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Background Randomized pre-post designs, with outcomes measured at baseline and after treatment, have been commonly used to compare the clinical effectiveness of two competing treatments. There are vast, but often conflicting, amount of information in current literature about the best analytic methods for pre-post designs. It is challenging for applied researchers to make an informed choice. Methods We discuss six methods commonly used in literature: one way analysis of variance (“ ANOVA” ) , analysis of covariance main effect and interaction models on the post-treatment score (“ ANCOVA I ” and “ ANCOVA II ”), ANOVA on the change score between the baseline and post-treatment scores (“ ANOVA-Change ”), repeated measures (“ RM” ) and constrained repeated measures (“ cRM” ) models on the baseline and post-treatment scores as joint outcomes. We review a number of study endpoints in randomized pre-post designs and identify the mean difference in the post-treatment score as the common treatment effect that all six methods target. We delineate the underlying differences and connections between these competing methods in homogeneous and heterogeneous study populations. Results ANCOVA and cRM outperform other alternative methods because their treatment effect estimators have the smallest variances. cRM has comparable performance to ANCOVA I in the homogeneous scenario and to ANCOVA II in the heterogeneous scenario. In spite of that, ANCOVA has several advantages over cRM: i) the baseline score is adjusted as covariate because it is not an outcome by definition; ii) it is very convenient to incorporate other baseline variables and easy to handle complex heteroscedasticity patterns in a linear regression framework. Conclusions ANCOVA is a simple and the most efficient approach for analyzing pre-post randomized designs.

Pre-post designs are widely used in clinical trials and experimental studies to assess the effectiveness of treatments. Common statistical methods for analyzing pre-post data include analysis of variance (ANOVA) using post-treatment or the change from baseline, analysis of covariance (ANCOVA) with homogeneous or heterogeneous slopes, and linear mixed models (LMM). While numerous studies have compared these methods, limited studies have investigated the impact of adjusting for influential baseline covariates under different randomization approaches. In this study, we conducted a series of comprehensive simulation studies to investigate the impact of adjusting baseline covariates under several randomization approaches: simple randomization, stratified block randomization, and covariate adaptive randomization using the minimization method by Pocock and Simon. Results demonstrated that when no covariates were considered in the randomization approach, the two ANCOVA methods always have good performance. Adjusting for relevant baseline covariates led to substantial power gains, with the extent of these gains depending on the size of the covariate effects and the randomization approach employed. Stratified block randomization and covariate adaptive randomization consistently outperformed simple randomization in terms of power gains after adjusting for covariates, with covariate adaptive randomization becoming more superior as the number of covariates increased.

Background In pre-post designs, analysis of covariance (ANCOVA) is a standard technique to detect the treatment effect with a continuous variable measured at baseline and follow-up. For measurements subject to a high degree of variability, it may be advisable to repeat the pre-treatment and/or follow-up assessments. In general, repeating the follow-up measurements is more advantageous than repeating the pre-treatment measurements, while the latter can still be valuable and improve efficiency in clinical trials. Methods In this article, we report investigations of using multiple pre-treatment and post-treatment measurements in randomized clinical trials. We consider the sample size formula for ANCOVA under general correlation structures with the pre-treatment mean included as the covariate and the mean follow-up value included as the response. We propose an optimal experimental design of multiple pre-post allocations under a specified constraint, that is, given the total number of pre-post treatment visits. The optimal number of the pre-treatment measurements is derived. For non-linear models, closed-form formulas for sample size/power calculations are generally unavailable, but we conduct Monte Carlo simulation studies instead. Results Theoretical formulas and simulation studies show the benefits of repeating the pre-treatment measurements in pre-post randomized studies. The optimal pre-post allocation derived from the ANCOVA extends well to binary measurements in simulation studies, using logistic regression and generalized estimating equations (GEE). Conclusions Repeating baselines and follow-up assessments is a valuable and efficient technique in pre-post design. The proposed optimal pre-post allocation designs can minimize the sample size, i.e., achieve maximum power.

Access to green schoolyards (schoolyards designed with greenery and natural elements to create a park-like environment, as opposed to asphalt-based playgrounds) are associated with many benefits for students, including improvements in physical and mental health. While many studies examining these associations are cross-sectional, some feature experimental designs that offer the possibility of causal inference. In this review, we looked at experimental studies that examine the impact of schoolyard greening on measures of physical activity and socioemotional health in children. Four electronic databases (Ovid Medline, PsycINFO, Scopus and Greenfile) were searched, and from 1843 articles retrieved, 6 articles met the inclusion criteria. Examination of the eligible studies revealed a general consensus on the positive impact of schoolyard greening on both physical activity and socioemotional health outcomes for students, suggesting that schoolyard greening is a viable intervention in reducing the health equity gaps and improving children’s health regardless of their racial or ethnic backgrounds or residential neighborhood socioeconomic status. Further experimental research on this topic should elucidate how educators, administrators, policy makers, and other stakeholders can harness the benefits of schoolyard greening to improve the health and well-being of children in their communities.

