Multivariate Random Effects Models Research Articles

Birge ratio method for modeling dark uncertainty in multivariate meta-analyses and inter-laboratory studies

In the paper, we introduce a new approach for combining multivariate measurements obtained in individual studies. The procedure extends the Birge ratio method, a commonly used approach in physics in the univariate case, such as for the determination of physical constants, to multivariate observations. Statistical inference procedures are derived for the parameters of the multivariate location-scale model, which is related to the multivariate Birge ratio method. The new approach provides an alternative to the methods based on the application of the multivariate random effects model, which is commonly used for multivariate meta-analyses and inter-laboratory comparisons. In two empirical illustrations, we show that the introduced multivariate Birge ratio approach yields confidence intervals for the elements of the overall mean vector that are considerably narrower than those obtained by the methods derived under the multivariate random effects model.

Are social protection and food security accelerators for adolescents to achieve the Global AIDS targets?

Without effective, scalable interventions, we will fail to achieve the Global AIDS Targets of zero AIDS-related deaths, zero HIV transmission and zero discrimination. This study examines associations of social protection and food security among adolescents living with HIV (ALHIV), with three Global AIDS Targets aligned outcomes: antiretroviral treatment (ART) adherence and viral suppression, HIV transmission risk behaviour and enacted stigma. We conducted three study visits over 2014-2018 with 1046 ALHIV in South Africa's Eastern Cape province. Standardized surveys provided information on receipt of government-provided cash transfers and past-week food security, alongside self-reported ART adherence, sexual debut and condom use, and enacted HIV-related stigma. Viral load (VL) data was obtained through data extraction from patient files and linkage with National Health Laboratory Service test results (2014-2020). We used a multivariable random-effects regression model to estimate associations between receiving government cash transfers and food security and three outcomes: ART adherence and viral suppression, delayed sexual debut or consistent condom use and no enacted stigma. We tested moderation by sex and age and fitted disaggregated models for each outcome. Among the 933 ALHIV completing all three study visits, 55% were female, and the mean age was 13.6 years at baseline. Household receipt of a government cash transfer was associated with improvements on all outcomes: ART adherence and viral suppression (aOR 2.03, 95% CI 1.29-3.19), delayed sexual debut or consistent condom use (aOR 1.62, 95% CI 1.16-2.27) and no enacted stigma(aOR 2.33, 95% CI 1.39-3.89). Food security was associated with improvements on all outcomes: ART adherence and viral suppression (aOR 1.73, 95% CI 1.30-2.30), delayed sexual debut or consistent condom use (aOR 1.30, 95% CI 1.03-1.64) and no enacted stigma (aOR 1.91, 95% CI 1.32-2.76). Receiving both cash transfers and food security increased the probability of ART adherence and VL suppression from 36% to 60%; delayed sexual debut or consistent condom use from 67% to 81%; and no enacted stigma from 84% to 96%. Government-provided cash transfers and food security, individually and in combination, are associated with improved outcomes for ALHIV aligned with Global AIDS Targets. They may be important, and underutilized, accelerators for achieving these targets.

Individual participant data meta-analysis to examine linear or non-linear treatment-covariate interactions at multiple time-points for a continuous outcome.

Individual participant data (IPD) meta-analysis projects obtain, harmonise, and synthesise original data from multiple studies. Many IPD meta-analyses of randomised trials are initiated to identify treatment effect modifiers at the individual level, thus requiring statistical modelling of interactions between treatment effect and participant-level covariates. Using a two-stage approach, the interaction is estimated in each trial separately and combined in a meta-analysis. In practice, two complications often arise with continuous outcomes: examining non-linear relationships for continuous covariates and dealing with multiple time-points. We propose a two-stage multivariate IPD meta-analysis approach that summarises non-linear treatment-covariate interaction functions at multiple time-points for continuous outcomes. A set-up phase is required to identify a small set of time-points; relevant knot positions for a spline function, at identical locations in each trial; and a common reference group for each covariate. Crucially, the multivariate approach can include participants or trials with missing outcomes at some time-points. In the first stage, restricted cubic spline functions are fitted and their interaction with each discrete time-point is estimated in each trial separately. In the second stage, the parameter estimates defining these multiple interaction functions are jointly synthesised in a multivariate random-effects meta-analysis model accounting for within-trial and across-trial correlation. These meta-analysis estimates define the summary non-linear interactions at each time-point, which can be displayed graphically alongside confidence intervals. The approach is illustrated using an IPD meta-analysis examining effect modifiers for exercise interventions in osteoarthritis, which shows evidence of non-linear relationships and small gains in precision by analysing all time-points jointly.

