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Abstract

Background

Fatigue is a common, persistent symptom in inflammatory bowel disease (IBD). Digital health technologies (DHTs) may enable ongoing monitoring and timely support, yet the relevant evidence remains dispersed.

Objective

To map how DHTs are used to monitor or manage IBD-related fatigue, summarize intervention characteristics, measures, feasibility, acceptability, and reported effectiveness.

Methods

Following the Joanna Briggs Institute (JBI) methodology and the Arksey O’ Malley framework, and reported per PRISMA extension for Scoping Reviews (PRISMA-ScR), eight databases and gray sources from inception to 30 October 2025 were searched using a Population-Concept-Context schema. Eligible studies used a DHT to assess or manage IBD-related fatigue. Screening and data charting were conducted in duplicate; findings were synthesized narratively.

Results

Eleven studies were included: four randomized trials, two cohorts, one program evaluation, one non-randomized feasibility study, one multisensor pilot, one mixed-methods study, and one qualitative study. Technologies fell into six groups: telemedicine portals, web-based cognitive behavioral therapy (CBT) self-management, mobile self-management applications, device-linked neuromodulation, wearable-enabled monitoring, and eDiary-based symptom tracking. Feasibility and acceptability were commonly reported in patient-facing studies, and implementation-focused evidence suggested professional acceptability when roles and workflows were clearly defined. Randomized comparisons rarely showed significant differences in fatigue improvement between the groups. Patient-reported outcomes predominated, including IBD-F, FACIT-F, FSS, and PROMIS-Fatigue. Device metrics were mainly activity-based with limited higher-frequency physiology. Engagement often declined, and misalignment between measurement and intervention design was common.

Conclusions

Current evidence suggests that DHTs for IBD-related fatigue are generally feasible and acceptable in the studied contexts, but evidence for reducing fatigue is limited and mixed. A pragmatic next step may be a hybrid measurement strategy combining validated fatigue questionnaires, brief daily ratings, and a small set of interpretable device metrics within timing-sensitive trial designs to support implementation in routine care.

Keywords

inflammatory bowel disease fatigue digital health mHealth scoping review

Introduction

Inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), has become a major public health challenge worldwide.¹ Its incidence is increasing not only in Western countries but also across Asia and other developing regions.² While modern therapies have successfully focused on healing the gut lining (mucosal healing), a significant gap remains between clinical remission and patients’ subjective experience.³ For many patients, fatigue is the most debilitating part of their daily life. It is remarkably common, affecting nearly 80% of those with active inflammation.⁴ More importantly, it persists in nearly half of patients even when their disease is clinically under control.^5,6 This relentless exhaustion is not just a side effect; it is a distinct problem that severely damages quality of life and ability to function.^7,8

Managing IBD-related fatigue effectively poses a significant challenge due to its multifactorial etiology, which involves a complex interplay of inflammation, anemia, psychological distress, poor sleep, and physical inactivity.^4,9,10 Moreover, standard clinical practice often overlooks fatigue, as assessment prioritizes endoscopic outcomes.³ Current evaluation relies on validated questionnaires, such as the Fatigue Severity Scale (FSS) or the Inflammatory Bowel Disease Fatigue scale (IBD-F), administered during infrequent clinic visits.^11,12 These tools, however, provide only a static, often weekly, snapshot.^13,14 They fail to capture the day-to-day fluctuations of fatigue, which are influenced by factors like sleep quality, pain, or daily stress.⁹ This occasional monitoring approach is therefore insufficient to detect the gradually worsening fatigue, and the absence of such monitoring often leads to the inability to take timely intervention.⁴

Digital health technologies (DHTs) such as smartphones, wearables, and telemedicine applications offer a potential solution by enabling continuous symptom tracking in real-world settings. Telemonitoring platforms, like MyIBDcoach, have been shown to safely reduce hospital visits and maintain patient satisfaction.^15,16

Most existing digital tools for IBD prioritize conventional physical symptoms (such as diarrhea or medication adherence) while largely neglecting fatigue. However, emerging evidence suggests that fatigue is both manageable and a critical outcome for patients.^17–19

Pilot applications have demonstrated potential in reducing patient fatigue,^20,21 and developing research suggests that wearable-derived data including sleep metrics and heart rate variability (HRV) could act as objective digital biomarkers to track it.^22,23 Combining these passive data streams with real-time, patient-reported symptoms may allow for a more granular, personalized characterization of an individual’s fatigue phenotype.^19,22,23

