Digital Health Interventions to Prevent Type 2 Diabetes Mellitus: Systematic Review
Open accessPublished version of a preprint
Abstract
Background: Digital health interventions (DHIs) have rapidly evolved and significantly revolutionized the health care system. The quadruple aims of health care (improving population health, enhancing consumer experience, enhancing health care provider [HCP] experience, and decreasing health costs) serve as a strategic guiding framework for DHIs. It is unknown how DHIs can impact the burden of type 2 diabetes mellitus (T2DM), as measured by the quadruple aims. Objective: This study aimed to systematically review the effects of DHIs on improving the burden of T2DM, as measured by the quadruple aims. Methods: PubMed, Embase, CINAHL, and Web of Science were searched for studies published from January 2014 to March 2024. Primary outcomes were the development of T2DM, hemoglobin A1c (HbA1c) change, and blood glucose change (dysglycemia changes). Secondary outcomes were consumer experience, HCP experience, and health care costs. Outcomes were mapped to the quadruple aims. DHIs were categorized using the World Health Organization’s DHI classification. For each study, DHI categories were assessed for their effects on each outcome, categorizing the effects as positive, negative, or neutral. The overall effects of each DHI category were determined by synthesizing all reported positive, neutral, or negative effects regardless of the number of studies supporting each effect. The Cochrane risk-of-bias version 2 (RoB 2) tool for randomized trials was used to assess the quality of randomized controlled trials (RCTs), while the ROBINS-I (risk of bias in nonrandomized studies of interventions) tool was applied for nonrandomized studies. Results: In total, 53 papers were included. For the T2DM development outcome, the effects of DHIs were positive in 1 (1.9%) study and neutral in 9 (17%) studies, and there were insufficient data to assess in 4 (7.5%) studies. For the dysglycemia outcome, the effects were positive in 23 (43.4%) studies and neutral in 24 (45.3%) studies, and there were insufficient data in 6 (11.3%) studies. There were mixed effects on consumer experience (n=13, 24.5%) and a lack of studies reporting HCP experience (n=1, 1.9%) and health care costs (n=3, 5.7%). All studies that reported positive population health outcomes used a minimum of 2 distinct categories of DHIs. Among these successful studies, the one that reported delaying the development of T2DM and 16 (69.6%) of those reporting improvements in dysglycemia involved HCP interaction. Targeted communication with persons (TCP), personal health tracking (PHT), and telemedicine (TM) showed some evidence as a potentially useful tool for T2DM prevention and dysglycemia. Conclusions: The effects of DHIs on T2DM prevention, as measured by the quadruple aims, have not been comprehensively assessed, with proven benefits for population health, mixed results for consumer experience, and insufficient studies on HCP experience and health care costs. To maximize their effectiveness in preventing T2DM and managing dysglycemia, DHIs should be used in combination and strategically integrated with in-person or remote HCP interaction. Trial Registration: PROSPERO CRD42024512690; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024512690
AI snapshot
Written from the paper’s full text.
TL;DR
This systematic review of 53 studies (34,488 participants) mapped digital health interventions for type 2 diabetes prevention to the quadruple aims. Evidence was strongest for dysglycemia improvement, mixed for consumer experience, and sparse for HCP experience and health care costs, with HCP interaction and combining DHI categories appearing important.
Key findings
- Among 53 included studies, T2DM development was assessed in 14: effects were positive in 1 (7.1%), neutral in 9 (64.3%), and insufficient in 4 (28.6%). Dysglycemia was assessed in 52: positive in 23 (43.4%), neutral in 24 (45.3%), and insufficient in 6 (11.3%).
- Consumer experience (n=13, 24.5%) had mixed effects, most often positive (n=7, 53.8%); HCP experience was reported in 1 (1.9%) study and was positive; health care costs were reported in 3 (5.7%) studies, with the 2 assessed showing negative effects.
- All studies reporting positive population health outcomes used at least 2 distinct DHI categories; among successful studies, the T2DM-delaying study and 16 (69.6%) dysglycemia-improvement studies involved HCP interaction.
- TCP, PHT, and TM showed some evidence as potentially useful for T2DM prevention and dysglycemia; DHIs were mostly applied with HCP interactions (n=43, 81.1%).
Methods
- PRISMA 2020 systematic review (PROSPERO CRD42024512690) searching PubMed, Embase, CINAHL, and Web of Science from January 2014 to March 2024; 53 papers with 34,488 participants included.
- Primary outcomes: development of T2DM, HbA1c change, and blood glucose change (dysglycemia); secondary outcomes: consumer experience, HCP experience, and health care costs, mapped to the quadruple aims.
- DHIs classified using WHO DHI classification; effects categorized as positive, negative, neutral, mixed, or not available; no meta-analysis due to heterogeneous designs/interventions/outcomes; RoB 2 for RCTs and ROBINS-I for nonrandomized studies.
Limitations
- Stated: T2DM diagnostic criteria varied across studies; broad inclusion criteria (design, population, DHI, duration) prevented meta-analysis and certainty-of-evidence assessment; intervention duration ranged from 1 to 48 months, short-term studies may miss long-term effects; intensity/frequency of DHIs was not summarized; English-only inclusion.
- Stated: nonrandomized studies had high moderate/serious risk of bias (n=17, 77.3%), mainly due to confounder recording/analysis; some RCT outcomes had some concerns or high risk.
- Evident: only 1 study reported HCP experience and 3 reported health care costs, so conclusions for those quadruple aims are very limited.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
60 of 69 cited sources checked · 26 supported · 4 flagged · accuracy not yet measured
- Findingcitation
Arora et al found a significant reduction in predicted HbA1c after the intervention (P<.001).
“For example, Arora et al [34] proved after the intervention that there is a significant reduction in predicted HbA1c (P<.001).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [34] source
- Findingcitation
Muralidharan et al and Holmes et al concluded that TM, in addition to TCP, does not have a significant effect on delaying T2DM.
“For example, Muralidharan et al [51] and Holmes et al [52] concluded that TM, in addition to TCP, does not have a significant effect on delaying T2DM.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [51] source
The Discussion (page unavailable) reports no change in fasting plasma glucose after 12 weeks of a multimodal mHealth intervention with human coach calls, and the Conclusions say a longer, more intensive intervention appears necessary for diabetes prevention. The paper does not test text messaging added to telephone counseling as a separate comparison or measure whether T2DM onset was delayed, so it does not support that specific conclusion. (LLM, conf=0.74)
Experimental — accuracy not yet measured - cites [52] source
The Abstract reports no significant difference in blood glucose levels between the postnatal lifestyle intervention and usual care. But the intervention combined education, weight-management referral, a pedometer, and telephone and text support; the trial measured weight loss at six months, not whether telemedicine delayed type 2 diabetes. (LLM, conf=0.85)
Experimental — accuracy not yet measured
- Findingcitation
Peacock et al showed that participants using wearables/trackers feel empowered in their choice of appropriate foods (P=.04).
“For example, Peacock et al [43] showed that participants using wearables/trackers feel empowered in their choice of appropriate foods (P=.04).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [43] source
Secondary Outcomes reports that the intervention group felt more empowered when faced with opportunities for poor food choices (P = 0.036, approximately .04). Randomisation shows that these women received both a pedometer-linked program and nutrition coaching, so the result cannot be attributed to tracker use alone. (LLM, conf=0.85)
Experimental — accuracy not yet measured
- Findingcitation
A PPC study by Katula et al reported consumer experience with negative feedback.
“A PPC study (6.3%) by Katula et al [37] reported consumer experience, with negative feedback of consumers.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [37] source
The Results and Discussion describe clinical outcomes and adverse events in a digital diabetes prevention trial, but do not report consumer experiences or negative consumer feedback. Searches for consumer feedback and participant experience found no passage addressing that claim. (LLM, conf=0.76)
Experimental — accuracy not yet measured
- Findingcitation
Karvela et al indicated that the effect of PHT on improving HbA1c was not significantly different compared to the control group (P=.31).
“Karvela et al [42] indicated that the effect of PHT on improving HbA1c was not significantly different compared to the control group (P=.31).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [42] source
- Findingcitation
In this review, AI used with wearables showed positive effects on glycemic status.
“In our review, AI used with wearables showed positive effects on glycemic status [46,56].”
Quote in the paperSubstantial claim2 of 2 sources checked- cites [46] source
The Results (Effectiveness and Safety; page unavailable) report a significant reduction in A1c, supporting a positive effect on one measure of glycemic status, but no significant change in fasting glucose. The Methods (Description of Sweetch Mobile Platform; page unavailable) describe AI using mobile-phone and digital-scale data, not a wearable device. The cited trial therefore does not support the wearable-specific part of the claim. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites [56] source
The Results > Health Outcomes section reports improved HbA1c among Low Carb Program participants. The Introduction > The Low Carb Program says users can connect wearables, and its architecture figure labels AI, but the paper does not evaluate whether AI used with wearables produced the glycemic improvement. Its single-arm design also does not support a causal conclusion. (LLM, conf=0.88)
Experimental — accuracy not yet measured
- Premisecitation
The meta-analysis by Schippers et al reported that mobile apps with personal interaction tools (messages, calls, email, or in-person meetings) are more effective for weight loss than automated interaction.
“The meta-analysis by Schippers et al [90] reported that mobile apps with personal interaction tools (messages, calls, email, or in-person meetings) are more effective for weight loss than automated interaction.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [90] source
In “Stratification by personal contact” (page not available), the meta-analysis reports significantly greater weight-loss effects for mobile-phone interventions with personal contact than for those without it. “Characteristics of included studies” identifies non-automated messages, emails, calls and face-to-face contact as examples. The paper does not specifically compare mobile apps with personal interaction tools against apps with automated interaction; its comparison is broader—mobile-phone interventions with versus without personal contact. (LLM, conf=0.85)
Experimental — accuracy not yet measured
- Premisecitation
Participants using devices with automatic data entry engaged with the platform 4 times longer than those who manually entered data.
“Participants using devices with automatic data entry engaged with the platform 4 times longer than those who manually entered data [94].”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [94] source
- Premisecitation
Chronic diseases, such as T2DM, develop over a long period.
“Chronic diseases, such as T2DM, develop over a long period [102].”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [102] source
The Type 2 Diabetes section says hyperglycemia develops gradually and type 2 diabetes frequently goes undiagnosed for many years, supporting the claim about T2DM. The paper does not establish that chronic diseases generally develop over a long period. (LLM, conf=0.82)
Experimental — accuracy not yet measured
- Premisecitation
PPC may be beneficial in glycemic control for diabetes management.