Background Interprofessional communication is of extraordinary importance for patient safety. To improve interprofessional communication, joint training of the different healthcare professions is required in order to achieve the goal of effective teamwork and interprofessional care. The aim of this pilot study was to develop and evaluate a joint training concept for nursing trainees and medical students in Germany to improve medication error communication. Methods We used a mixed-methods, quasi-experimental study with a pre-post design and two study arms. This study compares medical students (3rd year) and nursing trainees (2nd year) who received an interprofessional communication skills training with simulation persons (intervention group, IG) with a control group (CG). Both cohorts completed identical pre- and post-training surveys using the German Interprofessional Attitudes Scale (G-IPAS) and a self-developed interprofessional error communication scale. Descriptive statistics, Mann-Whitney-U-test and Wilcoxon-test were performed to explore changes in interprofessional error communication. Results A total of 154 were medical students, and 67 were nursing trainees (IG: 66 medical students, 28 nursing trainees / CG: 88 medical students, 39 nursing trainees). After training, there were significant improvements observed in the “interprofessional error communication” scale (p < .001) and the “teamwork, roles, and responsibilities” subscale (p = .012). Median scores of the subscale “patient-centeredness” were similar in both groups and remained unchanged after training (median = 4.0 in IG and CG). Conclusions Future studies are needed to find out whether the training sustainably improves interprofessional teamwork regarding error communication in acute care.

Background Limited access to onsite radiologists in Low- and Middle-Income Countries (LMICs) poses challenges for health facilities in delivering timely radiology services resulting in prolonged patient waiting times and dissatisfaction with the insufficient radiology services. In recent years, teleradiology has emerged as a potential solution to improve the timely diagnosis and treatment process. Therefore, this paper analysed the effect of a web-based teleradiology system that was developed and deployed to evaluate its effect on patient waiting time and service satisfaction in public hospitals of the Amhara Regional State. Methods A pre-post study design was employed to evaluate the effect of a web-based teleradiology system on patient waiting time and service satisfaction. The study included a total of 836 participants, out of which 417 participated during the pre-intervention and 419 in the post-intervention periods. Data were collected from October 2021 to February 2022 and from May 2022 to January 2023 for the pre-and post-implementation periods, respectively. Supportive measures, including user guides, onsite training, and onsite/virtual assistance, were given during the teleradiology implementation period. The effects of the teleradiology on waiting time and service satisfaction were evaluated with the Mann-Whitney U-test and the Generalized Linear Model. Waiting time was measured as the duration between image consultation and report completion. Furthermore, satisfaction was assessed using a 31-item, 5-point Likert scale. The statistical analysis was done using Stata version 17 software. Results After the implementation of the web-based teleradiology system, a significant decrease in the median waiting time was observed from 43.5 h (IQR: 22.88–71.63) to 4.62 h (IQR: 2.52–10.53) ( p -value < 0.01). The effect size for this improvement was found to be 0.84. Furthermore, the median patient satisfaction score was significantly improved from 96 (IQR: 89–103) to 113 (IQR: 105–124) ( p -value < 0.01) and an effect size of 0.65. Similarly, the percentage of the scale mean score (%SM) showed an increase in patient satisfaction levels from 52.6% (pre-implementation) [95% CI: 51.8–53.5] to 65.7% (post-implementation) [95% CI: 64.5 -66.9%]. The GLM analysis demonstrated a 71% decrease in patient waiting time and an 11% increase in radiography service satisfaction ( p -value < 0.01). Conclusion Implementing the web-based teleradiology system improved the patient’s waiting time and service satisfaction remarkably. The notable reduction in waiting time and the significant improvement in patient satisfaction scores highlighted the benefits of teleradiology in enhancing timely diagnosis and treatment. Deploying a web-based teleradiology system in public hospitals is recommended to enhance efficiency and improve patient satisfaction in radiology consultations. Trial registration number PACTR202401789144564. Trial registration date 09 January 2024.

Objectives To characterize the distribution of vaping retailers and examine the association between neighbourhood income and vaping retailer availability in Ontario prior to and after regulatory changes to the vaping market in 2018. Methods We quantified vaping access by number of vaping retailers for 19,964 dissemination areas (DAs) in Ontario and percentage of schools near a vaping retailer. We used mixed-effects regression models to examine the associations between vaping access and neighbourhood income in 2018 and 2019. Results Between 2016 and 2019, the number of vaping retailers in Ontario increased by 22.6% (5999 to 7355), despite a mild drop from 2016 to 2018. In 2019, 59.7% of urban neighbourhoods had one or more vaping retailers within 1000 m of their geographic centre, and 79.4% of elementary, 82.8% of secondary, and 84.2% of post-secondary schools had at least one within 1000 m. Neighbourhood income was associated with access to vaping retailers, with a greater number in low-income regions. In 2019, neighbourhoods in the lowest income quintile had over twice the number of vaping retailers per capita within 1000 m compared to the highest income quintile (adjusted incidence rate ratio 2.40; 95% CI 2.24–2.58). Increases over time in access to vaping retailers did not differ by geographic region, neighbourhood income quintile, or school type. Conclusion We observed a substantial increase in access to vaping retailers in Ontario including proximity to elementary and secondary schools following the 2018 provincial marketing regulations and federal nicotine regulations. Access to vaping was greatest in low-income neighbourhoods and may contribute to established inequities in vaping-related adverse events.

