A village doctor-led mobile health intervention for cardiovascular risk reduction in rural China: cluster randomised controlled trial.
Zhang X, Wang S, Zhou X, Tang Y, Xing L, Ma S, Xu Y, Wu C, Cui J, Yang Y, Lin C, Wu Y, Zhang H, Fan L, Xu C, Li X, SMARTER Collaborative Group
- DOI
- 10.1136/bmj-2024-082765
- Record issued
- 2026-08-15
- Engine
- 7.39.0
- Exported
- 2026-09-21
Prepared by Alpha1. This document is confidential: it is intended for the recipient it was shared with and must not be redistributed. The live record at alpha1science.com/verify/334174e0-1f93-44a5-b6fa-6516d25489c5 is authoritative.
How this rating was calculated
- IntegrityIntegrity concern ×3−1.5★
- ClaimsEfficacy rests on an unvalidated surrogate endpoint−0.5★
- ClaimsTreatment effect not shown to be clinically meaningful−0.5★
- ReportingData & code availability partially met−0.25★
- CitationsUnresolved reference−0.25★
- No data or code availability links were detected to verify.
- 01Efficacy rests on an unvalidated surrogate endpoint
The primary outcome is the change in predicted 10-year ASCVD risk using the China-PAR model, which is a surrogate for clinical cardiovascular events. The paper does not provide evidence linking this surrogate to hard clinical outcomes, nor does it demonstrate target engagement at the tested dose (the intervention is behavioral, not a drug). The efficacy claim rests on this surrogate without validation of its clinical meaningfulness.
“The primary outcome was mean change in 10 year risk of ASCVD based on the China-PAR model from baseline to the 12 month visit”
- 02Treatment effect not shown to be clinically meaningful
The primary effect is a 1.88% absolute reduction in predicted 10-year ASCVD risk, which is a small fraction of the baseline risk (18.0% to 11.7% in intervention vs 17.8% to 13.6% in control). The paper does not anchor this to a minimal clinically important difference or demonstrate that this reduction translates into meaningful clinical benefit. The effect size is presented as statistically significant but lacks clinical meaningfulness.
“absolute difference −1.88% (95% confidence interval (CI) −2.57% to −1.19%; P<0.001)”
This Kaimen Rigor review uses Kaimen Rigor reviewers trained on a curated corpus of high-fidelity and retracted papers, with expert supervision and curation. It can still make mistakes; verify each finding against the source before relying on it.
This cluster randomised controlled trial is methodologically rigorous, with a clear premise, robust design, and transparent reporting. The main weakness is the vague and incomplete data availability statement, which lacks a repository or clear access procedure.
Both reviewers agreed on study type (interventional). The evaluation covers all eight dimensions; no dimensions were excluded as not applicable. The statistics verification checked 10 tests and found all consistent; coverage is limited to tests with a test statistic and df or an effect estimate with CI.
Numerical inconsistencies
1 finding · worst lowValues that contradict each other or are impossible for the stated sample: recomputed p-values and test statistics, GRIM/GRIMMER checks on summary numbers, percentages against their own counts, totals against their parts, and estimates against their own confidence intervals.
- Internal contradictions in the reported numbersAssessed
Recomputed 10 tests: 10 consistent, 0 inconsistent; 1 recomputed directly from the reported test statistics, 9 via agent-written checks.
