{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:00:43Z","timestamp":1782846043376,"version":"3.54.5"},"reference-count":133,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Interact J Med Res"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Recommender systems are pivotal in organizing information to enhance noticeability, reduce overload, and streamline decision-making. They can be even more effective if combined with digital nudges. Digital nudging is a subtle approach that combines design, information, and interaction elements to create a choice architecture that can guide user behavior in digital environments. While promising in many fields, there is a notable gap in health promotion, particularly because digital nudges and recommender systems can encourage and support sustained healthier choices in nutrition, physical activity (PA), and sedentary behavior reduction to prevent overweight and obesity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This scoping review addresses these gaps by exploring how digital nudges and recommender systems are used in obesity prevention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We prospectively published the scoping review protocol and adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Eligibility was defined using the PCC (Population, Concept, Context) framework. We searched 7 bibliographic databases (MEDLINE and PsycINFO via Ovid, Web of Science, CINAHL via EBSCO, Scopus, ACM Digital Library, and IEEE Xplore) up to October 2023. Following a 2-stage screening by independent reviewers, we selected 68 articles that included 94 user evaluations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Most articles (36\/68, 53%) report on recommender systems focused on nutrition, with fewer (16\/68, 23%) aiming to promote PA. Most studies on digital nudges (11\/68, 16%) targeted nutrition-related nudges for shopping and meal selection (8\/68, 2%). Articles address PA and sedentary behavior less frequently (3\/68, 4%). Three out of 68 (4%) articles report on recommender systems in combination with games, and 2 out of 68 (3%) articles report on recommender systems and digital nudges. Approaches to item retrieval vary widely, with 31 out of 68 (46%) articles failing to describe their methods. In the scoping review, we found a discrepancy between the target group for which the system was developed and the group with which the evaluation was conducted. Sixty-eight evaluations report positive results, while 26 studies report mixed, negative, or no-difference results.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Integrating digital nudges and recommender systems might hold potential in overweight and obesity prevention by subtly encouraging healthier lifestyle choices. However, the heterogeneity in study designs, outcome measures, and reporting quality limits the comparability of findings and makes it difficult to draw robust conclusions about effectiveness. Future work should include detailed definitions, mechanism descriptions, broader geographic representation, and rigorous intervention testing and user evaluations to fully leverage these systems for improved health outcomes and to support sustainability and well-being objectives.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/73151","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T19:12:32Z","timestamp":1776453152000},"page":"e73151-e73151","source":"Crossref","is-referenced-by-count":0,"title":["Mapping Digital Nudges and Recommender Systems for Obesity Prevention: Scoping Review"],"prefix":"10.2196","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7169-675X","authenticated-orcid":false,"given":"Sarah","family":"Forberger","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5731-4209","authenticated-orcid":false,"given":"Lucia A","family":"Reisch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5197-3986","authenticated-orcid":false,"given":"Pieter","family":"Van Gorp","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9489-2385","authenticated-orcid":false,"given":"Christoph","family":"Stahl","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7780-255X","authenticated-orcid":false,"given":"Lara","family":"Christianson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8476-2513","authenticated-orcid":false,"given":"Jihan","family":"Halimi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7647-6767","authenticated-orcid":false,"given":"Karina Karolina","family":"De Santis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2048-9352","authenticated-orcid":false,"given":"Chungwan","family":"Lo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7693-323X","authenticated-orcid":false,"given":"Cassandra A","family":"Omane","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0355-803X","authenticated-orcid":false,"given":"Alejandra","family":"Loyola-Leyva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6601-5630","authenticated-orcid":false,"given":"Laurent","family":"Malisoux","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5480-183X","authenticated-orcid":false,"given":"Tiziana","family":"de-Magistris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7825-0697","authenticated-orcid":false,"given":"Torsten","family":"Bohn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,4,17]]},"reference":[{"key":"R1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122166","article-title":"A systematic review on food recommender systems","volume":"238","author":"Bondevik","journal-title":"Expert Syst Appl"},{"issue":"22","key":"R2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph192215115","article-title":"Health recommender systems development, usage, and evaluation from 2010 to 2022: a scoping review","volume":"19","author":"Cai","journal-title":"Int J Environ Res Public Health"},{"key":"R3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2025.100849","article-title":"A comprehensive review of recommender systems: