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The integration of generative artificial intelligence (AI) into academic research writing has revolutionized the field, offering powerful tools like ChatGPT and Bard to aid researchers in content generation and idea enhancement. We explore the current state of transparency regarding generative AI use in nursing academic research journals, emphasizing the need for explicitly declaring the use of generative AI by authors in the manuscript. Out of 125 nursing studies journals, 37.6% required explicit statements about generative AI use in their authors' guidelines. No significant differences in impact factors or journal categories were found between journals with and without such requirement. A similar evaluation of medicine, general and internal journals showed a lower percentage (14.5%) including the information about generative AI usage. Declaring generative AI tool usage is crucial for maintaining the transparency and credibility in academic writing. Additionally, extending the requirement for AI usage declarations to journal reviewers can enhance the quality of peer review and combat predatory journals in the academic publishing landscape. Our study highlights the need for active participation from nursing researchers in discussions surrounding standardization of generative AI declaration in academic research writing.

Introduction Research impact and influence are commonly measured quantitatively by citation count received by research articles. Many institutes also use citation count as one of the factors in faculty performance appraisal and candidate selection of academic positions. Various strategies were recommended to amplify and accelerate research influence, particularly citation counts, by bringing research articles to a wider reach for potential readers. However, no prior empirical study was conducted to examine and valid effects of those strategies on nursing studies. This study examines and verifies the direct effects and mediation effects of some strategies, namely, the use of Twitter, international collaboration, the use of ResearchGate, and open access publishing, for amplifying the citation of research and review articles in nursing studies. Design Cross‐sectional study design. Methods Articles published in top nursing journals in 2016 were identified in PUBMED and the citation metrics for individual articles until 2021 were extracted from Scopus. The primary outcome was the citation count of the article, while the tweet count on Twitter of the article was considered a mediator. The predictors included paper type, the total number of authors, the proportion of authors with a ResearchGate account in the article, funding support, open‐accessed article, and the number of different countries stated in the authors' affiliation. A mediation analysis was conducted to examine the predictors' direct and indirect effects (i.e., via tweet count) on the citation count of the article. Results A total of 2210 articles were included in this study, of which 223 (10.1%) were review articles. The median (IQR) number of Scopus citations, tweets, countries, and percentage of authors with ResearchGate accounts were 12 (6–21), 2 (0–6), 1 (1–1), and 75% (50%–100%) respectively. In the mediation analysis, tweet count, article type, number of countries, percentage of authors with a ResearchGate account, and journal impact factors in 2014 were positively associated with the Scopus citation count. The effects of article type, open access, and journals' impact factors in 2014 on Scopus citation count were mediated by the tweet count. Conclusion This study provides empirical support for some strategies researchers may employ to amplify the citation count of their research articles. The methodology of our study can be extended to compare research influence between entities (e.g., across countries or institutes). Clinical Relevance The citation refers to the research work cited by peers and is one of the indicators for research impact. Higher citations implied the research work is read and used by others, therefore, understanding the associated factors with higher citations is critical.

Caregivers of frail older adults face substantial challenges, often managing their own health while providing care. To address these issues, we developed the caregiver support model (CSM), a structured approach that uses systematic assessment, personalized intervention planning, and sustained support to address informal family caregivers' diverse and evolving needs and leverage their resources. This study aims to evaluate the effectiveness of CSM. A blinded cluster randomized controlled trial was conducted across 8 centers providing services for older adults in Hong Kong. The CSM is a social worker-guided intervention that integrates a structured assessment of caregiver needs and resources, personalized service planning, and ongoing monitoring over 6 months. Meanwhile, the control group continued with their usual procedures without a standardized caregiver assessment. Data were collected at baseline, 3 months, and 6 months. We recruited 565 informal family caregivers (281/565, 49.7% CSM intervention; 284/565, 50.3% standard care control). Both groups improved over time; compared with the control group, the CSM produced greater reductions in caregiver needs, particularly in role conflict, and greater gains in resources, such as health awareness. Improvements were more pronounced at 6 months compared to 3 months, indicating a lasting effect and consolidation of gains. The intervention was particularly effective for caregivers in other relationships (not spouse or child) and those with higher education than spousal caregivers. These findings highlight the importance of long-term tailored interventions that adapt to the evolving needs of caregivers through systematic assessment. The CSM offers a promising approach to enhancing the well-being of caregivers and managing the complex demands of caregiving, particularly in an aging population.

Residents in residential care homes for the elderly (RCHEs) are at high risk of severe illnesses and mortality, while staff have high exposure to intimate care activities. Addressing vaccine hesitancy is crucial to safeguard vaccine uptake in this vulnerable setting, especially amid a pandemic. In response to this, we conducted a cross-sectional survey to measure the level of vaccine hesitancy and to examine its associated factors among residents and staff in RCHEs in Hong Kong. We recruited residents and staff from 31 RCHEs in July–November 2022. Of 204 residents, 9.8% had a higher level of vaccine hesitancy (scored ≥ 4 out of 7, mean = 2.44). Around 7% of the staff (n = 168) showed higher vaccine hesitancy (mean = 2.45). From multi-level regression analyses, higher social loneliness, higher anxiety, poorer cognitive ability, being vaccinated with fewer doses, and lower institutional vaccination rates predicted residents’ vaccine hesitancy. Similarly, higher emotional loneliness, higher anxiety, being vaccinated with fewer doses, and working in larger RCHEs predicted staff’s vaccine hesitancy. Although the reliance on self-report data and convenience sampling may hamper the generalizability of the results, this study highlighted the importance of addressing the loneliness of residents and staff in RCHEs to combat vaccine hesitancy. Innovative and technology-aided interventions are needed to build social support and ensure social interactions among the residents and staff, especially amid outbreaks.

