This article has Open Peer Review reports available.
Design of the Dutch Obesity Intervention in Teenagers (NRG-DOiT): systematic development, implementation and evaluation of a school-based intervention aimed at the prevention of excessive weight gain in adolescents
© Singh et al; licensee BioMed Central Ltd. 2006
Received: 07 September 2006
Accepted: 16 December 2006
Published: 16 December 2006
Only limited data are available on the development, implementation, and evaluation processes of weight gain prevention programs in adolescents. To be able to learn from successes and failures of such interventions, integral written and published reports are needed.
Applying the Intervention Mapping (IM) protocol, this paper describes the development, implementation, and evaluation of the Dutch Obesity Intervention in Teenagers (DOiT), a school-based intervention program aimed at the prevention of excessive weight gain.
The intervention focussed on the following health behaviours: (1) reduction of the consumption of sugar-sweetened beverages, (2) reduction of energy intake derived from snacks, (3) decrease of levels of sedentary behaviour, and (4) increase of levels of physical activity (i.e. active transport behaviour and sports participation).
The intervention program consisted of an individual classroom-based component (i.e. an educational program, covering 11 lessons of both biology and physical education classes), and an environmental component (i.e. encouraging and supporting changes at the school canteens, as well as offering additional physical education classes).
We evaluated the effectiveness of the intervention program using a randomised controlled trial design. We assessed the effects of the intervention on body composition (primary outcome measure), as well as on behaviour, behavioural determinants, and aerobic fitness (secondary outcome measures). Furthermore, we conducted a process evaluation.
The development of the DOiT-intervention resulted in a comprehensive school-based weight gain prevention program, tailored to the needs of Dutch adolescents from low socio-economic background.
Overweight and obesity in adolescence are two of the main predictors for obesity throughout the further life course [1–3]. The rising trends in excess weight among children and adolescents represent an emerging threat to public health , as overweight and obesity in adulthood are clearly linked to an increased risk for type 2 diabetes [5, 6], cardiovascular disease [7, 8], and some cancers . The treatment of obesity has shown to be difficult and is often not successful in the longer term . Population-based prevention of overweight and obesity may prove to be more efficient.
Dietary behaviour and physical activity patterns should both be targeted in the prevention of obesity. This may be achieved by inducing changes in personal and environmental mediators of such energy balance-related behaviours . There is, however, little scientific evidence about successful population-based prevention programs in adolescents.
Several reviews on obesity prevention in children and adolescents have been produced during the last years [12–16]. Taken together, these reviews suggest that there is some evidence that prevention of obesity in children and adolescents is feasible. However, many intervention programs lack information on their development, exact content, and implementation , so that effective and ineffective components of these intervention programs cannot be determined. Hence, there is an obvious need for manuscripts that contain a detailed description of the development of the interventions under study, as well as their protocols for implementation and evaluation.
This paper describes the development, implementation, and evaluation design of the Dutch Obesity Intervention in Teenagers (NRG-DOiT), following the structure given by the Intervention Mapping protocol . NRG-DOiT is part of a multi-disciplinary project group (NHF-NRG) that focuses on a better understanding of the obesity epidemic as well as the development of preventive measures .
The IM protocol consists of five steps: (1) the definition of program objectives, based on a thorough analyses of the health problem, (2) the selection of adequate theories and methods to realize behavioural change(s), (3) the design of the intervention program, as well as the selection, testing, and production of the intervention materials, (4) the development of a plan for the implementation, and (5) evaluation. Applying IM can be a complex and time-consuming process, but it ensures that each program objective is based on empirical evidence and theory. It also guarantees that intervention materials and activities are tailored to relevant characteristics of the target population , as well as to the abilities and opportunities or the program implementers and intermediaries.
Please note that the development of our intervention is based on the first edition of 'Intervention Mapping' , in which the 'needs assessment' is not an integral part of IM but precedes the IM process. In this paper, the needs assessment will therefore be described only briefly, the main focus being the description of the actual intervention background, contents, implementation plan, and evaluation design.
The starting point for the needs assessment was the fact that overweight and obesity are becoming the main determinants of preventable diseases in many countries, and the fact that overweight and obesity are often initiated in youth. Furthermore, during adolescence cognitive and behavioural competencies are developed, which are necessary to understand and act upon health and behavioural change instructions [21, 22]. Therefore, health education programs aimed at adolescents may be successful in that they may lead to life-long healthy behavioural patterns, which in turn can positively influence both adolescent and adult health [2, 23–26].
Our needs assessment included a structured analysis of the main risk behaviours related to weight management and becoming overweight in youth, resulting in the formulation of target behaviours on which the DOiT-intervention would be focussed. The methods of the needs assessment included an evaluation of reviews of scientific literature (if available), and relevant national and international reports on obesity and obesity-related topics. Furthermore, focus groups among adolescents were held, as well as interviews with teachers, and experts in the field of physical activity, dietary behaviour, and health promotion. During these focus groups and interviews, the risk behaviours identified in literature were discussed with the relevant key actors for the intervention. All interviews were conducted according to predefined protocols.
This procedure led to the identification of risk behaviours from both sides of the energy balance: energy intake and energy expenditure.
Energy intake: sugar-sweetened beverages and snacks
The increase in the consumption of sugar-sweetened beverages [27, 28] has been suggested to play an important role in excessive weight gain [29–31], and has shown to be associated with energy intake and body weight , and with weight gain and obesity . Until now, only limited data are available on studies aimed at reducing the consumption of sugar-sweetened beverages in children and adolescents, but there is some evidence suggesting that avoiding the consumption of sugar-sweetened beverages can play an important role in obesity prevention .
Recent data show that as much as 30–35% of total energy intake of Dutch adolescents is derived from snacks and sugar-sweetened beverages . Like sugar-sweetened beverages, the increasing frequency of snack consumption is positively correlated with total energy intake . Considering that the problem of underreporting is very frequent in snack foods , the actual energy intake derived from snacks may even be higher than suggested.
Even though evidence of reducing adolescents' intake of high-sugar/high-fat products is limited, it seems obvious that the promotion of healthy dietary patterns should be part of obesity prevention programs .
Energy Expenditure: sedentary behaviour and physical activity
Two important aspects of energy expenditure that contribute to excessive weight gain in adolescents are sedentary behaviour and declining levels of physical activity, both being behavioural and therefore modifiable .
TV viewing has been suggested to be one of the main contributors to the rising prevalence of childhood obesity: it replaces physical activity and it reduces resting metabolism. In addition, energy intake indirectly causes an increase of energy intake via advertising effects  and/or through providing increased opportunities for snacking and grazing behaviour [40–42]. Time spent watching television has shown to be significantly associated with prevalence of overweight in children and adolescents . Children and adolescents spend an increasing amount of time on sedentary behaviours, like TV viewing and computer use. According to recent data, 42% of the Dutch adolescents aged 12–17 years spends 10–19 hours per week watching television, while 34% spends 20 hours or more . Computer use has greatly increased during the last years. In 2002, Dutch adolescents spent seven hours per week on average using the computer (four hours using internet), whereas in 2004 it had increased to ten hours (seven hours using internet) .