transitioning from theory to practice","volume":"59","author":"Raza","journal-title":"Comput Sci Rev"},{"issue":"12","key":"R4","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1145\/138859.138867","article-title":"Using collaborative filtering to weave an information tapestry","volume":"35","author":"Goldberg","journal-title":"Commun ACM"},{"issue":"1","key":"R5","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1016\/j.eswa.2004.08.013","article-title":"A hybrid collaborative filtering method for multiple-interests and multiple-content recommendation in e-commerce","volume":"28","author":"Li","journal-title":"Expert Syst Appl"},{"key":"R6","doi-asserted-by":"crossref","unstructured":"Pincay J Teran L Portmann E . Health recommender systems: a state-of-the-art review. Presented at: 2019 Sixth International Conference on eDemocracy & eGovernment (ICEDEG); Apr 24-26, 2019; Quito, Ecuador. [doi: 10.1109\/ICEDEG.2019.8734362]","DOI":"10.1109\/ICEDEG.2019.8734362"},{"key":"R7","doi-asserted-by":"publisher","DOI":"10.1016\/j.chbr.2020.100052","article-title":"Digital nudging with recommender systems: survey and future directions","volume":"3","author":"Jesse","journal-title":"Comput Hum Behav Rep"},{"key":"R8","unstructured":"Mirsch T Lehrer C Jung R , editors. Digital nudging: altering user behavior in digital environments. Presented at: Proceedings der 13 Internationalen Tagung Wirtschaftsinformatik; Feb 12-15, 2017:634-648; St Gallen, Switzerland. URL: https:\/\/aisel.aisnet.org\/cgi\/viewcontent.cgi?referer=&httpsredir=1&article=1076&context=wi2017 [Accessed 09-03-2026]"},{"key":"R9","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445555","article-title":"From reflection to action: combining machine learning with expert knowledge for nutrition goal recommendations","volume":"2021","author":"Mitchell","journal-title":"Proc SIGCHI Conf Hum Factor Comput Syst"},{"issue":"5","key":"R10","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1002\/bdm.1897","article-title":"A review and taxonomy of choice architecture techniques","volume":"29","author":"M\u00fcnscher","journal-title":"Behav Decis Mak"},{"issue":"6","key":"R11","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1007\/s12599-016-0453-1","article-title":"Digital nudging","volume":"58","author":"Weinmann","journal-title":"Bus Inf Syst Eng"},{"key":"R12","doi-asserted-by":"crossref","unstructured":"Dalecke S Karlsen R . Designing dynamic and personalized nudges. Presented at: Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics (WIMS 2020); Jun 30 to Jul 3, 2020; Biarritz, France. [doi: 10.1145\/3405962.3405975]","DOI":"10.1145\/3405962.3405975"},{"key":"R13","doi-asserted-by":"crossref","unstructured":"Bergram K Djokovic M Bezen\u00e7on V Holzer A . The digital landscape of nudging: a systematic literature review of empirical research on digital nudges. Presented at: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems; Apr 29 to May 5, 2022; New Orleans, Louisiana, USA. [doi: 10.1145\/3491102.3517638]","DOI":"10.1145\/3491102.3517638"},{"key":"R14","doi-asserted-by":"crossref","unstructured":"Decrinis L Reisch LA . Nudging employees for corporate sustainability: a systematic evidence map. In: Sunstein CR , editor. Research Handbook on Nudges and Society. Edward Elgar Publishing; 2023:152-173. [doi: 10.4337\/9781035303038.00017] ISBN: 9781035303021","DOI":"10.4337\/9781035303038.00017"},{"issue":"1","key":"R15","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1145\/3715966.3715973","article-title":"Digital nudging: a systematic literature review, taxonomy, and future research directions","volume":"56","author":"Valta","journal-title":"ACM SIGMIS Database"},{"key":"R16","doi-asserted-by":"publisher","DOI":"10.1016\/j.socec.2019.03.005","article-title":"How effective is nudging? A quantitative review on the effect sizes and limits of empirical nudging studies","volume":"80","author":"Hummel","journal-title":"J Behav Exp Econ"},{"key":"R17","unstructured":"World obesity atlas 2024. World Obesity Federation; 2024. URL: https:\/\/data.worldobesity.org\/publications\/WOF-Obesity-Atlas-v7.pdf [Accessed 09-06-2026]"},{"key":"R18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2890388","article-title":"Scientific paper recommendation: a survey","volume":"7","author":"Bai","journal-title":"IEEE Access"},{"key":"R19","doi-asserted-by":"crossref","unstructured":"Feng J Wei C Jiang S Zhou M Cao X Pogue B et al. MRI guided wearable near infrared spectral tomography: simulation study. Presented at: SPIE Photonics West \u2013 BiOS: Biomedical Optics Symposium; Mar 6-11, 2021. [doi: 10.1117\/12.2578356]","DOI":"10.1117\/12.2578356"},{"issue":"3","key":"R20","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1007\/s10844-017-0469-0","article-title":"An overview of recommender systems in the healthy food domain","volume":"50","author":"Trang Tran","journal-title":"J Intell Inf Syst"},{"key":"R21","unstructured":"Castmo M Persson R . The alliance between digital nudging & persuasive design [Master\u2019s Thesis]. Lund University, School of Economics and Management; 2018. URL: https:\/\/www.lunduniversity.lu.se\/lup\/publication\/8950219 [Accessed 09-03-2026]"},{"key":"R22","doi-asserted-by":"crossref","unstructured":"Caraban A Karapanos E Gon\u00e7alves D . 