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PubMed2026

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans↗

PubMed2026

Strategies to improve recruitment to randomised trials.

BACKGROUND: Recruiting participants to randomised controlled trials (RCTs) is challenging. Identifying effective recruitment strategies would benefit health research: poor recruitment leads to underpowered trials, reducing the reliability of findings and increasing the risk of wasted resources, ethical concerns, and trial failure. Evidence to inform recruitment strategies is increasingly generated through Studies Within A Trial (SWATs), which are methodological studies embedded within host RCTs. This is an update of a review last published in 2018. OBJECTIVES: Primary: to quantify the effects of strategies to improve recruitment of participants to RCTs. Secondary: to evaluate recruitment strategies' cost-effectiveness and impact on retention, and the equity, diversity, and inclusion (EDI) characteristics of recruited participants. SEARCH METHODS: We used MEDLINE, Embase, and six other databases to identify the studies included in the review. We also sought unpublished recruitment SWATs through social media and targeted email dissemination to trial methodology networks. The latest search date was 16 February 2023. SELECTION CRITERIA: We included randomised SWATs evaluating trial recruitment strategies embedded in healthcare and non-healthcare trials. We excluded quasi-randomised, hypothetical, questionnaire-only, retention-only, or clinician incentive studies. DATA COLLECTION AND ANALYSIS: Primary outcome: proportion of eligible participants or centres recruited. SECONDARY OUTCOMES: cost-effectiveness, retention rates, and EDI characteristics of included participants. We conducted random-effects meta-analysis for strategies evaluated in at least two studies; otherwise, we synthesised results narratively. We reported effects as risk differences (RDs) with 95% confidence intervals (CIs), and assessed between-trial heterogeneity. We used GRADE to assess the certainty of evidence for the primary outcome. We expressed cost-effectiveness as the incremental cost per additional participant recruited in pounds sterling (GBP). MAIN RESULTS: We identified 91 eligible studies (53 new to this update), providing 94 comparisons and involving at least 176,747 participants. Eighty-one studies involved strategies aimed at trial participants, while 10 evaluated strategies aimed at recruiters. All were healthcare studies. We found 65 recruitment strategies; 49 were evaluated in a single study. Only five strategies were supported by high-certainty evidence according to GRADE criteria, and we focus on these strategies in the summary below. Open-label trials versus blinded, placebo trials. Open-label trials recruited more participants than blinded trials (RD 10%, 95% CI 8% to 12%; 3 studies, 9004 participants), corresponding to approximately 10 additional participants per 100 approached. The studies involved mostly women in the UK and Estonia. No cost or retention data were reported. Telephone reminder versus no telephone reminder. Telephone reminders to people who did not respond to an initial postal invitation boosted recruitment by 6% (95% CI 3% to 9%; 2 studies, 1450 participants), in trials with low underlying recruitment (we are less certain for trials with over 10% recruitment). The studies involved people with a mean age of 58 years in Canada and Norway. No cost or retention data were reported. Recruitment primer letter versus no letter. Pre-recruitment letters and leaflets designed to encourage participation made little or no difference to recruitment (absolute improvement 1%, 95% CI -1% to 2%; 2 studies, 5376 participants), and were associated with increased costs compared to not sending a primer (incremental cost: GBP 2.08). The studies involved mostly older white people in the UK and Ireland. Multimedia information via a digital link/QR code plus paper participant information leaflet (PIL) versus paper PIL alone. This made little or no difference to recruitment (absolute improvement 0%, 95% CI -1% to 1%; 7 studies, 11,612 participants) and retention (absolute improvement 0%, 95% CI -2% to 3%; 5 studies, 7403 participants), and increased costs compared to not including multimedia information (incremental cost: GBP 0.78). The studies involved people in the UK. Optimised, user-tested PIL versus standard PIL. Optimising participant information leaflets (e.g. through user-testing the leaflet with the target population to shape its content, format, and appearance) made little or no difference to recruitment: absolute improvement was 0% (95% CI 0% to 1%; 6 studies, 27,805 participants). The studies involved people in the UK. Only one study reported EDI data; participants were mostly older women. No cost or retention data were reported. We had moderate-certainty evidence for 13 other strategies; confidence was often reduced because the results came from single studies. Seven strategies involved changes to how potential participants received information; four involved changes to trial conduct; one targeted the recruiter or recruitment site; and one tested non-monetary incentives. We had much less confidence in the other 47 comparisons because the studies had design flaws, were single studies, or had very uncertain results. Costs were reported in only 17 of 91 studies. Strategy impact on retention was reported in 15 studies. All but one study (99%) were from high-income countries. The most reported demographics were age (49 studies), sex (32 studies), gender (27 studies), and education level (16 studies). AUTHORS' CONCLUSIONS: The evidence on strategies to improve trial recruitment remains broad but lacks depth. Of 65 strategies evaluated, only five were supported by high-certainty evidence. Open-label trial designs and telephone reminders to non-responders increased recruitment, while optimised participant information leaflets, recruitment primer letters, and multimedia information provided alongside a paper participant information leaflet had little or no effect. Reporting of participant characteristics was poor, limiting assessment of equity, diversity, and inclusion across most studies. Evidence is heavily skewed toward high-income countries. Future research must prioritise evaluations in low-to-middle-income settings and consistently report cost, retention, and EDI outcomes. We strongly urge the methodology research community to strengthen the evidence base by prioritising replications of existing strategies over the development and testing of new ones. FUNDING: National Institute for Health and Care Research (Advanced Fellowship, Adwoa Parker, reference:NIHR302256). Health Research Board, Republic of Ireland, Evidence Synthesis Ireland (grant ESI-2021-001) REGISTRATION: This review updates an earlier Cochrane review, which was first published in 2002 and subsequently updated in 2007, 2010, and 2018. Previous versions of the review and their protocols are available at: https://doi.org/10.1002/14651858.MR000013.pub2 https://doi.org/10.1002/14651858.MR000013.pub3 https://doi.org/10.1002/14651858.MR000013.pub4 https://doi.org/10.1002/14651858.MR000013.pub5 https://doi.org/10.1002/14651858.MR000013.pub6.