Objective Bayesian Meta-Analysis Based on Generalized Marginal Multivariate Random Effects Model

Objective Bayesian inference procedures are derived for the parameters of the multivariate random effects model generalized to elliptically contoured distributions. The posterior for the overall mean vector and the between-study covariance matrix is deduced by assigning two noninformative priors to the model parameter, namely the Berger and Bernardo reference prior and the Jeffreys prior, whose analytical expressions are obtained under weak distributional assumptions. It is shown that the only condition needed for the posterior to be proper is that the sample size is larger than the dimension of the data-generating model, independently of the class of elliptically contoured distributions used in the definition of the generalized multivariate random effects model. The theoretical findings of the paper are applied to real data consisting of ten studies about the effectiveness of hypertension treatment for reducing blood pressure where the treatment effects on both the systolic blood pressure and diastolic blood pressure are investigated.

Gibbs sampler approach for objective Bayesian inference in elliptical multivariate meta-analysis random effects model

Bayesian inference procedures for the parameters of the multivariate random effects model are derived under the assumption of an elliptically contoured distribution when the Berger and Bernardo reference and the Jeffreys priors are assigned to the model parameters. A new numerical algorithm for drawing samples from the posterior distribution is developed, which is based on the hybrid Gibbs sampler. The new approach is compared to the two Metropolis-Hastings algorithms previously derived in the literature via an extensive simulation study. The findings are applied to a Bayesian multivariate meta-analysis, conducted using the results of ten studies on the effectiveness of a treatment for hypertension. The analysis investigates the treatment effects on systolic and diastolic blood pressure. The second empirical illustration deals with measurement data from the CCAUV.V-K1 key comparison, aiming to compare measurement results of sinusoidal linear accelerometers at four frequencies.

Obstetric Interventions Among Native and Migrant Women: The (Over)use of Episiotomy in Portugal.

Objective: Episiotomy, defined as the incision of the perineum to enlarge the vaginal opening during childbirth, is one of the most commonly performed surgical interventions in the world. We aimed to determine if migrant status is associated with episiotomy, and if individual characteristics mediate this association. Methods: We analyzed data from the Bambino study, a national, prospective cohort of migrant and native women giving birth at a public hospital in mainland Portugal between 2017 and 2019. We included all women with vaginal delivery. The association between migrant status and episiotomy was assessed using multivariable multilevel random-effect logistic regression models. We used path analysis to quantify the direct, indirect and total effects of migrant status on episiotomy. Results: Among 3,583 women with spontaneous delivery, migrant parturients had decreased odds of episiotomy, especially those born in Africa, compared to native Portuguese women. Conversely, with instrumental delivery, migrant women had higher odds of episiotomy. Disparities in episiotomy were largely explained by maternity units' factors, and little by maternal and fetal characteristics. Conclusion: Our results suggest non-medically justified differential episiotomy use during childbirth and highlight the importance of developing evidence-based recommendations for episiotomy use in a country with a high frequency of medical interventions during delivery.

Equivalencies Between Ad Hoc Strategies and Multivariate Models for Meta-Analysis of Dependent Effect Sizes

Meta-analyses of educational research findings frequently involve statistically dependent effect size estimates. Meta-analysts have often addressed dependence issues using ad hoc approaches that involve modifying the data to conform to the assumptions of models for independent effect size estimates, such as by aggregating estimates to obtain one summary estimate per study, conducting separate analyses of distinct subgroups of estimates, or combinations thereof. We show that these ad hoc approaches correspond exactly to certain multivariate models for dependent effect sizes. Specifically, we describe classes of multivariate random effects models that have likelihoods equivalent to those of models for effect sizes that have been averaged by study, classified into subgroups, or both. The equivalencies also apply to robust variance estimation methods.

Multistep estimators of the between-study covariance matrix under the multivariate random-effects model for meta-analysis.

