Safety Literature Research Articles

Sliding into My DMs: Detecting Uncomfortable or Unsafe Sexual Risk Experiences within Instagram Direct Messages Grounded in the Perspective of Youth

We collected Instagram data from 150 adolescents (ages 13-21) that included 15,547 private message conversations of which 326 conversations were flagged as sexually risky by participants. Based on this data, we leveraged a human-centered machine learning approach to create sexual risk detection classifiers for youth social media conversations. Our Convolutional Neural Network (CNN) and Random Forest models outperformed in identifying sexual risks at the conversation-level (AUC=0.88), and CNN outperformed at the message-level (AUC=0.85). We also trained classifiers to detect the severity risk level (i.e., safe, low, medium-high) of a given message with CNN outperforming other models (AUC=0.88). A feature analysis yielded deeper insights into patterns found within sexually safe versus unsafe conversations. We found that contextual features (e.g., age, gender, and relationship type) and Linguistic Inquiry and Word Count (LIWC) contributed the most for accurately detecting sexual conversations that made youth feel uncomfortable or unsafe. Our analysis provides insights into the important factors and contextual features that enhance automated detection of sexual risks within youths' private conversations. As such, we make valuable contributions to the computational risk detection and adolescent online safety literature through our human-centered approach of collecting and ground truth coding private social media conversations of youth for the purpose of risk classification.

Prediction of compliance with preventive measures among teachers in the context of the COVID-19 pandemic

The objective of this study is to examine, in primary and high schools, teachers' compliance with preventive infection control measures (in the context of the COVID-19 pandemic). Inspired by the technology acceptance model (TAM) and occupational health and safety (OHS) literature on personal protective equipment (PPE) use, we propose a model of compliance with preventive measures among teachers. Data were collected following an observational, cross-sectional design. The data for the study were collected via a questionnaire survey of teachers working in the province of Quebec, Canada. To study the impact of the explanatory variables on the dependent variable, we developed a multiple linear regression model. This model was estimated to assess the preventive measures as a whole (six items). Results show that having tested positive for a COVID test in the last year, judging that the situation does not require the use of the mask or the protective glasses, training received on preventive measures, factors related to comfort and use of protective eyewear, as well as age influence teacher compliance with COVID-19 preventive measures.

Moderation in all things, except when it comes to workplace safety: Accidents are most likely to occur under moderately hazardous work conditions

AbstractIn this article, we argue that the relationship between workplace hazardousness and accidents is best characterized as an inverted‐U, such that accidents are most likely to occur within moderately hazardous environments. Specifically, whereas highly hazardous work environments are strong situations in which there is a clear need for a high degree of safety behavior, the amount of safety behavior needed to minimize accidents within moderately hazardous environments is more ambiguous. Drawing on self‐regulatory theories of work motivation, we argue that most individuals tend to exhibit a proportional response to hazardousness, such that moderately hazardous environments are met with a moderate degree of safety behavior. However, we demonstrate that proportional responses to hazardousness will ultimately yield an inverted‐U relationship between hazardousness and accidents. Instead, a sharp, non‐linear increase in safety behavior is needed to keep accidents at a low and constant level as hazardousness increases. We present four studies to test our hypotheses. Studies 1 and 2 used archival data to test our hypothesis of an inverted‐U relationship between hazardousness and accidents in natural work settings. Studies 3 and 4 were experiments which replicated this finding, and more importantly, demonstrated that the inverted‐U relationship between hazardousness and accidents was driven by a failure to sharply increase safety behavior in response to small increases in hazardousness. We conclude with a discussion of the implications of these results for the safety literature, particularly the need to educate workers regarding the pattern of safety behavior needed to fully offset environmental hazardousness.

