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Research Article
Effects of the Informed Health Choices primary school intervention on the ability of children in Uganda to assess the reliability of claims about treatment effects, one-year follow-up: a cluster-randomised trial
Andrew David Oxman
Corresponding Author
ORCiD: 0000-0002-5608-5061
View the final published version at Trials.
Abstract
Introduction We evaluated an intervention designed to teach 10 to 12-year-old primary school children to assess claims about the effects of treatments (any action intended to maintain or improve health). We report here on outcomes measured one year after the intervention. Methods In this cluster-randomised trial, we included primary schools in the central region of Uganda that taught year-five children (aged 10 to 12 years). We randomly allocated a representative sample of eligible schools to either an intervention or control group. Intervention schools received the Informed Health Choices primary school resources (textbooks, exercise books, and a teachers’ guide). The primary outcome, measured at the end of the school term and again after one year, was the mean score on a test with two multiple-choice questions for each of the 12 concepts and the proportion of children with passing scores. Results We assessed 2960 schools for eligibility; 2029 were eligible, and a random sample of 170 were invited to recruitment meetings. After recruitment meetings, 120 eligible schools consented and were randomly assigned to either the intervention group (n=60, 76 teachers and 6383 children) or control group (n=60, 67 teachers and 4430 children). After one year, the mean score in the multiple-choice test for the intervention schools was 68.7% compared to 53.0% for the control schools (adjusted mean difference 16.7%, 95% CI 13.9 to 19.5; p<0·00001). In the intervention schools, 3160 (80.1%) of 3943 children that completed the test after one year achieved a predetermined passing score (≥13 of 24 correct answers) compared with 1464 (51.5%) of 2844 children in the control schools (adjusted difference 39.5%, 95% CI 29.9 to 47.5). Conclusion Use of the learning-resources led to a large improvement in the ability of children to assess claims, which was sustained for at least one year.
Keywords
evidence-based healthcare, training, critical thinking, health literacy, informed decision-making, public involvement, children
Figures
Figure 1
Figure 2
Summary Box
What is already known:
- There is an overload of unsubstantiated claims about the benefits and harms of treatments.
- Many people are unable to assess the reliability of these claims.
- This leads to poorly informed decisions, unnecessary suffering and waste.
What are the new findings:
- Children (aged 10–12) who used the Informed Health Choices primary school resources learned to think critically about treatment claims, and retained what they learned for at least one year.
How might it impact on clinical practice in the foreseeable future?
- In the short term, children are likely to think more critically about treatment claims and choices.
- In the long term, they may be enabled to make well-informed decisions as patients and future health professionals, and as citizens and future policymakers.
Background
We identified Informed Health Choices (IHC) Key Concepts that people need to understand and apply when assessing claims about treatments.1,2 Together with teachers in Uganda, we determined which of those concepts were relevant for primary school children.3 We then prototyped, user tested and piloted learning-resources to teach 12 Key Concepts (Box 1) to children,4 and we developed and validated a test to measure their ability to apply those concepts.5–9
The resulting learning-resources, which were in English, included a textbook, a teachers’ guide, an exercise book, a poster, and cards for an activity. The textbook10 consists of a story in a comic book format (Figure 1), instructions for classroom activities, exercises, a checklist summarising the concepts in the book, and a glossary of key words with definitions in English and translations to Luganda and Swahili. In addition to the textbooks, we provided intervention schools with a guide11 for each teacher, an exercise book for each child, a poster of the checklist for the classroom, and activity cards for the seventh lesson.12 The contents of the book and the teachers’ guide are shown in Box 2.
We conducted a cluster-randomised trial to evaluate the effects of using the learning-resources.13,14 The intervention included a two-day introductory workshop for the teachers, as well as providing them with the learning-resources. The trial showed that the intervention resulted in a large improvement in the ability of children to assess claims about the effects of treatments, measured at the end of the term during which the intervention was delivered.14 In this paper, we report on outcomes measured one year after the intervention. We report a process evaluation in a separate paper.15
Methods
Details regarding the study methods can be found in the trial protocol13 and report of the initial results.14 They are briefly summarised here.
Participants
Between April 11, 2016 and June 8, 2016, we randomly selected 170 out of 2029 eligible schools in central Uganda and recruited 120 of those schools (Figure 2). We included all year-five children in those schools.
Random allocation and blinding
We randomly allocated schools to the intervention or control group using a computer-generated sequence. We used stratified randomisation to help ensure equal distribution of schools for school ownership (public or private), and geographical location (urban, semi-urban, or rural). Research assistants labelled opaque envelopes with the unique codes, inserted cards with the study group allocated to each code in the envelopes, and sealed them. After obtaining consent from 120 schools, two research assistants selected each school from a list of the schools; identified the appropriate randomisation list to be used for that school, based on its geographical location and ownership; and assigned the next available code from that list.
We informed the participating head teachers and year-five teachers about the objectives of the study.13 After randomisation, they knew whether they were in the intervention or control arm. The consent form stated that the outcome measure consisted of “multiple-choice questions that assess an individual’s ability to apply concepts that people must be able to understand and apply to assess treatment claims and to make informed healthcare choices.” We did not show them the test until the end of the school term. Children in both arms of the trial were informed of the purpose of the test when their teachers asked them to complete it at the end of the term and again after one year.
Interventions
We designed the learning-resources to be used over nine weeks, with one double period (80 minutes) per week, during a single school term, and one hour to complete the test at the end of the term and again after one year. There was an expectation on the part of the head teachers and teachers that any content displaced by the lessons would be compensated, so that time was not taken away from other lessons. Each school decided how to do this. The intervention was delivered between June and August 2016.
We invited all participating teachers in the intervention group to attend an introductory workshop. At the workshop, we informed them about the study objectives and procedures, including the general nature of the outcome measure; went through all nine lessons outlined in the primary school resources; and addressed any questions or concerns that arose.
We invited year-five teachers in the control schools to a two-hour introductory meeting in each district. At these meetings, we informed them about the study procedures, including the general nature of the test that we would be using as the outcome measure. We told them that they would receive the primary school resources at the end of the study. We did not introduce them to the resources.
Outcomes
The primary outcomes, measured using the same test taken at the end of the term when the intervention was delivered, were:
- The mean test score (percent of correct answers) on the same test one year later
- The proportion of children with a passing score
Secondary outcomes were:
- The proportion of children with a score indicating mastery of the concepts
- For each concept, the proportion of children who answered both questions correctly
- The children’s intended behaviours and self-efficacy
- Self-reported behaviours
- Mean scores, passing scores, and mastery scores for the teachers, who took the same test as the children at the end of the intervention term and again one year later
Most teachers completed the test at the same time as the children. We contacted teachers who were not available on the day of the exam to arrange completion of the questionnaire on another day. The children and the teachers were aware that missing answers would be scored as wrong.
The test included 24 multiple-choice questions (two for each concept) (Supplementary file 1).6 The questions had between two and four response options, with an overall probability of answering 39% of the questions correctly by chance alone. Two additional multiple-choice questions were included because the test used in this trial was also used in a linked randomised trial evaluating a podcast given to the parents of some of the children.16 These two extra questions were not included in the primary analyses.
The test also included questions that assessed intended behaviours, self-efficacy, attitudes, and reading skills (Supplementary file 1). We used the answers to the reading skills questions as a covariate in exploratory analyses. In the test taken after one year, we also collected data on self-reported behaviours (Table 1). We made the comparisons shown in (Supplementary file 2- additional table 1) with the corresponding hypotheses. These were not specified in the original protocol for the study, but were planned prior to collecting the one-year follow-up data.
Children were counted as “passing” or “failing” depending on whether they met a pre-specified passing score (a minimum of 13 out of 24 questions answered correctly).9 We used a second cut-off for a score that indicated mastery of the 12 concepts (a minimum of 20 out of 24 questions answered correctly).
