High Rates Of Engagement Research Articles

Engagement, Advance Care Planning, and Hospice Use in a Telephonic Nurse-Led Palliative Care Program for Persons Living with Advanced Cancer.

Persons living with advanced cancer have intensive symptoms and psychosocial needs that often result in visits to the Emergency Department (ED). We report on program engagement, advance care planning (ACP), and hospice use for a 6-month longitudinal nurse-led, telephonic palliative care intervention for patients with advanced cancer as part of a larger randomized trial. Patients 50 years and older with metastatic solid tumors were recruited from 18 EDs and randomized to receive nursing calls focused on ACP, symptom management, and care coordination or specialty outpatient palliative care (ClinicialTrials.gov: NCT03325985). One hundred and five (50%) graduated from the 6-month program, 54 (26%) died or enrolled in hospice, 40 (19%) were lost to follow-up, and 19 (9%) withdrew prior to program completion. In a Cox proportional hazard regression, withdrawn subjects were more likely to be white and have a low symptom burden compared to those who did not withdraw. Two hundred eighteen persons living with advanced cancer were enrolled in the nursing arm, and 182 of those (83%) completed some ACP. Of the subjects who died, 43/54 (80%) enrolled in hospice. Our program demonstrated high rates of engagement, ACP, and hospice enrollment. Enrolling subjects with a high symptom burden may result in even greater program engagement.

Digital Health Solutions for Community-Based Control of Diabetes During COVID-19 Pandemic: A Scoping Review of Implementation Outcomes.

The COVID-19 pandemic has added to the pre-existing challenges of diabetes management in many countries. It has accelerated the wider use of digital health solutions which have tremendous potential to improve health outcomes for people with diabetes. However, little is known about the attributes and the implementation of these solutions. To identify and describe digital health solutions for community-based diabetes management and to highlight their key implementation outcomes. We searched Ovid Medline, CINAHL, Embase, PsycINFO, and Web of Science for relevant articles. A purposive search was also used to identify grey literature. Articles that described digital health solutions that aimed to improve community-based diabetes management were included in this review. We applied a thematic synthesis of evidence to describe the characteristics of digital health solutions, and to summarize their key implementation outcomes. We included 15 articles that reported digital health solutions that primarily focused on community-based diabetes management. Nine of the 15 innovations involved were mobile applications and/or web-based platforms, and five were based on social media platforms. The majority of the digital health solutions were used for diabetes education and support. High engagement, utilization, and satisfaction rates with digital health solutions were observed. The use of digital health solutions was also associated with improvement in self-management, taking medication, and reduction in glycated hemoglobin (HbA1c) levels. COVID-19 triggered digital health solutions have tremendous potential to improve health outcomes for people with diabetes. Further studies are needed to evaluate the sustainability and scale-up of these solutions.

The relationship of online pre-recorded neurology mini-lectures to medical student assessment: a pilot study

