Screening for in vitro systematic reviews: a comparison of screening methods and training of a machine learning classifier.

OBJECTIVE: Existing strategies to identify relevant studies for systematic review may not perform equally well across research domains. We compare four approaches based on either human or automated screening of either title and abstract or full text, and report the training of a machine learning algorithm to identify in vitro studies from bibliographic records. METHODS: We used a systematic review of oxygen-glucose deprivation (OGD) in PC-12 cells to compare approaches. For human screening, two reviewers independently screened studies based on title and abstract or full text, with disagreements reconciled by a third. For automated screening, we applied text mining to either title and abstract or full text. We trained a machine learning algorithm with decisions from 2000 randomly selected PubMed Central records enriched with a dataset of known in vitro studies. RESULTS: Full-text approaches performed best, with human (sensitivity: 0.990, specificity: 1.000 and precision: 0.994) outperforming text mining (sensitivity: 0.972, specificity: 0.980 and precision: 0.764). For title and abstract, text mining (sensitivity: 0.890, specificity: 0.995 and precision: 0.922) outperformed human screening (sensitivity: 0.862, specificity: 0.998 and precision: 0.975). At our target sensitivity of 95% the algorithm performed with specificity of 0.850 and precision of 0.700. CONCLUSION: In this in vitro systematic review, human screening based on title and abstract erroneously excluded 14% of relevant studies, perhaps because title and abstract provide an incomplete description of methods used. Our algorithm might be used as a first selection phase in in vitro systematic reviews to limit the extent of full text screening required.

Child labor and associated risk factors in the wake of the COVID-19 pandemic: a scoping review.

Child labor can significantly impact the health, welfare, and development of children engaged in labor. The spread of child labor around the globe is predicted to accelerate as a consequence of the COVID-19 pandemic. To this end, a scoping review was conducted to (a) synthesize emerging themes and results from recent research on child labor during the COVID-19 pandemic, (b) identify factors that increase the risk of children falling into child labor and (c) provide recommendations that can inform the development of policies and programs to ensure that previous efforts to combat child labor are not lost. Six electronic databases (Medline, EMBASE, Scopus, CINAHL, Global health, and Web of Science) were searched on January 21, 2022. The database searches, along with the grey literature search, identified 5,244 studies, of which 45 articles were included in the final review. Several of those articles (8 of 45 articles) reviewed concluded that the pandemic could increase child labor worldwide including the worst forms of child labor. The reviewed studies identified primary risk factors for child labor during the COVID-19 pandemic including economic challenges, temporary school closure and a greater demand for child labor, mortality among parents, and limited social protection. This scoping review identified the need for more field research on child labor following the COVID-19 pandemic to detect emerging patterns of child labor and to develop effective intervention measures. There is also a need for further empirical research on the consequences of the COVID-19 pandemic on gender differences in occupational exposure and health outcomes among working children and marginalized groups such as migrants, refugees, and minority groups. Based on the conclusions drawn from this review, it is evident that addressing child labor in the wake of the pandemic necessitates a multi-sectoral response by the government, businesses, civil society, and funding/donor agencies. This response should address various areas such as education, social and child protection, and legislation to support vulnerable children and their families in order to combat child labor subsequent to the pandemic.

Meta-analysis on reporting practices as a source of heterogeneity in in vitro cancer research.

Objectives: Heterogeneity of results of exact same research experiments oppose a significant socioeconomic burden. Insufficient methodological reporting is likely to be one of the contributors to results heterogeneity; however, little knowledge on reporting habits of in vitro cancer research and their effects on results reproducibility is available. Exemplified by a commonly performed in vitro assay, we aim to fill this knowledge gap and to derive recommendations necessary for reproducible, robust and translational preclinical science. Methods: Here, we use systematic review to describe reporting practices in in vitro glioblastoma research using the Uppsala-87 Malignant Glioma (U-87 MG) cell line and perform multilevel random-effects meta-analysis followed by meta-regression to explore sources of heterogeneity within that literature, and any associations between reporting characteristics and reported findings. Literature that includes experiments measuring the effect of temozolomide on the viability of U-87 MG cells is searched on three databases (Embase, PubMed and Web of Science). Results: In 137 identified articles, the methodological reporting is incomplete, for example, medium glucose level and cell density are reported in only 21.2% and 16.8% of the articles. After adjustments for different drug concentrations and treatment durations, the results heterogeneity across the studies (I2=68.5%) is concerningly large. Differences in culture medium glucose level are a driver of this heterogeneity. However, infrequent reporting of most experimental parameters limits the analysis of reproducibility moderating parameters. Conclusions: Our results further support the ongoing efforts of establishing consensus reporting practices to elevate durability of results. By doing so, this work can raise awareness of how stricter reporting may help to improve the frequency of successful translation of preclinical results into human application. The authors received no specific funding for this work. A preregistered protocol is available at the Open Science Framework (https://osf.io/9k3dq).

Double jeopardy: assessing the association between internal displacement, housing quality and chronic illness in a low-income neighborhood.

PURPOSE: This study analyzed associations between war-related internal displacement, housing quality and the prevalence of chronic illness in Nabaa, a low-income neighborhood on the outskirts of Beirut, Lebanon. METHODS: A cross-sectional survey of sociodemographics, household characteristics and health conditions of the study population was carried out in 2002. Using a structured questionnaire, the research team surveyed 1,151 households representing 4,987 residents of all ages. The survey was administered to a proxy respondent from each household in face-to-face interviews. A multiple logistic regression model using the generalized estimation equation method was constructed to assess the simultaneous effect of displacement and housing quality on reported ill health, while adjusting for potential confounders. RESULTS: Housing quality and internal displacement were strongly associated with occurrences of chronic illness. The most vulnerable respondents were older residents, females and internally displaced people, who reported high rates of chronic illnesses. Residents with high levels of education were less likely to report a chronic illness than those that had elementary education or less. CONCLUSION: Nabaa residents' experience of poor health was associated with inadequate housing quality. Moreover, residents who have been displaced experience worse living conditions and were more likely to experience poor health than those who were not displaced. These results reveal a need for policies to improve housing quality and alleviate war-related consequences in low-income neighborhoods.

Climate change and health research in the Eastern Mediterranean Region.

Anthropologically induced climate change, caused by an increased concentration of greenhouse gases in the atmosphere, is an emerging threat to human health. Consequences of climate change may affect the prevalence of various diseases and environmental and social maladies that affect population health. In this article, we reviewed the literature on climate change and health in the Eastern Mediterranean Region. This region already faces numerous humanitarian crises, from conflicts to natural hazards and a high burden of disease. Climate change is likely to aggravate these emergencies, necessitating a strengthening of health systems and capacities in the region. However, the existing literature on climate change from the region is sparse and informational gaps stand in the way of regional preparedness and adaptation. Further research is needed to assess climatic changes and related health impacts in the Eastern Mediterranean Region. Such knowledge will allow countries to identify preparedness vulnerabilities, evaluate capacity to adapt to climate change, and develop adaptation strategies to allay the health impacts of climate change.