We also report here attendance and scores on national examinations, for intervention term and for the following term. These comparisons were originally planned as part of the process evaluation.17 We asked participating schools to provide us with school attendance records and summary score sheets containing all pupils’ end of intervention term examination scores. The summary score sheet (Table 2) contains percentage scores for each end of intervention term examination and a total score across subjects (Supplementary file 2- additional table 2). The children receive marks for English, mathematics, social studies, and science. We measured the mean difference between the intervention and control groups for each subject and for their total score (out of 100). We hypothesized higher scores in the intervention schools for English (because of the time spent reading and learning new words in English during the IHC lessons), science (based on results of randomised trials of other interventions to teach critical thinking,18–20 and stimulation of interest in science), and average scores (due to expected higher scores in English and science).
We asked teachers to record unexpected adverse events and problems that might pose risks to the children or others, and to report these to the investigators or to the Institutional Review Board at Makerere University College of Health Sciences. Teachers in the intervention arm of the trial were given instructions for recording adverse events and problems in journals that they were asked to keep.15
Statistical analysis
We estimated that we would need a minimum of 55 schools in each arm to detect a difference of 10% in the proportion of children with a passing score.14
For the primary and secondary outcomes, we used mixed models with a random effects term for the clusters and the stratification variables modelled as fixed effects, using generalized logistic regression for dichotomous outcomes and linear regression for continuous outcomes. The statistical analyses were performed with R (R Core Team, Vienna, Austria; version 3.3.2). We converted odds ratios from logistic regression analyses to adjusted differences using the intervention group percentage as the reference. All the children and teachers who completed the test were included in the analyses.
For questions about intended behaviours and self-efficacy, we dichotomised the responses in the analysis and reported the proportions of children for each of the four response options. For comparisons of how frequently participants reported hearing treatment claims, we analysed the data as ordinal data, using mixed ordinal logistic regression and we dichotomised the responses.
User testing of the questions about self-reported behaviours by 40 children who did not participate in the trial suggested that the questions are understood by children in Uganda. In addition, we used the open-ended questions - “Please write down the treatment claim that you last heard”. (What did they say the treatment would change or not change about someone’s health?)" - to ensure that the children understood these questions correctly (Table 3). We coded answers to these questions as ‘correct’ or ‘incorrect’, and excluded from the comparisons in (Table 4), all participants who did not correctly identify the type of treatment (Supplementary file 2- additional table 3), or who did not report a treatment claim. For attendance, we compared rates in the intervention and control groups. For marks we compared mean exam scores (Supplementary file 2-additional table 5), the proportions of children with passing scores (> 35), and the proportions of children with distinction scores (> 70).
To explore the risk of bias due to attrition, which was larger in the control schools than in the intervention schools, we conducted two sensitivity analyses. First, we conducted an analysis using inverse probability weighting. In this, the children in each school were given a weight equal to the inverse of the proportion of children in the school who had completed the test. Second, using the Lee bounds approach,21 we calculated upper and lower bounds for the mean difference in test scores. The bounds are constructed by trimming the group with less attrition at the upper and lower tails of the outcome (test score) distribution, respectively. In this analysis, the sample was trimmed in the intervention schools so that the proportion of children included in the analysis was equal for both groups. We did not adjust for covariates in this analysis.
We explored whether there were differences in the effect of the intervention for children with advanced reading skills (all four literacy questions answered correctly) versus basic reading skills (both basic literacy questions correct and one or two of the advanced literacy questions wrong) versus lacking basic reading skills (one or both basic literacy questions wrong).
Parents of 675 children in either the intervention or control group were recruited to participate in a parallel trial.16 That trial evaluated the effects of a podcast designed to teach the parents of primary school children nine IHC Key Concepts, eight of which were included in the primary school resources. We conducted a second subgroup analysis to explore whether having a parent who listened to the podcast improved the scores of the children and whether there was an interaction between the effect of the podcast and the primary school resources. Because the parents allocated to listen to the podcast did not do so until after the children had completed the tests the first time, we only conducted this analysis for the one-year follow-up study. We used statistical models as described above for this analysis; the main effects of the podcast were also included in these analyses.
Results
All 120 schools that were randomised provided data for the primary outcome measures and were included in the primary analyses. Most of the schools in both groups were urban or semi-urban (Table 5). There were more public schools in the control group (55% versus 50%). For the one-year follow-up, there were fewer teachers who taught science as their main subject. Teachers in Ugandan primary schools frequently move and switch the major subject that they teach due to changes in staffing. Therefore changes in the main subject taught by teachers are not unusual. There were otherwise only minor differences in the characteristics of the participants between the end of the intervention term and the one year follow-up, and between the intervention and control groups.
Six intervention schools had more than one year-five class (with a different teacher for each class). This resulted in nine more teachers receiving training and being included in the intervention schools. No teachers were added in the control schools, since the teachers in the control schools did not receive training. For the one-year follow-up, 92% (78) teachers in the intervention schools and 88% (59) of the teachers in the control schools completed the same test that the children took at the end of the term.
Altogether, 6,787 children completed the one-year follow-up test (Table 5). As was the case with the test taken at the end of the intervention term was delivered, more children completed the follow-up test in the intervention schools (62%) than in the control schools (45%). We think this is because teachers who taught the lessons were more motivated to arrange for the children whom they had taught to take the test. The proportion of girls (55%) and the median age of children (12, 25th to 75th percentile: 10 to 14) in the two groups were the same. Most of the children answered all the questions. The proportion of missing values (unanswered questions) for each question was between 0.25% and 3.38%, and the number of missing values was similar between the intervention and control schools (Supplementary file 2- additional table 4).
Only 64 schools provided data on the secondary outcome of school attendance. Ninety-three schools provided data on examination scores for the intervention term, and 99 for the following term (Supplementary file 2- additional table 5).
Primary outcomes and sensitivity analyses
The average score for children in the intervention schools was 68.7% compared to 53.0% in the control schools (Table 7). The adjusted mean difference (based on the regression analysis) was 16.7% (95% CI 13.9% to 19.5%; p<0.00001) higher in the intervention than in the control group. The distribution of test scores is shown in (Supplementary file 3). In the intervention schools, 80.1% of the children had a passing score (> 13 out of 24 correct answers), compared to 51.5% in the control schools (Table 7). The adjusted difference (based on the odds ratio from the logistic regression analysis) was 39.5% more children who passed (95% CI 29.9% to 47.5%) in the intervention than in the control group. Although the average score and the proportion of children with a passing score in the intervention group were higher after one year than at the end of the intervention term, the differences between the intervention and control schools were smaller, because the scores increased more in the control schools than in the intervention schools between the first and second test.
We conducted two sensitivity analyses to assess the potential risk of bias from attrition - children who did not take the test (Table 8). There was very little difference between the results of analysis using inverse probability weighting and the primary analysis (Supplementary file 2- additional table 6), suggesting that the results are robust. In the second analysis, we calculated Lee bounds for the mean difference in test scores. This resulted in a lower (worst case) and upper (best case) mean difference of 6.4% and 26.6% respectively (95% CI 6.6% to 26.5%). This indicates that even with the worst-case scenario, the average test score in the intervention schools was still 6.4% higher than in the control schools. Moreover, the worst-case scenario, which removed 17% of the children with the highest test scores from the intervention group, is unlikely. This is equivalent to assuming that the children in the control schools who did not take the test would have had scores that corresponded to the top 17% of the children in the intervention schools, had they taken the test (Supplementary file 2- additional table 7). It is more likely that the children who were lost to follow-up and did not take the test would have done worse rather than better compared to the children who did take the test.