“PPC may be beneficial in glycemic control for diabetes management [95,96].”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [95] source
- cites [96] source
The Results (Value Added; page not provided) report a decline in A1c after an intervention combining lay health coaching with a diabetes management app. The Discussion describes this as an association from uncontrolled analyses. The paper therefore supports a possible glycemic benefit from the combined intervention, but does not establish a benefit from PPC alone. (LLM, conf=0.78)
Experimental — accuracy not yet measured
- Premisecitation
Evidence indicates that using AI technology in diabetes management is effective when combined with wearable technologies.
“Similarly, evidence indicates that using AI technology in diabetes management is effective when combined with wearable technologies [97].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [97] source
- Premisereasoning
Before-and-after studies or cohort studies can provide valuable insights into special populations such as patients with chronic liver disease or renal transplant.
“before-and-after studies or cohort studies can provide valuable insights into special populations, such as patients with chronic liver disease [57] or renal transplant [58]”
Quote in the paperSubstantial claim2 of 2 sources checked - Findingown data
The effects of DHIs on costs, assessed in 2 (3.8%) studies, were negative.
“The effects of DHIs on costs, assessed in 2 (3.8%) studies, were found to be negative.”
Quote in the paperNot a substantial claim - Findingown data
Using WHO's DHI classification, 7 DHI categories were identified: TCP, PPC, PHT, DCP, PHR, HCP DS, and TM.
“Using WHO’s DHI classification, 7 DHI categories were identified: TCP, PPC, PHT, DCP, PHR, HCP DS, and TM.”
Quote in the paperNot a substantial claim - Findingown data
Nonrandomized studies showed a disproportionately high number of moderate and serious risks of bias (n=17, 77.3%), predominantly due to not accurately recording and analyzing confounders.
“The nonrandomized studies showed a disproportionately high number of moderate and serious risks of bias (n=17, 77.3%), predominantly due to not accurately recording and analyzing confounders.”
Quote in the paperNot a substantial claim - Findingown data
In randomized controlled trials, risk of bias in population health outcomes ranged from low to high.
“In the RCTs, the risk of bias in population health outcomes ranged from low to high”
Quote in the paperNot a substantial claim - Findingown data
A few studies (n=7, 77.8%) had high risk of bias or some concerns in the T2DM development outcome.
“However, a few studies (n=7, 77.8%) had a high risk of bias or some concerns in the T2DM development outcome.”
Quote in the paperNot a substantial claim - Findingown data
All included studies (N=53, 100%) applied TCP.
“All included studies (N=53, 100%) applied TCP, including transmitting targeted health information or targeted alerts and reminders to patients.”
Quote in the paperNot a substantial claim - Findingown data
Of 13 DCP studies, 11 (84.6%) consisted of seeking supporting information and 3 (15.4%) simulated human-like conversations.
“Of the 13 (24.5%) studies on DCP, 11 (84.6%) consisted of seeking supporting information and 3 (15.4%) simulated human-like conversations.”
Quote in the paperNot a substantial claim - Findingown data
No studies reported PHT effects on HCP experience or health care costs.
“No studies reported HCP experience or health care costs.”
Quote in the paperNot a substantial claim - Findingcitation
Limaye et al reported PPC health care costs: the incremental cost of the DHI was GBP 35.8 (USD 47.5) per participant compared to GBP 23.3 (USD 30.9) per participant in the control group.
“The incremental cost of the DHI was GBP 35.8 (USD 47.5) per participant compared to GBP 23.3 (USD 30.9) per participant in the control group [38].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [38] source
- Findingnone given
No study assessed the effect of PPC on HCP experience.
“No study assessed the effect of PPC on HCP experience.”
Quote in the paperNot a substantial claim - Findingcitation
Limaye et al reported the effects of DCP on health care costs with negative results.
“Limaye et al [38] reported the effects of DCP on health care costs, with negative results.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [38] source
- Findingown data
The intervention duration in included studies fluctuated between 1 month and 48 months.
“The intervention duration fluctuated between 1 month and 48 months.”
Quote in the paperSubstantial claim - Findingown data
The effects of DHIs on the quadruple aims in T2DM prevention have mixed results for consumer experience.
“The findings from this systematic review demonstrate that the effects of DHIs on the quadruple aims in T2DM prevention have proven benefits for population health, mixed results for consumer experience, and insufficient studies on HCP experience and health care costs.”
Quote in the paperSubstantial claim - Findingown data
The effects of DHIs on the quadruple aims in T2DM prevention have proven benefits for population health.
“The findings from this systematic review demonstrate that the effects of DHIs on the quadruple aims in T2DM prevention have proven benefits for population health, mixed results for consumer experience, and insufficient studies on HCP experience and health care costs.”
Quote in the paperSubstantial claim - Findingreasoning
The diagnosis criteria for T2DM varied slightly across studies.
“The diagnosis criteria for T2DM varied slightly across studies.”
Quote in the paperSubstantial claim - Findingnone given
There are insufficient studies on HCP experience and health care costs for DHIs in T2DM prevention.
“The findings from this systematic review demonstrate that the effects of DHIs on the quadruple aims in T2DM prevention have proven benefits for population health, mixed results for consumer experience, and insufficient studies on HCP experience and health care costs.”
Quote in the paperSubstantial claim - Findingown data
DHIs have mixed results for consumer experience.
“The effects of DHIs on T2DM prevention, as measured by the quadruple aims, have not been comprehensively assessed, with proven benefits for population health, mixed results for consumer experience, and insufficient studies on HCP experience and health care costs.”
Quote in the paperSubstantial claim - Findingown data
Most studies (69.6%) successful in improving dysglycemia involved HCP interaction (75% remote, 12.5% in person, and 12.5% both).
“and most studies (69.6%) successful in improving dysglycemia involved HCP interaction (75% remote, 12.5% in person, and 12.5% both).”
Quote in the paperSubstantial claim - Findingnone given
Evidence supporting the effectiveness of DHIs in reducing the burden of T2DM remains limited.
“Although evidence supporting the effectiveness of DHIs in reducing the burden of T2DM remains limited, it is clear DHIs are effective in improving dysglycemia.”
Quote in the paperSubstantial claim - Findingnone given
DHIs are effective in improving dysglycemia.
“Although evidence supporting the effectiveness of DHIs in reducing the burden of T2DM remains limited, it is clear DHIs are effective in improving dysglycemia.”
Quote in the paperSubstantial claim - Findingown data
All 3 studies in this review indicated no positive cost outcomes in DHIs.
“Studies that reported health care costs of DHIs were sparse; all 3 studies in our review indicated no positive cost outcomes in DHIs.”
Quote in the paperSubstantial claim - Findingown data
Among the 10 studies with a low risk of bias in all outcomes and an intervention duration of at least 1 year, 70% demonstrated positive effects of DHIs on dysglycemia.
“Among the 10 studies with a low risk of bias in all outcomes and an intervention duration of at least 1 year, a high percentage of studies (70%) demonstrated positive effects of DHIs on dysglycemia.”
Quote in the paperSubstantial claim - Findingown data
All studies that reported positive population health outcomes used a minimum of 2 distinct categories of DHIs.
“Next, all studies that reported positive population health outcomes used a minimum of 2 distinct categories of DHIs.”
- Also stated in: § Results · plain
“All studies that reported positive population health outcomes used a minimum of 2 distinct categories of DHIs.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingnone given
The inclusion criteria permitted a wide range of variability in study design, study population, DHIs, and duration.
“The inclusion criteria of our study permitted a wide range of variability in aspects, such as study design, study population, DHIs, and duration.”
Quote in the paperSubstantial claim - Study design and conductreasoning
A meta-analysis was not performed because of the numerous heterogeneous study designs with different interventions or outcomes.
“A meta-analysis was not performed because of the numerous heterogeneous study designs with different interventions or outcomes.”
Quote in the paperSubstantial claim - Interpretationreasoning
The combination of TM, PHT, and TCP is effective in T2DM prevention.
“Our review also shows evidence that the combination of TM, PHT, and TCP is effective in T2DM prevention.”
Quote in the paperSubstantial claim - Interpretationnone given
DHIs have proven benefits for population health in T2DM prevention.
“The effects of DHIs on T2DM prevention, as measured by the quadruple aims, have not been comprehensively assessed, with proven benefits for population health, mixed results for consumer experience, and insufficient studies on HCP experience and health care costs.”
Quote in the paperNot a substantial claim - Interpretationown data
PHT showed evidence as a potentially useful tool for T2DM prevention and dysglycemia improvement.
“PHT showed evidence as a potentially useful tool for T2DM prevention and dysglycemia improvement in our review.”
Quote in the paperSubstantial claim - Interpretationreasoning
The diversity of included studies posed challenges in drawing direct comparisons.
“This diversity, while inclusive, posed challenges in drawing direct comparisons”
Quote in the paperSubstantial claim - Interpretationreasoning
The variation in T2DM diagnosis criteria across studies could lead to data inconsistencies because different criteria may classify the same participant differently.
“Although our study reflected a real-world scenario, the variation in diagnosis criteria could potentially lead to data inconsistencies, because different diagnosis criteria may classify the same participant differently.”
Quote in the paperNot a substantial claim - Interpretationown data
There is evidence that using DCP (look-up tools, human-like conversations) is helpful in diabetes prevention and management.
“There is evidence that using DCP (look-up tools, human-like conversations) is helpful in diabetes prevention and management.”
Quote in the paperSubstantial claim - Interpretationown data
These DHIs target HCPs rather than consumers.
“These DHIs target HCPs rather than consumers.”
Quote in the paperSubstantial claim - Interpretationown data
The effects of DHIs on T2DM prevention, as measured by the quadruple aims, have not been comprehensively assessed.
“The effects of DHIs on T2DM prevention, as measured by the quadruple aims, have not been comprehensively assessed, with proven benefits for population health, mixed results for consumer experience, and insufficient studies on HCP experience and health care costs.”
Quote in the paperSubstantial claim - Interpretationreasoning
The duration of DHI may play an important role in the effects on the population health outcome.
“Second, the duration of DHI may play an important role in the effects on the population health outcome.”
Quote in the paperSubstantial claim - Interpretationreasoning
For effective T2DM prevention, a minimum DHI duration of 9-12 months may be ideal.
“For effective T2DM prevention, a minimum DHI duration of 9-12 months may be ideal.”
Quote in the paperSubstantial claim - Interpretationown data
There was no evidence that DHIs are effective in preventing T2DM without HCP interaction.
“Third, there was no evidence that DHIs are effective in preventing T2DM without HCP interaction”
Quote in the paperSubstantial claim - Interpretationreasoning
Short-term studies may not allow the comprehensive effects of DHIs to show a clear impact on disease progression.