23 ways to nudge: a review of technology-mediated nudging in human-computer interaction. Presented at: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI \u201919); May 4-9, 2019; Glasgow, Scotland, UK. [doi: 10.1145\/3290605.3300733]","DOI":"10.1145\/3290605.3300733"},{"issue":"1","key":"R23","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.joep.2011.10.009","article-title":"Influencing behaviour: the mindspace way","volume":"33","author":"Dolan","journal-title":"J Econ Psychol"},{"key":"R24","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-psych-081914-124745","article-title":"The council of psychological advisers","volume":"67","author":"Sunstein","journal-title":"Annu Rev Psychol"},{"key":"R25","doi-asserted-by":"publisher","DOI":"10.1177\/20503121251348374","article-title":"Recommender systems for obesity prevention: scoping review of reviews","volume":"13","author":"De Santis","journal-title":"SAGE Open Med"},{"issue":"6","key":"R26","doi-asserted-by":"publisher","first-page":"591","DOI":"10.31661\/jbpe.v0i0.1248","article-title":"A systematic review of nutrition recommendation systems: with focus on technical aspects","volume":"9","author":"Abhari","journal-title":"J Biomed Phys Eng"},{"issue":"2","key":"R27","volume":"11","author":"Azmi","journal-title":"Int J Advance Soft Compu Appl"},{"issue":"6","key":"R28","doi-asserted-by":"publisher","DOI":"10.2196\/18035","article-title":"Health recommender systems: systematic review","volume":"23","author":"De Croon","journal-title":"J Med Internet Res"},{"key":"R29","doi-asserted-by":"crossref","unstructured":"Ferretto LR Cervi CR de Marchi ACB . Recommender systems in mobile apps for health a systematic review. Presented at: 2017 12th Iberian Conference on Information Systems and Technologies (CISTI); Jun 21-24, 2017; Lisbon, Portugal. [doi: 10.23919\/CISTI.2017.7975743]","DOI":"10.23919\/CISTI.2017.7975743"},{"key":"R30","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104365","article-title":"Precision nutrition: a systematic literature review","volume":"133","author":"Kirk","journal-title":"Comput Biol Med"},{"issue":"24","key":"R31","doi-asserted-by":"publisher","first-page":"12069","DOI":"10.3390\/app112412069","article-title":"Systematic review of nutritional recommendation systems","volume":"11","author":"Orue-Saiz","journal-title":"Appl Sci (Basel)"},{"key":"R32","doi-asserted-by":"publisher","DOI":"10.1016\/j.tifs.2022.10.018","article-title":"Digital nudging in online grocery stores: a scoping review on current practices and gaps","volume":"131","author":"Valen\u010di\u010d","journal-title":"Trends Food Sci Technol"},{"issue":"5","key":"R33","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph20054248","article-title":"A systematic review on food recommender systems for diabetic patients","volume":"20","author":"Yera","journal-title":"Int J Environ Res Public Health"},{"key":"R34","doi-asserted-by":"publisher","DOI":"10.1016\/j.ypmed.2021.106922","article-title":"Nudges used to promote physical activity and to reduce sedentary behaviour in the workplace: results of a scoping review","volume":"155","author":"Forberger","journal-title":"Prev Med"},{"key":"R35","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2024.1304439","article-title":"Knowledge-based recommender systems: overview and research directions","volume":"7","author":"Uta","journal-title":"Front Big Data"},{"key":"R36","doi-asserted-by":"publisher","DOI":"10.2196\/38184","article-title":"Development and evaluation of health recommender systems: systematic scoping review and evidence mapping","volume":"25","author":"Sun","journal-title":"J Med Internet Res"},{"issue":"7","key":"R37","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2023-080644","article-title":"'Let me recommend\u2026 ': use of digital nudges or recommender systems for overweight and obesity prevention-a scoping review protocol","volume":"14","author":"Forberger","journal-title":"BMJ Open"},{"issue":"7","key":"R38","doi-asserted-by":"publisher","first-page":"467","DOI":"10.7326\/M18-0850","article-title":"PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation","volume":"169","author":"Tricco","journal-title":"Ann Intern Med"},{"issue":"4","key":"R39","doi-asserted-by":"publisher","first-page":"2102","DOI":"10.1111\/jan.14743","article-title":"Undertaking a scoping review: a practical guide for nursing and midwifery students, clinicians, researchers, and academics","volume":"77","author":"Pollock","journal-title":"J Adv Nurs"},{"issue":"1","key":"R40","doi-asserted-by":"publisher","DOI":"10.1186\/s12966-017-0525-8","article-title":"Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome","volume":"14","author":"Tremblay","journal-title":"Int J Behav Nutr Phys Act"},{"key":"R41","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2018.00288","article-title":"Physical activity, inactivity, and sedentary behaviors: definitions and implications in occupational health","volume":"6","author":"Thivel","journal-title":"Front Public Health"},{"issue":"1","key":"R42","doi-asserted-by":"publisher","DOI":"10.1186\/s12966-022-01380-3","article-title":"Device-measured physical activity and sedentary time in a national sample of Luxembourg residents: the ORISCAV-LUX 2 study","volume":"19","author":"Collings","journal-title":"Int J Behav Nutr Phys Act"},{"key":"R43","unstructured":"Peters MDJ Godfrey CM McInerney P . Search strategy. In: The Joanna Briggs Institute Reviewers\u2019 Manual 2015: Methodology for JBI Scoping Reviews. Joanna Briggs Institute; 2015:13-14. URL: https:\/\/www.researchgate.net\/publication\/294736492_Methodology_for_JBI_Scoping_Reviews [Accessed 25-03-2026]"},{"key":"R44","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2016.01.021","article-title":"PRESS Peer Review of Electronic Search Strategies: 2015 guideline statement","volume":"75","author":"McGowan","journal-title":"J Clin Epidemiol"},{"key":"R45","doi-asserted-by":"crossref","unstructured":"Calvaresi D Eggenschwiler S Calbimonte JP Manzo G Schumacher M . A personalized agent-based chatbot for nutritional coaching. Presented at: IEEE\/WIC\/ACM International Conference on Web Intelligence (WI 2021); Dec 14-17, 2021:682-687; Melbourne, Australia. [doi: 10.1145\/3486622.3493992]","DOI":"10.1145\/3486622.3493992"},{"key":"R46","doi-asserted-by":"crossref","unstructured":"Jannach D Zanker M Felfernig A Friedrich G . Content-based recommendation. In: Jannach D Zanker M Felfernig A Friedrich G , editors. Recommender Systems: An Introduction. Cambridge University Press; 2010:51-80. [doi: 10.1017\/CBO9780511763113.005] ISBN: 