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Real-world patient outcomes for telehealth-delivered, remote eating disorder treatment: a scoping review | Journal of Eating Disorders | Full Text

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Only 30% of individuals with eating disorders receive specialized treatment. While preliminary evidence suggests that telehealth-delivered, remote eating disorder treatment may offer improved accessibility with similar effectiveness to in-person treatment, research on these services remains limited, particularly regarding the communities that are disproportionately affected by barriers to standard care. This scoping review sought to map the existing research on real-world patient outcomes in remote eating disorder treatment, identify knowledge gaps, and prioritize areas for future studies. This review followed the Joanna Briggs Institute methodology for scoping reviews. It comprises observational evaluations of telehealth-delivered, remote eating disorder treatment conducted in routine clinical settings. An electronic database search was performed in PsycINFO, PubMed, and ProQuest Dissertations & Theses Global in August 2024 and updated in September 2025. Following the search and screening process, 27 articles, comprising six case reports and 21 cohort/case series designs, were deemed eligible for inclusion. Remote treatments evaluated differed across level of care, therapeutic modalities, provider types, dosage, and adjunctive technologies used. Just under half of the studies compared outcomes from remote and in-person treatment, while the remainder examined remote treatment alone. Articles were published between 2011 and 2025 and, when excluding case reports, nearly 60% evaluated programs that rapidly transitioned to remote delivery due to COVID-19. While demographic reporting was limited and inconsistent, available information indicated that participants ranged from three to 75 years old and were predominantly White, cisgender women/females diagnosed with anorexia nervosa. Though preliminary, findings tentatively suggest that remote eating disorder treatment can yield improvements across core outcome domains, largely comparable to in-person settings. Less is known about how outcomes may differ across demographic groups. Overall, this body of literature remains small and characterized by limitations and inconsistencies, including differences in the treatment services evaluated as well as disparities in study design, methodology, and reporting. Utilization of remote treatment by historically excluded groups remains low, calling for further reflection around its accessibility for target communities. Additional studies with more rigorous, intentional designs are needed. The field would also benefit from standardization in relation to data collection and reporting to allow for better synthesis of findings. Remote eating disorder treatment (i.e., telehealth) may help improve access to care, especially for groups like racial and ethnic minorities who often face additional barriers, such as stigma. Research on patient outcomes in remote eating disorder services delivered in real-world clinical settings is limited, especially in relation to these historically underrepresented groups. This scoping review mapped the existing research to identify gaps and prioritize directions for future studies. Twenty-seven articles from 2011 to 2025 were included in the review. Many studies evaluated programs that quickly switched to remote care because of COVID-19. Overall, the treatment services evaluated were quite varied, studies had limitations related to design and methodology, and there were inconsistencies in how things were reported, making it difficult to combine findings and draw conclusions. Tentatively, results suggest that remote eating disorder treatment can be effective, however this conclusion should be interpreted with caution given the inconsistencies and limitations identified, including a lack of diversity in study participants which limits generalizability. Additional high-quality research is needed to confirm these findings. More consistency in what data are collected and how data are reported would allow for better interpretation of results across studies.

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Real-world patient outcomes for telehealth-delivered, remote eating disorder treatment: a scoping review