“Short-term studies may not allow for the comprehensive effects of DHIs to show a clear impact on disease progression.”
Quote in the paperSubstantial claim - Interpretationreasoning
PHT, particularly automated tracking devices, could play a pivotal role in prevention strategies for T2DM.
“This evidence strongly suggests that PHT, particularly automated tracking devices, could play a pivotal role in the prevention strategies for T2DM.”
Quote in the paperSubstantial claim
- May combine two claims. 56
- Classified as probably not a substantial claim. 26
May combine two claims.
Findingown dataOf 12 DCP studies assessing dysglycemia, 9 (75%) reported positive population health outcomes and 3 (25%) showed neutral effects.
“Of the 12 studies (92.3%) assessing the effects of dysglycemia, 9 (75%) reported positive population health outcomes, such as significant HbA1c reduction compared to the control group in Kim et al [45] using virtual reality (VR) technology and Everett et al [46] using AI interventions (P<.05). Furthermore, 3 (25%) studies [40,44,47] showed the effect was neutral.”
Quote in the paperSubstantial claim5 of 5 sources checked- cites [45] source
- cites [46] source
The Results (Effectiveness and Safety; page unavailable) report a significant A1c reduction of 0.1% (P=.04) in the intervention cohort, and the Introduction (Study Intervention; page unavailable) identifies Sweetch as AI-based. But the Methods (Statistical Analysis; page unavailable) compare participants’ measurements before and after the intervention, not against a control group. Everett et al. also do not report the citing review’s totals of 9 positive and 3 neutral studies. (LLM, conf=0.90)
Experimental — accuracy not yet measured - cites [40] source
- cites [44] source
- cites [47] source
The Results (Primary Outcomes; page unavailable) report no significant effect on fasting plasma glucose, but a significant HbA1c reduction in the TCM app group compared with controls. Thus, this paper does not support classifying its dysglycemia findings as neutral. As a single trial, it also cannot establish the citing review’s counts of 9 positive and 3 neutral studies. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
May combine two claims.
FindingcitationTM effects on consumer experience were varied: 5 (71.4%) studies reported positive effects, 1 (14.2%) no discernible effect, and 1 (14.2%) mixed effects.
“The effects of TM on consumer experience were varied, with 5 (71.4%) studies [39,44,48,53,54] reporting positive effects, 1 (14.2%) study [5] with no discernible effect, and 1 (14.2%) study [55] with mixed effects.”
Quote in the paperNot a substantial claim6 of 7 sources checked- cites [39] source
Citation [5] is attached to the claim that this study found no discernible effect on consumer experience, not to the seven-study tally. The Results (‘Adherence and satisfaction’; page unavailable) report participant satisfaction scores across three support centres, but do not report an intervention-versus-control effect on consumer experience. The Results (‘Primary outcomes’; page unavailable) report no overall effect on diabetes incidence, which is a different outcome. (LLM, conf=0.72)
Experimental — accuracy not yet measured - cites [44] source
The Results section on process measures reports high user ratings of the app (4.3 out of 5), and the Discussion says users accepted it and deemed it effective. The paper’s lack of a significant intervention effect concerns its primary clinical outcome, not a lack of discernible positive consumer experience. (LLM, conf=0.82)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured - cites [48] source
- cites [53] source
The citation [5] is attached to the claim that one study found no discernible effect on consumer experience. In Results > Psychosocial Factors (page unavailable), this study instead reports significantly greater exercise enjoyment for exercise-videogame participants than controls. The reported lack of difference in enjoyment was between standard exercise and controls, not between the videogame group and controls. (LLM, conf=0.82)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured - cites [54] source
The available copy identifies IGT Care Call as a telephone service, but its retrieved passages contain bibliographic information rather than findings about consumer experience. Searches for patient satisfaction, service-user experience, and an absence of discernible effect found no passage that could verify the result attributed to this study. The five-study and one-study counts are the citing authors’ synthesis, not a finding attributed to this individual source. (LLM, conf=0.72)
Experimental — accuracy not yet measured - cites [5] source
The Results section, “Process Measures and Other Behaviors” (page unavailable), reports high participation and significant improvements in self-confidence and other self-reported outcomes, supporting a positive finding for this intervention. It does not assess consumer experience directly or establish the citing paper’s seven-study breakdown; those counts are the citing authors’ synthesis. (LLM, conf=0.73)
Experimental — accuracy not yet measured - cites [55] source
May combine two claims.
FindingcitationOf 5 TM studies on T2DM development, 1 by Sakane et al indicated TM is effective, and the other 4 did not show significant differences compared to the control group.
“Of the 5 (20%) studies reporting the effects of TM on T2DM development, only 1 (20%) study by Sakane et al [39] indicated that TM is effective. The other 4 (80%) studies [35,40,44,50] did not show any significant differences compared to the control group.”
Quote in the paperNot a substantial claim5 of 5 sources checked- cites [39] source
The Results (Primary outcomes; page unavailable) report no reduction in T2DM development overall: HR 1.00 (95% CI 0.74–1.34). The Discussion (Main findings; page unavailable) explicitly says the study could not prove the intervention effective overall. A significant reduction appeared only in the subgroup at the centre providing 10 telephone calls, so describing the study without that qualification as showing TM was effective contradicts its overall finding. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured - cites [35] source
- cites [40] source
- cites [44] source
- cites [50] source
The Exploratory Outcomes section reports no statistically significant difference between intervention and usual care for *combined prediabetes or diabetes* incidence (hazard ratio 0.90, 95% CI 0.78–1.04). It does not report a separate significance test for type 2 diabetes development, so it supports the cited sentence only at the broader combined-outcome level. The paper does not assess the sentence’s count of five studies or its claim about Sakane et al. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThis systematic review was conducted and reported following PRISMA 2020 guidelines.
“This systematic review was conducted and reported following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines of 2020 [27].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [27] source
The Abstract identifies PRISMA 2020 as a guideline for reporting systematic reviews, supporting the citation’s identification of the reporting guideline. The Scope of the guideline section explicitly says it is not intended to guide systematic review conduct, so the claim that the review was conducted following PRISMA 2020 is not supported by this source. (LLM, conf=0.90)
Experimental — accuracy not yet measured
Classified as probably not a substantial claim. May combine two claims.
Study design and conductown dataRisk of bias was assessed using RoB 2 for randomized trials and ROBINS-I for nonrandomized studies by three reviewers.
“The Cochrane risk-of-bias version 2 tool (RoB 2) for randomized trials was used to assess the quality of RCTs [32], while the ROBINS-I (risk of bias in nonrandomized studies of interventions) tool was applied for nonrandomized studies [33] by TD, QO, and LJ.”
Quote in the paperSubstantial claim2 of 2 sources checkedMay combine two claims.
FindingcitationCastro Sweet et al used PPC, TCP, and PHT; after the interventions, the mean HbA1c of participants reduced by 0.1% (P=.001).
“For example, Castro Sweet et al [10] used PPC, TCP, and PHT in their DHIs; after the interventions, the change in the mean HbA1c of participants reduced by 0.1% (P=.001).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [10] source
The Method > Intervention section describes personalized health coaching, phone contact, and digital tracking tools, broadly consistent with the intervention description, though it does not use the acronyms PPC, TCP, or PHT. Results > Biometrics reports a mean HbA1c decrease of 0.14% in the 69 participants with available results, but gives P=.0001, not P=.001; the HbA1c result does not cover all participants. (LLM, conf=0.90)
Experimental — accuracy not yet measured
May combine two claims.
FindingcitationKim et al using virtual reality and Everett et al using AI interventions showed significant HbA1c reduction compared to the control group (P<.05).
“such as significant HbA1c reduction compared to the control group in Kim et al [45] using virtual reality (VR) technology and Everett et al [46] using AI interventions (P<.05).”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [45] source
- cites [46] source
The Results (Effectiveness and Safety) report a significant A1c reduction of 0.1% in the Sweetch intervention cohort (P=.04), and the Discussion (Significance of Findings) identifies the intervention as using machine learning. But the Methods (Statistical Analysis) describe a comparison with the cohort’s own baseline, not a control group; the paper therefore does not support the claimed between-group reduction. (LLM, conf=0.91)
Experimental — accuracy not yet measured
May combine two claims.
Findingown dataOf 5 PHT studies on T2DM prevention, 1 (20%) posted a positive effect and 4 (80%) reported a neutral effect.
“Of the 5 (13.5%) studies on PHT reporting its effects on preventing T2DM, 1 (20%) study [39] posted a positive effect, with 4 (80%) other studies [35,36,40,41] reporting a neutral effect on T2DM development.”
Quote in the paperNot a substantial claim5 of 5 sources checked- cites [39] source
- cites [35] source
- cites [36] source
The Results (section 3.2) report a 3% cumulative incidence of type 2 diabetes at two years and a 52.3% incidence of normoglycemia, supporting a promising prevention finding. But this was a single-arm pilot study; the Discussion says it was not designed to establish superiority over other interventions and calls for further research on diabetes prevention. It therefore does not establish the positive effect on T2DM development implied by the citing sentence. The counts and percentages of studies are the citing authors’ classification, not a finding attributed to this paper. (LLM, conf=0.86)
Experimental — accuracy not yet measured - cites [40] source
- cites [41] source
May combine two claims.
FindingcitationOnly 1 (14.2%) study assessed HCP experience in TM interventions, with HCP participants leaving positive feedback for TM, according to Savas et al.
“Only 1 (14.2%) study assessed HCP experience in TM interventions, with HCP participants leaving positive feedback for TM, according to Savas et al [54].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [54] source
The available passages from the indexed copy are bibliographic metadata identifying a telephone-based service, not findings about healthcare professionals. Searches for HCP experience and positive feedback returned no relevant passage, so the attributed feedback cannot be verified from our copy. The 1 (14.2%) figure describes the citing document's set of studies, not a finding expected from Savas et al. (LLM, conf=0.73)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationParticipants from Block et al reported both positive and negative feedback.
“For example, participants from Block et al [5] reported both positive and negative feedback.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [5] source
The Discussion’s “Features Promoting Effectiveness” section (page unavailable) says some people appreciate the team feature while others dislike it, supporting the idea of mixed reactions. It does not say that participants reported positive and negative feedback, so the claim overstates what the paper documents. (LLM, conf=0.80)
Experimental — accuracy not yet measured
May combine two claims.
Findingown dataTwo DCP studies reported prevention effectiveness, and both had a neutral effect.