Secondary outcomes
In the intervention schools, 28.9% of the children had a score indicating mastery of the 12 key concepts (> 20 out of 24 correct answers) compared to 4.9% of the children in the control schools (Table 7). The adjusted difference was 25.0% more children in the intervention schools who mastered the concepts (95% CI 23.2% to 26.5%). This is a larger difference than there was at the end of the term during which the intervention had been delivered (18.0%). The proportion of children with a score indicating mastery increased from 18.6% to 28.9% in the intervention group between the first and second test, compared to an increase from 0.9% to 4.9% in the control group.
After one year, most teachers in both the intervention and control groups (98.7% and 85.9% respectively) had passing scores (adjusted difference 8.6%, 95% CI 1% to 55.5%) (Table 7). The teachers in the intervention group were much more likely to have a score indicating mastery of the concepts (67.9% versus 21.9%; adjusted difference 46.3%, 95% CI 31.5% to 56.6%). These results are similar to those we found at the end of the intervention term.
For each concept, the proportion of children who answered both questions correctly was higher in the intervention schools than in the control schools, including for the concept that was not covered in the primary school resources (p<0.0001 for all 13 concepts after a Bonferroni correction for multiple comparisons) (Table 9).
Compared with children in the control schools, children in the intervention schools were more likely to respond that they would find out the basis for a claim (adjusted difference 8.1%, 95% CI 3.7% to 12.6%) and to participate in a research study if asked (adjusted difference 7.7%, 95% CI 2.0% to 13.5%) (Supplementary file 2- additional table 8). These findings are similar to those we found one year earlier. However, there was little if any difference in how likely they were to find out if a claim was based on research (adjusted difference 2.6%, 95% CI –1.9% to 7.2%). This contrasts with what we found a year earlier (10.8%, 95% CI 6.3% to 15.1%).
Similar to what we found a year earlier, children in the intervention schools were more likely to consider it easy to assess whether a claim is based on research than children in the control schools (adjusted difference 14.8%, 95% CI 8.9% to 20.5%) (Table 10). They were also more likely to consider it easy to find information about treatments based on research (adjusted difference 7.2%, 95% CI 2.6% to 11.5%) (Table 11), whereas a year earlier we had detected little if any difference (Supplementary file 2-additonal table 9). We detected little if any difference in how easy children thought it was to assess how sure they could be about the results of research, or to assess how relevant research findings are to them. A year earlier, compared to children in the control group, the children in the intervention group were less likely to consider it easy to assess how sure they could be about the results of research.
The children in the intervention schools were more likely to report hearing one or more treatment claims daily or weekly (Table 12) compared to children in the control schools (adjusted difference 7.0%, 95% CI 0.5% to 12.9%) (Supplementary file 2- additional table 10). The children in the intervention schools were less likely to be very sure or not know whether a claim could be trusted (Table 13) (adjusted difference –15%, 95% CI –9.9% to –19.7%) and more likely to assess the trustworthiness of a claim consistently with what they identified as the basis of the claim (adjusted difference 7.6%, 95% CI 3.5% to 11.1%) (Supplementary file 2- additional table 11). However, there were only slight differences in how likely children in the intervention schools were to think about the basis of the last claim that they heard (Table 14) (adjusted difference 4.1%, 95% CI –1.2% to 9.6%) (Supplementary file 2- additional table 12 and additional table 13), and in their assessments of the advantages and disadvantages of the most recent treatment they had used (Table 15) (Supplementary file 2- additional table 14). The difference in attendance or examination scores was also small (Supplementary file 2- additional table 5). As reported previously,14 none of the teachers or research assistants who observed the lessons reported any adverse events.
Subgroup analyses
As was the case at the end of the intervention term, the intervention still had positive effects a year later, regardless of reading skills (Table 16), but with larger effects for children with better reading skills (Supplementary file 2- additional table 15). Compared to the control schools (Table 17), reading skills were better in the intervention schools at the end of the intervention term and after one year (Supplementary file 2- additional table 16). They had improved by about the same amount in both the intervention and control schools after one year. We did not detect an interaction between having a parent who listened to the podcast and the primary school intervention (Table 18) (adjusted difference for the interaction 3.8%, 95% CI –3.9% to 11.4%) (Supplementary file 2- additional table 17).
Discussion
The large effect that the Informed Health Choices intervention had on the ability of primary school children in Uganda to assess claims about treatment effects was sustained after one year. The mean score and the proportions of children with passing and mastery scores increased in the intervention schools (Table 7). However, because the scores in the control schools increased more than the scores in the intervention schools, the differences between the intervention and control schools for the mean score and the proportion of children with a passing score were smaller, albeit still large. On the other hand, the difference in the proportion of children with a mastery score increased.
We considered five possible explanations for these findings, none of which seem likely. First, the apparent differences in the effect estimates between the first and second measurement might have occurred by chance alone. To explore this, we calculated the probability of a difference as large as or larger than that we had observed having occurred by chance (Supplementary file 2- additional table 18). It is highly unlikely that the differences in the effect estimates would have occurred by chance (P>0.00001). Second, the difference might reflect bias resulting from differential loss to follow-up. To explore this, we calculated the effects at the end of the intervention term excluding children who were lost to follow-up (Supplementary file 2- additional table 19). The effect estimates are similar.
A third possible explanation is that there was a learning effect from taking the test the first time, which was greater in the control schools than in the intervention schools. It is possible that the learning effect of taking the test alone would be greater than the added learning effect of taking the test after having been exposed to the IHC lessons. “Testing effects” - gains in learning that occur when students take a practice test - are well documented.22,23 They occur with and without feedback,22 and for higher level thinking (“application” in Bloom’s taxonomy) as well as for recall of basic facts.23 However, most studies investigating testing effects have been conducted over a much shorter time-frame,22 and we are not aware of any studies that have documented a difference in testing effects between students who studied before taking a practice test and others who did not study.
A fourth possible explanation is that children learn to think critically about treatment claims naturally as they grow older or through the existing curriculum, and the control schools were catching up with the intervention schools because of this. However, as documented in our process evaluation, the content of the lessons was new for all of the teachers and not something that they had previously taught. Furthermore, we did not deliver the learning-resources to the control schools until after the follow-up data had been collected. Fifth, it also seems unlikely that the improvement was due to an improvement in reading skills in the control schools, since the change in reading skills was similar in the intervention and control schools.
The effects that we found for the children for each IHC Key Concept, and the effects that we found for the teachers were similar to those we found at the end of the intervention term. Overall, these findings support the conclusion that the effects of the intervention were sustained, even though we are unable to explain why the children’s scores increased more in the control schools than in the intervention schools.
Other findings provide modest support for the conclusion that the children in the intervention schools were more likely to use what they had learned. The children in the intervention schools remained more likely than those in control schools to find out the basis for a treatment claim, more confident in their ability to assess whether a treatment claim is based on research, and more likely to participate in a research study if asked. They also appeared to be somewhat more aware of treatment claims, more sceptical of treatment claims, and more likely to assess the trustworthiness of treatment claims. However, all of these differences were smaller than the difference for the primary outcome measures. Moreover, at the end of the intervention term, children in the intervention schools were more likely than children in the control schools to say they would find out if a treatment claim was based on research, but after one year there was little difference.
The data we were able to collect for attendance and national examinations were incomplete, but based on those data, there was little difference between children in the intervention and control schools (Table 6). This contrasts with findings of studies in the UK, which have found beneficial effects of critical thinking or meta-cognition interventions on academic achievement.18–20 Possible explanations for this include the limitations of the data we were able to collect for these outcomes and differences between the interventions and the contexts in which they were delivered.
