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Nutrients 2017, 9(5), 474;

A Review of Recruitment, Adherence and Drop-Out Rates in Omega-3 Polyunsaturated Fatty Acid Supplementation Trials in Children and Adolescents
Welten Institute, Research Centre for Learning, Teaching, and Technology, Open University of The Netherlands, 6419 AT Heerlen, The Netherlands
School of Medicine, University of Wollongong, Wollongong, NSW 2522, Australia
NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, 6200 MD Maastricht, The Netherlands
Author to whom correspondence should be addressed.
Received: 30 January 2017 / Accepted: 2 May 2017 / Published: 10 May 2017


Introduction: The influence of n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFA) supplementation on health outcomes has been studied extensively with randomized controlled trials (RCT). In many research fields, difficulties with recruitment, adherence and high drop-out rates have been reported. However, what is unknown is how common these problems are in n-3 LCPUFA supplementation studies in children and adolescents. Therefore, this paper will review n-3 LCPUFA supplementation studies in children and adolescents with regard to recruitment, adherence and drop-out rates. Methods: The Web of Science, PubMed and Ovid databases were searched for papers reporting on RCT supplementing children and adolescents (2–18 years) with a form of n-3 LCPUFA (or placebo) for at least four weeks. As a proxy for abiding to CONSORT guidelines, we noted whether manuscripts provided a flow-chart and provided dates defining the period of recruitment and follow-up. Results: Ninety manuscripts (reporting on 75 studies) met the inclusion criteria. The majority of the studies did not abide by the CONSORT guidelines: 55% did not provide a flow-chart, while 70% did not provide dates. The majority of studies provided minimal details about the recruitment process. Only 25 of the 75 studies reported an adherence rate which was on average 85%. Sixty-five of the 75 studies included drop-out rates which were on average 17%. Conclusion: Less than half of the included studies abided by the CONSORT guidelines (45% included a flow chart, while 30% reported dates). Problems with recruitment and drop-out seem to be common in n-3 LCPUFA supplementation trials in children and adolescents. However, reporting about recruitment, adherence and dropout rates was very heterogeneous and minimal in the included studies. Some techniques to improve recruitment, adherence and dropout rates were identified from the literature, however these techniques may need to be tailored to n-3 LCPUFA supplementation studies in children and adolescents.
recruitment; adherence; drop-out rates; omega-3 fatty acids; children; adolescents

1. Introduction

Fatty acids, and especially the omega-3 long-chain polyunsaturated fatty acids (n-3 LCPUFA), are being researched extensively for a wide array of health outcomes varying from, but not exclusive to, cardiovascular diseases, depression and cognition [1,2,3]. As in every health related field, randomized controlled supplementation trials are the gold standard to demonstrate efficacy of n-3 LCPUFA [4]. For these trials, voluntary participants are needed, however recruitment of participants can be challenging, especially when it involves research in children and adolescents (<18 years) [5]. It has been reported that less than 31% of British studies funded by two funding bodies between 1994 and 2002 achieved their original recruitment target number [6]. Similarly, others have reported that up to 60% of the randomized controlled trials (RCT) fail to meet their participant target or need an extension [7] and this percentage might be even higher in paediatric and adolescent studies [8,9]. However, even after the recruitment phase, difficulties with conducting research do not end, because drop-out and non-adherence are also common. Drop-out in RCT is normal and attrition rates can vary enormously from 0 up to 65% [10,11,12]. Compliance and adherence are often used interchangeably, but are not the exactly same. Compliance is the extent to which the behaviour of a person coincides with the advice given by a doctor or researcher. The term compliance has received criticism because of its paternalistic connotation [13] and because it implies patient passivity [14]. As a more neutral term, adherence has been suggested, which presumes that the person agrees with the advice given by a doctor or researcher [14]. We choose to use the term adherence in the current manuscript. Adherence issues, are common, with non-adherence ranging anywhere from 3.5 to 80% [15,16]. One must also be aware that there is no one single definition of adherence. This means that somebody who is considered non-adherent in one study, might be considered adherent in another (e.g., one study defined a participant as non-adherent when the participant took less than 75% of the prescribed medicine or supplements, while another used a cut-off level of <80%). As low recruitment rates, high drop-out and high non-adherence are common and have serious consequences [6,17,18], it is important to study factors which possibly affect recruitment, drop-out, and adherence rates.
In 2013, we started a one-year long double blind randomized n-3 LCPUFA supplementation trial in healthy Dutch adolescents called Food2Learn [19]. We experienced difficulties in the recruitment, drop-out and adherence of the study participants. Furthermore, many other n3- LCPUFA supplementation studies have had the same difficulties (personal communication). However, a review of recruitment, adherence and drop-out rates in nutrition interventions and in specific n-3 LCPUFA supplementation studies in children and adolescents does not, to our knowledge, exist. Therefore, the aim is to execute a thorough review to summarize n-3 LCPUFA supplementation studies in children (2–12 years) and adolescents (12–18 years) with regard to recruitment effort, drop-out and adherence rates.

