Approximately 230 million children under 5 years old of age suffer from malnutrition and over half of the children below 5 years old deaths are due to malnutrition nowadays. To gain a better understanding of this problem, the application of spatial analysis has risen exponentially in recent years. In this review, the present state of information on the use of spatial analysis in childhood malnutrition studies was evaluated using four databases of digital scientific journals: ScienceDirect, Scopus, PubMed and CINAHL. We chose 2,278 articles from the search results and a total of 27 articles met our criteria for review. The following information was extracted from each article: objective of study, study area, types of malnutrition, subject, data sources, computer software packages, spatial analysis and factors associated with childhood malnutrition. A total of 10 spatial analysis methods were reported in the reviewed articles and the Bayesian geoadditive regression model was the most common method applied in childhood malnutrition studies. This review highlights the importance of the application of spatial analysis in determining the geographic distribution of malnutrition cases, hotspot areas and risk factors correlated with childhood malnutrition. It also provides implications for strategic initiatives to eradicate all forms of malnutrition. Malnutrition is a complicated issue that is believed to cause more than one-third of all mortality, despite the fact that it is rarely mentioned as the primary cause . UndernuMalnutrition in children is caused by a variety of factors. Poverty has typically been the leading cause of childhood malnutrition . Other fNowadays, the availability of updated satellite imagery and internet data, as well as the usability of geographic information system (GIS) applications, allows for faster innovation and development . GIS proA review article on the implementation of spatial analysis in childhood malnutrition exploration was carried out by Marx et al. . HoweverThe primary objectives of this review were to: i) analyse the use of spatial analysis methods in the studies of the geographic variation of childhood malnutrition and its potential factors; ii) synthesise the spatial analysis methods of the selected studies and separate the methods into three categories: spatial regression model, spatial autocorrelation/clustering and spatial interpolation and iii) evaluate the benefits and disadvantages of using spatial analysis methods in childhood malnutrition studies. The following questions were posed for this review: i) What spatial analysis methods have been used to analyse childhood malnutrition? ii) What spatial analysis method is frequently used in childhood malnutrition studies? iii) What are the benefits and disadvantages of spatial analysis in childhood malnutrition studies? The findings from this review will make a significant contribution to the production of information that can be used to develop policies that improve children’s nutrition security. Furthermore, insights into strategic interventions to eradicate all forms of childhood malnutrition can be obtained. To make the review coherent, we structured it to contain some background information, an objective, a summary of datasets and eligibility, results, discussion and conclusion.The Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) were utilised for this review . PRISMA-The systematic search of the present study was conducted on four digital scientific journal databases: ScienceDirect, Scopus, PubMed and CINAHL (EBSCO host interface).The following terms were used to identify related articles in conjunction with keyword searches: ‘spatial’ OR ‘geographic information system’ OR ‘mapping’ AND ‘childhood malnutrition’. The terms were paired with the logical OR operator, while the logical AND operator was used to merge the two terms. Only articles conducting spatial analysis methods to discuss childhood malnutrition were identified as relevant to this review.The articles were chosen for evaluation if they met the requirements for inclusion criteria. The first criterion was the literature type, with the researchers deciding to concentrate solely on journals (research articles) because they served as a primary source of empirical data. As a result, a systematic review, review, meta-analysis, meta-synthesis, book series, books, book chapters and conference proceedings were excluded from this study. This review only included research articles published in English between January 2010 and March 2020. Research articles that have not explicitly reported spatial analysis applications in childhood malnutrition studies were removed from this review.The titles, abstracts and contents of all articles were fully reviewed to verify that they met the inclusion criteria and were appropriate for use in the current study to meet the objectives. In the first stage, the selection of articles was carried out independently by three reviewers by screening the titles after the database search. The purpose of this stage was to remove duplicate articles. If either of them decided the title of an article was relevant, the article was included—otherwise, the article was excluded. All selected articles were subjected to abstract screening in the second stage. The reviewers must agree to include an article based on the defined relevance criteria during this stage. Any disagreements were resolved by discussion and consensus among all reviewers. When the abstracts of articles could not be presented as relevant or irrelevant, their full-text articles were retrieved for additional review. The full-text articles that met the inclusion criteria were further evaluated and information was retrieved from each article.Information from each of the selected articles, such as the objective of the study, study area, types of childhood malnutrition, subject of the study, data sources, computer software packages, spatial analysis (method) and factors associated with childhood malnutrition, was extracted using Microsoft Excel. Then, we further distinguished the spatial analysis methods used in the selected articles into the categories of: i) spatial regression model; ii) spatial autocorrelation/clustering and iii) spatial interpolation. The frequency of each spatial analysis used was tabulated in a table. It should be noted that many types of spatial analysis might be applied in a study.n = 19). Thus, a total of 27 relevant articles  were selected in this review. Our initial search in the ScienceDirect database yielded 644 articles, the Scopus database yielded 419 articles, the PubMed database yielded 34 articles and the CINAHL database yielded 1,178 articles. A total of 2,278 articles were listed, of which 1,912 articles were chosen based on research articles. A total of 1,819 articles were removed based on their title (title screening) and 18 duplicates were removed at the screening stage. In the second stage, 75 abstracts of articles were reviewed and only 46 articles were selected for full-text review. After reviewing the full text for each of the articles, we excluded all articles that did not use the spatial analysis method and did not focus on childhood malnutrition issues  had a research objective containing geographical terms such as distribution, spatial or geographical variability, spatial clustering, and regional differences. All the studies selected for this review were conducted in developing countries . More than half of the studies  were conducted in African countries  studied child stunting           , 35, 37,, 33.3%) , 37, 39,, 22.2%) , 39, 40 , 11.1%) , 39, 40..1%) n = , 85.2%  –39, 41, 1, 3.7%) , one stu1, 3.7%) , one stun = 15, 55.6%)           , 40, 41,, 14.8%) , 22, 37,2, 7.4%) , 32, two2, 7.4%) , 34, two2, 7.4%) , 28, one1, 3.7%) , one stu1, 3.7%) , one stu1, 3.7%)  and one 1, 3.7%) .n = 6, 22.2%)      (R-INLA) packages  , WinBUGS , SaTScan , BayesX  and QGIS . Four articles did not mention the computer software packages they used in their studies .Climate data  was used by six studies , 22.2%) , 32, 33,, 14.8%) , 32, 33,, 11.1%) , 29, 32,2, 7.4%) , 32 and 2, 7.4%) , 35. For, 33.3%) , with fopackages . The sec.2% , 32,, 29.6%) , 39, 40,The spatial analysis used in childhood malnutrition studies by the selected articles is presented in n = 11, 40.7%)     , 37, 41., 14.8%) , 22, 33,, 11.1%) , 18, 22 2, 7.4%) , 22.n = 10, 37.0%)      –28, 38. , 18.5%) , 25, 38., 11.1%) , 39, 40,, 11.1%) , 30, 35 2, 7.4%) , 27.n = 2, 7.4%)  , 33. In 2, 7.4%) , the span = 27) implies that spatial analysis is still new to childhood malnutrition studies. However, considering that spatial analysis is still rarely used in the field of childhood malnutrition, this result is not surprising.In our search of more than 10 years (January 2010–March 2020) of research articles on childhood malnutrition studies, we found that only 27 studies used spatial analysis in their studies. This might be connected to the particular search strategy. We aimed to eliminate false positives, as is the norm in systematic reviews, by choosing search words that were sensitive but not specific. The inclusion of all articles resulted in a vast number of impractical studies, with only a few articles appearing to be relevant. Since we may have overlooked a few articles in this review, we concluded that the specificity of the study did not significantly alter our findings. The small number of chosen articles  from the median height-for-age value of the WHO Child Growth Standards in 2013 , 31.In public health research, GIS methods are applied in several ways. Spatial data exploration and visualisation are two of the most function of GIS. This review has demonstrated several spatial analysis methods used in childhood malnutrition studies. The Bayesian geoadditive regression model is the most commonly used to investigate the spatial dimension of childhood malnutrition. This method was predominantly used because it promotes the calculation of the conditional association between the state of childhood malnutrition and spatial dependency within the country and across regions . The finOther methods of spatial regression models, such as OLS, SLM and SEM regression, have also been applied by several studies to deepen knowledge of the spatial aspect of childhood malnutrition. The fundamental principle of SLM is that the results of the dependent variables are influenced in the neighbourhood areas, whereas SEM is used to assess the influence of certain variables that are not present in the regression model but have an impact on the output variables. The primary difference between the two models is that, unlike SEM, SLM does not include spatial dependency in the error term. A study by Khan and Mohanty  found thThe spatial autocorrelation/clustering is a method for determining the existence and absence of non-random spatial patterns in a study area. These approaches, also known as hotspot analysis, yield estimates disaggregated to the spatial unit level to characterise significantly autocorrelated local areas. In this review, this method was used by the selected articles to identify areas where childhood malnutrition cases are higher or lower than expected under the assumption that childhood malnutrition cases are uniformly distributed spatially. If the cases are not random, this method helps identify significant spatial clusters. Applying this analysis to childhood malnutrition studies can facilitate improved regional targeting by stratifying areas of higher risks and identifying physical locations that are important for the design of nutrition intervention programmes in target regions . TargeteSpatial interpolation is a method of estimating values at an unsampled location using a network of known-valued points . The kriThe selected articles showed that many factors contribute to childhood malnutrition. The determinants of the nutritional condition of children can be classified into several factors, such as: i) proximate factors e.g. age of child, sex of child, birth size, insufficient food intake and infection; ii) distal factors e.g. sociocultural, economic, environmental and climatic variables; and iii) intermediate factors e.g. wealth index, mothers’ ethnicity and level of education of mother and father. Depending on geographical and climatic conditions and anthropogenic influences, these factors are believed to differ temporally and spatially . TherefoThe potential drawbacks of this review are the omission of non-English articles and limited search terms, which could have contributed to the unintended exclusion of studies. This review was dominated by cross-sectional studies. This suggests that the study focused on data collected at a particular point in time, making it difficult to discover patterns in childhood malnutrition status over time. The cross-sectional studies are efficient, inexpensive and simple to conduct; however, they may cause the researcher to be biased in their depiction of the result, which may impact secondary data . A longiMany studies have conducted various spatial analysis methods by combining national and regional childhood malnutrition data and attempts have been made to illustrate the geographic distribution of childhood malnutrition using a map. The methodological strength of such studies spans from mapping and advance statistical spatial analyses through the identification of environmental and other geographical factors on childhood malnutrition. As a result, researchers, policymakers and programme managers have acknowledged location as a crucial determinant of population and health outcomes. This is especially true in the case of childhood malnutrition, which can be impacted by geographical, cultural and environmental factors. According to the findings of this review, the application of spatial analysis methods in childhood malnutrition research is important for understanding the geographic distribution of malnutrition cases, hotspot areas and risk factors associated with childhood malnutrition. To assist the government, policymakers and other authorities in implementing strategies and designing intervention programmes in high-risk areas to reduce malnutrition in children throughout the world, it is necessary to evaluate and understand the geographical distribution of childhood malnutrition cases.