The main limitations of our follow-up study are similar to those discussed in our report of effects found immediately after the intervention.14 First, we cannot rule out some degree of bias due to attrition. However, sensitivity analyses suggest that the effect estimates are robust. Second, we used an outcome measure that we developed ourselves. Outcome measures developed by the study authors for use in a study may be more likely to find larger effects than studies using established measures of critical thinking.24 We developed the outcome measure because there was no pre-existing outcome measure suitable for our study.5 Although we have demonstrated the validity and reliability of the outcome measure,6–9 one should be cautious about comparing our results to the effects of other critical thinking interventions. Moreover, we are unaware of any other directly comparable studies.24–29 Other interventions in primary schools have been found to improve critical thinking,24 but these studies have been conducted in high-income countries, few have measured outcomes after one year, and neither the interventions nor the outcome measures are directly comparable.24,27
It remains uncertain how transferable the findings of this study are to other countries. However, pilot testing in Kenya, Norway, and Rwanda suggest that it may be possible to use the IHC primary school resources without substantial modifications. They have already been translated to Kiswahili, Kinyarwanda, Spanish, French, and Farsi. There are plans or expressions of interest to translate them to other languages, including Chinese, German, and Italian. Pilot studies have been completed or planned in several other countries, including Ireland and South Africa. The resources are open access and we have prepared a guide for translating, contextualising, and testing them.30
Conclusions
It is possible to teach young children in a low-income country to think critically about the trustworthiness of claims about the benefits and harms of treatments, and children retain what they have learned for at least one year. In this study we were also able to document modest effects on self-reported behaviours. However, we believe that a one-off intervention is unlikely to have large long-term effects on decision-making, health behaviours, or health. Rather, we view this as the first step in developing a set of interventions for a spiral curriculum.31,32 Using this approach, some of the IHC Key Concepts would be introduced, as we did in this study. Then those concepts would be reinforced in subsequent cycles, and other more complex concepts would be introduced. We believe it is highly desirable to begin teaching the IHC Key Concepts at a young age, and we have shown that this is possible.
List of abbreviations
IHC
Informed Health Choices Project
Declarations
Ethics approval and consent to participate
Ethics approval was obtained from the School of Medicine’s institutional review board at Makerere University College of Health Sciences (reference number 2013–105) and the Uganda National Council for Science and Technology (reference number SS3328) at the beginning of the study and renewal of approval was sought for the follow-up study.
Informed consent for all grade five classes to participate in the trial was obtained from school heads (the head teacher or school director) and grade five teachers. We provided the head teacher of each school with information about the study and obtained written consent from them on behalf of their school to participate in the first trial (at the end of the intervention term) and the second trial (one-year follow up). In addition, we obtained written consent from the primary-five (year five of primary school) teachers identified by the head teachers. Informed consent was not required from the children or their parents. We did not obtain assent from individual primary five children or consent from their parents since the intervention posed minimal risk and no more risk than other teaching materials [33], almost none of which have been evaluated [28,29]. Informed consent by individual children or their parents, in effect, would be meaningless once the decision to participate was taken by the head teacher and the teachers, who have the responsibility and authority to make decisions about lesson plans and the administration of tests [34]. Individual children and their parents had the same right to refuse participation as they do for any other lesson or test in primary schools.
Consent to publish
Not applicable.
Availability of data and materials
The data files for the one-year follow-up are available from the Norwegian Centre for Research Data (http://www.nsd.uib.no/nsd/english/index.html).
Competing interests
All the authors declare that they have no competing interests.
Funding
This trial was funded by the Research Council of Norway, Project number 220603/H10. The funder had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. The principal investigator had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Authors’ contributions
AN and DS are the principal investigators. They drafted the protocol with help from the other investigators and were responsible for the day-to-day management of the trial. NKS and ADO had primary responsibility for overseeing the trial. All the investigators reviewed the manuscript, provided input, and agreed on this version. MO and SR had primary responsibility for developing the primary school resources. AM shared primary responsibility for developing the teachers’ guide. All the investigators other than KYD contributed to the development of the resources and to the protocol. AAD had primary responsibility for developing and validating the outcome measure. AN and DS had primary responsibility for data collection. KYD did the statistical analysis.
The Norwegian Institute of Public Health, recipient of the grant from the Research Council of Norway, is the coordinating centre for the Informed Health Choices project. ADO, SR, AAD and IC are principal members of the coordinating group for the trial and, together with NKS and the principal investigators, acted as the steering committee for the trial. They were responsible for final decisions about the protocol and reporting of the results.
Acknowledgements
We are grateful for support for this research from the Global Health and Vaccination Research (GLOBVAC) programme of the Research Council of Norway, and to the English National Institute for Health Research for supporting Iain Chalmers and the James Lind Initiative. This work was also partially supported by a Career Development Award from the DELTAS Africa Initiative grant # DEL–15–011 to THRiVE–2. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)‘s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust grant # 107742/Z/15/Z and the UK government. The views expressed in this publication are those of the author(s) and not necessarily those of AAS, NEPAD Agency, Wellcome Trust or the UK government. Alun Davies, Lena Nordheim, Peter O. Okebukola, Newton Opiyo, Jonathan Sharples, Helen Wilson, and Charles Shey Wiysonge determined the cut-off scores for passing and mastery. Miriam Grønli was responsible for the textbook colouring and Nora Rosenbaum assisted. Aisha Hashi, Sara Jaber, Rida Shah, and Katie Tveiten helped test prototypes. Michael Mugisha, Anne-Marie Uwitonze, and Jenny Moberg helped with piloting and user testing an earlier version of the learning-resources. We want to thank Dr. Daniel Nkaada at the Ugandan Ministry of Education for technical guidance; Sarah Natunga at the National Curriculum Development Centre in Uganda for reviewing the materials; Martin Mutyaba, Esther Nakyejwe, Margaret Nabatanzi, Hilda Mwebaza, Peter Lukwata, Rita Tukahirwa, David Ssimbwa, Adonia Lwanga, Enock Steven Ddamulira and Solomon Segawa for their help with data management; and all the research assistants who helped with data collection and entry. We would also like to thank the Informed Health Choices advisory group. We are especially grateful to the many teachers and children in Uganda, Kenya, Rwanda, and Norway who helped with the development of the Informed Health Choices primary school resources; and to all the children, teachers, and head teachers at the schools who participated in this trial.