Although physical activity is difficult to measure, especially in children, increasingly more data are available on duration and intensity of physical activity in children and adolescents. According to these data, levels of physical activity show a gradual decline with increasing age. This decrease is most marked at ages 13–16 [45, 46].
Results of a recent review on the relationship between physical activity with overweight and obesity suggest that increased levels of physical activity and decreased levels of sedentary behaviour are protective against relative weight and fatness gains during adolescence .
During this step of the IM process, the target group and the setting of the intervention was further specified to be able to tailor the intervention to the specific needs of the target group. In addition, performance objectives were specified, which were based on the program objectives identified during the needs assessment. The performance objectives clarified the exact behavioural 'performance(s)' expected from the target group. These performance objectives refer to changes in individual level behaviours, motivations, and abilities, as well as to environmental opportunities for such behaviours at the organisational and/or community level . Finally, we developed matrices that combined the four identified risk behaviours and their hypothesized determinants. These matrices enabled the translation of the more general performance objectives into very specific intervention goals.
Person and environment
The poor success up to now of many interventions might be attributed to the fact that most of the interventions have aimed exclusively at behavioural change, using a traditional, individual-level approach. Egger and Swinburn  have instead proposed an ecological model that defines obesity as a net result of not only behavioural, biological, but also of environmental influences. Therefore, our intervention will address both individual as well as environmental level factors.
Targeting early adolescents from low-socio economic background
We decided to aim the intervention at adolescents attending prevocational secondary schools, in their first year (mean age 12–13 years). We selected this particular age group for several reasons. First, the onset of the decrease in physical activity-levels starts at age 13. Second, high levels of sedentary behaviour, unhealthy eating habits with regard to sugar-sweetened beverages, and high-sugar/high-fat content snacks can be observed in this age group. Since socio-economic status is inversely related to overweight [49, 50], we decided to focus on adolescents with lower socio-economic and educational level.
The school setting
Schools can play a critical role in the prevention of overweight and obesity in children. With their existing organizational, social, and communication structures, they provide opportunities for health education and health enhancing environment on a regular basis [14, 29].
In the Netherlands, adolescents attend secondary school at the prevocational educational level during four years. In general, they follow a basic educational program during the first two years, after which they choose a specific educational path, according to their desired occupational field. As the group composition is nearly the same during the first two years, this feature of the Dutch educational system makes both intervention and research in this age group very attractive.
At the environmental level, we defined school staff (teachers, headmasters, canteen employees) as the second target group, in order to accomplish environmental changes that facilitate behavioural changes among adolescents.
Specification of performance objectives
To be able to tailor the intervention to the specific needs of the target group, important and modifiable determinants of the target behaviours must be identified .
In Additional file 1 we present a matrix of performance objectives crossed with the individual and environmental determinants. These determinants are again based on a combination of an analysis of systematic reviews on determinants of energy balance-related behaviours [53–56], and personal interviews with teachers, parents, experts in the field of physical activity, dietary behaviour, and behavioural change.
Theory-based methods and practical strategies
In this step of the Intervention Mapping process, theoretical methods and practical strategies that are likely to create the expected changes in the determinants were identified. Theoretical methods are general techniques or processes, derived from empirical evidence, mostly from behavioural and social science research , and describe the association between an intervention action and a change in behavioural determinants. Practical strategies are defined as techniques for the application of the theoretical methods. These strategies must be tailored to the specific needs of the target population and the setting where the intervention takes place. We identified relevant theoretical methods by literature review, investigation of existing programs , and in-depth interviews with teachers. Although underlying theoretical models and methods of behavioural change are rarely fully reported , Hardeman et al.  proposed a taxonomy of behaviour change methods that may assist individuals in developing interventions directed at weight gain prevention. Behaviour change methods, selected from this taxonomy, in order to change the performance objectives of NRG-DOiT were: (self) monitoring, self-evaluation, reward, increasing skills, goal setting, environmental changes, social encouragement, social support, information regarding behaviour and personalized messages.
Theoretical methods matched with practical strategies, identified for the DOiT-intervention program. Example: determinants of reduction consumption of sugar-sweetened beverages (SSBs) (program objective 1)
Methods from theory
Passive learning/providing information
Providing written and verbal information
Information in print materials (workbook/worksheets) during school lessons on label reading health consequences of excessive consumption SSBs
Videotape on clandestine advertising
Posters in school canteen
Active processing of information
Knowledge tests (quizzes: DRINKiT)
Cut and paste worksheets regarding SSB
Role model stories
Test recipes (workbook/worksheet)
Invent own recipes (website)
Self-monitoring and feedback
Monitoring of own behaviour (social) comparison
Pocket-size diary (CHECKiT, 3 days)
Skills training (label reading and taste)
Practice label reading in groups
Social modelling/peer modelling/social comparison
Workbook/worksheets/computer tailored advice (questionnaires, website or CD-rom)
Breaking automatic stimulus-response relations, rising awareness of habitual behaviour
Changing the environment/point-of-decision prompts
Posters near food access points/changing canteen assortment
Formulation of implementation intentions
Worksheets to help exact planning goals (How? When? Where? With whom?)
Role model stories
Discussion barriers/difficult situations, possible solutions
Computer tailored advice (website or CD-rom)
Providing feedback Evaluation of change processes
Analyses difficult situations
Computer tailored advice (website or CD-rom)
Association of attitude object with other positive stimuli
Role model stories
Facilitation of healthy behaviours
Changes in school canteen assortment
Posters in school canteen
The name of the research project 'Dutch Obesity Intervention in Teenagers' led to the acronym 'DOiT', and became the central theme of the intervention program. 'DOiT' refers to the growth of behavioural self-determination, distinctive for the age of our target group. Close collaboration with professional designers and representatives of the target group representatives led to a 'fresh', 'cool', and 'not too childish', but 'more mature' logo (see Additional file 2) and appearance of the intervention materials.
Personal interviews with teachers and parents revealed that it was of utmost importance that words related to 'weight loss' or 'dieting' should be avoided in the intervention program. Hence, the main message of the intervention program consisted of 'maintaining energy balance', and extra attention was paid to distinct messages with regard to unhealthy dieting practices, such as anorexia nervosa or bulimia nervosa.
