scholarly journals Pharmacist-Led Interventions to Improve Medication Adherence in Older Adults: A Meta-Analysis

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 335-335
Author(s):  
Zachary Marcum ◽  
Shangqing Jiang ◽  
Jennifer Bacci ◽  
Todd Ruppar
Keyword(s):  
Older Adults ◽  
Medication Adherence ◽  
Effect Size ◽  
English Language ◽  
Randomized Clinical Trials ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Analysis Model ◽  
Improve Medication Adherence ◽  
The Mean

Abstract As pharmacists work to ensure reimbursement for chronic disease management services on the national (e.g., Medicare) level, summative evidence of their impact on important health metrics, such as medication adherence, is needed. The objective of this study was to assess the effectiveness of pharmacist-led interventions on medication adherence in older adults. In April 2020, a comprehensive search was conducted in six databases for publications of randomized clinical trials of pharmacist-led interventions to improve medication adherence in older adults. English-language studies with codable data on medication adherence and diverse adherence-promoting interventions targeting older adults (age 65+) were eligible. A standardized mean difference effect size (intervention vs. control) was calculated for the medication adherence outcome in each study. Study effect sizes were pooled using a random-effects meta-analysis model. Moderator analyses were then conducted to explore for differences in effect size due to intervention, sample, and study characteristics. The primary outcome was medication adherence using any method of measurement. This meta-analysis included 40 unique randomized trials of pharmacist-led interventions with data from 8,822 unique patients (mean age, range: 65 to 85 years). The mean effect size was 0.57 (95% Confidence Interval [CI]: 0.38-0.76). When two outlier studies were excluded from the analysis, the mean effect size decreased to 0.41 (95% CI: 0.27-0.54). Moderator analyses showed larger effect sizes for interventions containing medication education and when interventions had components delivered at least partly in patients’ homes. In conclusion, this meta-analysis found a significant improvement in medication adherence among older adults receiving pharmacist-led interventions.

Test Frequency, Stakes, and Feedback in Student Achievement: A Meta-Analysis

2019 ◽  
Vol 43 (3-4) ◽  
pp. 111-151 ◽  
Author(s):  
Richard P. Phelps
Keyword(s):  
Student Achievement ◽  
Early Childhood ◽  
Effect Size ◽  
English Language ◽  
Variance Estimation ◽  
Meta Analysis ◽  
The United States ◽  
Research Literature ◽  
Effect Sizes ◽  
Test Frequency

Background: Test frequency, stakes associated with educational tests, and feedback from test results have been identified in the research literature as relevant factors in student achievement. Objectives: Summarize the separate and joint contribution to student achievement of these three treatments and their interactions via multivariable meta-analytic techniques using a database of English-language studies spanning a century (1910–2010), comprising 149 studies and 509 effect size estimates. Research design: Analysis employed robust variance estimation. Considered as potential moderators were hundreds of study features comprising various test designs and test administration, demographic, and source document characteristics. Subjects: Subjects were students at all levels, from early childhood to adult, mostly from the United States but also eight other countries. Results: We find a summary effect size of 0.84 for the three treatments collectively. Further analysis suggests benefits accrue to the incremental addition of combinations of testing and feedback or stakes and feedback. Moderator analysis shows higher effect sizes associated with the following study characteristics: more recent year of publication, summative (rather than formative) testing, constructed (rather than selected) item response formats, alignment of subject matter between pre- and posttests, and recognition/recall (rather than core subjects, art, or physical education). Conversely, lower effect sizes are associated with postsecondary students (rather than early childhood–upper secondary), special education population, larger study population, random assignment (rather than another sampling method), use of shadow test as outcome measure, designation of individuals (rather than groups) as units of analysis, and academic (rather than corporate or government) research.

scholarly journals Introducere în metaanaliză. Metaanaliza corelațiilor

2020 ◽  
Vol 6 (2) ◽  
pp. 112-127
Author(s):  
Laurențiu Maricuțoiu
Keyword(s):  
Statistical Method ◽  
Confidence Intervals ◽  
Effect Size ◽  
Meta Analysis ◽  
Relevant Information ◽  
Effect Sizes ◽  
The Mean

The present paper discusses the fundamental principles of meta-analysis, as a statistical method for summarising results of correlational studies. We approach fundamental issues such as: the finality of meta-analysis and the problems associated with study artefacts. The paper also contains recommendations for: selecting the studies for meta-analysis, identifying the relevant information within these studies, computing mean effect sizes, confidence intervals and heterogeneity indexes of the mean effect size. Finally, we present indications for reporting meta-analysis results.

