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Haerens L, Deforche B, Maes L, Brug J, Vandelanotte C, De Bourdeaudhuij I. A computer-tailored dietary fat intake intervention for adolescents: Results of a randomized controlled trial. Ann Behav Med. 2007 Nov-Dec; 34(3): 253-262.

PubMed ID: 18020935
Study Design:
Randomized Controlled Trial
A - Click here for explanation of classification scheme.
POSITIVE: See Research Design and Implementation Criteria Checklist below.
Research Purpose:
  • To evaluate the acceptability and feasibility of a computer-tailored dietary fat intake education program for adolescents
  • To investigate the short-term impact of this computer-tailored dietary fat intake intervention (compared to a no-intervention group) on adolescents' dietary fat intake.
Inclusion Criteria:

All secondary schools with at least two classes of seventh graders within two cities in Belgium. 

Exclusion Criteria:
  • Principal declined participation
  • Parent unwilling to sign an informed consent form
  • Student was absent on the day of pre- or post-test measurements.
Description of Study Protocol:


All secondary schools with at least two classes of seventh graders from two cities in Belgium were invited to participate.


Clustered randomized control trial: A random sample of 10 schools were selected to participate and, within each of the 10 schools, two classes of seventh graders were randomly assigned to the intervention or the control (no-intervention) condition. Questionnaires were completed one week before and three months after the one-time intervention session.

Dietary Intake/Dietary Assessment Methodology

  • A paper-and-pencil food-frequency questionnaire (FFQ) for measuring dietary fat intake based on items taken from validated food intake questionnaires for adolescents and adults
  • Test-retest reliability showed Cronbach’s alpha coefficient of 0.83 for total fat intake
  • The questionnaire was validated against a seven-day food diary and showed appropriate validity (R=0.78).


  • The intervention was an adaptation of an adult computer-tailored dietary intake intervention that was aimed at encouraging a reduction in dietary fat intake:
    • Students were exposed once, in class, to a 50-minute, theory-based computer-tailored dietary fat intake intervention, provided as a self-explanatory CD-ROM
    • Students completed the program independently
    • The computer program consisted of three interactive parts:
      • An introduction page (general information about the diagnostic tool)
      • A diagnostic tool (questionnaires about demographic information, dietary fat intake and psychosocial determinants of dietary fat intake)
      • Intervention messages (messages tailored to the students' responses in the diagnostic tool)
  • The trans-theoretical model was used to define the content and approach of the feedback in the intervention messages. An algorithm that was used to tailor to students’ stage of change based on their responses in the FFQ in the diagnostic tool of the computer program.

Statistical Analysis

  • Independent sample T-tests and chi-square analyses were used to explore baseline differences between conditions for demographic, motivational and behavioral characteristics
  • Two-way analyses of variance were used to explore differences in feasibility and acceptability according to gender and education type (general vs. technical-vocational school)
  • Linear mixed models on post-intervention measures of total dietary fat intake, with condition, gender and type of education as between-subject factors, were used to explore the intervention effects of dietary fat intake in the total sample
    • Class was nested within condition to take into account clustering within classes
    • Analyses were adjusted for baseline values of dietary fat intake
  • Linear mixed models were repeated in the same way with process measures (stage of change, evaluation items) as between-subject factors to assess the moderating effects of these process measures on student dietary changes. 
Data Collection Summary:

Timing of Measurements

  • Pre-test: One week prior to the intervention
  • Post-test: Three months after the intervention.

Dependent Variables

  • Acceptability and feasibility of the computer program measured by paper-and-pencil questionnaires
  • Dietary fat intake (g per day) at post-test measured by a paper-and-pencil FFQ.

Independent Variables

  • Students' gender and education (general vs. vocational-technical secondary school)
  • Computerized dietary fat intake intervention vs. no intervention
  • Stage of change (pre-contemplation, contemplation, preparation, action, maintenance) as a moderator variable.

Control Variables

Dietary fat intake (g per day) at baseline. 

Description of Actual Data Sample:
  • Initial N: 339 students
  • Attrition (final N): 304 students (153 in intervention group, 151 in control group)
  • Age: 13.2±0.5 years
  • Ethnicity: White
  • Other relevant demographics:
    • 70.4% (N=214) girls
    • 57.2% attended general secondary school vs. 42.8% attended technical-vocational secondary school
  • Location: Two cities in Belgium.
Summary of Results:

Pre- and Post-dietary Fat Intake Levels and F-values for Gender and Type of Education

 Total Dietary Fat Intake (g per Day) Intervention/Control  Pre (M±SD Post (M±SD)  Post-hoc2 
Total General  90 



  65  Iread






 Boys General 41 




   26 Iread








Girls General  49 




  39  Iread 



  54  104.3±38.0 


Total technical-vocational  63 



  46  Iread 






 Boys technical-vocational









 Girls technical-vocational 54 



  43  Iread 






F-values  I-C  Iread-C       
 FConditionXGenderXEducation 7.1**  5.9**       

Note. I = intervention; Iread = intervention students who had read the intervention messages; C = control.

a Post-hoc reported only, when applicable and significant.