Intervention program and materials
Guided by tables 1 and 2 we first selected components from existing intervention programs that could fit into a school-based intervention program with a duration of one school-year (i.e. eight months, from October – May), tailored to the specific objectives of the DOiT-project. We adopted several ideas from a the 'Krachtvoer' program , an intervention promoting healthy eating among Dutch adolescents of the same age and socio-economic background as our target group. Suitable components were selected and integrated in cooperation with biology and physical education teachers, since they were supposed to implement the larger part of the program. If existing tools were not available, were not well enough tailored to the objective(s), were not accepted by the teachers, or their use was too costly, we either customized parts of already existing tools or developed new tools.
The DOiT-intervention program consisted of two components: an individual classroom-based intervention and an environmental intervention.
The individual classroom-based intervention consisted of an educational program, covering 11 lessons for the biology and physical education classes. Two 'schoolbooks' were developed, accompanied by specific worksheets for each lesson.
The first six lessons of the classroom intervention, named BALANCEiT (see Additional file 3), aimed at raising awareness and information processing with regard to energy balance-related behaviours. The adolescents monitored their own behaviour during three days, using a pocket-sized diary named CHECKiT (see Additional file 4), reported it back in the classroom, and received feedback from the teacher. Based on this monitoring process, the intervention program guided the adolescents in their choice which of the four risk behaviours they were going to change initially and helped to formulate implementation intentions . Implementation intentions are not only formulated intentions of behaviours or behavioural changes to be accomplished, but they include a specification of circumstances wherein the behaviour is accomplished. The formulation of implementation intentions has shown to be effective in changing energy balance-related behaviours [59–61].
The second five lessons of the classroom intervention, named CHOOSEiT (see Additional file 5), aimed at facilitation of the choice to improve one of the identified risk behaviours. Assisted by the teachers and worksheets, adolescents identified their own risk behaviour(s), set personal goals, formulated implementation intentions, identified possible barriers/difficult situations, improved their self-efficacy, and evaluated change processes. Offering the adolescents the possibility of individual choice on how to maintain their energy balance, and not forcing them into one prescribed behavioural change, seems to be a potentially effective ingredient of our intervention . To provide adolescents with individualized feedback and guide the adolescents through the change processes, a computer-tailored program was developed, which was based on existing materials , and accessible via the internet  or CD-rom. Computer-tailored education has shown to be more effective regarding dietary changes, especially with regard to the reduction of dietary fat, than general information .
To fit the DOiT-intervention optimally into the regular curriculum, the main objectives of the regular biology and physical education curricula, formulated by the Dutch Ministry of Education, Culture and Science, were taken into account.
The environmental part of the intervention consisted of a school-specific advice on the assortment of the school canteen, taking into account individual school characteristics and possibilities (for example distance to the nearest supermarket, policy with regard to permission to leave the school ground during breaks, or the relationship between the school canteen and the school board [in the Netherlands school canteens are run by either the school itself or outsourced to an independent entrepreneur]). Proposed change options were: offering smaller portion sizes (cans instead of bottles, normal size instead of king size); offering more 'healthy' products in the (products containing less fat, less sugar); or restricting access to vending machines (i.e. only after lunch break). In addition, we delivered posters for the school canteens, with 'traffic-light' suggestions for healthier choices. Foodstuffs were thus labelled as red ('Better do not'), yellow ('Only sometimes'), or green ('DOiT').
Furthermore, we encouraged the school board to offer additional physical activity options. We offered schools funding for two weekly hours of additional physical activity, under the following conditions: (1) The lessons should be supervised by a physical education teacher; (2) the lessons should fit within the school schedule (no break between the last official school lesson and the additional lesson physical activity); (3) a minimum number of twelve lessons should be taught between November 2003 and April 2004; (4) easy accessible activities, i.e. no specific knowledge or physical conditions necessary; (5) adolescents should be physically active during a major part of the lesson; (6) activities during the lessons should encourage adolescents to increase their leisure time physical activity as well.
Pre-testing of the materials
To explore whether the developed materials were acceptable for both adolescents and teachers, we pre-tested parts of the intervention materials during personal interviews with representatives of both groups. Pre-testing took place in schools that did not take part in the trial. Pre-testing revealed the need for low information density of the lessons (workbooks and worksheets), adapted language use to make the materials easy to understand, and not too much theory, but predominantly practical assignments.
Adoption and implementation plan
In this step of the IM process, a plan for the implementation of the intervention was developed. Performance objectives were formulated with regard to expected behavioural changes of implementers and adopters of the intervention program. To gain insight into facilitating factors and possible barriers regarding the implementation, teachers and school staff were interviewed at schools, willing and unwilling to adopt the program.
In the planning of the program, a time schedule for deliverance of the intervention program was formulated, taking into consideration extracurricular activities. Based on this schedule it was decided that the intervention should start October 2003 and end in May 2004, to ensure time wise a comparable implementation in all schools. All teachers received a manual describing the structure of each lesson and goals for the distinctive parts of the lessons.
The principle investigator indicated to be available for teachers via mail or telephone any time for possible questions on the intervention.
In this step of IM an evaluation plan and the corresponding evaluation measures were identified and developed, covering as much as possible the evaluation steps, as defined in the CONSORT statement [66, 67], a checklist that intents to improve quality of reports of randomised controlled trials, by clarifying experimental processes.
We evaluated the intervention with regard to effects on body composition (primary outcome measure), behaviour, behavioural determinants, and aerobic fitness (secondary outcome measures). We also conducted a process evaluation to assess the reach, adoption, and implementation of the program, as well as conditions for program maintenance, such as appreciation of the project by students and school staff.
The effectiveness of the intervention program was evaluated using a cluster randomised controlled trial design, with measurements at baseline, after eight, twelve, and twenty months. The Medical Ethical Committee of the VU University Medical Center (Amsterdam, The Netherlands) approved the study protocol.
Recruitment of the study population
Recruitment of schools
We recruited schools using the following three methods: (1) We sent written information about the study to approximately 400 schools, offering secondary prevocational education, located in the vicinity of maximal 150 kilometres from Amsterdam. One week later, all schools were approached by phone to ask for their willingness to participate; (2) in specialist journals for biology and physical education teachers, we placed advertisements to attract schools to participate; such schools could express their interest by mail, phone, or email; (3) we gave an oral presentation on a continuous education day for physical education teachers. Written information on study participation, including contact information, was handed out to those who were interested.
Biology teachers, physical education teachers, or first year coordinator were designated as possible contact persons. Schools that were interested (n = 20) were informed by means of an oral presentation on the demands of possible participation of the school in the DOiT-project. Inclusion criteria for the schools were: (1) being able to provide three classes to participate in the study, (2) willing to appoint a contact person for the duration of the trial, (3) willing not to change the curricula during the study period when assigned to the control group, and (4) being able to provide sufficient computer facilities in order to accomplish the lessons with the computer-tailored advice via internet or CD-rom.
If requested, we provided intervention materials to all first classes of the school and only charged the extra production-costs for the additional materials.