- CONSISTENTreported p = .003 · recomputed p = .003Recomputed odds ratio 0.60 (95% CI 0.43–0.84), reported p=0.003
“odds ratio 0.60, 95% CI 0.43 to 0.84; P=0.003”
Taken as given: 0.43–0.84 is a two-sided 95% confidence interval for the odds ratio of 0.60, not a range, an IQR, or a different interval level; the odds ratio is a RATIO measure, so the interval is symmetric on the log scale; p=0.003 is the p for THIS estimate, not for another comparison in the same sentenceMethod: back the two-tailed p out of the log-scale CI width and compare it against the printed pHow we recomputed it: pCI(0.6, 0.43, 0.84, 1) - CONSISTENTreported p < .001 · recomputed p = <.001Reviewers 1, 2Primary outcome difference in change of 10-year ASCVD risk
“with a difference of −1.88% (−2.57% to −1.19%, P<0.001) at 12 months”
Taken as given: The estimate is the difference in mean change between groups.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported estimate and 95% CI using the normal approximation.How we recomputed it: pCI(-1.88, -2.57, -1.19, 0) - CONSISTENTreported p < .001 · recomputed p = <.001Reviewer 1Difference in lifetime ASCVD risk change
“with a difference of −4.59% (−6.22% to −2.95%, P<0.001)”
Taken as given: The estimate is the difference in mean change between groups.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported estimate and 95% CI using the normal approximation.How we recomputed it: pCI(-4.59, -6.22, -2.95, 0) - CONSISTENTreported p < .001 · recomputed p = <.001Reviewers 1, 2Difference in systolic blood pressure change
“difference −7.64 mm Hg, −9.31 to −5.98; P<0.001”
Taken as given: The estimate is the difference in mean change between groups.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported estimate and 95% CI using the normal approximation.How we recomputed it: pCI(-7.64, -9.31, -5.98, 0) - CONSISTENTreported p < .001 · recomputed p = <.001Reviewer 1Difference in diastolic blood pressure change
“difference −3.59 mm Hg, −4.66 to −2.53; P<0.001”
Taken as given: The estimate is the difference in mean change between groups.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported estimate and 95% CI using the normal approximation.How we recomputed it: pCI(-3.59, -4.66, -2.53, 0) - CONSISTENTreported p < .008 · recomputed p = .008Reviewers 1, 2Difference in fasting blood glucose change
“difference −0.30 mmol/L, −0.52 to −0.08; P=0.008”
Taken as given: The estimate is the difference in mean change between groups.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported estimate and 95% CI using the normal approximation.How we recomputed it: pCI(-0.30, -0.52, -0.08, 0) - CONSISTENTreported p < .003 · recomputed p = .003Reviewers 1, 2Odds ratio for daily smoking
“odds ratio 0.60, 95% CI 0.43 to 0.84; P=0.003”
Taken as given: The odds ratio is the effect estimate.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported odds ratio and 95% CI using the normal approximation on the log scale.How we recomputed it: pCI(0.60, 0.43, 0.84, 1) - CONSISTENTreported p < .030 · recomputed p = .026Reviewers 1, 2Odds ratio for insufficient physical activity
“odds ratio 0.63, 0.42 to 0.95; P=0.03”
Taken as given: The odds ratio is the effect estimate.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported odds ratio and 95% CI using the normal approximation on the log scale.How we recomputed it: pCI(0.63, 0.42, 0.95, 1) - CONSISTENTreported p < .001 · recomputed p = <.001Reviewers 1, 2Odds ratio for insufficient leisure time activity
“odds ratio 0.38 (0.24 to 0.59; P<0.001)”
Taken as given: The odds ratio is the effect estimate.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported odds ratio and 95% CI using the normal approximation on the log scale.How we recomputed it: pCI(0.38, 0.24, 0.59, 1) - CONSISTENTreported p = .870 · recomputed p = .875Reviewers 1, 2Hazard ratio for MACE
“hazard ratio 1.04, 0.64 to 1.70; P=0.87”
Taken as given: The hazard ratio is the effect estimate.; The 95% CI is two-sided.; The p-value is two-tailed.Method: Recomputed p-value from the reported hazard ratio and 95% CI using the normal approximation on the log scale.How we recomputed it: pCI(1.04, 0.64, 1.70, 1)
- lowinternal contradictionThe abstract reports 4533 participants randomized, but the results section reports 2284 and 2224 with outcome data, summing to 4508, leaving 25 lost to follow-up. This is consistent with the stated loss to follow-up.