* P<0 .05; ** P<0.01.

Summary of Main Findings

  • In girls undertaking technical-vocational education, P<0.05, but not in boys undertaking technical-vocational education; a significantly greater dietary fat intake decrease was seen for the intervention group (14.0g per day) compared to the control group (7.1g per day)
  • No significant (NS) gender X condition or condition effects were seen in the general education group
  • Secondary analyses, including only those intervention students who reported to have read the intervention messages, revealed positive effects for students from general schools and for girls undertaking technical-vocational education:
    • For students from general schools who reported to have read the intervention messages, the intervention group had a significantly greater decrease in dietary fat intake (16.2g per day) compared to the control group (2.7g per day) (P<0.05)
    • For girls from technical-vocational schools who reported to have read the intervention messages, the intervention group had a significantly greater decrease in dietary fat intake (13.7g per day) compared to the control group (7.1g per day) (P<0.05)
  • Students' self-rated "stage of change" was a significant moderator of change in total dietary fat intake (P<0.05). Dietary fat intake decreased by the following amounts in the following groups:
    • 10.1g per day in pre-contemplators
    • 6.2g per day in contemplators
    • 33.7g per day in pre-parators
    • 12.3g per day in actors
    • 6.4g per day in maintainers
  • Students who reported to have read the intervention messages decreased their dietary fat intake by a significantly greater amount (14.4g per day), compared to students who reported to not have read the intervention messages (4.6g per day) (P<0.05).

Other Findings

  • With respect to the acceptability and feasibility of the diagnostic tool:
    • Most students reported that the diagnostic tool questions were easy to read (73.8% agreed), were comprehensible (61.1%) and had clear instructions (64.1%)
    • Approximately half of the students thought the questions were easy to fill in (56%), had good grammatical style (56.7%) and had clear answering options (51.6%)
    • Approximately half (54.8%) of the students thought the diagnostic tool had too many questions
    • No gender or type of education differences were seen for most items related to the diagnostic tool with two exceptions:
      • There was a trend (P<0.08) for boys from general schools to find the diagnostic tool questions more comprehensible compared to boys from technical-vocational schools
      • Significantly more girls than boys reported that the diagnostic tool instructions were clear (P<0.01)
  •  With respect to the acceptability and feasibility of the dietary fat intervention messages:
    • Only approximately half of the students reported the intervention messages were easy to understand (52.8%), complete (43.3%) and good (57.3%)
    • A minority of students felt the intervention messages were interesting (34.4%), taught them new things (38.1%), were personally relevant (26.1%), credible (34.4%) and correct (38.3%)
    • Approximately half of students (53.6%) reported that they had read the fat intake recommendations, but only 37.5% of the students were positive about using the recommendations
    • Significant gender X education interactions were found for the items "personally relevant," "confusing," "good" and "I am going to use the intervention messages"
      • Girls from technical-vocational schools perceived the intervention messages to be significantly more personally relevant (P<0.001) and good (P<0.05), and significantly less confusing (P<0.05), compared to girls from general schools
      • Girls from technical-vocational schools planned significantly more to use the intervention messages when compared to girls from general schools (P<0.001)
      • NS differences were found for boys
    • Girls reported that they read the intervention messages significantly more often than boys (P<0.001)
  •   With respect to the acceptability and feasibility of the computer program:
    • Most of the students found that the computer program was user friendly (71.1%), conveniently arranged (66.2%) and good for such interventions (58.8%)
    • A significant gender X education interaction effect was found for the item "conveniently arranged"
      • Girls from technical-vocational schools thought that the intervention messages were more conveniently arranged when compared to girls from general schools
      • NS differences were found for boys. 
Author Conclusion:
  • Aim one: Acceptability and feasibility of the computer-based intervention:
    • Adolescents had few problems with the diagnostic tool, although most adolescents commented that there were too many questions
    • Most adolescents did not perceive the intervention messages as interesting, new, personally relevant or correct
    • Because a large proportion of students were pre-contemplators (i.e., they were unaware of their high dietary fat intake), they may have thought a tailored intervention was not applicable to them and were less likely to evaluate the intervention messages as positive and to make efforts to read the messages or decrease their dietary fat intake
  • Aim two: Effectiveness of the computer-based intervention:
    • The intervention did not show effectiveness on the total sample
      • However, one fourth of the students reported that the had not read the intervention messages; thus, the lack of impact in the total sample is not surprising
      • Secondary analyses of only students who had read the intervention messages showed that tailored feedback had a positive impact on dietary fat intake of boys and girls undertaking general education
    • A positive impact of the intervention was seen for girls undertaking technical-vocational education; this effect remained when only examining students who had read the intervention messages:
      • Previous research has shown that tailored feedback is especially effective for people who are at least somewhat motivated to change
      • Motivation levels for the adolescents in this study may have varied since the intervention took place in a classroom-based session
  • Study strengths:
    • The school environment was identical for students in both the intervention and control groups, allowing the effects found to be largely attributed to the computer-tailored intervention
    • The computer-tailored intervention was implemented in a real-life setting, increasing the external validity of the results
  • Study limitations:
    • Boys were under-represented in the study; there were only 19 boys from technical-vocational schools, which may have resulted in a lack of power to detect possible intervention effects
    • This study investigated only the short-term effectiveness of the computer-tailored intervention. It remains uncertain whether effects would be sustained over a longer period.
    • A three-month period may have been too short for students to make substantial changes in some of their diets
    • The self-report used to assess tailoring effects could have resulted in a reporting bias
    • By assigning classes within the same school to either an intervention or a control group, contamination between the intervention and control group may have occurred.
Reviewer Comments:
  • This study is limited by the fact that the intervention group (who received a tailored intervention) was compared to a no-intervention control group. However, a non-tailored intervention group should have also been used as a control group.
  • Notes on the Research Design and Implementation Rating Checklist:
    • Relevance Question 1: Unclear was marked because the intervention did not work in the total sample of adolescents. Intervention effectiveness was moderated by gender, education type and stage of change. Thus, it is unclear as to whether this intervention would work for other samples of adolescents. Additionally, because this tailored intervention was not compared to a non-tailored intervention, it is unclear as to whether it is the preferable mode of intervention dissemination.
    • Validity Question 2.4: Unclear was marked because the authors did not provide a thorough report of the samples' demographic characteristics or a discussion as to how representative these adolescents are of the total population of adolescents in Belgium. The schools and classrooms recruited for this study were randomly selected; however, only 19 boys from technical-vocational schools participated in the intervention. Thus, this may not have been a representative sample. Overall, there was not enough information provided to determine the representativeness of the schools studies and the adolescents sampled. 
    • Blinding Questions 5, 5.1-5.5: It was not possible for the researchers to blind the subjects to their condition because the treatment was overt; the students either participated in the intervention or they did not. The authors never mentioned whether the data collectors or investigators who analyzed the data where blinded to the conditions.
    • Exposure Question 6.3: This question is a bit subjective in this situation, but "no" was chosen because the intervention was not effective for the total sample and because it was a one time intervention; a more intensive intervention may have been more effective.