Value Alignment for Advanced Artificial Judicial Intelligence

AbstractThis paper considers challenges resulting from the use of advanced artificial judicial intelligence (AAJI). We argue that these challenges should be considered through the lens of value alignment. Instead of discussing why specific goals and values, such as fairness and nondiscrimination, ought to be implemented, we consider the question of how AAJI can be aligned with goals and values more generally, in order to be reliably integrated into legal and judicial systems. This value alignment framing draws on AI safety and alignment literature to introduce two otherwise neglected considerations for AAJI safety: specification and assurance. We outline diverse research directions and suggest the adoption of assurance and specification mechanisms as the use of AI in the judiciary progresses. While we focus on specification and assurance to illustrate the value of the AI safety and alignment literature, we encourage researchers in law and philosophy to consider what other lessons may be drawn.

Automatic classification of construction safety reports using semi-supervised YAKE-Guided LDA approach

Literature on supervised Machine-Learning (ML) approaches for classifying text-based safety reports for the construction sector has been growing. Recent studies have emphasized the need to build ML approaches that balance high classification accuracy and performance on management criteria, such as resource intensiveness. However, despite being highly accurate, the extensively focused, supervised ML approaches may not perform well on management criteria as many factors contribute to their resource intensiveness. Alternatively, the potential for semi-supervised ML approaches to achieve balanced performance has rarely been explored in the construction safety literature. The current study contributes to the scarce knowledge on semi-supervised ML approaches by demonstrating the applicability of a state-of-the-art semi-supervised learning approach, i.e., Yet, Another Keyword Extractor (YAKE) integrated with Guided Latent Dirichlet Allocation (GLDA) for construction safety report classification. Construction-safety-specific knowledge is extracted as keywords through YAKE, relying on accessible literature with minimal manual intervention. Keywords from YAKE are then seeded in the GLDA model for the automatic classification of safety reports without requiring a large quantity of prelabeled datasets. The YAKE-GLDA classification performance (F1 score of 0.66) is superior to existing unsupervised methods for the benchmark data containing injury narratives from Occupational Health and Safety Administration (OSHA). The YAKE-GLDA approach is also applied to near-miss safety reports from a construction site. The study demonstrates a high degree of generality of the YAKE-GLDA approach through a moderately high F1 score of 0.86 for a few categories in the near-miss data. The current research demonstrates that, unlike the existing supervised approaches, the semi-supervised YAKE-GLDA approach can achieve a novel possibility of consistently achieving reasonably good classification performance across various construction-specific safety datasets yet being resource-efficient. Results from an objective comparative and sensitivity analysis contribute to much-required knowledge-contesting insights into the functioning and applicability of the YAKE-GLDA. The results from the current study will help construction organizations implement and optimize an efficient ML-based knowledge-mining strategy for domains beyond safety and across sites where the availability of a pre-labeled dataset is a significant limitation.

Impact of crosswinds and truck weight on rollover propensity when negotiating combined curves

The share of freight transportation is increasing on Wyoming’s roads. These roads are characterized by challenging mountainous terrain and severe crosswinds. The stability of freight trucks in such conditions is of great concern to transportation agencies. Therefore, high-fidelity vehicle dynamics simulation modeling was implemented to investigate the rollover propensity of trucks navigating curves. Scenarios included various road geometric designs, truck characteristics and wind conditions. A multiple linear regression model was also developed to investigate the impact of key parameters on truck rollover propensity. The modeling results indicated that wind speed and direction were influential factors in terms of truck roll stability. Trucks had a 76% higher chance of rolling over when subjected to 40 mph winds relative to being subjected to 20 mph winds assuming all else was unchanged. This study also demonstrated that the most unfavorable wind direction was not perpendicular (90 degrees) to the truck since the truck would continuously change its orientation when traversing combined horizontal and vertical curves. Its speed would also constantly fluctuate. On the contrary, this study’s results indicated that the 120-degree wind direction was the most critical one. Also, under blowing lateral wind conditions, the gross weight of the truck was found to be a contributing factor to rollover risk. Its impact varied depending on the radius of the horizontal curve the truck was navigating. This critical interaction was ignored in the road safety literature. This study offered new insights about the impacts of truck rollover precursors and, hence, this would lead to the proposition of effective truck safety countermeasures.