Recruitment of adolescents
The students and their parents received an information brochure about the study. There were no individual inclusion and exclusion criteria for study enrolment. As the aim of the intervention was to prevent excessive weight gain in all adolescents, and in order to avoid stigmatisation of the obese, children at all levels of body weight were eligible. Written informed consent was obtained from all students as well as their parents.
Schools were randomly assigned to either the intervention or control group, using SPSS for a random selection of a sample. Randomisation took place at school level, and was stratified by urbanization grade (urban versus rural). Control schools were requested to maintain their regular curriculum for the duration of the project (two school years). Randomisation took place at the beginning of the school year, before baseline measurements took place, because intervention schools needed an adequate amount of time for the preparation of the classes.
The sample size calculation was based on differences between the experimental and control schools with regard to changes in body weight. A difference in weight gain of 0.5 kg between the intervention and control group after eight months was considered to be clinically relevant. Assuming α = 0.05, power = 0.90, and two-sided tests, 233 participants per group were needed to show a mean difference in weight of 0.5 kg (SD 1.5 kg) between the intervention and control group. To perform multi-level analyses and taking into account the cluster randomisation design and drop out (10–15%), a sample size between 500 and 600 subjects from 16 schools was required.
To minimize seasonal influences, all measurements were performed within a six-week period in all schools. Measurements were completed according to a standardized protocol by a trained research team. The research assistants were also involved in the organization of the measurements, and were therefore not be blinded to group assignment. Each measurement period the research team consisted of two research assistants, who performed all anthropometric measurements (one for female adolescents, one for male adolescents), two master students who assisted the research assistants (e.g. writing down the measurement results), and the principle researcher, who performed the shuttle-run test.
Before the measurements, the contact person was asked to designate two lessons physical education per class (approximately 30 students) to complete the anthropometric measures and the shuttle run test, and two other lessons for the completion of the questionnaires as a classroom activity. During the physical measurements, at least one teacher (preferably the physical education teacher) had to be present. After completion of each measurement period adolescents received a small incentive (key ring, mugs, etc).
At the start of the measurements, the procedure of the physical measurements was explained to the students. Then, students were divided into three groups of about ten students. While the first group was measured (body weight, height, skin folds, waist and hip circumference), the second group performed the shuttle run test, and the third group was waiting. When the first two groups had completed their measurements, the groups transferred to the next measurement section, until every student had completed all measurements. Optimal privacy was assured during the anthropometric measurements by measuring one adolescent at a time in a separate room.
Body height and body weight
Body height was measured and recorded with an accuracy of 1 mm with a portable stadiometer. We assembled a level to the stadiometer to ensure that the head position was standardized during the measurement. Body weight was measured and recorded within 0.1 kg with a calibrated electronic flat scale, levelled after each placement.
Skin folds, waist and hip circumference
Skin folds (m.triceps, m.biceps, m.suprailiacalis, m.subscapularis) were measured at the right side of the body to the nearest 0.2 mm . We determined skin fold thickness by averaging two measurements. If the two measurements differed by more than 1 mm, a third measurement was performed, and skin fold thickness was taken as the average over the three measurements. Waist and hip circumference were measured with a flexible band to an accuracy of 0.5 cm.
Before each measurement period, intra-rater and inter-rater reliability for all four skin folds were determined. Values for intra-rater reliability (ICC) varied between 0.82 and 0.95. Values for inter-rater reliability (ICC) varied between 0.88 and 0.99.
To assess aerobic fitness, a group-administered shuttle run test (SRT) was conducted . Due to limited size of the sports hall at several schools we changed the distance for each shuttle from 20 to 18 meters at all schools. We used the protocol of the Eurofit test . The SRT consists of a number of stages, each lasting one minute, paced by beeps at set intervals. Participants ran the 18-meter course back and forth, starting at a speed of 7.2 km/h. As the test proceeds, the interval between each successive beep reduces, forcing the student to increase running speed. The SRT test has been shown to be a reliable and valid field test to estimate maximal oxygen uptake (VO2max) in 8–19 year old children [69, 71]. To increase motivation the SR test was preformed with music. Each measurement period the same music were used.
Measurements on behavioural outcome measures
Objective measure of physical activity
In a sub sample of the study population (five schools, one class each) physical activity levels were assessed objectively using Manufacturing Technology Inc. (MTI) accelerometers (model 7164). The MTI is a valid [72–74] and reliable  instrument to measure vertical displacement of the human body.
Depending on the number of participants on each school, 15 to 25 adolescents were asked to wear the accelerometer for six consecutive days, since Trost et al.  found that a minimum of four to five days of monitoring was necessary to establish a reliability of at least 0.80. The adolescents were asked to wear the accelerometer during all waking hours, and to remove it during swimming, bathing and showering.
The participants as well as their parents received a letter with uniform instructions on how, when and where the accelerometer had to be worn. The accelerometer was secured by a waist belt and worn on the right side of the hip. To overcome the problem of inter-instrument differences, we aimed to provide each participant with the same accelerometer during all four measurement periods.
Students were requested to complete the questionnaires in the classroom. Before the questionnaires were handed out, a member of the DOiT-team shortly explained the procedure for the completion of the questionnaire. A teacher and/or a member of the DOiT-team supervised the completion of the questionnaires and took care of collecting the completed questionnaires. On average the adolescents required 60 minutes to complete the questionnaire.
Questionnaires contained frequency questions regarding the four identified risk behaviours: (1) consumption of sugar-sweetened beverages, (2) consumption of high-sugar/high-fat content snacks, (3) sedentary behaviour (watching television and using the computer), (4) low levels of physical activity (i.e. active transport to school and participation in physical activity and sports).
The questionnaire was based on other validated questionnaires for assessing dietary intake, physical activity, behaviour-specific cognitions, and habit strength in adolescent populations [77–79]. We adjusted the questionnaires according to our study population.
The structure of the questionnaire was equal for all risk behaviours. For example, adolescents had to indicate how many days a week they consumed sugar-sweetened beverages, and the amount/number of servings of sugar-sweetened beverages they usually consumed on these days, thinking of the last week. Frequency and quantity were multiplied to obtain estimates of mean daily consumption.
- Motivational determinants of behaviour
Questions on personal and social environmental determinants of each of the risk behaviours included questions on attitude, subjective norm, perceived behavioural control, personal barriers, intention and habit-strength. The determinant variables were based on the EnRGframework , an integrative framework that applies insights from Dual-Process Theory , the ANGELO model , the Theory of Planned Behaviour , and habit theory . Most variables were measured on bipolar five-point Likert scales.
The self-administered questionnaire was pre-tested for clarity and length, by means of cognitive interviewing of four adolescents from a school not participating in the study .