2. Materials and Methods

The Web of Science, PubMed and Ovid databases were searched up to 2 March 2017. We searched for human clinical trials including children aged between 2 and 18 years. We used the search terms: “Omega-3”, “DHA”, “EPA”, “LCPUFA” and “PUFA” in combination with “RCT”, “randomized controlled trial”, “supplementation”, “trial” or “fish oil” and “child*)“, “adolescent”, “school”, “preschool” or “toddler”. Furthermore, a myriad of reviews were checked for additional studies [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40] and reference lists of all articles were hand checked for additional references. Moreover, a search of the Cochrane library was also conducted to identify reviews regarding n-3 LCPUFA supplementation. The studies included in the Cochrane reviews were checked for inclusion in the current study [41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56]. Lastly, for all included articles, the “cited by” option of Web of Science was checked (this option gives all articles that cite that specific article).
Studies were eligible for inclusion if they met the following criteria: (1) participants were aged between 2 and 18 years; (2) the study was a randomized placebo controlled n-3 LCPUFA supplementation trial; (3) the trial had at least 10 participants per treatment arm; (4) supplementation duration was at least 4 weeks; and (5) studies were published in English.
All papers were scanned by the first author, and the following information was extracted and entered in a database:
Participants’ characteristics: Age range of participants, percentage of girls, healthy participants or those with a diagnosed disease, and country in which the study was executed;
Study characteristics: Number of participants, number of measurement moments (i.e., how often did participants have to come to the research facility/how often did they have to fill out questionnaires), number of measurements, treatment condition, placebo condition, form of supplementation, if capsules were used then how many, if supplementation was taken under supervision, if supplement was taken in multiple dosages or once a day, whether an incentive was provided, duration of the study, manner in which adherence was assessed, adherence rate, whether fatty acids were determined in blood, and percentage of people who quit the treatment (hereafter called drop-out); and
Recruitment characteristics: Invited/responded or screened, started, finished as well as method of recruitment, recruitment setting, and study period.
The recruitment characteristics were defined as follows:
  • Invited: The total number of potential participants invited to participate;
  • Responded: The total number of potential participants who responded to the invitation or the number of participants that were screened for participation in the study; and
  • Started: The number of participants who were assessed as eligible and began supplementation.
Furthermore, efficiency percentages were calculated, namely: started/invited (dividing the number of people who started by the number of people who were invited times 100), started/responded (dividing the number of people who started by the number of people who responded times 100) and started/finished (dividing the number of people who finished by the number of people who started times 100).
As a proxy for adherence to the CONSORT guidelines, we noted whether the article included a flow-chart and whether the article provided the dates defining the period of recruitment and follow-up.


All extracted data were entered in SPSS (IBM SPPS statistics for Windows, version 24, Armonk, NY, USA). SPSS was used to calculate averages and SDs for the participant’ characteristics, study characteristics and recruitment characteristics. For comparison reasons outpatient clinics and hospitals were combined into one setting, which was named “hospital setting”. Countries were furthermore grouped in regions for comparisons (Europe, USA/Canada, Asia, Middle East, Australia, Africa and South America). When a study mentioned multiple compliance rates, these were combined into one compliance rate for the whole study.

3. Results

3.1. Study Characteristics

The original search led to 2163 hits. Upon first screening, 1656 articles were excluded, additional screening of the whole articles led to a further exclusion of 173 articles. Additional checking of the reference lists of reviews, included articles and forward checking led to 15 more studies being included (see Figure 1, adapted from [57]). Thus, in total, 90 papers, describing 75 studies, were included in this review. The characteristics of these studies can be found in Table 1. Fifteen studies focussed on healthy children. The other 60 studies focused on children with a disorder or disease, with attention deficit hyperactivity disorder (ADHD) being the most studied disorder (n = 21) (see Table 1). The majority of studies focussed on children (defined as aged between 2 and 12 years, n = 38) or both children and adolescents (n = 31). A minority of studies focussed only on adolescents (n = 6) (see Table 1). Duration of study varied from 4 to 52 weeks, with the majority of studies lasting 26 weeks or less (n = 59, 79%, see Table 2. Number of measurement moments (i.e., how often did participants have to come to the research facility/how often did they have to fill out questionnaires) varied from 2 to 16 with a mean of 3.7 (SD 2.7), the number of different measurements per moment varied from 1 to 19 with a mean of 4.9 (SD 3.7).
Two studies were published before the start of the CONSORT guidelines. Of the 73 studies that were published after the start of the CONSORT guidelines, 33 studies (45%) provided a flow diagram and 22 studies (30%) reported the dates defining the period of recruitment and follow-up.

3.2. Recruitment

Most of the studies included in this review did not report the number of children or adolescents that were invited to participate in the study, as only 11 out of 75 studies mentioned the number of participants that were invited. The total number of people invited to participate varied from 46 to 3562 (Mean (M) = 804.5, SD = 1083.28). The percentage of invited participants that eventually started the study ranged from 2.4 to 87% (see Table 3).
Forty out of 75 studies mentioned the number of participants that responded to the invitation or were screened for the study and this varied from 30 to 1556, with 12 to 100% of these people actually starting the study.
Most studies did not specify the exact method(s) of recruitment, mostly just mentioning the recruitment setting. Most studies recruited their participants from a hospital or outpatient clinic setting (n = 33). Other settings from which participants were recruited were schools (n = 23) and the community (n = 15). Nine studies reported multiple settings for recruitment; one study recruited participants from a summer camp for children with ADHD and other disorders; one study recruited from an online registry; one study recruited participants from those who participated in earlier studies; and eight studies did not mention the recruitment setting.
Looking at the efficiency percentages for started/invited, started/responded or started/finished for studies including those with an illness (averages 43.5%, 63.5%, and 83.1%, respectively) and those without (averages 36.2%, 53.1%, and 84.2%, respectively), there was a clear difference for started/invited and started/responded but not for started/finished. A comparison for average rates between studies including only children (38.8%, 62.2%, and 85.4%, respectively), only adolescents (15.5%, 56.4%, and 87.8%, respectively) or both (53.4%, 52.7%, and 79.6%, respectively) showed notable differences. For different recruitment settings, there were mainly clear differences for started/invited. However, for all rates, the school setting had the highest average rate: hospital (17.7%, 56.8%, and 82.9%, respectively), community (29.9%, 57.1%, and 81.7%, respectively), and school (46.0%, 64.6%, and 86.8%, respectively). Lastly, when looking at these average efficiency percentages for the different continents, we also saw clear differences: Europe (35.3%, 64.3%, and 87.8%, respectively), North America (6.6%, 48%, and 77.7%, respectively), Asia (49.5%, 48.7%, and 92.6%, respectively), Africa (NA, 28%, and 91.1%, respectively), Middle East (33.2%, 64.6%, and 79%, respectively), Australia (72.9%, 69.5%, and 70.7%, respectively), and South America (54%, 93.2%, and 90.9%, respectively).