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Tables
Table 1. Comparisons related to self-reported behaviours in the one-year follow-up
Question | Hypothesis and basis for the hypothesis |
How often do you hear treatment claims? | Children in the intervention group will report hearing treatment claims more often because of being more aware of treatment claims and identifying them when they are made. |
[For the last treatment claim that you heard,] did you think about what that treatment claim that you heard was based on? | A larger proportion of children in the intervention group will answer yes because of being more aware that many claims do not have a reliable basis. |
How sure are you that the treatment claim you heard is true or can be trusted? | A smaller proportion of children in the intervention group will answer “very sure” or “I don’t know”, and a larger proportion of children in the intervention group will answer this question consistently with their answer to the preceding question about the basis of the claim (Table 3) because of being better able to assess the trustworthiness of claims and many claims not having a reliable basis. |
How sure are you about the advantages and disadvantages of the [most recent] treatment you used? | A higher proportion of the children in the intervention group will answer “not very sure because I only know about the advantages” and a smaller proportion will answer “very sure”, because information about the disadvantages of treatments is often lacking. However, this difference, if there is one, will likely be small, because children in the intervention group are more likely to consider and seek information about the disadvantages of treatments. |
Who do you think should decide for you whether you should use a treatment or not use a treatment? | A higher proportion of the children in the intervention group will answer that they want to be included (A, C, D, F, or G) because of having learned about how to make informed health choices; and that someone who knows a lot about treatments should be included (E, F, or G), because of being more aware of the importance of assessing the reliability of evidence of effects and the skills that are needed to do this. However, this difference, if there is one, will likely be small, because children in the intervention group are more likely to recognise that expert opinion alone is not a reliable basis for a claim about treatment effects. What happens if the claim that comes in is about negative effects of the treatment? A larger proportion of children in the intervention group will answer, “Not very sure because there was not a good reason behind the claims about the advantages of the treatment”, because they are more likely to identify a claim whose basis was bad. |
Given your thoughts about the basis of the claim, what did you yourself decide to do about the treatment? | A smaller proportion of children in the intervention group versus the control group would choose to use a treatment (in question 29.7) having recognised that the basis of the claim was untrustworthy (in question 29.6) |
Table 2. Ranges of marks and points awarded for each subject
Exam score (out of 100) | Points awarded | Marks |
80-100 | 1 | Distinction 1 |
70-79 | 2 | Distinction 2 |
65-69 | 3 | Credit 3 |
60-64 | 4 | Credit 4 |
55-59 | 5 | Credit 5 |
50-54 | 6 | Credit 6 |
45-49 | 7 | Pass 7 |
35-44 | 8 | Pass 8 |
Below 35 | 9 | Failure |
Table 3. Consistent (correct) answers regarding certainty about treatment claims*
If you heard about a treatment claim, what was it based on? | How sure are you that the treatment claim you heard is true or can be trusted? |
Someone’s personal experience using the treatment | Not very sure because the reason behind the claim was not good |
What an expert said about it | Not very sure because the reason behind the claim was not good |
A research study that compared the treatment with another treatment or no treatment | Not very sure because the reason behind the claim was not good OR Very sure because the reason behind the claim was good |
Something else | Not very sure because the reason behind the claim was not good |
I could not tell what the treatment claim was based on | Not very sure because I don’t know the reason behind the claim |
* Questions 28.5 and 28.6 in Appendix 1
Table 4. Exclusion criteria for self-reported behaviours
Response options for questions 28.2 and 29.3 | Response to questions 28.3 and 29.4 |
28.2 What was the treatment in the claim you last heard about | 28.3 Please write the claim that you last heard |
29.3 What was the treatment for which you or an adult made the decision? | What was the claim about the treatment for which you or an adult made the decision? |
Using a medicine (e.g. taking a tablet or syrup) | Exclude if the claim is not about a medicine |
Getting an operation (e.g. removing a bad tooth) | Exclude if the claim is not about an operation |
Using something to feel better or to heal more quickly (e.g. using a bandage or glasses) | Exclude if the claim is not about equipment |
Something else (Eating food or drinking something to feel better (e.g. herbs or fruit)) | Exclude if the claim is not about eating/drinking something e.g. herbs or fruit |
Avoiding doing something to feel better (e.g. not drinking milk) | Exclude if the claim is not about avoiding something |
Something else | Exclude if the claim is not about a treatment (“anything done to care for yourself, so you stay well or, if you are sick or injured, so you get better and not worse”) |
Table 5. Characteristics of the participants
One-year follow-up | End of intervention term | ||||
Control schools | Intervention schools | Control schools | Intervention schools | ||
Schools (selected from the Central region of Uganda) | N=60 | N=60 | N=60 | N=60 | |
Location | Rural | 8 (13%) | 6 (10%) | 8 (13%) | 6 (10%) |
Semi-urban | 15 (25%) | 14 (23%) | 15 (25%) | 14 (23%) | |
Urban | 37 (62%) | 40 (67%) | 37 (62%) | 40 (67%) | |
Ownership | Public | 33 (55%) | 30 (50%) | 33 (55%) | 30 (50%) |
Private | 27 (45%) | 30 (50%) | 27 (45%) | 30 (50%) | |
Teachers† | N=74 | N=85 | N=74 | N=85 | |
Completed tests | 59 (80%) | 78 (92%) | 67 (91%) | 85 (100%) | |
Education | Certificate | 27 (46%) | 34 (44%) | 30 (45%) | 39 (46%) |
Diploma | 31 (53%) | 35 (45%) | 33 (49%) | 35 (41%) | |
University degree | 1 (2%) | 9 (12%) | 3 (4%) | 10 (12%) | |
Main subject taught | Science | 32 (54%) | 48 (56%) | 49 (73%) | 68 (80%) |
Sex | Women | 24 (41%) | 32 (45%) | 29 (43%) | 34 (40%) |
Children (enrolled in year-5 at the start of the term) | N=6256 | N=6383 | N=6256 | N=6383 | |
Completed tests* | 2844 (45%) | 3943 (62%) | 4430 (71%) | 5753 (90%) | |
Completed tests per school‡ | Median (25th to 75th percentile) (Range) | 40 (24 to 57) (4 to 300) | 49 (30 to 77) (10 to 270) | 60 (40 to 95) (12 to 150) | 61 (43 to 89) (18 to 176) |
Sex | Girls | 1558 (55%) | 2164 (55%) | 2457 (55%) | 3154 (55%) |
Age | Median (25th to 75th percentile) (Range) | 12 (10 to 14) (9 to 18) | 12 (10 to 14) (8 to 19) | 11 (10 to 12) (8 to 20) | 11 (10 to 12) (8 to 18) |
* Questions about the characteristics of the teachers and children were included in the test completed at the end of the school term and one year later.
† The numbers of teachers who completed the test at the end of the first term. Head teachers were initially asked to identify teacher who taught science to children in the fifth year of primary school. However, some schools had more than one year-5 class. Six intervention schools with more than one year-5 class (with a different teacher for each class) requested that nine additional teachers be included altogether.
‡ The average number of year-5 children per school at the start of the term was 84 in both groups.
Table 6. Attendance and national examinations
SD = standard deviation
Table 7. Main results - test scores - one-year follow-up
Control schools | Intervention schools | Adjusted difference* | Odds ratio* | ICC | |
Primary outcome | |||||
One-year follow-up Mean score, % |
Mean score: 53.0% (SD 16.8%) |
Mean score: 68.7% (SD 18.2%) |
Mean difference: 16.7% (95% CI 13.9% to 19.5%) P <0.00001 |
0.18 | |
End of intervention term Mean score, % |
Mean score: 43.1% (SD 15.2%) |
Mean score: 62.4% (SD 18.8%) |
Mean difference: 20.0% (95% CI 17.3% to 22.7%) |
0.18 | |
One-year follow-up Passing score (> 13 out of 24 correct answers) |
51.5 % of children (N=1464/2844) |
80.1 % of children (N=3160/3943) |
39.5% more children (95% CI 29.9% to 47.5%) |
5.88 (95% CI 4.00 to 8.33) P <0.00001 |
0.20 |
End of intervention term Passing score (> 13 out of 24 correct answers) |
26.8 % of children (N=1186/4430) |
69.0 % of children (N=3967/5753) |
49.8% more children (95% CI 43.8% to 54.6%) |
9.34 (95% CI 6.62 to 13.18) |
0.19 |
Secondary outcomes | |||||
One-year follow-up Mastery score (> 20 out of 24 correct answers) |
4.9% of children (N=139/2844) |
28.9% of children (N=1138/3943) |
Mean difference: 25.0% (23.2%-26.5%) |
10.00 (95% CI 6.67 to 16.67) P <0.00001 |
0.19 |
End of intervention term Mastery score (> 20 out of 24 correct answers) |
0.9% of children (N=38/4430) |
18.6% of children (N=1070/5753) |
18.0% more children (95% CI 17.5% to 18.2%) |
35.33 (95% CI 20.58 to 60.67) |
0.21 |
Teachers’ scores | |||||
One-year follow-up Mean score, % |
Mean score: 68.5% (SD 14.9%) |
Mean score: 86.2% (SD 10.2%) |
Mean difference: 17.5% (13.2% to 21.8%) P <0.00001 | ||
End of intervention term Mean score, % |
Mean score: 66.7% (SD 14.3%) |
Mean score: 84.6% (SD 17.1%) |
Mean difference: 18.3% (95% CI 12.9% to 23.3%) | ||
One-year follow-up Passing score (> 13 out of 24 correct answers) |
85.9% of teachers (N=50/59) |
98.7% of teachers (N=77/78) |
9.4% more teachers (1.3% to 52.0%) |
9.12† (95% CI 2.01 to 86.7) P=0.003 | |
End of intervention term Passing score (> 13 out of 24 correct answers) |
86.6% of teachers (N=58/67) |
97.6% of teachers (N=83/85) |
11.3% more teachers (95% CI 4.0% to 13.0%) |
7.24 (95% CI 1.49 to 35.26) | |
One-year follow-up Mastery score (> 20 out of 24 correct answers) |
22.0% of teachers (N=13/59) |
67.9% of teachers (N=53/78) |
46.5% more teachers (28.1% to 61.3%) |
7.70 (95% CI 3.56 to 17.70) P <0.00001 | |
End of intervention term Mastery score (> 20 out of 24 correct answers) |
14.9% of teachers (N=10/67) |
71.8% of teachers (N=61/85) |
56.7% more teachers (95% CI 37.3% to 70.4%) |
14.38 (95% CI 6.24 to 33.14) |
* The adjusted difference is based on mixed models with a random effects term for the clusters (for the children only) and the stratification variables modelled as fixed effects, using logistic regression for dichotomous outcomes and linear regression for continuous outcomes. The odds ratios from the logistic regressions have been converted to differences based on the intervention school proportions and the odds ratios calculated using the intervention schools as the reference (the inverse of the odds ratios shown here).