Depression is a common, depleting, and potentially life-threatening disorder. This pilot study examined the feasibility and applicability, reported preliminary evidence for effectiveness, and explored the potential healing mechanisms of a faith-based spiritual intervention for people with depression. The intervention consisted of six weekly sessions focused on restoring a connection with the divine, forgiveness and freedom, suffering and transcendence, hope, gratitude, and relapse prevention. Seven adults with mild or moderate depressive symptoms were recruited. A qualitative evaluation was conducted via focus group discussions, and rating scales were administered at baseline, after the intervention, and at the 3-month follow-up. The mean difference scores of the treatment’s effect over time were analyzed using Friedman’s ANOVA. The themes identified by the focus group included the meaning of the spiritual intervention, the effect of involvement in a spiritual group, and the therapeutic components. The results indicated a significant decrease in the mean scores for depression (PHQ-9) after intervention and at the 3-month follow-up. Participants expressed their improvement in terms of increased knowledge about depression, enhanced coping mechanisms, and improved self-esteem. The preliminary evidence suggested that the faith-based spiritual intervention was effective in reducing depressive symptoms and also helped participants develop a greater sense of connection with themselves, others, and their environment.

To access temporal changes in psychobehavioral responses to the coronavirus disease (COVID-19) pandemic, we conducted a 5-round (R1–R5) longitudinal population-based online survey in Hong Kong during January–September 2020. Most respondents reported wearing masks (R1 99.0% to R5 99.8%) and performing hand hygiene (R1 95.8% to R5 97.7%). Perceived COVID-19 severity decreased significantly, from 97.4% (R1) to 77.2% (R5), but perceived self-susceptibility remained high (87.2%–92.8%). Female sex and anxiety were associated with greater adoption of social distancing. Intention to receive COVID-19 vaccines decreased significantly (R4 48.7% to R5 37.6%). Greater anxiety, confidence in vaccine, and collective responsibility and weaker complacency were associated with higher tendency to receive COVID-19 vaccines. Although its generalizability should be assumed with caution, this study helps to formulate health communication strategies and foretells the initial low uptake rate of COVID-19 vaccines, suggesting that social distancing should be maintained in the medium term.

During the early phase of the coronavirus disease epidemic in Hong Kong, 1,715 survey respondents reported high levels of perceived risk, mild anxiety, and adoption of personal-hygiene, travel-avoidance, and social-distancing measures. Widely adopted individual precautionary measures, coupled with early government actions, might slow transmission early in the outbreak.

Depression is one of the most prevalent mental disorders worldwide. This study examined the effect of a spiritual connectivity intervention on individuals with depression in a randomized waitlist-controlled trial. Fifty-seven participants with mild or moderate depressive symptoms were randomly assigned to either the intervention group (n = 28) or the waitlist control group (n = 29). The intervention comprised eight weekly sessions focusing on divine connection, forgiveness and freedom, suffering and transcendence, hope, gratitude, and relapse prevention. The outcome measures included depressive symptoms, anxiety, hope, meaning in life, self-esteem, and social support. Participants completed self-administered questionnaires at baseline (week 0), post-intervention (week 8), and 3-month follow-up (week 20). Repeated-measures ANOVA and one-way ANCOVA were used to compare the within-group and between-group differences in the changes in outcome variables. Participants in the intervention group showed significant improvements in depression, anxiety, spiritual experience, hope, self-esteem, and perceived social support after the intervention. Effect size statistics showed small to large differences (Cohen’s d, 0.308 to −1.452). Moreover, 85.71% of participants in the intervention group also experienced clinically significant reductions in PHQ-9 scores from baseline to immediate post-intervention. This study highlights the effectiveness of a low-cost, accessible intervention suitable for community implementation by clergy and faith-based organizations.

A ChatGPT search engine with chatbot function offers travellers pre-, during and post-travel consultations. Users should critically evaluate information provided and assess source reliability. Integrating user feedback and reviews could enhance information quality. With responsible artificial intelligence (AI) development, leveraging travel medicine specialists’ expertise and AI-based search engines can transform travel medicine.

Objectives. We assessed the effectiveness of a 5-year trial of a comprehensive school-based program designed to prevent substance use, violent behaviors, and sexual activity among elementary-school students. Methods. We used a matched-pair, cluster-randomized, controlled design, with 10 intervention schools and 10 control schools. Fifth-graders (N = 1714) self-reported on lifetime substance use, violence, and voluntary sexual activity. Teachers of participant students reported on student (N = 1225) substance use and violence. Results. Two-level random-effects count models (with students nested within schools) indicated that student-reported substance use (rate ratio [RR] = 0.41; 90% confidence interval [CI] = 0.25, 0.66) and violence (RR = 0.42; 90% CI = 0.24, 0.73) were significantly lower for students attending intervention schools. A 2-level random-effects binary model indicated that sexual activity was lower (odds ratio = 0.24; 90% CI = 0.08, 0.66) for intervention students. Teacher reports substantiated the effects seen for student-reported data. Dose-response analyses indicated that students exposed to the program for at least 3 years had significantly lower rates of all negative behaviors. Conclusions. Risk-related behaviors were substantially reduced for students who participated in the program, providing evidence that a comprehensive school-based program can have a strong beneficial effect on student behavior.