scholarly journals RADT-37. THE IMPACT OF POSTOPERATIVE RADIATION THERAPY (PORT) AND EXTENT OF SURGERY ON CLINICAL OUTCOMES OF ATYPICAL MENINGIOMA (AM): A META-ANALYSIS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii189-ii189
Author(s):  
Philip Haddad ◽  
Furqan Akhtar ◽  
Kevin Gallagher
Keyword(s):  
Clinical Outcomes ◽  
Comparative Studies ◽  
English Language ◽  
Randomized Clinical Trials ◽  
Meta Analysis ◽  
Subtotal Resection ◽  
Recurrence Rates ◽  
Postoperative Radiation Therapy ◽  
Extent Of Surgery ◽  
The Impact

Abstract BACKGROUND Although meningiomas are among the most prevalent types of brain tumors, AMs account for around 4% of all meningiomas. AMs tend to be more aggressive with relatively higher rates of recurrence and mortality. Gross total resection (GTR) has been the standard of care when possible. However, GTR itself is not always enough to prevent the recurrence of AMs. The role of PORT remains controversial in AM as the comparative studies to support its use have provided conflicting RESULTS: The purpose of this meta-analysis is to evaluate the impact of PORT on clinical outcomes according to the extent of resection in AMs. METHODS A review of the medical literature was conducted using online databases. Inclusion criteria consisted of AM diagnosis, English language, Simpson graded resections, and comparative studies reporting recurrence rates (RcR), Progression-Free Survival (PFS), and Overall Survival (OS) with hazard ratios (HR) or Kaplan-Meier curves. A meta-analysis was conducted using an inverse variance method with a random-effects model. RESULTS Twenty-two comparative studies with a total of 5,129 patients were included and analyzed. When GTR was attained, PORT was associated with improved RcR (HR =0.72, 95%CI:0.59-0.86) and PFS (HR=0.77, 95%CI:0.65-0.90), but not OS (HR=0.93, 95%CI:0.83-1.04). When subtotal resection (STR) was attained, PORT was associated with improved PFS (HR=0.35, 95%CI:0.26-0.48) as well as OS (HR=0.70, 95%CI:0.54-0.89). The extent of surgery also impacted AM outcomes as GTR demonstrated superior PFS (HR=0.45, 95%CI:0.31-0.65) and OS (HR=0.30, 95%CI:0.13-0.72). CONCLUSIONS This is the first meta-analysis to show that PORT is associated with PFS benefit in AMs with GTR and STR. Moreover, PORT significantly improved OS of AMs that underwent STR but had no impact on OS when GTR was achieved. In the absence of randomized clinical trials, this meta-analysis represents the most compelling data supporting the use of PORT in this patient population.

scholarly journals A Statistical Method for Synthesizing Meta-Analyses

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Liansheng Larry Tang ◽  
Michael Caudy ◽  
Faye Taxman
Keyword(s):  
Statistical Method ◽  
Effect Size ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Weighted Mean ◽  
Summary Effect ◽  
Different Types ◽  
Meta Analyses ◽  
Size Estimates ◽  
Similar Search

Multiple meta-analyses may use similar search criteria and focus on the same topic of interest, but they may yield different or sometimes discordant results. The lack of statistical methods for synthesizing these findings makes it challenging to properly interpret the results from multiple meta-analyses, especially when their results are conflicting. In this paper, we first introduce a method to synthesize the meta-analytic results when multiple meta-analyses use the same type of summary effect estimates. When meta-analyses use different types of effect sizes, the meta-analysis results cannot be directly combined. We propose a two-step frequentist procedure to first convert the effect size estimates to the same metric and then summarize them with a weighted mean estimate. Our proposed method offers several advantages over existing methods by Hemming et al. (2012). First, different types of summary effect sizes are considered. Second, our method provides the same overall effect size as conducting a meta-analysis on all individual studies from multiple meta-analyses. We illustrate the application of the proposed methods in two examples and discuss their implications for the field of meta-analysis.

scholarly journals Changes of Ankle Dorsiflexion Using Compression Tissue Flossing: A Systematic Review and Meta-Analysis

2020 ◽  
pp. 1-9
Author(s):  
Devin S. Kielur ◽  
Cameron J. Powden
Keyword(s):  
Confidence Interval ◽  
Range Of Motion ◽  
Effect Size ◽  
Evidence Synthesis ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Lower Extremity Injury ◽  
Level Of Evidence ◽  
Physically Active ◽  
Evidence Database