A wide variety of methods are available to estimate the between-study variance under the univariate random-effects model for meta-analysis. Some, but not all, of these estimators have been extended so that they can be used in the multivariate setting. We begin by extending the univariate generalised method of moments, which immediately provides a wider class of multivariate methods than was previously available. However, our main proposal is to use this new type of estimator to derive multivariate multistep estimators of the between-study covariance matrix. We then use the connection between the univariate multistep and Paule-Mandel estimators to motivate taking the limit, where the number of steps tends toward infinity. We illustrate our methodology using two contrasting examples and investigate its properties in a simulation study. We conclude that the proposed methodology is a fully viable alternative to existing estimation methods, is well suited to sensitivity analyses that explore the use of alternative estimators, and should be used instead of the existing DerSimonian and Laird-type moments based estimator in application areas where data are expected to be heterogeneous. However, multistep estimators do not seem to outperform the existing estimators when the data are more homogeneous. Advantages of the new multivariate multistep estimator include its semi-parametric nature and that it is computationally feasible in high dimensions. Our proposed estimation methods are also applicable for multivariate random-effects meta-regression, where study-level covariates are included in the model.

Chemotherapy-Related Amenorrhea and Quality of Life Among Premenopausal Women With Breast Cancer

Younger survivors of breast cancer frequently report more treatment-related symptoms, mostly related to the menopausal transition. To assess factors associated with chemotherapy-related amenorrhea (CRA) and to evaluate its association with long-term quality of life (QOL). The prospective, longitudinal Cancer Toxicities Study, a multicenter French cohort study, includes women with a diagnosis of stage I to III breast cancer and collects data approximately yearly after diagnosis. The current study reports outcomes up to 4 years after diagnosis for participants enrolled from 2012 to 2017. Participants included premenopausal women younger than 50 years treated with chemotherapy and not receiving adjuvant ovarian function suppression. Data analysis was performed from September 2021 to June 2023. Clinical, socioeconomic, tumor, and treatment characteristics assessed at diagnosis (for the analysis of factors associated with CRA) and persistent CRA (for the QOL analysis). The main outcome of interest was CRA at year 1 (Y1), year 2 (Y2), and year 4 (Y4) after diagnosis. Generalized estimating equations assessed associations of exposure variables with CRA. In the QOL analysis, QOL at Y4 (assessed with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaires C30 and BR23) was the outcome of interest. Multivariable random-effect mixed models assessed the association of persistent CRA (ie, never recovering menses after treatment) with QOL. Among 1636 women, the mean (SD) age at diagnosis was 42.2 (5.6) years. Overall, 1242 of 1497 women (83.0%) reported CRA at Y1, 959 of 1323 women (72.5%) reported it at Y2, and 599 of 906 women (66.1%) reported it at Y4. Older age vs 18 to 34 years (adjusted odds ratio [OR] for 35 to 39 years, 1.84 [95% CI, 1.32 to 2.56]; adjusted OR for 40 to 44 years, 5.90 [95% CI, 4.23 to 8.24]; and adjusted OR for ≥45 years, 21.29 [95% CI, 14.34 to 31.61]) and receipt of adjuvant tamoxifen (adjusted OR, 1.97 [95% CI, 1.53 to 2.53]) were associated with higher likelihood of CRA. In the QOL analysis, 416 of 729 women (57.1%) had persistent CRA. However, late menses recovery among women aged 18 to 34 years with no menses at Y2 were reported by 11 of 21 women (52.4%) between Y2 and Y4. Persistent CRA was associated with worse insomnia (mean difference vs recovery at any time, 9.9 points [95% CI, 3.2 to 16.5 points]; P = .004), systemic therapy-related adverse effects (mean difference, 3.0 points [95% CI, 0.2 to 5.8 points]; P = .04), and sexual functioning (mean difference, -9.2 points [95% CI, -14.3 to -4.1 points]; P < .001) at Y4. In this cohort study of premenopausal women with breast cancer, persistent CRA was common, although some women recovered menses late, and was associated with worse long-term QOL. This study can help inform risk communication, personalized counseling, and early supportive care referrals for such patients.

The Relationship Between Alcohol Consumption, BMI, and Type 2 Diabetes: A Systematic Review and Dose-Response Meta-analysis.

