scholarly journals l-arginine and Erectile Dysfunction

2019 ◽  
Vol 1 (1) ◽  
pp. 37-43 ◽  
Author(s):  
Arpit Koolwal ◽  
Shivananda Manohar J. ◽  
T. S. Sathyanarayana Rao ◽  
Ghanshyam D. Koolwal
Keyword(s):  
Nitric Oxide ◽  
Erectile Dysfunction ◽  
Review Article ◽  
Small Sample ◽  
Cochrane Library ◽  
Sample Sizes ◽  
Positive Evidence ◽  
Small Sample Sizes ◽  
Larger Sample ◽  
Natural Precursor

l-arginine, being a natural precursor of nitric oxide, is one of the more commonly used adjuvants to regular medicines in the treatment of erectile dysfunction. Objectives: Here, in this review article, we aim to highlight various studies and the research studies done on l-arginine in the treatment of erectile dysfunction. Method: Reviewing the databases such as Medline (PubMed), Cochrane Library, Excerpta Medica dataBASE, Trip, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, the Allied and Complementary Medicine Database, and the British Nursing Index. Results:l-arginine has been studied alone as well as in combination with various other molecules for the treatment of erectile dysfunction, but the studies are very limited in number and have very small sample sizes. Conclusion: Positive evidence is available for the efficacy of l-arginine and its various combinations. Further research with larger sample sizes and standardized tools are required to recommend the routine use of these products in erectile dysfunction.

How Strong Is the Evidence for the Effectiveness of Working Memory Training?

2019 ◽  
pp. 58-76
Author(s):  
Claudia C. von Bastian ◽  
Sabrina Guye ◽  
Carla De Simoni
Keyword(s):  
Working Memory ◽  
Cognitive Abilities ◽  
Small Sample ◽  
Sound Studies ◽  
Working Memory Training ◽  
Memory Training ◽  
Sample Sizes ◽  
Small Sample Sizes ◽  
Transfer Tasks ◽  
Larger Sample

This chapter argues that the question of whether working memory training can induce cognitive plasticity in terms of transfer effects cannot be conclusively answered yet due to persisting methodological issues across the literature. The shortcomings discussed include the lack of theoretically motivated selection of training and transfer tasks, the lack of active control groups, and small sample sizes. These problems call into question the strength of the existing evidence. Indeed, reevaluating published findings with Bayesian inference indicated that only a subset of published studies contributed interpretable evidence. The chapter concludes that the current body of literature cannot conclusively support claims that WM training does or does not improve cognitive abilities and stresses the need for theory-driven, methodologically sound studies with larger sample sizes.

scholarly journals A correction to the exact test based on the Ewens sampling distribution

1996 ◽  
Vol 68 (3) ◽  
pp. 259-260 ◽  
Author(s):  
Montgomery Slatkin
Keyword(s):  
Small Sample ◽  
Sampling Distribution ◽  
Sample Sizes ◽  
Exact Test ◽  
Small Sample Sizes ◽  
Larger Sample

SummaryThe exact test for neutrality based on the Ewens sampling distribution described previously (Slatkin, 1994) is not correct. The problem is that the test as described is based on the probability of the ordered configuration of numbers of alleles, while it should be based on the probability of the unordered configuration. The correctly implemented exact test leads to results that are similar to those from the homozygosity test proposed by Watterson (1977) for relatively small sample sizes but can still differ substantially for larger sample sizes. Programs to perform the exact test are available from the author.

scholarly journals Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review

10.2196/15981 ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. e15981 ◽  
Author(s):  
Jack Parker ◽  
Lauren Powell ◽  
Susan Mawson
Keyword(s):  
Upper Limb ◽  
Complex Interventions ◽  
Wearable Technology ◽  
Small Sample ◽  
International Classification Of Functioning ◽  
Cochrane Library ◽  
Stroke Survivors ◽  
Sample Sizes ◽  
Small Sample Sizes

