BMC Medical Research Methodology最新文献

{"title":"Grey literature scoping review: a synthesis of the application of participatory methodologies in underrepresented groups at an elevated risk of dementia.","authors":"Katrina Messiha, Nicole Thomas, C Brayne, D M Agnello, L Delfmann, M Giné-Garriga, S Lippke, J Downey","doi":"10.1186/s12874-025-02577-3","DOIUrl":"https://doi.org/10.1186/s12874-025-02577-3","url":null,"abstract":"<p><strong>Background: </strong>Diverse populations are more exposed to life course influences on adverse ageing, including brain ageing. Research into dementia in the United Kingdom inadvertently lacks diversity. Therefore, there is a need for more inclusive dementia research, developed in a way to ensure those who are currently missing from standard health data are represented. This may warrant the use of co-creation (emphasising collaborative creation and solution development), drawing on participatory methodologies in healthcare, research and service delivery.</p><p><strong>Methods: </strong>This study presents a scoping review of grey literature using Arksey and O'Malley's methodology. Literature was sourced from the Patient Experience Library and supplemented by a targeted Google Scholar search, employing snowball sampling to identify additional materials. The search strategy incorporated keywords such as \"marginalised\", \"vulnerable\", \"disadvantaged\" and participatory terms like \"co-creation\" and \"co-design\". Two reviewers independently screened and extracted key higher-level attributes (e.g., type of report, purpose of the activity (design), participating stakeholders/target populations) as well as data related to \"co-creation process dimensions\" and \"participation levels\".</p><p><strong>Results: </strong>Our review identified 30 grey literature reports on participatory methodologies among underrepresented groups living with or at elevated risk of dementia, covering diverse locations within the United Kingdom. The reported activities aimed to enhance healthcare and social services through stakeholder participation. Our findings highlight a focus on multi-stakeholder collaborative action as the dominant co-creation dimension identified. However, there was also a notable absence of more inclusive methodologies, with consultation being the most commonly used approach.</p><p><strong>Conclusions: </strong>Our scoping review highlights the value of grey literature in understanding participatory methodologies for underrepresented populations at risk of or living with dementia. It reveals there is still a potential need to shift from mere consultations to sustained partnerships, promoting meaningful inclusion and greater ownership of (health) outcomes among these populations.</p><p><strong>Ethics and dissemination: </strong>Ethical approval was not required for this grey literature scoping review.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"122"},"PeriodicalIF":3.9,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12048973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143957517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patterns of intra-cluster correlation coefficients in school-based cluster randomised controlled trials of interventions for improving social-emotional functioning outcomes in pupils: a secondary data analysis of five UK-based studies.","authors":"Kitty Parker, Michael Nunns, ZhiMin Xiao, Tamsin Ford, Paul Stallard, Willem Kuyken, Nick Axford, Obioha C Ukoumunne","doi":"10.1186/s12874-025-02574-6","DOIUrl":"https://doi.org/10.1186/s12874-025-02574-6","url":null,"abstract":"<p><strong>Background: </strong>The cluster randomised trial (CRT) design is increasingly used to evaluate the impact of school-based interventions for improving social-emotional functioning outcomes in pupils. Good knowledge is required on plausible values of the intra-cluster correlation coefficient (ICC) of the outcome to calculate the required sample size in such studies. Using data from five school-based CRTs in the UK, we estimate, and describe patterns in, ICCs for social-emotional functioning outcomes.</p><p><strong>Methods: </strong>Mixed effects linear regression models were fitted to estimate the ICC and variance components. Estimates for baseline data were obtained by fitting \"null\" models that had no predictor variables; estimates at follow-up were adjusted for trial arm status.</p><p><strong>Results: </strong>Five hundred and twenty-nine (529) ICCs were estimated. Variation across clusters in the outcomes was present at the school, year group and classroom levels. Overall, the ICCs were not markedly different between the primary and secondary school settings. Most of the school- and classroom-level ICCs were less than 0.04 for pupil-reported outcomes and less than 0.035 for parent-reported outcomes; a notable exception for pupil-reported outcomes was for outcomes that reflect a common experience shared by children, such as school climate, where the ICCs were as large as 0.1. The ICCs for teacher-reported outcomes (up to 0.1 at the school level and 0.2 at the classroom level) were larger than for pupil- and parent-reported outcomes. In the CRT that allocated schools to trial arms and only sampled one classroom from each school, the nominal school-level ICCs for teacher-reported outcomes took values up to 0.25. ICCs for teacher-reported measures of internalising behaviour problems and pro-social behaviour were larger than for externalising behaviour problems.