Moderate alcohol use may be associated with lower risk of type 2 diabetes mellitus (T2DM). Previous reviews have reached mixed conclusions. To quantify the dose-response relationship between alcohol consumption and T2DM, accounting for differential effects by sex and BMI. Medline, Embase, Web of Science, and one secondary data source. Cohort studies on the relationship between alcohol use and T2DM. Fifty-five studies, and one secondary data source, were included with a combined sample size of 1,363,355 men and 1,290,628 women, with 89,983 and 57,974 individuals, respectively, diagnosed with T2DM. Multivariate dose-response meta-analytic random-effect models were used. For women, a J-shaped relationship was found with a maximum risk reduction of 31% (relative risk [RR] 0.69, 95% CI 0.64-0.74) at an intake of 16 g of pure alcohol per day compared with lifetime abstainers. The protective association ceased above 49 g per day (RR 0.82, 95% CI 0.68-0.99). For men, no statistically significant relationship was identified. When results were stratified by BMI, the protective association was only found in overweight and obese women. Our analysis relied on aggregate data. We included some articles that determined exposure and cases via self-report, and the studies did not account for temporal variations in alcohol use. The observed reduced risk seems to be specific to women in general and women with a BMI ≥25 kg/m2. Our findings allow for a more precise prediction of the sex-specific relationship between T2DM and alcohol use, as our results differ from those of previous studies.

Bayesian estimation in multivariate inter-laboratory studies with unknown covariance matrices

In the paper we present Bayesian inference procedures for the parameters of multivariate random effects model, which is used as a quantitative tool for performing multivariate key comparisons and multivariate inter-laboratory studies. The developed new approach does not require that the reported covariance matrices of participating laboratories are known and, as such, it can be used when they are estimated from the measurement results. The Bayesian inference procedures are based on samples generated from the derived posterior distribution when the Berger and Bernardo reference prior and the Jeffreys prior are assigned to the model parameter. Three numerical algorithms for the construction of Markov chains are provided and implemented in the CCAUV.V-K1 key comparisons. All three approaches yield similar Bayesian estimators with wider credible intervals when the Berger and Bernardo reference prior is used. Also, the Bayesian estimators for the elements of the inter-laboratory covariance matrix are larger under this prior than for the Jeffreys prior. Finally, the constructed joint credible sets for the components of the overall mean vector indicate the presence of linear dependence between them which cannot be captured when only univariate key comparisons are performed.

Association between the use of Sci-Hub and consultation of scientific journals by medical students from six Latin American countries: A secondary analysis

Introduction and objectiveSci-Hub is a website that allows users to download full-text versions of millions of scientific articles for free. The objective of this study was to evaluate the association between the use of Sci-Hub and consultation of scientific journals by medical students from six Latin American countries. MethodsWe conducted a secondary analysis of data from a 2017 cross-sectional study of medical students from six Latin American countries (Argentina, Bolivia, Chile, Colombia, Paraguay, and Peru). Consultation of scientific journals was considered as the dependent variable, while the independent variable was the use of Sci-Hub. Responses were categorized as: “do not know”; “did not use it”; “used it at least once a week”; “used it more than once a week”; and “used it every day of the month”. In simple and multiple regression analyses, multivariate random-effects models were used to estimate prevalence ratios (PR), with 95% confident intervals (CI). ResultsOf the 6632 participants, 38.2% consulted scientific journals and 10.3% used Sci-Hub once a week. Using Sci-Hub at least once a week was associated with a 20% increase in the prevalence of consulting scientific journals (PR: 1.20, 95% CI: 1.10–1.31, p < 0.001). The variables positively associated with Sci-Hub use included being in the sixth year of medical school (PR: 2.34), affiliation to more than one academic research group (PR: 1.81), being a medical student in Colombia (PR: 1.63), intermediate (PR: 1.16) and advanced levels of English (PR: 1.23), and daily use of PubMed (PR: 1.66), SciELO (PR: 1.87), and/or SCOPUS (PR: 1.58). ConclusionAmongst medical students surveyed from the above six Latin American countries, the use of Sci-Hub at least once a week was significantly associated with the self-reported prevalence of consulting scientific journals.