“In addition, 2 (15.4%) studies [40,44] reported prevention effectiveness of DCP, and both had a neutral effect.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [40] source
The Results report no significant between-group differences in impaired glucose tolerance or type 2 diabetes at 12 months, which supports describing the observed diabetes-related effect as neutral. But the Discussion says a larger, longer study is needed to determine whether the program prevents progression to type 2 diabetes; this trial was powered for postpartum weight retention, not prevention effectiveness. (LLM, conf=0.82)
Experimental — accuracy not yet measured - cites [44] source
May combine two claims.
FindingcitationOf 16 PPC studies, 2 reviewing T2DM prevention showed a neutral effect, with no significant difference in T2DM diagnosis compared to the control group.
“Of 16 (30.2%) studies, 2 (12.5%) studies reviewing the effects of PPC on T2DM prevention were by Fitzpatrick et al [35] and McKenzie et al [36]. Results showed a neutral effect, with no significant difference in the T2DM diagnosis compared to the control group.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [35] source
- cites [36] source
The Results (section 3.3) say that type 2 diabetes prevalence was unchanged from baseline after correction for multiple comparisons. But the Methods (section 2.1) describe a single-arm study, so McKenzie et al. did not find a nonsignificant difference in diagnoses compared with a control group. (LLM, conf=0.88)
Experimental — accuracy not yet measured
May combine two claims.
FindingcitationOne study applied PHR and HCP DS; Mann et al reported no change in HbA1c and blood glucose levels after the intervention.
“One study applied PHR and HCP DS in their DHIs. Mann et al [49] reported no change in HbA1c and blood glucose levels after the intervention.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [49] source
The Discussion (page unavailable) explicitly reports a lack of change in A1C, and the Abstract reports no change in glycemic control. The Methods list A1C, but not a separate blood-glucose measurement; they describe EMR tools used by primary care providers rather than a patient health record (PHR). (LLM, conf=0.87)
Experimental — accuracy not yet measured
May combine two claims.
FindingcitationOf 3 DCP studies on consumer experience, Cha et al and Potzel et al reported better experience outcomes for patients in the DHI groups, while Block et al showed no effect.
“Of the 3 (23.1%) studies reporting the effectiveness of DCP on consumer experience, Cha et al [48] and Potzel et al [44] reported better experience outcomes for patients in the DHI groups, while Block et al [5] showed no effect.”
Quote in the paperNot a substantial claim3 of 3 sources checked- cites [48] source
The Results section on participant satisfaction (page unavailable) reports that participants rated the digital-platform intervention 4.15 out of 5 and described positive aspects of their experience. However, the Method > Study design section describes a one-group pretest–posttest study, so it cannot establish better consumer experience in a DHI group relative to another group. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites [44] source
The Results (Per-protocol group; page unavailable) report higher well-being and lower perceived stress than in controls among regular app users, but these differences were not statistically significant. The Results (Process measures of the intervention; page unavailable) also report favorable app ratings from users, without a control-group comparison. Thus the paper supports favorable experience findings, but not a clear improvement across the intervention group. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites [5] source
The Results sections report clinical outcomes and program participation, but no comparison of consumer-experience outcomes between groups. I searched for patient experience, satisfaction, acceptability, and quality of life; the copy does not establish the attributed finding of no effect on consumer experience. (LLM, conf=0.76)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationGentili et al indicated that several types of DHIs, such as videoconferencing systems, messaging, calls, mobile apps, and web-based platforms, help reduce health care costs.
“They indicated that several types of DHIs, such as videoconferencing systems, messaging, calls, mobile apps, and web-based platforms, help reduce health care costs.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [101] source
The Discussion reports cost savings for studies of videoconferencing, text messaging, web platforms, and mobile applications. But the Telephone support section says calls produced similar or slightly higher costs, not savings; the Text messaging intervention section reports savings in only one of five studies. The claim overgeneralizes the cost-reduction finding to all the listed types. (LLM, conf=0.90)
Experimental — accuracy not yet measured
May combine two claims.
PremisecitationHabit formation usually takes 2-3 months, and significant HbA1c changes require at least 3 months.
“This can be because habit formation usually takes 2-3 months [86], and significant HbA1c changes require at least 3 months [87].”
Quote in the paperSubstantial claim2 of 2 sources checked- cites [86] source
- cites [87] source
The citation [87] applies only to the HbA1c clause, not the separate habit-formation claim [86]. The Correlation Between BGM and A1C section discusses A1C as a measure of average glucose, and Table 6.1 describes glucose readings collected over three months per A1C measurement. Neither establishes that a significant HbA1c change requires at least three months; that minimum is unsupported. (LLM, conf=0.83)
Experimental — accuracy not yet measured
May combine two claims.
FindingcitationAll studies successful in improving dysglycemia had a DHI duration of at least 3 months, while the study successful in T2DM prevention had a duration of 12 months.
“All studies successful in improving dysglycemia had a DHI duration of at least 3 months, while the study successful in T2DM prevention had a duration of 12 months [39].”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [39] source
The Methods (Intervention arm; page unavailable) describe telephone support over one year, and the Results (Primary outcomes; page unavailable) report significantly lower T2DM incidence for the high-frequency centre C subgroup. The trial found no overall reduction in T2DM incidence, however, so calling the study successful without that qualification overstates its findings. This single trial also does not establish that all studies improving dysglycemia lasted at least three months. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAccording to Gentili et al, there is convincing evidence of the cost-effectiveness of DHI in health care.
“According to a systematic review of DHIs by Gentili et al [101], there is convincing evidence of the cost-effectiveness of DHI in health care.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [101] source
The Conclusion reports some evidence of favorable cost and health outcomes, but calls the overall evidence for cost-effectiveness in health care “scarce and limited.” It also says methodological heterogeneity makes comparisons difficult. “Convincing evidence” overstates the review’s conclusion. Page numbers were not provided in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measured
May combine two claims.
PremisecitationMany studies showed that PHT successfully increases physical activity and decreases a sedentary lifestyle.
“Similarly, many studies showed that PHT successfully increases physical activity and decreases a sedentary lifestyle [91-93].”
Quote in the paperNot a substantial claim1 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationLampickienė et al concluded that HCPs mostly report positive experiences with digital consultations, which have advantages for HCPs and patients.
“Lampickienė et al [100] concluded that HCPs mostly report positive experiences with digital consultations, which have advantages for HCPs and patients.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [100] source
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe only study reporting HCP experience indicated a positive effect.
“The only study reporting HCP experience indicated a positive effect.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataDHIs were mostly applied in combination with HCP interactions (n=43, 81.1%).
“DHIs were mostly applied in combination with HCP interactions (n=43, 81.1%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataFor the T2DM development outcome, DHI effects were positive in 1 study, neutral in 9 studies, and there were insufficient data in 4 studies.
“For the T2DM development outcome, the effects of DHIs were positive in 1 (7.1%) study and neutral in 9 (64.3%) studies, and there were insufficient data to assess in 4 (28.6%) studies.”
- Also stated in: § Results · plain
“For the T2DM development outcome, the effects of DHIs were positive in 1 (1.9%) study and neutral in 9 (17%) studies, and there were insufficient data to assess in 4 (7.5%) studies.”
Quote in the paperSubstantial claim- Also stated in: § Results · plain
May combine two claims.
Findingown dataFive outcomes were reported: consumer experience (n=13, 24.5%), health care costs (n=3, 5.7%), HCP experience (n=1, 1.9%), development of T2DM (n=14, 26.4%), and dysglycemia changes (n=52, 98.1%).
“Five outcomes were reported: consumer experience (n=13, 24.5%), health care costs (n=3, 5.7%), HCP experience (n=1, 1.9%), development of T2DM (n=14, 26.4%), and dysglycemia changes (n=52, 98.1%).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIn total, 15 DHIs were investigated.
“In total, 15 DHIs were investigated.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe effects of DHIs on consumer experience were mixed, with most being positive (n=7, 53.8%).
“The effects of DHIs in all studies on consumer experience were mixed, with most being positive (n=7, 53.8%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataApproximately 12 of 22 (54.5%) randomized controlled trials for HbA1c change and 10 of 23 (43.5%) for blood glucose change had some concerns or high risk of bias.
“the risks of bias in HbA1c and blood glucose change outcomes exhibited some similarities, with approximately 12 of 22 (54.5%) and 10 of 23 (43.5%) studies, respectively, presenting either some concerns or high risks.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenThe HCP experience outcome was not assessed in randomized controlled trials.
“The HCP experience outcome was not assessed in RCTs.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataFor the dysglycemia outcome, DHI effects were positive in 23 (43.4%) studies, neutral in 24 (45.3%) studies, and there were insufficient data in 6 (11.3%) studies.
“For the dysglycemia outcome, the effects were positive in 23 (43.4%) studies and neutral in 24 (45.3%) studies, and there were insufficient data in 6 (11.3%) studies.”
- Also stated in: § Study Interventions · plain
“For the dysglycemia outcome, the effects were positive in 23 (43.4%) studies and neutral in 24 (45.3%) studies, and there were insufficient data in 6 (11.3%) studies.”
Quote in the paperSubstantial claim- Also stated in: § Study Interventions · plain
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataAll included studies had a duration of at least 3 months.
“All studies had a duration of at least 3 months.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAmong 10 (18.9%) studies with a low risk of bias in all outcomes and an intervention duration of at least 1 year, none assessed T2DM development; dysglycemia effects were positive in 7 (70%), neutral in 2 (20%), and insufficient in 1 (10%).
“Among the 10 (18.9%) studies with a low risk of bias in all outcomes and an intervention duration of at least 1 year, none assessed the development of T2DM; the effects of DHIs on dysglycemia were positive in 7 (70%) studies and neutral in 2 (20%) studies, and there were insufficient data in 1 (10%) study.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataRandomized controlled trials were the most common research design (n=31, 58.5%).
“RCTs were the most common research design (n=31, 58.5%).”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationMost included studies were conducted in health care settings (n=35, 66%) and in high-income countries (n=49, 92.5%).
“Most studies were conducted in health care settings (n=35, 66%) and in high-income countries (n=49, 92.5%) [84].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [84] World Bank country and lending groupsWorld Bank20242025-04-17https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Findingown dataThere were no high risks of bias in consumer experience and health care cost outcomes, with the majority having low risks (n=37, 70%, and n=35, 66.7%, respectively).
“There were no high risks of bias in consumer experience and health care cost outcomes, with the majority having low risks (n=37, 70%, and n=35, 66.7%, respectively).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn total, 3373 citations were retrieved, 53 (1.6%) met the inclusion criteria, encompassing 34,488 participants.