IntroductioneLearning has become an essential part of medical education. However, there is a lack of published research on student engagement with online pre-recorded mini-lectures and its relation to assessment. The aim of this pilot study is to explore the relationship between newly introduced neurology pre-recorded mini-lectures and undergraduate medical students engagement and assessment. This may encourage the wider use of mini-lectures in undergraduate medical curricula.MethodsThe engagement of medical students with 48 online pre-recorded neurology mini-lectures was assessed through a Learning Management System. To measure engagement, data was stratified according to the number of watched/downloaded mini-lectures. A point system was used (out of 5): − 1 point = watching/downloading 0–10 mini-lectures, 2 points = watching/downloading 11–20 mini-lectures, 3 points = watching/downloading 21–30 mini-lectures, 4 points = watching/downloading 31–40 mini-lectures and, 5 points = watching/downloading 41–48 mini-lectures. The students’ engagement was correlated with their neurology assessments [Objective Structured Clinical Examination (OSCE), and knowledge-based assessment 10 Multiple Choice Questions (MCQs) and one 10-mark Short Answer Question, (SAQ)], internal medicine grade and annual grade point average (GPA) using the Pearson correlation coefficient.ResultsThe mean engagement of 34, Year 5, medical students is 3.9/5. There is a significant positive correlation between engagement and internal medicine grade (r = 0.35, p = 0.044). There is a moderate correlation between engagement and neurology OSCE (r = 0.23), annual Year 5 GPA (r = 0.23), neurology knowledge-based score (r = 0.22) and composite neurology knowledge/OSCE (r = 0.27). The knowledge-based assessment included SAQ and MCQs: there was a moderate correlation with SAQ (r = 0.30), but a weak negative correlation with the MCQs (r =-0.11). Sub-groups analysis comparing the top- and low- or non- engaging students made these weaker correlations stronger.ConclusionThis pilot study indicates a high rate of engagement with an online pre-recorded mini-lectures resource and evidence of moderate correlation between engagement and assessment. Online pre-recorded mini-lectures should be used more in delivering the curriculum contents of the clinical clerkships. Further studies are needed to evaluate the relation and the impact of the mini-lectures on assessment.

The impact of road traffic context on secondary task engagement while driving.

Driver distraction has been recognized for a long time as a significant road safety issue. It has been consistently reported that drivers spend considerable time engaged in activities that are secondary to the driving task. The temporary diversion of attention from safety-critical driving tasks has often been associated with various adverse driving outcomes, from minor driving errors to serious motor vehicle crashes. This study explores the role of the driving context on a driver's decision to engage in secondary activities non-critical to the driving task. The study utilises the Naturalistic Engagement in Secondary Tasks (NEST) dataset, a complementary dataset derived from the SHRP2 naturalistic dataset, the most extensive naturalistic study to date. An initial exploratory analysis is conducted to identify patterns of secondary task engagements in relation to context variables. Maximum likelihood Chi-square tests were applied to test for differences in engagement between types of driver distraction for the selected contextual variables. Pearson residual graphs were employed as a supplementary method to visually depict the residuals that constitute the chi-square statistic.Lastly, a two-step cluster analysis was conducted to identify common execution scenarios among secondary tasks. The exploratory analysis revealed interesting behavioral trends among drivers, with higher engagement rates in left curves compared to right curves, while driving uphill compared to driving downhill, in low-density traffic scenarios compared to high-density traffic scenarios, and during afternoon periods compared to morning periods. Significant differences in engagement were found among secondary tasks in relation to locality, speed, and roadway design. The clustering analysis showed no significant associations between driving scenarios of similar characteristics and the type of secondary activity executed. Overall, the findings confirm that the road traffic environment can influence how car drivers engage in distracted driving behavior.

Integration of evolutionary algorithm in an agent-oriented approach for an adaptive e-learning

This paper describes an agent-oriented approach that aims to create learning situations by solving problems. The proposed system is designed as a multi-agent that organizes interfaces, coordinators, sources of information, and mobiles. The objective of this approach is to get learners to solve a problem that leads them to get engaged in several learning activities, chosen according to their level of knowledge and preferences in order to ensure adaptive learning and reduce the rate of learner abundance in an e-learning system. The search for learning activities procedure is based on evolutionary algorithms typically a genetic algorithm, to offer learners the optimal solution adapted to their profiles and ensure a resolution of the proposed learning problem. In terms of results, we have adopted “immigration strategies” to improve the performance of the genetic algorithm. To show the effectiveness of the proposed approach we have made a comparative study with other artificial intelligence optimization methods. We conducted a real experiment with primary school learners in order to test the effectiveness of the proposed approach and to set up its functioning. The experiment results showed a high rate of success and engagement among the learners who followed the proposed adaptive learning scenario.

Engagement and Utilization of a Complete Remote Digital Care Program for Musculoskeletal Pain Management in Urban and Rural Areas Across the United States: Longitudinal Cohort Study.