3.3. Supplementation

Most studies used capsules as the form of supplementation (n = 57), however there were also some other approaches (see Table 2). The number of capsules that participants were instructed to take also varied widely from 1 to 12 capsules a day, with some studies basing the dose per body weight of the participant (see Table 2). Moreover, a huge range of different placebos was used (see Table 2).

3.4. Adherence

The included studies mentioned a wide variety of methods to measure adherence: capsule count (or product weighting) (n = 30), diaries or tick-off forms (n = 13), interviews face to face/via phone/ via e-mail (n = 11), taking the capsules under supervision (n = 8), and blood values (n = 5) (see Table 4). Thirteen studies used more than one method to assess adherence. Furthermore, 23 studies did not specify how or whether they assessed adherence. The way in which adherence was reported in the studies also varied greatly. Some studies mentioned percentages of capsules taken, the average number of capsules taken per day, blood values, or just mentioned that adherence was good or mentioned how many students were excluded due to non- adherence.
Twenty-five studies mentioned a specific percentage of adherence, which varied from 60 to 97%, mean 85% (SD 10.1). In addition, the levels of capsules that needed to be taken to be considered as being adherent differed per study, varying from 65 to 90%. Other studies defined adherence as the number of days of not taking capsules.
Looking at the adherence percentage between studies in healthy and diseased children, there seemed to be a slightly lower average adherence in diseased children (M = 83.7%, SD = 11.9), compared to healthy children (M = 87.6%, SD = 7.1). When we looked at the different age groups recruited, there seemed to be a lower average adherence in the child only group (M = 82.5%, SD = 9.5), compared to adolescents (M = 89.2%, SD = 1.1) or the combined group (M = 88.5%, SD = 11.2). The difference in average adherence in different recruitment settings was less clear; hospital (M = 86%, SD = 10.6), community (M = 89.5%, SD = 7.8), and school (M = 83.9%, SD = 11.6). The average adherence rate also differed between continents with a lower average rate in Australia and USA/Canada: Europe (M = 87.5%, SD = 9.3), USA/Canada (M = 78.7%, SD = 6.5), Asia (M = 92%, SD = 1.4), Africa (M = 95%, SD = 0.5), Australia (M = 79.7%, SD = 13.5), and South America (M = 94.5%, just one study). There seemed to be a tendency for higher average adherence when capsules were used (M = 88.2%, SD = 8.0) instead of food (M = 74.8%, SD = 14.3) or drinks (M = 81.5%, SD = 9.2), or other forms of supplementation (M = 80.3%, SD = 18.0). Some studies mentioned that participants took capsules under supervision, but they did not show a higher mean adherence (M = 82.8%, SD = 15.2) than those that did not have supervision of capsule intake (M = 86.2%, SD = 8.3). Seven studies, that reported adherence, reported that participants consumed capsules more than once a day while 12 studies, that reported adherence, mentioned that the capsules were only taken once a day. There was no difference in average adherence between those two methods of supplementation (M = 87.3%, SD = 9.4 vs. M = 87.6%, SD = 7.8). Fifteen studies, reporting adherence, mentioned talking to parents or participants either via telephone or face to face (or via e-mail) during the study about the supplementation to increase adherence [61,67,69,70,72,90,91,107,111,113,131,134,135,136,143]. The studies that included a phone call did not have a higher average adherence rate (M = 81.5%, SD = 9.5) than those that did not include a phone call (M = 86.2%, SD = 10.3). There were three studies that provided some form of incentive [98,107,146], however only one of these studies reported an adherence percentage. Forty-six studies mentioned that they took either blood or cheek samples, but only five studies mentioned that they used blood as an adherence measure [61,85,86,117,134].

3.5. Drop-Out

Sixty-five of the 75 included studies mentioned a drop-out rate or included numbers which made it possible to calculate the drop-out rate. The average drop-out was 17% (SD 13%), but it varied between 0% and 58% (see Table 4). There was no clear difference in average drop-out rate between studies in healthy (mean = 16.5%, SD = 11.5) and diseased populations (M = 17.9%, SD = 13.7). There was a difference in average drop-out with regard to the recruited age group: children M = 15%, SD = 11.1), adolescents (M = 12.3%, SD = 7.3) or both (M = 21.5%, SD = 14.9); with a higher average drop-out rate in the combined age group.
There was also no clear difference in mean drop-out between recruitment setting: hospital (M = 15%, SD = 11.1), community (M = 18.2%, SD = 8.6) or school (M = 15.3%, SD = 13). Differences could be seen in the average drop-out according to the continent on which the study was executed: Europe (M = 13.3%, SD = 9.8), USA/Canada (M = 23.1%, SD = 11.6), Asia (M = 6.8%, SD = 7.4), Africa (M = 11.6%, SD = 3.9), Middle East (M = 20.1%, SD = 16.7), Australia (M = 34.9%, SD = 7.8), and South-America (M = 9.1%, just one study). When looking at different forms of supplementation, no clear differences in average drop-out rate could be seen: capsules (M = 17.5%, SD = 12.9), food (M = 14.1%, SD = 14.9), drinks (M = 19%, SD = 13.7), and others (M = 17.9%, SD = 8.4). Eight studies who reported drop-out rate mentioned that capsules were taken under supervision, this seemed to lead to somewhat lower average drop-out rate (M = 13%, SD = 15.6), compared to the 57 studies in which participants did not take the capsules under supervision (M = 17.9%, SD = 15.6). Sixteen studies that reported drop-out rate divided the capsules over multiple intake moments (M = 17.2%, SD = 9.3). This did not seem to increase or decrease the average drop-out rate if compared to those studies that specified one intake moment (M = 17.1%, SD = 13.6). Fourteen studies that noted drop-out rate reported that they contacted the participants during the study. Studies that did so seemed to have a slightly higher average drop-out rate (M = 20.4%, SD = 11.4) than studies that did not contact participants during the study (M = 16.5%, SD = 14.4). Of the studies that reported giving participants an incentive, two mentioned a drop-out rate, this was on average 15.3% (SD 20.4). Studies that did not state an incentive had an average drop-out rate of 17.4% (SD 12.7). Of the 65 studies that mentioned a drop-out rate, 50 specified a reason for drop-out (six did not have drop-out, and nine did not specify the drop-out). Fifty-two different reasons for drop-out were mentioned, with the most common reasons mentioned being lost to follow-up, poor or no compliance or inability to take supplement.