“In total, 3373 citations were retrieved from the database search, of which 53 (1.6%) met the inclusion criteria, encompassing a total of 34,488 participants.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThere were 24 (45.3%) studies with a low risk of bias in all outcomes and 10 (41.7%) studies with both a low risk of bias and an intervention duration of at least 1 year.
“There were 24 (45.3%) studies with a low risk of bias in all outcomes and 10 (41.7%) studies with both a low risk of bias and an intervention duration of at least 1 year.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe DHI duration ranged from 1 to 48 months.
“The DHI duration fluctuated from 1 to 48 months.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenNo studies reported the effects of on-demand communication on HCP experience.
“No studies reported the effects of on-demand communication on HCP experience.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataOf 47 studies assessing TCP effects on dysglycemia changes, 24 (51.1%) reported neutral and 23 (48.9%) positive effects.
“Of the 47 (88.7%) studies assessing dysglycemia changes, 24 (51.1%) reported neutral effects, and 23 (48.9%) posted positive effects.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataOf 15 PPC studies assessing dysglycemia, 10 (66.7%) posted positive effects and 5 (33.3%) showed no discernible effect.
“Of the 15 (93.8%) PPC studies assessing dysglycemia changes, 10 (66.7%) posted positive effects and 5 (33.3%) showed no discernible effect.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataOf 20 TM studies assessing glycemia, 11 (55%) showed that TM improves HbA1c or blood glucose significantly and 9 (45%) reported neutral effects.
“Of the 20 (80%) studies assessing changes in the glycemia status of participants, 11 (55%) showed that TM improves HbA1c or blood glucose significantly and 9 (45%) reported neutral effects.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn 37 (69.8%) studies, PHT allowed individuals to self-monitor their health or diagnostic data (n=28, 75.7%) or actively capture/store health data to the digital platform (n=15, 40.5%).
“In 37 (69.8%) studies, PHT allowed individuals to self-monitor their health or diagnostic data (n=28, 75.7%) or actively capture/store health data to the digital platform (n=15, 40.5%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataOf 37 PHT studies, 34 (91.9%) assessed dysglycemia changes, with positive (61.8%) and neutral (38.2%) effects.
“Of the 37 (69.8%) studies, 34 (91.9%) assessed the effectiveness of PHT in dysglycemia changes, with both positive (61.8%) and neutral (38.2%) effects.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataOf 10 studies reviewing TCP effects on T2DM prevention, 9 (90%) were neutral and 1 (10%) was positive.
“Of the 10 (18.9%) studies reviewing the effects of TCP on T2DM prevention, 9 (90%) were neutral, and 1 (10%) was positive.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataEffects of PHR and HCP DS on T2DM prevention, consumer experience, HCP experience, and health care costs were not included in the study.
“Effects on T2DM prevention, consumer experience, HCP experience, and health care costs were not included in the study.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataTCP effects on consumer experience were mixed, on HCP experience positive, and on health care cost neutral (n=1, 33.3%) or negative (n=2, 66.7%).
“The effects of TCP on consumer experience was mixed, on HCP experience was positive, and on health care cost was neutral (n=1, 33.3%) or negative (n=2, 66.7%).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataTM included remote consultations (n=25, 47.2%) and remote health monitoring (n=7, 13.2%).
“TM included remote consultations (n=25, 47.2%) and remote health monitoring (n=7, 13.2%).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataOf 10 PHT studies on consumer experience, 4 (40%) showed a positive effect, 3 (30%) negative, 2 (20%) neutral, and 1 (10%) mixed.
“Of the 10 (27%) studies assessing the effects of PHT on consumer experience, the results varied; 4 (40%) studies showed a positive effect, 3 (30%) showed a negative effect, 2 (20%) were inconclusive or neutral, and 1 (10%) showed mixed effects.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThere are insufficient studies on HCP experience and health care costs.
“The effects of DHIs on T2DM prevention, as measured by the quadruple aims, have not been comprehensively assessed, with proven benefits for population health, mixed results for consumer experience, and insufficient studies on HCP experience and health care costs.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataHealth records and HCP DS were the least common in this review, with only 1 included study showing neutral effects.
“Health records and HCP DS were the least common in our review, with only 1 included study showing neutral effects.”
Quote in the paperSubstantial claimMay combine two claims.
FindingreasoningAutomatic data capture in wearables and medical devices received more positive feedback than manual data capture, which had only neutral or negative effects.
“Automatic data capture in wearables and medical devices received more positive feedback than manual data capture, which had only neutral or negative effects.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThere were insufficient studies assessing HCP experience (1 study) and health care costs (3 studies).
“Finally, there were insufficient studies assessing HCP experience (1 study) and health care costs (3 studies).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAmong successful studies, the one that reported delaying the development of T2DM and 16 (69.6%) of those reporting improvements in dysglycemia involved HCP interaction.
“Among these successful studies, the one that reported delaying the development of T2DM and 16 (69.6%) of those reporting improvements in dysglycemia involved HCP interaction.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataData extraction was checked by two reviewers, and discordance was resolved by consensus.
“Data from the selected papers were extracted and then checked (TD and QO). Any discordance was resolved via discussion and consensus of the reviewers.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe protocol of this systematic review was prospectively registered at PROSPERO (CRD42024512690).
“The protocol of our systematic review was prospectively registered at PROSPERO (International Prospective Register of Systematic Reviews; registration number CRD42024512690).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataTitles and abstracts were screened twice by four reviewers, and full texts were independently evaluated by reviewers.
“Titles and abstracts of identified studies were screened twice (by TD, WW, QO, and LW) for potential eligibility using the inclusion and exclusion criteria. Full texts that met the inclusion criteria were retrieved and independently evaluated for their eligibility by the reviewers.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThis is the first systematic review to evaluate the effects of DHIs on the quadruple aims in T2DM prevention.
“This is the first systematic review to evaluate the effects of DHIs on the quadruple aims in T2DM prevention.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataMost neutral studies still demonstrated clinical improvements in T2DM development, though these improvements did not reach statistical significance.
“Despite this, most of these neutral studies still demonstrated clinical improvements in T2DM development, though these improvements did not reach statistical significance.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThis is the first systematic review of T2DM prevention using WHO's DHI classification.
“This is also the first systematic review of T2DM prevention using WHO’s DHI classification”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThere is emerging evidence supporting the effectiveness of DHIs in preventing T2DM; however, the evidence remains limited.
“First, there is emerging evidence supporting the effectiveness of DHIs in preventing T2DM; however, the evidence remains limited.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataThe evidence is clearer on dysglycemia, where the effects were positive in nearly half of the studies and neutral in the other half.
“The evidence is clearer on dysglycemia, where the effects were positive in nearly half of the studies and neutral in the other half.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataAlthough PPC or DCP did not prove effective in preventing T2DM, they showed evidence of improving dysglycemia.
“Although PPC or DCP did not prove effective in preventing T2DM, they showed evidence of improving dysglycemia.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThere is a significant correlation between TM and PHT.
“Consequently, there is a significant correlation between TM and PHT.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenOur study did not summarize the intensity and frequency of the DHI used in each included study.
“Our study did not summarize the intensity and frequency of the DHI used in each included study.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationAdvanced algorithms and data from everyday activities allowed AI to provide real-time, personalized, contextual lifestyle recommendations, contributing to patient-centered care.
“Advanced algorithms and data from everyday participants’ activities allowed AI to provide lifestyle recommendations, which were real time, personalized, and contextual for each participant, contributing to delivering patient-centered care [98].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [98] 2016, WHO Global Strategy on Integrated People-Centred Health Services 2016-2026
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductreasoningIt was unfeasible to conduct a meta-analysis or certainty-of-evidence assessment due to the diversity of included studies.
“This diversity, while inclusive, posed challenges in drawing direct comparisons and made it unfeasible to conduct a meta-analysis or certainty-of-evidence assessment.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe inclusion criteria included papers in English only.
“Finally, our inclusion criteria included papers in English only.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataTCP was adopted in all included studies, demonstrating its widespread use and simplicity.
“In our review, TCP, which involves transmitting health information or health alerts and reminders to patients, was adopted in all included studies, demonstrating its widespread use and simplicity.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningSince preventing T2DM requires participants to modify lifestyles for a long period, DHIs that motivate and engage consumers may be more beneficial than DHIs targeting HCPs alone.
“Since preventing T2DM requires participants to modify lifestyles for a long period, DHIs that motivate and engage consumers may be more beneficial than DHIs targeting HCPs alone.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningHCP interaction plays a critical role in preventing T2DM, and replacing in-person HCP interactions with remote interactions has promising potential for effective DHIs for T2DM prevention.
“This underscores the critical role of HCP interaction in preventing T2DM, while also revealing the promising potential of replacing in-person HCP interactions with remote interactions for effective DHIs for T2DM prevention.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataTM may be effective in preventing T2DM and managing dysglycemia.
“Our review suggests that TM may be effective in preventing T2DM and managing dysglycemia.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningAlthough the findings in this review were different, the small number of studies suggests that it may still be feasible to implement DHIs that are cost-effective in T2DM prevention.
“Although the findings in our review were different, the small number of studies suggests that it may still be feasible to implement DHIs that are cost-effective in T2DM prevention.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationVR was used in 1 study, providing an immersive experience that increased participant engagement and enjoyment.
“VR was used in 1 study, providing an immersive experience that increased participant engagement and enjoyment [99].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [99] source
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe English-only inclusion criterion may have potentially excluded some relevant studies.
“This may have potentially excluded some relevant studies.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataTCP, PHT, and TM showed some evidence as potentially useful tools for T2DM prevention and dysglycemia.
“Targeted communication with persons (TCP), personal health tracking (PHT), and telemedicine (TM) showed some evidence as a potentially useful tool for T2DM prevention and dysglycemia.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationRecent evidence from diabetes prevention programs shows that long intervention durations are required for delaying T2DM, with the National Health Service recommending at least 9 months and the Centers for Disease Control and Prevention suggesting 12 months.
“However, recent evidence from DPPs that have proven to be successful shows that long intervention durations are required for delaying T2DM [88], with the National Health Service recommending at least 9 months and the Centers for Disease Control and Prevention suggesting 12 months.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [88] Diabetes prevention program (DPP)National Institutes of Health2025-04-18https://www.niddk.nih.gov/about-niddk/research-areas/diabetes/diabetes-prevention-program-dpp
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
The paper relies on this without support.
The impact of DHIs on the burden of T2DM, as measured by the quadruple aims, is largely unknown.
“It is unknown how DHIs can impact the burden of type 2 diabetes mellitus (T2DM), as measured by the quadruple aims.”
