OBJECTIVE: Different tools to assess the potential risk of bias (RoB) for cross-sectional studies have been developed, but it is unclear whether all pertinent bias concepts are addressed. We aimed to identify RoB concepts applicable to cross-sectional research validity and to explore coverage for each in existing appraisal tools.
METHODS: This scoping review followed the Joanna Briggs Institute methodology. We included records of any study design describing or reporting methods, concepts or tools used to consider RoB in health research reported to be descriptive/prevalence survey or analytic/association (cross-sectional) study designs. Synthesis included quantitative and qualitative analysis.
RESULTS: Of the 4556 records screened, 90 were selected for inclusion; 67 (74%) described the development of, or validation process for, appraisal tools, 15 (17%) described methodological content or theory relevant to RoB for cross-sectional studies and 8 (9%) records of methodological systematic reviews. Review of methodological reports identified important RoB concepts for both descriptive/prevalence and analytic/association studies. Tools identified (n = 64 unique tools) were either intended to appraise quality or assess RoB in multiple study designs including cross-sectional studies (n = 21; 33%) or cross-sectional designs alone (n = 43; 67%). Several existing tools were modified (n = 17; 27%) for application to cross-sectional studies. The RoB items most frequently addressed in the RoB tools were validity and reliability of the exposure (53%) or outcome (65%) measurement and representativeness of the study population (59%). Most tools did not consider nonresponse or missingness appropriately or at all.
CONCLUSIONS: Assessing cross-sectional studies involve unique RoB considerations. We identified RoB tools designed for broad applicability across various study designs as well as those specifically tailored for cross-sectional studies. However, none of the identified tools comprehensively address all potential biases pertinent to cross-sectional studies. Our findings indicate a need for continued improvement of RoB tools and suggest that the development of context-specific or more precise tools for this study design may be necessary.

OBJECTIVE: The aim of this study was to review hospital-based health information system (HIS) studies that used qualitative research methods and evaluate their methodological contexts and implications. In addition, we propose practical guidelines for HIS researchers who plan to use qualitative research methods.
METHODS: We collected papers published from 2012 to 2022 by searching the PubMed and CINAHL databases. As search keywords, we used specific system terms related to HISs, such as \"electronic medical records\" and \"clinical decision support systems,\" linked with their operational terms, such as \"implementation\" and \"adaptation,\" and qualitative methodological terms such as \"observation\" and \"in-depth interview.\" We finally selected 74 studies that met this review\'s inclusion criteria and conducted an analytical review of the selected studies.
RESULTS: We analyzed the selected articles according to the following four points: the general characteristics of the selected articles; research design; participant sampling, identification, and recruitment; and data collection, processing, and analysis. This review found methodologically problematic issues regarding researchers\' reflections, participant sampling methods and research accessibility, and data management.
CONCLUSIONS: Reports on the qualitative research process should include descriptions of researchers\' reflections and ethical considerations, which are meaningful for strengthening the rigor and credibility of qualitative research. Based on these discussions, we suggest guidance for conducting ethical, feasible, and reliable qualitative research on HISs in hospital settings.

Despite decades of social epidemiologic research, health inequities remain pervasive and ubiquitous in Canada and elsewhere. One reason may be our use of socioeconomic measurement, which has often relied on single point-in-time exposures. To explore the extent to which researchers have incorporated dynamic socioeconomic measurement into cardiovascular health outcome evaluations, we performed a narrative review. We estimated the prevalence of socioeconomic longitudinal cardiovascular research studies that identified socioeconomic exposures at 2 or more points in time between the years of 2019 and 2023. We defined cardiovascular outcome studies as those that examined coronary artery disease, myocardial infarction, acute coronary syndrome, stroke, heart failure, cardiac arrhythmias, cardiac death, cardiometabolic factors, transient ischemic attacks, peripheral artery disease, or hypertension. Socioeconomic exposures included individual income, neighbourhood income, intergenerational social mobility, education, occupation, insurance status, and economic security. Seven percent of socioeconomic cardiovascular outcome studies have measured socioeconomic status at 2 or more points in time throughout the follow-up period, hypothesized mechanisms by which dynamic socioeconomic measures affected outcome focused on social mobility, accumulation, and critical period theories. Insights, implications, and future directions are discussed, in which we highlight ways in which postal code data can be better used methodologically as a dynamic socioeconomic measure. Future research must incorporate dynamic socioeconomic measurement to better inform root causes, interventions, and health-system designs if health equity is to be improved.