4533 participants from 127 villages: 2297 (64 villages) were randomly assigned to the intervention group and 2236 (63 villages) to the control group. ... Primary and secondary outcome data were available for 2284 (99.4%) participants in the intervention group and 2224 (99.5%) in the control group.
Abstractreviewer’s wording
Overstated conclusions
3 findings · worst highConclusions that reach past what the paper's own results support — including a significance claim that no longer holds when the statistic is recomputed, and efficacy resting on an unvalidated surrogate endpoint.
- Efficacy rests on an unvalidated surrogate endpointAssessed
- Treatment effect not shown to be clinically meaningfulAssessed
- Conclusions only partially backed by the presented evidenceAssessed
4 major claims checked against the paper's own evidence: 1 only partially supported (evidence backs part of the claim; gaps or caveats remain); the rest adequately supported.
- partialReviewers 1, 2This feasible approach could be scaled up in rural China and other under-resourced settings.The intervention showed high adherence and effectiveness, but scalability is inferred from mHealth use and engagement of village doctors, not directly tested.Evidence: High adherence rates and qualitative feedback from village doctors; no implementation science evaluation.
“This feasible approach could be scaled up in rural China and other under-resourced settings to improve health management based on the local primary healthcare system.”
ConclusionFind in source - supportedReviewers 1, 2The village doctor-led mobile health intervention was effective at reducing cardiovascular risk.The primary outcome showed a statistically significant difference in 10-year ASCVD risk reduction between groups.Evidence: Primary outcome: difference −1.88% (95% CI −2.57% to −1.19%; P<0.001).
“The village doctor-led mobile health intervention was effective at reducing cardiovascular risk and improving control of behavioural and metabolic risk factors.”
AbstractFind in source - supportedReviewers 1, 2The intervention improved control of behavioural and metabolic risk factors.Secondary outcomes showed significant improvements in blood pressure, glucose, smoking, and physical activity, though not in lipids or obesity.Evidence: Secondary outcomes: SBP difference −7.64 mm Hg, DBP −3.59 mm Hg, glucose −0.30 mmol/L, smoking OR 0.60, physical activity OR 0.63; non-HDL and obesity not significant.
“Compared with the control group, the intervention group showed larger reductions in lifetime ASCVD risk (−15.9% v −11.0%; difference −4.59%; P<0.001), systolic blood pressure (−23.2 mm Hg v −15.2 mm Hg; difference −7.64 mm Hg; P<0.001), diastolic blood pressure (−10.9 mm Hg v −6.9 mm Hg; difference: −3.59 mm Hg; P<0.001), fasting blood glucose (−0.9 mmol/L v −0.5 mmol/L; difference −0.30 mmol/L; P=0.008), proportion of daily smokers (−3.1% v −0.6%; odds ratio 0.60, 95% CI 0.43 to 0.84; P=0.003), and insufficient physical activity (−3.0% v 1.3%; odds ratio 0.63, 0.42 to 0.95; P=0.03).”
AbstractFind in source - supportedReviewers 1, 2Men, non-agricultural workers, people with lower income, and those with higher cardiovascular risk showed greater benefits.Subgroup analyses showed statistically significant interaction effects for these groups.Evidence: Subgroup analysis: men difference −2.18% (P=0.048), non-agricultural workers −2.63% (P=0.03), low income −2.70% (P=0.02), higher risk −2.54% (P<0.001).
“In subgroup analysis on 10 year risk of ASCVD, the difference in change between groups was greater in men (−2.18%, −3.02% to −1.33%; P=0.048 for interaction), non-agricultural workers (−2.63%, −3.40% to −1.86%; P=0.03 for interaction), people with low income (−2.70%, −3.83% to −1.57%; P=0.02 for interaction), and those at higher baseline risk of ASCVD (−2.54%, −3.38% to −1.70%; P<0.001 for interaction) than their counterparts.”
ResultsFind in source
Premise concern: surrogate not validated for clinical benefit; effect size not shown to be clinically meaningful.