Food Insecurity and Intimate Partner Violence in Mwanza, Tanzania: A Longitudinal Analysis

Food insecurity is a potential predictor of intimate partner violence. This study (1) describes the prevalence of food insecurity and various forms of intimate partner violence experience among women in Mwanza, Tanzania; and (2) assesses the effect of food insecurity and hunger on various forms of women's experience of intimate partner violence longitudinally. Women (aged 18-70 years) who reported being in a relationship in the past 12 months, who had participated in the control arms of two randomized controlled trials conducted as part of the MAISHA study were interviewed at four time points (N=1,004 at baseline in 2017). Analyses were conducted in 2022. Associations between food insecurity exposures and intimate partner violence outcomes were assessed, and univariate random effect logistic models were conducted to identify relevant sociodemographic variables (including age, education level, and SES) that were statistically significant. Multivariable random effects logistic models were conducted, including time as a fixed effect, to calculate odds ratios indicating associations between food insecurity exposures and intimate partner violence outcomes. Prevalence of food insecurity was 47.7%, 55.6%, 47.2%, and 50.8% for each of the 4 waves, respectively, with significant difference in proportion of food insecurity between baseline and Wave 2. Multivariable random effects models indicated that food insecurity was associated with increased odds of exposure to all forms of intimate partner violence outcomes, and hunger was significantly associated with increased odds of experience of all intimate partner violence outcomes, apart from controlling behaviors. Results from this longitudinal analysis of food insecurity and women's reports of intimate partner violence experience in a low- and middle-income country setting indicate that food insecurity is significantly associated with all forms of intimate partner violence, apart from controlling behaviors, among women in this sample in Mwanza, Tanzania. Policy and programmatic implications include the need for integrated intimate partner violence prevention programming to take into account household food needs.

F.4 Relationship between poor postoperative pain control and surgical outcomes after elective spine surgery

Background: Inadequate pain control after spine surgery is common, but its impact on long-term surgical outcomes has not been studied. Accordingly, this study aimed to investigate the relationship between poor postoperative pain control and surgical outcomes. Methods: Consecutive adult patients undergoing elective spine surgery were enrolled. Poor surgical outcome was defined as failure to achieve a minimal clinically important difference (MCID) of 30% improvement on the Oswestry Disability Index or Neck Disability Index at follow-up (3-months, 1-year, 2-years). Poor pain control was defined as a mean numeric rating scale score of &gt;4 within 24-hours postoperatively. Univariable analyses followed by multivariable random-effects models were used, after adjusting for known risk factors that impact surgical outcomes. Results: 42.8% of 1305 patients failed to achieve MCID at follow-up. 56.9% had poor postoperative pain control. Poor pain control was independently associated with failure to achieve MCID (OR 2.15 [95%CI=1.42-3.25], p&lt;0.001), after adjusting for age (p=0.15), sex (p=0.59), PHQ-9 score (p=0.030), ASA physical status &gt;2 (p&lt;0.001), ≥3 motion segment surgery (p=0.003), revision surgery (p=0.032), and follow-up time (p&lt;0.001). Conclusions: Poor pain control 24-hours after elective spine surgery was an independent risk factor for poor surgical outcome. Perioperative strategies to improve pain control may lead to improved outcomes.

The Optimal Dose, Efficacy and Safety of Tranexamic Acid and Epsilon-Aminocaproic Acid to Reduce Bleeding in TKA: A Systematic Review and Bayesian Network Meta-analysis.

The optimal dose and efficacy of tranexamic acid (TXA) and epsilon-aminocaproic acid (EACA) in total knee arthroplasty (TKA) were under controversial, and we aimed to make comparisons between different doses of TXA and EACA in intravenous (IV) or intra-articular (IA) applications in patients undergoing TKA. This network meta-analysis was guided by the Priority Reporting Initiative for Systematic Assessment and Meta-Analysis (PRISMA). According to the administrations of antifibrinolytic agents, patients in eligible studies were divided into three subgroups: (i) IA applications of TXA and EACA; (ii) IV applications (g) of TXA and EACA; (iii) IV applications (mg/kg) of TXA and EACA. Total blood loss (TBL), hemoglobin (HB) drops and transfusion rates were the primary outcomes, while drainage volume, pulmonary embolism (PE) or deep vein thrombosis (DVT) risk were the secondary outcomes. A multivariate Bayesian random-effects model was adopted in the network analysis. A total of 38 eligible trials with different regimens were assessed. Overall inconsistency and heterogeneity were acceptable. Taking all primary outcomes into account, 1.0-3.0 g TXA were most effective in IA applications, 1-6 g TXA and 10-14 g EACA were most effective in IV applications (g), while 30 mg/kg TXA and 150 mg/kg EACA were most effective in IV applications (mg/kg). None of the regimens showed increasing risk for pulmonary embolism (PE) or deep vein thrombosis (DVT) compared with placebo. 0 g IA TXA, 1.0 g IV TXA or 10.0 g IV EACA, as well as 30 mg/kg IV TXA or 150 mg/kg IV EACA were most effective and enough to control bleeding for patients after TKA. TXA was at least 5 times more potent than EACA.