To evaluate the effects of the intervention, multilevel analysis was used. Using this technique, regression coefficients can be adjusted for the clustering of observations within one school and/or class. We defined three levels in our multi-level analysis: 1) student, 2) class, and 3) school. Linear and logistic models were used to examine the effect of the intervention on each of the outcome values. All analyses were performed according to the intention-to-treat-principle, that means that we did not impute values for missing data .
Process evaluation was based on the Diffusion of Innovations Theory , and involved data gathering among pupils, teachers, and members of the school boards.
Teachers and members of the school board the intervention program
All teachers and members of the board, who were involved in the implementation of the DOiT-program, were asked to participate in a semi-structured interview (questionnaire) during and after the intervention period. The questionnaire mostly consisted of structured questions, measured on a bipolar five-point Likert scale (e.g. much better, better, not better/not worse, worse, much worse). A couple of open-ended questions were added. The questionnaire was based on already existing questionnaires, used to evaluate interventions aimed at enhancing physical activity applied by general practitioners [88, 89], and consisted of 31 questions. The questionnaire contained questions on the overall impression of the DOiT-project, contentment with the communication with the DOiT team, and time spent on implementing the DOiT-program. The teachers' manual, educational appliances, the implementation of the intervention, and barriers for correct implementation were also evaluated. Finally, the intention and opportunities for implementing the DOiT-program in the future were discussed.
Additionally, we aimed to visit minimally one lesson of the classroom part of the intervention for a structured observation.
For the additional lessons physical activity, teachers were requested to register the presence of the adolescents. Forms were handed out to register activities, and teachers were asked to send the forms back monthly. We aimed to visit minimally one lesson additional physical activity at each school, checking whether the required conditions were fulfilled (by means of a form).
At the end of the intervention, all teachers physical education involved in the supervision and organization of the additional lessons physical activity were sent a short evaluation questionnaire.
During the second measurement (after eight months) questions on the lessons about healthy food, physical activity behaviour, sedentariness, changes in the assortment of the school canteen, and additional lessons physical activity were added to the questionnaire. During the last lessons of the intervention, a short questionnaire was handed out to the students of the experimental schools, evaluating the intervention program shortly (ten questions on content and attractiveness of the lessons, including intervention materials).
We applied the IM protocol for the development of an intervention aiming at the prevention of excessive weight gain among Dutch adolescents. We perceived the use of the IM protocol as a useful tool that has guided us through the process of the development of our intervention program. Since application of the IM protocol, as described by Bartholomew et al. , demands more time than was available within the DOiT-project, we decided to take a short-cut in the IM process. Following examples of other research groups that had applied the IM protocol before [57, 90], we modified the original protocol by restricting the amount and complexity of matrices in steps 1 and 2. Although we perceived the development of our intervention according to the IM as a complex and time-consuming process, we believe that the application of theory will improve the likelihood of effectiveness of interventions , and the several feedback loops in the process assured that the program matched the needs of our target population.
In conclusion, the development of the DOiT-intervention according to the IM protocol resulted in a comprehensive school-based weight gain prevention program, specifically tailored to the needs of Dutch adolescents. To determine the effectiveness of our program, we examined body composition, behaviour and behavioural determinants, and aerobic fitness. Furthermore, a process evaluation was conducted to gain insight in effective and ineffective parts of the intervention.
The results of the analyses will help to gain more insight school-based prevention of overweight and obesity in adolescents. Results of the intervention will be available in 2007.
This study is part of NHF-NRG and is funded by the Netherlands Heart Foundation (No: 2000Z003), the Dutch Ministry of Health, Welfare, and Sports, and the Royal Association of Teachers of Physical Education. None of the funders had input into protocol development, data collection, or analyses or interpretation.
We want to thank Karin Proper for the critical revision of an early draft of the manuscript.
- Barnekow-Bergkvist M, Hedberg G, Janlert U, Jansson E: Adolescent determinants of cardiovascular risk factors in adult men and women. Scand J Public Health. 2001, 29: 208-217. 10.1080/140349401316983635.View ArticlePubMedGoogle Scholar
- Kvaavik E, Tell GS, Klepp KI: Predictors and tracking of body mass index from adolescence into adulthood: follow-up of 18 to 20 years in the Oslo Youth Study. Arch Pediatr Adolesc Med. 2003, 157: 1212-1218. 10.1001/archpedi.157.12.1212.View ArticlePubMedGoogle Scholar
- Serdula MK, Ivery D, Coates RJ, Freedman DS, Williamson DF, Byers T: Do obese children become obese adults? A review of the literature. Prev Med. 1993, 22: 167-177. 10.1006/pmed.1993.1014.View ArticlePubMedGoogle Scholar
- Lobstein T, Baur L, Uauy R: Obesity in children and young people: a crisis in public health. Obes Rev. 2004, 5 Suppl 1: 4-85. 10.1111/j.1467-789X.2004.00133.x.View ArticlePubMedGoogle Scholar