</p><p><strong>Conclusions: </strong>When randomising school clusters, sub-sampling of lower-level clusters such as classrooms should be accounted for in the sample size calculation. Teacher-reported ICCs are likely to be greater than those for pupil- and parent-reported outcomes as teachers will often provide data for many or all pupils in a given school or classroom. Differences across reporter type and across outcomes need to be considered when specifying plausible values of the ICC to calculate sample size.</p><p><strong>Trial registration: </strong>STARS study (ISRCTN84130388); KiVa study (ISRCTN23999021); PACES study (ISRCTN23563048); PROMISE study (ISRCTN19083628); MYRIAD study (ISRCTN86619085).</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"120"},"PeriodicalIF":3.9,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12048950/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143973654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Survey administration and participation: a randomized trial in a panel population health survey.","authors":"M S Grønkjær, P Elsborg, C J Lau, M Bekker-Jeppesen, N Gøtzsche, M H Jacobsen, A H Andreasen, M H Eliasen","doi":"10.1186/s12874-025-02578-2","DOIUrl":"10.1186/s12874-025-02578-2","url":null,"abstract":"<p><strong>Background: </strong>Choice of survey administration features in surveys mapping population health may influence the participation and the generalizability of the results. This randomized study aimed to investigate whether three digital letters (denoted single-mode administration) lead to similar participation as two digital and three physical letters mailed with shorter duration between reminders (denoted sequential mixed-mode administration).</p><p><strong>Methods: </strong>In total, 9,489 individuals who participated in The Danish Capital Region Health Survey in 2017 were randomized to re-invitation in 2021 (≥ 20 years) by either single-mode with three digital letters (N = 4,745) or sequential mixed-mode survey administration with two digital and then three physical letters (N = 4,744). To investigate the influence of survey administration on representativeness, the two groups were compared regarding sociodemographic characteristics of participants (age, sex, country of origin, education, labor market attachment). Generalized linear models were used to estimate absolute and relative differences between the two administration groups in participation rates (overall and the increase after reminders). It was also investigated whether sociodemographic factors moderated the association between administration group and participation.</p><p><strong>Results: </strong>At the end of follow-up, the participation rate was significantly higher in the sequential mixed-mode group, which received five letters (78%), than in the single-mode group, which received three letters (61%), primarily due to a greater increase in participation after switching to physical administration and an increase after the two additional reminders in the mixed-mode group. Overall, individuals who decided to participate in the two groups were comparable in all sociodemographic factors, yet older participants appeared to benefit more from switching to physical administration and younger participants from additional reminders.</p><p><strong>Conclusions: </strong>Depending on the target population, sequential mixed-mode survey administration and/or multiple reminders could be considered to increase participation; however, it does not necessarily improve the sociodemographic representativeness of participants.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"119"},"PeriodicalIF":3.9,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12049040/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143958524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors that affect clinical youth engagement in digital mental health research: a qualitative sub-study nested within a prospective cohort study.","authors":"Amanda Bye, Emma Wilson-Lemoine, Kylee Trevillion, Ben Carter, Rina Dutta","doi":"10.1186/s12874-025-02571-9","DOIUrl":"https://doi.org/10.1186/s12874-025-02571-9","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;There has been extensive debate about the role of social media and smartphone use in youth mental health and self-harm. Research to date lacks sufficient detail to determine the mechanisms underpinning any associations. The Social Media, Smartphone use and Self-harm in Young People (3S-YP) study is a prospective cohort study that was co-produced with young people to investigate temporal patterns of social media and smartphone use prior to an episode of self-harm in a clinical youth sample. Young people were actively involved in all key stages of the research process to ensure the research would be relevant and acceptable to the intended population. This included defining the research question and designing the methods. This qualitative sub-study nested within the main 3S-YP study aimed to evaluate young people's experiences of engaging in this innovative digital mental health study. This will help inform understanding regarding the added value of co-production and future research in this field.