- INADEQUATESurrogate endpointThe primary outcome is the change in predicted 10-year ASCVD risk using the China-PAR model, which is a surrogate for clinical cardiovascular events. The paper does not provide evidence linking this surrogate to hard clinical outcomes, nor does it demonstrate target engagement at the tested dose (the intervention is behavioral, not a drug). The efficacy claim rests on this surrogate without validation of its clinical meaningfulness.
“The primary outcome was mean change in 10 year risk of ASCVD based on the China-PAR model from baseline to the 12 month visit”
- INADEQUATEEffect sizeThe primary effect is a 1.88% absolute reduction in predicted 10-year ASCVD risk, which is a small fraction of the baseline risk (18.0% to 11.7% in intervention vs 17.8% to 13.6% in control). The paper does not anchor this to a minimal clinically important difference or demonstrate that this reduction translates into meaningful clinical benefit. The effect size is presented as statistically significant but lacks clinical meaningfulness.
“absolute difference −1.88% (95% confidence interval (CI) −2.57% to −1.19%; P<0.001)”
Data authenticity concerns
2 findings · worst lowAn adversarial read for patterns associated with data that may not be genuine: results that look too clean, implausibly large effects, duplicated data or images, and methods that do not match the results reported.
- Data look implausibly cleanAssessed
- Other integrity concernAssessed
3 integrity concerns flagged (0 high).
- lowdata too cleanBaseline characteristics are very well balanced between groups, which is expected in a large randomized trial, but the similarity in some variables (e.g., mean systolic blood pressure 157.6 vs 157.1) is notable.
“Mean (SD) systolic blood pressure (mm Hg) | 157.4 (16.2) | 157.6 (16.3) | 157.1 (16.2)”
Table 1Find in source - lowotherThe data availability statement is truncated, which may be a copyediting issue rather than a validity concern.
“The data underlying the study findings are op”
Data availabilityFind in source
Reporting gaps
1 finding · worst mediumRequired detail the manuscript never states — study design, biological variables, ethics approval and consent, key resources, statistical reporting, data and code availability, and overall transparency.
- Data/code availability incompleteAssessed
The introduction cites the burden of cardiovascular disease in China, suboptimal implementation of lifestyle modifications, and the scarcity of mHealth evidence for primary prevention. It identifies gaps in involving primary healthcare workforce and justifies the need for the SMARTER study. Limitations of prior research are implicitly addressed by the study design, though not explicitly detailed.
“Mobile health (mHealth) tools appear promising in the secondary prevention of cardiovascular disease, but evidence on primary prevention, particularly based on randomised controlled trials, is scarce. More importantly, the primary healthcare workforce has rarely been involved, as those mHealth tools were primarily developed to support self-management.”
“To meet practical needs and fill knowledge gaps, we developed a village doctor-led health management strategy featuring scalable tools based on mHealth technologies.”
“Mobile health (mHealth) tools appear promising in the secondary prevention of cardiovascular disease, but evidence on primary prevention, particularly based on randomised controlled trials, is scarce.”
“To meet practical needs and fill knowledge gaps, we developed a village doctor-led health management strategy featuring scalable tools based on mHealth technologies.”
Randomization used a central system with minimisation algorithm and random element. Allocation concealed from statisticians; participants and village doctors unblinded due to intervention nature, which is acceptable. Power analysis provided with assumptions and achieved power. Inclusion/exclusion criteria clearly defined. Outlier handling not explicitly described but missing data approach (ITT) is stated. Controls are the usual care group. Independent replication not applicable for a single trial.
“Overall, 127 villages (clusters), stratified by counties, were randomly assigned (1:1) to either the intervention group or the control group using a central randomisation system.”
“Allocation was, however, concealed from the study statisticians.”
“The minimum sample size of 4200 participants in 120 villages (60 villages in each comparison group, and 35 participants in each village) was calculated for the primary outcome. We estimated that a study of this sample size would provide a statistical power of 90% at a two sided α of 0.05 to detect a 1.0% absolute difference (ie, 10% relative difference) in mean change in 10 year risk of ASCVD between the intervention and control groups at 12 months.”