4. Discussion

We conducted a thorough review to examine recruitment, adherence and drop-out rates in n-3 LCPUFA supplementation studies in children and adolescents, in order to identify strategies which can be implemented to improve those rates. Even though the CONSORT guidelines clearly state what data need to be included in the report of a RCT, the majority of the included studies did not provide a flow-chart (55% did not) or the dates defining the period of recruitment and follow-up (70% did not).

4.1. Recruitment

The majority of studies provided minimal details about the recruitment process. The low number of studies that reported the number of participants that they invited and screened is, however, not uncommon in research studies as similar numbers were reported by Toerien et al. who studied 129 studies in six major journals [148]. The literature does give some suggestions for methods that could increase recruitment; for example, telephone calls to those who do not reply, an opt-out system (participants contact the researchers if they do not want to participate, please do note that this is not legal in all countries), including incentives, making trials open, and in person recruitment [149]. The use of clinical referral is also suggested to be related to higher recruitment rates, as most patients will have a trusting relationship with their doctor [150]. When we looked at the research setting (hospital, community, school), though, the mean started/invited rate and mean started/responded rate seemed to be slightly higher in the school setting. However, in the studies that looked at diseased populations, the average percentage efficiency of started/invited and started/responded was higher than studies looking at healthy populations (M = 43.5% vs. M = 36.2% and M = 63.5% vs. M = 53.1%, respectively).
It has been shown that in adolescents, giving monetary incentives does improve response rates and has a positive effect on their willingness to participate in studies [151]. However, the provision of monetary incentives might be considered unethical in children/adolescents [152,153]. One might thus consider a form on non-monetary incentive, for example in Food2Learn participants received a cinema voucher [19]. In the current review, there were only three studies that provided an incentive and these studies did not have remarkably higher recruitment rates. Hence, more studies that do provide incentives are needed to elucidate whether or not incentives improve recruitment. Moreover, there are myriad reasons as to why somebody would or would not participate in a study. There are participant characteristics which in adults have been associated with a higher chance of non-participation such as younger age, being male, lower social economic status, and lower education level [154,155]. However, in the limited number of studies on recruitment in children, no association between age or sex has been seen, although the education level of parents was associated with higher enrolment rates [5].
Beliefs about the effectiveness of the treatment may also play a role. Examples of reasons as to why adolescents did not participate informally given in Food2learn included: (1) the belief that n-3 LCPUFA are not effective in improving health; (2) the belief that they already consume sufficient amount of n-3 LCPUFA/already eat healthy; (3) the belief that participation will take too much time/effort; and (4) lack of interest in research in general. These factors should be taken into account during the research process and it seems wise to include explanations that most people do not get enough n-3 LCPUFA in their diet as well as elaborating on the possible health benefits of n-3 LCPUFA specific to the age group being assessed.

4.2. Adherence

Just 25 studies mentioned a specific adherence percentage, which varied between 60% and 97% with a mean of 85%. Moreover, most studies included in the current review used indirect adherence assessment methods (i.e., diaries, interviews, and capsules counts) which are all subject to problems with reporting bias and errors or intentional manipulation [156]. More direct methods such as the determination of fatty acid levels in the blood seems to be the most reliable method to assess adherence, which was done in only five studies. However, it should be noted that taking blood samples in younger children might not be acceptable for all parents or ethical committees and could therefore lead to lower recruitment numbers.
In the current review, there was no difference in mean adherence in those studies where participants received a telephone call to try and increase adherence compared to those in which participants received no telephone call (M = 81.5% vs. M = 87.7%). There were only three studies that provided an incentive and only one of these studies provided an adherence percentage, which was 75%. There seemed to be a higher average adherence of capsules (M = 88.2%) compared to other forms of supplementation (M = 74.8%, M = 81.5%, M = 80.3%, for food, drink and other forms, respectively). Lastly, there was no difference in the mean adherence between those who took capsules multiple times a day compared to those who took capsules only once a day (M = 87.3% vs. M = 87.6%). It is however important to remember that all these findings are based on only 25 studies that mentioned an adherence rate.
Other studies suggest factors that are associated with higher adherence in children and adolescents, these include: sociodemographic factors (i.e., older children and older adolescents are less likely to be adherent, and boys are less likely to be adherent), disease associated factors (i.e., if the disease also has positive symptoms the person is less likely to be adherent), the belief and attitude that a person has towards the treatment (i.e., those that belief that the treatment will be effective are more likely to be adherent), their mood (i.e., those with depression are less likely to be adherent) and the social context (i.e., those who are supported by family and friends are more likely to be adherent) [157,158]. Methods to increase adherence rates have also been suggested. Methods that have been employed to increase adherence include: educating participants about adherence, making medicine (or supplementation) more palatable, providing incentives/tokens, and involving parents or schools [159,160]. However, one must take into consideration that the vast majority of studies looking at which methods can help increase adherence have been executed in a medical setting with patients requiring medications and these results do not by definition translate to nutritional interventions in healthy participants or those with diagnosed disorders such as ADHD.
Some suggestions for improving adherence for n-3 LCPUFA supplementation studies may include: providing sufficient information about the importance of adherence (i.e., explaining the importance of adherence to get valid results), getting parents involved, and providing appropriate incentives [159,160].