“The impacts of DHIs on improving the burden of T2DM, as measured by the quadruple aims, still remain largely unknown.”
The paper relies on this without support.
The diagnostic criteria for T2DM include HbA1c, blood glucose, and clinical criteria.
“considering that the diagnostic criteria for T2DM include HbA1c, blood glucose, and clinical criteria”
The paper relies on this without support.
DHIs are intended for real-life implementation.
“DHIs are intended for real-life implementation”
The paper relies on this without support.
The condition of RCTs is unlikely to match routine settings.
“the condition of RCTs is unlikely to match those routine settings”
The paper relies on this without support.
Patients with chronic liver disease or renal transplant are often difficult to enroll in RCTs.
“groups that are often difficult to enroll in RCTs”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Health care cost results disagree on count and effect
MajorOne passage says costs were assessed in two studies and the effects were negative. Another accounts for three studies, including one with a neutral effect.
“The effects of DHIs on costs, assessed in 2 (3.8%) studies, were found to be negative.”
“The effects of TCP on consumer experience was mixed, on HCP experience was positive, and on health care cost was neutral (n=1, 33.3%) or negative (n=2, 66.7%).”
Three of 13 DCP studies is not 15.4%
MinorThe stated denominator is 13 DCP studies. Three studies represent approximately 23.1%, not 15.4%.
Reported 15.4 · recomputed 23.076923
“Of the 13 (24.5%) studies on DCP, 11 (84.6%) consisted of seeking supporting information and 3 (15.4%) simulated human-like conversations.”
PPC consumer experience is described as both negative-only and positive
MinorThe PPC section identifies one study reporting consumer experience and describes its feedback as negative. Table 2 nevertheless lists both negative and positive PPC consumer experience effects.
“A PPC study (6.3%) by Katula et al [37] reported consumer experience, with negative feedback of consumers.”
“| PPCe | Neutral | Neutral/positive | Negative/positive | N/Af | Negative |”
PHT cost finding contradicts claim that no studies reported costs
MinorThe PHT section says no studies reported health care costs, but Table 2 assigns PHT a negative health care cost effect.
“No studies reported HCP experience or health care costs.”
“| PHTg | Neutral/positive | Neutral/positive | Negative/neutral/positive | N/A | Negative |”
Cites
The PRISMA 2020 statement: An updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · BMJ · doi:10.1136/bmj.n71 · Cited by 108,283 · see citing works
RoB 2: a revised tool for assessing risk of bias in randomised trials
Sterne, J. A. C., Savović, J., Page, M. J., Elbers, R. G., Blencowe, N. S., Boutron, I., Cates, C. J., Cheng, H.-Y., Corbett, M. S., Eldridge, S. M., et al. (2019) · BMJ · doi:10.1136/bmj.l4898 · Cited by 33,583 · see citing works
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions
Sterne, J. A., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., Henry, D., Altman, D. G., Ansari, M. T., Boutron, I., et al. (2016) · BMJ · doi:10.1136/bmj.i4919 · Cited by 20,329 · see citing works
Tuomilehto, J., Lindström, J., Eriksson, J. G., Valle, T. T., Hämäläinen, H., Ilanne-Parikka, P., Keinänen-Kiukaanniemi, S., Laakso, M., Louheranta, A., Rastas, M., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200105033441801 · Cited by 10,873 · see citing works
2. Classification and Diagnosis of Diabetes: <i>Standards of Medical Care in Diabetes—2022</i>
American Diabetes Association Professional Practice Committee (2022) · Diabetes Care · doi:10.2337/dc22-s002 · Cited by 4,792 · see citing works
From Triple to Quadruple Aim: Care of the Patient Requires Care of the Provider
Bodenheimer, T., & Sinsky, C. (2014) · The Annals of Family Medicine · doi:10.1370/afm.1713 · Cited by 3,462 · see citing works
The Diabetes Prevention Program (DPP)
The Diabetes Prevention Program (DPP) Research Group (2002) · Diabetes Care · doi:10.2337/diacare.25.12.2165 · Cited by 1,938 · see citing works
Ramachandran, A., Snehalatha, C., Mary, S., Mukesh, B., Bhaskar, A. D., Vijay, V., & Indian Diabetes Prevention Programme (IDPP) (2006) · Diabetologia · doi:10.1007/s00125-005-0097-z · Cited by 1,881 · see citing works
International Diabetes Federation: a consensus on Type 2 diabetes prevention
Alberti, K. G. M. M., Zimmet, P., & Shaw, J. (2007) · Diabetic Medicine · doi:10.1111/j.1464-5491.2007.02157.x · Cited by 778 · see citing works
6. Glycemic Targets: <i>Standards of Care in Diabetes—2023</i>
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Hilliard, M. E., Isaacs, D., Johnson, E. L., et al. (2023) · Diabetes Care · doi:10.2337/dc23-s006 · Cited by 684 · see citing works
Making health habitual: the psychology of ‘habit-formation’ and general practice
Gardner, B., Lally, P., & Wardle, J. (2012) · British Journal of General Practice · doi:10.3399/bjgp12x659466 · Cited by 591 · see citing works
The cost-effectiveness of digital health interventions: A systematic review of the literature
Gentili, A., Failla, G., Melnyk, A., Puleo, V., Tanna, G. L. D., Ricciardi, W., & Cascini, F. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.787135 · Cited by 444 · see citing works
Block, G., Azar, K. M., Romanelli, R. J., Block, T. J., Hopkins, D., Carpenter, H. A., Dolginsky, M. S., Hudes, M. L., Palaniappan, L. P., & Block, C. H. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4897 · Cited by 255 · see citing works
3. Prevention or Delay of Diabetes and Associated Comorbidities: Standards of Care in Diabetes—2023
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Gaglia, J. L., Hilliard, M. E., Isaacs, D. M., et al. (2022) · Diabetes Care · doi:10.2337/dc23-s003 · Cited by 210 · see citing works
Sepah, S. C., Jiang, L., & Peters, A. L. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.4052 · Cited by 206 · see citing works
Self-citationA Novel Diabetes Prevention Intervention Using a Mobile App
Fukuoka, Y., Gay, C. L., Joiner, K. L., & Vittinghoff, E. (2015) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2015.01.003 · Cited by 204 · see citing works
Van Rhoon, L., Byrne, M., Morrissey, E., Murphy, J., & McSharry, J. (2020) · DIGITAL HEALTH · doi:10.1177/2055207620914427 · Cited by 182 · see citing works
Ferrara, A., Hedderson, M. M., Brown, S. D., Albright, C. L., Ehrlich, S. F., Tsai, A.-L., Caan, B. J., Sternfeld, B., Gordon, N. P., Schmittdiel, J. A., et al. (2016) · Diabetes Care · doi:10.2337/dc15-1254 · Cited by 171 · see citing works
The Influence of Wearables on Health Care Outcomes in Chronic Disease: Systematic Review
Mattison, G., Canfell, O., Forrester, D., Dobbins, C., Smith, D., Töyräs, J., & Sullivan, C. (2022) · Journal of Medical Internet Research · doi:10.2196/36690 · Cited by 171 · see citing works
Self-citationSchippers, M., Adam, P. C. G., Smolenski, D. J., Wong, H. T. H., & de Wit, J. B. F. (2017) · Obesity Reviews · doi:10.1111/obr.12492 · Cited by 150 · see citing works
Machine Learning and Smart Devices for Diabetes Management: Systematic Review
Makroum, M. A., Adda, M., Bouzouane, A., & Ibrahim, H. (2022) · Sensors · doi:10.3390/s22051843 · Cited by 145 · see citing works
Nicklas, J. M., Zera, C. A., England, L. J., Rosner, B. A., Horton, E., Levkoff, S. E., & Seely, E. W. (2014) · Obstetrics & Gynecology · doi:10.1097/aog.0000000000000420 · Cited by 140 · see citing works
Castro Sweet, C. M., Chiguluri, V., Gumpina, R., Abbott, P., Madero, E. N., Payne, M., Happe, L., Matanich, R., Renda, A., & Prewitt, T. (2018) · Journal of Aging and Health · doi:10.1177/0898264316688791 · Cited by 130 · see citing works
Lee, Y., Kim, G., Jun, J. E., Park, H., Lee, W. J., Hwang, Y., & Kim, J. H. (2023) · Diabetes Care · doi:10.2337/dc22-1929 · Cited by 116 · see citing works
Ehrhardt, N. M., & Zaghal, E. A. (2018) · Journal of Diabetes Science and Technology · doi:10.1177/1932296818790994 · Cited by 111 · see citing works
Toro-Ramos, T., Michaelides, A., Anton, M., Karim, Z., Kang-Oh, L., Argyrou, C., Loukaidou, E., Charitou, M. M., Sze, W., & Miller, J. D. (2020) · JMIR mHealth and uHealth · doi:10.2196/17842 · Cited by 107 · see citing works
Barwais, F. A., Cuddihy, T. F., & Tomson, L. (2013) · Health and Quality of Life Outcomes · doi:10.1186/1477-7525-11-183 · Cited by 104 · see citing works
Everett, E., Kane, B., Yoo, A., Dobs, A., & Mathioudakis, N. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9723 · Cited by 101 · see citing works
Digital Therapeutics in Hypertension: Evidence and Perspectives
Kario, K., Harada, N., & Okura, A. (2022) · Hypertension · doi:10.1161/hypertensionaha.122.19414 · Cited by 99 · see citing works
A Review of Technology-Assisted Interventions for Diabetes Prevention
Grock, S., Ku, J.-H., Kim, J., & Moin, T. (2017) · Current Diabetes Reports · doi:10.1007/s11892-017-0948-2 · Cited by 91 · see citing works
Effects of a Digital Diabetes Prevention Program: An RCT
Katula, J. A., Dressler, E. V., Kittel, C. A., Harvin, L. N., Almeida, F. A., Wilson, K. E., Michaud, T. L., Porter, G. C., Brito, F. A., Goessl, C. L., et al. (2022) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2021.10.023 · Cited by 86 · see citing works
Digital interventions for the management of chronic obstructive pulmonary disease