Psychosocial safety climate and psychological capital for positive customer behavioral intentions in service organizations

PurposeThe purpose of this paper is to articulate a synergic-mediated model of positive service behaviors enabled by what could be called a “psychosocial resource caravan” for improved customer behavioral intentions to help service organizations especially during coronavirus disease 2019 (COVID-19) crisis.Design/methodology/approachThis paper adopts a multi-level approach and is based on positive organizational behavior and occupational health and safety literature. An empirical study of synergic-mediated model of positive service behaviors has been developed and tested using a quantitative approach.FindingsThis paper offers a theoretical framework proposing that a psychosocially safe work environment (psychosocial safety climate (PSC)) interacts with employees' positive psychological capital (PsyCap) to facilitate positive service behaviors that influence customers' behavioral intentions. As PsyCap and PSC have origin, respectively, in different organizational levels, those both can combine and create a context for positive service encounters. The proposed model has been operationalized and then the reliability and validity of the constructs have been examined. A series of CFAs has been conducted and the fitness of the prosed model was compared to other possible models. The model showed a better fitness compared to the other plausible models. All hypotheses of the model were also significant.Originality/valueThe proposed model integrates positive organizational behavior and occupational health and safety literature to consider the conditions for positive service behaviors. High levels of PsyCap among team members and a psychosocially safe working environment, i.e. PSC can impact customers through positive service behaviors. The articulation of the proposed model presented in this paper invites future empirical research on the synergic nature of psychosocial resources. The paper also suggests some key points to operationalize “psychosocial resource caravan.”

Can family-work conflict influence safety behavior in airline pilots? The mediating role of fatigue and the moderating role of extraversion

Airline pilot safety behavior is vital to inflight safety. Drawing upon the conservation of resources theory, this study examined whether family-work conflict (FWC) would influence airline pilot safety behavior, whether fatigue would mediate the link between FWC and safety behavior, and whether extraversion would play a moderating role in the relationships. Data were obtained by investigating a sample of 331 civil pilots and their supervisors from two Chinese airlines. The results showed that FWC negatively affected safety behavior (including safety compliance and safety participation), and fatigue played a mediating role in these relationships. Furthermore, the findings suggested that higher levels of extraversion mitigated the effect of FWC on fatigue, as well as the effect of FWC on safety compliance and safety participation. These findings demonstrated a deep understanding of the mechanisms by which FWC influences pilots’ safety behavior and contributed to occupational safety literature. Theoretical and practical implications, limitations, and future research directions are provided and discussed.

Teaching cultural safety principles: optometry student perceptions

ABSTRACT Clinical relevance Providing optometry learners with cultural safety training can improve patient safety and health outcomes among Indigenous Peoples. Background Healthcare practitioners require cultural safety training to provide safe eye care to Indigenous Peoples in Canada. Culturally safe care requires optometrists to critically reflect upon their unconscious biases and power differences that impact patient care. Informed by the cultural safety literature and working directly with learners, revisions were made to first and second-year optometry clinic experience courses in a Canadian Doctor of Optometry program. This descriptive study examined student feedback on curricular changes, focused on enhancing cultural safety. Methods An 8-item, anonymous, online survey was offered to all learners (n = 178) enrolled in clinic experience courses at in fall 2021 and winter 2022. The survey addressed student understanding of cultural safety, comfort with self-reflective activities, and course effectiveness in teaching patient-centred care. Six items used a 5-point Likert response scale. Descriptive statistics were analyzed (Wilcoxon and Wilcoxon-Pratt). Two open-ended items were analysed using content analysis for themes. Results Thirty-three surveys were completed. Overall respondents found the clinic experience courses provided effective training in cultural safety and were of professional value. Comfort engaging in self-reflective activities increased (before: mean response 4.0; after: 4.4), and students made connections with societal problems (overall mean 3.5) and with bias/power differential (overall mean 4.0). Suggested changes to support the learning objectives included increased clinic observation, scaffolding these topics in additional courses, and adding relevant literature (e.g. anti-racism) and guest speakers with Indigenous knowledge and experience. Conclusion Optometry learners were favourable about the inclusion of cultural safety concepts in their clinic experience courses. Their feedback points to areas for improvement including deepening course content, and collaborating with Indigenous Peoples in content, course design, and cross-curricular scaffolding.