Research Design and Implementation Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies)
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about?
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to nutrition or dietetics practice?
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies)
Validity Questions
1. Was the research question clearly stated?
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified?
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated?
  1.3. Were the target population and setting specified?
2. Was the selection of study subjects/patients free from bias?
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study?
  2.2. Were criteria applied equally to all study groups?
  2.3. Were health, demographics, and other characteristics of subjects described?
  2.4. Were the subjects/patients a representative sample of the relevant population?
3. Were study groups comparable?
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT)
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline?
  3.3. Were concurrent controls used? (Concurrent preferred over historical controls.)
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis?
  3.5. If case control or cross-sectional study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable. Criterion may not be applicable in some cross-sectional studies.)
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")?
4. Was method of handling withdrawals described?
  4.1. Were follow-up methods described and the same for all groups?
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.)
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for?
  4.4. Were reasons for withdrawals similar across groups?
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study?
5. Was blinding used to prevent introduction of bias?
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate?
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.)
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded?
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status?
  5.5. In diagnostic study, were test results blinded to patient history and other test results?
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described?
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied?
  6.2. In observational study, were interventions, study settings, and clinicians/provider described?
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect?
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured?
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described?
  6.6. Were extra or unplanned treatments described?
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups?
  6.8. In diagnostic study, were details of test administration and replication sufficient?
7. Were outcomes clearly defined and the measurements valid and reliable?
  7.1. Were primary and secondary endpoints described and relevant to the question?
  7.2. Were nutrition measures appropriate to question and outcomes of concern?
  7.3. Was the period of follow-up long enough for important outcome(s) to occur?
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures?
  7.5. Was the measurement of effect at an appropriate level of precision?
  7.6. Were other factors accounted for (measured) that could affect outcomes?
  7.7. Were the measurements conducted consistently across groups?
8. Was the statistical analysis appropriate for the study design and type of outcome indicators?
  8.1. Were statistical analyses adequately described and the results reported appropriately?
  8.2. Were correct statistical tests used and assumptions of test not violated?
  8.3. Were statistics reported with levels of significance and/or confidence intervals?
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)?
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)?
  8.6. Was clinical significance as well as statistical significance reported?
  8.7. If negative findings, was a power calculation reported to address type 2 error?
9. Are conclusions supported by results with biases and limitations taken into consideration?
  9.1. Is there a discussion of findings?
  9.2. Are biases and study limitations identified and discussed?
10. Is bias due to study’s funding or sponsorship unlikely?
  10.1. Were sources of funding and investigators’ affiliations described?
  10.2. Was the study free from apparent conflict of interest?