Janjua, S., Banchoff, E., Threapleton, C. J., Prigmore, S., Fletcher, J., & Disler, R. T. (2021) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd013246.pub2 · Cited by 85 · see citing works
Nanditha, A., Thomson, H., Susairaj, P., Srivanichakorn, W., Oliver, N. S., Godsland, I. F., Majeed, A., Darzi, A. W., Satheesh, K., Simon, M., et al. (2020) · Diabetologia · doi:10.1007/s00125-019-05061-y · Cited by 71 · see citing works
Holmes, V. A., Draffin, C. R., Patterson, C. C., Francis, L., Irwin, J., McConnell, M., Farrell, B., Brennan, S. F., McSorley, O., Wotherspoon, A. C., et al. (2018) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2017-02654 · Cited by 68 · see citing works
Australia's digital health journey
Hambleton, S. J., & Aloizos, J. (2019) · The Medical Journal of Australia · doi:10.5694/mja2.50039 · Cited by 68 · see citing works
Singareddy, S., Vijay Prabhu, S. N., Jaramillo, A. P., Yasir, M. B., Iyer, N., Hussein, S., & Nath, T. S. (2023) · Cureus · doi:10.7759/cureus.46066 · Cited by 67 · see citing works
Efficacy of the Type 2 Diabetes Prevention Using LifeStyle Education Program RCT
Aguiar, E. J., Morgan, P. J., Collins, C. E., Plotnikoff, R. C., Young, M. D., & Callister, R. (2015) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2015.08.020 · Cited by 65 · see citing works
Use of Mobile Health Technology in the Prevention and Management of Diabetes Mellitus
Hartz, J., Yingling, L., & Powell-Wiley, T. M. (2016) · Current Cardiology Reports · doi:10.1007/s11886-016-0796-8 · Cited by 64 · see citing works
Donevant, S. B., Dawson, R. M., Culley, J. M., Habing, B., & Adams, S. A. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy104 · Cited by 64 · see citing works
Lim, S. L., Ong, K. W., Johal, J., Han, C. Y., Yap, Q. V., Chan, Y. H., Zhang, Z. P., Chandra, C. C., Thiagarajah, A. G., & Khoo, C. M. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2021.780567 · Cited by 61 · see citing works
Ross, J., Barron, E., McGough, B., Valabhji, J., Daff, K., Irwin, J., Henley, W., & Murray, E. (2022) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2021-002736 · Cited by 60 · see citing works
Applications of Digital Health Technologies in Knee Osteoarthritis: Narrative Review
Shah, N., Costello, K. E., Mehta, A., & Kumar, D. (2022) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/33489 · Cited by 60 · see citing works
Peacock, A. S., Bogossian, F. E., Wilkinson, S. A., Gibbons, K. S., Kim, C., & McIntyre, H. D. (2015) · International Journal of Endocrinology · doi:10.1155/2015/423717 · Cited by 59 · see citing works
Limaye, T., Kumaran, K., Joglekar, C., Bhat, D., Kulkarni, R., Nanivadekar, A., & Yajnik, C. (2017) · Diabetic Medicine · doi:10.1111/dme.13258 · Cited by 50 · see citing works
Mobile App to Reduce Inactivity in Sedentary Overweight Women
Finkelstein, J., Bedra, M., Li, X., Jeffrey, W., & Ouyang, P. (2015) · Studies in health technology and informatics · doi:10.3233/978-1-61499-564-7-89 · Cited by 43 · see citing works
Mann, D. M., Palmisano, J., & Lin, J. J. (2016) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2016.05.012 · Cited by 42 · see citing works
Sakane, N., Kotani, K., Takahashi, K., Sano, Y., Tsuzaki, K., Okazaki, K., Sato, J., Suzuki, S., Morita, S., Oshima, Y., et al. (2015) · BMJ Open · doi:10.1136/bmjopen-2014-007316 · Cited by 40 · see citing works
Al‐Hamdan, R., Avery, A., Aldisi, D. A., et al. (2021) · Journal of Diabetes Investigation · doi:10.1111/jdi.13531 · Cited by 40 · see citing works
Kitazawa, M., Takeda, Y., Hatta, M., Horikawa, C., Sato, T., OSAWA, T., Ishizawa, M., Suzuki, H., Matsubayashi, Y., Fujihara, K., et al. (2023) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgad639 · Cited by 40 · see citing works
Staite, E., Bayley, A., Al-Ozairi, E., Stewart, K., Hopkins, D., Rundle, J., Basudev, N., Mohamedali, Z., & Ismail, K. (2020) · JMIR mHealth and uHealth · doi:10.2196/15448 · Cited by 39 · see citing works
Rollo, M. E., Baldwin, J., Hutchesson, M., Aguiar, E. J., Wynne, K., Young, A. M., Callister, R., Haslam, R. L., & Collins, C. E. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17197115 · Cited by 39 · see citing works
Lakka, T. A., Aittola, K., Järvelä‐Reijonen, E., Tilles‐Tirkkonen, T., Männikkö, R., Lintu, N., Karhunen, L. J., Kolehmainen, M., Harjumaa, M., Mattila, E., et al. (2022) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2022.100527 · Cited by 38 · see citing works
Kim, J. Y., Wineinger, N. E., Taitel, M., Radin, J. M., Akinbosoye, O., Jiang, J., Nikzad, N., Orr, G., Topol, E., & Steinhubl, S. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.6371 · Cited by 37 · see citing works
Type 2 Diabetes Prevention Focused on Normalization of Glycemia: A Two-Year Pilot Study
McKenzie, A. L., Athinarayanan, S. J., McCue, J. J., Adams, R. N., Keyes, M., McCarter, J. P., Volek, J. S., Phinney, S. D., & Hallberg, S. J. (2021) · Nutrients · doi:10.3390/nu13030749 · Cited by 37 · see citing works
Moravcová, K., Karbanová, M., Bretschneider, M. P., Sovová, M., Ožana, J., & Sovová, E. (2022) · Nutrients · doi:10.3390/nu14102005 · Cited by 37 · see citing works
Show me the money: how do we justify spending health care dollars on digital health?
Woods, L. S., Eden, R., Canfell, O. J., Nguyen, K., Comans, T. A., & Sullivan, C. M. (2022) · The Medical Journal of Australia · doi:10.5694/mja2.51799 · Cited by 37 · see citing works
Self-citationRoutine measurement of patient experience
Benson, T., & Benson, A. (2023) · BMJ Open Quality · doi:10.1136/bmjoq-2022-002073 · Cited by 37 · see citing works
Sly, B., Russell, A. W., & Sullivan, C. (2022) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2021.104596 · Cited by 36 · see citing works
Self-citationCha, E., Kim, K. H., Umpierrez, G., Dawkins, C. R., Bello, M. K., Lerner, H. M., Narayan, K. M. V., & Dunbar, S. B. (2014) · The Diabetes Educator · doi:10.1177/0145721714539736 · Cited by 35 · see citing works
Self-Management Mobile Virtual Reality Program for Women with Gestational Diabetes
Kim, S.-H., Kim, H. J., & Shin, G. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18041539 · Cited by 31 · see citing works
Khunti, K. K., Griffin, S. J., Brennan, A., Dallosso, H. M., Davies, M. J., Eborall, H., Edwardson, C. L., Gray, L. J., Hardeman, W., Heathcote, L., et al. (2021) · Health Technology Assessment · doi:10.3310/hta25770 · Cited by 29 · see citing works
Chung, H.-W., Tai, C.-J., Chang, P., Su, W.-L., & Chien, L.-Y. (2023) · JMIR mHealth and uHealth · doi:10.2196/41099 · Cited by 29 · see citing works
Nguyen, V. L., Ara, P., Simmons, D., & Osuagwu, U. L. (2024) · Clinical Medicine Insights Endocrinology and Diabetes · doi:10.1177/11795514241246419 · Cited by 26 · see citing works
Neto, O. L., & von Wyl, V. (2023) · JMIR Public Health and Surveillance · doi:10.2196/49575 · Cited by 25 · see citing works
Recent Findings on the Effectiveness of Peer Support for Patients with Type 2 Diabetes
Werner, J. J., Ufholz, K., & Yamajala, P. (2024) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-024-00737-6 · Cited by 24 · see citing works
Asthana, S., & Prime, S. J. (2023) · Frontiers in Health Services · doi:10.3389/frhs.2023.1225757 · Cited by 23 · see citing works
Karvela, M., Golden, C. T., Bell, N., Martin-Li, S., Bedzo-Nutakor, J., Bosnic, N., DeBeaudrap, P., de Mateo-Lopez, S., Alajrami, A., Qin, Y., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-55105-6 · Cited by 23 · see citing works
Brazeau, A., Leong, A., Meltzer, S. J., Cruz, R., DaCosta, D., Hendrickson-Nelson, M., Joseph, L., Dasgupta, K., & MoMM study group (2014) · Cardiovascular Diabetology · doi:10.1186/1475-2840-13-104 · Cited by 22 · see citing works
Muralidharan, S., Ranjani, H., Anjana, R. M., Gupta, Y., Ambekar, S., Koppikar, V., Jagannathan, N., Jena, S., Tandon, N., Allender, S., et al. (2021) · DIGITAL HEALTH · doi:10.1177/20552076211039032 · Cited by 22 · see citing works
Wilson, M. G., Castro, C. M., Edge, M. D., Madero, E. N., McGuire, M., Pilsmaker, M., Carpenter, D., & Kirschner, S. (2017) · Journal of Occupational and Environmental Medicine · doi:10.1097/jom.0000000000001091 · Cited by 20 · see citing works
Potzel, A. L., Gar, C., Banning, F., Sacco, V., Fritsche, A., Fritsche, L., Müssig, K., Dauben, L., Seissler, J., & Lechner, A. (2022) · PLOS ONE · doi:10.1371/journal.pone.0267258 · Cited by 20 · see citing works
Summers, C., Tobin, S., & Unwin, D. (2021) · JMIR Diabetes · doi:10.2196/25751 · Cited by 19 · see citing works
Lee, J., Lim, S., Cha, S., Han, C.-J., Jung, A. R., Kim, K.-R., Yoon, K., & Ko, S. (2021) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2020.0225 · Cited by 17 · see citing works
Healthcare Professionals’ Experience of Performing Digital Care Visits—A Scoping Review
Lampickienė, I., & Davoody, N. (2022) · Life · doi:10.3390/life12060913 · Cited by 16 · see citing works
Vaughan, E. M., Cardenas, V. J., Chan, W., Amspoker, A. B., Johnston, C. A., Virani, S. S., Ballantyne, C. M., & Naik, A. D. (2023) · Journal of General Internal Medicine · doi:10.1007/s11606-023-08434-7 · Cited by 16 · see citing works
Tokunaga-Nakawatase, Y., Nishigaki, M., Taru, C., Miyawaki, I., Nishida, J., Kosaka, S., Sanada, H., & Kazuma, K. (2014) · Primary care diabetes · doi:10.1016/j.pcd.2014.01.007 · Cited by 15 · see citing works