9780511763113","DOI":"10.1017\/CBO9780511763113"},{"key":"R47","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4939-1985-7_9","article-title":"Introduction on health recommender systems","volume":"1246","author":"Sanchez-Bocanegra","journal-title":"Methods Mol Biol"},{"key":"R48","doi-asserted-by":"crossref","unstructured":"Jannach D Zanker M Felfernig A Friedrich G . Collaborative recommendation. In: Jannach D Zanker M Felfernig A Friedrich G , editors. Recommender Systems: An Introduction. Cambridge University Press; 2010:13-50. [doi: 10.1017\/CBO9780511763113.004] ISBN: 9780511763113","DOI":"10.1017\/CBO9780511763113"},{"key":"R49","unstructured":"De Santis KK Stiens L Christianson L et al. What do we know about recommender systems for obesity prevention? Scoping review of reviews within a project HealthyW8 [Poster] [Article in German]. Presented at: Gesundheit \u2013 Gemeinsam, Kooperationstagung Der Deutschen Gesellschaft F\u00fcr Medizinische Informatik, Biometrie Und Epidemiologie (GMDS), Deutschen Gesellschaft F\u00fcr Sozialmedizin Und Pr\u00e4vention (DGSMP), Deutschen Gesellschaft F\u00fcr Epidemiologie (DGEpi), Deutschen Gesellschaft F\u00fcr Medizinische Soziologie (DGMS). Sep 8-13, 2024:Dresden. 8-13; Deutsches Hygiene\u2011Museum Dresden, Dresden, Germany. URL: https:\/\/www.egms.de\/de\/meetings\/gmds2024\/ [Accessed 25-03-2026]"},{"key":"R50","doi-asserted-by":"crossref","unstructured":"Abbas F Najjar N Wilson D . The bites eclectic: critique-based conversational recommendation for diversity-focused meal planning. Presented at: International Conference on Case\u2011Based Reasoning (ICCBR 2021); Sep 13-16, 2021:1-16; Salamanca, Spain. [doi: 10.1007\/978-3-030-86957-1_1]","DOI":"10.1007\/978-3-030-86957-1_1"},{"issue":"1S","key":"R51","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2808207","article-title":"Supporting healthy grocery shopping via mobile augmented reality","volume":"12","author":"Ahn","journal-title":"ACM Trans Multimedia Comput Commun Appl"},{"key":"R52","doi-asserted-by":"crossref","unstructured":"Chao WY Hass Z Gao Q Zhou J . Choice-based user interface design of a smart healthy food recommender system for nudging eating behavior of older adult patients with newly diagnosed type II diabetes. Presented at: 6th International Conference, ITAP 2020, Held as Part of the 22nd HCI International Conference, HCII 2020; Jul 19-24, 2020:221-234; Copenhagen, Denmark. [doi: 10.1007\/978-3-030-50249-2_17]","DOI":"10.1007\/978-3-030-50249-2_17"},{"key":"R53","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2016.07.003","article-title":"Social networks for improving healthy weight loss behaviors for overweight and obese adults: a randomized clinical trial of the social pounds off digitally (Social POD) mobile app","volume":"94","author":"Hales","journal-title":"Int J Med Inform"},{"key":"R54","doi-asserted-by":"crossref","unstructured":"He Q Agu E . On11: an activity recommendation application to mitigate sedentary lifestyle. Presented at: Proceedings of the 2014 Workshop on Physical Analytics (WPA \u201914); Jun 14, 2014:3-8; Bretton Woods, New Hampshire, USA. [doi: 10.1145\/2611264.2611268]","DOI":"10.1145\/2611264.2611268"},{"key":"R55","doi-asserted-by":"crossref","unstructured":"DiCosola BM Neff G . Nudging behavior change: using in-group and out-group social comparisons to encourage healthier choices. Presented at: 2022 CHI Conference on Human Factors in Computing Systems (CHI \u201922); Apr 30 to May 5, 2022; New Orleans, Louisiana, USA. [doi: 10.1145\/3491102.3502088]","DOI":"10.1145\/3491102.3502088"},{"key":"R56","doi-asserted-by":"crossref","unstructured":"Rabbi M Aung MH Zhang M Choudhury T Acm D et al. MyBehavior: automatic personalized health feedback from user behaviors and preferences using smartphones. Presented at: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2015); Sep 7, 2015 to Sep 11, 2025:707-718; Osaka, Japan. [doi: 10.1145\/2750858.2805840]","DOI":"10.1145\/2750858.2805840"},{"key":"R57","unstructured":"Sengupta A Bhattacherjee A Dutta K Beckie T . Information technology interventions in cardiac rehabilitation: a theory driven approach. Presented at: International Conference on Information Systems (ICIS 2020); Dec 13, 2020 to Dec 16, 2022; Hyderabad, India. URL: https:\/\/aisel.aisnet.org\/icis2020\/is_health\/is_health\/18\/ [Accessed 09-03-2026]"},{"issue":"1","key":"R58","doi-asserted-by":"publisher","DOI":"10.1145\/3072614","article-title":"Yum-Me: a personalized nutrient-based meal recommender system","volume":"36","author":"Yang","journal-title":"ACM Trans Inf Syst"},{"key":"R59","unstructured":"Berger M N\u00fcske N M\u00fcller C . Digital nudging in online grocery stores - towards ecologically sustainable nutrition. Presented at: 41st International Conference on Information Systems (ICIS 2020); Dec 13-16, 2020; Hyderabad, India. URL: https:\/\/aisel.aisnet.org\/icis2020\/societal_impact\/societal_impact\/11\/ [Accessed 09-03-2026]"},{"key":"R60","doi-asserted-by":"crossref","unstructured":"Cromjongh R Reenen QV K\u00f6nig L et al. Group adapted avatar recommendations for exergames. Presented at: 31st ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2023); Jun 26-29, 2023:283-290; Limassol, Cyprus. [doi: 10.1145\/3563359.3597389]","DOI":"10.1145\/3563359.3597389"},{"key":"R61","doi-asserted-by":"crossref","unstructured":"Elsweiler D Trattner C Harvey M . Exploiting food choice biases for healthier recipe recommendation. Presented at: 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017); Aug 7-11, 2017:575-584; Tokyo, Japan. [doi: 10.1145\/3077136.3080826]","DOI":"10.1145\/3077136.3080826"},{"key":"R62","doi-asserted-by":"crossref","unstructured":"Starke A Asotic E Trattner C . \u201cServing each user\u201d: supporting different eating goals through a multi-list recommender interface. Presented at: Fifteenth ACM Conference on Recommender Systems (RecSys \u201921); Sep 27 to Oct 1, 2021; Amsterdam, Netherlands. [doi: 10.1145\/3460231.3474232]","DOI":"10.1145\/3460231.3474232"},{"key":"R63","unstructured":"Starke A El Majjodi A Trattner C Brusilovsky P Gemmis M Felfernig A et al. Boosting health? examining the role of nutrition labels and preference elicitation methods in food recommendation. Presented at: 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2022); Sep 22, 2022:67-84; Seattle, Washington, United States."