“Overall, 127 villages (clusters), stratified by counties, were randomly assigned (1:1) to either the intervention group or the control group using a central randomisation system.”
“The minimum sample size of 4200 participants in 120 villages (60 villages in each comparison group, and 35 participants in each village) was calculated for the primary outcome.”
“The inclusion criteria for participants were age ≥35 years with a predicted 10 year risk of atherosclerotic cardiovascular disease (ASCVD) of ≥10% based on the China-PAR (Prediction for ASCVD Risk in China) risk prediction model, ownership of a smartphone and understanding how to use basis apps, and contract with the local village doctor for family doctor services.”
Sex is reported for all participants (50.3% women). Age, blood pressure, glucose, lipids, BMI, and other health indicators are reported. Demographics include age, sex, education, occupation, income, marital status, and insurance. Since both sexes are enrolled, sex_justified is not applicable. Species/strain and housing conditions are not applicable for a human trial.
“The mean age of participants was 57.7 (SD 8.2) years, 2282 (50.3%) were women”
“At baseline, mean systolic and diastolic blood pressure was 157.4 (SD 16.2) mm Hg and 93.0 (SD 10.9) mm Hg, respectively, fasting blood glucose level was 7.1 (SD 2.6) mmol/L, and non-high density lipoprotein cholesterol level was 3.4 (SD 1.3) mmol/L.”
“The mean age of participants was 57.7 (SD 8.2) years, 2282 (50.3%) were women”
“At baseline, mean systolic and diastolic blood pressure was 157.4 (SD 16.2) mm Hg and 93.0 (SD 10.9) mm Hg, respectively, fasting blood glucose level was 7.1 (SD 2.6) mmol/L”
The trial was approved by the central ethics committee at Fuwai Hospital with approval number 2022-1781. Written informed consent was obtained from all participants. Regulatory compliance is implied by adherence to ethical standards, though not explicitly named.
“This trial was approved (approval No 2022-1781) by the central ethics committee at Fuwai Hospital, Beijing, China.”
“Written informed consent was obtained from all participants before inclusion.”
“This trial was approved (approval No 2022-1781) by the central ethics committee at Fuwai Hospital, Beijing, China.”
“Written informed consent was obtained from all participants before inclusion.”
The smart band (Huawei Band 4) is identified with manufacturer. The WeChat mini program and SAS 9.4 are named. No antibodies, cell lines, or organisms are used. Reagents are not applicable. Software tools are identified with version.
“Each participant in the intervention group received a smart band (Huawei Band 4; Huawei Technologies, Dongguan, China).”
“All analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC).”
“Each participant in the intervention group received a smart band (Huawei Band 4; Huawei Technologies, Dongguan, China).”
“All analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC).”
Tests are named (linear mixed effects, generalized linear mixed effects, Cox frailty). Assumptions are handled by design (mixed models). Exact p-values are reported. Effect sizes with CIs are provided. Software identified. Data presentation includes per-group n and CIs. Mathematical plausibility checks: baseline percentages sum correctly; subgroup counts sum to totals; no arithmetic errors detected.
“Differences between the two groups were tested using linear mixed effects models for continuous variables and generalised linear mixed effects models for categorical variables.”
“with a difference of −1.88% (−2.57% to −1.19%, P<0.001) at 12 months”
“Differences between the two groups were tested using linear mixed effects models for continuous variables and generalised linear mixed effects models for categorical variables.”
“with a difference of −1.88% (−2.57% to −1.19%, P<0.001) at 12 months”
“All analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC).”
The data availability statement says 'The data underlying the study findings are op...' (truncated) and mentions code in supplementary files, but no repository or accession numbers are provided. This is inadequate for a clinical trial.
“The data underlying the study findings are op”
“The supplementary files include the code used to analyse the data in the study.”
“The data underlying the study findings are op”
“The supplementary files include the code used to analyse the data in the study.”