In recent years, female drinking has been on the rise worldwide, and this trend can be observed in Korea as well. Accordingly, this study aimed to examine the heterogeneous longitudinal changes in drinking patterns among Korean women, while also exploring the determinants of these changes. In particular, the study identified the gender perspective-related determinants of the classified patterns of problem drinking.Data on 4615 adult women who participated in the Korea Welfare Panel Study (KOWEPS) for 3 years (2018–2020) were analyzed longitudinally using SPSS Statistics 22.0 and M-plus 7.0. The changes in female drinking patterns were analyzed using latent class growth analysis. Subsequently, multinomial logistic regression analysis was performed to identify the predictive factors affecting the changes in drinking patterns.p < .05) and higher levels of satisfaction with social relationships  increased the probability of belonging to the “moderate problem drinking/maintained” group compared to the low problem drinking/decreased class; ii) in the “high problem drinking/increased” class, relative to the low problem drinking/decreased class, experience of domestic violence , work–family balance stress , and gender role perception  were significant predictors of drinking behavior.Latent class analysis yielded three classes: “low problem drinking/decreased,” “moderate problem drinking/maintained,” and “high problem drinking/increased.” Of the participants, 80.4% were in the first class, 14.5% in the second, and 5.1% in the third. After controlling for sociodemographic and psychosocial factors, we found: i) domestic violence, work–family balance stress, and gender role perception were not statistically significant for the “moderate problem drinking/maintained” class; lower levels of depression (odds ratio; OR = .750, Problem drinking in Korean women demonstrated heterogeneous patterns of change, with gender-specific factors being the main predictors of this change. Therefore, this study developed a strategy for reducing the harmful effects of female drinking, which considers the characteristics of the changes in women’s drinking patterns as well as factors from the gender perspective. While there has been a general decline in alcohol consumption in many countries in recent years, an increasing trend of hazardous drinking behaviors, such as high-risk drinking and binge drinking, has been noted among women and youth , 2. TradThis rising rate of female drinking is evident in Korea as well. While the rate of male drinking dropped slightly from 21.4 to 20.8% in 2019, female drinking rates rose sharply from 5.4 to 8.4% during the same period [The discussion over problem drinking has been primarily focused on men. Recently, however, there has been an increased interest in the gender differences in the prevalence, clinical characteristics, biological vulnerability, and course of treatment , 6. As wStudies thus far have noted differences between men and women in terms of the biological impact of alcohol consumption and drinking predictors . For exaMeanwhile, some scholars have argued that the perspective of gender is necessary to pinpoint the underlying causes of increased drinking among women accurately. This necessity is accentuated considering compositional and social contextual characteristics such as gender roles and norms that have changed over time, , 9, 16. However, previous studies have a limitation in that they are mainly described based on demographic variables , 32, 33.Traditionally, it has been accepted that culturally defined gender roles shape male and female drinking patterns , 35. SomProblem drinking involves cumulative and continuous drinking, which has harmful consequences. As drinking is a type of social behavior , for an Therefore, this study aims to identify the types of longitudinal changes in female drinking behaviors and explores their characteristics. It also seeks to investigate the effects of gender-related experiences of women arising from the social structure—domestic violence, work–family balance stress, and perceived gender roles—on the types of longitudinal changes in their drinking. Based on our findings, we present clinical and policy directions to reduce the negative effects of problem drinking behaviors in women.https://www.koweps.re.kr). Especially, the KOWEPS provides representative and reliable data for longitudinal research [We used secondary sources of data of 4615 adult women collected during the 13th–15th (2018–2020) Korea Welfare Panel Study (KOWEPS) for our analysis. The KOWEPS, conducted by the Korean Institute of Social and Health Affairs in conjunction with the Social Welfare Research Institute of Seoul National University, is an ongoing National Approval Statistics (No. 33109) of nationally representative Korean households. The purpose of this panel survey was to dynamically identify the socio-economic characteristics of the population and the multidimensional changes in living situation amid social change, and to investigate the welfare needs of each population group, ultimately contributing to the formation of welfare policies. Surveys were conducted by trained individuals in the form of face-to-face interviews at the participants’ homes using structured questionnaires. The survey is repeated annually, and proportional systematic stratified cluster sampling was used to select participants. Further details of the sampling design, methods and data sets can be found on the relevant website —a 10-item screening test developed by the World Health Organization. Each item is rated on a five-point Likert scale, with the total score ranging from 0 to 40. This scale is interpreted based on a cut-off, with an AUDIT score of 6 or higher indicating hazardous alcohol consumption in women, and a score of 10 or higher indicating alcohol use disorder. However, the total score is sometimes interpreted based on a continuum of scores. A higher score indicated a higher level of problem drinking and a higher risk of engaging in hazardous drinking behaviors.Experience of domestic violence was measured using three items: “insulting and malicious words,” “threat of physical violence,” and “direct infliction of physical violence.” The items were rated on a scale of 0 (“never”) to 3 (“more than 6 times”). The total score was determined by summing the individual scores. A higher score indicates more experience of domestic violence.We used eight modified items  from theGender role values were measured using two items from the ISSP instrument : “Men’s Depression was measured using the Center for Epidemiologic Studies Depression Scale (CES-D). The scale, which was developed for easy measurement of depression in the general population, is widely used in research, both in Korea and other countries. The 11-item scale  is a self-report questionnaire for measuring individuals’ psychological attitudes and behaviors; generally, a higher total score indicates more severe depression. For this study, we used the total score as a continuous variable.The degree of satisfaction with social relationships was measured using a five-point Likert scale, with a higher score indicating greater satisfaction with social relationships.Sociodemographic factors include age, religion, education level, employment status (economic activity status), presence of a spouse, and  income. For this study, age and education level were used as continuous variables, and religion, presence of a spouse, and employment status were used as dummy variables . Equivalized income was analyzed as a natural logarithm (ln) to ensure the normality of the data.The data were analyzed using SPSS Statistics 22.0 and M-plus 8.0 software. First, the general characteristics and main variables were analyzed using frequencies and descriptive statistics. Second, the patterns of changes in drinking level among women were analyzed using latent class growth analysis (LCGA). Latent growth modeling—the primary method of analysis chosen by existing longitudinal research—assumes that the study population undergoes an equal pattern of change. Therefore, it cannot detect the different trends of changes within the population. Conversely, the LCGA, a type of growth mixture modeling, which we employed for this study, is useful for identifying latent classes—subsets that differ in their characteristics, such as baseline values or rates of change—and examining the growth patterns among individuals included in these heterogeneous classes , 50. TheIn LCGA, the heterogeneous growth trajectories are identified through statistical model fit testing. The commonly used fit indices are the Akaike information criterion (AIC), Bayesian information criterion (BIC), sample-size adjusted Bayesian information criterion (SSABIC), entropy, and Vuong-Lo-Mendell-Rubin likelihood ratio test (VLMR). In general, a model is determined to have a good fit when the AIC, BIC, and SSABIC values are smaller, entropy is close to 1, and VLMR is significant. Moreover, models with classes that include fewer than 5% of the samples can be excluded . These iTable Table The types of changes in female drinking according to the final model are presented in Table p < .05) and 1.257 times higher when they had higher satisfaction with social relationships . In terms of sociodemographic factors, the odds of being in the moderate level/maintained class, with reference to the low level/decreased class, were lower with advancing age  and absence of religious beliefs , and higher among the employed . Further, the odds of being in the “high level/increased” class were 1.857 times higher with more experience of domestic violence  and 1.309 times higher with higher levels of work–family