Social media and social impact assessment: Evolving methods in a shifting context.

Among many by-products of Web 2.0 come the wide range of potential image and text datasets within social media and content sharing platforms that speak of how people live, what they do, and what they care about. These datasets are imperfect and biased in many ways, but those flaws make them complementary to data derived from conventional social science methods and thus potentially useful for triangulation in complex decision-making contexts. Yet the online environment is highly mutable, and so the datasets are less reliable than censuses or other standard data types leveraged in social impact assessment. Over the past decade, we have innovated numerous methods for deploying Instagram datasets in investigating management or development alternatives. This article synthesizes work from three Canadian decision contexts - hydroelectric dam construction or removal; dyke realignment or wetland restoration; and integrating renewable energy into vineyard landscapes - to illustrate some of the methods we have applied to social impact assessment questions using Instagram that may be transferrable to other social media platforms and contexts: thematic (manual coding, machine vision, natural language processing/sentiment analysis, statistical analysis), spatial (hotspot mapping, cultural ecosystem modeling), and visual (word clouds, saliency mapping, collage). We conclude with a set of cautions and next steps for the domain.

Parmi les nombreux sous-produits du Web 2.0 figure un large éventail de données provenant d'images et de textes, de contenus de médias sociaux et de plateformes numériques, qui révèlent comment les gens vivent, ce qu'ils font et les questions qui les préoccupent. Ces ensembles de données sont imparfaits et biaisés à bien des égards, mais nombre de leurs lacunes les rendent complémentaires des informations collectées par les sciences sociales à l'aide de méthodes conventionnelles. D'où leur utilité potentielle pour la triangulation dans des contextes décisionnels complexes. Cet article synthétise le travail de trois études de cas menées au Canada pour illustrer certaines des méthodes que nous avons développées et qui pourraient être utiles à d'autres chercheurs en EIS: thématiques (codage, apprentissage automatique, analyse sémantique, association statistique), spatiales (cartographie des points chauds, modélisation du transfert des bénéfices) et visuelles (cartes de saillance, collage).

Entre los muchos subproductos de la Web 2.0 se encuentra una amplia gama de datos de imágenes y texto, contenidos en redes sociales y plataformas digitales, que hablan de cómo vive, qué hace y por qué cuestiones se preocupa la gente. Estos conjuntos de datos son imperfectos y sesgados en muchos sentidos, pero muchos de sus defectos los hacen complementarios a la información recogida por las ciencias sociales con métodos convencionales. De ahí su potencial utilidad para la triangulación en contextos complejos de toma de decisiones. Este artículo sintetiza el trabajo de tres estudios de caso llevados a cabo en Canadá para ilustrar algunos de los métodos que hemos desarrollado y pueden resultar útiles para otros investigadores en EIS: temáticos (codificación, machine learning, análisis semántico, asociación estadística), espaciales (mapeo de puntos críticos, modelización de transferencia de beneficios) y visuales (mapas de saliencia, collage).

Drug use and pattern of injuries sustained by drivers involved in road traffic crashes.

OBJECTIVE: Road traffic crashes are one of the global public health concerns and remain at high priority in many countries. Driving under the influence of drugs increases the risk of crashes through altering the driver's mental state and reactions. This study was conducted to determine the relationship between driving pattern and substance abuse among drivers in Kerman, a city in Iran, in order to enable policy makers to make the necessary decisions in planning and executing guidelines. METHODS: The population of this descriptive study was drivers involved in road traffic crashes admitted to the emergency department of Shahid Bahonar university hospital in summer 2019. After obtaining demographic information, type of vehicle, type of collision and pattern of serious injury, 222 eligible drivers were tested for tramadol, cannabis, amphetamine, methamphetamine, morphine and methadone using one step urine test strips. Chi-square test, Fisher's exact test, Whitney-Mann and Kruskal-Wallis tests and one-way Anova test was performed using SPSS version 22. RESULTS: The statistics showed that most drivers were male (90.5%), married (63.5%), age group (18-30) and had positive urine test (76.6%). In addition to uniqueness of dual-drug detection among male drivers (7.7%), the most common substances detected were methadone and morphine with 34.7% and 27.5% respectively. The most common injuries were lower limb and hip injuries mostly among motorcyclists. The results indicated that characteristics of being under 30's, married, school dropout, self-employed and motorcyclist had significant relationship with substance use. CONCLUSIONS: Substance use, especially methadone, has undoubtedly a significant role in both road traffic crashes and resulted injuries. The high rate of injuries on drivers influenced by methadone in traffic crashes needs to be screened and prevented. It is recommended to not only authoritatively deal with the excessive supply of methadone in the community but also restricting the driving of people receiving methadone treatment.

Association between playing computer games and mental and social health among male adolescents in Iran in 2014.

BACKGROUND: As adolescents spend much time on playing computer games, their mental and social effects should be considered. The present study aimed to investigate the association between playing computer games and the mental and social health among male adolescents in Iran in 2014. MATERIALS AND METHODS: This is a cross-sectional study conducted on 210 adolescents selected by multi-stage random sampling. Data were collected by Goldberg and Hillier general health (28 items) and Kiez social health questionnaires. The association was tested by Pearson and Spearman correlation coefficients, one-way analysis of variance (ANOVA), and independent t-test. Computer games related factors such as the location, type, length, the adopted device, and mode of playing games were investigated. RESULTS: Results showed that 58.9% of the subjects played games on a computer alone for 1 h at home. Results also revealed that the subjects had appropriate mental health and 83.2% had moderate social health. Results showed a poor significant association between the length of games and social health (r = -0.15, P = 0.03), the type of games and mental health (r = -0.16, P = 0.01), and the device used in playing games and social health (F = 0.95, P = 0.03). CONCLUSIONS: The findings showed that adolescents' mental and social health is negatively associated with their playing computer games. Therefore, to promote their health, educating them about the correct way of playing computer games is essential and their parents and school authorities, including nurses working at schools, should determine its relevant factors such as the type, length, and device used in playing such games.

Concentration of cd, pb, hg, and se in different parts of human breast cancer tissues.

Breast cancer is the major cause of cancer morbidity and mortality between women in the world. Metals involved in environmental toxicology are closely related to tumor growth and cancer. On the other hand, some metals such as selenium have anticarcinogenic properties. The aim of this study is to determine the concentration of cadmium, lead, mercury, and selenium in separated parts of tegmen, tumor, tumor adiposity, and tegmen adiposity of 14 breast cancer tissues which have been analyzed by graphite furnace atomic absorption (AA-670) and ICP-OES (ULTIMA 2CE). Our results show that Se and Hg have maximum and minimum concentration, respectively. Statistical analysis reveals no significant differences between metal accumulations in different parts of cancer tissues (P > 0.05) and this observation might be due to the close relation of separated parts of fatty breast organ. Thus, we could conclude that a high level of these heavy metals is accumulated in Iranian cancerous breasts and their presence can be one of the reasons of cancer appearance.