Context: Impaired dorsiflexion range of motion (DFROM) has been established as a predictor of lower-extremity injury. Compression tissue flossing (CTF) may address tissue restrictions associated with impaired DFROM; however, a consensus is yet to support these effects. Objectives: To summarize the available literature regarding CTF on DFROM in physically active individuals. Evidence Acquisition: PubMed and EBSCOhost (CINAHL, MEDLINE, and SPORTDiscus) were searched from 1965 to July 2019 for related articles using combination terms related to CTF and DRFOM. Articles were included if they measured the immediate effects of CTF on DFROM. Methodological quality was assessed using the Physiotherapy Evidence Database scale. The level of evidence was assessed using the Strength of Recommendation Taxonomy. The magnitude of CTF effects from pre-CTF to post-CTF and compared with a control of range of motion activities only were examined using Hedges g effect sizes and 95% confidence intervals. Randomeffects meta-analysis was performed to synthesize DFROM changes. Evidence Synthesis: A total of 6 studies were included in the analysis. The average Physiotherapy Evidence Database score was 60% (range = 30%–80%) with 4 out of 6 studies considered high quality and 2 as low quality. Meta-analysis indicated no DFROM improvements for CTF compared with range of motion activities only (effect size = 0.124; 95% confidence interval, −0.137 to 0.384; P = .352) and moderate improvements from pre-CTF to post-CTF (effect size = 0.455; 95% confidence interval, 0.022 to 0.889; P = .040). Conclusions: There is grade B evidence to suggest CTF may have no effect on DFROM when compared with a control of range of motion activities only and results in moderate improvements from pre-CTF to post-CTF. This suggests that DFROM improvements were most likely due to exercises completed rather than the band application.

scholarly journals Cognitive Behavioral Therapy combined with physical exercise for depression, anxiety, fatigue and pain in adults with chronic diseases: systematic review and meta-analysis

2018 ◽  
Author(s):  
Paquito Bernard ◽  
Romain Ahmed Jérôme ◽  
Johan Caudroit ◽  
Guillaume Chevance ◽  
Carayol Marion ◽  
...  
Keyword(s):  
Physical Exercise ◽  
Methodological Quality ◽  
Randomized Clinical Trials ◽  
Behavioral Therapy ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Cognitive Behavior ◽  
Cochrane Central Register ◽  
Depression And Anxiety ◽  
Central Register

Objective. The present meta-analysis aimed to determine the overall effect of cognitive behavior therapy combined with physical exercise (CBTEx) interventions on depression, anxiety, fatigue, and pain in adults with chronic illness; to identify the potential moderators of efficacy; and to compare the efficacy of CBTEx versus each condition alone (CBT and physical exercise). Methods. Relevant randomized clinical trials, published before July 2017, were identified through database searches in Pubmed, PsycArticles, CINAHL, SportDiscus and the Cochrane Central Register for Controlled Trials.Results. A total of 30 studies were identified. CBTEx interventions yielded small-to-large effect sizes for depression (SMC = -0.34, 95% CI [-0.53; -0.14]), anxiety (SMC = -0.18, 95% CI [-0.34; -0.03]) and fatigue (SMC = -0.96, 95% CI [-1.43; -0.49]). Moderation analyses revealed that longer intervention was associated with greater effect sizes for depression and anxiety outcomes. Low methodological quality was also associated with increased CBTEx efficacy for depression. When compared directly, CBTEx interventions did not show greater efficacy than CBT alone or physical exercise alone for any of the outcomes. Conclusion. The current literature suggests that CBTEx interventions are effective for decreasing depression, anxiety, and fatigue symptoms, but not pain. However, the findings do not support an additive effect of CBT and exercise on any of the four outcomes compared to each condition alone.

Effect Sizes: Conventional Choices and Calculations

2013 ◽  
Author(s):  
Michael S. Rosenberg ◽  
Hannah R. Rothstein ◽  
Jessica Gurevitch
Keyword(s):  
Critical Point ◽  
Effect Size ◽  
Evolutionary Biology ◽  
Meta Analysis ◽  
Statistical Parameter ◽  
Effect Sizes ◽  
Common Effect ◽  
Inference Methods ◽  
Conventional Effect ◽  
Estimate Effect Size

One of the fundamental concepts in meta-analysis is that of the effect size. An effect size is a statistical parameter that can be used to compare, on the same scale, the results of different studies in which a common effect of interest has been measured. This chapter describes the conventional effect sizes most commonly encountered in ecology and evolutionary biology, and the types of data associated with them. While choice of a specific measure of effect size may influence the interpretation of results, it does not influence the actual inference methods of meta-analysis. One critical point to remember is that one cannot combine different measures of effect size in a single meta-analysis: once you have chosen how you are going to estimate effect size, you need to use it for all of the studies to be analyzed.

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