Despite this potential, the existing evidence is highly fragmented across technologies, outcomes, and disciplines,^17–19 leaving a critical synthesis of evaluated interventions and their efficacy lacking. To address this knowledge gap, we conducted a scoping review to synthesize the current evidence, clarify key concepts, and identify research gaps. To ensure methodological rigor, the frameworks established by Arksey and O’ Malley and the Joanna Briggs Institute (JBI) were followed,^24,25 and the review was reported using the PRISMA Extension for Scoping Reviews (PRISMA-ScR).²⁶ The review specifically addresses three key questions: (1) What types of DHTs have been utilized to monitor or manage IBD-related fatigue? (2) What digital biomarkers or metrics are captured to assess fatigue? (3) What evidence is available on the feasibility, acceptability, and reported effectiveness of these technologies for managing fatigue in individuals with IBD, and what implementation evidence (including healthcare professionals’ perspectives) informs their delivery and adoption? By systematically mapping this field, we aim to provide a foundation for integrating data-driven fatigue care into routine IBD clinical practice.

Methods

Study design

This study reports on a scoping review that mapped how DHTs are utilized to monitor and/or manage IBD-Fatigue. The JBI methodology was followed for scoping reviews,²⁵ which incorporates the five-stage framework proposed by Arksey and O’ Malley²⁴: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; and (5) collating, summarizing, and reporting the results. This review was reported following the Preferred Reporting Items for Systematic reviews and PRISMA-ScR guidelines.²⁶ The protocol was not registered, as PROSPERO does not currently accept scoping reviews.

Review question

The specific research questions addressed in this review are: (1) Which DHTs have been used to monitor or manage IBD-related fatigue? (2) What digital biomarkers or metrics, including activity, sleep, heart-rate dynamics, or passive sensing signals, are being captured to objectively assess fatigue, and how are these paired with patient-reported outcomes (PROs)? (3) What evidence is available on the feasibility, acceptability, and reported effectiveness of these technologies for managing fatigue in individuals with IBD? What implementation evidence, including healthcare professionals’ perspectives, informs their delivery, workflow integration, and adoption?

Eligibility criteria

Eligibility criteria were informed by the Population-Concept-Context (PCC) framework. This framework defined the scope and informed the search strategy. Eligibility decisions were based on the operational criteria below. Inclusion criteria: Studies were eligible if they met all of the following criteria. (1) Population: Individuals with a confirmed diagnosis of IBD, including CD, UC, or IBD-unclassified, of any age. To capture implementation evidence, we also included studies reporting healthcare professionals’ perspectives on the delivery, workflow integration, or professional acceptability of fatigue-related DHTs. These data were analyzed as implementation-focused evidence and were not used to draw conclusions about patient-level fatigue outcomes or effectiveness. (2) Concept: The study evaluated a DHT used to monitor, assess, or manage IBD-related fatigue. Fatigue had to be prespecified as a primary or secondary outcome. The study also had to report fatigue-relevant measures or monitoring variables. During synthesis, we considered whether fatigue was a primary or secondary outcome because this may influence the focus of the intervention and interpretation of fatigue findings. (3) Context: Any healthcare setting and any geographical region were eligible. (4) Study designs: Quantitative, qualitative, and mixed-methods studies were eligible. Quantitative designs included randomized controlled trials (RCTs), observational studies, and feasibility or pilot studies. Exclusion criteria: Studies were excluded if they met any of the following criteria. (1) The DHT targeted general IBD management and fatigue was assessed only as a subscale or single item within a broader composite instrument, with no fatigue-specific aim or analysis. This included studies using the systemic or energy subscale of the Inflammatory Bowel Disease Questionnaire (IBDQ) as the only fatigue indicator. (2) The intervention focused solely on non-digital approaches for fatigue, including standard face-to-face cognitive behavioral therapy (CBT) or pharmacological trials without a digital component. (3) The publication type was a systematic review, meta-analysis, conference abstract, or study protocol.

Data sources and search strategy

A systematic search of electronic databases was conducted from database inception to 30 October 2025. The databases included PubMed, ProQuest, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, and Scopus, as well as China National Knowledge Infrastructure (CNKI), and Wanfang Data. To enhance comprehensiveness, we also searched grey literature, limited to doctoral and master’s theses in ProQuest and CNKI, and screened reference lists of included studies and relevant reviews. Search terms were developed using the PCC framework (IBD; DHTs; fatigue) and combined with Boolean operators. Controlled vocabulary (such as MeSH and Emtree) and free-text keywords were used where available. The full PubMed search strategy is provided in Supplemental File 1, and strategies were adapted to each database’s indexing and syntax.