- Carey VJ, Walters EE, Colditz GA, Solomon CG, Willett WC, Rosner BA, Speizer FE, Manson JE: Body fat distribution and risk of non-insulin-dependent diabetes mellitus in women. The Nurses' Health Study. Am J Epidemiol. 1997, 145: 614-619.View ArticlePubMedGoogle Scholar
- Chan JM, Rimm EB, Colditz GA, Stampfer MJ, Willett WC: Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men. Diabetes Care. 1994, 17: 961-969.View ArticlePubMedGoogle Scholar
- Donahue RP, Abbott RD, Wilson PW: Effect of diuretic use on the development of diabetes mellitus. The Framingham study. Horm Metab Res Suppl. 1990, 22: 46-48.PubMedGoogle Scholar
- Rexrode KM, Carey VJ, Hennekens CH, Walters EE, Colditz GA, Stampfer MJ, Willett WC, Manson JE: Abdominal adiposity and coronary heart disease in women. JAMA. 1998, 280: 1843-1848. 10.1001/jama.280.21.1843.View ArticlePubMedGoogle Scholar
- Overweight, obesity, and health risk. National Task Force on the Prevention and Treatment of Obesity. Arch Intern Med. 2000, 160: 898-904. 10.1001/archinte.160.7.898.Google Scholar
- Seidell JC: The current epidemic of obesity. Physical Activity and Obesity. Edited by: Bouchard C. 2000, Champaign, Illinois, Human KineticsGoogle Scholar
- Hill JO, Wyatt HR, Reed GW, Peters JC: Obesity and the environment: where do we go from here?. Science. 2003, 299: 853-855. 10.1126/science.1079857.View ArticlePubMedGoogle Scholar
- Doak CM, Visscher TL, Renders CM, Seidell JC: The prevention of overweight and obesity in children and adolescents: a review of interventions and programmes. Obes Rev. 2006, 7: 111-136. 10.1111/j.1467-789X.2006.00234.x.View ArticlePubMedGoogle Scholar
- Summerbell CD, Waters E, Edmunds LD, Kelly S, Brown T, Campbell KJ: Interventions for preventing obesity in children. Cochrane Database Syst Rev. 2005, CD001871-Google Scholar
- Story M: School-based approaches for preventing and treating obesity. Int J Obes Relat Metab Disord. 1999, 23 Suppl 2: S43-S51. 10.1038/sj.ijo.0800859.View ArticlePubMedGoogle Scholar
- Resnicow K: School-based obesity prevention. Population versus high-risk interventions. Ann N Y Acad Sci. 1993, 699: 154-166. 10.1111/j.1749-6632.1993.tb18847.x.View ArticlePubMedGoogle Scholar
- Flodmark CE, Marcus C, Britton M: Interventions to prevent obesity in children and adolescents: a systematic literature review. Int J Obes (Lond). 2006, 30: 579-589. 10.1038/sj.ijo.0803290.View ArticleGoogle Scholar
- Hardeman W, Griffin S, Johnston M, Kinmonth AL, Wareham NJ: Interventions to prevent weight gain: a systematic review of psychological models and behaviour change methods. Int J Obes Relat Metab Disord. 2000, 24: 131-143. 10.1038/sj.ijo.0801100.View ArticlePubMedGoogle Scholar
- Bartholomew LK, Parcel GS, Kok G, Gottlieb NH: Intervention Mapping: designing theory and evidence-based health promotion programs. 2001, MountainView, CA: MayfieldGoogle Scholar
- Kremers SP, Visscher TL, Brug J, Chin A Paw MJ, Schouten EG, Schuit AJ, Seidell JC, Van Baak MA, Van Mechelen W, Kemper HC, Kok FJ, Saris WH, Kromhout D: Netherlands research programme weight gain prevention (NHF-NRG): rationale, objectives and strategies. Eur J Clin Nutr. 2005, 59: 498-507. 10.1038/sj.ejcn.1602100.View ArticlePubMedGoogle Scholar
- Kok G, Schaalma H, Ruiter RA, van Empelen P, Brug J: Intervention mapping: protocol for applying health psychology theory to prevention programmes. J Health Psychol. 2004, 9: 85-98. 10.1177/1359105304038379.View ArticlePubMedGoogle Scholar
- Killen JD, Robinson TN, Telch MJ, Saylor KE, Maron DJ, Rich T, Bryson S: The Stanford Adolescent Heart Health Program. Health Educ Q. 1989, 16: 263-283.View ArticlePubMedGoogle Scholar
- Frenn M, Malin S, Bansal NK: Stage-based interventions for low-fat diet with middle school students. J Pediatr Nurs. 2003, 18: 36-45. 10.1053/jpdn.2003.6.View ArticlePubMedGoogle Scholar
- Tammelin T, Nayha S, Hills AP, Jarvelin MR: Adolescent participation in sports and adult physical activity. Am J Prev Med. 2003, 24: 22-28. 10.1016/S0749-3797(02)00575-5.View ArticlePubMedGoogle Scholar
- Mikkila V, Rasanen L, Raitakari OT, Pietinen P, Viikari J: Longitudinal changes in diet from childhood into adulthood with respect to risk of cardiovascular diseases: The Cardiovascular Risk in Young Finns Study. Eur J Clin Nutr. 2004, 58: 1038-1045. 10.1038/sj.ejcn.1601929.View ArticlePubMedGoogle Scholar
- Lien N, Lytle LA, Klepp KI: Stability in consumption of fruit, vegetables, and sugary foods in a cohort from age 14 to age 21. Prev Med. 2001, 33: 217-226. 10.1006/pmed.2001.0874.View ArticlePubMedGoogle Scholar
- Steinbeck K: Childhood obesity. Treatment options. Best Pract Res Clin Endocrinol Metab. 2005, 19: 455-469. 10.1016/j.beem.2005.04.010.View ArticlePubMedGoogle Scholar
- Nielsen SJ, Siega-Riz AM, Popkin BM: Trends in food locations and sources among adolescents and young adults. Prev Med. 2002, 35: 107-113. 10.1006/pmed.2002.1037.View ArticlePubMedGoogle Scholar
- Health Council of the Netherlands.Commitee on Trends in food consumption.: Significant trends in food consumption in the Netherlands [Dutch]. 2002, The Hague, Health Council of the Netherlands, publication no. 2002/12:Google Scholar
- World Health Organization: Diet, nutrition, and prevention of chronic diseases, Joint WHO/FAO Expert Consultation, Geneva, 28 Jan - 1 Feb 2002. 2003, Geneva, Switzerland, WHO technical report series 916:Google Scholar
- Giammattei J, Blix G, Marshak HH, Wollitzer AO, Pettitt DJ: Television watching and soft drink consumption: associations with obesity in 11- to 13-year-old schoolchildren. Arch Pediatr Adolesc Med. 2003, 157: 882-886. 10.1001/archpedi.157.9.882.View ArticlePubMedGoogle Scholar
- Ludwig DS, Peterson KE, Gortmaker SL: Relation between consumption of sugar-sweetened drinks and childhood obesity: a prospective, observational analysis. Lancet. 2001, 357: 505-508. 10.1016/S0140-6736(00)04041-1.View ArticlePubMedGoogle Scholar
- Tordoff MG, Alleva AM: Effect of drinking soda sweetened with aspartame or high-fructose corn syrup on food intake and body weight. Am J Clin Nutr. 1990, 51: 963-969.PubMedGoogle Scholar
- Malik VS, Schulze MB, Hu FB: Intake of sugar-sweetened beverages and weight gain: a systematic review. Am J Clin Nutr. 2006, 84: 274-288.PubMedPubMed CentralGoogle Scholar