The results of years of dental study serve as the foundation for the practise of medicine and, for that matter, dentistry. Doctors may have their own preferences for techniques and materials, but whether directly or indirectly, their decisions are influenced by systematic reviews and meta-analyses. However, due to poorly conducted or presented research, this very basic foundation may not be reliable. Bias in research is one of several factors that might make study results or research itself unreliable. Bias can be introduced into research at many stages, deliberately or unknowingly. Bias can appear at any point during the research process, even before the study itself begins. There are many biases in research, but some of them are more relevant to dentistry research than others. Because it is said that \"eyes see what the mind knows\", it is essential to have a complete understanding of the different types of bias, how and when they get entrenched, and what steps may be taken to prevent or lessen them if they do occur. This comprehensive summary of bias in dentistry research is provided by this synoptic review. The goal is to identify gaps and measures that have been taken-or that should have been taken-by providing both descriptive and evaluative summaries, as well as examples from the literature, when needed.

Understanding barriers to abortion care is particularly important post-Dobbs. However, many abortion access studies recruit from abortion-providing facilities, which overlook individuals who do not present for clinic-based care. To our knowledge, no studies have reviewed research recruitment strategies in the literature or considered how they might affect our knowledge of abortion barriers. We aimed to identify populations included and sampling methods used in studies of abortion barriers in the United States.
We used a scoping review protocol to search five databases for articles examining US-based individuals\' experiences accessing abortion. We included English-language articles published between January 2011 and February 2022. For included studies, we identified the sampling strategy and population recruited.
Our search produced 2763 articles, of which 71 met inclusion criteria. Half of the included papers recruited participants at abortion-providing facilities (n = 35), while the remainder recruited from online sources (n = 14), other health clinics (n = 10), professional organizations (n = 8), abortion funds (n = 2), community organizations (n = 2), key informants (n = 2), and an abortion storytelling project (n = 1). Most articles (n = 61) reported information from people discussing their own abortions; the rest asked nonabortion seekers (e.g., physicians, genetic counselors, attorneys) about barriers to care.
Studies of abortion barriers enroll participants from a range of venues, but the majority recruit people who obtained abortions, and half recruit from abortion clinics.
As abortion access becomes constrained and criminalized in the post-Roe context, our findings indicate how investigators might recruit study participants from a variety of settings to fully understand the abortion seeking experience.

OBJECTIVE: To determine the intermethod agreement of self-reported vs. register data of \'sickness absence\' (SA) and \'return to work\' (RTW) outcome measurements.
METHODS: We conducted a systematic review and a meta-analysis of studies reporting mean differences (MDs) and sensitivity and specificity for self-report vs. register data and an inductive analysis of the self-report question formulations. An information specialist searched Medline, Embase, PsycINFO for studies published from inception to November 2022. Screening and data extraction was done by two authors independently.
RESULTS: Twenty-three studies were included of which eighteen with an overall high risk of bias. Self-reports had a pooled MD of 1.84 SA days (95% confidence interval [CI] 0.26-3.41, I2 98%, 18 studies, 38,716 participants) compared to registries which varied among studies from 204 more to 17 days less. The median average sick leave in studies in the self-report group was 8 days (interquartile range 4-23 days). Being absent from work measured with self-report had a sensitivity of 0.83 (0.76-0.88 95% CI) and a specificity of 0.92 (0.88-0.94 95% CI) compared to registry data. The high heterogeneity amongst the studies could not be explained by recall time, gender, register type, prospective or retrospective self-reports, health problem, SA at baseline or risk of bias. Studies lacked standard outcome reporting, had unclearly formulated questions in self-reports and there was little information on the registers\' quality.
CONCLUSIONS: Current self-reports may differ from register-based absence data but in an inconsistent way. Due to inconsistency and high risk of bias the evidence is judged to be of very low certainty. Further research is needed to develop clear standard questions which can be used for SA and RTW self-reports. Quality of registers needs to be better evaluated. Percentage positive and negative agreement, MDs and 2 × 2 tables should be reported for studies investigating agreement between SA and RTW outcome measures.