Study selection and search results

All search results were imported into EndNote reference management software. Duplicated records were removed prior to screening. Before formal screening, a subset of records was reviewed jointly to ensure consistent interpretation of the eligibility criteria. Two researchers (ZTR and SGX) then independently screened titles and abstracts, followed by full-text review, based on the eligibility criteria. Disagreements at either stage were resolved through discussion. If consensus was not reached, a third researcher (ZXL) made the final decision. Reasons for exclusion at the full-text stage were recorded according to predefined categories. Records that could not be retrieved after reasonable attempts were documented and reported in the PRISMA-ScR flow diagram. Database searching across PubMed, CINAHL, Embase, Web of Science, Scopus, ProQuest, CNKI, and Wanfang Data, plus reference-list screening, yielded 1057 records (databases: n=956; reference lists: n=101). After de-duplication (n=414), 643 titles/abstracts were screened and 265 full texts were sought, of which 36 were not retrieved. Of the 229 full texts assessed, 218 were excluded (no fatigue focus: n=106; irrelevant population: n=87; non-digital interventions: n=25), leaving 11 studies for data extraction. The study selection process is summarized in the PRISMA-ScR flow diagram (Figure 1).

Figure 1.

PRISMA flow diagram.

Data extraction: Charting the data

A data charting form was developed a priori by the review team to extract key information relevant to the research questions. The form was piloted on a small subset of included studies and refined iteratively to ensure consistent interpretation. Two researchers (ZTR and SGX) independently charted data from all included studies and compared extracted items for consistency; discrepancies were resolved by discussion and consensus, and unresolved items were adjudicated by a senior researcher (ZXL). Consistent with our PCC framework, evidence sources were classified as patient-level or implementation-focused (such as healthcare professionals’ perspectives). Implementation-focused studies were charted and synthesized separately and were not used to infer patient-level fatigue outcomes or effectiveness. The charted variables covered several key domains: study characteristics (author, year, country, and design); population (sample size, IBD diagnosis); digital health technology (its specific type, such as mobile app or wearable; the device/software name, if reported; and its intended function); monitoring variables (the fatigue assessment method, including the specific PRO instrument, and any digital biomarkers captured, such as step count or HRV); intervention characteristics, when applicable (components, theoretical rationale, such as CBT, duration, and delivery mode); and key outcomes (findings related to feasibility, such as recruitment, adherence; acceptability, such as usability; and reported effectiveness on fatigue and quality of life). An example of the data charting form is provided in Supplemental File 2.

Analysis: Collating, summarizing, and reporting results

As a scoping review, its primary goal was to map the breadth and nature of the evidence rather than to test causal effects. Therefore, a formal risk-of-bias assessment of the included studies was not performed, as this is not a mandatory component of the Arksey and O’ Malley framework.²⁴

The data synthesis involved a two-part approach: (1) the extracted data were narratively synthesized, and (2) descriptive statistics were employed to summarize study characteristics. The findings were then organized thematically, guided by our primary research questions, to produce a focused overview of the existing literature on technologies targeting IBD-related fatigue.

Results

Characteristics and results of sources of evidence

A total of 11 studies met the inclusion criteria and were included in the narrative synthesis (Table 1). Consistent with the scoping review questions, these studies reported evidence on the types of DHTs used, the fatigue-related measures and biomarkers captured, and the outcomes related to feasibility, acceptability, and effectiveness, as well as implementation contexts. Publications spanned 2017 to 2025,^16,32,36 with seven of eleven studies published from 2023 onward.^{28–32,35,36} Most research was conducted in Europe (n=8; Netherlands,^16,31 Denmark,²⁷ UK,^28,32,33 Finland,²⁹ EU multi-site³⁴), with additional studies from the USA^30,35 (n=2) and Korea³⁶ (n=1). The set comprised four randomized trials,^27,28,32,36 two observational cohorts,^30,31 one program evaluation,²⁹ one multisensor pilot,³⁴ one mixed-methods study,³⁵ one qualitative study,³³ and one non-randomized feasibility study.¹⁶ Samples ranged from 30 to 780.^16,32 Ten studies enrolled adults with IBD to evaluate patient-level outcomes. One study³³ examined implementation from the perspective of IBD nurses; it was synthesized separately as implementation-focused evidence and was not used to infer patient-level outcomes.