4.3. Drop-Out

In the current review, the average drop-out was 17% (range 0–58%). Three studies mentioned some form of incentive [98,107,146] and they reported a slightly lower average drop-out than those that did not use (or did not report) an incentive (M = 15.3% vs. M = 17.4%). There were differences in average drop-out rates between continents, with drop-out rates being higher in Australia (M = 34.9%), USA/Canada (M = 23.1%), and the Middle East (M = 20.1%) compared to Europe (M = 13.3%), Africa (M = 11.6%) and Asia (M = 6.8%). We can only speculate about explanations for this difference (e.g., individualistic vs. collective societies) and do point out that these differences have to be interpreted with caution as the number of studies per continent did differ greatly. A number of methods to decrease drop-out in studies involving adults has been suggested. They include emphasizing the benefit of participation, flexible scheduling of appointments, regular positive communication from the research team to the participants (e.g., birthday and Christmas cards, newsletters, etc.), a consistent research staff so participants can build a bond with the researchers, and appropriate incentives [150,161,162,163]. Other strategies that have been suggested include decreasing the complexity of the treatment and limiting the number of follow-up visits to the bare minimum [164]. Furthermore, a combination of multiple strategies is suggested to be most effective in increasing retention [161,164]. All these methods to decrease drop-out have been studied in adults; more research on methods to decrease drop-out in children and adolescents in RCT is warranted.
Suggestions for decreasing drop-out in n-3 LCPUFA supplementation trial include: keeping in regular contact with the participants, providing flexible appointment possibilities, providing incentives for participants and providing reminders. With regard to the supplement, one should keep the regime as simple as possible e.g., one (concentrated) capsule per day [150,161,162,163,164].

4.4. Strengths and Limitations

Limitations of the current review include the fact that many of the included studies did not report all data on recruitment, dropout and (assessment of) adherence. Due to the incomplete reporting of data, results should be viewed with caution. The main advantage of the current review is the fact that we included all studies investigating n-3 LCPUFA supplementation in children/adolescents regardless of whether they were healthy children/adolescents or children/adolescents with a disease or disorder.

5. Conclusions

The conclusions drawn are based on minimal reporting from the included studies in this review. Less than half of the included studies abided by the CONSORT guidelines. Problems with recruitment and drop-out seem to be common in n-3 LCPUFA supplementation trials in children and adolescents. However, since the reporting about recruitment, adherence and dropout rates was very heterogeneous and minimal in the included studies, we cannot provide specific suggestions to improve LCPUFA supplementation studies in children and adolescents.

6. Recommendations

It is important for future studies to report on recruitment effort and rate, adherence (including the method of assessing adherence) and drop-out rates according to the CONSORT Guidelines.
Suggestions from other scientific areas to increase recruitment, adherence and minimize drop-out include: the provision of sufficient information about the importance of adherence (i.e., explaining the importance of adherence to get valid results), getting parents involved, provision of appropriate incentives, emphasizing the benefit of participation, being flexible with the scheduling of appointments, the research team engaging in regular positive communication with the participants, having a consistent research staff member so participants can build a bond with the researchers and to keep the supplementation regime as simple as possible.


Open access publication is financially supported by the Dutch Scientific Organization Incentive Fund Open Access.

Author Contributions

Inge S. M. van der Wurff conducted the literature search and wrote the first draft of the paper. Inge S. M. van der Wurff, Barbara J. Meyer and Renate H. M. de Groot interpreted the data, revised subsequent drafts and approved the final manuscript before publication.

Conflicts of Interest

The authors declare that they have no conflict of interest.