Musculoskeletal (MSK) conditions are the number one cause of disability worldwide. Digital care programs (DCPs) for MSK pain management have arisen as alternative care delivery models to circumvent challenges in accessibility of conventional therapy. Despite the potential of DCPs to reduce inequities in accessing care, the outcomes of such interventions in rural and urban populations have yet to be studied. The aim of this study was to assess the impact of urban or rural residency on engagement and clinical outcomes after a multimodal DCP for MSK pain. This study consists of an ad hoc analysis of a decentralized single-arm investigation into engagement and clinical-related outcomes after a multimodal DCP in patients with MSK conditions. Patients were coded according to their zip codes to a specific rural-urban commuting area code and grouped into rural and urban cohorts. Changes in their engagement and clinical outcomes from baseline to program end were assessed. Latent growth curve analysis was performed to estimate change trajectories adjusting for the following covariates: age, gender, BMI, employment status, and pain acuity. Outcomes included engagement, self-reported pain, and the results of the Generalized Anxiety Disorder 7-item, Patient Health Questionnaire 9-item, and Work Productivity and Activity Impairment scales. A minimum clinically important difference (MCID) of 30% was considered for pain. Patients with urban and rural residency across the United States participated in the program (n=9992). A 73.8% (7378/9992) completion rate was observed. Both groups reported high satisfaction scores and similar engagement with exercise sessions, with rural residents showing higher engagement with educational content (P<.001) and higher program completion rates (P=.02). All groups showed a significant improvement in all clinical outcomes, including pain, mental health, and work productivity, without statistically significant intergroup differences. The percentage of patients meeting the MCID was similar in both groups (urban: 67.1%, rural: 68.3%; P=.30). This study advocates for the utility of a DCP in improving access to MSK care in urban and rural areas alike, showcasing its potential to promote health equity. High engagement, satisfaction, and completion rates were noted in both groups, as well as significant improvements in clinical outcomes. ClinicalTrials.gov NCT04092946; https://clinicaltrials.gov/ct2/show/NCT04092946.

Effectiveness of Substance Use Navigation for Emergency Department Patients with Substance Use Disorders: An Implementation Study.

We implemented a whole person care-informed intervention delivered by substance use navigators (SUN) for emergency department (ED) patients with substance use disorders. This was an implementation study of adult patients discharged from 3 public hospital EDs between September 1, 2021 through January 31, 2022 with cocaine, methamphetamine, alcohol, and opioid use-related diagnoses. The primary effectiveness outcome was treatment engagement within 30 days of ED discharge among patients with and without the SUN intervention. We used logistic regression and nearest neighbor propensity score matching without replacement to control for confounding effects. There were 1,328 patients in the cohort, and 119 (9.0%) received the SUN intervention; 50.4% of patients in the SUN intervention group and 15.9% of patients without the SUN intervention were engaged in outpatient treatment within 30 days of ED discharge (difference in proportions: 34.5%, 95% confidence interval [CI] 25.3% to 43.8%). In the unadjusted analysis, the SUN intervention was associated with higher rates of treatment engagement after ED discharge for patients with alcohol, opioid, and cocaine-related diagnoses; patients with methamphetamine-related diagnoses had low engagement rates with or without the SUN intervention. In addition, the SUN intervention was associated with higher odds of treatment engagement in the multivariable model (aOR 3.7, 95% CI 2.4 to 5.8) and in the propensity score-matched analysis (OR 2.1, 95% CI 1.2 to 3.5). A whole person care-informed intervention delivered by SUNs for ED patients with substance use disorders was strongly associated with higher engagement rates in addiction treatment after discharge.

Development and cross-validation of a veterans mental health risk factor screen.