Background: This study examined changes in psychological adjustment among patients with Anorexia Nervosa (AN) and Binge Eating Disorder (BED) following a 3-week inpatient multidisciplinary (disease-tailored) rehabilitation program. Methods: twenty consecutive Italian female adults with a diagnosis of AN (mean age ± SD: 25.9 ± 9.4 years; mean Body Mass Index: BMI: kg/m2: 15.8 ± 1.61) and fifteen consecutive Italian female adults with diagnosis of BED (mean age ± SD: 43.5 ± 15.3 years; mean Body Mass Index: BMI: kg/m2: 41.1 ± 7.82) were admitted to the study. Psychological functioning and well-being were assessed pre- and post-intervention using the Strengths and Difficulties Questionnaire and the Psychological General Well-Being Index. Results: Significant improvements in emotional symptoms [F(1, 31) = 21.1973, p < 0.001, ƞ2p = 0.406] and overall psychological functioning [F(1, 31) = 10.0062, p = 0.373, ƞ2p = 0.026] were observed in both groups, with the most pronounced changes in internalizing symptoms, such as anxiety and depression. Changes in BMI were significantly associated with emotional symptoms, vitality [F(1, 31) = 4.89, p = 0.035, ƞ2p = 0.136], and total well-being scores [F(1, 31) = 6.341, p = 0.017, ƞ2p = 0.170]. By contrast, no significant changes were observed in domains such as behavioral problems, hyperactivity/inattention, and peer relationships, probably indicating the need for more prolonged and targeted, domain-specific interventions. Conclusions: A 3-week inpatient multidisciplinary program was associated with improvements in internalizing symptoms and psychological well-being in women with AN and BED. Domains such as behavioral regulation and social functioning showed limited change, indicating the need for longer and targeted psychosocial components.

Hazard experience has been shown to influence risk perceptions, hazard salience, and the types of hazard adjustments people consider and undertake. Literature exploring the impact of experience on these constructs and decisions is, however, limited, with scholars often disagreeing on what counts as experience and lacking pre-event measures to compare to post-event outcomes. Given the difficulties in both predicting hazard occurrences with the temporal accuracy required to conduct pre-impact assessments close to the event and implementing surveys in a post-disaster environment, pre–post studies of disasters are rare. This study, by serendipity, achieved just this by distributing a survey exploring responses to techna earthquakes by college students in Oklahoma, receiving responses in the period just before and after the largest earthquake in modern Oklahoma history. In line with much of the existing literature, our results show that the Pawnee earthquake had significant impacts on respondents’ risk perceptions and hazard salience. Contrary to other findings, we did not find a relationship between hazard salience and hazard adjustments. Adjustments undertaken were predominately limited to information-seeking measures. Risk perceptions, of note, were more likely to be correlated with adjustment measures after the earthquake. This indicates that risk perceptions prior to the earthquake were not enough to motivate intention to adopt adjustments, but the Pawnee earthquake led those with heightened risk perceptions, along with others that had their risk perceptions positively influenced by the earthquake, to consider adopting hazard adjustments. We suggest that emergency managers use this window to encourage residents to undertake adjustment measures.

Pre-Post intervention factorial design with multiple observations for each subject before and after the intervention frequently arises in Quality-of-Life (QoL) research. Usually not only a global hypothesis on intervention is of interest, but also the hypotheses of pre-post change and also the interaction between intervention and pre-post change. In most practical situations, the distribution of the observed data is unknown and there may exist a number of atypical measurements and outliers. More importantly, QoL outcomes are measured in rating scales and the multiple Quality-of-Life measurements before and after the intervention present complex within-subject correlations. Hence, use of parametric and semi-parametric procedures that impose restrictive distributional and correlation assumptions becomes questionable. This emphasizes the demand for statistical procedures that enable us to accurately and reliably analyze QoL outcomes with minimal conditions. Nonparametric methods offer such a possibility and thus become of particular practical importance in the field of QoL. In this article, we aim to expose researchers and practitioners in the biomedical and behavioral science to nonparametric methods for the analysis of data collected in clustered randomized design. We also illustrate the use of the R package npclust we developed for an easy and user-friendly access to nonparametric methods for the analysis of Quality-of-Life data. It provides procedures for pre-processing the data, performing various hypothesis tests and computing confidence intervals for the estimated effects. The procedures also contain methods for visual display of the results. We illustrate the implemented procedures with Pediatric Asthma Quality-of-Life data collected from the Asthma Randomized Trial of Indoor wood Smoke (ARTIS).