Table 1.

Overview of included studies.

No.	First author, year; country	Design	Population (patients/HCPs)	Digital health technology			Monitoring variables		Application of DHT/intervention details	Key outcomes
No.	First author, year; country	Design	Population (patients/HCPs)	Type	Name	Primary function	Fatigue PRO	Digital biomarkers	Application of DHT/intervention details	Feasibility	Acceptability	Effectiveness
1	de Jong,¹⁶ 2017; Netherlands	Feasibility	Adults with IBD (n=30) Patients	Telemedicine platform	MyIBDcoach	Remote monitoring; education	VAS fatigue (0–10)	/	Monthly monitoring plus e-learning; fully remote; 3-month use	100% adherence to monthly monitoring; 90% completed ≥1 e-learning module	Satisfaction 7.8/10; 93% would recommend	/
2	Ankersen,²⁷ 2019; Denmark	RCT	Adults with IBD (n=102) Patients	Web platform + home test	IBD Constant-Care + FC	Self-monitoring; remote diagnostics	FACIT-F	FC	Patient-led screening vs fixed 3-monthly checks; remote support; 12-month follow-up	Implementable; fewer kits with patient-led screening	Engagement acceptable	No between-arm difference in fatigue (exploratory)
3	Huang,²⁸ 2025; UK	RCT (feasibility)	Adults with IBD (n=36) Patients	Device + app	TEAS device + app	Digital therapeutics	IBD-F	/	30 min/day for 3 weeks; remote training; two schedules tested	Good adherence (≥18 sessions common)	81% would recommend	Improvements in depression/QoL; fatigue exploratory
4	Oddsson,²⁹ 2023; Finland	Program evaluation	Adults with IBD (ITT n=205, 80 completers) Patients	Mobile app program	Sidekick Health	Self-management; coaching	In-app energy item	App engagement logs	16-week education, lifestyle tasks, coaching via app	High engagement during active weeks	Retention acceptable (completers)	Improvements in energy/stress among completers; no control
5	Griffin,³⁰ 2024; USA	Observational	Adults with IBD (n=430) Patients	Wearables + portal	Fitbit/Garmin (BYOD)	Self-monitoring; analytics	PROMIS-Fatigue	Steps/day, MVPA, distance	Passive syncing; PROs biannually; 6-week data windows before PROs	High wear-time in analysis windows	/	Lower activity associated with higher fatigue; no intervention
6	Bredero,³¹ 2025; Netherlands	observational cohort	Adults with IBD (n=320; many in remission) Patients	Telemedicine portal	MyIBDcoach	Teleconsultation; self-report	VAS fatigue (0–10)	/	Routine online consultations every 6–12 months over about 5 years	Routine use feasible	/	Five trajectories; 1/3 chronic high fatigue; linked to sleep/stress/low PA
7	Moss-Morris,³² 2025, UK	RCT	Adults with IBD (n=780) Patients	Online CBT program	IBD-BOOST	Self-management; guided CBT	IBD-F	/	Structured web modules up to 12 months	Large-scale delivery feasible	Positive clinician/user feedback	FI improved; IBD-F not significantly changed; primary QoL unchanged
8	Matthias,³³ 2021; UK	Qualitative	IBD nurses (n=45) HCPs (implementation)	Online support model	IBD-BOOST support	Client support services	/	/	Defined nurse role/workflows to support program	Barriers/enablers identified	Positive with training/resources	/
9	Antikainen,³⁴ 2022; EU multi-site	Pilot	n=136 (include 18 IBD) Patients	Multisensor wearables + app	Multimodal devices + app	Self-monitoring; analytics	App fatigue Likert	HR/HRV, accelerometry, sleep, temperature	High-frequency PRO prompts with continuous sensing over ∼2 weeks	High data completeness/quality	Acceptable burden	Associations between digital metrics and fatigue; no therapy
10	Regueiro,³⁵ 2023; USA	Mixed-methods	Adults with CD (n=35) Patients	eDiary app	Smartphone diary	Self-reporting	FACIT-F	/	Daily fatigue capture for 14 days; twice-weekly assessments	Daily capture feasible	Positive relevance feedback	/
11	Lee,³⁶ 2025; Korea	RCT	Obese adults with IBD (n=49) Patients	Mobile app + wearable	App with community page	Self-management; activity coaching	FSS	Steps/day; weight logs	10-week target ≥7,000 steps on ≥5 days/week; weekly submissions; education videos	Good retention	Remote format acceptable	Improved body composition; fatigue decreased within intervention; no between-group difference