VA primary care patients are routinely screened for current symptoms of PTSD, depression, and alcohol disorders, but many who screen positive do not engage in care. In addition to stigma about mental disorders and a high value on autonomy, some veterans may not seek care because of uncertainty about whether they need treatment to recover. A screen for mental health risk could provide an alternative motivation for patients to engage in care. Data from samples of veterans and traumatic injury survivors were analyzed to identify mental health risk factors that are characteristics of individuals or stressors or of post-trauma, post-deployment, or post-military service resources, experiences, or responses. Twelve risk factors were strongly related to PTSD (r > .50): current PTSD, depression, dissociation, negative thinking, and emotional lability symptoms, life stress, relationship stress, social constraints, and deployment experiences of a difficult environment, concerns about life and family, perceived threat, and moral injury. Items assessing each of these risk factors were selected and their validity to prospectively predict PTSD and/or depression 6 months later was assessed in a new sample of 232 VA primary care patients. Twelve items assessing dissociation, emotional lability, life stress, and moral injury correctly classified 86% of those who later had elevated PTSD and/or depression symptoms (sensitivity) and 75% of those whose later symptoms were not elevated (specificity). Performance was also very good for 110 veterans who identified as members of ethnic/racial minorities. Mental health status was prospectively predicted in VA primary care patients with high accuracy using a screen that is brief, easy to administer, score, and interpret, and fits well into VA's integrated primary care. When care is readily accessible, appealing to veterans, and not perceived as stigmatizing, information about mental health risk may result in higher rates of engagement than information about current mental disorder status.

Early detection of depression using a conversational AI bot: A non-clinical trial.

Artificial intelligence (AI) has gained momentum in behavioural health interventions in recent years. However, a limited number of studies use or apply such methodologies in the early detection of depression. A large population needing psychological-intervention is left unidentified due to barriers such as cost, location, stigma and a global shortage of health workers. Therefore, it is essential to develop a mass screening integrative approach that can identify people with depression at its early stage to avoid a potential crisis. This study aims to understand the feasibility and efficacy of using AI-enabled chatbots in the early detection of depression. We use Dialogflow as a conversation interface to build a Depression Analysisn (DEPRA) chatbot. A structured and authoritative early detection depression interview guide, which contains 27 questions combining the structured interview guide for the Hamilton Depression Scale (SIGH-D) and the inventory of depressive symptomatology (IDS-C), underpins the design of the conversation flow. To attain better accuracy and a wide variety of responses, we train Dialogflow with the utterances collected from a focus group of 10 people. The occupation of the focus group members included academics and HDR candidates who are conscious, vigilant and have a clear understanding of the questions. In addition, DEPRA is integrated with a social media platform to provide practical access to all the participants. For the non-clinical trial, we recruited 50 participants aged between 18 and 80 from across Australia. To evaluate the practicability and performance of DEPRA, we also asked participants to submit a user satisfaction survey at the end of the conversation. A sample of 50 participants, with an average age of 34.7 years, completed this non-clinical trial. More than half of the participants (54%) are male and the major ethnicities are Asian (63%), Middle Eastern (25%), and others 12%. The first group comprises professional academic staff and HDR candidates, the second and third groups comprise relatives, friends, and volunteers who were recruited via social media promotions. DEPRA uses two scientific scoring systems, QIDS-SR and IDS-SR to verify the results of early depression detection. As the results indicate, both scoring systems return a similar outcome with slight variations for different depression levels. According to IDS-SR, 30% of participants were healthy, 14% mild, 22% moderate, 14% severe, and 20% very severe. QIDS-SR suggests 32% were healthy, 18% mild, 10% moderate, 18% severe, and 22% very severe. Furthermore, the overall satisfaction rate of using DEPRA was 79% indicating that the participants had a high rate of user satisfaction and engagement. DEPRA shows promises as a feasible option for developing a mass screening integrated approach for early detection of depression. Although the chatbot is not intended to replace the functionality of mental health professionals, it does show promise as a means of assisting with automation and concealed communication with verified scoring systems.

Feasibility of Implementation and the Impact of a Digital Prehabilitation Service in Patients Undergoing Treatment for Oesophago-Gastric Cancer.