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Semi-structured interviews were conducted with a purposive sample of participants from the 3S-YP study. Interview data was analysed using codebook thematic analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Sixteen young people (mean 19.8 years old, SD 2.9; n = 10 female, 63%) participated in the interviews. Participants were generally comfortable answering questions about sensitive topics using remote digital tools, appreciating the greater privacy, convenience and opportunity for self-reflection they provide, whilst noting periods of poor mental health may affect study engagement. The remote research methods (including the participation information and tools for recruitment and data collection) were considered user-friendly and were complemented by the active role of the research team who facilitated young people's engagement with the study. Despite the relevance and support for research on the impact of digital technology use on youth mental health, concerns about data sharing and a complex process for accessing data from social media platforms complicated study engagement. The role of parental involvement was also described.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;User-friendly remote research methods, coupled with proactive, responsive researchers and parental support are beneficial for conducting research with clinical youth populations. Whilst young people endorse research in this field, concerns about data sharing and barriers to data access need addressing if researchers are to effectively employ innovative solutions to investigating the impact of smartphones and social media use on youth mental health and self-harm. The findings from this study demonstrate the value of actively involving those with lived experience throughout the research process and provide useful insight for researchers intending to conduct similar research.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Trial registration: &lt;/strong&gt;This study is registered on","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"118"},"PeriodicalIF":3.9,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12042430/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143983504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Barriers and strategies for recruitment of pregnant women in contemporary longitudinal birth cohort studies.","authors":"Slawa Rokicki, Amulya Gobburu, Melissa Weidner, Nashwah Azam, Michelle Jansen, Zorimar Rivera-Núñez, Adriana De Resende, Veenat Parmar, Gloria Bachmann, Nancy Reilly, Reynold Panettieri, Maria Gloria Dominguez-Bello, Daniel B Horton, Martin J Blaser, Emily S Barrett","doi":"10.1186/s12874-025-02570-w","DOIUrl":"https://doi.org/10.1186/s12874-025-02570-w","url":null,"abstract":"<p><strong>Background: </strong>Pregnancy and birth cohort studies are essential for studying the social and biological determinants of human health, yet racial and ethnic minority populations are underrepresented due to low recruitment and retention rates. Remote data collection has potential to improve recruitment of underrepresented populations. The aims of this descriptive qualitative study were to explore the perspectives of pregnant and postpartum women about the barriers and facilitators to enrolling themselves, their child, and their partner in a longitudinal birth cohort study, identify data collection strategies to address barriers, and generate recommendations for future cohort studies.</p><p><strong>Methods: </strong>Online focus groups and in-person interviews in English and Spanish were conducted between August and November 2022 with pregnant and postpartum women. Participants were recruited from Black and Hispanic serving obstetric clinics and community-based health and social organizations to ensure a racially and ethnically diverse sample. Analysis was conducted using an inductive thematic approach.