An Overview of Publications of Complementary and Alternative Medicine Research

This chapter presents an overview of the quantity and quality of clinical research in CAM and publication bias. Descriptive studies and their systematic reviews on CAM, e.g., prevalence and reasons for CAM use, have been widely conducted worldwide. The findings of the efficacy of herbal medicine, traditional Chinese medicine and acupuncture for treating various illnesses, have been highly published. Publications of CAM safety are limited. A number of clinical studies of CAM in treating kidney diseases were lower than other illnesses. Studies of Ayurveda and other CAMs are still lacking. The quality of CAM publications is described based on systematic reviews of assessing CAM publications. Publication bias is explained in terms of selective publications and location bias, language bias and conflict of interest. The mainstream journals are more likely to publish positive findings. Predatory open access and recommendations for assessing predatory journals are addressed in this chapter.

A Narrative Literature Review of Bias in Collecting Patient Reported Outcomes Measures (PROMs)

There is a growing interest in the collection and use of patient reported outcomes because they not only provide clinicians with crucial information, but can also be used for economic evaluation and enable public health decisions. During the collection phase of PROMs, there are several factors that can potentially bias the analysis of PROM data. It is crucial that the collected data are reliable and comparable. The aim of this paper was to analyze the type of bias that have already been taken into consideration in the literature. A literature review was conducted by the authors searching on PubMed database, after the selection process, 24 studies were included in this review, mostly regarding orthopedics. Seven types of bias were identified: Non-response bias, collection method related bias, fatigue bias, timing bias, language bias, proxy response bias, and recall bias. Regarding fatigue bias and timing bias, only one study was found; for non-response bias, collection mode related bias, and recall bias, no agreement was found between studies. For these reasons, further research on this subject is needed in order to assess each bias type in relation to each medical specialty, and therefore find correction methods for reliable and comparable data for analysis.

Determining the safety and effectiveness of Tai Chi: A critical overview of 210 systematic reviews of controlled clinical trials

Background: This overview aims to critically appraise the best available systematic review (SR) evidence on the health effects of Tai Chi. Methods: Nine databases (English and Chinese languages) were searched for SRs of controlled clinical trials of Tai Chi interventions published between Jan-2010 and Dec-2020 in any language. Excluded were primary studies and meta-analyses that combined Tai Chi with other interventions. To minimise overlap, effect estimates were extracted from the most recent, comprehensive, highest quality SR for each population, condition, and outcome. SR quality was appraised using AMSTAR 2 and effect estimates with GRADE.Results: Of the 210 included SRs, 193 only included randomised controlled trials, one only included non-randomised studies of interventions, and 16 included both. The most common conditions were neurological (18.6%), falls/balance (14.7%), cardiovascular (14.7%), musculoskeletal (11.0%), cancer (7.1%) and diabetes mellitus (6.7%). Except for stroke, no evidence for disease prevention was found, instead proxy-outcomes/risks factors were evaluated. 114 effect estimates were extracted from 37 SRs (2 high quality, 6 moderate, 18 low, and 11 critically low), representing 59,306 adults. Compared to active and/or inactive controls, a clinically important benefit from Tai Chi was reported for 66 effect estimates; 53 reported an equivalent or marginal benefit, and 6 an equivalent risk of adverse events. Eight effect estimates (7.0%) were graded as high certainty evidence, 43 (37.7%) moderate, 36 (31.6%) low, and 27 (23.7%) very low. This was due to concerns with risk of bias in 92 (80.7%) effect estimates, imprecision in 43 (37.7%), inconsistency in 37 (32.5%) and publication bias in 3 (2.6%). SR quality was limited by the search strategies, language bias, inadequate consideration of clinical, methodological and statistical heterogeneity, poor reporting standards, and/or no registered protocol. Conclusions: The findings suggest Tai Chi has multisystem effects with physical, psychological, and quality of life benefits for a wide range of conditions, including individuals with multiple health problems. Clinically important benefits were most consistently reported for Parkinson’s disease, falls risk, knee osteoarthritis, low back pain, cardiovascular diseases including hypertension, and stroke. Notwithstanding, for most conditions, higher quality primary studies and SRs are required.

Language Bias in the Google Scholar Ranking Algorithm

The visibility of academic articles or conference papers depends on their being easily found in academic search engines, above all in Google Scholar. To enhance this visibility, search engine optimization (SEO) has been applied in recent years to academic search engines in order to optimize documents and, thereby, ensure they are better ranked in search pages (i.e., academic search engine optimization or ASEO). To achieve this degree of optimization, we first need to further our understanding of Google Scholar’s relevance ranking algorithm, so that, based on this knowledge, we can highlight or improve those characteristics that academic documents already present and which are taken into account by the algorithm. This study seeks to advance our knowledge in this line of research by determining whether the language in which a document is published is a positioning factor in the Google Scholar relevance ranking algorithm. Here, we employ a reverse engineering research methodology based on a statistical analysis that uses Spearman’s correlation coefficient. The results obtained point to a bias in multilingual searches conducted in Google Scholar with documents published in languages other than in English being systematically relegated to positions that make them virtually invisible. This finding has important repercussions, both for conducting searches and for optimizing positioning in Google Scholar, being especially critical for articles on subjects that are expressed in the same way in English and other languages, the case, for example, of trademarks, chemical compounds, industrial products, acronyms, drugs, diseases, etc.