## 4 Discussion
There are, however, quite contradictory results published in the literature from similar studies. In a multi-center, randomized controlled clinical trial involving 1685 participants who self-monitored their physical activity, followed a reduced-energy diet in accordance with the Dietary Approaches to Stop Hypertension (DASH) guidelines and participated in behavioral therapy interventions, surprisingly, individuals aged 60 and above exhibited significantly greater initial weight loss compared to younger groups, and this trend persisted throughout the additional 3 years of the study [48]. In another 400-participant observational, open, prospective study, participants engaged in a 12-month online weight loss program where energy intake was reduced by 15% and physical activity was increased. The program resulted in the same weight loss across age groups [49]. Compared to these studies, our study confirms the general clinical expectation, with a distinctive feature that we applied linear regression analysis. Dietary intervention involves behaviour changes which in old age can be hindered by lack of peer support, motivation, health literacy and financial resources [50]. As nutrition is part of our identity [51], changing it in old age is particularly difficult and challenging for both the dietitian and the patient. Therefore, the intervention designed for older adults should be more personalised, offering low-cost, seasonal food recipes and group dietetic education sessions, as well as implement any change in very small steps, with dietary suggestions adapted to the patient's preferences. After 90 days, the volunteers were offered to extend their participation in the trial to six months or more, and ca. 40% of them accepted this offer. These volunteers could preserve their weight loss success. However, currently we do not yet have enough data to assess the long-term sustainability of the results. In the future, we plan to introduce this kind of rehabilitation in routine clinical practice with a long term (some years) follow-up period. Other studies also suggest that the longer the intervention, even with a low or gradually decreasing effort, the lower the chance is for a relapse [52]. A _strength_ of our approach is the classification of logged items into elaborate food set hierarchies, which was made possible by a sophisticated dietary expert database. Compared to other studies, another unique feature is the analysis of significant temporal trends in weight loss and in food set preferences. A _limitation_ of our study is that due to COVID-19 restrictions, we could not randomize the selection of the control group, which decreases the reliability of the control-intervention comparison. However, by the formation of the successful vs. unsuccessful weight loser subgroups within the intervention group, we could still perform meaningful and statistically relevant group level comparisons. This can be regarded as added value aside from within-subject trend analysis results. We also think that the moderate sample size (cf. Table 1) of our study is somewhat counterbalanced by the longer and more detailed dietary logs; i.e., we have more data per patient. The differences between the control and the intervention group consisted of more intensive coaching, telemedicine and dietary logging; however, our study design did not make it possible to separate these effects. Similarly, we have not measured the patient or expert satisfaction with the specific features of the telemedical platform, though we believe that the effective and intuitive graphical user interface is the key to success. Comparing our solution to similar studies reported in the literature is also very hard because the available information is scarce, and the related studies were using a variety of apps and telemedical designs, cf. the intervention summary of related studies in Appendix A. A recent guideline on rehabilitation also underlines the lack of standardization of telemedical solutions [53].