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Only 30% of individuals with eating disorders receive specialized treatment. While preliminary evidence suggests that telehealth-delivered, remote eating disorder treatment may offer improved accessibility with similar effectiveness to in-person treatment, research on these services remains limited, particularly regarding the communities that are disproportionately affected by barriers to standard care. This scoping review sought to map the existing research on real-world patient outcomes in remote eating disorder treatment, identify knowledge gaps, and prioritize areas for future studies. This review followed the Joanna Briggs Institute methodology for scoping reviews. It comprises observational evaluations of telehealth-delivered, remote eating disorder treatment conducted in routine clinical settings. An electronic database search was performed in PsycINFO, PubMed, and ProQuest Dissertations &amp; Theses Global in August 2024 and updated in September 2025. Following the search and screening process, 27 articles, comprising six case reports and 21 cohort/case series designs, were deemed eligible for inclusion. Remote treatments evaluated differed across level of care, therapeutic modalities, provider types, dosage, and adjunctive technologies used. Just under half of the studies compared outcomes from remote and in-person treatment, while the remainder examined remote treatment alone. Articles were published between 2011 and 2025 and, when excluding case reports, nearly 60% evaluated programs that rapidly transitioned to remote delivery due to COVID-19. While demographic reporting was limited and inconsistent, available information indicated that participants ranged from three to 75 years old and were predominantly White, cisgender women/females diagnosed with anorexia nervosa. Though preliminary, findings tentatively suggest that remote eating disorder treatment can yield improvements across core outcome domains, largely comparable to in-person settings. Less is known about how outcomes may differ across demographic groups. Overall, this body of literature remains small and characterized by limitations and inconsistencies, including differences in the treatment services evaluated as well as disparities in study design, methodology, and reporting. Utilization of remote treatment by historically excluded groups remains low, calling for further reflection around its accessibility for target communities. Additional studies with more rigorous, intentional designs are needed. The field would also benefit from standardization in relation to data collection and reporting to allow for better synthesis of findings. Remote eating disorder treatment (i.e., telehealth) may help improve access to care, especially for groups like racial and ethnic minorities who often face additional barriers, such as stigma. Research on patient outcomes in remote eating disorder services delivered in real-world clinical settings is limited, especially in relation to these historically underrepresented groups. This scoping review mapped the existing research to identify gaps and prioritize directions for future studies. Twenty-seven articles from 2011 to 2025 were included in the review. Many studies evaluated programs that quickly switched to remote care because of COVID-19. Overall, the treatment services evaluated were quite varied, studies had limitations related to design and methodology, and there were inconsistencies in how things were reported, making it difficult to combine findings and draw conclusions. Tentatively, results suggest that remote eating disorder treatment can be effective, however this conclusion should be interpreted with caution given the inconsistencies and limitations identified, including a lack of diversity in study participants which limits generalizability. Additional high-quality research is needed to confirm these findings. More consistency in what data are collected and how data are reported would allow for better interpretation of results across studies.

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                for (var i = 0; i < bodyScripts.length; ++i) {
                    var scriptEl = createScript(bodyScripts[i]);
                    d.body.appendChild(scriptEl);
                }
            });

            // Webfont repeat view
            var config = w.config;
            if (config && config.publisherBrand && sessionStorage.fontsLoaded === 'true') {
                d.documentElement.className += ' webfonts-loaded';
            }
        })(window, document);
    }


Journal of Eating Disorders

Element.prototype.matches||(Element.prototype.matches=Element.prototype.matchesSelector||Element.prototype.mozMatchesSelector||Element.prototype.msMatchesSelector||Element.prototype.oMatchesSelector||Element.prototype.webkitMatchesSelector||function(a){a=(this.document||this.ownerDocument).querySelectorAll(a);for(var b=a.length;0<=--b&&a.item(b)!==this;);return-1<b});

(function(){var a=google_tag_manager["rm"]["50443292"](253);window.uetq=window.uetq||[];window.uetq.push("consent","update",{ad_storage:a})})();

Meta/Facebook

X/Twitter

Google

Consent Management Platform

First-Party Tracking

✅ Low Risk - https://jeatdisord.biomedcentral.com/articles/10.1186/s40337-025-01441-5

Requests	IP Address	Location	AS Autonomous System
67	104.18.35.13	Unknown	Unknown
1	142.250.74.194	Unknown	Unknown
1	142.250.185.66	Unknown	Unknown
1	142.250.186.65	Unknown	Unknown
1	142.250.185.67	Unknown	Unknown
1	150.171.27.10	Unknown	Unknown
1	142.250.186.98	Unknown	Unknown
1	172.217.18.3	Unknown	Unknown
1	157.240.0.6	Unknown	Unknown
1	18.66.112.96	Unknown	Unknown
157	91	-	-

Security Scan Report: jeatdisord.biomedcentral.com

Summary

AI Security Verdict

Safe Website

Safety Factors

Details

Screenshot

Page Load Overview

Language Analysis

Primary Language

Detection Details

Website Classification

Primary Category

All Detected Categories

Detected Features

Domain & IP Information

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

ssdeep (Context Triggered Piecewise Hashing)

sdhash (Similarity Digest Hashing)

Image Hashes

Perceptual Hashes

Other Hashes

Scan History