Background With advances in technology, the adoption of wearable devices has become a viable adjunct in poststroke rehabilitation. Upper limb (UL) impairment affects up to 77% of stroke survivors impacting on their ability to carry out everyday activities. However, despite an increase in research exploring these devices for UL rehabilitation, little is known of their effectiveness. Objective This review aimed to assess the effectiveness of UL wearable technology for improving activity and participation in adult stroke survivors. Methods Randomized controlled trials (RCTs) and randomized comparable trials of UL wearable technology for poststroke rehabilitation were included. Primary outcome measures were validated measures of activity and participation as defined by the International Classification of Functioning, Disability, and Health. Databases searched were MEDLINE, Web of Science (Core collection), CINAHL, and the Cochrane Library. The Cochrane Risk of Bias Tool was used to assess the methodological quality of the RCTs and the Downs and Black Instrument for the quality of non RCTs. Results In the review, we included 11 studies with collectively 354 participants at baseline and 323 participants at final follow-up including control groups and participants poststroke. Participants’ stroke type and severity varied. Only 1 study found significant between-group differences for systems functioning and activity (P≤.02). The 11 included studies in this review had small sample sizes ranging from 5 to 99 participants at an average (mean) age of 57 years. Conclusions This review has highlighted a number of reasons for insignificant findings in this area including low sample sizes and the appropriateness of the methodology for complex interventions. However, technology has the potential to measure outcomes, provide feedback, and engage users outside of clinical sessions. This could provide a platform for motivating stroke survivors to carry out more rehabilitation in the absence of a therapist, which could maximize recovery. Trial Registration PROSPERO CRD42017057715; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=57715

scholarly journals Progress of Acupuncture Therapy in Diseases Based on Magnetic Resonance Image Studies: A Literature Review

2021 ◽  
Vol 15 ◽  
Author(s):  
Jinhuan Zhang ◽  
Zihan Li ◽  
Zhixian Li ◽  
Jiaying Li ◽  
Qingmao Hu ◽  
...  
Keyword(s):  
Acupuncture Therapy ◽  
Data Extraction ◽  
Premotor Cortex ◽  
Sham Acupuncture ◽  
Small Sample ◽  
Cochrane Library ◽  
Sample Sizes ◽  
Brain Response ◽  
Small Sample Sizes ◽  
The Brain

The neural mechanisms of acupuncture are not well-understood. Over the past decades, an increasing number of studies have used MRI to investigate the response of the brain to acupuncture. The current review aims to provide an update on acupuncture therapy in disease. The PubMed, Embase, Web of Science, and Cochrane Library databases were searched from inception to January 31, 2021. Article selection and data extraction were conducted by two review authors. A total of 107 publications about MRI in acupuncture were included, the collective findings of which were as follows: (1) stroke and GB34 (Yanglingquan) are the most studied disease and acupoint. Related studies suggested that the mechanism of acupuncture treatment for stroke may associate with structural and functional plasticity, left and right hemispheres balance, and activation of brain areas related to movement and cognition. GB34 is mainly used in stroke and Parkinson's disease, which mainly activates brain response in the premotor cortex, the supplementary motor area, and the supramarginal gyrus; (2) resting-state functional MRI (rs-fMRI) and functional connectivity (FC) analysis are the most frequently used approaches; (3) estimates of efficacy and brain response to acupuncture depend on the type of sham acupuncture (SA) used for comparison. Brain processing after acupuncture differs between patients and health controls (HC) and occurs mainly in disorder-related areas. Factors that influence the effect of acupuncture include depth of needling, number and locations of acupoints, and deqi and expectation effect, each contributing to the brain response. While studies using MRI have increased understanding of the mechanism underlying the effects of acupuncture, there is scope for development in this field. Due to the small sample sizes, heterogeneous study designs, and analytical methods, the results were inconsistent. Further studies with larger sample sizes, careful experimental design, multimodal neuroimaging techniques, and standardized methods should be conducted to better explain the efficacy and specificity of acupuncture, and to prepare for accurate efficacy prediction in the future.

scholarly journals Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review (Preprint)

2019 ◽  
Author(s):  
Jack Parker ◽  
Lauren Powell ◽  
Susan Mawson
Keyword(s):  
Upper Limb ◽  
Complex Interventions ◽  
Wearable Technology ◽  
Small Sample ◽  
International Classification Of Functioning ◽  
Cochrane Library ◽  
Stroke Survivors ◽  
Sample Sizes ◽  
Small Sample Sizes

BACKGROUND With advances in technology, the adoption of wearable devices has become a viable adjunct in poststroke rehabilitation. Upper limb (UL) impairment affects up to 77% of stroke survivors impacting on their ability to carry out everyday activities. However, despite an increase in research exploring these devices for UL rehabilitation, little is known of their effectiveness. OBJECTIVE This review aimed to assess the effectiveness of UL wearable technology for improving activity and participation in adult stroke survivors. METHODS Randomized controlled trials (RCTs) and randomized comparable trials of UL wearable technology for poststroke rehabilitation were included. Primary outcome measures were validated measures of activity and participation as defined by the International Classification of Functioning, Disability, and Health. Databases searched were MEDLINE, Web of Science (Core collection), CINAHL, and the Cochrane Library. The Cochrane Risk of Bias Tool was used to assess the methodological quality of the RCTs and the Downs and Black Instrument for the quality of non RCTs. RESULTS In the review, we included 11 studies with collectively 354 participants at baseline and 323 participants at final follow-up including control groups and participants poststroke. Participants’ stroke type and severity varied. Only 1 study found significant between-group differences for systems functioning and activity (<italic>P</italic>≤.02). The 11 included studies in this review had small sample sizes ranging from 5 to 99 participants at an average (mean) age of 57 years. CONCLUSIONS This review has highlighted a number of reasons for insignificant findings in this area including low sample sizes and the appropriateness of the methodology for complex interventions. However, technology has the potential to measure outcomes, provide feedback, and engage users outside of clinical sessions. This could provide a platform for motivating stroke survivors to carry out more rehabilitation in the absence of a therapist, which could maximize recovery.