},{"issue":"4","key":"R64","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3581930","article-title":"Examining the user evaluation of multi\u2011list recommender interfaces in the context of healthy recipe choices","volume":"1","author":"Starke","journal-title":"ACM Trans Recomm Syst"},{"key":"R65","doi-asserted-by":"crossref","unstructured":"Starke AD Brynestad EKK Hauge S L\u00f8keland LS . Nudging healthy choices in food search through list re-ranking. Presented at: 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2021); Jun 26-29, 2021:293-298; [doi: 10.1145\/3450614.3464621]","DOI":"10.1145\/3450614.3464621"},{"issue":"5","key":"R66","doi-asserted-by":"publisher","first-page":"923","DOI":"10.1007\/s11257-021-09301-y","article-title":"Effects and challenges of using a nutrition assistance system: results of a long-term mixed-method study","volume":"32","author":"Hauptmann","journal-title":"User Model User-Adap Inter"},{"key":"R67","unstructured":"Leipold N Madenach M Sch\u00e4fer H Lurz M Terzimehi\u0107 N Groh G et al. Nutrilize a personalized nutrition recommender system: an enable study. Presented at: 3rd International Workshop on Health Recommender Systems (HealthRecSys 2018); Oct 6, 2018:24-29; Vancouver, Canada. URL: https:\/\/ceur-ws.org\/Vol-2216\/healthRecSys18_paper_5.pdf [Accessed 09-03-2026]"},{"key":"R68","doi-asserted-by":"crossref","unstructured":"Lin Y Jessurun J Vries B Timmermans H . Motivate: towards context-aware recommendation mobile system for healthy living. Presented at: 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops; May 23-26, 2011:250-253; Dublin, Ireland. [doi: 10.4108\/icst.pervasivehealth.2011.246030]","DOI":"10.4108\/icst.pervasivehealth.2011.246030"},{"issue":"5","key":"R69","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1080\/0960085X.2023.2229787","article-title":"Salience, transparency, and self-nudging: a digital nudge to promote healthier food product choices","volume":"33","author":"Michels","journal-title":"Eur J Inf Syst"},{"key":"R70","doi-asserted-by":"publisher","DOI":"10.1016\/j.ahj.2023.04.001","article-title":"Digital Health Nudging to increase physical activity in pediatric patients with congenital heart disease: a randomized controlled trial","volume":"262","author":"Willinger","journal-title":"Am Heart J"},{"key":"R71","doi-asserted-by":"publisher","DOI":"10.3389\/fspor.2022.1024996","article-title":"Nudging digital physical activity breaks for home studying of university students-a randomized controlled trial during the COVID-19 pandemic with daily activity measures","volume":"4","author":"Teuber","journal-title":"Front Sports Act Living"},{"key":"R72","doi-asserted-by":"crossref","unstructured":"Sch\u00e4fer H Willemsen MC . Rasch-based tailored goals for nutrition assistance systems. Presented at: 24th International Conference on Intelligent User Interfaces (IUI 2019); Mar 17-20, 2019; Los Angeles, California, USA. [doi: 10.1145\/3301275.3302298]","DOI":"10.1145\/3301275.3302298"},{"key":"R73","doi-asserted-by":"publisher","DOI":"10.1016\/j.foodqual.2021.104384","article-title":"Healthy or not: influencing attention to bias food choices","volume":"96","author":"Schomaker","journal-title":"Food Qual Prefer"},{"issue":"1","key":"R74","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1007\/s11257-023-09368-9","article-title":"Connecting physical activity with context and motivation: a user study to define variables to integrate into mobile health recommenders","volume":"34","author":"Coppens","journal-title":"User Model User-Adap Inter"},{"key":"R75","doi-asserted-by":"crossref","unstructured":"Coppens I Martens L De Pessemier T . Motivating people to move more with personalized activity and tip recommendations: a randomized controlled trial. Presented at: IUI \u201923 Companion: Companion Proceedings of the 28th International Conference on Intelligent User Interfaces; Mar 27-31, 2023:123-126; Sydney, New South Wales, Australia. [doi: 10.1145\/3581754.3584149]","DOI":"10.1145\/3581754.3584149"},{"key":"R76","doi-asserted-by":"crossref","unstructured":"Coppens I Martens L Pessemier TD . Analyzing accuracy versus diversity in a health recommender system for physical activities: a longitudinal user study. Presented at: Proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023); Sep 18-22, 2023:1146-1151; Singapore, Singapore. [doi: 10.1145\/3604915.3610650]","DOI":"10.1145\/3604915.3610650"},{"key":"R77","doi-asserted-by":"publisher","DOI":"10.1016\/j.appet.2022.105971","article-title":"Digital nudges to stimulate healthy and pro-environmental food choices in E-groceries","volume":"172","author":"De Bauw","journal-title":"Appetite"},{"key":"R78","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-023-04909-6","article-title":"Recipe recommendations for individual users and groups in a cooking assistance app","volume":"53","author":"Vanhecke","journal-title":"Appl Intell"},{"key":"R79","unstructured":"Guti\u00e9rrez F Cardoso B Verbert K et al. PHARA: a personal health augmented reality assistant to support decision-making at grocery stores. Presented at: 2nd International Workshop on Health Recommender Systems (HealthRecSys\u201917); Aug 31, 2017:10-13; Como, Italy. URL: https:\/\/ceur-ws.org\/Vol-1953\/healthRecSys17_paper_7.pdf [Accessed 09-03-2026]"},{"key":"R80","unstructured":"Castiglia G El Majjodi A Cal\u00f2 F Deldjoo Y Narducci F Starke A et al. Nudging towards health in a conversational food recommender system using multi-modal interactions and nutrition labels. Presented at: 4th