conflict . In terms of perceived gender roles, the odds of being in the “high level/increased” class, with reference to the “low level/decreased” class, were .705 times lower with more conservative gender role perceptions . In terms of sociodemographic factors, the odds of being in the “high level/increased” class were lower with advancing age , absence of religious beliefs , and higher education level , and lower among the employed .First, to check for multicollinearity among the major variables, a correlation analysis was performed. The correlation coefficients were below 0.8 and ranged from .007–.636, In addition, the Variance Inflation Factor (VIF) between the independent variables was calculated to be less than ten, with a minimum of 1.042 and a maximum of 6.924, indicating that multicollinearity was not present. Next, multinomial logistic regression was performed to identify the factors pertaining to gender-related experiences in the social structure that could predict the types of longitudinal changes in female drinking. The results are shown in Table We examined the types of longitudinal changes in female drinking by analyzing 3 years of KOWEPS (2018–2020) data using LCGA and explored their features. We also identified the gender-related determinants of the different classes of changes in female drinking.First, three classes emerged in relation to changes in drinking patterns among women: “low level/decreased,” “moderate level/maintained,” and “high level/increased.” This confirms that there were heterogeneous changes in drinking patterns among women. With reference to the cut-off criteria for AUDIT scores, the “moderate level/maintained” group could be considered to engage in social drinking. Further, the “high level/increased” group demonstrated hazardous drinking behaviors at the baseline, but progressed to suspected alcohol use disorder over time, suggesting that they are a more risky drinking group compared to the other groups. These are different from previous longitudinal studies, which used the traditional potential growth model, in which only the pattern of decrease or increase over time was considered depending on the predictor , 54, 55.Second, after adjusting for sociodemographic factors  and psychosocial factors , which differ according to the types of changes in female drinking, we found: I) Gender-related factors were not significant for the “moderate level/maintained” class compared to other reference classes. However, depression and satisfaction with social relationships were significant predictors of drinking behavior. II) Unlike for the “moderate level/maintained” class, experience of domestic violence, work–family conflict, and perceived gender roles were identified as significant predictors in the “high level/increased” class. In other words, women with low levels of depression and high levels of satisfaction with social relationships were likely to be in the “moderate level/maintained” class, which engaged in a healthy and enjoyable level of drinking. Meanwhile, the odds of being in the “high level/increased class”—women engaging in hazardous drinking behaviors at the baseline and quickly progressing to suspected alcohol use disorder (addiction) over time—were higher among women with more experience of domestic violence, higher work–family conflict, and more open gender role perceptions. This supports previous findings that women victims of domestic violence frequently experience substance use disorder , 57, womIn particular, it is noteworthy that, as per the traditional gender roles in Korean society, women are perceived to place more value on family and are required to fulfill their duties as a spouse, parent, daughter-in-law, and daughter, all of which contribute to controlling their alcohol consumption. This can also be understood in terms of the association between gender role perceptions and work–family conflict. Considering reports that women with more traditional gender role perceptions face greater difficulties in becoming economically active , 62, it From a gender perspective, the highest odds ratios, or the highest likelihood, of a woman being in the ‘high-problem drinking/increased class’, were associated with experiences of domestic violence, followed by work-family balance stress and perceived gender roles, in that order. Its implications are as follows: First, the experience of domestic violence is a strong predictor of being in the “high level/increased” group, and individuals experiencing post-traumatic stress disorder seek to lower alertness  or relieSecond, there is a need for programs in the community and workplaces to promote mental health or coping skills that can help women cope with the stress caused by their heavy role in socio-economic activities and housework. In modern society, the increase in participation from women in socio-economic activities is a natural phenomenon. However, women still shoulder the burden of housework and childcare, the stress of which can be the most prevalent cause of drinking behavior in them. Additionally, women with a high level of work-family stress are likely to experience increasing levels of problem drinking, not only due to existing social perceptions of women’s problem drinking, but also the fact that their commitment to treatment is limited by their primary role of family care. Therefore, when designing a problem drinking prevention policy or a drinking problem intervention program for women, it is necessary to consider measures such as the inclusion of a work-family stress reduction program.Third, from the perspective of promoting women’s health, educational programs that improve social perceptions by separating women’s identity from gender role perceptions and programs that prevent problem drinking in women need to be developed. In terms of gender role attitudes (perceptions), society has traditionally been lenient toward male drinking, but relatively stricter toward female drinking . HoweverTaken together, the alcohol consumption of women has increased dramatically in recent years. The combination of the perception that drinking liberates women who have been socially oppressed for a long time, and the implicit social coercion of drinking being essential for smooth work and social life contributes to patterns of problem drinking in women in South Korea. On the other hand, the problem of female drinking due to domestic violence is not a phenomenon that can only be explained by demographic, socioeconomic, and psychological factors. Therefore, this study emphasizes that problem drinking in women should be addressed from a gender perspective, in terms of their vulnerability within existing social and cultural hierarchies, based on their experiences. Gender-conscious policies should be proposed to reduce the harm of problem drinking in women, such as prevention education, improvement of the drinking environment, policy development, preparation of research and monitoring systems, and the establishment of leadership to implement them.This study has several strengths. First, we shed light on the heterogeneous changes in drinking within the female population by not assuming that all women undergo the same changes in their drinking patterns over time. Second, we address the shortcomings of previous studies that have primarily examined sociodemographic, psychosocial, and relational factors as predictors of problem drinking in women. we analyze the effects of women’s gender-related experiences in the actual social structure on the longitudinal changes in their drinking patterns. This examination has enriched our discussion on female drinking from a gender perspective. However, the study is not without limitations. We could not examine gender gaps in the effects studied—we could not study how the gender perspective influences men. In addition, it was not possible to capture specific and minute changes of patterns by time point because we investigated patterns of change with data over 3 years, which is the minimum number of time points required for conducting a longitudinal study. Also, this study did not reflect the pattern of changes in independent variables, though they did exist. Finally, despite the change in social perceptions of women’s drinking, we are unable to rule out the possibility that respondents underreported their drinking due to pre-existing negative perceptions. Moreover, we believe that accounting for the limitations of our study and mapping gender differences and differences across generations (cohorts) within the female population would lead to more interesting findings.In recent years, the gender gap in the indices for alcohol use has narrowed, and alcohol consumption among women has increased. We identified three latent classes with different trajectories that reflect changing patterns in problem drinking. Furthermore, this study identified gender-specific predictors of the types of longitudinal changes in female drinking. Three classes of changes in female drinking emerged: “low problem drinking/decreased,” “moderate problem drinking/maintained,” and “high problem drinking/increased.” Gender-related factors in the social structure—experience of domestic violence, work–family conflict, and gender role perceptions—were identified as significant predictors of drinking only in the “high level/increased” group. These results highlight the need for interventions tailored to the specific classes of changes in female drinking patterns as opposed to a one-size-fits-all approach. They also show the necessity of formulating policies for reducing the harmful consequences of hazardous drinking in women by considering gender-related factors, such as domestic violence and work–family conflict.


