Low Engagement Research Articles

Authentic leadership – for better and for worse? Leader well-being and inconsistency as moderating factors in the relation between daily authentic leadership and follower well-being

ABSTRACT Despite comprehensive insights on favourable outcomes of authentic leadership for followers, there is a limited understanding about boundary conditions of authentic leadership. Leaders’ decreased well-being (i.e. high trait emotional irritation and low trait work engagement) or inconsistency in authentic leadership may attenuate the relation between authentic leadership and follower well-being (i.e. emotional irritation and work engagement). We tested these assumptions using a daily diary study design over five consecutive working days with a sample of 64 leaders and 162 followers. We found partial support for the cross-level moderation of authentic leadership inconsistency across these five days, as daily authentic leadership was related to daily work engagement (but not emotional irritation) of followers, when authentic leadership inconsistency was low. Contrary to our predictions, neither high leader trait emotional irritation nor low leader trait work engagement attenuated the relation between daily authentic leadership and daily follower well-being. The results point out to the importance of consistency in authentic leadership behaviour. However, leaders do not need to be overly concerned about negative consequences for followers when they lead authentically while having a reduced trait well-being.

Pandemic Hinders First-Time Voter Engagement in Indonesia

This study examines the role of the General Election Commission (KPU) in boosting first-time voter participation in Seketi Village, Balongbendo District, Sidoarjo. Using qualitative methods, data were collected via interviews, observations, and documentation, and analyzed using the Miles and Huberman model. The KPU's roles as Regulator and Dynamistator were effectively implemented, but their roles as Catalyst and Facilitator were less successful. Socialization efforts and provided facilities were hindered by the pandemic and low engagement from first-time voters, leading to decreased voter participation. The findings highlight the need for improved communication strategies and resource utilization to enhance first-time voter engagement. Highlights: Effective Roles: KPU succeeded as Regulator and Dynamistator. Pandemic Impact: Socialization and voter engagement hindered by COVID-19. Communication Gaps: Insufficient social media use reduced first-time voter information. Keywords: General Election Commission, first-time voters, voter participation, regional elections, qualitative study

Why does job anxiety negatively impact employee creativity? an ego depletion theory perspective

Job anxiety has long been seen as a major factor affecting employees' job performance. The reasons and processes by which affective commitment and work engagement impact employee creativity can be studied through the lens of ego depletion theory. In this study, we surveyed employees in a theme park and applied structural equation modeling to analyze the survey data. Our observations suggested that the decline in employee creativity due to job anxiety was possibly the result of low affective commitment and work engagement, with work engagement being a key mediating factor. The development of emotional ego depletion in service industry employees after experiencing job anxiety could explain our observations. Emotional depletion not only affects employees' work attitudes and emotional expressions but also reduces their motivation for creativity.

The Potential for Digital Phenotyping in Understanding Mindfulness App Engagement Patterns: A Pilot Study.

Background: Low app engagement is a central barrier to digital mental health efficacy. With mindfulness-based mental health apps growing in popularity, there is a need for new understanding of factors influencing engagement. This study utilized digital phenotyping to understand real-time patterns of engagement around app-based mindfulness. Different engagement metrics are presented that measure both the total number of app-based activities participants completed each week, as well as the proportion of days that participants engaged with the app each week. Method: Data were derived from two iterations of a four-week study exploring app engagement in college students (n = 169). This secondary analysis investigated the relationships between general and mindfulness-based app engagement with passive data metrics (sleep duration, home time, and screen duration) at a weekly level, as well as the relationship between demographics and engagement. Additional clinically focused analysis was performed on three case studies of participants with high mindfulness activity completion. Results: Demographic variables such as gender, race/ethnicity, and age lacked a significant association with mindfulness app-based engagement. Passive data variables such as sleep and screen duration were significant predictors for different metrics of general and mindfulness-based app engagement at a weekly level. There was a significant interaction effect for screen duration between the number of mindfulness activities completed and whether or not the participant received a mindfulness notification. K-means clusters analyses using passive data features to predict mindfulness activity completion had low performance. Conclusions: While there are no simple solutions to predicting engagement with mindfulness apps, utilizing digital phenotyping approaches at a population and personal level offers new potential. The signal from digital phenotyping warrants more investigation; even small increases in engagement with mindfulness apps may have a tremendous impact given their already high prevalence of engagement, availability, and potential to engage patients across demographics.