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Figure 1. Flow diagram of study selection: 90 manuscripts were found reporting on 75 studies.
Figure 1. Flow diagram of study selection: 90 manuscripts were found reporting on 75 studies.
Nutrients 09 00474 g001
Table 1. Characteristics of studies.
Table 1. Characteristics of studies.
Reference Age Range or Mean (SD)Gender (%Female)Population: Healthy, Disorder or Disease Country
[58]3–1544Acute lymphoblastic leukemiaEgypt
[62]8–140ADHD The Netherlands
[63]6–1641 (after intervention) ADHDIsrael
[72]6–1227ADHDSri Lanka
[82]7–1243 (after intervention)ADHD or lower IQChina
[85]8–1648Aggressive behaviourMauritius
[86]6–1442Asthma USA
[87]8–1256Asthma Australia
[88]10–1231Asthma Taiwan
[89]10.2 (2.5) fish oil, 11.9 (3.1) control48Bronchial asthmaJapan
[90]3–811Autism USA
[91]5–8NRAutism USA
[92]2–526Autism Canada
[94]6–1748% placebo, 46% flax oilBipolar disorder USA
[96]5–1647Crohn’s diseaseItaly
[98]10.643Dyslexia Finland
[101]7–953Healthy South-Africa
[109]6–1046HealthyAustralia and Indonesia
[113]10–12 100HealthyTurkey
[117]14 (2) 31Hypertriglyceridemia and low LDLUSA
[118,119,120,121]6–1149Iron deficiencySouth-Africa
[122]8–1215Literacy problemsUK
[127]10–1859 (after intervention)Metabolic syndrome Iran
[128]9–1747NAFL and obesityTurkey
[129,130]11–1514NAFL and overweightPoland
[134]10.8 (2.8)48NAFL and overweight Italy
[136,137]14–1756Obesity Sweden
[140]9–18NROverweight + insulin resistanceMexico
[142]6–1818Tourette’s DisorderUSA
[143,144,145]10 (7)45Type-1 type-1 hyperphenylalaninemia, HPAItaly
ADHD = attention deficit hyperactivity disorder; NAFL = non-alcoholic fatty liver; MDD = major depressive disorder; DCD = Developmental Co-ordination Disorder; CF = cystic fibrosis, NR = not reported.
Table 2. Treatment characteristics per study.
Table 2. Treatment characteristics per study.
Reference Treatment per Day Unless Otherwise StatedPlacebo Form of SupplementationNumber of CapsulesDuration b (Weeks)
[108]DHASCO a: 400 or 1200 mg DHACorn oil Capsules68
[106]800 mg FO: 400 mg DHA, 56 mg EPAOlive oilChewable capsules 216
[113]670 mg FO Olive oilCapsules216
[110]2400 mg FO and 600 mg evening primrose oil: 174 mg DHA, 558 mg EPA, 60 mg GLA. Palm oilCapsules628.6
[104]174 mg DHA, 558 mg EPA, 60 mg GLAPalm oilCapsules612 + 12 (open)
[102]1260 mg DHA rich oil: 652 mg DHA, 101 mg EPAPlacebo oil (656 mg LA, 87 mg ALA)Capsules612
[101]Fish flour: 892 mg of DHA per weekPlacebo spread contained bread flourMargarine NA14.9
[107]14–21 mg DHA, 20–30 mg AAPlacebo supplementSachets to mix into foods 2–3 sachets30
[103]FO: 3600 mg DHA, 840 mg EPA per week50% soybean oil, 50% rapeseed oil (4200 mg LA per week)Bread and sausagesNA12
[114]541 mg FO: 116 mg DHA, 165 mg EPA Sunflower oilCapsules212
[112]DHASCO-S a: 400 mg DHAHigh oleic sunflower oilCapsules216
[115]FO: 1 g DHA, 200 mg EPASoybean oil Chocolate milkNA 15.6
[109]88 mg DHA, 22 mg EPAUnclear DrinkNA52
[105]500 mg DHASCO-S a: 200 mg DHA, 4 mg EPAVegetable oil (15 mg ALA, 250 mg LA) Capsules58
[111]FO in dairy drink 120 mg DHA, 60 mg EPA Whole milkMilk drinkNA20
[117]4 g FO: 1.5 g DHA, 1.86 g EPACorn oilUnclearUnclear8 + 8 with 4 weeks wash-out in between
[100]3 mL dose of 1200 mg FO: 240 mg DHA, 360 mg EPA. Corn oilLiquid oilNA12
[88]FO: 125 mg DHA, 230 mg EPACorn oilCapsulesDependent on bw 16
[96]3 g O3FAOlive oilCapsulesDependent on bw52
[92]1.875 mL FO: 0.75 g of DHA + EPA. If well tolerated dose ×2 after 2 weeks.Olive oil and medium chain triglycerides.Liquid oilNA24
[65]165 mg DHA, 635 mg EPA, 100 mg other O3FAOlive oilCapsulesNS8
[67,68]174 mg DHA, 558 mg EPA, 60 mg GLAOlive oilCapsules612 + 12 (open)
[97]FO and EPO: 174 mg DHA, 558 mg EPA, 60 mg GLAOlive oilCapsules626
[79]120 mg DHA, 600 mg EPA Olive oilCapsules216
[122]480 mg DHA, 186 mg EPA, 96 mg GLA, 864 mg LA, 42 mg AA, 8 mg thyme oil Olive oilCapsulesNR12
[66]DHA-rich fish oil: 3600 mg DHA 700 mg EPA per week.Olive oilMilk and breadNA12
[76]480 mg DHA, 80 mg EPA, 40 mg AA, 96 mg GLAOlive oilCapsules816
[143,144,145]LCPUFA supplementation: varying dosage Olive oilCapsules1 per 4 kg of bw52
[94]Flax seed oil: 0.55 to 6.6 g ALAOlive oilCapsulesVarying up to 1216
[89]FO: DHA 7.3 ± 11.5 mg/kg of bw, EPA 17.0 ± 26.8 mg/kg of bwOlive oilCapsulesDependent on bw: 6–1243.6
[83]PCSO-524 c: 16.5–22 mg DHA, 21.9–29.2 mg EPAOlive oil, lecithin and coconut oilCapsulesDependent on bw: 3–414
[86]Drink containing FO (1.6 g DHA, 3 g EPA) and borage oil (3.0 g GLA)Control drink with high oleic safflower oilDrink NA12
[70]EPA-rich FO: 108 mg DHA, 1,109 mg EPA or DHA-rich FO: 1,032 mg DHA, 264 mg EPA Safflower oilCapsules416 + 16 + 16
[90]FO: 1.1 g DHA + EPASafflower oilPudding packet2 pudding packs12
[123] FO: 180 mg DHA, 270 mg EPASoybean oilCapsules312
[135]2 g FO: 1200 mg DHA + EPASunflower oilCapsules424
[87]FO: 1.2 g O3FASunflower oilCapsules, salad dressing and margarine424
[72]FO and EPO oil: 592.74 mg O3FA Sunflower oilCapsules226
[58]1 g FO:120 mg DHA, 180 mg EPASunflower oilCapsulesUnclear24
[61]100–400 mg DHA, 500–100 mg EPA Sunflower oilCapsules Dependent on bw: 2–416
[129,130]AO: 450–1300 mg O3FA (DHA: EPA in 3:2 proportion)Sunflower oilCapsulesDependent on bw 24
[116]AO: 500 mg DHA or FO:500 mg DHA + EPA Wheat gern oilCapsules116
[131,132,133]AO: 250 or 500 mg DHA Germ oilCapsules126.1
[134]AO: 250 mg DHAGerm oilCapsulesNR26