scholarly journals Efficacy of St. John's Wort for Treating Mild to Moderate Depression

2007 ◽  
Vol 12 (3) ◽  
pp. 184-195 ◽  
Author(s):  
Tera Gahlsdorf ◽  
Robert Krause ◽  
Margaret W. Beal
Keyword(s):  
Small Sample ◽  
Sample Sizes ◽  
Control Groups ◽  
St John’S Wort ◽  
St John's Wort ◽  
Moderate Depression ◽  
Pharmaceutical Group ◽  
Conflicting Evidence ◽  
Small Sample Sizes ◽  
Larger Sample

Current studies regarding the efficacy of the herb St. John's wort (SJW) in treating mild to moderate cases of depression show conflicting evidence. In this article, we review the literature and consider similarities and differences between studies showing some efficacy and those showing none. Twelve published reports were reviewed. The majority of studies indicated the efficacy of SJW in the treatment of mild to moderate cases of depression. Most trials have had small sample sizes and either a placebo group or a standard pharmaceutical group. Two studies (both pediatric) were uncontrolled. Studies generally reported outcomes that had positive implications for their financial supporters and/or those with whom the primary investigators had acknowledged financial affiliations. More studies that have larger sample sizes and include placebo and pharmaceutical control groups are needed.

No Evidence that Experiencing Physical Warmth Promotes Interpersonal Warmth: Two Failures to Replicate Williams and Bargh (2008)

2018 ◽  
Author(s):  
Christopher Chabris ◽  
Patrick Ryan Heck ◽  
Jaclyn Mandart ◽  
Daniel Jacob Benjamin ◽  
Daniel J. Simons
Keyword(s):  
Null Hypothesis ◽  
Small Sample ◽  
Sample Sizes ◽  
Double Blind ◽  
Bayesian Analyses ◽  
Physical Warmth ◽  
Small Sample Sizes ◽  
Interpersonal Warmth

Williams and Bargh (2008) reported that holding a hot cup of coffee caused participants to judge a person’s personality as warmer, and that holding a therapeutic heat pad caused participants to choose rewards for other people rather than for themselves. These experiments featured large effects (r = .28 and .31), small sample sizes (41 and 53 participants), and barely statistically significant results. We attempted to replicate both experiments in field settings with more than triple the sample sizes (128 and 177) and double-blind procedures, but found near-zero effects (r = –.03 and .02). In both cases, Bayesian analyses suggest there is substantially more evidence for the null hypothesis of no effect than for the original physical warmth priming hypothesis.

scholarly journals G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Florent Le Borgne ◽  
Arthur Chatton ◽  
Maxime Léger ◽  
Rémi Lenain ◽  
Yohann Foucher
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Statistical Power ◽  
Small Sample ◽  
Causal Effects ◽  
Small Samples ◽  
Support Vector ◽  
Sample Sizes ◽  
Super Learner ◽  
Small Sample Sizes

AbstractIn clinical research, there is a growing interest in the use of propensity score-based methods to estimate causal effects. G-computation is an alternative because of its high statistical power. Machine learning is also increasingly used because of its possible robustness to model misspecification. In this paper, we aimed to propose an approach that combines machine learning and G-computation when both the outcome and the exposure status are binary and is able to deal with small samples. We evaluated the performances of several methods, including penalized logistic regressions, a neural network, a support vector machine, boosted classification and regression trees, and a super learner through simulations. We proposed six different scenarios characterised by various sample sizes, numbers of covariates and relationships between covariates, exposure statuses, and outcomes. We have also illustrated the application of these methods, in which they were used to estimate the efficacy of barbiturates prescribed during the first 24 h of an episode of intracranial hypertension. In the context of GC, for estimating the individual outcome probabilities in two counterfactual worlds, we reported that the super learner tended to outperform the other approaches in terms of both bias and variance, especially for small sample sizes. The support vector machine performed well, but its mean bias was slightly higher than that of the super learner. In the investigated scenarios, G-computation associated with the super learner was a performant method for drawing causal inferences, even from small sample sizes.

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