Characteristics of mHealth therapy app engagement by young adults with OUD

While rates of opioid use disorder (OUD) continue to rise across the country, young adults with OUD are at particular risk as they have poorer treatment outcomes and lack developmentally appropriate treatment options. The introduction of mobile applications for OUD present a new avenue to improve treatment outcomes for young adults. One such app, reSET® provides app users with weekly cognitive behavioral therapy lessons focusing on addiction with built in contingency management for completion of lessons and negative urine drug screens. This exploratory study aimed to identify the characteristics of patients who engaged with the application, reSET®, as well as to describe potential differences in treatment outcomes between engagers and non-engagers. This observational cohort study analyzed clinical and other program data from 35 young adults between the ages of 20–28 that were involved in the care and prescribed medications for OUD in Baltimore, Maryland during the 12-week period of app prescription. Results indicated that young adults had dichotomous levels of engagement, with almost 30% engaging highly with the app, completing >90% of lessons, and approximately 70% having low engagement, completing <25% of lessons. There were no differences in mental health outcomes, but engagers were more likely to be retained in care at the end of the 12-week prescription as compared to non-engagers. Overall, results suggest that mHealth apps targeted for OUD treatment offer potential treatment benefits for young adults, especially regarding treatment retention. Future studies should investigate the treatment and mental health impacts of reSET® and other mHealth apps within this population.

Advance care planning and predictive factors among Brazilian patients with cancer from an outpatient palliative care program.

e24062 Background: Advance care planning (ACP) is crucial for informed decision-making in patient care. However, barriers such as time constraints and discomfort with discussions hinder widespread ACP adoption. A previous study (Cohen et al. JNCCN 2023) indicated a low ACP engagement rate (17%), but participation in a palliative care program has shown potential to increase this proportion. Therefore, we sought to determine the prevalence of ACP and identify associated predictor factors among patients with cancer in Brazil enrolled in an outpatient palliative care (OPC) program. Methods: A retrospective analysis was performed from November 2022 to December 2023. Eligible patients were those who passed away during the study period and had received care from an OPC program at one of the largest private joint cancer centers in Latin America. We assessed the prevalence of ACP and explored its potential associations with clinical characteristics (age, gender and type of cancer), OCP support (follow-up period, appointments and family support), and end-of-life care (treatment in the past month, intensive care unit (ICU) admission in the past month, home care service referrals, and place of death).Comparative analyses involved two groups: those who had undergone ACP and those who had not (no-ACP). Logistic models were employed. Results: A total of 849 patients were included in the final analyses. Patients’ characteristics were well balanced between groups. Most patients were women (56%), with an average of 68.2 years (SD =15.3). Patients were mostly diagnosed with gastrointestinal (36%), breast (13%), and lung (13%) cancers. Notably, 43% of patients had ACP, significantly higher than literature controls (95% confidence interval [CI]= 22-31%, P = 0.001). Among the factors associated with ACP, clinical characteristics were not significant. However, OCP support and end-of-life care were significantly predicted by ACP, including the follow-up period (MACP= 179 vs. Mno-ACP= 101; P = 0.001), family support (MACP= 0.6 vs. Mno-ACP= 0.3; P &lt; 0.001) , ICU admission at the last 30 days of life (ACP = 28% vs. no-ACP = 72%; P &lt; 0.001), and home care service referral (ACP = 72% vs. no-ACP = 28%; P &lt; 0.001). Conclusions: These findings underscore that prolonged engagement with the OPC program is associated with increased adoption of ACP among Brazilian patients with cancer. Given the scarcity of data from developing countries, our findings suggest that the OPC program plays a pivotal role in optimizing end-of life care support through ACP.