[95]Algae triacylglycerol 100 mg DHA/kg/day 1st month then 1 g DHA/dayGerm oilCapsules452
[93]AO: 200 mg DHACorn oil + soy bean oil Capsules126
[146,147]AO: 600 mg DHACorn oil + soy oilCapsules316
[138,139]4.9 g FO: 892 mg DHA, 191 mg EPA 6:1:1 mix of palm shortening, soy oil, and rapeseed oilBreadNA16
[141]2.5–4 g FO (12% DHA, 18% EPA)Blackcurrant seed oil (45.7% LA, 18% GLA, 14% ALA) CapsulesDependent on bw: 5-826
[62]650 mg DHA, 650 mg EPANormal margarine (1 g LA)Margarine NA16
[99]FO: 720 mg DHA, 1080 mg EPA1800mg lactoseCapsules28+8
[125]200 mg DHA, 1400 mg EPA, 400 mg other O3FAPlacebo capsuleCapsules212
[136,137]FO and EPO: 290 mg DHA, 930 mg EPA, 100 mg GLA PlaceboCapsules1012 + 12 with 6 weeks wash-out in between
[91]FO: 1.1 g DHA + EPAIdentical placeboPudding packet2 pudding packs6
[128]1000 mg PUFAPlaceboCapsule152
[63]2 g sage oil: 1 g ALALactose placeboCapsules28
[60]240 mg DHA, 360 mg EPAPlaceboCapsules28
[64]FO: 2.7 mg DHA, 500 mg EPA PlaceboCapsules115
[127]2.4 g omega-3Vitamin E or placeboTabletsNR8
[84]100 mg DHA, 250 mg EPA, 25 mg phospholipidsSunflower oilCapsulesAccording to bw: 1–2 16
[124]1 g FO: 120 mg DHA, 180 mg EPAPlacebo capsuleCapsules1At least 8 weeks
[78]Algae oil: 345 mg DHAPlacebo capsuleCapsules1 16
[59]241 mg DHA, 33 mg EPA, and 180 mg omega-6Identical placeboCapsules 110
[118,119,120,121]FO: 155 mg DHA, 29 mg EPAPlaceboCapsules 215
[142]Varying 500–6000 mg O3FAPlaceboCapsulesVarying up to 1220
[140]Salmon oil: 360 mg DHA, 540 mg EPAPlacebo (corn starch, lactose, magnesium stearate and polyvinyl pyrrolidone) CapsulesNR4
[85]300 mg DHA, 200 mg EPA, 400 mg ALA, 100 mg of DPADrink without omega-3DrinkNA24
[77]FO: 96 mg DHA, 153 mg EPA or n-3 LC-PUFA containing PLs: 95 mg DHA, 156 mg EPARapeseed oil Chocolate flavoured spreadNA13.1
[73]240 mg LA, 60 mg ALA, 95 mg mineral oilVitamine C capsulesCapsules17
[69]FO and EPO: 174 mg DHA, 558 mg EPA, 60 mg LA.Medium chain triglyceridesCapsules612
[126]200 mg DHA 400 mg EPA, or 180 mg DHA, 380 mg EPAOlive oil or safflower oil Capsules1–216
[74,75]FO and EPO: 174 mg DHA, 558 mg EPA, 60 mg GLAPalm oil Capsules630
[98]500 mg ethyl-EPATriglycerides and celluloseCapsulesNR12.9
[80,81]1–15 weeks: 120 mg EPA + DHA
16–30 weeks: 60 mg EPA + DHA
CelluloseCapsules415 + 15
[82]321 mg DHA, 42.2 g EPA per 100 g eggOrdinary eggEgg113.1
a DHASCO is an algal triglyceride DHA; b Some studies gave duration in months or number of days supplementation was received, we recalculated the duration to weeks; c PCSO-524 is an lipid extract of the New Zealand green-lipped mussel; bw: body weight, NA: not appropriate, NR: not reported.
Table 3. Recruitment effort and recruitment rates.
Table 3. Recruitment effort and recruitment rates.
Reference InvitedResponded/ScreenedStartedFinishedStarted/Invited %Started/Responded %Started/Finished %Recruitment Method Recruitment SettingStudy Period
[141]NSNS2121--100NSDepartment of PaediatricsNS
[66]4640404087100100Parents of summer camp participants were asked.Summer camp for children with psychiatric disordersNS
[98]107107616157 100Teachers nominated children with reading difficultiesSchoolAutumn 2005–January 2006
[116]NSNS3636--100NSHospital8 month period
[146,147]1376675362359265499Parents of underperforming children received a letter inviting their children to take part in the formal screening assessments. SchoolNS
[105]NSNS9088--98Via advertising in newspapers and schoolsCommunity and schoolsNS
[88]NS298197192-6698Participants with asthma diagnosis were recruited from elementary schools through parent conferencesSchoolsNS
[82]15561556179171121296Children were screened from students in two township primary schoolsSchoolsNS
[62]NS3727976-2196Via hospital and advertising at schools. Hospital and schoolsNS
[72]NS4229894-2396NSOutpatient treatment programNS
[114]NS 408196189-4896NSSchoolNS
[118,119,120,121]NS926321294-3592Parents were invited to an information meeting. SchoolNovember 2009–November 2010
[127]NSNS9083--92NSCardiovascular Research CentreNS
[60]NSNS7569--92NSOutpatient ADHD clinic2007
[103]NS230179166-7892Via advertisements CommunityNS
[85]NS938200184-2192Via parents who themselves had participated in a study. Participants earlier studyNovember 2009–December 2011
[123]NS595550-9391Parents were invited to a meeting at which the study procedures were explained and a written informed consent from the tutors and a verbal assent from their children were obtained.SchoolNS
[138,139]3652NS87782-90Subjects were recruited via addresses obtained from the Danish Civilian Person Register. Community NS
[134]NS1185851-4988NSHospitalMay 2012–September 2014
[113]NS443329-7588Via public flyersCommunityNS
[135]NS 302421-8088NSHospitalNS
[87]NSNS4539--87NSNSOver period of 16 mo.
[86]NSNS4337--86NSOutpatient clinicNS
[97]189129117100629186Letters of invitation were sent to parents of children who were identified by teachers. SchoolNS
[78]NS2506354-2586Via advertisements CommunityNS
[79]NS33411095-3386Via health professionals, teachers, leaflets handed out to support groups, leaflet distributed at community centres and advertisements in a free of charge regional newspaper.Community, Health professionals, schools, support groups.NS
[64]NSNS10992--84NSHospital and secondary treatment centresJanuary 2005–June 2007.
[92]NS1013832-3884NSHospitalDecember 2010–December 2013