Microbially influenced concrete corrosion (MICC) causes substantial financial losses to modern societies. Concrete corrosion with various environmental factors has been studied extensively over several decades. With the enhancement of public awareness on the environmental and economic impacts of microbial corrosion, MICC draws increasingly public attention. In this review, the roles of various microbial communities on MICC and corresponding protective measures against MICC are described. Also, the current status and research methodology of MICC are discussed. Thus, this review aims at providing insight into MICC and its mechanisms as well as the development of protection possibilities.

Wikipedia is an open-source online encyclopedia and one of the most-read sources of online health information. Likewise, Wikipedia page views have also been analyzed to inform public health services and policies. The present review analyzed 29 studies utilizing Wikipedia page views for health research. Most reviewed studies were published in recent years and emanated from high-income countries. Together with Wikipedia page views, most studies also used data from other internet sources, such as Google, Twitter, YouTube, and Reddit. The reviewed studies also explored various non-communicable diseases, infectious diseases, and health interventions to describe changes in the utilization of online health information from Wikipedia, to examine the effect of public events on public interest and information usage about health-related Wikipedia pages, to estimate and predict the incidence and prevalence of diseases, to predict data from other internet data sources, to evaluate the effectiveness of health education activities, and to explore the evolution of a health topic. Given some of the limitations in replicating some of the reviewed studies, future research can specify the specific Wikipedia page or pages analyzed, the language of the Wikipedia pages examined, dates of data collection, dates explored, type of data, and whether page views were limited to Internet users and whether web crawlers and redirects to the Wikipedia page were included. Future research can also explore public interest in other commonly read health topics available in Wikipedia, develop Wikipedia-based models that can be used to predict disease incidence and improve Wikipedia-based health education activities.

Frailty, neurodegeneration and geriatric syndromes cause a significant impact at the clinical, social, and economic level, mainly in the context of the aging world. Recently, Information and Communication Technologies (ICTs), virtual reality tools, and machine learning models have been increasingly applied to the care of older patients to improve diagnosis, prognosis, and interventions. However, so far, the methodological limitations of studies in this field have prevented to generalize data to real-word. This review systematically overviews the research designs used by studies applying technologies for the assessment and treatment of aging-related syndromes in older people.
Following the PRISMA guidelines, records from PubMed, EMBASE, and Web of Science were systematically screened to select original articles in which interventional or observational designs were used to study technologies\' applications in samples of frail, comorbid, or multimorbid patients.
Thirty-four articles met the inclusion criteria. Most of the studies used diagnostic accuracy designs to test assessment procedures or retrospective cohort designs to build predictive models. A minority were randomized or non-randomized interventional studies. Quality evaluation revealed a high risk of bias for observational studies, while a low risk of bias for interventional studies.
The majority of the reviewed articles use an observational design mainly to study diagnostic procedures and suffer from a high risk of bias. The scarce presence of methodologically robust interventional studies may suggest that the field is in its infancy. Methodological considerations will be presented on how to standardize procedures and research quality in this field.

Two deprescribing search filters for MEDLINE and one deprescribing search filter for Embase have been recently developed, including objectively developed search filters. The objective of this case study was to implement these three deprescribing search filters in systematic review (SR) search strategies and to assess their effect on performances. SR that independently developed original search strategies (OSS) were selected. The deprescribing filters were implemented in each OSS, generating two implemented search strategies (ISS1 and ISS2) in MEDLINE and one ISS (ISS3) in Embase. OSS were re-run on the same date as ISS. The performances of ISS and OSS were calculated and compared. Two SR were included (SR1 and SR2). For MEDLINE, SR1 included 12 articles. The sensitivity was 50% for OSS, 58% for ISS1 and 42% for ISS2. SR2 included four articles. The sensitivity of OSS, ISS 1 and 2 was 25%. For Embase, SR1 included 12 articles. The sensitivity was 33% for OSS and 58% for ISS3. SR2 included four articles. None of the four included articles were retrieved with OSS or ISS3. While sensitivity of OSS was moderate, the objectively developed deprescribing filters maintained or slightly improved this sensitivity when implementing.