Real-world implementation of an EHR-integrated, SMS text remote patient monitoring platform at an academic cancer center.

e13669 Background: Remote monitoring studies in oncology have shown improved quality of life, decreased healthcare utilization, and even improved overall survival in an oncologic population, however applications in a real-world setting have been limited. Barriers to successful deployment include low patient engagement rates with smartphone apps, lack of integration with the EHR and burdensome clinical workflows for staff. Methods: We sought to assess the feasibility of an EHR-integrated, SMS text conversational AI agent to automate the collection of ePRO data as well as the assessment and triage of common patient symptoms for patients with GI and GU tumors receiving anti-cancer therapy. This program was developed collaboratively by a health system digital health team, nursing informatics, IT support resources, oncology nurses, medical oncologists, and representatives from Memora Health. Core components included 1) weekly ePRO collection based on the NIH’s CTCAE, 2) NLP activated symptom triage for 16 common symptoms and toxicities 3) weekly symptom check-in 4) weekly medication adherence assessment for patients on oral therapy. Patients received all messages through SMS on their phones, and all data collected were routed into the EHR. In-EHR visualizations allowed nurse coordinators to track ePRO symptoms over time and symptoms that met pre-specified criteria triggered EHR-based alerts. Results: Of 99 patients ordered into this SMS program, 83 enrolled (84% enrollment rate), with 55 Uro Onc patients; 44 GI Onc patients. A total of 2,583 surveys were sent to patients. 98% of patients completed at least 1 survey. Overall patient survey completion rate was 62%. Medication adherence surveys had the highest completion rate at 81%. ePRO completion rates were higher for GU (65%) vs GI (39%) patients (p&lt;0.01). 71% of ePRO surveys generated a symptom alert to the nursing staff. Patient satisfaction was high with 93% rating this SMS program as “excellent” or “good” (n=78). Care team surveys found that 3 of the 6 Oncologists believe ePRO collection is valuable and 3 of 6 used ePRO data to adjust a care plan. Nurse coordinators had a mixed view of the program with a majority reporting that there were too many symptom alerts. Conclusions: We successfully deployed an EHR-integrated SMS program to collect ePRO data, track patient symptoms, and monitor adherence to oral therapy. We believe having a physician champion influenced patient engagement in the GU patient population. Patients had a favorable impression of this program and survey completion rates demonstrated ease of use for patients. Clinical staff, particularly nurses, felt that there were too many alerts. Additional workflow changes may reduce alert burden and better incorporate ePRO learnings into clinical practice.

Nurturing perseverance: The influence of workplace spirituality

Orientation: The turbulent external environment has caused employees to resign at an alarming rate. Employers are also struggling with issues such as low productivity and low work engagement. In response to these challenges, it is necessary to consider what motivates employees to work hard consistently without giving up when faced with adversity and setbacks.Research purpose: The purpose of the study was to establish whether workplace spirituality at an individual, work unit and organisational level enhances perseverance.Motivation for the study: Contemporary employees are challenged personally and in the work context. Remaining motivated and invested in their work despite these challenges requires a higher form of inspiration, which suggests the importance of workplace spirituality.Research approach/design and method: The research adopted both a deductive and an inductive research approach, and a descriptive cross-sectional research design was used. Data were collected utilising a survey strategy, and the final sample consisted of 385 respondents.Main findings: The study’s findings show that individual spirituality influences perseverance. Individual spirituality fully mediates the influence of organisational spirituality and work unit spirituality on perseverance.Practical/managerial implications: To ensure that employees work hard consistently despite challenges and hardships, workplace spirituality should be considered at the individual, work unit and organisational levels. Emphasis also needs to be placed on supporting the spiritual development and growth of spiritual employees, as individual spirituality seems to promote perseverance.Contribution/value-add: The study contributes to theory development and knowledge creation of workplace spirituality and perseverance constructs.

The Role of Anxiety and Prosocial Behaviors on Adherence Behaviors to Prevent COVID-19 in University Students in the United States: Cross-Sectional Study.