Trial registered (NCT05645640). Reporting guideline not explicitly mentioned but the paper follows CONSORT-like structure. All outcomes reported including null results. Limitations discussed. Conclusions proportional. Funding and COI provided.
“Trial registration ClinicalTrials.gov NCT05645640 .”
“This study has several limitations. Firstly, group assignment was not concealed from the research staff.”
“Trial registration ClinicalTrials.gov NCT05645640 .”
“This study has several limitations. Firstly, group assignment was not concealed from the research staff.”
“Funding: This trial was supported by the National High Level Hospital Clinical Research Funding (2022-GSP-GG-4), Chinese Academy of Medical Sciences Innovation Fund for Medical Science (2024-I2M-ZD-002; 2021-1-I2M-011), and 111 Project from the Ministry of Education of China ( B16005 ).”
Registered (1 ID: ClinicalTrials.gov). No reporting guideline cited.
Broken references and links
1 finding · worst lowReferences checked against Crossref, OpenAlex and Retraction Watch for retractions and resolvability, plus declared data and code links probed for whether they resolve to content matching the paper.
- References not resolvable to a published paperRecomputed
Checked 34 references by DOI: 32 verified — 1 DOI unresolved, 1 no DOI (shown, not verified).
- UNRESOLVED10.3760/cma.j.cn112148-20201009-00796[Chinese guideline on the primary prevention of cardiovascular diseases]Cited DOI does not resolve to any Crossref record.
- NO DOIAnnual Report on Cardiovascular Health and Disease in China (2022)No DOI in the reference — shown for manual review; not independently verifiable (not a fabrication signal).
Copyediting
7 minorWording, consistency and formatting errors that need correcting before submission.
No major wording or formatting errors. 7 minor suggestions below.
7 copyedit issues flagged: mostly typo, consistency, clarity.
- MINORtypoAbstract, Results“−1.88% (95% confidence interval (CI) −2.57% to −1.19%; P<0.001)”→ Add a space before the parenthesis for consistency: '−1.88% (95% CI −2.57% to −1.19%; P<0.001)'Minor formatting inconsistency.
- MINORconsistencyTable 2, footnote“† Lifetime risk of ASCVD could not be calculated using the China-PAR model in one participant owing to age (>85 years).”→ Ensure the footnote marker is correctly placed in the table.Check footnote placement.
- MINORclarityData availability statement“The data underlying the study findings are op”→ Complete the sentence and provide a clear access route.Truncated sentence.
- MINORtypoAbstract, Participants“owned a smart phone”→ owned a smartphoneInconsistent hyphenation of 'smartphone'.
- MINORconsistencyMethods, Intervention group“Huawei Band 4; Huawei Technologies, Dongguan, China”→ Ensure consistent formatting of manufacturer details.Manufacturer details are given in parentheses; elsewhere similar details are formatted differently.
- MINORgrammarMethods, Statistical analysis“The actual intracluster correlation coefficient was 0.06, with a statistical power of 88% achieved.”→ Consider rephrasing to 'The actual intracluster correlation coefficient was 0.06, and the achieved statistical power was 88%.'Awkward phrasing.
- MINORpunctuationResults, Secondary outcomes“decreased by−10.9 mm Hg”→ decreased by −10.9 mm HgMissing space after 'by'.
The published paper is robust overall, but an informed reader should weigh the incomplete data availability statement and the one reference not found in the registry. A correction or erratum to complete the data availability statement and verify the missing reference would strengthen the paper's transparency.
- 1.HIGHdata codeComplete the data availability statement in the Data availability statement section: specify a repository (e.g., a managed-access platform) with a DOI or accession number, or describe a clear data access committee procedure with conditions and timeframe.The current statement is truncated and does not provide a verifiable access route, which is a reporting gap for a clinical trial.
- 2.HIGHdata codeDeposit the analysis code in a public repository (e.g., GitHub, Zenodo) with a persistent identifier and reference it in the data availability statement.Code mentioned only in supplementary files without a persistent identifier reduces reproducibility and transparency.