Abbreviations: CBT, Cognitive Behavioral Therapy; CD, Crohn’s disease; DHT, digital health technology; EU, European Union; FACIT-F, Functional Assessment of Chronic Illness Therapy–Fatigue; FC, fecal calprotectin; FI, fecal incontinence; FSS, Fatigue Severity Scale; HR, heart rate; HRV, heart rate variability; IBD-BOOST, IBD-BOOST program (UK self-management support program); IBD-F, Inflammatory Bowel Disease Fatigue (scale); ITT, intention-to-treat; MVPA, moderate-to-vigorous physical activity; PA, physical activity; PRO, patient-reported outcome; PROMIS, Patient-Reported Outcomes Measurement Information System; QoL, quality of life; RCT, randomized controlled trial; TEAS, transcutaneous electrical acupoint stimulation; VAS, visual analogue scale.

Notes:/= not applicable, not collected, or not reported. Unless otherwise specified: duration in weeks; frequency in sessions/week; session length in min/session. Significance based on two-sided p values. “Effectiveness” summarizes change in fatigue, QoL, or clinical endpoints; feasibility-only, measurement, or observational studies are marked “/”. Scale scoring: VAS fatigue 0-10 (higher=worse); FACIT-F 0-52 (higher=less fatigue); IBD-F (higher=worse); PROMIS-Fatigue T-score (mean=50, SD=10; higher=worse). Fatigue measures and assessment schedules varied across studies, and fatigue was frequently a secondary outcome. Feasibility and acceptability findings mainly reflect implementation and engagement and should not be interpreted as evidence of clinical effectiveness.

Types of DHTs and their functions

The 11 included studies were mapped to six categories by technological platform and primary function, with some overlap in capabilities.

Telemedicine/eHealth portals (n=3). This category comprised comprehensive systems for remote follow-up, structured self-report, and patient education. MyIBDcoach supported routine e-consultations and longitudinal symptom capture in both a feasibility study¹⁶ and a long-term (about 5-year) service cohort.³¹ IBD Constant-Care integrated web-based self-monitoring with home fecal calprotectin (FC) testing, enabling a patient-led screening pathway within a telemonitoring framework.²⁷

Web-based CBT self-management (n=2). Both studies centered on IBD-BOOST and delivered as a structured, multi-module online CBT self-management program for patients.³² Parallel work examined IBD-BOOST as an implementation support model, specifying the clinical roles and workflows required of IBD nurses to facilitate program delivery.³³

Mobile app self-management programs (n=2). This group included app-based coaching platforms. One was Sidekick Health, offering gamified education, goal-setting and nurse coaching with improvements reported among completers.²⁹ The other was a 10-week randomized trial of an app-based walking program for adults with obesity and IBD, combining educational videos, a community page, and daily step targets (7000 steps/day).³⁶

Device-linked digital therapeutics (n=1). This study examined a connected transcutaneous electrical acupuncture-point stimulation device paired with a smartphone application to enable home-based neuromodulation, remote training, and user guidance.²⁸

Wearable-enabled monitoring and analytics (n=2). One large observational study utilised bring-your-own-device consumer wearables (Fitbit/Garmin) linked to a portal to relate real-world activity patterns to fatigue and other PROs.³⁰ A separate pilot employed a multisensor system to capture high-frequency physiology (such as HR/HRV), accelerometry, temperature, sleep features) to explore feasibility and the identification of digital fatigue/sleep signatures.³⁴

eDiary/patient-reported capture (n=1). A smartphone-based daily diary quantified short-term variability in fatigue and examined the content validity and measurement properties of Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) in a CD population.³⁵

Functionally, these technologies converged on four recurring aims: remote or self-monitoring of fatigue and related symptoms,^{16,27,30,31,35} provision of self-management support and coaching,^29,36 delivery of structured therapy (online CBT or device-based neuromodulation),^28,32 and objective data capture with analytics, including wearable-derived metrics (steps, activity, HR/HRV, sleep) and home FC embedded in telemonitoring pathways.^27,30,34