</p><p><strong>Results: </strong>60 women participated in 10 focus groups and 11 interviews. Five themes emerged: challenges in committing time and resources to a research study; utility of compensation and resources; fears that research procedures would negatively impact child; concerns regarding data privacy and children's consent; and benefits for their family, community, and society. Black participants voiced concern about historical discrimination in science and mistrust of research, but also wanted to increase Black representation in research for future generations. Spanish-speaking participants expressed hesitancy related to fear of child injury and misuse of data. Women felt their partners would be reluctant to participate, but that incentives such as parental education would be motivating. Participants liked the flexibility of remote data collection in easing logistical challenges to participation but also expressed importance of personal study contact for facilitating access to resources, enhancing trust in the research process, and motivating retention. Participants also expressed the importance of transparency in data collection procedures and communication on study progress.</p><p><strong>Conclusions: </strong>Leveraging technological advances in remote data collection may reduce some challenges to recruitment of women and families to birth cohort studies. However, building and maintaining trust among communities with engagement, transparency, and communication is critical for recruitment of underrepresented populations.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"117"},"PeriodicalIF":3.9,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12036123/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143953725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing Large language models to select literature for meta-analysis shows workload reduction while maintaining a similar recall level as manual curation.","authors":"Xiangming Cai, Yuanming Geng, Yiming Du, Bart Westerman, Duolao Wang, Chiyuan Ma, Juan J Garcia Vallejo","doi":"10.1186/s12874-025-02569-3","DOIUrl":"https://doi.org/10.1186/s12874-025-02569-3","url":null,"abstract":"<p><strong>Background: </strong>Large language models (LLMs) like ChatGPT showed great potential in aiding medical research. A heavy workload in filtering records is needed during the research process of evidence-based medicine, especially meta-analysis. However, few studies tried to use LLMs to help screen records in meta-analysis.</p><p><strong>Objective: </strong>In this research, we aimed to explore the possibility of incorporating multiple LLMs to facilitate the screening step based on the title and abstract of records during meta-analysis.</p><p><strong>Methods: </strong>Various LLMs were evaluated, which includes GPT-3.5, GPT-4, Deepseek-R1-Distill, Qwen-2.5, Phi-4, Llama-3.1, Gemma-2 and Claude-2. To assess our strategy, we selected three meta-analyses from the literature, together with a glioma meta-analysis embedded in the study, as additional validation. For the automatic selection of records from curated meta-analyses, a four-step strategy called LARS-GPT was developed, consisting of (1) criteria selection and single-prompt (prompt with one criterion) creation, (2) best combination identification, (3) combined-prompt (prompt with one or more criteria) creation, and (4) request sending and answer summary. Recall, workload reduction, precision, and F1 score were calculated to assess the performance of LARS-GPT.</p><p><strong>Results: </strong>A variable performance was found between different single-prompts, with a mean recall of 0.800. Based on these single-prompts, we were able to find combinations with better performance than the pre-set threshold. Finally, with a best combination of criteria identified, LARS-GPT showed a 40.1% workload reduction on average with a recall greater than 0.9.</p><p><strong>Conclusions: </strong>We show here the groundbreaking finding that automatic selection of literature for meta-analysis is possible with LLMs. We provide it here as a pipeline, LARS-GPT, which showed a great workload reduction while maintaining a pre-set recall.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"116"},"PeriodicalIF":3.9,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12036192/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143977078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dietary misreporting: a comparative study of recalls vs energy expenditure and energy intake by doubly-labeled water in older adults with overweight or obesity.","authors":"Leinys S Santos-Báez, Michele N Ravelli, Diana A Díaz-Rizzolo, Collin J Popp, Dympna Gallagher, Bin Cheng, Dale Schoeller, Blandine Laferrère","doi":"10.1186/s12874-025-02568-4","DOIUrl":"https://doi.org/10.1186/s12874-025-02568-4","url":null,"abstract":"<p><strong>Background: </strong>Self-report methods are widely used to assess energy intake but are prone to measurement errors. We aimed to identify under-reported, over-reported, and plausible self-reported energy intake by dietary recalls (rEI) using a standard method (Method 1) that calculates the rEI ratio against measured energy expenditure (mEE) by doubly-labeled water (DLW), and compare it to a novel method (Method 2), which calculates the rEI ratio against measured energy intake (mEI) by the principle of energy balance (EB = mEE + changes in energy stores).