Edition of Knowledge-aware and Conversational Recommender Systems (KaRS) Workshop @ RecSys 2022; Sep 18-23, 2022:29-35; Seattle, Washington, USA. URL: https:\/\/ceur-ws.org\/Vol-3294\/long1.pdf [Accessed 09-03-2026]"},{"key":"R81","unstructured":"Elahi M Ge M Ricci F Fern\u00e1ndez-Tob\u00edas I Berkovsky S David M et al. Interaction design in a mobile food recommender system. Presented at: 9th ACM Conference on Recommender Systems (RecSys 2015); Sep 16-20, 2015:49-52; Vienna, Austria. URL: https:\/\/shlomo-berkovsky.github.io\/files\/pdf\/RecSys15c.pdf [Accessed 09-03-2026]"},{"key":"R82","doi-asserted-by":"crossref","unstructured":"Massimo D Elahi M Ricci F Ge M . Item contents good, user tags better: empirical evaluation of a food recommender system. Presented at: 25th Conference on User Modeling, Adaptation and Personalization (UMAP 2017); Jul 3-12, 2017:373-374; Bratislava, Slovakia. [doi: 10.1145\/3079628.3079640]","DOI":"10.1145\/3079628.3079640"},{"key":"R83","doi-asserted-by":"crossref","unstructured":"Musto C Starke AD Trattner C Rapp A Semeraro G . Exploring the effects of natural language justifications in food recommender systems. Presented at: Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP \u201921); Jun 21-25, 2021:147-157; Utrecht, Netherlands. [doi: 10.1145\/3450613.3456827]","DOI":"10.1145\/3450613.3456827"},{"key":"R84","doi-asserted-by":"crossref","unstructured":"Musto C Trattner C Starke A Semeraro G . Towards a knowledge-aware food recommender system exploiting holistic user models. Presented at: 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2020); Jul 14-17, 2020:333-337; Genoa (Genova), Italy. [doi: 10.1145\/3340631.3394880]","DOI":"10.1145\/3340631.3394880"},{"issue":"3","key":"R85","doi-asserted-by":"publisher","first-page":"779","DOI":"10.3390\/ejihpe10030057","article-title":"A mobile-based tailored recommendation system for parents of children with overweight or obesity: a new tool for health care centers","volume":"10","author":"Afonso","journal-title":"Eur J Investig Health Psychol Educ"},{"issue":"20","key":"R86","doi-asserted-by":"publisher","DOI":"10.3390\/s19204531","article-title":"PHAROS 2.0-A PHysical Assistant RObot System improved","volume":"19","author":"Martinez-Martin","journal-title":"Sensors (Basel)"},{"key":"R87","doi-asserted-by":"crossref","unstructured":"Ribeiro D Machado J Ribeiro J Vasconcelos MJM Vieira EF Barros AC et al. SousChef: mobile meal recommender system for older adults. Presented at: Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2017); Feb 21-23, 2017:36-45; Porto, Portugal. [doi: 10.5220\/0006281900360045]","DOI":"10.5220\/0006281900360045"},{"key":"R88","doi-asserted-by":"crossref","unstructured":"Samagaio AM Cardoso HL Ribeiro D Univ Porto F Fraunhofer Portugal PP Lab Inteligencia A et al. A chatbot for recipe recommendation and preference modeling. Presented at: 20th EPIA Conference on Artificial Intelligence (EPIA 2021); Sep 7-9, 2021:389-402; Virtual event. [doi: 10.1007\/978-3-030-86230-5_31]","DOI":"10.1007\/978-3-030-86230-5_31"},{"issue":"11","key":"R89","doi-asserted-by":"publisher","first-page":"638","DOI":"10.14569\/IJACSA.2021.0121173","article-title":"Ontology-based daily menu recommendation system for complementary food according to nutritional needs using na\u00efve Bayes and TOPSIS","volume":"12","author":"Showafah","journal-title":"Int J Adv Comput Sci Appl"},{"issue":"10","key":"R90","first-page":"466","volume":"21","author":"Norouzi","journal-title":"Arch Iran Med"},{"key":"R91","doi-asserted-by":"crossref","unstructured":"Thongyoo P Anantapanya P Jamsri P Chotipant S . A personalized food recommendation chatbot system for diabetes patients. Presented at: 17th International Conference of Cooperative Design, Visualization, and Engineering (CDVE 2020); Oct 25-28, 2020:19-28; Bangkok, Thailand. [doi: 10.1007\/978-3-030-60816-3_3]","DOI":"10.1007\/978-3-030-60816-3_3"},{"key":"R92","doi-asserted-by":"crossref","unstructured":"Sookrah R Dhowtal JD Devi Nagowah S . A DASH diet recommendation system for hypertensive patients using machine learning. Presented at: 7th International Conference on Information and Communication Technology (ICoICT 2019); Jul 24-26, 2019; Kuala Lumpur, Malaysia. [doi: 10.1109\/ICoICT.2019.8835323]","DOI":"10.1109\/ICoICT.2019.8835323"},{"key":"R93","doi-asserted-by":"crossref","unstructured":"Giabbanelli PJ Deck P Andres L Schiphorst T Finegood DT . Supporting a participant-centric management of obesity via a self-improving health game. Presented at: 22nd International Conference on Human\u2011Computer Interaction (HCI International 2013) \u2014 Healthcare and Safety of the Environment and Transport track; Jul 21-26, 2013:189-196; Las Vegas, Nevada, USA. [doi: 10.1007\/978-3-642-39173-6_23]","DOI":"10.1007\/978-3-642-39173-6_23"},{"issue":"16","key":"R94","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17165763","article-title":"Pilot testing of a nudge-based digital intervention (Welbot) to improve sedentary behaviour and wellbeing in the workplace","volume":"17","author":"Haile","journal-title":"Int J Environ Res Public Health"},{"issue":"13","key":"R95","doi-asserted-by":"publisher","DOI":"10.3390\/s20133778","article-title":"Health promotion for childhood obesity: an approach based on self-tracking of data","volume":"20","author":"G\u00f3mez-Del-R\u00edo","journal-title":"Sensors (Basel)"},{"key":"R96","unstructured":"Alcaraz-Herrera H Palomares I Elsweiler D Ludwig B Said A Schafer H et al. Evolutionary approach for 'healthy bundle' wellbeing recommendations. Presented at: Proceedings of the 4th International Workshop on Health Recommender Systems co-located with 13th ACM Conference on Recommender Systems (HealthRecSys\u201919); Sep 16-20, 2019:18-23; Copenhagen, Denmark. 