Patient Safety and the Question of Dignitary Harms.

Patient safety is a central aspect of healthcare quality, focusing on preventable, iatrogenic harm. Harm, in this context, is typically assumed to mean physical injury to patients, often caused by technical error. However, some contributions to the patient safety literature have argued that disrespectful behavior towards patients can cause harm, even when it does not lead to physical injury. This paper investigates the nature of such dignitary harms and explores whether they should be included within the scope of patient safety as a field of practice. We argue that dignitary harms in health care are-at least sometimes-preventable, iatrogenic harms. While we caution against including dignitary harms within the scope of patient safety just because they are relevantly similar to other iatrogenic harms, we suggest that thinking about dignitary harms can help to elucidate the value of patient safety, and to illuminate the evolving relationship between safety and quality.

Connecting tradition with modernity: Safety literature review

Connecting tradition with modernity: Safety literature review

Systemic barriers to reporting work injuries and illnesses in contexts of language barriers

Workers who experience language barriers are at increased risk of work-related injuries and illnesses and face difficulties reporting these health problems to their employer and workers' compensation. In the existing occupational health and safety literature, however, such challenges are often framed in individual-level terms. We identify systemic barriers to reporting among injured workers who experience language barriers within the varying contexts of Ontario and Quebec, Canada. This study merges data from two qualitative studies that investigated experiences with workers' compensation and return-to-work, respectively, for injured workers who experience language barriers. We conducted semi-structured interviews with 39 workers and 70 stakeholders in Ontario and Quebec. Audio recordings were transcribed and coded using NVivo software. The data was analysed thematically and iteratively. Almost all workers (34/39) had filed a claim, though most had initially delayed reporting their injuries or illnesses to their employer or to workers' compensation. Workers faced several obstacles to reporting, including confusion surrounding the cause and severity of injuries and illnesses; lack of information, misinformation, and disinformation about workers' compensation; difficulties accessing and interacting with care providers; fear and insecurity linked to precarity; claim suppression by employers; negative perceptions of, and experiences with, workers' compensation; and lack of supports. Language barriers amplified each of these difficulties, resulting in significant negative impacts in economic, health, and claim areas. Improving the linguistic and cultural competence of organizations and their representatives is insufficient to address under-reporting among workers who experience language barriers. Efforts to improve timely reporting must tackle the policies and practices that motivate and enable under-reporting for workers, physicians, and employers.

A meta-analysis of leadership and workplace safety: Examining relative importance, contextual contingencies, and methodological moderators.

Given the high human and economic costs of workplace safety, researchers and practitioners have paid increasing attention to how leadership behaviors relate to workplace safety. Previous research has demonstrated that leadership behaviors are important for workplace safety. In this meta-analysis, we extend our understanding of the leadership-workplace safety relationship by (a) examining the associations between a broader range of five leadership categories-change-oriented, relational-oriented, task-oriented, passive, and destructive-and seven workplace safety variables; (b) investigating the relative importance of these leadership categories in explaining variance in these workplace safety variables; and (c) testing contextual and methodological contingencies of the leadership-workplace safety relationship. Using effect sizes from 194 samples (N = 104,364), we find that although leadership behaviors are associated with workplace safety, the leadership categories vary considerably in their relative importance. Task-oriented leadership followed by relational-oriented leadership emerge as the most important contributors to workplace safety. Change-oriented leadership (which includes transformational leadership) does not emerge as the largest contributor for any of the seven tested safety variables, despite it being the most frequently examined leadership model in the workplace safety literature. Effectiveness of leadership behaviors in relation to workplace safety varies by national culture power distance, industry risk, workforce age, as well as by contextualized forms of leadership (i.e., safety-specific vs. generalized). Finally, there is meta-analytic evidence for publication bias and common-method variance. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