In situations of acute stress, individuals may engage in prosocial behaviors or risk-taking self-oriented behaviors. The COVID-19 pandemic created large stress-promoting conditions that impacted individuals' decisions to adhere to COVID-19 preventative behaviors. The study aimed to examine the relationship between anxiety during the pandemic and adherence behaviors to prevent the spread of COVID-19, and the moderating influence of prosocial behaviors. We hypothesized that individuals with high anxiety during COVID-19 would adhere more to preventive COVID-19 behaviors than ones with low anxiety and that this relationship would be stronger in those individuals with higher prosocial behaviors. A web-based survey was administered through the SONA web-based participant tool of the psychology department of a university in the Northeastern United States. A final sample of 54 undergraduate students completed web-based questionnaires during the second wave of the COVID-19 pandemic, from January to May 2021, which included demographic measures and surveys on prosocial behaviors, anxiety, and COVID-19 preventive behaviors. Moderation analyses were conducted using PROCESS in SPSS. Participants reported high levels of trait and state anxiety symptoms, most of them meeting or exceeding the cutoff criteria to be clinically meaningful (state anxiety: 47/54, 87%; trait anxiety: 38/44, 86%), and over 50% highly adhered to the COVID-19 preventive behaviors of wearing a face mask, using hand sanitizer, handwashing, coughing/sneezing into their elbow or a tissue, self-quarantining, maintaining social distance, avoiding social gatherings, and avoiding nonessential travel. No significant associations were observed between prosocial behavior, anxiety types, and adherence to COVID-19 preventive behaviors. However, when moderation analyses were conducted between anxiety types and adherence to COVID-19 preventive behaviors, results demonstrated a statistically significant interaction of public prosocial behavior with state anxiety (β=-.17, t53=-2.60; P=.01), predicting engagement in COVID-19 preventative behaviors. At high levels of anxiety, low levels of prosocial public behaviors were associated with higher engagement in COVID-19 preventative behaviors. In contrast, high levels of public prosocial behavior were associated with low engagement in COVID-19 preventative behaviors at higher levels of anxiety. These results provide information that can aid in the creation of interventions that could increase adherence to COVID-19 preventative behaviors (Reviewed by the Plan P #PeerRef Community).

Engagement personas in patients living with atrial fibrillation and multimorbidity, and their caregivers: results from the AFFIRMO international online survey

Abstract Introduction Patients with atrial fibrillation (AF) often experience concomitant long-term health conditions. Their level of engagement, defined as their active role in the management of their condition, is crucial in identifying strategies to improve their care and self-management; similarly, the engagement level of their caregivers is also important. Purpose The AFFIRMO study aims to examine ways of optimising care and self-management for AF patients with multimorbidity by identifying characteristics of engagement personas for patients and their caregivers. Methods An online survey, distributed between June 2022 and January 2023, open to AF patients and their caregivers in five countries (UK, Italy, Denmark, Romania and Spain) collected data related to patients and caregivers’ engagement in the healthcare process using the Patient Health Engagement Scale® (PHE-s), the Altarum Consumer Engagement (ACE), and the Caregiver Health Engagement Scale® (CHE-s). Patients and caregivers were grouped into ‘high’ and ‘low’ engagement groups, based on scale-specific cut-off values, and compared by age group, sex, level of education and country of recruitment, using Chi-square tests (p&amp;lt;0.05). Results 659 patients (311 (47.2%) male, 70.9 (10.2) years), and 201 caregivers (54 (26.9%) male, 58.3 (15.2) years) participated. Based on the PHE-s®, 428 (64.9%) were classified as ‘high’ engagement level. Patients in the high engagement group were significantly more likely to be male, aged &amp;lt;75 years, have secondary level education or above, and have &amp;lt;3 co-morbidities; no differences in engagement level based on country of recruitment. Based on the ACE scale, 369 (56.0%) were categorised as ‘high’ engagement level. Those with ‘high’ engagement were significantly more likely to be &amp;lt;65 years old, living in Northern Europe, educated to degree level or above, and had &amp;lt;3 co-morbidities, with no sex differences in engagement level. One hundred thirty-eight (68.7%) caregivers reported ‘high’ engagement. However, there were no significant differences between sex, age group, region of recruitment, or level of education between high and low engagement in caregivers. Conclusions Identification of engagement personas of patients and their caregivers could help to develop better management pathways for AF patients with multimorbidity.Table 1.Level of engagement

Less-proficient EFL students' use of Grammarly in writing: Behavior, cognition, and affect

This multiple case study examines less-proficient Intermediate EFL students' attitudes toward the use of Grammarly's free version in writing. The study explored the participants' behavior, cognition, and affect, aiming to provide detailed insights into their experiences and perspectives. Utilizing Zoom recordings, stimulated recall, and semi-structured interviews, the study reveals that the less-proficient learners were product-oriented in revising their writing, showing low cognitive engagement with Automated Written Corrective Feedback (AWCF). Although one participant did not fully trusted Grammarly’s accuracy, all of them accepted its suggestions quickly and uncritically. The desire to increase the scores seemed to play a significant role in their engagement with AWCF. Despite this, the study primarily highlights how inadequate linguistic knowledge posed challenges for the students in effectively utilizing the technology. Nonetheless, the students expressed overall satisfaction with Grammarly's assistance, recognizing its ability to improve their drafts. To optimize the technology's benefits for less-proficient EFL students, the study the need for providing metalinguistic knowledge and user training to enhance their language learning through its feedback.