† Penalized-maximum likelihood logistic regression (R package “logistf”) was used for this analysis because of rare events (only one teacher in the intervention group did not have a passing score).
Table 8. Sensitivity analyses - one-year follow-up
Adjusted difference* | Odds ratio | |
Mean score | ||
Primary analysis | Mean difference: 16.7% (95% CI 13.9% to 19.5%) P <0.00001 | |
Weighted analysis | Mean difference: 16.7% (95% CI 13.9% to 19.5%) | |
Lee bounds | 6.4% to 26.6% (95% CI 6.6% to 26.5%) | |
Passing score (> 13 out of 24 correct answers) | ||
Primary analysis | 39.5% (95% CI 29.9%-47.5%) | 5.88 (95% CI 4.00 to 8.33) P<0.0001 |
Weighted analysis | 40.9% (95% CI 31.0% to 49.4%) | 6.25 (95% CI 4.17 to 9.09) P<0.0001 |
* The adjusted difference is based on mixed models with a random effects term for the clusters and the stratification variables modelled as fixed effects, using logistic regression for dichotomous outcomes and linear regression for continuous outcomes. The odds ratios from the logistic regressions for passing scores have been converted to differences based on the intervention school proportions and the odds ratios calculated using the intervention schools as the reference (the inverse of the odds ratios shown here).
Table 9. Results for each concept for children - one-year follow-up
No | Concept | Control schools % correct* N schools = 60 N children = 2844 | Intervention schools % correct* N schools = 60 N children = 3943 | Adjusted difference† (95% CI) | ICC‡ | Odds Ratio (95% CI) |
Claims | ||||||
1.1 | Treatments may be harmful | 40.5% (n=1152) | 64.6% (n=2547) | 29.2% (22.4% - 35.0%) | 0.120 | 3.33 (2.50 - 4.35) P<0.00001 |
1.2 | Personal experiences or anecdotes (stories) are an unreliable basis for assessing the effects of most treatments | 26.5% (n=753) | 52.0% (n=2052) | 30.0% (24.5% - 34.2%) | 0.119 | 3.85 (2.86 - 5.00) P<0.00001 |
1.3 | A treatment outcome may be associated with a treatment, but not caused by the treatment§ | 27.3% (n=776) | 36.4% (n=1436) | 11.2% (6.4% – 15.2%) | 0.087 | 1.69 (1.33 - 2.13) P=0.00002 |
1.4 | Widely used treatments or treatments that have been used for a long time are not necessarily beneficial or safe | 26,3% (n=748) | 54,4% (n=2144) | 30.0% (23.8% - 35.1%) | 0,157 | 3.70 (2.70 - 5.00) P<0.00001 |
1.5 | New, brand-named, or more expensive treatments may not be better than available alternatives | 48.9% (n=1392) | 73.6% (n=2901) | 28.1% (22.2% -34.5%) | 0.088 | 3.33 (2.63 - 4.35) P<0.00001 |
1.6 | Opinions of experts or authorities do not alone provide a reliable basis for deciding on the benefits and harms of treatments | 43.2% (n=1230) | 67.6% (n=2664) | 26.8% (20.3% - 33.3%) | 0.113 | 3.03 (2.33 - 4.00) P<0.00001 |
1.7 | Conflicting interests may result in misleading claims about the effects of treatments | 37.0% (n=1051) | 47.2% (n=1861) | 10.8% (5.5% - 15.9%) | 0.077 | 1.56 (1.25 - 1.96) 0.00009 |
Comparisons | ||||||
2.1 | Evaluating the effects of treatments requires appropriate comparisons | 10.3% (n=294) | 32.0% (n=1263) | 24.2% (21.1% - 26.2%) | 0.148 | 5.56 (3.85 - 7.69) P<0.00001 |
2.2 | A part from the treatments being compared, the comparison groups need to be similar (i.e. 'like needs to be compared with like') | 12.1% (n=344) | 29.3% (n=1155) | 16.6% (14.2% - 18.9%) | 0.063 | 2.86 (2.33 - 3.57) P<0.00001 |
2.5 | If possible, people should not know which of the treatments being compared they are receiving | 23.3 % (n=664) | 36.2 % (n=1428) | 15.1% (11.4% - 18.8%) | 0.070 | 2.13 (1.72 - 2.70) P<0.00001 |
3.1 | Small studies in which few outcome events occur are usually not informative and the results may be misleading | 32.6 % (n=928) | 50.3 % (n=1984) | 20.5% (15.8% - 25.3%) | 0.082 | 2.38 (1.92 - 3.03) P<0.00001 |
4.1 | The results of single comparisons of treatments can be misleading | 29.1% (n=827) | 44.8 % (n=1766) | 17.6% (12.4% - 22.2%) | 0.096 | 2.17 (1.69 - 2.78) P<0.00001 |
Choices | ||||||
5.1 | Treatments usually have beneficial and harmful effects | 35.2 % (n=1000) | 50.8 % (n=2004) | 16.8% (11.4% - 22.1%) | 0.090 | 2.00 (1.59 - 2.56) P<0.00001 |
* There were two multiple-choice questions for each concept. The proportions are for the percentage of children who answered both questions correctly.
† The adjusted difference is based on mixed models with a random effects term for the clusters and the stratification variables modelled as fixed effects, using logistic regression. The odds ratios from the logistic regressions have been converted to differences based on the intervention school proportions and the inverse of the odds ratios shown here.
‡ Intraclass correlation coefficient
§ This concept was not included in the learning resources or counted in the average, pass, or mastery scores.
Table 10. Intended behaviours - one-year follow-up
Think about an illness that you might get. Imagine someone claiming (saying) that a particular treatment might help you get better.