Home-based and supervised prehabilitation programmes are shown to have a positive impact on outcomes in patients with oesophago-gastric (OG) cancer. The primary aim of this study was to establish the feasibility of delivering a digital prehabilitation service. Patients undergoing treatment for OG cancer with curative intent were recruited into the study. During the COVID-19 pandemic, patients were offered a digital prehabilitation service. Following the lifting of COVID-19 restrictions, patients were also offered both a hybrid clinic-based in-person service and a digital service. Implementation and clinical metrics from the two prehabilitation models were compared. 31 of 41 patients accepted the digital service (75%). Of the people who started the digital programme, 3 dropped out (10%). Compliance with the weekly touchpoints was 86%, and the median length of programme was 12 weeks. Twenty-six patients enrolled in the in-person service. Two patients dropped out (10%). Average compliance to weekly touchpoints was 71%, and the median length of programme was 10 weeks. In the digital group, sit to stand (STS) increased from 14.5 (IQR 10.5-15.5) to 16 (IQR 16-22); p = 0.02. Median heart rate recovery (HRR) increased from 10.5 (IQR 7.5-14) to 15.5 (IQR 11-20) bpm; p = 0.24. There was a significant drop in distress (median 3 (IQR 0-5) to 1 (IQR 0-2); p = 0.04) and a small drop in anxiety (median 3 (0-5) to 2 (0-3); p = 0.22). There was no difference in the postoperative complication rate and length of hospital stay between the two groups. This study has shown that digital prehabilitation can be delivered effectively to patients with OG cancer, with high engagement and retention rates. We observed improvements in some physical and psychological parameters with the digital service, with comparable clinical outcomes to the in-person service.

Local Community Care-based Activism and Civic Engagement Among Canadian Arab Youth

Youth today are engaging in civic-oriented activities in ways that differ from previous generations. Civic engagement refers to volunteerism and service-oriented activities and programs that expand community, ground social networks, help people, and make civil society possible. We find from this study that Canadian Arab youth give considerable service back to their communities, especially within the communities of their own cultural milieu, but also significantly within their wider Canadian municipalities, and that, on balance, they have higher rates of engagement than the wider Canadian youth population. In this paper, we problematize and substantiate many arguments about ethnic minority youth political participation through an analysis of the local community-care activism and civic engagement of Canadian Arab youth.

Influence of the exercise intensity during EA Sport Active 2 on physiology and psychology variables

Purpose.Exergames purportedly aim to gamify physical activity, achieving both the high engagement rates found in video games and the health benefits derived from regular exercise. Therefore, this study sought to verify the influence of the EA&lt;sup&gt;®&lt;/sup&gt; Active Sport 2&lt;sup&gt;®&lt;/sup&gt; game level on heart rate, perceived exertion and future intention to play, affection, and fun.Methods.28 individuals (19 men and 9 women) aged between 19 and 25 years, students, participated in the study. The volunteers had their body composition measured and completed an exercise preference and tolerance questionnaire. On the second visit, the participants had their resting heart rate measured and, subsequently, underwent a maximum incremental test to determine the ventilatory thresholds. The third and fifth visits tested different exercise intensities (light, moderate and strong) determined by EA Active Sport, for PlayStation 3. To minimise the risk of bias, the sessions were randomised. Heart rate, affection, perceived exertion, motivation and future intention to play were measured in game sessions.Results.During exercise, the mean heart rate (HR) at rest was below the heart rate reserve (HRres) and the ventilatory threshold 1 (LV1) in low-intensity exercise and in the lower limit of the heavy domain for moderate and Active Game High. The assessment of perceived exertion (RPE) and affection did not show differences between the different intensities of the game.Conclusions.The EA Active Sport 2 differentiates light from moderate and high-intensity exercise, but not between moderate and high game intensities. Affection, RPE, intention to play, and enjoyment did not differ between game intensities.

Understanding adolescent esports bettors: Are they a homogeneous group?