</p><p><strong>Methods: </strong>The rEI:mEE and rEI:mEI ratios were assessed for each subject. Group cut-offs were calculated for both methods, using the coefficient of variations of rEI, mEE, and mEI. Entries within ± 1SD of the cutoffs were categorized as plausible, < 1SD as under-reported, and > 1SD as over-reported. Kappa statistics was calculated to assess the agreement between both methods. Percentage bias (bβ) was estimated by linear regression. Remaining bias (dβ) was calculated after applying each method cutoffs.</p><p><strong>Results: </strong>The percentage of under-reporting was 50% using both methods. Using Method 1, 40.3% of recalls were categorized as plausible, and 10.2% as over-reported. With Method 2, 26.3% and 23.7% recalls were plausible and over-reported, respectively. There was a significant positive relationship between mEI with weight (ß = 21.7, p < 0.01) and BMI (ß = 48.8, p = 0.04), but not between rEI with weight (ß = 13.1, p = 0.06) and BMI (ß = 41.8, p = 0.11). The rEI relationships were significant when only plausible entries were included using Method 1 (weight: ß = 17.4, p < 0.01, remaining bias = 49.5%; BMI: ß = 44.6, p = 0.01, remaining bias = 60.2%) and Method 2 (weight: ß = 19.5, p < 0.01, remaining bias = 24.9%; BMI: ß = 44.8, p = 0.03, remaining bias = 56.9%).</p><p><strong>Conclusions: </strong>The choice of method significantly impacts plausible and over-reported classification, with the novel method identifying more over-reported entries. While rEI showed no relationships with anthropometric measurements, applying both methods reduced bias. The novel method showed greater bias reduction, suggesting that it may have superior performance when identifying plausible rEI.</p><p><strong>Clinical trials registration: </strong>NCT04465721.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"115"},"PeriodicalIF":3.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12034172/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143970359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of rare events in healthcare intervention using department of defense data: intravenous immune globulin therapy for bullous pemphigoid.","authors":"Onur Baser, Huseyin Yuce, Gabriela Samayoa","doi":"10.1186/s12874-025-02559-5","DOIUrl":"https://doi.org/10.1186/s12874-025-02559-5","url":null,"abstract":"<p><strong>Introduction: </strong>Rare events data have proven difficult to explain and predict. Standard statistical procedures can sharply underestimate the probability of rare events, such as intravenous immune globulin therapy (IVIg) for bullous pemphigoid.</p><p><strong>Methods: </strong>This retrospective cross-sectional study used Department of Defense TRICARE data to determine factors associated with IVIg therapy among bullous pemphigoid patients. We used prior and weighted correction methods for logit regression to solve rare event bias.</p><p><strong>Results: </strong>We identified 2,720 individuals diagnosed with bullous pemphigoid from 2019 to 2022, of which 14 were treated with IVIg. Patients who received IVIg therapy were younger (65.07 vs. 75.85, P =.0016) and more likely to be female (13 vs. 1, P =.0036). The underestimation with the standard regression model for event probabilities ranged from 11% to 102% using the prior correction method and from 15% to 107% using the weighted correction method.</p><p><strong>Conclusion: </strong>Rare events are low-frequency, high-severity problems that can have significant consequences. Rare diseases and rare therapies are individually unique but collectively contribute to substantial health and social needs. Therefore, correct estimation of the events is the first step toward assessing the burden of rare diseases and the pricing of their therapies.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"114"},"PeriodicalIF":3.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12034191/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143969327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equality, equity, diversity, and inclusion principles: how should we apply these to statistical methodology research?","authors":"Ellesha Smith, Carol Akroyd, Rebecca Barnes, Emma Beeston, Jonathan Broomfield, Sylwia Bujkiewicz, Natalie Darko, Christopher Newby, Mark J Rutherford, Aiden Smith, Rachael Stannard, Freya Tyrer, Laura J Gray","doi":"10.1186/s12874-025-02564-8","DOIUrl":"https://doi.org/10.1186/s12874-025-02564-8","url":null,"abstract":"<p><strong>Background: </strong>The aim of equality, equity, diversity, and inclusion (EDI) is to ensure fair treatment, equal opportunities, equitable outcomes, and representation. The NIHR Research Design Service (RDS) EDI toolkit ( https://www.rssleicesterresources.org.uk/edi-toolkit ) helps researchers embed EDI throughout their work. This study evaluated the applicability of the RDS EDI toolkit for statistical methodology research and proposed adaptations to enable statistical methodologists to embed EDI in their research.