Providing insights into health data science education through artificial intelligence

BackgroundHealth Data Science (HDS) is a novel interdisciplinary field that integrates biological, clinical, and computational sciences with the aim of analysing clinical and biological data through the utilisation of computational methods. Training healthcare specialists who are knowledgeable in both health and data sciences is highly required, important, and challenging. Therefore, it is essential to analyse students’ learning experiences through artificial intelligence techniques in order to provide both teachers and learners with insights about effective learning strategies and to improve existing HDS course designs.MethodsWe applied artificial intelligence methods to uncover learning tactics and strategies employed by students in an HDS massive open online course with over 3,000 students enrolled. We also used statistical tests to explore students’ engagement with different resources (such as reading materials and lecture videos) and their level of engagement with various HDS topics.ResultsWe found that students in HDS employed four learning tactics, such as actively connecting new information to their prior knowledge, taking assessments and practising programming to evaluate their understanding, collaborating with their classmates, and repeating information to memorise. Based on the employed tactics, we also found three types of learning strategies, including low engagement (Surface learners), moderate engagement (Strategic learners), and high engagement (Deep learners), which are in line with well-known educational theories. The results indicate that successful students allocate more time to practical topics, such as projects and discussions, make connections among concepts, and employ peer learning.ConclusionsWe applied artificial intelligence techniques to provide new insights into HDS education. Based on the findings, we provide pedagogical suggestions not only for course designers but also for teachers and learners that have the potential to improve the learning experience of HDS students.

Emergency remote teaching amid global distress: how did teacher educators respond, cope, and plan for recovery?

This study explored the emergency remote teaching experiences of Ghanaian teacher educators during COVID-19. The study employed a basic qualitative interpretive approach and purposively interviewed 25 teacher educators from 15 teacher training institutions. Teacher educators in this study reported that emergency remote teaching (ERT) was a learning opportunity and professional capacity-building experience for them to engage in contemporary pedagogical practices. Teachers also indicated that synchronous and asynchronous remote teaching was helpful for their students, as it provided students with the opportunity to engage in self-paced learning due to their access to learning resources at any time. ERT promoted peer teaching, team teaching, and effective collaboration among teacher educators. However, with little preparation and training for remote teaching and learning, both teachers and students struggled with the remote teaching and learning process. A myriad of challenges were identified including the unsuitability and unfamiliarity of online teaching and learning platforms, a high rate of absenteeism and low student engagement, a lack of parental and school support, and inadequate technological resources. The study revealed that mathematics and science teachers needed advanced technological resources to support student learning. Implications for educational policy and practice are discussed.

Say what you want: Evaluation and engagement with YouTube broadcasts on ChatGPT

ChatGPT caused a worldwide sensation upon its launch, as evidenced by the extensive coverage across traditional and new media. This paper delves into the diverse evaluative discourses about this AI chatbot both in YouTube news videos (originally, television broadcasts) and in user comments facilitated by YouTube’s interactivity. The qualitative-quantitative discourse analysis probes diversified evaluations within YouTube broadcast talk, together with their impact on viewers’ perceptions of the broadcasts’ stance and viewers’ evaluations of ChatGPT and the broadcasts, as reflected by user comments. The findings present balanced effects, speaking to polarised opinions and mixed feelings about this AI development, but point to a potential boomerang effect in users’ evaluation of the new AI bot relative to the broadcasts considered to be biased. The study also reports low user engagement with the broadcasts. This challenges the notion of user engagement with broadcast content as lying at the heart of user interactivity on YouTube.