Rosculus terrestris ECOP02 and/or Cerocomonas lenta ECOP01, on the survival of the inoculants Bacillus mycoides M2E15 (BM) or B. pumilus ECOB02 (BP). We also evaluated the impact of bacterial inoculation with or without protozoan addition on the abundance and diversity of native soil bacterial and protist communities. While the addition of both protozoa decreased the survival of BM, their presence contrarily increased the BP abundance. Protists’ selective predation governs the establishment of these bacterial inoculants via modifying the soil microbiome structure and the total bacterial abundance. In the BP experiment, the presence of the introduced protozoa altered the soil community structures and decreased soil bacterial abundance at the end of the experiment, favouring the invader survival. Meanwhile, the introduced protozoa did not modify the soil community structures in the BM experiment and reduced the BM + Protozoa inoculants’ effect on total soil bacterial abundance. Our study reinforces the view that, provided added protozoa do not feed preferentially on bacterial inoculants, their predatory behaviour can be used to steer the soil microbiome to improve the success of bacterial inoculations by reducing resource competition with the resident soil microbial communities.Protists’ selective predation of bacterial cells is an important regulator of soil microbiomes, which might influence the success of bacterial releases in soils. For instance, the survival and activity of introduced bacteria can be affected by selective grazing on resident communities or the inoculant, but this remains poorly understood. Here, we investigated the impact of the introduction in the soil of two protozoa species,  Global food demand will soon outpace global crop production , as the Recently, the use of protozoa as inoculants, alone or in parallel with bacterial inoculants, has been proposed for several purposes. First, the bacterivorous features of protozoa can lead to nutrient releases, given that protozoan C:N ratios are often higher than those of their bacterial prey . In the The combination of the plant beneficial effects of protozoan and bacterial inoculations might represent an interesting strategy to boost crop production. However, it is essential to evaluate to what extent the protozoa interfere with the survival of the introduced bacteria, either positively or negatively. Predation by protozoa is known to be often selective, i.e., it depends on the protozoan feeding mode and motility, the prey morphology  and chemical traits  . MoreoveRosculus terrestris ECOP02 (from now on referred to as Rosculus) and the free-swimming flagellate Cercomonas lenta ECOP01 (Cercomonas), for use in conjunction with the bacterial inoculants Bacillus mycoides M2E15 (from now on referred to as BM) or B. pumilus ECO-B-002 (BP). Each Bacillus strain was selected due to its ability to promote the plant growth, likely via phosphate solubilisation, iron acquisition, indole acetic acid and antimicrobial peptides  production Rosculus Acanthamoeba castellanii improved the survival of the inoculant Pseudomonas fluorescens [A previous study showed that added orescens . Howeverorescens  indicateRosculus and the flagellate Cercomonas used in this study have different morphotypes and volumes, driving the physical scope of their effects. The study found that protist cell volume could explain a significant portion of the predation effects. Another study revealed that the cell volumes of cercozoan species link to predation activity [Apparent differences were found between the BM and BP experiments. In the BM experiment, the microbial release did not change the structure of the bacterial and protist communities. However, in the BP experiment, each invader incited significant changes in the tested communities, although this depended on the time point and the type of invaded community  being examined. Thus, the impact is linked to the type of invader and the interaction between protozoan and bacterial inoculants. Indeed, Gao et al.  showed tactivity . Accordiactivity , 56. Moractivity , 35. It activity . HoweverWe also found that the addition of protozoa and bacteria led to a more substantial impact than the single-strain introduction of BP since the latter only temporarily affected the protist community structure. This may indicate that co-inoculation increases the magnitude of disturbance and selection pressure. A previous study suggested that the magnitude and frequency of a disturbance are key facets determining impact . MoreoveTaken altogether, our results show that top-down control by protists, through selective predation, can be used to steer the soil microbiome to improve the success of bacterial releases into the soil. However, we demonstrate that a positive effect of the added protozoa on the bacterial inoculant survival can sometimes be jeopardised by preferential feeding of these protozoa on the incoming bacteria. As the impact was dependent on the protozoan species, a systematic characterisation of their functional traits, their ecological behaviour  and feeding preferences of the protozoa are needed to predict better the consequences of their predation on the soil microbiome and introduced bacteria.Supplementary Information


As the reach of science content in traditional media declines, many institutions and scientists are turning to YouTube as a powerful tool for communicating directly with non-expert publics. They do so with little empirical social science research guiding their efforts. This study explores how video characteristics and social endorsement cues provided by audience members might influence user engagement with online science videos. Shorter videos are more likely to be viewed. Social endorsement cues significantly relate to variations in user engagement, with likes having a consistent positive association with all types of engagement. Implications for science communication through YouTube are discussed. Research and practice in science communication have a long tradition of focusing on legacy media given their primary role in disseminating news about scientific breakthroughs and bridging the science-public divides. However, nowadays such media no longer have the central place they used to occupy in the science communication process ,2. IndeeFaced with the deteriorated influence of legacy media in science communication, many leaders in the scientific community have called for scientists to engage and communicate directly with the public ,4 and arThe video-sharing site YouTube is particularly well suited for successful science communication online. As the world’s largest video-sharing site , YouTubeWithin this context, we provide initial insights on the makeup of YouTube science audiences and some of the factors that influence user engagement with YouTube science videos, by analyzing a unique, comprehensive set of back-end data from YouTube Analytics made available by the American Chemical Society. While previous research on YouTube and science communication has almost exclusively focused on the relationship between video content factors and user engagement, we explore how video characteristics that are not primarily content-related, including audience cues, associate with variations in user engagement. Such non-primarily content-related factors are important to understand because they reflect the larger infrastructural and algorithmic influence of the YouTube platform, which plays a central role in shaping video popularity but remains a black box to outsiders. Moreover, we expand current understanding of user engagement on YouTube by exploring additional engagement activities that are, albeit understudied, useful for garnering a fuller understanding of user engagement on YouTube. By showing how different video characteristics and audience cues can influence a variety of user engagement activities with online science videos, our study demonstrates the importance of attending to these factors in using YouTube for science communication and sheds light on specific strategies that may make science videos more likely to cut through the online noise and effectively reach viewers.Our primary outcome variable is user engagement with science videos on YouTube. In the broadest term, user engagement speaks to user-initiated actions that contribute to co-creation of value and knowledge among the online community ,15. ThisResearch on user engagement with YouTube videos has traditionally focused on popularity metrics such as video views, comments, (dis)likes –21 and lThe additional measures that we propose complement existing measures of user engagement in a number of ways: first, unlike click- and comment-based interactions, average view duration and average percentage viewed reveal closer details about the way users consume a video, since these two measures track down how well the video holds the attention of the users once they are pulled in; second, a video may intrigue users so much that they want to see more videos from the channel in the long term, by subscribing to the channel after watching a video, which signifies a deeper level of commitment and engagement than one-time clicks and comments; third, users can save a video in playlists for future reference if they are not able to watch it immediately upon encountering it despite finding it interesting, or if they find the video so relevant that they want to come back to it again in the future. Despite the distinct value of understanding these forms of user engagement, these phenomena are rarely studied by prior research because they typically require access to back-end YouTube data, which can be quite unobtainable. By exploring these additional user activities, we expand the scope of user engagement currently defined and capture a fuller picture of user engagement with science videos on YouTube.Founded in 2005 and purchased by Google in 2006, YouTube has grown to be the second largest network channel in the world  and the Science and technology is one of the most prominent video categories on YouTube, accounting for approximately 4% of all video uploads and ranking seventh of all categories in 2017 ,30. SomeWith the aim of maximizing user retention over the long run , YouTubeThe YouTube recommendation system takes into account both video content-based and content-independent factors when making recommendations . While mMany of the factors influencing YouTube recommendations  are visible to YouTube users and provide social information about the video; that is, they may serve as cues of social endorsement and carry their own psychological implications for stimulating user engagement. In the next section, we review how social endorsement cues may shape user engagement with online information.Users can derive from social endorsement cues the knowledge about how likely a piece of online information is to be correct or good, since these cues are indicative of other users’ (dis)approval of the information . EndorseEmploying an experimental design in which participants watched one of two science comedy clips, Cacciatore et al. found that audience laughter included in the video clip could serve as a powerful social cue indicating others’ endorsement on the content, which increased participants’ favorable affective response to the video clip and their intentions to engage with science more broadly . In an aWhile a plethora of studies have examined how user behaviors may be shaped by social endorsement cues in other social media contexts, few studies have paid attention to the YouTube platform, the second largest social networking space . In theiTaken together, we propose the following research question about user engagement with science videos on YouTube, which has particular relevance to practitioners of science communication:RQ1: To what extent are video characteristics and social endorsement cues embedded in the YouTube environment associated with levels of user engagement with science videos?Reactions. Reactions channel is one of the fastest growing science education channels on YouTube that produces short, entertaining videos about everyday chemistry and science. As of the time this paper was written, Reactions had gained more than 36 million views and 298,805 subscribers since its launch in January 2014. Our data came from YouTube Analytics and were made available by the American Chemical Society, which provided us with the unique opportunity to access a primary dataset with information from millions of users on aggregate audience characteristics, user engagement, and video characteristics for a total N = 210 videos since the channel’s launch to June 9, 2017. Addressing potential concerns about research collaborations between academic and industry partners [To understand variations in user engagement with YouTube science and chemistry videos, we partnered with the American Chemical Society to analyze comprehensive user data of their YouTube channel partners , all datBefore we dive into the dataset and variables, it is worth noting that our methodological approach has several advantages. First, our data recorded behaviors of YouTube users as they interacted with real-world stimuli in natural environments––––rather than artificial manipulation of the independent variables in a lab setting, which oftentimes does not equate with how complex dynamics play out in the real world . In otheThe dataset contained dozens of variables about a variety of video characteristics , aggregate information on audience characteristics  and user engagement activities . Note that user engagement data were broken down either by video or by aggregate audience characteristic. User engagement data at the channel level were also available on a day-to-day basis. We draw on these comprehensive data to explore how user engagement with science videos is shaped by algorithmic and social influences.We examine a number of dependent variables that capture aspects of user engagement with YouTube videos, including video view count , shares , comments , average view duration , average percentage viewed , number of subscribers gained , and number of playlists added in .Several video characteristics and social endorsement cues including video length , view count , likes , dislikes , and comments  were included as independent variables in our analysis of user engagement because a) prior work suggests that these factors presumably affect how YouTube makes video recommendations, which subsequently influences user engagement with online science videos; and b) video view count, likes, dislikes, and comments are visible to users as they visit YouTube video webpages and thus serve as social endorsement cues that could impact user psychology relative to engaging with online science videos. Count independent variables including view count, likes, dislikes, and comments were log transformed due to skewness.To contextualize our findings, we first provide summary user engagement data broken down by key demographic and audience characteristic variables in Tables Reactions science videos and what their engagement styles are. Overall, younger and male users were the most active