[143,144,145]NSNS2420--83NSNSRecruited over 6 month
[125]NS1782319-1383Via advertisements and clinician referrals. Community and referral July 2011–May 2014
[109]NS932780643-8482Via advertisement at schools and media advertisement. SchoolsAuguet 2003–April 2005
[136,137]108473125296681NS.Outpatient clinicNS
[73]NS~3007863-2681Via advertisement on radio health program, in health newspapers and in ADHD clinics. Community and ADHD clinicJanuary 2007–June 2007
[80,81]NS247200162-8181Advertisements in newspapers, on the Internet and medical centres. CommunityNS
[91]863118574574879E-mail invitations to in registry and longitudinal study of families of children affected by ASD. Online registry18 September 2012–31 December 2012
[67,68]NSNS7559--79NSHospitalOctober 2004–August 2006
[128]NSNS138108--78NSOutpatient clinicMarch 2010–June 2012
[106]NS511450348-8877Via schoolSchoolsNS
[89]NSNS3023--77NSHospitalJanuary 1994–March 1995
[142]NSNS3325--76Via community, hospital and through patient association.Community and referral NS
[69]NS1387657-5575School and parent group circulated screening information to all potential eligible familiesSchools and parent groupsNS
[77]2501028360338172Newspaper advertisementCommunityJuly 2004–January 2005
[93]NS1434834-3471Via recruitment flyers across campus and sent to autism support groups. Campus, autism support groupsNS
[61]NSNS3726--70NSADHD clinicNS
[90]NS322719-8470NSOutpatient autism clinic5 November 2008–25 June 2009
[104]NS162154105-9568Via teachers who informed families SchoolDecember 2009–July 2011
[76]NS 1935033-2666NSCommunityNS
[74,75]NS 201167109-8365NSNSStart March–May 2004
[70]NS1999657-4859Via media releases, television interviews, newspaper advertisements, school newsletters, and flyers.Community and SchoolJune 2007–June 2009
[110]560447408227739156Via information sessions and school newsletters. SchoolsDecember 2010–May 2011
[94]NSNS5124--47NSHospitalNovember 2001–March 2005
[63]NSNS4017--43NSADHD clinicNS
[59]NSNS40NS---NSOutpatient ADHD clinicJune 2009–March 2010
[124]NSNS25NR---NSHospital NS
[140]142NS76NS54--From previous sample children with insulin resistance were identified and invitedCommunityNS
[102]NSNS233NS---Via schoolSchoolNS
NS = not specified.
Table 4. Adherence and drop out characteristics per study.
Table 4. Adherence and drop out characteristics per study.
ReferenceAdherence AssessmentAdherence Mean or nr. of Part. Non-AdherentBlood FA Determined?Drop-Out Rate (%)
[114]Supervision and tick-off formActive: 88.4%, Placebo: 88.5%Y3.16.1
[108]NRNRYLow DHA: 20; High DHA: 7.117
[112]Capsule countNearly 100%Y7.15.6
[101]SupervisionActive: 94.8%, Placebo: 94.5%Y119.8
[106]Pill diary by teacher or parentActive: 68.4%, Placebo: 66.7%Y2421
[109]Sachet count and diary (Australia)/Supervision (Indonesia)Australia: 73-84%Y2734
Indonesia: 85-87% 3.65.3
[111]Interviewsmall increase in DHA in supplemented groupYNRNR
[107]Diaryn = 6YNRNR
[105]Parental signing of diary card>80%.NNRNR
[110]SupervisionPhase 1: 59%, Phase 2: 61%N4742
With disorder or illness
[140]Pill countActive: 93%, Placebo: 96%YNRNR
[82]Supervisioncount of consumed eggs showed good compliance and % of adherence to treatment was 100%Y5.63.2
[127]Pill countpill count revealed no essential irregularitiesY13.3Vit. E: 0, Placebo: 10
[80,81]Pill countn = 14N2018
[83]Pill count, compliance diary and telephone call96.7%N2323
[95]NRn = 2 DHA supplementation induced a median plasma DHA enrichment of 5% suggesting adherenceY145
[79]Capsule countn = 1Y1311
[86]Diary and blood values80–85%Y21.111.1
[77]Phone calls and product weightingn = 6YPhospholips: 38, Fish oil: 2524
[94]Capsule count and diary>75%Y4264
[70]Capsule countEPA: 83%, DHA: 86% , LA: 85%YCOCO
[87]Capsule count75%YNRNR
[131,132,133]Capsule count and interviewexcellent in all groupsYNRNR
[62]Product weightingn = 1Y05.1
[135]Capsule count and interviewNRY025
[78]Capsule countActive: 96.7%, Placebo: 100%Y1513
[93]Capsule countexcellentY2138
[136,137]Capsule countn = 1YCOCO
[90]Parent interviewActive: 69%, Placebo: 75%Y3623
[69]Capsule countFA changed in the expected direction.Y2430
[64]Capsule countNRY3019
[116]Capsule countDHA: 96.5%, DHA + EPA: 96.9%, Placebo: 96.7%YDHA: 0, DHA + EPA: 00
[117]Blood valueNRYCOCO
[129,130]Capsule count95.5%Y2111
[128]Capsule countNRYNRNR
[134]Blood valuesn = 5Y1410
[98]NRAccording to parents children took the capsules carefullyYNRNR
[88]Supervision and capsule countPill count: 91%Y00
[92]NRthere was no overlap between the distributions of plasma levels between groups at week 24Y2111
[65]Capsule countn = 5NNRNR
[97]Capsule count and diaryPeriod 1: 88.7%, Period 2: 85.5%N1712
[91]Parents e-mailActive: 69%, Placebo: 83%N2814
[85]Parent interview and blood valuesAverage number of drink per week 6.5.N1022
[73]Capsule countActive 7.88 capsules left; Placebo: 14 capsules leftN1821
[67,68]Parent interviewPeriod 1: 93.4%, Period 2: 93.3%NCOCO
[126]NRn = 5NNRNR
[122]Capsule countActive: 90.4%, placebo 86.6%N2321
[74,75]Capsule count and diaryn = 2NCOCO
[63]Capsule countNRN6055
[96]NRCompliance was optimalNNRNR
[146,147]DiaryAt school: 75%N0.61.1
[58]NRn = 5N8.65.7
[123]Diary and capsule countNRN020
[104]InterviewActive: 94%, Placebo: 92%, Period 2: 91%NCOCO
[99]NRn = 1NCOCO
CO: cross-over study, NR: not reported.

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