Zooming in: The role of nonverbal behavior in sensing the quality of collaborative group engagement

Successful computer-supported collaborative learning (CSCL) relies on collaborative group engagement, a complex construct characterized by multifaceted, dynamic, socio-emotional, and socio-cognitive processes. This paper provides a detailed analysis of collaborative group engagement, with a particular focus on nonverbal behaviors as indicators of high versus low group engagement. Using video observations and a multi-method approach, we examine in detail the relationships between different dimensions of group engagement (i.e., behavioral, social, cognitive, and conceptual-to-consequential engagement) and nonverbal behaviors. Using qualitative case analysis, we also provide a rich examination of selected cases to identify the role that nonverbal behaviors play in high-engagement sequences compared with low-engagement sequences. Our findings shed light on specific nonverbal behaviors, including nodding, laughing, and eye contact, as significant indicators of high versus low collaborative group engagement. Notably, more of these nonverbal behaviors are evident in high-engagement sequences, suggesting mutual reinforcement on each dimension of engagement—with the exception of behavioral engagement, where increased laughing or smiling is evident in low-engagement sequences, but still serves a productive group process. The paper concludes with a discussion and implications of the findings. By demonstrating the role of nonverbal behaviors as important indicators, this work contributes to the understanding of the complex, dynamic, and contextualized nature of collaborative group engagement in CSCL settings.

Patient experiences of interprofessional collaboration and intersectoral communication in rare disease healthcare in Germany – a mixed-methods study

BackgroundRare diseases are often complex, chronic and many of them life-shortening. In Germany, healthcare for rare diseases is organized in expert centers for rare diseases. Most patients additionally have regional general practicioners and specialists for basic medical care. Thus, collaboration and information exchange between sectors is highly relevant. Our study focuses on the patient and caregiver perspective on intersectoral and interdisciplinary care between local healthcare professionals (HCPs) and centers for rare diseases in Germany. The aims were (1) to investigate patients’ and caregivers’ general experience of healthcare, (2) to analyse patients’ and caregivers’ perception of collaboration and cooperation between local healthcare professionals and expert centers for rare diseases and (3) to investigate patients’ and caregivers’ satisfaction with healthcare in the expert centers for rare diseases.ResultsIn total 299 individuals of whom 176 were patients and 123 were caregivers to pediatric patients participated in a survey using a questionnaire comprising several instruments and constructs. Fifty participants were additionally interviewed using a semistructured guideline. Most patients reported to receive written information about their care, have a contact person for medical issues and experienced interdisciplinary exchange within the centers for rare diseases. Patients and caregivers in our sample were mainly satisfied with the healthcare in the centers for rare diseases. The qualitative interviews showed a rather mixed picture including experiences of uncoordinated care, low engagement and communication difficulties between professionals of different sectors. Patients reported several factors that influenced the organization and quality of healthcare e.g. engagement and health literacy in patients or engagement of HCPs.ConclusionsOur findings indicate the high relevance of transferring affected patients to specialized care as fast as possible to provide best medical treatment and increase patient satisfaction. Intersectoral collaboration should exceed written information exchange and should unburden patients of being and feeling responsible for communication between sectors and specialists. Results indicate a lack of inclusion of psychosocial aspects in routine care, which suggests opportunities for necessary improvements.

The Use of Cultural Landscape Fragmentation for Rural Tourism Development in the Zemplín Geopark, Slovakia

This study outlines the creation of hiking routes in Slovakia’s cultural landscape, focusing on regions with marginal interest, low tourism engagement, and predominant monocultural blocks. The methodology was systematically applied to the Zemplín Geopark in eastern Slovakia, drawing upon historical cartographic records from the Josephine mapping period (1764–1787) to the present day. The investigation identified and delineated 14 hiking trails, offering historical and tourism significance while promoting multifunctionality. Our research introduces sustainable development avenues for regions with marginal interest, providing ecological and tourist benefits that enhance the overall quality of life. The findings align with the Common Agricultural Policy’s objectives for 2021–2027, addressing challenges related to large-scale field fragmentation. Two identified obstacles include property-legal challenges and issues arising from inadequate map registration, which current methods, unfortunately, fail to address.

Community Engagement in Vaccination Promotion: Systematic Review and Meta-Analysis.