2019.URL: https:\/\/ceur-ws.org\/Vol-2439\/5-paginated.pdf [Accessed 09-03-2026]"},{"key":"R97","doi-asserted-by":"crossref","unstructured":"Li J Zhang H He Z et al. LifeRec: a mobile app for lifelog recording and ubiquitous recommendation. Presented at: CHIIR 2022 \u2013 Conference on Human Information Interaction and Retrieval; Mar 14-18, 2022; Regensburgm, Germany. [doi: 10.1145\/3498366.3505837]","DOI":"10.1145\/3498366.3505837"},{"issue":"6","key":"R98","doi-asserted-by":"publisher","first-page":"2434","DOI":"10.5370\/JEET.2015.10.6.2434","article-title":"Individualized exercise and diet recommendations: an expert system for monitoring physical activity and lifestyle interventions in obesity","volume":"10","author":"Nam","journal-title":"J Electr Eng Technol"},{"issue":"6","key":"R99","doi-asserted-by":"publisher","first-page":"2783","DOI":"10.1007\/s40815-022-01286-z","article-title":"F\u2011EvoRecSys: an extended framework for personalized well\u2011being recommendations guided by fuzzy inference and evolutionary computing","volume":"24","author":"Palomares","journal-title":"Int J Fuzzy Syst"},{"key":"R100","doi-asserted-by":"crossref","unstructured":"Svensson M H\u00f6\u00f6k K C\u00f6ster R . Evaluating social trails. Presented at: ACM CHI 2003 \u2013 Conference on Human Factors in Computing Systems; Apr 5-10, 2003:844-845; Ft Lauderdale, Florida, USA. [doi: 10.1145\/765891.766026]","DOI":"10.1145\/765891.766026"},{"key":"R101","doi-asserted-by":"crossref","unstructured":"Abdool H Pooransingh A Li Y . Recommend my dish: a multi-sensory food recommender. Presented at: IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM 2015); Aug 24, 2015; Victoria, BC, Canada. [doi: 10.1109\/PACRIM.2015.7334841]","DOI":"10.1109\/PACRIM.2015.7334841"},{"key":"R102","unstructured":"Khan MA Rushe E Smyth B Coyle D Elsweiler D Ludwig B et al. Personalized, health-aware recipe recommendation: an ensemble topic modeling based approach. Presented at: HealthRecSys 2019 \u2013 4th Workshop on Health Recommender Systems; Sep 20, 2019:4-10; Copenhagen, Denmark. URL: https:\/\/ceur-ws.org\/Vol-2439\/3-paginated.pdf [Accessed 09-03-2026]"},{"issue":"2","key":"R103","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s10844-021-00639-8","article-title":"Addressing the complexity of personalized, context-aware and health-aware food recommendations: an ensemble topic modelling based approach","volume":"57","author":"Khan","journal-title":"J Intell Inf Syst"},{"key":"R104","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2021.733835","article-title":"Designing persuasive food conversational recommender systems with nudging and socially-aware conversational strategies","volume":"8","author":"Pecune","journal-title":"Front Robot AI"},{"key":"R105","doi-asserted-by":"crossref","unstructured":"Grace K Finch E Gulbransen-Diaz N Henderson H . Q-chef: the impact of surprise-eliciting systems on food-related decision-making. Presented at: CHI 2022 \u2013 Conference on Human Factors in Computing Systems; Apr 30 to May 5, 2020; New Orleans, Louisiana, USA. [doi: 10.1145\/3491102.3501862]","DOI":"10.1145\/3491102.3501862"},{"key":"R106","doi-asserted-by":"crossref","unstructured":"Ozeki S Kotera M Ishiguro K Nishimura T Higuchi K . Recipe recommendation for balancing ingredient preference and daily nutrients. Presented at: Proceedings of the 1st International Workshop on Multimedia for Cooking, Eating, and related APPlications (CEA 2022), co-located with ACM Multimedia 2022 (MM \u201922); Oct 10, 2022:11-19; Lisbon, Portugal. [doi: 10.1145\/3552485.3554941]","DOI":"10.1145\/3552485.3554941"},{"issue":"9","key":"R107","doi-asserted-by":"publisher","first-page":"3753","DOI":"10.1007\/s10115-023-01897-4","article-title":"FoodRecNet: a comprehensively personalized food recommender system using deep neural networks","volume":"65","author":"Hamdollahi Oskouei","journal-title":"Knowl Inf Syst"},{"issue":"3","key":"R108","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1002\/cb.2129","article-title":"Nudging green food: the effects of a hedonic cue, menu position, a warm\u2010glow cue, and a descriptive norm","volume":"22","author":"Reinholdsson","journal-title":"J Consum Behav"},{"issue":"2","key":"R109","doi-asserted-by":"publisher","first-page":"598","DOI":"10.1016\/j.tjnut.2022.12.022","article-title":"Principles and validations of an artificial intelligence-based recommender system suggesting acceptable food changes","volume":"153","author":"Vandeputte","journal-title":"J Nutr"},{"key":"R110","doi-asserted-by":"crossref","unstructured":"El Majjodi A Starke AD Trattner C . Nudging towards health? Examining the merits of nutrition labels and personalization in a recipe recommender system. Presented at: 30th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2022); Jul 4-7, 2022:48-56; Barcelona, Spain. [doi: 10.1145\/3503252.3531312]","DOI":"10.1145\/3503252.3531312"},{"key":"R111","doi-asserted-by":"crossref","unstructured":"Garcia MB . Plan-cook-eat: a meal planner app with optimal macronutrient distribution of calories based on personal total daily energy expenditure. Presented at: 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM); Nov 29 to Dec 1, 2019; Laoag, Philippines. [doi: 10.1109\/HNICEM48295.2019.9073490]","DOI":"10.1109\/HNICEM48295.2019.9073490"},{"key":"R112","doi-asserted-by":"crossref","unstructured":"Garcia MB Mangaba JB Tanchoco CC . Acceptability, usability, and quality of a personalized daily meal plan recommender system: the case of virtual dietitian. Presented at: 2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM); Dec 28-30, 2021; Manila, Philippines. [doi: 10.1109\/HNICEM54116.2021.9732056]","DOI":"10.1109\/HNICEM54116.2021.9732056"},{"issue":"11","key":"R113","doi-asserted-by":"publisher","DOI":"10.3390\/s21113747","article-title":"Multi-criteria recommendation systems to foster online grocery","volume":"21","author":"Hafez","journal-title":"Sensors (Basel)"},{"key":"R114","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2021.729589","article-title":"Digital nudging for online food choices","volume":"12","author":"Jesse","journal-title":"Front