Monitoring variables: PROs and digital biomarkers

Across the 11 studies, fatigue was measured primarily with PROs, and in a smaller subset with objective digital or clinical signals. For PROs, instruments fell into two groups. IBD-specific measurement was represented by the IBD-F, which was used in two intervention trials.^28,32 Generic validated scales (deployed in IBD populations) included FACIT-F in telemonitoring and diary-based studies,^27,35 PROMIS-Fatigue in a community wearables cohort,³⁰ and the FSS in an app-based walking trial.³⁶ Several platforms opted for brief capture rather than a multi-item scale, recording a 10-point visual analogue rating or in-app items such as ‘energy’ or ‘physical fatigue’.^16,31,29,34 One qualitative study centered on implementation from the nurse perspective and did not collect patient fatigue outcomes.³³

Administration schedules mirrored study aims. The diary study used daily fatigue entries with a weekly FACIT-F to respect the seven-day recall period.³⁵ Behaviour-change and therapy trials assessed fatigue at trial-anchored timepoints before and after the intervention, with follow-up where specified.^28,32,36 Telemedicine cohorts embedded fatigue assessments into routine service intervals, typically monthly or periodic check-ins within the platform workflow.^16,27,31 Taken together, these schedules captured both short-term variability and program-level change.

Objective capture was less common. Six of the eleven studies did not record objective digital or biological measures relevant to fatigue. Of these, five relied exclusively on PROs,^{16,28,31,32,35} and one was qualitative.³³ Among the five studies with objective data, three reported direct fatigue-related digital signals derived from consumer or study devices. Activity measures such as steps per day, moderate-to-vigorous physical activity, and distance were the dominant signals,^30,36 while one pilot added high-frequency passive physiology: HR and HRV, accelerometry, temperature, and sleep features to probe potential digital signatures of fatigue.³⁴ In addition, one trial integrated a clinical proxy biomarker, home FC, within a web pathway to support patient-led screening, reflecting intestinal inflammation rather than fatigue itself.²⁷ Finally, one program analyzed app engagement logs as a usage and adherence indicator rather than a physiological marker.²⁹

Key outcomes: Feasibility, acceptability, and effectiveness

Feasibility

Across trials and service settings, interventions were reported as implementable, with adherence and data capture varying by study. Within MyIBDcoach, monthly monitoring modules reached 100% adherence, and 90% of participants completed at least one e-learning module.¹⁶ A five-year service cohort reported routine use over time.³¹ Remote workflows were workable: a web pathway that combined symptom entry with home FC enabled patient-led screening without overloading services.²⁷ Sensor-enabled studies reported high data completeness and acceptable wear-time for activity and sleep signals,³⁴ while the app-guided walking trial met protocol demands for step logging and intervention content.³⁶ A daily diary schedule with a weekly fatigue scale (seven-day recall) achieved high compliance for short-term measurement.³⁵ Large-scale delivery was reported in a web-based CBT program (n=780),³² and a home neuromodulation feasibility trial reported high adherence in one arm (83%) with only a single discontinuation due to mild skin sensitivity.²⁸ Multi-session programs reported engagement decline over time: 57% completed at least four sessions in the CBT program,³² and a 16-week coaching app reported 39% completion in the intention-to-treat cohort.²⁹ Nurse-supported delivery was feasible where roles, escalation, rules and training were explicit.³³

Acceptability. User experience was commonly reported as acceptable across modalities where assessed. MyIBDcoach achieved a mean satisfaction of 7.8/10, with 93% willing to recommend.¹⁶ The neuromodulation intervention reported 81% willingness to recommend.²⁸ Participants described diary and multisensor protocols as acceptable in burden and relevant to symptom tracking.^34,35 From a service perspective, clinicians, particularly IBD nurses, viewed the facilitator role as acceptable when training, role boundaries, and workload resourcing were clearly defined.³³ App-based self-management reported engagement during active weeks.^29,36

Effectiveness

Findings for fatigue were mixed and depended on design and endpoint. In randomized evaluations, between-group effects on fatigue were generally absent. The telemonitoring pathway with home testing showed no between-arm difference on fatigue outcomes.²⁷ In the large web-based CBT trial (IBD-BOOST), there were no between-group differences on the co-primary endpoints (UK-IBDQ and GRSR) at six months, and no significant difference on the secondary IBD-F; a significant improvement was observed for the fecal incontinence score among secondary endpoints.³² The walking-app RCT recorded a decrease in fatigue within the intervention arm but no between-group difference; body mass index and body fat improved between groups as primary outcomes.³⁶ The neuromodulation feasibility study reported improvements in mood and mental quality of life with exploratory change in fatigue.²⁸ Outside randomized designs, a pre-post coaching program described improvements among completers but lacked a control group, limiting inference about causality.²⁹ Observational and sensor pilots consistently associated lower free-living activity and disturbed sleep with greater fatigue burden, supporting the face validity of activity and sleep signals as correlates rather than determinants.^27,30 Longitudinal telemedicine data identified a chronic, stable high-fatigue subgroup and linked persistent fatigue with sleep problems, stress and low activity.³¹ Measurement work with daily capture supported the content validity and reliability of the fatigue assessment when paired with a weekly recall instrument.³⁵

