166 | Chapter 8 Power of (cost-)effectiveness study This study was powered to detect a 50% reduction in the number of falls in the intervention group compared to the control group, representing a large effect (305, 326). However, in our study we observed a 15% reduction in falls in the intervention group compared to the control group. This means that the study was underpowered to detect a statistically significant effect. By increasing the sample size it is possible that a statistically significant effect could be detected. On the other hand, the clinical relevance of the results does not change with a larger sample size and thus also not the conclusions and recommendations about In Balance. COVID-19 This study was initiated during the COVID-19 pandemic, which was accompanied with several challenges. For instance, we had to delay the start of participant inclusion by six months compared to the original plan due to COVID-19 measures. Initially, recruitment was slow, likely because older adults were hesitant to participate, because they had to visit a location for measurements and would attend group training sessions if randomized to the In Balance group. Additionally, early in the study, measures such as social distancing and mask-wearing were in place. When the first groups completed the intervention, another lockdown was implemented, delaying the start of new In Balance groups. Despite these practical and logistical difficulties, we do not anticipate that these issues impacted the study’s results, since the COVID-19 measures primarily affected the first few groups participating in the In Balance intervention. Besides, the COVID-19 measures at that moment, such as social distancing and wearing face masks, were not that extreme and could be relatively easily incorporated into training sessions. Last, no training sessions had to be halted or cancelled due to the measures. Participant characteristics Although our study included participants from various regions across the Netherlands (see also Figure 1.2 in the introduction), the majority was recruited in Amsterdam. This concentration may limit the generalizability of our findings to the national population, as regional differences could influence the outcomes. Moreover, it was notable that both participants of the In Balance program in practice and in this study are primarily highly educated women without a migration background, which is often the case in other fall prevention studies (327-329). It would be good to include a representative sample of the population in fall prevention programs. However, it is difficult to motivate specific groups, such as people who are lower educated or people with a migration background. In Chapter 7 we did some recommendations to also include this group within fall prevention programs. For example, focus on the social element of the program, use a person-centered approach, use positive labeling and use language at the ECRL-B1 level.
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