Psychol"},{"key":"R115","unstructured":"Herrmanny K L\u00f6ppenberg S Schwarz M Brusilovsky P Gemmis M Felfernig A et al. Investigating mechanisms for user integration in the activity goal recommendation process by interface design. Presented at: 6th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2019); Sep 19, 2019:46-54; Copenhagen, Denmark. URL: https:\/\/ceur-ws.org\/Vol-2450\/paper6.pdf [Accessed 09-03-2026]"},{"key":"R116","doi-asserted-by":"crossref","unstructured":"Ono S Yotsuya Y Takahashi N Sakamoto T Kato T . Physical-exercise recommendation system based on individual daily schedule. Presented at: 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS); Nov 29 to Dec 2, 2022; Ise, Japan. [doi: 10.1109\/SCISISIS55246.2022.10001861]","DOI":"10.1109\/SCISISIS55246.2022.10001861"},{"issue":"4","key":"R117","doi-asserted-by":"publisher","DOI":"10.2196\/19968","article-title":"Effects of a personalized fitness recommender system using gamification and continuous player modeling: system design and long-term validation study","volume":"8","author":"Zhao","journal-title":"JMIR Serious Games"},{"key":"R118","doi-asserted-by":"publisher","DOI":"10.3389\/frai.2021.621743","article-title":"Nudging healthy choices in food search through visual attractiveness","volume":"4","author":"Starke","journal-title":"Front Artif Intell"},{"key":"R119","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3588663","article-title":"Integrating digital food nudges and recommender systems: current status and future directions","volume":"13","author":"El Majjodi","journal-title":"IEEE Access"},{"issue":"12","key":"R120","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1016\/j.healthpol.2021.10.010","article-title":"The nudge strategies for weight loss in adults with obesity and overweight: a systematic review and meta-analysis","volume":"125","author":"Li","journal-title":"Health Policy"},{"key":"R121","unstructured":"Purohit AK Holzer A , editors. Unhooked by design: scrolling mindfully on social media by automating digital nudges. Presented at: Twenty-Seventh Americas Conference on Information Systems (AMCIS) 2021; Aug 9-13, 2021. URL: https:\/\/libra.unine.ch\/server\/api\/core\/bitstreams\/cd8c2ccf-ca8c-42e9-b3e2-2100acbbe09d\/content [Accessed 09-03-2026]"},{"key":"R122","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2023.1284511","article-title":"Recommender systems for sustainability: overview and research issues","volume":"6","author":"Felfernig","journal-title":"Front Big Data"},{"key":"R123","doi-asserted-by":"crossref","unstructured":"Murphy S\u00d3 Manzano \u00d3 Brown KN , editors. Design and evaluation of a constraint-based energy saving and scheduling recommender system. Presented at: 21st International Conference of Principles and Practice of Constraint Programming (CP 2015); Aug 31 to Sep 4, 2015; Cork, Ireland. [doi: 10.1007\/978-3-319-23219-5_47]","DOI":"10.1007\/978-3-319-23219-5_47"},{"issue":"10","key":"R124","doi-asserted-by":"publisher","DOI":"10.1093\/pnasnexus\/pgae422","article-title":"Choice architecture promotes sustainable choices in online food-delivery apps","volume":"3","author":"Lohmann","journal-title":"PNAS Nexus"},{"key":"R125","doi-asserted-by":"publisher","DOI":"10.1016\/j.foodpol.2022.102298","article-title":"Review: do green defaults reduce meat consumption?","volume":"110","author":"Meier","journal-title":"Food Policy"},{"key":"R126","doi-asserted-by":"publisher","DOI":"10.1017\/bpp.2025.10015","article-title":"META BI: a tool for describing behavioural interventions","author":"Dewies","journal-title":"Behav Public Policy"},{"key":"R127","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2020.123717","article-title":"Mitigating climate change via food consumption and food waste: a systematic map of behavioral interventions","volume":"279","author":"Reisch","journal-title":"J Clean Prod"},{"key":"R128","doi-asserted-by":"publisher","DOI":"10.1057\/s41599-024-03428-0","article-title":"Choice engines and paternalistic AI","volume":"11","author":"Sunstein","journal-title":"Humanit Soc Sci Commun"},{"key":"R129","doi-asserted-by":"publisher","DOI":"10.1007\/s44187-025-00552-x","article-title":"Leveraging LLMs for predictive insights in food policy and behavioral interventions","volume":"5","author":"Kaiser","journal-title":"Discov Food"},{"issue":"3","key":"R130","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1007\/s10844-021-00674-5","article-title":"Towards psychology-aware preference construction in recommender systems: overview and research issues","volume":"57","author":"Atas","journal-title":"J Intell Inf Syst"},{"key":"R131","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2023.1281614","article-title":"An overview of video recommender systems: state-of-the-art and research issues","volume":"6","author":"Lubos","journal-title":"Front Big Data"},{"issue":"3","key":"R132","doi-asserted-by":"publisher","DOI":"10.1111\/obr.13863","article-title":"Recommender systems use in weight management mHealth interventions: a scoping review","volume":"26","author":"de Castro","journal-title":"Obes Rev"},{"issue":"1","key":"R133","doi-asserted-by":"publisher","DOI":"10.1186\/s12966-017-0601-0","article-title":"Is sedentary behaviour just physical inactivity by another name?","volume":"14","author":"van der Ploeg","journal-title":"Int J Behav Nutr Phys Act"}],"container-title":["Interactive Journal of Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.i-jmr.org\/2026\/1\/e73151","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T18:03:41Z","timestamp":1782842621000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.i-jmr.org\/2026\/1\/e73151"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,17]]},"references-count":133,"URL":"https:\/\/doi.org\/10.2196\/73151","relation":{},"ISSN":["1929-073X"],"issn-type":[{"value":"1929-073X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,17]]},"article-number":"v15i22e73151"}}