audiences of Reactions . The Akaike Information Criterion (AIC) dropped by 0.4 (from 5266.00 to 5265.61) while the Bayesian Information Criterion (BIC) increased by 3 (from 5276.04 to 5278.99). The rules of thumb for interpreting change in the AIC and BIC can be found in Fabozzi et al. [χ2 = 371.50, df = 3, p < .001). Turning to the fit statistics, both the AIC and the BIC dropped considerably .To answer RQ1, we now turn to negative binomial regression analyses of video view count, shares, comments, number of subscribers gained, and number of playlists added in. Results from the final models are shown in i et al. . Althougχ2 = 1.97, df = 1, p = .16, AIC increase by 0.04 from 2255.91 to 2255.95, BIC increase by 3.4 from 2265.95 to 2269.33; for shares: χ2 = .17, df = 1, p = .68, AIC increase by 1.8 from 2810.31 to 2812.15, BIC increase by 5.2 from 2820.35 to 2825.54). The third and final models accounted for social endorsement cues and significantly improved the second models .We applied the same modeling strategy to analyzing commenting, sharing, and subscribing behaviors, as well as adding a video to playlists. In the analyses of comments and shares, the baseline models included only the control variable, time elapsed since video upload. The second models considered video length, which did not explain additional and distinct variance above and beyond the baseline model . The third models incorporated social endorsement cues including likes, dislikes, comments and views and explained a significant amount of additional variance above and beyond the second models .Turning to our analyses of number of subscribers gained and number of playlists added in, we again included only time elapsed since video upload as the control variable in the baseline models. Next, video length was entered in the second models, which did not significantly improve the baseline models , comments , and subscribers gained , and negatively related to number of shares  and playlists a video was added in . Exponentiating these regression coefficients, we obtained the incident rate ratios for views (IRR = 1.03), comments (IRR = 1.03), shares (IRR = .99), subscribers (IRR = 1.06), and playlists (IRR = .98). As the number of days a video has been posted online increases by thirty, the incident rates that the video gets views, comments, and subscribers increase on average by 3.43%, 2.77%, and 5.72%, respectively, with everything else held constant. The incident rates for getting shared and added in playlists decrease on average by 1.47% and 1.79%, respectively. Turning to video characteristics, video length was significantly and negatively associated with views . That is, the longer a video is, the fewer views it will generate. Incident rate ratios for views (IRR = .84) was obtained by exponentiating the corresponding regression coefficient. With every one-minute increase in video length, the incident rate of a video getting viewed decreases on average by 15.85%, when everything else is held constant.Time elapsed since a video was uploaded was significantly positively related to greater number of views , commenting , sharing , subscribing , and adding to playlists . Moreover, with the incident rate ratios obtained from exponentiating the corresponding negative binomial regression coefficients for viewing (IRR = 11.20), commenting (IRR = 6.14), sharing (IRR = 3.39), subscribing (IRR = 10.47), and adding to playlists (IRR = 2.84), respectively, we found that a ten-fold increase in likes received by a video was associated with an average increase in the incident rates of getting viewed, commented, shared, subscribed, and added in playlists by 1020.12%, 513.65%, 239.28%, 947.46%, and 184.48%, respectively.Social endorsement cues were indeed related to user engagement with science videos. Our results suggested that videos receiving endorsement in the form of likes was positively related to all five types of user engagement being examined––––viewing  but negatively associated with attracting new subscribers . A ten-fold increase in dislikes was associated with an average increase in the incident rate of getting commented by 66.19% (IRR = 1.66) and an average decrease in the incident rate of getting subscribers by 39.45% (IRR = .61). Receiving comments was positively related to a video being added to playlists , as a ten-fold increase in comments was associated with an average increase in the incident rate of being added to playlists by 66.67% (IRR = 1.67). Videos receiving views was also positively related to getting shared , subscribed , and being added in playlists , with a ten-fold increase in views being associated with an average increase in the incident rates of getting shared (IRR = 2.40), subscribed (IRR = 2.25), and being added in playlists (IRR = 1.80) by 140.47%, 125.04%, and 79.55%, respectively.Finally, videos receiving dislikes was positively related to getting user comments  but smaller percentages  on average. In terms of social endorsement cues, videos with more likes were on average viewed for longer time  and greater proportions . In contrast, videos with more dislikes were watched for shorter durations  and smaller proportions  on average. Videos with more comments were watched on average for greater durations  and proportions . Lastly, videos that received more views were watched on average for shorter time  and smaller percentages .We applied hierarchical OLS regression to analyzing average view duration and average percentage viewed . Time elReactions. The objective of this study is to understand variations in user engagement with online science videos.While video characteristics that are not primarily content-based play an important role in influencing the ranking of YouTube videos and how users respond to them, they have received less scholarly attention . In addiReactions toward an understanding of the makeup of audiences for YouTube science videos more generally.To this end, we specifically examined how video characteristics and social endorsement cues embedded in the YouTube environment explained such variations in user engagement. Although it is intuitive to speculate that gaining social endorsement such as likes will increase a video’s chances of receiving greater engagement from users, it is still up to empirical investigations to find out to what extent such social cues matter. To our knowledge, our study is the first one to have quantified the information on the interrelationships among video length, cues of social endorsement and various user engagement measures. Moreover, we present key demographic information and audience characteristics of Reactions channel. Thus, they do not tell us much about how to engage publics that are less interested in science overall. This finding resonates with research on audiences for other types of science media. For example, blog readers were found to be sophisticated science consumers who already possessed high levels of scientific knowledge [Before discussing the implications of our findings for effective science outreach and public engagement through YouTube videos, it is important to note several potential limiting factors related to the interpretation of our results. First, our data came from users who were likely already engaged to some extent with science videos from the nowledge . Neverthnowledge . Future Why Do Dogs Smell Each Other’s Butts; Is it OK to Pee in the Ocean) helped boost viewership and engagement, perhaps because such video titles pointed to the entertainment orientation of the YouTube platform [Second, even though video content factors were not the main focus of our analysis, they are nonetheless relevant aspects to consider when exploring user engagement. Previous research discovered that user-generated science videos were more popular than professionally produced videos on YouTube and that having consistent science communicators deliver the content might increase video popularity . Use of platform . Short, Reactions channel are doing well in reaching and engaging YouTube audiences. Reactions has more than 25 million views and 264,781 subscribers. The average number of views of a Reactions video is 122,574 and the median number of views is 48,203. To put these numbers into perspective, the median number of views for a YouTube video is 89 [Reactions viewers roughly resemble that of YouTube users in general, with the 18–44 age group and males being more active and engaged. This echoes past research in that males are found to be more active audiences for online science media [With these considerations in mind, our findings have important theoretical and practical implications for science communication research and outreach. Overall, science videos on the eo is 89 . An avereo is 89  and an aeo is 89 . Demograce media . Howeverce media .We found that older users (55 years old and above) do not necessarily spend more time watching each individual video than younger users but they somehow manage to watch each video in its greater entirety. It therefore seems plausible that older users tend to either watch shorter videos or to fast forward and/or speed up while watching, although empirical evidence directly supporting this speculation is lacking. Future research is needed to clarify these dynamics. In addition, the finding that female audiences are less active and engaged with science videos on YouTube may be explained in part by the fact that there is a lack of female representation in YouTube science videos. Female communicators are conspicuously absent from Science, Technology, Engineering, and Mathematics-themed video content on YouTube ,69. AddrReactions videos come from non-subscribers, indicating the substantive reach of the channel beyond its subscribers, subscribers are overall more engaged with the videos. Subscribers generate approximately three times more shares and thirteen times more likes per view of video than non-subscribers. Subscribers also watch for longer time and greater proportion per view of video compared with non-subscribers. Although there appears to be a correlation between subscription status and engagement as subscribers are more engaged with YouTube science videos, it is impossible to pinpoint the exact causal mechanisms with our data. Nonetheless, prior research may shed some light on these underlying processes. Once subscribing to a channel, users will receive notifications when the channel publishes any new videos and they will be continuously exposed to those videos in their subscriptions feed [Our findings reveal that whereas the majority of views of the ons feed ; therefoons feed  and provons feed , which mReactions videos through mobile phones exhibit the highest levels of social viewing behaviors such as liking and sharing videos compared with all other types of access devices. This pattern holds even after taking into account total number of views. Prior research on college student millennial samples has similarly shown that watching YouTube videos on mobile phones is linked to higher frequency of video sharing, possibly due to the ease of sharing videos on social media apps on mobile phones [In addition, our findings show that computers and mobile phones are the top two access devices that generate the largest number of views. YouTube’s internal data have also confirmed that mobile devices are a major source of views, accounting for over 70% of total watch time . More ime phones . Moreovee phones . During e phones . These fWhile previous research found that longer videos were more likely to be recommended by YouTube than shorter videos ,42, we fConsistent with what prior research suggests, we found that overall social endorsement cues were indeed positively related to user engagement with science videos on YouTube, with a few exceptions. Among all social cues, likes appeared to have the strongest association with all seven types of user engagement—not only instantaneous and effortless click-based engagement such as viewing and sharing, but also more effortful and long-term engagement such as commenting, subscribing, and adding to playlists and attention-based engagement such as viewing a video for longer and viewing a video in its entirety. Unlike other social endorsement cues such as comment and view counts, likes explicitly indicate users’ favorable evaluation and/or appreciation of video content  and therAs expected, videos with more dislikes received less user engagement in terms of subscribers gained, average view duration, and average percentage viewed. However, greater dislikes were associated with more comments received. The causal mechanism may go two ways: on the one hand, a high number of dislikes may indicate that a video contains controversial content, which may consequently elicit more user comments  because Finally, although videos with higher view counts were also shared and added to playlists more often and attracted more subscribers, they received lower attention-based user engagement in terms of both average view duration and average percentage viewed. While there is little empirical research evidence that can easily reconcile these findings, we speculate that the most highly viewed videos enticed a larger audience base than the channel’s usual suspects, due to peripheral factors such as “clickbaity” video titles and descriptions. In other words, users might be attracted to those videos hoping for something else than what the videos were really about, and once they found out about it, they stopped watching. However, more research is needed to unravel the relationship between video view count and the attention-based user engagement measures before any final conclusions can be drawn. Moreover, our findings point out that science communicators will likely run into competing demands when optimizing their public engagement strategies. When this occurs, communicators should be clear about which goals to prioritize given that different goals may determine different courses of action.More importantly, science communicators should pay attention to how increasing user engagement fits into the broader goals of public communication of science. The online measures of user engagement provided by YouTube are an imperfect indicator of the degree to which science video consumption leads to the various outcomes that effective science communication seeks to accomplish, including sharing the findings and excitement of science, growing appreciation for science as a useful way of making sense of the world, increasing knowledge and understanding of science, influencing people’s opinions, behavior and policy preferences, and engaging with diverse perspectives about science held by different publics in solving societal problems . IncreasIn sum, we believe our findings illustrate the importance of attending to not just video content factors but also factors that are not primarily content-related when understanding various user engagement activities with online science videos. Using videos for public engagement and science outreach has gained increased popularity in practice and has ample room for growth in research . DocumenS1 File(XLSX)Click here for additional data file.