Community engagement plays a vital role in global immunization strategies, offering the potential to overcome vaccination hesitancy and enhance vaccination confidence. Although there is significant backing for community engagement in health promotion, the evidence supporting its effectiveness in vaccination promotion is fragmented and of uncertain quality. This review aims to systematically examine the effectiveness of different contents and extent of community engagement for promoting vaccination rates. This study was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A comprehensive and exhaustive literature search was performed in 4 English databases (PubMed, Embase, Web of Science, and Cochrane Library) and 2 Chinese databases (CNKI and Wan Fang) to identify all possible articles. Original research articles applying an experimental study design that investigated the effectiveness of community engagement in vaccination promotion were eligible for inclusion. Two reviewers independently performed the literature search, study selection, quality assessment, and data extraction. Discrepancies were resolved through discussion, with the arbitration of a third reviewer where necessary. A total of 20 articles out of 11,404 records from 2006 to 2021 were retrieved. The studies used various designs: 12 applied single-group pre-post study designs, 5 were cluster randomized controlled trials (RCTs), and 3 were non-RCTs. These studies targeted multiple vaccines, with 8 focusing on children's immunization, 8 on human papillomavirus vaccine, 3 on hepatitis B virus vaccine, and 1 on COVID-19 vaccine. The meta-analysis revealed significant increases in vaccination rates both in pre-post comparison (rate difference [RD] 0.34, 95% CI 0.21-0.47, I2=99.9%, P<.001) and between-group comparison (RD 0.18, 95% CI 0.07-0.29, I2=98.4%, P<.001). The meta-analysis revealed that participant recruitment had the largest effect size (RD 0.51, 95% CI 0.36-0.67, I2=99.9%, P<.001), followed by intervention development (RD 0.36, 95% CI 0.23-0.50, I2=100.0%, P<.001), intervention implementation (RD 0.35, 95% CI 0.22-0.47, I2=99.8%, P<.001), and data collection (RD 0.34, 95% CI 0.19-0.50, I2=99.8%, P<.001). The meta-analysis indicated that high community engagement extent yielded the largest effect size (RD 0.49, 95% CI 0.17-0.82, I2=100.0%, P<.001), followed by moderate community engagement extent (RD 0.45, 95% CI 0.33-0.58, I2=99.6%, P<.001) and low community engagement extent (RD 0.15, 95% CI 0.05-0.25, I2=99.2%, P<.001). The meta-analysis revealed that "health service support" demonstrated the largest effect sizes (RD 0.45, 95% CI 0.25-0.65, I2=99.9%, P<.001), followed by "health education and discussion" (RD 0.39, 95% CI 0.20-0.58, I2=99.7%, P<.001), "follow-up and reminder" (RD 0.33, 95% CI 0.23-0.42, I2=99.3%, P<.001), and "social marketing campaigns and community mobilization" (RD 0.24, 95% CI 0.06-0.41, I2=99.9%, P<.001). The results of this meta-analysis supported the effectiveness of community engagement in vaccination promotion with variations in terms of engagement contents and extent. Community engagement required a "fit-for-purpose" approach rather than a "one-size-fits-all" approach to maximize the effectiveness of vaccine promotion. PROSPERO CRD42022339081; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=339081.

An LSTM-based prediction model for gradient-descending optimization in virtual learning environments

A virtual learning environment (VLE) is an online learning platform that allows many students, even millions, to study according to their interests without being limited by space and time. Online learning environments have many benefits, but they also have some drawbacks, such as high dropout rates, low engagement, and students' self-regulated behavior. Evaluating and analyzing the students' data generated from online learning platforms can help instructors to understand and monitor students learning progress. In this study, we suggest a predictive model for assessing student success in online learning. We investigate the effect of hyperparameters on the prediction of student learning outcomes in VLEs by the long short-term memory (LSTM) model. A hyperparameter is a parameter that has an impact on prediction results. Two optimization algorithms, adaptive moment estimation (Adam) and Nesterov-accelerated adaptive moment estimation (Nadam), were used to modify the LSTM model's hyperparameters. Based on the findings of research done on the optimization of the LSTM model using the Adam and Nadam algorithm. The average accuracy of the LSTM model using Nadam optimization is 89%, with a maximum accuracy of 93%. The LSTM model with Nadam optimisation performs better than the model with Adam optimisation when predicting students in online learning.

Recruitment of Hard-To-Reach Populations in Randomized Controlled Trials Using Medical Students and Electronic Con-sents

Viral hepatitis is concentrated in populations with low healthcare system engagement, including non-white, rural, non-English speaking, and low socioeconomic status persons. Recruiting these participants for clinical trials has immense implications for trial feasibility and generalizability. Through the example of a trial delivering a behavioral intervention to patients with hepatitis C virus (HCV) in a network of medical student-run clinics, we describe the implementation of a student-run HCV testing program in the community and describe novel strategies to improve the recruitment of hard-to-reach participants using medical student counselors and electronic consents.