{"doi":"10.1002/oby.70060","title":"New Frontiers in Stand‐Alone Digital Obesity Treatment","abstract":"Effective remotely delivered behavioral obesity treatment that does not require direct human interaction holds great promise for achieving the goal of universal access to lifestyle interventions. However, previous research has found attenuated weight loss in digital approaches, particularly among those that do not have a “human touch” [1]. It is in this context that we view the noteworthy work of Thomas and colleagues in reporting the outcomes of their factorial experiment that tested treatment components that all aimed to improve weight loss outcomes for individuals engaged in a digital program [2]. The investigators examined five distinct online components and their combinations using the multiphase optimization strategy (MOST) framework [3] to determine which constellation of these components produced the optimal weight loss outcomes when incorporated into their core digital program. While they found that none of the individual components improved weight loss on its own, the combination of the core online behavioral obesity approach plus interactive video feedback, attention to dysregulated eating, and social support with friendly competition significantly improved weight loss outcomes, with models indicating weight losses of 8.4% at 12 months. The effect of this specific amalgamation of treatment components can be compared with just 3.0% weight loss achieved with the online core treatment alone and 5.9% across the study overall with the various combinations of the treatment components. An 8% weight loss at 12 months produced by a stand-alone digital intervention without any personnel staffing required could offer a real advancement over existing digital programs; were an effective digital obesity intervention with these outcomes to be broadly disseminated, the potential for positively impacting public health is substantial. The benefits of utilizing a factorial experiment to optimize digital obesity treatment are highlighted in these results. The effects of the treatment components examined were not additive in the Thomas et al. study [2], likely because engaging in more components can increase participant burden (and perhaps therefore decrease overall engagement) or because different components might potentially achieve the same behavioral goals through the same mechanism and thus be redundant. Indeed, some specific combinations were synergistic, but others were antagonistic (i.e., diminishing the effectiveness of one another). Although the reasons for the antagonistic interaction are not clear, the fact remains that some components were counterproductive when paired together. Further, no significant main effects emerged for any of these treatment components. Thus, part of the value of this factorial study design is in the ability to explore interactions (or combinations of the treatment components added to the basic treatment package). That said, the study was powered to detect significant main effects and markedly underpowered to detect the interaction effects, which is where the beneficial effects were seen. It is also important to note that the findings of the optimization experiment within the MOST framework are exploratory (for the Thomas et al. study [2] and all optimization phase experiments) and can be compared to a pilot study requiring confirmation. Thus, the Thomas et al. optimized package (i.e., combining the core digital program with video feedback on dietary intake, strategies for coping with emotional eating, and social support with friendly competition) must be tested in a definitive, fully powered trial before firm conclusions about the effectiveness of this package can be drawn and before it should be disseminated broadly. Perhaps the most profound insight from this study is the need to test combinations of treatment elements to be confident that the components complement and augment one another rather than detract from one another. Within the context of emerging pharmacotherapies for obesity, there are","journal":"Obesity","year":2025,"id":576208,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9471,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":452613,"name":"Rebecca A. Krukowski","orcid":"0000-0001-9193-2783","position":1,"is_corresponding":false},{"id":689105,"name":"Delia Smith West","orcid":"0000-0002-4375-2785","position":0,"is_corresponding":true}],"reference_count":5,"raw_metadata":null,"created_at":"2026-07-19T02:57:56.636458Z","pmid":"41017229","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}