- James J, Thomas P, Cavan D, Kerr D: Preventing childhood obesity by reducing consumption of carbonated drinks: cluster randomised controlled trial. BMJ. 2004, 328: 1237-10.1136/bmj.38077.458438.EE.View ArticlePubMedPubMed CentralGoogle Scholar
- Jansen J, Schuit AJ, van der Lucht F: Time for healthy living: Health promotion for specific target groups. Edited by: National Institute for Public Health and the Environment BTN. 2002, Houten, The Netherlands, Bohn Stafleu Van Loghum, 270555004:Google Scholar
- Nicklas TA, Baranowski T, Cullen KW, Berenson G: Eating patterns, dietary quality and obesity. J Am Coll Nutr. 2001, 20: 599-608.View ArticlePubMedGoogle Scholar
- Poppitt SD, Swann D, Black AE, Prentice AM: Assessment of selective under-reporting of food intake by both obese and non-obese women in a metabolic facility. Int J Obes Relat Metab Disord. 1998, 22: 303-311. 10.1038/sj.ijo.0800584.View ArticlePubMedGoogle Scholar
- Rennie KL, Johnson L, Jebb SA: Behavioural determinants of obesity. Best Pract Res Clin Endocrinol Metab. 2005, 19: 343-358. 10.1016/j.beem.2005.04.003.View ArticlePubMedGoogle Scholar
- Halford JC, Gillespie J, Brown V, Pontin EE, Dovey TM: Effect of television advertisements for foods on food consumption in children. Appetite. 2004, 42: 221-225. 10.1016/j.appet.2003.11.006.View ArticlePubMedGoogle Scholar
- Prentice AM, Jebb SA: Obesity in Britain: gluttony or sloth?. BMJ. 1995, 311: 437-439.View ArticlePubMedPubMed CentralGoogle Scholar
- Robinson TN: Television viewing and childhood obesity. Pediatr Clin North Am. 2001, 48: 1017-1025. 10.1016/S0031-3955(05)70354-0.View ArticlePubMedGoogle Scholar
- Andersen RE, Crespo CJ, Bartlett SJ, Cheskin LJ, Pratt M: Relationship of physical activity and television watching with body weight and level of fatness among children: results from the Third National Health and Nutrition Examination Survey. JAMA. 1998, 279: 938-942. 10.1001/jama.279.12.938.View ArticlePubMedGoogle Scholar
- Zeijl E, Beker M, Breedveld K, van den Broek A, de Haan J, Herweijer L, Huysmans F, Wittebrood K: Rapportage jeugd 2002. 2003, Den Haag, Sociaal en Cultureel PlanbureauGoogle Scholar
- StatLine: . 2006, [http://statline.cbs.nl/StatWeb/start.asp?LA=nl&DM=SLNL&lp=Search%2FSearch]
- Van Mechelen W, Twisk JW, Post GB, Snel J, Kemper HC: Physical activity of young people: the Amsterdam Longitudinal Growth and Health Study. Med Sci Sports Exerc. 2000, 32: 1610-1616. 10.1097/00005768-200009000-00014.View ArticlePubMedGoogle Scholar
- Riddoch CJ, Andersen LB, Wedderkopp N, Harro M, Klasson-Heggebo L, Sardinha LB, Cooper AR, Ekelund U: Physical activity levels and patterns of 9- and 15-yr-old European children. Med Sci Sports Exerc. 2004, 36: 86-92. 10.1249/01.MSS.0000106174.43932.92.View ArticlePubMedGoogle Scholar
- Must A, Tybor DJ: Physical activity and sedentary behavior: a review of longitudinal studies of weight and adiposity in youth. Int J Obes (Lond). 2005, 29 Suppl 2: S84-S96. 10.1038/sj.ijo.0803064.View ArticleGoogle Scholar
- Egger G, Swinburn B: An "ecological" approach to the obesity pandemic. BMJ. 1997, 315: 477-480.View ArticlePubMedPubMed CentralGoogle Scholar
- Wang Y: Cross-national comparison of childhood obesity: the epidemic and the relationship between obesity and socioeconomic status. Int J Epidemiol. 2001, 30: 1129-1136. 10.1093/ije/30.5.1129.View ArticlePubMedGoogle Scholar
- Hulshof KF, Brussaard JH, Kruizinga AG, Telman J, Lowik MR: Socio-economic status, dietary intake and 10 y trends: the Dutch National Food Consumption Survey. Eur J Clin Nutr. 2003, 57: 128-137. 10.1038/sj.ejcn.1601503.View ArticlePubMedGoogle Scholar
- Zimmermann BM: Attaining self-regulation. Handbook of self-regulation. Edited by: Boekaerts M, Pintrich PR and Zeidner M. 2000, San Diego, Academic Press, 13-39.View ArticleGoogle Scholar
- Bauman AE, Sallis JF, Dzewaltowski DA, Owen N: Toward a better understanding of the influences on physical activity. The role of determinants, correlates, causal variables, mediators, moderators, and confounders. Am J Prev Med. 2002, 23: 5-14. 10.1016/S0749-3797(02)00469-5.View ArticlePubMedGoogle Scholar
- Sallis JF, Prochaska JJ, Taylor WC: A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc. 2000, 32: 963-975. 10.1097/00005768-200005000-00014.View ArticlePubMedGoogle Scholar
- Gordon-Larsen P, Mcmurray RG, Popkin BM: Determinants of adolescent physical activity and inactivity patterns. Pediatrics. 2000, 105: E83-10.1542/peds.105.6.e83.View ArticlePubMedGoogle Scholar
- Baranowski T, Cullen KW, Baranowski J: Psychosocial correlates of dietary intake: advancing dietary intervention. Annu Rev Nutr. 1999, 19: 17-40. 10.1146/annurev.nutr.19.1.17.View ArticlePubMedGoogle Scholar
- Gorely T, Marshall SJ, Biddle SJ: Couch kids: correlates of television viewing among youth. Int J Behav Med. 2004, 11: 152-163. 10.1207/s15327558ijbm1103_4.View ArticlePubMedGoogle Scholar
- Martens MK, van Assema P, Paulussen GW, Schaalma H, Brug J: Krachtvoer: process evaluation of a Dutch programme for lower vocational schools to promote healthful diet (in press). Health Education Research. 2006Google Scholar
- Gollwitzer PM: Implementation Intentions: Strong effects of simple plans. American Psychologist. 1999, 54: 493-503. 10.1037/0003-066X.54.7.493.View ArticleGoogle Scholar
- Armitage CJ: Evidence that implementation intentions reduce dietary fat intake: a randomized trial. Health Psychol. 2004, 23: 319-323. 10.1037/0278-6188.8.131.529.View ArticlePubMedGoogle Scholar
- Milne S, Orbell S, Sheeran P: Combining motivational and volitional interventions to promote exercise participation: protection motivation theory and implementation intentions. Br J Health Psychol. 2002, 7: 163-184. 10.1348/135910702169420.View ArticlePubMedGoogle Scholar
- Verplanken B, Faes S: Good intentions, bad habits, and effects of forming implementation intentions on healthy eating. European Journal of Social Psychology. 1999, 29: 591-604. 10.1002/(SICI)1099-0992(199908/09)29:5/6<591::AID-EJSP948>3.0.CO;2-H.View ArticleGoogle Scholar
- Kremers SPJ, De Bruijn GJ, Schaalma H, Brug J: Clustering of energy balance-related behaviours and their intrapersonal determinants. Psychology & Health. 2004, 19: 595-606. 10.1080/08870440412331279630.View ArticleGoogle Scholar