How likely are you to find out what the claim was based on (for example by asking the person making the claim)? | How likely are you to find out if the claim was based on a research study comparing the treatment to no treatment (a fair comparison)? | How likely are you to say “yes” if you are asked to participate in a research study comparing two treatments for your illness (a fair comparison)? | ||||
Control schools N=2844 | Intervention schools N=3943 | Control schools N=2844 | Intervention schools N=3943 | Control schools N= 2844 | Intervention schools N= 3943 | |
Missing | 69 (2.4%) | 67 (1.7%) | 87 (3.1%) | 70 (1.8%) | 36 (1.3%) | 44 (1.1%) |
Very unlikely | 217 (7.6%) | 376 (9.5%) | 301 (10.6%) | 467 (11.8%) | 245 (8.6%) | 277 (7.0%) |
Unlikely | 289 (10.2%) | 376 (9.5%) | 424 (14.9%) | 569 (14.4%) | 329 (11.6%) | 429 (10.9%) |
Likely | 975 (34.3%) | 1510 (38.3%) | 747 (26.3%) | 997 (25.3%) | 1045 (36.7%) | 1577 (40.0%) |
Very likely | 678 (23.8%) | 1082 (27.4%) | 705 (24.8%) | 1164 (29.5%) | 719 (25.3%) | 1155 (29.3%) |
I don’t know | 616 (21.7%) | 532 (13.5%) | 580 (20.4%) | 676 (17.1%) | 470 (16.5%) | 461 (11.7%) |
Likely or very likely* | 1653 (58.1%) | 2592 (65.7%) | 1452 (51.1%) | 2161 (54.8%) | 1764 (62.0%) | 2732 (69.3%) |
Odds ratio (95% CI)† | 1.41 (1.18 - 1.69) P=0.00020 | 1.11 (0.93 - 1.33 ) P=0.269 | 1.41 (1.10 - 1.79) P=0.00629 | |||
Adjusted Difference† | 8.1% (3.7%-12.6%) | 2.6% (-1.9% - 7.2%) | 7.7% (2.0% - 13.5%) | |||
Likely or very likely | 2440 (55.1%) | 3731 (64.9%) | 1967 (44.4%) | 3114 (54.1%) | 2163 (48.8%) | 3201 (55.6%) |
Odds ratio | 1.56 (95% CI 1.29 to 1.88) | 1.54 (95% CI 1.29 to 1.84) | 1.37 (95% CI 1.16 to 1.62) | |||
Adjusted Difference | 10.6% (95% CI 6.2% to 14.7%) | 10.8% (95% CI 6.3% to 15.1%) | 7.8% (95% CI 3.7% to 11.9%) |
* Missing values and don’t know are pooled with unlikely and very unlikely.
† The difference is an adjusted difference, based on mixed models with a random effects term for the clusters and the stratification variables modelled as fixed effects, using logistic regression. The odds ratios from the logistic regressions have been converted to differences using the intervention schools as the reference and the inverse of the odds ratios shown here.
‡ Results based on responses at the end of the term when the intervention was delivered.
Table 11. Self-efficacy
How difficult or easy would you find each of these actions to be?
Assessing whether a claim about a treatment is based on a research study comparing treatments (a fair comparison) | Assessing where I can find information about treatments that is based on research studies comparing treatments (fair comparisons) | Assessing how sure I can be about the results of a research study comparing treatments (the trustworthiness of the results) | Assessing if the results of a research study comparing treatments are likely to be relevant to me | |||||
Control schools N=2844 | Intervention schools N=3943 | Control schools N=2844 | Intervention schools N=3943 | Control schools N=2844 | Intervention schools N=3943 | Control schools N=2844 | Intervention schools N=3943 | |
Missing | 71 (2.5%) | 55 (1.4%) | 73 (2.6%) | 71 (1.8%) | 82 (2.9%) | 84 (2.1%) | 72 (2.5%) | 86 (2.2%) |
Very difficult | 357 (12.6%) | 455 (11.5%) | 338 (11.9%) | 431 (10.9%) | 488 (17.2%) | 581 (14.7%) | 436 (15.3%) | 568 (14.4%) |
Difficult | 779 (27.4%) | 865 (21.9%) | 634 (22.3%) | 876 (22.2%) | 653 (23.0%) | 1007 (25.5%) | 513 (18.0%) | 727 (18.4%) |
Easy | 837 (29.4%) | 1517 (38.5%) | 899 (31.6%) | 1348 (34.2%) | 640 (22.5%) | 897 (22.7%) | 694 (24.4%) | 1027 (26.0%) |
Very easy | 334 (11.7%) | 623 (15.8%) | 525 (18.5%) | 856 (21.7%) | 454 (16.0%) | 712 (18.1%) | 562 (19.8%) | 779 (19.8%) |
I don’t know | 466 (16.4%) | 428 (10.9%) | 375 (13.2%) | 361 (9.2%) | 527 (18.5%) | 662 (16.8%) | 567 (19.9%) | 756 (19.2%) |
Easy or very easy* | 1171 (41.2%) | 2140 (54.3%) | 1424 (50.1%) | 2204 (55.9%) | 1094 (38.5%) | 1609 (40.8%) | 1256 (44.2%) | 1806 (45.8%) |
Odds ratio (95% CI)† | 1.82 (1.43 - 2.33 ) P<0.00001 | 1.33 (1.11 - 1.59) P=0.00171 | 1.10 (0.94 - 1.30) P=0.233 | 1.10 (0.93 - 1.28) P=0.279 | ||||
Adjusted difference† | 14.8% (8.9% - 20.5%) | 7.2% (2.6% – 11.5%) | 2.3% (-1.4% - 6.1%) | 2.3% (-1.9% - 6.1%) | ||||
End of intervention term‡ | ||||||||
Easy or very easy | 1886 (42.6%) | 3244 (56.4%) | 3069 (53.3%) | 2238 (50.5%) | 1777 (40.1%) | 2112 (36.7%) | 2002 (45.2%) | 2727 (47.4%) |
Odds ratio | 1.83 (95% CI 1.55 to 2.16) | 1.13 (95% CI 0.96 to 1.33) | 0.84 (95% CI 0.73 to 0.96) | 1.08 (95% CI 0.93 to 1.25) | ||||
Adjusted difference | 15.0% (95% CI 10.9% to 19.0%) | 3.0% (95% CI -1.0% to 7.0%) | -4.1% (95% CI -1.0% to -7.3%) | 1.9% (95% CI -1.8% to 5.6%) |
* Missing values and don’t know are pooled with difficult and very difficult.
† The difference is an adjusted difference, based on mixed models with a random effects term for the clusters and the stratification variables modelled as fixed effects, using logistic regression. The odds ratios from the logistic regressions have been converted to differences using the intervention schools as the reference and the inverse of the odds ratios shown here.
‡ Results based on responses at the end of the term when the intervention was delivered.
Table 12. Self-reported behaviour - awareness of treatment claims
How often do you hear treatment claims?
Control schools N=2844 | Intervention schools N=3943 | |
One or more most days | 572 (20.1%) | 1000 (25.4%) |
One or more most weeks | 374 (13.2%) | 599 (15.2%) |
One or more most months | 497 (17.5%) | 715 (18.1%) |
Almost never | 653 (23.0%) | 788 (20.0%) |
I don’t know | 717 (25.2%) | 810 (20.5%) |
Missing | 31 (1.1%) | 31 (0.8%) |
One or more most days or most weeks | 946 (33.8%) | 1599 (40.6%) |
Odds ratio* | 1.35 (95% CI 1.02 - 1.79) P = 0.0356 | |
Adjusted difference† | 7.0% (95% CI 0.5% to 12.9%) |
*The odds ratio for the dichotomised data is shown in the table. The odds ratio from the mixed ordinal logistic regression was 1.30 (95% CI 1.01 to 1.67, P = 0.0431).
† The difference is an adjusted difference, based on a mixed model with a random effects term for the clusters and the stratification variables modelled as fixed effects, using logistic regression. The odds ratio from the logistic regression has been converted to a difference using the intervention schools as the reference and the inverse of the odds ratios shown here.
Table 13. Self-reported behaviour - assessment of trustworthiness of treatment claims
How sure are you that the treatment claim you heard is true or can be trusted?
Control schools N=2844 | Intervention schools N=3943 | |
Missing | 49 (1.7%) | 60 (1.5%) |
Not very sure because I don’t know the reason behind the claim | 665 (23.4%) | 1039 (26.4%) |
Not very sure because the reason behind the claim was not good | 543 (19.1%) | 1087 (27.6%) |
Very sure because the reason behind the claim was good | 704 (24.8%) | 790 (20.0%) |
I don’t know because I don’t know how to decide whether it is true or not | 883 (31.0%) | 967 (24.5%) |
Very sure or I don’t know | 1587 (55.8%) | 1757 (44.6%) |
0.55 (95% CI 0.45 - 0.67) P<0.0001 | ||
Adjusted difference* | -15.0% (95% CI -9.9% to -19.7%) | |
Odds ratio (consistent with what they identified as the basis for the claim)† | 1.45 (95% CI 1.18 - 1.75) P=0.000549 | |
Adjusted difference* | 7.6% (95% CI 3.5% - 11.1%) |
* The differences are adjusted differences, based on mixed models with a random effects term for the clusters and the stratification variables modelled as fixed effects, using logistic regression. The odds ratio from the logistic regression has been converted to a difference using the intervention schools as the reference and the inverse of the odds ratios shown here.