Randomized Controlled Trials as Topic↗

PubMed2026

Cardiorespiratory training for people with stroke.

RATIONALE: Low levels of cardiorespiratory fitness are common after stroke and are associated with post-stroke disability and increased risk of secondary stroke. Cardiorespiratory training interventions aim to increase cardiorespiratory fitness, improve physical function, reduce disability, and help prevent future strokes. Clinical guidelines recommend exercise as part of lifestyle modification for secondary prevention, and strongly recommend exercise for rehabilitation. This review is one of three reviews that were originally a single review on physical fitness training for stroke. OBJECTIVES: The primary objective of this review was to determine whether cardiorespiratory training after stroke has an effect on death, disability, adverse events, risk factors, fitness, walking, and indices of physical function when compared to a non-exercise control. SEARCH METHODS: In April 2025, we searched nine bibliographic databases and two trials registers to identify studies for inclusion in the review. We checked reference lists, tracked citations, and contacted experts. ELIGIBILITY CRITERIA: We included randomised controlled trials comparing cardiorespiratory training interventions with usual care, no intervention, or a non-exercise intervention in people with stroke. OUTCOMES: Our critical outcomes were death, disability, adverse events, risk factors, fitness, walking, and indices of physical function, assessed at the end of the intervention and the end of the longest follow-up. RISK OF BIAS: We used the Cochrane RoB 1 tool to assess the risk of bias in the included studies. SYNTHESIS METHODS: The studies evaluated different comparisons (e.g. cardiorespiratory training versus no intervention/waiting list control or versus attention control or versus usual care), which we synthesised into a single comparison: cardiorespiratory training versus control. We used random-effects meta-analysis on arm-level data (risk difference (RD) for dichotomous data, and mean difference (MD) or standardised mean difference (SMD) for continuous data, with 95% confidence intervals (CIs)). For outcome data that we did not meta-analyse, we followed Synthesis Without Meta-analysis (SWiM) guidance. We used GRADE to assess the certainty of the evidence for critical outcomes. INCLUDED STUDIES: We included 53 studies (2672 participants, with an average age of 61.9 years). Most studies recruited ambulatory participants in the early subacute (7 days to 3 months) or chronic (> 6 months) phases of recovery. Exercise duration recommendations were met in 49 studies, and frequency recommendations in 48. Twenty-eight studies lacked balanced exposure between groups. Programme duration was 12 weeks or more in 16 studies (maximum: 24 weeks). Sixteen studies had a post-intervention follow-up period (12 weeks to 12 months from baseline). One study planned a six-month follow-up but did not report it. SYNTHESIS OF RESULTS: Cardiorespiratory training does not increase or decrease deaths at the end of intervention (RD 0.00, 95% CI -0.01 to 0.01; 36 studies, 1563 participants; high-certainty evidence) or the end of follow-up (RD -0.00, 95% CI -0.02 to 0.02; 10 studies, 713 participants; high-certainty evidence). Cardiorespiratory training may improve indices of disability slightly at the end of intervention (SMD 0.35, 95% CI 0.12 to 0.57; 17 studies, 1073 participants; very