Otolaryngology is a surgical speciality well suited for the application of intraoperative video recording as an educational tool considering the number procedures within the speciality that utilize digital technology. Intraoperative recording has been utilized in endoscopic surgeries and in evaluating technique in mastoidectomy, myringotomy and grommet insertion. The impact of intra-operative video recording in otolaryngology education is vast in creating access to surgical videos for preparation outside the operating room to individualized coaching and assessment. The purpose of this project is to highlight the role of intraoperative video recording in otolaryngology training and elucidate the challenges and considerations associated with implementation.Related publications between 1999 to 2022 were reviewed from PubMed and Embase databases utilizing search terms “intraoperative videography,” “video recording surgery,” “otolaryngology,” and “surgical education.” 109 articles were screened independently by HB and SK, by title and abstract then full text review. 28 articles from the original search and 6 from the secondary reference review were included.The application of intraoperative video recording is evident in otolaryngology surgeries including endoscopic sinus surgery, laryngeal surgery, and other endoscopic procedures. There have been significant advancements in recording tools, including devices that can capture the surgeon’s perspective. The considerations and challenges identified with utilizing this educational tool were categorized into different themes including ethics/consent, regulation, liability, data, technology, and human resources.Intra-operative video recording has been demonstrated to have significant impact within otolaryngology education. It is critical to elucidate the challenges and considerations involved to utilize this educational tool effectively. Future directives will see video-based performance analytics providing comparative metrics to encourage precise coaching of surgical residents. Intraoperative video recording is frequently used for education, research and quality improvement across various surgical specialties, including general surgery, ophthalmology and orthopedic surgery –3. This Otolaryngology is a surgical speciality well suited for the application of intraoperative video recording as an educational tool considering the number procedures within the speciality that utilize digital technology with recording capability. Surgical videos have also been used in surgical preparation and mastery of surgical anatomy in many otolaryngology procedures including otological surgeries, laryngoscopy, thyroidectomy, neck dissection, rhinoplasty and rhytidectomy. –10 IntraRelated publications between 1999 to 2022 were reviewed from PubMed and Embase databases utilizing search terms “intraoperative videography,” “video recording surgery,” “otolaryngology,” and “surgical education.” The search strategy is outlined in Fig. (P) The population focus of this study was residents in otolaryngology head and neck surgery. (I) The intervention analyzed was intraoperative video recording, for education and assessment. (C) The use of intraoperative video recording was compared to traditional educational resources and assessment approaches. (O) The major considerations and challenges of implementing intraoperative video in otolaryngology education and assessment were identified in terms of technology, data, human resources, ethics/consent, regulation and liability.Operative videos have been increasingly employed within otolaryngology training. The need for this resource has been highlighted by the COVID-19 pandemic which impacted hands-on training. Access to surgical videos is an important resource for medical students, residents, and practicing surgeons seeking continuing educational opportunities, as well as surgeons in countries with various levels of training resources. In a survey of resident trainees, the resource of surgical video library was utilized most frequently in the preparation for upcoming cases, but was also used for general surgical anatomy learning and solidifying concepts after being involved in a case . A smallThe educational value of utilizing surgical video has also been elucidated in a number of studies. One study demonstrated the value of intraoperative video in learning surgically relevant head and neck anatomy with two groups of medical students utilizing novel surgical video atlas for thyroidectomy compared with traditional textbook resources. The video atlas arm scored higher in the post test and were more satisfied with their learning compared to those using traditional textbook resources . A studyIntraoperative video recording has been utilized in the development of a teaching module for thyroidectomy surgery and neck dissection, utilizing a 3-camera viewing system for multiple vantage points. These modules were assessed using intraoperative video as well, in which residents wore a headlight camera while performing a thyroid lobectomy and neck dissection before and after watching the teaching module , 8. The Otolaryngology residency programs utilize various assessment tools, including case logs, oral and written examinations as well as evaluations under supervision in the operating room. Recently surgical education has shifted towards competency-based medical education (CBME), which emphasizes assessment to track progress . A studyOne of the strengths of utilizing intraoperative video in assessment and evaluation is how multiple independent evaluators can assess the resident’s surgical skills, creating a reliable and valid evaluation system. Another benefit of this assessment approach is allowing for objective, unbiased evaluation of surgical skills by blinding the identity of the resident to the evaluator. Additionally, many surgeries with small operative fields and microscopic endoscopic approaches can be difficult for supervisor to visualize while assessing trainees.A study by Bowles et al. evaluated the use of intra-operative video recording as an objective assessment tool for myringotomy and grommet insertion . The stuA study evaluating surgical technique in mastoidectomy, which blindly evaluated intra-operative video for junior and senior residents and attending surgeons was also reviewed. The study demonstrated reasonable metrics for evaluation of surgeon skill level including drill stroke count, drilling efficiency, stroke pattern and use of suction irrigator. As evaluation and assessment can be time consuming, this study also highlighted how short video segments can provide valuable information on skill level . AnotherA video-based assessment tool was developed at John Hopkins Hospital for evaluation of surgical skills in endoscopic sinus surgery (ESS), utilizing intraoperative video recording and assessment checklists . There wThis form of assessment also allows for incorporation of artificial intelligence (AI) to provide a deeper understanding of the surgical skills with less required human analysis. Intraoperative tool movement tracking data has been shown to be clinically useful in quantifying surgical performance. A study demonstrated that machine learning can be utilized to identify surgical instruments within endoscopic endonasal intraoperative video and increase access to this information of surgical performance . Deep neAlong with assessment, intraoperative video recording also allows for coaching. This approach has been implemented in sports settings, where coaches review plays with team members following a game to identify areas of improvement . This coAs patient safety and outcomes are directly related to surgical performance and technical skill, video-based coaching (VBC) has the potential to identify individual areas of improvement and subsequently impact quality of care and safety. VBC has been demonstrated to impact skill acquisition, as surgical residents who received VBC had significant improvements compared to the residents who did not receive this video coaching when evaluated with standardized assessments . AnotherWithin Otolaryngology, a recent study evaluated video-based coaching for mastoidectomy education and highlighted the resident-perceived benefit of richer teaching and promotion of a deeper surgical understanding. Notably video-based coaching can be implemented easily in otolaryngology subspecialty surgeries utilizing video-recording capable equipment. The role of intraoperative education is summarized in Fig. The considerations and challenges associated with implementing intraoperative video recording in Otolaryngology education are outlined below and shown in Fig. There have been significant advancements in the devices available for recording intraoperatively as well as in the recording techniques utilized. An important consideration in intraoperative recording is consideration of the type of device that will be used and the advantages and disadvantages involved.The ability to capture the operator’s perspective has had an impact on the educational value of the footage as well. This is especially important in microscopic endoscopic surgical approaches which can be difficult for supervising surgeon to visualize. GoPro head mounted cameras have been utilized on the surgeon and surgical assistant to provide different optimal views of otolaryngology surgery and gather footage which can aid in the education of both surgeons and surgical assistants . AnotherThe use of mobile smartphone devices has also been evaluated as a method for intraoperative recording of various head and neck surgeries including submandibular gland resections, neck dissections, and supraglottic laryngectomy . An iPhoIn order to implement intraoperative video recording into otolaryngology training ethics, consent and privacy of the patient need to be considered.It is also necessary to review the impact of video recording on OR staff. Staff attitude regarding implementing recording initiatives has been assessed and categorized into themes of safety culture, imposter syndrome and privacy concerns . AnotherInformed consent of the patient is vital in the ability to perform a surgical procedure. Before video recording takes place within the operating room, the patient must understand the purpose for recording, the intended audience, where and how long the data will be kept and the procedures in place to de-identify the information and protect privacy . The queAs previously mentioned, some of the devices that can be used for videography have communication features that are critical to be cognizant of to implement the necessary precautions to protect patient privacy. The study that utilized a mobile smart phone demonstrated this by using a phone without a sim card and Wi-Fi connection and storing the data in a secure fashion without identifying information . NotablyIt is also critical to consider the resident and surgeon perspective in terms of