COVID-19 related negative emotions and emotional suppression are associated with greater risk perceptions among emergency nurses: A cross-sectional study

BackgroundAs the COVID-19 pandemic began, frontline nurses experienced many emotions as they faced risks relevant to both patients (e.g., making errors resulting in patient harm) and themselves (e.g., becoming infected with COVID-19). Although emotions are often neglected in the patient safety literature, research in affective science suggests that emotions may significantly impact nurses’ perceptions of risk, which can have downstream consequences. Further, the use of chronic emotion regulation strategies that are known to differ in adaptability and effectiveness (i.e., emotional suppression, reappraisal) can impact risk perceptions. ObjectiveTo investigate the relationship between nurses’ emotional experiences in response to the pandemic and their estimates of how likely they would be to experience adverse outcomes related to both patients and themselves within the next six months. Additionally, we investigated the extent to which the use of suppression and reappraisal processes to manage emotions are associated with these risk perceptions. DesignCross-sectional survey. SettingOnline survey distributed via email to emergency nurses at eight hospitals in the northeastern United States during fall 2020. Participants132 emergency nurses (Mage = 37.05; 81.1% Female; 89.4% White). MethodsNurses reported the extent to which they experienced a variety of positive (e.g., hope, optimism) and negative (e.g., fear, sadness) emotions in response to the COVID-19 pandemic, and reported their perceptions of risk to both patients and themselves. Nurses also completed the Emotion Regulation Questionnaire, a measure of chronic tendencies to engage in emotional suppression and reappraisal. Immediately prior to providing data for this study, nurses completed an unrelated decision-making study. ResultsNurses’ negative emotions in response to COVID-19 were associated with greater perceptions of both patient safety risks (b = 0.31, p < .001) and personal risks (b = 0.34, p < .001). The relationships between positive emotions and risk perceptions were not statistically significant (all p values > 0.66). Greater chronic tendencies to suppress emotions uniquely predicted greater perceptions of patient safety risks (b = 2.91, p = .036) and personal risks (b = 2.87, p = .040) among nurses; however, no statistically significant relationships with reappraisal emerged (all p values > 0.16). ConclusionsUnderstanding factors that influence perceptions of risk are important, given that these perceptions can motivate behaviours that may adversely impact patient safety. Such an understanding is essential to inform the development of interventions to mitigate threats to patient safety that emerge from nurses’ negative emotional experiences and their use of different emotion regulation strategies. Tweetable abstractCovid-related negative emotions and emotional suppression are associated with greater patient and personal risk perceptions among emergency nurses @lindamisbell @Nathan_Huff_1

Further compelling evidence for safety-in-numbers: It is more than meets the eye

In the extant road safety literature, estimating safety-in-numbers is dominated by conventional cross-sectional methods in which active mode (pedestrian or cyclist) volume together with motorised traffic volume are present in regression models explaining active mode safety directly. There is “direct” evidence for safety-in-numbers when the coefficient associated with active mode volume is negative (safety improves as volume increases) or when it is smaller than one (safety decreases at a lower rate compared to the rate of increase in active mode volume). In this article we extend the concept of safety-in-numbers in the traffic safety field, introducing “indirect” safety-in-numbers, which constitutes a new form of evidence for this phenomenon. We provide empirical evidence to support this, discussing that using an approach based on heterogeneity in mean modelling–a form of random parameters (slopes) models–it is possible to reveal “indirect” safety-in-numbers effects. Therefore, such models can reveal further compelling evidence for safety-in-numbers. Accurate knowledge of safety-in-numbers effects (both direct and indirect) and their underlying mechanisms can help provide robust motives for promoting active travel and will have valuable implications for the design of road safety interventions.

Medication safety in the perioperative setting: A comparison of methods for detecting medication errors and adverse medication events.