With the rapid rise of competitive video gaming (esports), increased attention has been placed on understanding the profiles of youth who wager on esports. With adolescents being at increased risk of gambling problems and endorsing high rates of past year engagement in video games, there is a need for research investigating psychological and social correlates of adolescent esports bettors and to identify whether youth who engage in esports betting are a homogenous group. Survey responses were collected from 5,997 high-school students (48.4 % male, Mage = 14.7 years [SD = 1.6], age range 12–17) from Wood County, Ohio, United States. A latent class analysis was conducted to identify subgroups of esports bettors based on self-reported measures of gambling frequency, risk for problem gambling, gaming frequency, disordered gaming, preference for virtual life and risky loot box use. Results indicated that 5.5 % of the sample reported esports betting over the past year. Four classes of esports bettors were identified which were indicative of a group of low-risk esports bettors, a group of esports bettors at risk of gaming problems, a group of esports bettors at risk of gambling problems, and a group of esports bettors at high risk of both gambling and gaming problems. Although no significant differences based on sex and age were noted between the classes, differences were noted in experienced childhood adversity, mental health symptoms and problem behavior severity. Results are discussed in line with previous findings relevant to adolescent and adult esports betting.

COVID-19 Messaging on Social Media for American Indian and Alaska Native Communities: Thematic Analysis of Audience Reach and Web Behavior.

During the COVID-19 pandemic, tribal and health organizations used social media to rapidly disseminate public health guidance highlighting protective behaviors such as masking and vaccination to mitigate the pandemic's disproportionate burden on American Indian and Alaska Native (AI/AN) communities. Seeking to provide guidance for future communication campaigns prioritizing AI/AN audiences, this study aimed to identify Twitter post characteristics associated with higher performance, measured by audience reach (impressions) and web behavior (engagement rate). We analyzed Twitter posts published by a campaign by the Johns Hopkins Center for Indigenous Health from July 2020 to June 2021. Qualitative analysis was informed by in-depth interviews with members of a Tribal Advisory Board and thematically organized according to the Health Belief Model. A general linearized model was used to analyze associations between Twitter post themes, impressions, and engagement rates. The campaign published 162 Twitter messages, which organically generated 425,834 impressions and 6016 engagements. Iterative analysis of these Twitter posts identified 10 unique themes under theory- and culture-related categories of framing knowledge, cultural messaging, normalizing mitigation strategies, and interactive opportunities, which were corroborated by interviews with Tribal Advisory Board members. Statistical analysis of Twitter impressions and engagement rate by theme demonstrated that posts featuring culturally resonant community role models (P=.02), promoting web-based events (P=.002), and with messaging as part of Twitter Chats (P<.001) were likely to generate higher impressions. In the adjusted analysis controlling for the date of posting, only the promotion of web-based events (P=.003) and Twitter Chat messaging (P=.01) remained significant. Visual, explanatory posts promoting self-efficacy (P=.01; P=.01) and humorous posts (P=.02; P=.01) were the most likely to generate high-engagement rates in both the adjusted and unadjusted analysis. Results from the 1-year Twitter campaign provide lessons to inform organizations designing social media messages to reach and engage AI/AN social media audiences. The use of interactive events, instructional graphics, and Indigenous humor are promising practices to engage community members, potentially opening audiences to receiving important and time-sensitive guidance.

Implementation and Evaluation of a Wraparound Virtual Care Program for Children with Medical Complexity.