ethics, consent and privacy with intraoperative video use. In the same way, informed consent is required from the patient it is also essential to obtain from the resident and surgeon involved as well. Defining the use of the video data for educational purpose, who will have access, where and how long it will be stored also need to be address in this context. Answering these important questions prior to using this tool can ensure that can concerns about how the data may be used in residency assessment and impact future career endeavors, potentially serving as a means to demonstrate skill competency.Video Recording in the OR can be used for education, research, and quality improvement and clarifying the purpose of the data is essential in regard to ethics, consent and medicolegal concerns. Surgical video recording has also been shown to be associated with reduction in errors and positive impact on patient safety . The priRegulation is important to consider in the educational application of intraoperative video considering the videos that are available, the methods and approach to videography and the implementation in assessment.With multiple devices available, the importance of standardizing the video method for optimal view and positioning for educational purposes is evident. Optimal videography also varies between procedures and the unique challenges associated with different subspecialty surgeries. Rhinoplasty, for example, has challenges including a small surgical field with limited sightlines and requires unique viewing angles which vary throughout the procedure. An analysis of the video standards for rhinoplasty education identified that upward camera angle has been most frequently used and endoscopic view was least frequent . AnotherAs Intraoperative video recording can allow for objective assessment of residents, there is a need for regulation of the assessment approach to promote standardization. The question of whether to edit the footage that is being evaluated is important to consider . The advIt is also important to consider liability and potential legal impact of intraoperative video recording. There is potential for the recording to be utilized in defense or prosecution of the surgeon when implicated in negligence or misconduct. There are laws that protect information collected for quality improvement from being used as evidence in malpractice lawsuits through nondisclosure and confidentiality rights . ClearlyOutlining how the video data can be used, in this case for education of surgical trainees, is critical in terms of the medicolegal perspective. If the intent for the data collected was for quality improvement or research purposes, the ownership of the information would be the hospital and physicians for case review, clinical research and protected from litigation . If the One of the major considerations in intraoperative video as an educational tool is the quality of existing data and videos that are publicly available. Publicly available surgical videos on YouTube have been assessed in a number of studies. A study reviewed the available surgical videos for rhytidectomy on YouTube and found variability in the videos, many lacking discussions of key aspects of successful surgery and concluded that discretion should be utilized when accessing such videos as a learning tool . A similGiven this variability of intraoperative videos, international recommendations have been created to assist in the creation and standardization of educational surgical videos in otolaryngology and head and neck surgery. These recommendations include ethics considerations anonymizing the patient, technical aspects of editing and high quality, narration, and surgery steps . AnotherAn open-access comprehensive otolaryngology head and neck surgery video atlas has recently been developed to allow for access to high quality videos narrated with important commentary including surgical steps and key landmarks.  ConsolidThe human resources required to utilize intraoperative video recording is also critical to review. While some devices capture the perspective of the operator with little to no adjustment needed, other devices require angle changes and adjustments throughout the surgery. The personnel required to make such adjustments, set up the devices and maintain the devices would be an additional cost. Additionally, implementing this tool in surgical education also requires personnel to edit the footage as well. Another considerations for video-based assessment includes the time and human resources outside the OR required by attending physicians to review the video and provide individualized feedback . AlthougIntra-operative video recording has been demonstrated to have significant impact within otolaryngology education, in terms of its application in knowledge pre-operative preparation, assessment and coaching. It is critical to elucidate the challenges and considerations involved to utilize this educational tool effectively. Future directives will see video-based performance analytics providing comparative metrics to encourage precise coaching of surgical residents.


Excessive internet gaming in high prevalence is a very common problem that has been increasing in recent years, especially in teenagers and university students. However, there is a lack of psychometric evaluation for Internet Gaming Disorder in the Latin American context, particularly in Ecuador. This paper aims to examine the psychometric properties of the Spanish version of the Internet Gaming Disorder test (IGD-20 test) in university and high school students ( The Diagnostic and Statistical Manual of Mental Disorders (DSM), according to DSM-IV and DSM-IV-TR, recently included pathological gaming under Impulse Control Disorders, and not classified elsewhere. However, the DSM-5 includes a chapter on behavioral addictions, arguing that these behaviors activate reward systems similar to those activated by drugs and cause some behavioral symptoms similar to those produced by substances, while not related to substance use addiction. However, they possess some characteristics that make them considerable as a potential disorder . In thisAccording to previous research, video games can have some positive effects in some domains such as the following: (i) in education, if they are properly used, they can offer great potential to develop cognitive abilities ,5,6,7; iThe Internet is a technology that has favored the expansion and use of online video games through multiple devices  , which gSimilarly, ICD-11, described in Section 6C51, is a gaming disorder characterized by a pattern of persistent or recurrent gaming behaviour , which may be internet-based or offline, manifested by: (1) poor control over gaming; (2) increased the priority given to the extent that it takes precedence over other life interests and daily activities; and (3) continuation or intensification of gaming despite the occurrence of negative consequences .It is worth mentioning that there is still not enough research to classify IGD as a disorder in the diagnostic manuals (DSM-5), although, in the ICD-11, it has recently been considered as such, which is why tools were developed to assess these behaviors. An example of these tools is the Internet Gaming Disorder Test IGD-20, developed by , which wSince 2014, researchers have published different studies covering this topic. In the In recent years, there has been an increase in worldwide research on video game addiction; however, in the Ecuadorian population, research about this phenomenon is scarce, considering that in Ecuador, the internet is used by about 57.8% of the population (10.17 million people), and 47% of the worldwide population play video games, according to the reports from We Are Social . TherefoThe Internet Gaming Disorder IGD-20 was constructed by  to assesThe study was conducted following the ethical guidelines for research in psychology. First, a research protocol was designed by , which hLastly, data was collected in the classrooms in middle schools during 2016 and in universities from Loja-Ecuador during 2020 using non-parametric incidental sampling techniques. Thus, data collection was dependent on availability. The study was approved by the vice-director of research of the “Universidad Técnica Particular de Loja”.Together with the IGD-20 Test, we also applied a socio-demographic test as an ad hoc survey designed for data collection related to the main aim of this work. It is composed by 9 short-answer questions which collect data about: age, gender, family type, schooling status (dropout), neighborhood, socioeconomic level, weekly game time, weekends and holidays game time and parental control. The sample is composed of 2931 participants, who were 14- to 28-years old  Comparative Fit Index (CFI) greater than 0.90; (iii) Tucker–Lewis fit Index (TlI) greater than 0.90; (iv) Root Mean Square Error of Approximation (RMSEA) less than 0.06 [In order to validate the IGD-20 test among Ecuadorian students, the Confirmatory Factor Analysis (CFA) was conducted using an open-source R package called Lavaan  using mahan 0.06 ,39; and han 0.06 ,39,40.To examine female and male samples, we follow the recommendations made by Yu et al., (2019) : conductAll these guidelines were used to identify which models best fit the data.This research was done following the ethical guidelines for research in psychology through a protocol developed by Andrade & Ontaneda (2015) . In addiFirst, we tried to replicate the model proposed by Griffiths (2005)  composedWe tested a two-factor model combining the items from “salience”, “tolerance”, “withdrawal”, “conflict” and “relapse” since these latent variables reflected a higher-order factor of engagement or correlation. This model showed an acceptable fit: , (2017) .In the p < 0.05), the change in CFI was equal to 0.001 and the change in the TLI was equal to 0.001, and the RSMEA was equal to 0.004, which is in concordance with [The model in the nce with  that it According to Cronbach’s alpha showed in p < 0.01). Thus, for teenagers and young people who spend more time in front of video games, the results showed greater symptoms of problematic video game use. Meanwhile the correlation between being a school dropout and IGD-20 showed a moderate inverse relationship (p < 0.01), which indicates that problematic video games use does not have influence over the loss of school years. On the other hand, there were no statistically significant results between IGD-20 and the variables: family type (p < 0.05), neighborhood (p < 0.01), weekends and holidays gameplay (p < 0.01), parental control (p < 0.01), gender , neighborhood, socioeconomic level, parental control, weekly gameplay, weekends and holidays gameplay, gender and age) were explored to verify concurrent validity. The correlation between video game use during weekdays and IGD-20 is positive . A total of 4% of the respondents had symptoms of problematic use, playing between 1 and 4 h per day. Of the students that were school dropouts, 14.8% had symptoms of problematic video game use, while 1.7% of the respondents that were not school dropouts showed symptoms of problematic use; this explains the moderate negative correlation between IGD and being a school dropout (p < 0.01).According to the results, our study showed an excellent internal consistency, higher than that of all the works analyzed in shown in . The stushown in  presentsThis study has some limitations, since it is necessary to work with a more homogeneous dataset. Moreover, answers may be biased based on social desirability as reported in the original and Spanish versions ,30. It i