The purpose of this study was to evaluate perioperative medication-related incidents (medication errors (MEs) and/or adverse medication events (AMEs)) identified by 2 different reporting methods (self-report and direct observation), and to compare the types and severity of incidents identified by each method. We compared perioperative medication-related incidents identified by direct observation in Nanji et al's 2016 study[1] to those identified by self-report via a facilitated incident reporting system at the same 1046-bed tertiary care academic medical center during the same 8-month period. Incidents, including MEs and AMEs were classified by type and severity. In 277 operations involving 3671 medication administrations, 193 MEs and/or AMEs were observed (5.3% incident rate). While none of the observed incidents were self-reported, 10 separate medication-related incidents were self-reported from different (unobserved) operations that occurred during the same time period, which involved a total of 21,576 operations and approximately 280,488 medication administrations (0.004% self-reported incident rate). The distribution of incidents (ME, AME, or both) did not differ by direct observation versus self-report methodology. The types of MEs identified by direct observation differed from those identified by self-report (P = .005). Specifically, the most frequent types of MEs identified by direct observation were labeling errors (N = 37; 24.2%), wrong dose errors (N = 35; 22.9%) and errors of omission (N = 27; 17.6%). The most frequent types of MEs identified by self-report were wrong dose (N = 5; 50%) and wrong medication (N = 4; 40%). The severity of incidents identified by direct observation and self-report differed, with self-reported incidents having a higher average severity (P < .001). The procedure types associated with medication-related incidents did not differ by direct observation versus self-report methodology. Direct observation captured many more perioperative medication-related incidents than self-report. The ME types identified and their severity differed between the 2 methods, with a higher average incident severity in the self-reported data.

Cambodian American Listening as Memory Work

Cambodian American Listening as Memory Work

Is school safety mainly about school shootings? Research-informed guidance for the field

School violence, and particularly, school shootings, remain a serious concern among parents, community members, educators, and governmental leadership at the local, state, and national levels. While school shootings periodically dominate media coverage of school safety issues, schools are among the safest places for students in the community. This article unpacks key issues central to the field. We provide an overview of school violence program coherence, curriculum alignment, staff development, support systems to meet student needs, and related capacity issues. The article also explores issues not commonly included in the school safety literature such as gangs and weapons in school and the conflation of mental health problems and violent behavior. We offer take-away implications from the extant literature that is relevant for schools.

Integrating Policy into School Safety Theory and Research

Multiple fields including social work, public health, psychology, and education have been researching school safety issues for the past 40 years. Findings from research and intervention have been a driving force in school safety policy change. Likewise, policy and funding patterns created have dramatically altered how and what school safety researchers study. Yet school safety policy has not been the focus of empirical studies in social work or other research fields as either independent or dependent variables. Based on prior work and current school safety policy issues, the authors created a new theoretical ecological model to generate a conceptual policy-focused model of school safety. They identified thematic, conceptual, methodological, and analytic gaps in the school safety literature using the new model as a guide. Examples from policy and empirical work are given to elucidate the conceptual model. Suggestions are made for researchers and universities to close the gap between school safety research and policy.

Exploring the temporal variability of the factors affecting driver injury severity by body region employing a hybrid econometric approach

The current study contributes to safety literature by incorporating the influence of temporal factors (observed and unobserved) within a multivariate model system for medical professional generated body region specific injury severity score. For this purpose, we adopt a hybrid econometric modeling approach that accommodates for the unobserved factors using two mechanisms. First, we parameterize unobserved temporal factor variation through the customization of the variance by time cohort (heteroscedasticity). Second, the common unobserved factors affecting severity across various body regions is accommodated through traditional random parameter consideration process. The proposed model system is estimated using data drawn from the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) database for the time cohorts 2003, 2006, 2009, 2012, and 2015. For the current analysis, we consider 6-point Abbreviated Injury Scale (AIS) for eight body regions (head, face, neck, abdomen, thorax, spine, lower extremity, and upper extremity). The proposed model system offers interesting insights on body region severity evolution over time. The model estimation is augmented with post-estimation exercises including hold-out sample validation analysis, illustrative policy analysis and extensive elasticity effect computation.