low-certainty evidence), but the evidence is very uncertain. Re-expressed using the Barthel Index (0 to 20), the equivalent effect is MD 1.68, 95% CI 0.59 to 2.74. It is unclear if the effect is clinically meaningful (the minimal clinically important difference (MCID) is +1.85). The effect is unclear at the end of follow-up (SMD -0.14, 95% CI -0.36 to 0.08; 5 studies, 347 participants; low-certainty evidence). Cardiorespiratory training does not increase or decrease the incidence of secondary cardiovascular or cerebrovascular events at the end of intervention (RD -0.00, 95% CI -0.03 to 0.02; 8 studies, 544 participants; high-certainty evidence) and probably does not affect them at the end of follow-up (RD -0.02, 95% CI -0.08 to 0.04; 4 studies, 412 participants; moderate-certainty evidence). It is very uncertain whether cardiorespiratory training affects systolic blood pressure (mmHg) at the end of intervention (MD -2.12, 95% CI -5.81 to 1.57; 9 studies, 535 participants; very low-certainty evidence) (MCID -2 mmHg) or follow-up (MD 0.93, 95% CI -4.30 to 6.16; 3 studies, 155 participants; very low-certainty evidence); the 95% CIs include the MCID. Cardiorespiratory training probably results in a slight improvement in cardiorespiratory fitness (VO2 ml/kg/min) at the end of intervention (MD 2.37, 95% CI 1.39 to 3.36; 13 studies, 608 participants; moderate-certainty evidence); it is unclear if the effect is clinically meaningful (MCID +3.5 ml/kg/min). The effect may be similar at the end of follow-up (MD 2.76, 95% CI 1.36 to 4.16; 5 studies, 237 participants; low-certainty evidence). Subgroup analysis favoured longer interventions. Cardiorespiratory training probably results in a slight increase in comfortable walking speed (metres per second) at the end of intervention (MD 0.08, 95% CI 0.04 to 0.12; 16 studies, 647 participants; moderate-certainty evidence), but the effect is not clinically meaningful (MCID +0.13). The effect is unclear at the end of follow-up (MD 0.02, 95% CI -0.05 to 0.10; 3 studies, 182 participants; low-certainty evidence). Cardiorespiratory training may improve indices of balance at the end of intervention (SMD 0.31, 95% CI 0.15 to 0.47; 18 studies, 772 participants; very low-certainty evidence), but the evidence is very uncertain. Re-expressing using the Berg Balance Scale, the equivalent effect is MD 2.09, 95% CI 1.10 to 3.07; and it is unclear if it is clinically meaningful (MCID of +2). The effect is unclear at the end of follow-up (MD 0.90, 95% CI -1.32 to 3.12; 6 studies, 253 participants; low-certainty evidence). Overall, our certainty about the evidence is limited for most outcomes by imprecision (small number of studies and participants) or risks of bias (e.g. imbalanced exposure doses) or both. AUTHORS' CONCLUSIONS: Cardiorespiratory training after stroke does not affect mortality or the incidence of secondary events at the end of the aerobic exercise training programme or end of follow-up. It may increase fitness, reduce disability, increase walking speed, and improve balance at the end of intervention, but it is unclear if these improvements are clinically meaningful. Further well-designed randomised trials are needed to fully understand the potential benefits and long-term effects of cardiorespiratory training and the optimal exercise prescription. FUNDING: No dedicated funding REGISTRATION: Protocol (and previous versions) available via DOI 10.1002/14651858.CD003316.

Humans↗