Objectives: Children and adolescents with medical complexity benefit from care coordination and specialized pediatric care, but many access barriers exist. We implemented a virtual wraparound model to support patients with medical complexity and their families and used an economic framework to measure outcomes. Methods: Children with medical complexity were identified and enrolled in a virtual complex care program with a dedicated multidisciplinary team, which provided care coordination, education, parental support, acute care triage, and virtual visits. A retrospective pre- and postanalysis of data obtained from the Hospital Industry Data Institute (HIDI) database measured inpatient, outpatient, and emergency department (ED) utilization and charges before implementation and during the 2-year program. Results: Eighty (n = 80) children were included in the economic evaluation, and 75 had sufficient data for analysis. Compared to the 12 months before enrollment, patients had a 35.3% reduction in hospitalizations (p = 0.0268), a 43.9% reduction in emergency visits (p = 0.0005), and a 16.9% reduction in overall charges (p = 0.1449). Parents expressed a high degree of satisfaction, with a 70% response rate and 90% satisfaction rate. Conclusions: We implemented a virtual care model to provide in-home support and care coordination for medically complex children and adolescents and used an economic framework to assess changes in utilization and cost. The program had high engagement rates and parent satisfaction, and a pre/postanalysis demonstrated statistically significant reduction in hospitalizations and ED visits for this high-cost population. Further economic evaluation is needed to determine sustainability of this model in a value-based payment system.

Effectiveness of implementing a Graduated Driver Licensing (GDL) law among young Serbian drivers

Introduction: Young novice drivers have higher rates of engagement in road crashes worldwide, often owing to unfavorable attitudes toward road safety or lack of knowledge, experience, and risk consciousness. However, the implementation of graduated driver licensing (GDL) systems has proven effective in reducing the high incidence of young drivers involved in crashes. Method: The purpose of this study was to compare the change in driving outcomes (e.g., attitudes toward traffic safety, behavior patterns while driving, risk assessment in traffic, assessment of personal driving skills, and involvement in traffic crashes) of young drivers prior to and following the implementation of a GDL law. Respondents (n = 642) completed a battery of questions, including a driver attitudes questionnaire (Behaviour of Young Novice Drivers Scale), a self-assessed driving ability questionnaire, and a risk perception questionnaire. Of the total sample size, 324 drivers passed the old system of training driver’s license candidates, and 318 drivers passed the new GDL system. Results: The results showed that drivers licensed with GDL reported safer attitudes toward traffic rule violations and speed, and higher levels of safety orientation with regard to their driving abilities. They also reported much higher levels of risk perception and lower exposure to risky situations (risky driving exposure). There were no differences between GDL drivers and non-GDL drivers in terms of self-reported crashes or transient or fixed violations. In addition, GDL was not related to the number of traffic crashes, the number of fatalities, or serious and slight injuries in crashes involving young drivers in crashes obtained from official records. Conclusions: The results suggest that GDL contributed to the improvement of drivers’ attitudes and understanding of risk but did not contribute to significant changes in the behavior of young drivers and traffic crashes. In addition, the GDL program in Serbia only ranks fair on the Insurance Institute for Highway Safety (IIHS) scale. Strengthening the GDL program in Serbia with additional components in line with GDL programs rated as good by the IIHS scale could improve the safety of young and novice drivers in traffic.

An empirical survey on prevalence and demographic differences in academic dishonesty among undergraduates from four public universities in China

PurposeThis empirical survey is conducted to investigate the prevalence rate of academic dishonesty (AD) in examinations and assignments among undergraduates. The study compared the difference in admitted behaviours of academic dishonesty between male and female students comprising second-year, third-year and fourth-year students from the discipline of business, engineering, information technology (IT) and education.Design/methodology/approachA cross-sectional study was utilized in this study and collected data via the online questionnaire. A total of 1,624 respondents participated from four public universities of four provinces in China Mainland.FindingsThe findings showed that the proportion of respondents from China participating in AD is between 15.4 and 51.7%. The findings showed that more than two-thirds of the respondents stated involved dishonesty in examinations and assignments at least once during the previous academic year. In addition, male and female undergraduates in second-year, third-year and fourth-year showed statistically significant differences in dishonest behaviours. Specifically, the male/senior students were more involved in dishonest behaviours than the females/sophomores.Originality/valueUnlike previous studies, this study found that discipline in the Chinese context was not a significant demographic predictor of dishonesty. Although not significantly different, the respondents majoring in business reported a high engagement rate of dishonesty, followed by engineering and information technology undergraduates, but education undergraduates revealed the lowest engagement rate of dishonesty. The target integrity education should be imparted among male and senior students.

