2012 Mar;15(2):136-141. [doi:10.1016/j.jsams.2011.09.003] [Medline: 22051688]
Hardy LL, Booth ML, Okely AD. The reliability of the adolescent sedentary activity questionnaire (ASAQ). Prev Med
2007 Jul;45(1):71-74. [doi: 10.1016/j.ypmed.2007.03.014] [Medline: 17532371]

http://formative.jmir.org/2020/7/e19485/

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Champion et al

JMIR Form Res 2020 | vol. 4 | iss. 7 | e19485 | p. 15(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
39.

40.
41.

42.

43.
44.

45.
46.

47.

48.

49.
50.
51.
52.
53.
54.

Champion et al

Nguyen B, Ding D, Mihrshahi S. Fruit and vegetable consumption and psychological distress: cross-sectional and longitudinal
analyses based on a large Australian sample. BMJ Open 2017 Mar 15;7(3):e014201 [FREE Full text] [doi:10.1136/bmjopen-2016-014201] [Medline: 28298322]
Rustihauser I, Webb K, Abraham B, Allsopp R. Evaluation of Short Dietary Questions From the 1995 NNS. Canberra,
Australia: Commonwealth Department of Health and Aged Care; 2001.
Golley RK, Maher CA, Matricciani L, Olds TS. Sleep duration or bedtime? Exploring the association between sleep timing
behaviour, diet and BMI in children and adolescents. Int J Obes (Lond) 2013 Apr;37(4):546-551. [doi: 10.1038/ijo.2012.212][Medline: 23295498]
Teesson M, Newton NC, Slade T, Chapman C, Birrell L, Mewton L, et al. Combined prevention for substance use, depression,and anxiety in adolescence: a cluster-randomised controlled trial of a digital online intervention. Lancet Digit Health 2020
Feb;2(2):e74-e84. [doi: 10.1016/s2589-7500(19)30213-4]
National Health and Medical Research Council. Australian Dietary Guidelines. Canberra, Australia: NHMRC; 2013.
Hirshkowitz M, Whiton K, Albert SM, Alessi C, Bruni O, DonCarlos L, et al. National sleep foundation's sleep time duration
recommendations: methodology and results summary. Sleep Health 2015 Mar;1(1):40-43. [doi: 10.1016/j.sleh.2014.12.010][Medline: 29073412]
National Health and Medical Research Council. Australian Guidelines to Reduce Health Risks From Drinking Alcohol.
Canberra, Australia: Commonwealth of Australia; 2009.
Guerin N, White V. Secondary School Students’ Use of Tobacco, Alcohol and Other Drugs in 2017. Australian Government
Department of Health. 2018. URL: https://www.health.gov.au/resources/publications/secondary-school-students-use-of-tobacco-alcohol-and-other-drugs-in-2017 [accessed 2020-04-20]
Muscular Fitness: It’s Time for a Jump Start. Active Healthy Kids Australia. 2018. URL: https://www.
activehealthykidsaustralia.com.au/siteassets/documents/2018/ahka-report-card-long-form-2018-final-for-web.pdf [accessed2020-04-20]
Australian 24-Hour Movement Guidelines for Children and Young People (5-17 years) – An Integration of Physical Activity,
Sedentary Behaviour and Sleep. Australian Government Department of Health. 2019. URL: https://www1.health.gov.au/internet/main/publishing.nsf/Content/health-24-hours-phys-act-guidelines [accessed 2020-07-09]
Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall;1986.
Kelman HC. Compliance, identification, and internalization three processes of attitude change. J Conflict Resolut 2016
Jul;2(1):51-60. [doi: 10.1177/002200275800200106]
Ryan RM, Deci EL. Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp Educ Psychol
2000 Jan;25(1):54-67. [doi: 10.1006/ceps.1999.1020] [Medline: 10620381]
Borbély AA. A two process model of sleep regulation. Hum Neurobiol 1982;1(3):195-204. [Medline: 7185792]
Daan S, Beersma DG, Borbély AA. Timing of human sleep: recovery process gated by a circadian pacemaker. Am J Physiol
1984 Feb;246(2 Pt 2):R161-R183. [doi: 10.1152/ajpregu.1984.246.2.R161] [Medline: 6696142]
Teesson M, Champion KE, Newton NC, Kay-Lambkin F, Chapman C, Thornton L, Health4Life Team. Study protocol ofthe Health4Life initiative: a cluster randomised controlled trial of an eHealth school-based program targeting multiple
lifestyle risk behaviours among young Australians. BMJ Open 2020 Jul 13;10(7):e035662 [FREE Full text] [doi:10.1136/bmjopen-2019-035662] [Medline: 32665344]

Abbreviations
eHealth: electronic health
HREC: human research ethics committee
MVPA: moderate-to-vigorous physical activity
SMD: standard mean difference

Edited by G Eysenbach; submitted 20.04.20; peer-reviewed by H Thabrew, R Pine; comments to author 12.06.20; revised version
received 22.06.20; accepted 25.06.20; published 28.07.20
Please cite as:Champion KE, Gardner LA, McGowan C, Chapman C, Thornton L, Parmenter B, McBride N, Lubans DR, McCann K, Spring B,
Teesson M, The Health4Life Team, Newton NC
A Web-Based Intervention to Prevent Multiple Chronic Disease Risk Factors Among Adolescents: Co-Design and User Testing of the
Health4Life School-Based Program
JMIR Form Res 2020;4(7):e19485
URL: http://formative.jmir.org/2020/7/e19485/
doi: 10.2196/19485
PMID: 32720898
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JMIR FORMATIVE RESEARCHChampion et al©Katrina Elizabeth Champion, Lauren Anne Gardner, Cyanna McGowan, Cath Chapman, Louise Thornton, Belinda Parmenter,
Nyanda McBride, David R Lubans, Karrah McCann, Bonnie Spring, Maree Teesson, The Health4Life Team, Nicola Clare
Newton. Originally published in JMIR Formative Research (http://formative.jmir.org), 28.07.2020. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR
Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on
http://formative.jmir.org, as well as this copyright and license information must be included.

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