</p><p><strong>Methods: </strong>A full-day meeting was held to consider how the RDS EDI toolkit could inform the inclusion of EDI principles in statistical methodology research. Twelve individuals attended from the University of Leicester and the NIHR Research Support Service (RSS) Hub delivered by the University of Leicester and Partners. At the meeting, definitions of statistical methodology research and EDI were agreed. The RDS EDI Toolkit was interrogated to identify relevant aspects and additional considerations for statistical methodology research.</p><p><strong>Results: </strong>Overall, the RDS EDI toolkit was valuable for incorporating EDI in statistical methodology research. Five recommendations to supplement the toolkit are proposed to reflect specific EDI challenges for statistical methodology research. Statistical methodology researchers should: 1. Perform formal assessments of the required resources for maximising EDI from the outset of statistical methodology research projects, including consideration of research team, training, patient and public involvement, and appropriate budgeting. 2. Conduct prospective and retrospective context-specific evaluations of the impact of their methodological research on exacerbating or reducing inequalities. 3. Evaluate the selection of data sets, work with multiple, diverse databases, or use data sets that have undergone equality impact assessments. 4. Clearly communicate EDI assessments and limitations, including which data sets are used and their purpose, such as illustrating or comparing methods, informing simulations, or guiding clinical practice. 5. Incorporate EDI in dissemination activities and advocate for EDI principles in the peer review process.</p><p><strong>Conclusions: </strong>Embedding EDI principles throughout statistical methodology research will improve its relevance and quality, better serve the public, and build public trust. It is essential that statistical methodologists strive towards equity in all aspects of their work. This paper demonstrates the value of the NIHR RDS EDI toolkit for statistical methodology research and encourages methodologists to adopt the recommendations in this paper. Further extensions to this work are needed to seek the wider views and experiences of statistical methodologists and public contributors from diverse and under-represented groups.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"113"},"PeriodicalIF":3.9,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12023504/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143978942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing and adjusting for bias in ecological analysis using multiple sample datasets.","authors":"Qingfeng Li","doi":"10.1186/s12874-025-02552-y","DOIUrl":"https://doi.org/10.1186/s12874-025-02552-y","url":null,"abstract":"<p><strong>Background: </strong>Ecological analysis utilizes group-level aggregate measures to investigate the complex relationships between individuals or groups and their environment. Despite its extensive applications across various disciplines, this approach remains susceptible to several biases, including ecological fallacy.</p><p><strong>Methods: </strong>Our study identified another significant source of bias in ecological analysis when using multiple sample datasets, a common practice in fields such as public health and medical research. We show this bias is proportional to the sampling fraction used during data collection. We propose two adjustment methods to address this bias: one that directly accounts for the sampling fraction and another based on measurement error models. The effectiveness of these adjustments is evaluated through formal mathematical derivations, simulations, and empirical analysis using data from the 2014 Kenya Demographic and Health Survey.</p><p><strong>Results: </strong>Our findings reveal that the sampling fraction bias can lead to significant underestimation of true relationships when using aggregate measures from multiple sample datasets. Both adjustment methods effectively mitigate this bias, with the measurement-error-adjusted estimator showing particular robustness in real-world applications. The results highlight the importance of accounting for sampling fraction bias in ecological analyses to ensure accurate inference.</p><p><strong>Conclusion: </strong>Beyond the ecological fallacy uncovered by Robinson's seminar work, our research identified another critical bias in ecological analysis that is likely just as prevalent and consequential. The proposed adjustment methods provide potential tools for researchers to adjust for this bias, thereby improving the validity of ecological inferences. This study underscores the need for caution when pooling aggregate measures from multiple sample datasets and offers potential solutions to enhance the reliability of ecological analyses in various research domains.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"112"},"PeriodicalIF":3.9,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12023363/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143958492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}