Synthesis

Available evidence suggests that digital monitoring and self-management were generally feasible and acceptable in the studied contexts. However, confidence in these observations is limited by heterogeneity in study designs, control conditions, follow-up durations, and outcome instruments, as well as the predominance of small-sample feasibility studies. Evidence for fatigue improvement remains mixed, and randomized trials rarely demonstrated statistically significant between-group benefit. These findings support feasibility primarily for short-term monitoring and engagement, while support for sustained fatigue reduction remains preliminary.^27,30,34,36

Discussion

Principal findings

This scoping review synthesizes the findings from 11 studies on DHTs for IBD-related fatigue. The identified technologies fell into six categories: telemedicine portals,^16,27,31 web-based CBT self-management,^32,33 mobile self-management apps,^29,36 device-linked neuromodulation,²⁸ wearable-enabled monitoring,^30,34 and eDiary-based symptom tracking.³⁵ Interventions ranged from passive data collection^16,30,31 to more active self-management support.^29,32,36 Feasibility and acceptability were reported as acceptable in pilot and observational contexts, while randomized trials generally did not demonstrate statistically significant between-group improvements in fatigue.^27,32,36 Validated PROs, including IBD-F,^28,32 FACIT-F,^27,35 and FSS,³⁶ were the dominant measures, whereas objective biomarkers were primarily limited to activity metrics such as step counts.^30,36 High-frequency physiological sensing, including sleep features and HRV, was rarely assessed.³⁴ Collectively, these findings suggest a disconnect between feasible deployment and evidence of clinical efficacy.

Interpreting the feasibility-effectiveness gap

The observation that DHTs were reported as feasible but not yet supported by consistent evidence of fatigue improvement may reflect several related factors. A key contributor may be intervention scope. Many interventions targeted a single contributor to fatigue, such as physical activity, whereas IBD-related fatigue is multifactorial and shaped by inflammation, sleep disturbance, and stress.³⁷ Single-component approaches may therefore have limited impact on global fatigue outcomes. Evidence from other chronic conditions suggests that multimodal interventions combining physical activity, psychological support, and sleep management may achieve more sustained improvements.³⁸

Technology function may also influence observed effectiveness. Technologies in this review ranged from monitoring platforms, such as MyIBDcoach,^16,31 eDiaries,³⁵ and wearable-enabled tracking³⁰ to active therapeutic interventions, including IBD-BOOST CBT³² and device-linked neuromodulation.²⁸ Limited evidence of effectiveness may partly reflect the predominance of monitoring-focused studies. Monitoring platforms can be feasible for data capture but may not deliver a therapeutic dose. Clear methodological separation between monitoring tools and intervention tools is therefore important in future evaluations.

Measurement strategy may further contribute to this gap. Static PROs with seven-day recall periods may not capture the fluctuating nature of fatigue. Brief daily ratings may provide higher temporal resolution and may better detect short-term effects.³⁵ This measurement gap extends to objective data. While wearables tracking sleep and activity could complement PROs,^30,36,39,40 even high-frequency physiological data, which could offer real-time insights, remain largely underexplored.³⁴ Beyond these measurement challenges, methodological issues further complicate the observed results. Chief among them are engagement decay and sample heterogeneity. While initial engagement with DHTs is often high, attrition rates increase over time, particularly in long-term interventions.^29,32,41 Compounding this, many studies did not enrich their sample by fatigue severity at baseline, which may have diluted the observed effects. This underscores the need for future studies to stratify participants by baseline fatigue levels and evaluate methods for sustaining engagement, such as gamification,⁴² adaptive reminders, and personalized feedback.⁴³

Beyond methodological and design factors, the dynamic clinical course of IBD may also contribute to the observed feasibility and effectiveness gap. IBD follows a relapsing and remitting pattern in which symptom burden and clinical priorities change over time.³ During active disease, severe gastrointestinal symptoms often require immediate management. In this context, participation in fatigue-focused digital interventions may become secondary. During remission, inflammation may be controlled, yet fatigue often persists and may arise from multiple contributors. When interventions are evaluated across patients at different stages of disease activity, a uniform program delivered over a fixed trial period may achieve high feasibility but lead to limited changes in overall fatigue scores. Greater attention to disease stage, symptom context, and timing of intervention may help align digital strategies with clinical needs.