Using Artificial Intelligence to Enhance Ongoing Psychological Interventions for Emotional Problems in Real- or Close to Real-Time: A Systematic Review.

Emotional disorders are the most common mental disorders globally. Psychological treatments have been found to be useful for a significant number of cases, but up to 40% of patients do not respond to psychotherapy as expected. Artificial intelligence (AI) methods might enhance psychotherapy by providing therapists and patients with real- or close to real-time recommendations according to the patient’s response to treatment. The goal of this investigation is to systematically review the evidence on the use of AI-based methods to enhance outcomes in psychological interventions in real-time or close to real-time. The search included studies indexed in the electronic databases Scopus, Pubmed, Web of Science, and Cochrane Library. The terms used for the electronic search included variations of the words “psychotherapy”, “artificial intelligence”, and “emotional disorders”. From the 85 full texts assessed, only 10 studies met our eligibility criteria. In these, the most frequently used AI technique was conversational AI agents, which are chatbots based on software that can be accessed online with a computer or a smartphone. Overall, the reviewed investigations indicated significant positive consequences of using AI to enhance psychotherapy and reduce clinical symptomatology. Additionally, most studies reported high satisfaction, engagement, and retention rates when implementing AI to enhance psychotherapy in real- or close to real-time. Despite the potential of AI to make interventions more flexible and tailored to patients’ needs, more methodologically robust studies are needed.

The Effect of Access to Training and Development Opportunities, on Rates of Work Engagement, Within the U.S. Federal Workforce

This study aims to identify how the access to training and development opportunities influence rates of work engagement in the U.S. federal workforce. Organizations with high rates of work engagement tend to be happier and more efficient than those with lower rates of work engagement. Studies have evidenced that organizational and managerial characteristics can promote work engagement among employees. Through the lens of high-performance work systems and the job demands-resource theory, access to training and development is used as both a high-performance work practice and a job resource to explore its effect on work engagement. Data were drawn from the 2017 Federal Employee Viewpoint Survey, a nationally representative sample of U.S. federal employees. By employing ordinary least squares analyses, this study shows that there is a positive correlation between having access to training and development opportunities and higher rates of work engagement across the federal workforce.

Professional Outcomes and Satisfaction Among Graduate Medical Education Wilderness Medicine Fellowship Alumni in the United States.

Wilderness medicine (WM) graduate medical education (GME) fellowships were established in 2003. Outcomes and satisfaction of US WM GME fellowship alumni can inform prospective applicants and program directors of the strengths of fellowships and professional gaps in them. A 34-question Qualtrics survey was emailed to 111 alumni from 17 institutions listed in the Wilderness Medical Society's GME database in May 2019. Professional service, scholarship, and satisfaction were queried. Results are represented as percent response (n=answered affirmative) based on the number of respondents per question. The survey response rate was 41% (n=46); 67% reported (n=31) Fellowship of the Academy of Wilderness Medicine recognition. Within the last 5 y, 71% (n=32) reported publications in WM. Free text entry questions had 78% (n=28) describe improved clinical skills, and 68% (n=26) were exposed to new career choices in fellowship. Those who rated exposure to a variety of WM knowledge and skills highly rated the overall fellowship experience higher (P<0.001), as did those reporting a higher number of WM publications (P=0.023). Nearly half, 48% (n=21), felt they could hold their current position without fellowship training. In hindsight, 76% (n=34) would follow the same professional path. WM GME fellowship alumni reported high rates of professional engagement and scholarly productivity in the subspecialty. Responding alumni overwhelmingly rated the fellowship experience positively. Fellowships that ensure a wide exposure to experiences and foster scholarly productivity are more likely to yield professionally satisfied graduates.