In this study, we present and validate a novel concept for target tracking in 4D ultrasound. The key idea is to replace image patch similarity metrics by distances in a latent representation. For this, 3D ultrasound patches are mapped into a representation space using sliced-Wasserstein autoencoders.A novel target tracking method for 4D ultrasound is presented that performs tracking in a representation space instead of in images space. Sliced-Wasserstein autoencoders are trained in an unsupervised manner which are used to map 3D ultrasound patches into a representation space. The tracking procedure is based on a greedy algorithm approach and measuring distances between representation vectors to relocate the target . The proposed algorithm is validated on an in vivo data set of liver images. Furthermore, three different concepts for training the autoencoder are presented to provide cross-patient generalizability, aiming at minimal training time on data of the individual patient.Eight annotated 4D ultrasound sequences are used to test the tracking method. Tracking could be performed in all sequences using all autoencoder training approaches. A mean tracking error of 3.23 mm could be achieved using generalized fine-tuned autoencoders. It is shown that using generalized autoencoders and fine-tuning them achieves better tracking results than training subject individual autoencoders.It could be shown that distances between encoded image patches in a representation space can serve as a meaningful measure of the image patch similarity, even under realistic deformations of the anatomical structure. Based on that, we could validate the proposed tracking algorithm in an in vivo setting. Furthermore, our results indicate that using generalized autoencoders, fine-tuning on only a small number of patches from the individual patient provides promising results. In recent years, ultrasound imaging has become of high interest for usage in image guided interventions, e.g., in minimally invasive surgery  or in raTypically, target tracking is performed in image space by comparing a reference image patch to candidate patches using pixel-based metrics . HoweverAll these methods rely on the comparison of candidate patches with a reference patch in image space. In contrast, in Wulff et al. , it coulIn this work, we present a novel concept for tracking in 3D ultrasound by assessing the similarity between two image patches in a latent representation derived using unsupervised representation learning. Thus, we formulate a tracking algorithm following this idea and provide a proof of concept on an in vivo data set of liver motion. Furthermore, we present a thorough evaluation of transfer learning concepts to increase the applicability of our method in a clinical scenario.The objective of this study is to investigate whether tracking of deformable objects in time resolved 3D ultrasound can be performed in a representation space. Ultrasound patches are mapped into latent representation vectors, so measuring patch similarities becomes measuring vector distances. A long-term 3D ultrasound data set is used for training and validation of different autoencdoers and for evaluating the tracking performance. It is investigated whether generalized autoencoders are applicable instead of patient individual autoencoders. For the clinical workflow, this would be beneficial and time saving as learning patient individual networks could be replaced by using pretrained generalized networks. However, the optimal representation space dimensionality is unknown yet, so investigating this is part of this study. Ngoc and Hwang  proposedThe ultrasound data used in this study were acquired and published by Ipsen et al. . The datmentclass2pt{minimThe autoencoders receive an ultrasound patch in the size entclass1pt{minimaX and By using an autoencoder, the tracking process is transferred from the image space into a latent representation space. 3D ultrasound patches are encoded into latent representation vectors using 3D convolutional autoencoders. Thus, the data dimensionality is strongly reduced, while simultaneously the most important information is preserved. The general architecture of the autoencoders is illustrated in Fig. r (SWAE) . During r (SWAE) , the SWAmentclass2pt{minimk corresponds to a data reduction by Several autoencoders are generated in three different ways. Sets of subject individual autoencoders entclass1pt{minimaa, b are 3D ultrasound patches and x, y, z are the axes of the 3D ultrasound image space:To evaluate the training success, the reconstruction accuracy is measured using the validation data sets entclass1pt{minima Liver motion is mainly caused by the breathing cycle and has translation, rotation and deformation parts [Using representation learning, the tracking process is transferred from image space into representation space. However, an algorithm to recognize the target representation within a new ultrasound volume is still necessary. A naive approach is using template matching where the target representation is compared to all representation candidates within a region-of-interest . Since ton parts . DeformaAll autoencoders are used to perform landmark tracking in the sequences entclass1pt{minimaTo evaluate the reconstruction accuracy, the autoencoders are tested using the validation data sets The reconstruction accuracy increases with the representation space size and saturates at a mean accuracy of about Tracking is performed as described in “Landmark tracking” section. For evaluating the tracking accuracy, the tracking positions are compared to the ground truth landmarks using the L2-norm to determine the tracking error. In Fig. At lower representation space sizes, the tracking error is high and it decreases when the representation space size is set higher. However, the tracking error saturates at a mean error of 4.47 ± 4.42 mm, 4.33 ± 5.14 mm and 3.23 ± 3.13 mm in individual, generalized and generalized fine-tuned autoencoders, respectively, at a representation space size of 512. While in the experiments with a representation space size smaller than 64 the tracking error is quite high, the experiments with the remaining representation space sizes the tracking algorithm was able to follow the target with a low position error. However, in Fig. Deformable target tracking in 3D ultrasound is a challenging task due to low image quality, high noise ratio and the high degree of deformable target motion. In this study, an approach is presented to track a target patch in a representation space of a SWAE. Autoencoders are trained with different representation space sizes and in three different ways . The reconstruction accuracy is evaluated, so it can be seen that all autoencoders converged during training. The results show that the reconstruction accuracy is in the same order of magnitude for all three kinds of autoencoders. This indicates that it is not necessary to train patient individual autoencoders, but a pretrained generalized autoencoder could be used. These results are promising concerning the clinical workflow since acquiring a mass of training data and training patient individual autoencoders is time consuming.After training, the autoencoders were used to perform landmark tracking in representation space. The results indicate that the tracking algorithm is successful when using a representation space size larger than 64 and the error is not getting less when setting it very high as the error saturates after the representation space size of 256. The mean tracking errors of individual, generalized and generalized fine-tuned autoencoders indicate that the performances of individual and generalized autoencoders are comparable as the mean tracking error difference is 0.14 mm. However, using generalized autoencoders is beneficial because the mean tracking error decreases by 1.10 mm after fine-tuning the generalized autoencoders with small data sets. As seen in the reconstruction accuracy results, for the clinical workflow this is promising since for fine-tuning a pretrained generalized autoencoder acquiring a huge data set is not necessary. In addition, in the fine-tuning process only the fully connected layers are updated, so the computing time is reduced compared to training from scratch.z axis in Fig. z axis between two annotated frames. Such shifts lead to tracking errors because the assumption that the next target position lies nearby the previous target position is violated. In these cases, the greedy search algorithm is not able to recover the target as it is a simple algorithm without any outlier handlings or regularizations. Apart form these cases, tracking with the greedy algorithm was successful which means that the target was not lost.As can be seen in Fig. However, in some experiments the tracking error increased repeatedly in the same phase in the motion pattern. In Fig. To the best of our knowledge, the presented method is the first unsupervised learning approach for target tracking in 4D ultrasound as well as the first approach that utilizes 3D Convolutional Neural Networks. In contrast, previously published approaches either use 2D slice images and are trained in a supervised fashion  or do noIt could be seen that tracking in representation space worked for all tested sequences. Since the presented method is based on autoencoders that were not trained for performing tracking but for simply reducing data dimensionality Eq. , this isTarget tracking in time resolved 3D ultrasound images is a challenging task. In this paper, a proof of concept for performing tracking in 3D ultrasound in a representation space generated by an SWAE is presented. It is a novel simple approach that uses a 3D convolutional network to perform target tracking in 3D ultrasound images. It could be shown that using a generalized autoencoder and fine-tuning it for a specific patient is more promising than training an individual autoencoder from scratch. In addition, it is shown that tracking in 3D ultrasound images can be performed without the need of a large labeled data set by using unsupervised representation learning. This approach holds the potential to learn the possible target deformations, e.g., by using deforming autoencoders  which co