- Oenema A, Tan F, Brug J: Short-term efficacy of a web-based computer-tailored nutrition intervention: main effects and mediators. Ann Behav Med. 2005, 29: 54-63. 10.1207/s15324796abm2901_8.View ArticlePubMedGoogle Scholar
- doitproject. 2006, [http://www.doitproject.com]
- Kroeze W, Werkman A, Brug J: A systematic review of randomized trials on the effectiveness of computer-tailored education on physical activity and dietary behaviors. Ann Behav Med. 2006, 31: 205-223. 10.1207/s15324796abm3103_2.View ArticlePubMedGoogle Scholar
- Begg C, Cho M, Eastwood S, Horton R, Moher D, Olkin I, Pitkin R, Rennie D, Schulz KF, Simel D, Stroup DF: Improving the quality of reporting of randomized controlled trials. The CONSORT statement. JAMA. 1996, 276: 637-639. 10.1001/jama.276.8.637.View ArticlePubMedGoogle Scholar
- Altman DG, Schulz KF, Moher D, Egger M, Davidoff F, Elbourne D, Gotzsche PC, Lang T: The revised CONSORT statement for reporting randomized trials: explanation and elaboration. Ann Intern Med. 2001, 134: 663-694.View ArticlePubMedGoogle Scholar
- Durnin JV, Rahaman MM: The assessment of the amount of fat in the human body from measurements of skinfold thickness. Br J Nutr. 1967, 21: 681-689. 10.1079/BJN19670070.View ArticlePubMedGoogle Scholar
- Leger LA, Mercier D, Gadoury C, Lambert J: The multistage 20 metre shuttle run test for aerobic fitness. J Sports Sci. 1988, 6: 93-101.View ArticlePubMedGoogle Scholar
- Council of Europe: Eurofit: handbook for the Eurofit tests of physical fitness. 1988, Rome, Council of EuropeGoogle Scholar
- Van Mechelen W, Hlobil H, Kemper HC: Validation of two running tests as estimates of maximal aerobic power in children. Eur J Appl Physiol Occup Physiol. 1986, 55: 503-506. 10.1007/BF00421645.View ArticlePubMedGoogle Scholar
- Melanson EL, Freedson PS: Validity of the Computer Science and Applications, Inc. (CSA) activity monitor. Med Sci Sports Exerc. 1995, 27: 934-940.View ArticlePubMedGoogle Scholar
- Puyau MR, Adolph AL, Vohra FA, Butte NF: Validation and calibration of physical activity monitors in children. Obes Res. 2002, 10 (3): 150-157.View ArticlePubMedGoogle Scholar
- Trost SG, Ward DS, Moorehead SM, Watson PD, Riner W, Burke JR: Validity of the computer science and applications (CSA) activity monitor in children. Med Sci Sports Exerc. 1998, 30: 629-633.View ArticlePubMedGoogle Scholar
- Metcalf BS, Curnow JS, Evans C, Voss LD, Wilkin TJ: Technical reliability of the CSA activity monitor: The EarlyBird Study. Med Sci Sports Exerc. 2002, 34: 1533-1537. 10.1097/00005768-200209000-00022.View ArticlePubMedGoogle Scholar
- Trost SG: Objective measurement of physical activity in youth: current issues, future directions. Exerc Sport Sci Rev. 2001, 29: 32-36. 10.1097/00003677-200101000-00007.View ArticlePubMedGoogle Scholar
- van Assema P, Brug J, Ronda G, Steenhuis I, Oenema A: A short dutch questionnaire to measure fruit and vegetable intake: relative validity among adults and adolescents. Nutr Health. 2002, 16: 85-106.View ArticlePubMedGoogle Scholar
- van Assema P, Brug J, Ronda G, Steenhuis I: The relative validity of a short Dutch questionnaire as a means to categorize adults and adolescents to total and saturated fat intake. J Hum Nutr Diet. 2001, 14: 377-390. 10.1046/j.1365-277X.2001.00310.x.View ArticlePubMedGoogle Scholar
- Robinson TN: Reducing children's television viewing to prevent obesity: a randomized controlled trial. JAMA. 1999, 282: 1561-1567. 10.1001/jama.282.16.1561.View ArticlePubMedGoogle Scholar
- Kremers SP, de Bruijn GJ, Visscher TL, van Mechelen W, de Vries NK, Brug J: Environmental influences on energy balance-related behaviors: A dual-process view. Int J Behav Nutr Phys Act. 2006, 3: 9-10.1186/1479-5868-3-9.View ArticlePubMedPubMed CentralGoogle Scholar
- Chaiken S, Trope Y: Dual-Process Theory in Social Psychology. Edited by: Chaiken S and Trope Y. 1999, New York, Guilford PressGoogle Scholar
- Swinburn B, Egger G, Raza F: Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev Med. 1999, 29: 563-570. 10.1006/pmed.1999.0585.View ArticlePubMedGoogle Scholar
- Ajzen I: The theory of planned behavior. Org Behav Hum Decis. 1991, 50: 179-211. 10.1016/0749-5978(91)90020-T.View ArticleGoogle Scholar
- Aarts H, Paulussen T, Schaalma H: Physical exercise habit: on the conceptualization and formation of habitual health behaviours. Health Educ Res. 1997, 12: 363-374.View ArticlePubMedGoogle Scholar
- van der HK, Kremers S, Ferreira I, Singh A, Oenema A, Brug J: Perceived parenting style and practices and the consumption of sugar-sweetened beverages by adolescents. Health Educ Res. 2006Google Scholar
- Hollis S, Campbell F: What is meant by intention to treat analysis? Survey of published randomised controlled trials. BMJ. 1999, 319: 670-674.View ArticlePubMedPubMed CentralGoogle Scholar
- Rogers EM: Diffusion of innovations. 1995, New York, The Free Press, 4th editionGoogle Scholar
- Long BJ, Calfas KJ, Wooten W, Sallis JF, Patrick K, Goldstein M, Marcus BH, Schwenk TL, Chenoweth J, Carter R, Torres T, Palinkas LA, Heath G: A multisite field test of the acceptability of physical activity counseling in primary care: project PACE. Am J Prev Med. 1996, 12: 73-81.PubMedGoogle Scholar
- van Sluijs EM, van Poppel MN, Stalman WA, van Mechelen W: Feasibility and acceptability of a physical activity promotion programme in general practice. Fam Pract. 2004, 21: 429-436. 10.1093/fampra/cmh414.View ArticlePubMedGoogle Scholar
- Perez-Rodrigo C, Wind M, Hildonen C, Bjelland M, Aranceta J, Klepp KI, Brug J: The pro children intervention: applying the intervention mapping protocol to develop a school-based fruit and vegetable promotion programme. Ann Nutr Metab. 2005, 49: 267-277. 10.1159/000087249.View ArticlePubMedGoogle Scholar
- Brug J, Oenema A, Ferreira I: Theory, evidence and Intervention Mapping to improve behavior nutrition and physical activity interventions. Int J Behav Nutr Phys Act. 2005, 2: 2-10.1186/1479-5868-2-2.View ArticlePubMedPubMed CentralGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/6/304/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.