Translational pathway: From feasibility to effective implementation

Bridging feasibility and effectiveness requires alignment between outcomes, measurement frequency, and intervention design. A pragmatic approach is a measurement strategy that integrates validated PROs for comparability,⁴⁴ brief daily fatigue ratings,³⁵ and a small set of interpretable device metrics prioritizing sleep and activity.^30,34,36 To support reproducibility, future trials should pre-specify rules for sensor completeness, valid-day thresholds, and missing data handling. A minimum measurement set could include a primary static endpoint such as IBD-F^28,32 a daily fluctuation measure, such as a VAS rating,^16,31 and a core set of objective metrics prioritizing activity and sleep.^30,36

Timing-sensitive designs may help evaluate the proximal effects of brief, real-time interventions. Frameworks such as Micro-randomized trials^45,46 and sequential multiple assignment randomized trial designs⁴⁷ can test when and for whom specific components work based on time-varying data. These designs can support optimization of intervention sequencing and delivery under real-world variation in symptoms and context.

To close the loop between monitoring and management, future DHTs may incorporate multi-signal triggers that combine fatigue scores, activity, and sleep to activate tailored interventions.⁴⁸ These systems may be automated and may include nurse escalation protocols when needed so that patients can receive timely care. Successful scaling also depends on workflow integration and equity. Implementation evidence in this review suggests that a human-supported model can assist with onboarding, data interpretation, and alert management, and may help sustain engagement.³³ Future designs should also consider digital inclusion through offline-tolerant and multilingual interfaces.

Strengths and limitations

This review provides a structured synthesis of DHTs aimed at managing IBD-related fatigue and integrates patient-level and implementation-focused evidence. Strengths include a comprehensive multi-database search and eligibility criteria focused on fatigue-specific outcomes. However, limitations should be acknowledged. Robustness is constrained by the predominance of small-sample feasibility studies and the lack of active control groups in several trials, which limits causal inference. Heterogeneity in technologies and outcome measures precluded meta-analysis. The scarcity of studies using high-frequency physiological data limits understanding of digital biomarkers. These constraints support cautious interpretation of effectiveness findings and indicate the need for larger, adequately powered randomized trials.

Conclusion

Current evidence suggests that DHTs for IBD-related fatigue are generally feasible and acceptable for short-term monitoring in the studied contexts, but evidence for sustained clinical improvement remains preliminary and mixed. Future work should align measurement sensitivity with symptom fluctuation and evaluate multimodal, fatigue-targeted interventions within supported clinical workflows.

Supplemental material

Supplemental Material - Digital health technologies for monitoring and managing IBD-related fatigue: A scoping review

Supplemental Material for Digital health technologies for monitoring and managing IBD-related fatigue: A scoping review by Tianrong Zhu, Guixiao Sheng, Xiaoli Zhou and Liping Yang in Digital Health.

Supplemental material

Supplemental Material - Digital health technologies for monitoring and managing IBD-related fatigue: A scoping review

Supplemental Material for Digital health technologies for monitoring and managing IBD-related fatigue: A scoping review by Tianrong Zhu, Guixiao Sheng, Xiaoli Zhou and Liping Yang in Digital Health.

Supplemental material

Supplemental Material - Digital health technologies for monitoring and managing IBD-related fatigue: A scoping review

Supplemental Material for Digital health technologies for monitoring and managing IBD-related fatigue: A scoping review by Tianrong Zhu, Guixiao Sheng, Xiaoli Zhou and Liping Yang in Digital Health.

Footnotes

Acknowledgments

The authors wish to thank all.

ORCID iD

Tianrong Zhu

Author contributions

All authors were involved in the conceptualization and design of the study. ZTR was responsible for the study design, developing the literature search strategy, literature search, data extraction and writing the first draft. SGX and ZXL were responsible for the literature search, data extraction and writing part of the first draft. YLP was responsible for providing her expertise, making suggestions and critically revising the first draft.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Medical and Health Science Program of Zhejiang Province (Grant Number: 2025HY0358).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental material

Supplemental material for this article is available online.

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