Validation of a theoretically based mental health literacy framework: A meta-analytic structural equation modeling approach

IntroductionMental Health Literacy (MHL) includes four distinct but interrelated components: maintenance of positive mental health (MH), recognition of mental disorders (R), mental illness stigma attitudes (S), and help-seeking efficacy (E). A fifth component, help-seeking attitude (A) was included in a MHL model because it is a strong predictor of help-seeking behaviors. The five-factor model of MHL has been validated previously. In the study of multiple mediation model of MHL, it demonstrated the mediation role of help-seeking efficacy between recognition of mental disorders and help-seeking attitude (R-E-A path), but the roles of mental illness stigma attitudes or maintenance of positive mental health remain unknown.ObjectivesThe present study aimed to examine the theory-based multifaceted MHL model by utilizing a meta-analytic structural equation modeling analyses (MASEM) method.MethodsSystematic search of articles from electronic databases, including APA PsycArticles, ERIC, MEDLINE, Psychology and Behavioral Sciences Collection, Pubmed, and Airiti Library (Chinese), from inception up to July 31, 2022, was conducted by raters independently assessed study eligibility, and extracted 127 empirical, quantitative, non-interventional studies with properly reported effect sizes (k=192). MASEM analyses were conducted via a two-stage approach. First, a pooled correlation matrix was obtained for each mediation model by applying a multivariate random-effects model using Comprehensive Meta-Analysis Version 3.3. Second, a structural equation model was fitted on the pooled correlation matrices to test for mediation effects (i.e., indirect effects) using IBM SPSS Amos.ResultsIn the single-mediator model analysis, there was a significant partial mediation effect of help-seeking efficacy and Mental illness stigma attitudes on the relationship between recognition of mental disorders and help-seeking attitude (R-E-A path &amp; R-S-A path, p &lt;.05). The multiple-mediator model has showed adequate fit (RMSEA = 0.09, SRMR = 0.04, CFI = 0.93, GFI = .99). It confirmed the help-seeking efficacy served as a mediator. A sequential mediation of maintenance of positive mental health and mental illness stigma attitudes was found (p &lt;.05) between recognition of mental disorders and help-seeking attitude (R-MH-S-A path).ConclusionsThere is a robust mediation effect of Help-seeking efficacy on the relationship between recognition of mental disorders and help-seeking attitude either in the single mediation model or the multiple mediation model. Furthermore, increased recognition of mental disorder was related to increased maintenance of positive mental health, therefore decreased mental illness stigma attitude, and eventually increased help-seeking attitude. Future research directions regarding pathways in the MHL models were discussed.Disclosure of InterestNone Declared

Comparing the fundamental movement skill proficiency of children with intellectual disabilities and typically developing children: a systematic review and meta-analysis.

Children around the world, particularly those with intellectual disabilities (ID), are exhibiting poor motor skill proficiency. Compared with typically developing children (TDC), children with intellectual disabilities (CwID) are 65% more likely to exhibit low levels of motor competence. The purpose of this meta-analysis was to compare the motor skill proficiency levels, in terms of fundamental movement skills (FMS) of CwID to TDC. FMS are the building blocks required for lifelong participation in sport and physical activity. The meta-analysis was conducted according to PRISMA statement guidelines. 6 electronic databases were searched and 16, 679 studies were found. A total of 26 studies (total participants n = 3,525) met the inclusion criteria. A multivariate maximum likelihood multivariate random effects model was fitted to the data using the metafor package in R. The study showed that the standardised mean difference (Hedges' g) in FMS between TDC and CwID is large (g = 1.24; CI 95% [.87, 1.62]). Specifically, significant differences between the two groups emerged in all five outcomes: (1) total locomotor score, (2) total object manipulation score, (3) balance, (4) run skill and (5) throw skill. Further investigation into effective intervention strategies is required in order to reduce the magnitude of difference in motor skill proficiency between the two groups. In addition to developing, implementing and evaluating these interventions, researchers need to work hand in hand with national governing bodies (NGB) of sport and policy makers to ensure that teachers and coaches are being provided with opportunities to upskill in the area of FMS.