† See Table 3.
Table 14. Self-reported behaviour - assessment of the basis of treatment claims
For the last treatment claim that you heard, did you think about what that treatment claim that you heard was based on?
Control schools N=2844 | Intervention schools N=3943 | |
Missing | 50 (1.8%) | 57 (1.4%) |
No | 512 (18.0%) | 845 (21.4%) |
Yes | 1387 (48.8%) | 2116 (53.7%) |
I don’t remember | 895 (31.5%) | 925 (23.5%) |
Odds ratio (yes versus other) | 1.18 (95% CI 0.95 - 1.47) P=0.130 | |
Adjusted difference* | 4.1% (95% CI -1.2% - 9.6%) |
* The difference is an adjusted difference, based on a mixed model with a random effects term for the clusters and the stratification variables modelled as fixed effects, using logistic regression. The odds ratio from the logistic regression has been converted to a difference using the intervention schools as the reference and the inverse of the odds ratios shown here.
Table 15. Self-reported behaviour - assessment of advantages and disadvantages of treatments
How sure are you about the advantages and disadvantages of the [most recent] treatment you used?
Control schools N=2844 | Intervention schools N=3943 | |
A) Not very sure because I don’t know the reasons behind the claims about the good and bad things that treatment makes happen | 531 (18.7%) | 851 (21.6%) |
B) Not very sure because there was not a good reason behind the claims about the advantages of the treatment | 355 (12.5%) | 549 (13.9%) |
C) Not very sure because I only know about the advantages of the treatment. I also need to know about the disadvantages | 765 (26.9%) | 992 (25.2%) |
D) Very sure because there is a good reason behind the claims about the advantages and disadvantages of the treatment | 652 (22.9%) | 929 (23.6%) |
E) I did not use any treatment | 498 (17.5%) | 590 (15.0%) |
Missing | 43 (1.5%) | 32 (0.8%) |
Odds ratio (C versus any other response) | 1.05 (95% CI 0.86 - 1.30) P=0.62 | |
Adjusted difference answer C vs else | -0.9% (95% CI -5.3% - 2.7%) | |
Odds ratio (D versus any other response) | 1.03 (95% CI 0.85 - 1.23) P=0.79 | |
Adjusted difference answer D vs else | -0.5% (95% CI -3.9% - 2.8%) |
Table 16. Subgroup analysis - reading skills
Control schools | Intervention schools | Adjusted difference† | Odds ratio | ICC | |
Mean score, % | |||||
N children = 893 | N children = 882 | ||||
Lacking basic reading skills (N=1775) | Mean score: 47.2% (SD 16.4%) | Mean score: 57.1% (SD 18.1%) | Mean difference: 11.2% (95% CI 8.2% to 14.2%) |
0.146 | |
N children = 1093 | N children = 1579 | ||||
Basic reading skills (N=2672) | Mean score: 55.2% (SD 16.9%) | Mean score: 67.9% (SD 16.8%) | Mean difference: 14.8% (95% CI 12.3% to 17.3%) |
0.162 | |
N children = 858 | N children = 1482 | ||||
Advanced reading skills (N=2340) | Mean score: 56.3% (SD 15.6%) | Mean score: 76.5% (SD 15.5%) | Mean difference: 19.4% (95% CI 16.9% to 21.9%) |
0.117 | |
Passing score (> 13 out of 24 correct answers) | |||||
N children = 893 | N children = 882 | ||||
Lacking basic reading skills (N=1775) | 36.6% of children N=327 | 59.3% of children N=523 | 28.9% more children (95% CI 20.8% to 36.7%) | 0.30 (95% CI 0.20 to 0.43) | 0.144 |
N children = 1093 | N children = 1579 | ||||
Basic reading skills (N=2672) | 57.0% of children N=623 | 81.2% of children N= 1282 | 33.6% more children (95% CI 24.0% to 41.9%) | 0.21 (95% CI 0.15 to 0.31) | 0.150 |
N children = 858 | N children = 1482 | ||||
Advanced reading skills (N=2340) | 60.0% of children N=514 | 91.4% of children N=1355 | 33.4% more children (95% CI 25.7% to 42.5%) | 0.13 (95% CI 0.09 to 0.18 ) | 0.098 |
Mastery score (> 20 out of 24 correct answers) | |||||
N children = 893 | N children = 882 | 0.22 | |||
Lacking basic reading skills (N=1775) | 3.0 % of children N=27 | 10,1 % of children N=89 | 7.7% more children (95% CI 5.6% to 8.8%) | (95% CI 0.12 to 0.42) | 0.220 |
N children = 1093 | N children = 1579 | 0.15 | |||
Basic reading skills (n=2672) | 6.5% of children N=71 | 24.1% of children N=380 | 19.6% more children (95% CI 17.0% to 21.3%) | (95% CI 0.09 to 0.24) | 0.192 |
N children = 858 | N children = 1482 | 0.06 | |||
Advanced reading skills (n=2340) | 4.8% of children N=41 | 45.1% of children N=669 | 40.4% more children (95% CI 38.2% to 41.9%) | (95% CI 0.04 to 0.09) | 0.139 |
* Because reading skills were measured after the intervention, we have not reported a test of interaction here (see Appendix 3).
† The adjusted difference is based on mixed models with a random effects term for the clusters and the stratification variables modelled as fixed effects, using logistic regression for dichotomous outcomes and linear regression for continuous outcomes. The odds ratios from the logistic regressions for passing scores and mastery scores have been converted to differences using the intervention school proportions and the inverse of the odds ratios shown here.
Table 17. Differences in reading skills
Reading skills | Immediately after the intervention* | One-year follow-up* | Change from first to second test* | ||||||
Control schools N children 4412 n (%) | Intervention schools N children 5711 n (%) | Diff | Control schools N children 2844 n (%) | Intervention schools N children 3943 n (%) | Diff | Control schools | Intervention schools | Diff | |
Lacking basic reading skills | 2139 (48.5%) | 2224 (38.9%) | -9.5% | 893 (31.4%) | 882 (22.4%) | -9.0% | -17.1% | -16.6% | 0.5% |
Basic reading skills | 1507 (34.2%) | 2155 37.7% | 3.6% | 1093 (38.4%) | 1579 (40.0%) | 1.6% | 4.3% | 2.3% | -2.0% |
Advanced reading skills | 766 (17.4%) | 1332 23.3% | 6.0% | 858 (30.2%) | 1482 (37.6%) | 7.4% | 12.8% | 14.3% | 1.5% |
* Reading skills as measured by first four questions in the test administered at the end of the term when the intervention was delivered and the same test one year later. The differences (Diff) are shown between the intervention and control schools for each time the test was administered and the change from the first to the second time.
Table 18. Subgroup analysis - parent who listened to the podcast
Control schools | Intervention schools | Adjusted effect of the interaction* | |
N children = 69 | N children = 98 | ||
Parent in control group (N=167) | Mean score: 55.1% (SD 16.4%) | Mean score: 64.5% (SD 20.2%) | |
Mean difference: 3.8% (95% CI -3.9% to 11.4%) P=0.3443 | |||
N children = 64 | N children = 104 | ||
Parent in podcast group (N=168) | Mean score: 53.6% (SD 15.9%) | Mean score: 66.3% (SD 18.6%) |
*Adjusted for location, ownership and random effect of clustering, ICC=0.185