Patel, M. S., Polsky, D. E., Small, D. S., Park, S.-H., Evans, C. N., Harrington, T. O., DJARAHER, R. L., Changolkar, S., Snider, C. K., & Volpp, K. G. M. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00541-1 · Cited by 14 · see citing works
Sevilla-González, M. D. R., Bourguet-Ramirez, B., Lazaro-Carrera, L. S., Martagón, A. J., Gómez‐Velasco, D., & Viveros-Ruiz, T. L. (2021) · JMIR Diabetes · doi:10.2196/25105 · Cited by 12 · see citing works
Petroni, M. L., Brodosi, L., Armandi, A., Marchignoli, F., Bugianesi, E., & Marchesini, G. (2023) · Nutrients · doi:10.3390/nu15030792 · Cited by 12 · see citing works
Savas, L. A., Grady, K., Cotterill, S., Summers, L., Boaden, R., & Gibson, J. M. (2015) · Primary Care Diabetes · doi:10.1016/j.pcd.2014.07.003 · Cited by 11 · see citing works
Complementarity of Digital Health and Peer Support: “This Is What’s Coming”
Tang, P. Y., Duni, J., Peeples, M. M., Kowitt, S. D., Bhushan, N. L., Sokol, R. L., & Fisher, E. B. (2021) · Frontiers in Clinical Diabetes and Healthcare · doi:10.3389/fcdhc.2021.646963 · Cited by 11 · see citing works
Vahlberg, B. M., Lundström, E., Eriksson, S., Holmbäck, U. C., & Cederholm, T. (2021) · BMJ Open · doi:10.1136/bmjopen-2021-054851 · Cited by 11 · see citing works
Pires, M., Shaha, S. K., King, C., Morrison, J., Nahar, T., Ahmed, N., Jennings, H. M., Akter, K., Haghparast‐Bidgoli, H., Khan, A., et al. (2022) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2021-217293 · Cited by 11 · see citing works
Laur, C. V., Agarwal, P., Thai, K., Kishimoto, V., Kelly, S., Liang, K., Bhatia, R. S., Bhattacharyya, O. K., Martin, D., & Mukerji, G. (2022) · JMIR Human Factors · doi:10.2196/35091 · Cited by 10 · see citing works
Bhatti, S., Dahrouge, S., Muldoon, L. K., & Rayner, J. (2022) · BJGP Open · doi:10.3399/bjgpo.2022.0031 · Cited by 10 · see citing works
Alcántara-Aragón, V., Rodrigo-Cano, S., Lupianez-Barbero, A., Martínez, M. J., Martinez, C., Tapia, J. A. R., Iniesta-Chamorro, J. M., Tenés, S., Urgell, E., Navarro, G., et al. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0456 · Cited by 9 · see citing works
Exercise and Prediabetes After Renal Transplantation (EXPRED-I): A Prospective Study
Morales Febles, R., Marrero Miranda, D., Jiménez Sosa, A., González Rinne, A., Cruz Perera, C., Rodríguez-Rodríguez, A. E., Álvarez González, A., Díaz Martín, L., Negrín Mena, N., Acosta Sørensen, C., et al. (2023) · Sports Medicine - Open · doi:10.1186/s40798-023-00574-8 · Cited by 9 · see citing works
Virtual reality tools for training in gastrointestinal endoscopy: A systematic review
Dương, T. Q., & Soldera, J. (2024) · Artificial Intelligence in Gastrointestinal Endoscopy · doi:10.37126/aige.v5.i2.92090 · Cited by 9 · see citing works
Ranjani, H., Sharma, N., Anjana, R., Ramalingam, S., Mohan, V., & Saligram, N. (2020) · Journal of Diabetology · doi:10.4103/jod.jod_6_19 · Cited by 7 · see citing works
Bock, B. C., Dunsiger, S. I., Wu, W.-C., Ciccolo, J. T., Serber, E. R., Lantini, R., & Marcus, B. H. (2019) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2019.06.011 · Cited by 6 · see citing works
Fitzpatrick, S. L., Mayhew, M., Rawlings, A. M., Smith, N., Nyongesa, D. B., Vollmer, W. M., Stevens, V. J., Grall, S. K., & Fortmann, S. P. (2022) · Clinical Diabetes · doi:10.2337/cd21-0114 · Cited by 5 · see citing works
Arora, S., Lam, C. N., Burner, E., & Menchine, M. (2024) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231162601 · Cited by 5 · see citing works
Neri, S., & Ornaghi, A. (2014) · Springer eBooks · doi:10.1007/978-94-007-0753-5_1260 · Cited by 4 · see citing works
Salmon, M. K., Gordon, N., Constantinou, D., Reid, K. S., Wright, B. S., Kridl, T. L., & Faircloth, G. C. (2021) · American Journal of Lifestyle Medicine · doi:10.1177/15598276211019012 · Cited by 2 · see citing works
Technology and Human Connection to Prevent Diabetes in Rural United States
Dachel, T. A., & Mota, D. (2021) · The Journal for Nurse Practitioners · doi:10.1016/j.nurpra.2021.06.001 · Cited by 1 · see citing works
Birse, C. E., McPhaul, M. J., Arellano, A. R., Fragala, M. S., & LAGIER, R. J. (2022) · Journal of Occupational and Environmental Medicine · doi:10.1097/jom.0000000000002598 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 6
- Magliano, D, 2021, IDF Diabetes Atlas
- 2023, Classification of Digital Interventions, Services and Applications in Health: A Shared Language to Describe the Uses of Digital Technology for Health (2nd Ed.)
- 2018, Classification of Digital Health Interventions v 1
- 10.35680/2372-0247.1004 · DOI
- Finkelstein, J, 2015, Stud Health Technol Inform, 216, 89
- 2016, WHO Global Strategy on Integrated People-Centred Health Services 2016-2026
Cited by
Sorted by citations
Mathioudakis, N., Lalani, B., Abusamaan, M. S., Alderfer, M., Alver, D., Dobs, A., Kane, B., McGready, J., Riekert, K., Ringham, B., et al. (2025) · JAMA · doi:10.1001/jama.2025.19563 · Cited by 41 · see citing works
Deng, M., Yang, R., Zheng, X., Deng, Y., & Jiang, J. (2025) · Frontiers in Endocrinology · doi:10.3389/fendo.2025.1620132 · Cited by 10 · see citing works
Polu, P. R. (2026) · Obesity Medicine · doi:10.1016/j.obmed.2026.100686 · Cited by 5 · see citing works
Pinilla, L., Sansom, K., Letzelter, P., et al. (2026) · npj Digital Medicine · doi:10.1038/s41746-026-02469-w · Cited by 4 · see citing works
“These tools allow for digital phenotyping of physiological processes over extended periods, and capture dynamic fl uctuations that traditional, single timepoint assessments overlook 34 – 39 .”
Utomo, W. B., Muzdalipah, Muhajir, R. A., & Fawzi, Y. (2025) · INTERNATIONAL JOURNAL OF NURSING AND MIDWIFERY SCIENCE (IJNMS) · doi:10.29082/ijnms/2025/vol9/iss1/703 · Cited by 1 · see citing works
Glavas, C., Ma, J., Sood, S., George, E. S., Daly, R. M., Gvozdenko, E., de Courten, B. V., Scott, D. S., & Jansons, P. (2025) · Technologies · doi:10.3390/technologies13110511 · Cited by 1 · see citing works
“These modes of delivery are not exclusive to DVA devices, given that multiple digital modalities have the ability to leverage audiovisual hardware to appeal to this population [47–49].”
Digital Health Technologies for Chronic Disease Prevention: A Narrative Review
Almohammadi, A. A. (2026) · Current Medical Issues · doi:10.4103/cmi.cmi_227_25 · Cited by 2 · see citing works
Kuri, K. A. C., Viola, V., & Pozzilli, P. (2026) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2026.113389 · Cited by 1 · see citing works
Jeleff, M., Dorner, T. E., Ban, M., Schön, M., Lischka, C., Lichtenegger, K. M., Dür, M., Hochwarter, S., Feichtner, F., & Haider, S. (2026) · BMJ Open · doi:10.1136/bmjopen-2025-110671
“26 Further, DHIs may have their limitations in terms of socio-emotional skills, context-sensitive appraisal and ethical responsibility.”
Whitehead, L., Zhang, M., Kwok, W. H., Arabiat, D. H., & Towell‐Barnard, A. (2026) · JMIR Diabetes · doi:10.2196/70912
“In light of the low-to-very low certainty evidence, DHIs are best used as adjunctive tools in prediabetes management with health care provider involvement, rather than as stand-alone solutions, to maximize effectiveness [6, 48].”
Treatment outcomes in patients with ischemic stroke depending on glycemic status
Yasnii, O. M. (2026) · INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine) · doi:10.22141/2224-0721.22.2.2026.1692
Kowalska, A. M., Kuls, A. A., Sobol, A. Z., Pabis, B., Wiktorowicz, J. M., Kadłubańska, M., Bulińska, N., Sinczak, Z., Zembrzuska, S., & Bajerski, S. (2026) · International Journal of Innovative Technologies in Social Science · doi:10.31435/ijitss.2(50).2026.5544
Heterogeneity of effects of a mobile health disease management programme on glycaemic control
Shiraishi, R., Miki, T., Ishida, S., Kanai, M., Hagiwara, Y., & Ikeda, T. (2026) · BMJ Nutrition Prevention & Health · doi:10.1136/bmjnph-2025-001465
AI-Driven Lifestyle Interventions for Reducing Diabetes Risk: Systematic Review
Ekwunife, O. I., Nauta, T., Fraser, R. A., Campbell, J. A., Aidoo-Frimpong, G. A., Walker, R. J., & Egede, L. E. (2026) · Journal of Medical Internet Research · doi:10.2196/104940
- Authors
- Duong, T., Olsen, Q., Menon, A., Woods, L., Wang, W., Varnfield, M., Jiang, L., & Sullivan, C.
- Affiliations
- The University of Queensland (AU)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2025-04-25
- Volume
- 27
- Pages
- e67507
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC12064978
- OpenAlex
- W4409786397
- Cited by
- 14
- References
- 95
- Citations by year
- 2026: 10 · 2025: 4
- FWCI
- 3.46
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Metro South Health
- Đại học Huế
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- digital health interventions, type 2 diabetes prevention, Quadruple Aim, population health, customer experience, health professionals' experiences, health care costs, dysglycemia, HbA1c, Diabetes Prevention Program, telemedicine, mobile health apps, remote patient monitoring, digital therapeutics
- MeSH terms
- Digital Health, Blood Glucose, Diabetes Mellitus, Type 2, Glycated Hemoglobin, Humans, Health Care Costs, Telemedicine
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-16.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-16.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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