Analysis of the impact of research output on economic growth with using a multivariate random effects model

Analysis of the impact of research output on economic growth with using a multivariate random effects model

Lower Extremity Musculoskeletal Injuries After Concussion in Collegiate Student-Athletes

Background: An association has been identified between concussion and lower extremity musculoskeletal injury (LEMSKI) after return to sports participation. However, the collegiate student-athlete studies have relied on relatively small single-institution studies, which limits generalizability. Purpose: To assess odds of, and time to, LEMSKI after concussion in US collegiate athletes, using the National Collegiate Athletic Association (NCAA) Injury Surveillance Program (ISP). Study Design: Descriptive epidemiology study. Methods: Data from the NCAA ISP during the 2010-2011 through 2019-2020 athletic seasons were considered for analysis. Frequency distributions were examined for details related to the initial and subsequent injuries (injuries to bone, bursa, joint, ligament, muscle, or tendon). Multivariable logistic regression models and random-effects Poisson regression models examined odds of time loss (TL) and non–time loss (NTL) LEMSKI after concussion, as well as the time interval between initial concussion and subsequent LEMSKI in a single athletic season, or initial musculoskeletal injury (MSKI) and subsequent LEMSKI in a single athletic season. Analyses were performed separately for football and other sports. Results: A total of 31,556 initial injuries were recorded (football: 11,900; other sports: 19,656), which were followed by 0 or 1 injury in the same season. Overall, first injury type was not a significant predictor of subsequent LEMSKI, although certain contrasts yielded significant estimates. In football, the odds of NTL LEMSKI were higher after concussion than after upper extremity MSKI (UEMSKI; adjusted odds ratio [ORAdj], 1.56; 95% CI, 1.06-2.31). In football, the odds of TL LEMSKI were lower after concussion than after UEMSKI (ORAdj, 0.71; 95% CI, 0.51-0.99). No other significant effect estimates were observed for football or other sports. Conclusion: First injury type, either concussion or upper extremity, was not associated with an elevated risk of LEMSKI. Specifically, the results of this study did not identify an elevated odds of LEMSKI after a concussion. However, the authors observed greater odds of NTL LEMSKI and lower odds of TL LEMSKI in football.

Variation and Correlation of Potential Unintended Consequences of Antipsychotic Reduction in Ontario Nursing Homes Over Time.

Potentially inappropriate antipsychotic use has declined in nursing homes over the past decade; however, increases in the documentation of relevant clinical indications (eg, delusions) and the use of other psychotropic medications have raised concerns about diagnosis upcoding and medication substitution. Few studies have examined how these trends over time vary across and within nursing homes, information that may help to support antipsychotic reduction efforts. To jointly model facility-level time trends in potentially inappropriate antipsychotic use, antidepressant use, and the indications used to define appropriate antipsychotic use. We conducted a repeated cross-sectional study of all nursing homes in Ontario, Canada between April 1, 2010 and December 31, 2019 using linked health administrative data (N=649). Each nursing home's quarterly prevalence of potentially inappropriate antipsychotic use, antidepressant use, and relevant indications were measured as outcome variables. With time as the independent variable, multivariate random effects models jointly estimated time trends for each outcome across nursing homes and the correlations between time trends within nursing homes. We observed notable variations in the time trends for each outcome across nursing homes, especially for the relevant indications. Within facilities, we found no correlation between time trends for potentially inappropriate antipsychotic and antidepressant use ( r =-0.0160), but a strong negative correlation between time trends for potentially inappropriate antipsychotic use and relevant indications ( r =-0.5036). Nursing homes with greater reductions in potentially inappropriate antipsychotics tended to show greater increases in the indications used to define appropriate antipsychotic use-possibly leading to unmonitored use of antipsychotics.