Different methodological approaches were used to explore the variety of topics of interest in the four studies within PRIMA Meal, eventually leading to the discussed conceptual framework. Throughout the studies, we aimed to remedy each successive study’s limitations in a subsequent study with different designs and participants. Still, we need to discuss some important considerations regarding these two topics.
Study design
In the PRIMA Meal study, we started exploring our topics of interest with a qualitative study of professionals, followed by a mixed-methods study of older adults. The findings from the latter reflected those from the former well, indicating that the interviewed professionals are familiar with their target group. In addition, the interviews with older adults helped us to ask the right questions and offer the most appropriate answer options in the survey, after which we saw the findings from the interviews confirmed by the survey. Later on, we used the knowledge from these studies in a single-blind crossover trial and a double-blind controlled trial, as we assessed the acceptability and effectiveness of protein-enriched regular products. This use of different methodological approaches that increased the strength of the study is an obvious asset of the PRIMA Meal study.
Nonetheless, we also encountered some limitations. Throughout all our studies, we relied on self-reported data. It is possible that information bias occurred in both the professionals and the older adults, either intentionally (social desirability bias) or unintentionally (recall bias), which would negatively affect internal validity [38]. We cannot be certain that participants did not provide socially desirable answers; however, we tried to overcome this with the guarantee of anonymity in the interviews and the survey throughout all studies. We tried to overcome recall bias by encouraging participants to fill in their food record immediately after eating in Study 4. In addition, choosing to conduct a double-blind trial in Study 4 decreased the chance of this kind of information bias affecting the ultimate outcomes in protein intake [39].
Another challenge related to the level of control in particularly Study 3 and Study 4.
In Study 3, we could exactly weigh everything that was consumed, thereby increasing control and precision, whereas the lab setting in which we did so might have evoked behaviour that would not have occurred at home, thereby decreasing sustainability and applicability [40]. The exact opposite was the case in Study 4, where choosing to stay close to the regular life of our participants increased our knowledge on sustainability and applicability of the protein-enriched products, while it simultaneously decreased our level of control and precision. Although we have no reason to assume that any information bias differed between the control and the intervention group, this trade-off leads to
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the notion that we cannot be sure whether the reported consumptions were the actual consumptions in these groups. For this reason, the accuracy of the protein intake data in Study 4 would have benefited from the verification of the self-reported data with proxy sources like direct observation (e.g. via cameras) and biological markers (e.g. via urine collection). Nonetheless, these proxy measurements would in turn have created issues relating to the generalisability of the results, as we could expect that these measurements would result in the participation of fewer and healthier participants, as explained in the next section. Lastly, the generalisability of our two-week randomised controlled trial to months or even years is limited. Still, the positive product evaluations in the in-depth interviews indicate that the findings might be sustainable over a longer period than the current two weeks.
Study participants
Undeniably, the participants in our trials were more independent and healthier than the final target group, the meals-on-wheels clients. In Study 2, we did manage to involve dependent older adults by means of elderly meals-on-wheels clients. Although we reached only 10% of the invited interviewees, we reached 50% of them for the survey.
The latter reach was higher as this was a non-invasive measurement. As we expected a much lower response among these older adults for the more invasive trials in Study 3 and Study 4, we opted to invite relatively more independent older adults. Here, we reached a response rate of 50% and 20%, respectively; these are expectable numbers given the intensity levels of these studies. Still, the latter percentage for Study 4 is low enough to warrant the choice for older adults who are healthier than the ultimate target group, the meals-on-wheels clients.
To illustrate this claim with Study 4: some of the residents had, for example, medical or mental issues that prevented them from participating. We expect cases like that to be even more prevalent in meals-on-wheels clients, decreasing the chance of attracting enough participants. In addition, many residents stated that they did not feel like participating in a study, as it would cost them too much effort without really knowing what they would get back in return. This was already the case without the aforementioned suggested observations and biological markers that would increase accuracy and the inclusion of such measurements could further lower the response rate. Here, the barrier of being part of a scientific study for the first time may be large enough to prevent dependent older adults from participating. For this reason, it would be more apposite to recommend setting up consumer panels like the SenTo panel that we used in Study 3, in which senior consumers are included starting at 55y [41]. Although some of them will suffer from the same medical and mental issues by the time they reach 70y or even 80y, at least they will have become used to participating in a study. Setting up longitudinal studies and
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consumer panels like these, with the early inclusion of future older adults, can therefore overcome the reluctance to be part of a scientific study. Until that time, it is more likely that we will mainly attract the relatively healthy community-dwelling older adults for trials like ours, even those that target frail populations like senior centre residents.
Despite the inclusion of relatively healthier older adults in Study 4, we actually do not expect any problems with generalisability regarding the acceptability of the protein-enriched products. The reason for this is that earlier studies have found very little difference in liking between healthy and frail older adults [42,43], and it was suggested that liking could be tested in healthy older adults [44]. Moreover, the in-depth interviews after Study 4 indicated that the protein-enriched products were so much liked that the participants expressed that they would use them as they became older and frailer. Nevertheless, this positive notion does not extend to the generalisability of the level of consumption of the enriched products, hence requiring its assessment in the ultimate target group with their possibly lower appetite. Although the residents in Study 4 were more dependent than the consumer panel members of Study 3, food intake still has to be measured in the ultimate target group. For this reason, we would recommend conducting nutritional studies in different phases, starting with the global exploration of many necessary outcomes in healthier older adults, and becoming denser in measurements as the study gets closer to the ultimate, frail target group. In the latter, studies should measure only what could not be extrapolated fully from measurements in the healthier target group, such as food intake and subsequent satiety in our particular case.