- 3.HIGHreportingVerify the reference not found in the registry: [Chinese guideline on the primary prevention of cardiovascular diseases] (doi:10.3760/cma.j.cn112148-20201009-00796) — correct the citation or provide a verifiable source.A reference that cannot be located in any registry may be fabricated or contain an error; this is a potential integrity concern.
- 4.MEDIUMreportingExplicitly state adherence to a reporting guideline such as CONSORT in the Methods or a separate section.Although the paper follows CONSORT-like structure, explicitly mentioning the guideline improves transparency and helps readers assess reporting completeness.
- 5.MEDIUMethicsAdd a statement about regulatory compliance (e.g., Declaration of Helsinki) in the Ethics statements section.Regulatory compliance is implied but not explicitly stated, which is a minor gap in ethical reporting.
- 6.MEDIUMreportingInclude a note on how outliers were handled in the Statistical analysis section.Outlier handling is not explicitly described; adding this detail would improve methodological completeness.
- 7.LOWcopyeditIn the Abstract, Results, add a space before the parenthesis: change '−1.88% (95% confidence interval (CI) −2.57% to −1.19%; P<0.001)' to '−1.88% (95% CI −2.57% to −1.19%; P<0.001)'.Minor formatting inconsistency for cleaner presentation.
- 8.LOWcopyeditIn the Abstract, Participants, change 'owned a smart phone' to 'owned a smartphone'.Inconsistent hyphenation of 'smartphone'.
- 9.LOWcopyeditIn the Results, Secondary outcomes, add a space after 'by': change 'decreased by−10.9 mm Hg' to 'decreased by −10.9 mm Hg'.Missing space after 'by'.
- 10.LOWcopyeditIn the Methods, Statistical analysis, rephrase 'The actual intracluster correlation coefficient was 0.06, with a statistical power of 88% achieved.' to 'The actual intracluster correlation coefficient was 0.06, and the achieved statistical power was 88%.'Awkward phrasing.
- 11.LOWcopyeditEnsure consistent formatting of manufacturer details throughout (e.g., in Methods, Intervention group, the smart band details are in parentheses; check other instances).Consistency in formatting improves readability.
- 12.LOWcopyeditIn Table 2, ensure the footnote marker for '† Lifetime risk of ASCVD could not be calculated using the China-PAR model in one participant owing to age (>85 years).' is correctly placed in the table.Check footnote placement for clarity.
The star rating is the report’s one-glance summary. Every paper starts at 5★ and loses stars for the concrete problems the review finds — so a rating is never a vague average, it’s a running total you can read line by line under “How this rating was calculated.”
- Reporting — 8 dimensionseach dimension that fully fails−½★
- each dimension partially met−¼★
- Statistics · Integrity · Claimseach serious problem−1★
- each medium problem−½★
- Citationseach retracted or unverifiable reference−¼★
- Copyeditonly when the manuscript needs a full edit−½★
The rating never drops below 1★, and a demonstrable critical failure (an impossible statistic, a proven ethics violation) caps it at 1★ on its own — so the stars can never look healthy when the verdict is CRITICAL.
The rating draws on a panel of agents. Three independent Kaimen Rigor reviewers grade the eight dimensions below across several independent passes (the shown verdict is their majority vote — steadier than any single run), isolate the paper’s major claims and check its own evidence backs them, and flag integrity concerns. Alongside them, a citation agent resolves every reference against Crossref, OpenAlex, and Retraction Watch; a statistics agent recomputes reported tests; and rule-based checks verify that declared data/code links actually resolve. Full text is required — an abstract-only submission is not analyzed.
Graded against NIH, MDAR, ARRIVE 2.0, CONSORT, EQUATOR, and RRID guidelines. A dimension that doesn’t apply to the study type is skipped, never penalized.
This Kaimen Rigor review is model-assisted and is not a substitute for formal expert review. It complements human evaluation by surfacing potential methodological concerns — verify each finding against the source.