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PubMed2026

Migration intentions among nigerian neurosurgeons: a national survey of workforce retention.

Physician emigration from low- and middle-income countries creates critical workforce shortages. This study explored factors influencing migration intentions among Nigerian neurosurgeons and trainees. We conducted an anonymized survey of consultant neurosurgeons, fellows, and residents practicing in Nigeria. Invitations were sent by email and professional messaging platforms, and snowball sampling was used to increase participation. The survey included quantitative and open-ended questions on demographics, income, migration plans, and retention factors. Seventy-nine respondents participated (61.5 % consultants; 93.7 % male; median age: 44 years). Nearly all practiced general neurosurgery (97.3 %), and many also performed trauma (65.3 %) and spine (61.3 %) neurosurgery. Most (85.7 %) reported that their earnings were insufficient to support their families. Nearly 40 % were considering emigration, most often citing financial pressures (88.5 %) and poor working conditions (63.5 %) as push factors. By contrast, personal or family ties (63.0 %) and relocation costs (45.2 %) were cited as reasons to stay. Respondents identified higher salaries (58.1 %) and greater investment in the health sector (51.4 %) as key measures to improve retention. In univariable analyses, younger age, income insufficiency, income dissatisfaction, and feeling undervalued at work were associated with migration intention. Financial insecurity emerged as the dominant driver of migration intentions among Nigerian neurosurgeons. In addition to salary increases, sustained investment in healthcare infrastructure and workforce support is essential to improve retention. International partnerships may complement these efforts by building neurosurgical capacity and mitigating brain drain.

Humans↗
PubMed2026

Effectiveness of Embedded Social Media Content on E-cigarette Attitudes and Behaviors: Results from a Randomized Control Trial.

BACKGROUND: This longitudinal randomized controlled trial examined the effects of anti-vaping social media content on e-cigarette attitudes and intentions among U.S. young adults (ages 18-24; n=3,400). METHODS: Targeted content was embedded directly into participants' social media feeds, with varying levels of impressions. RESULTS: Results indicate that increased exposure to anti-vaping messages significantly elevated perceived risk of harm (&#x3b2;=0.11, 95% CI: 0.03-0.20, p < .01) and social unacceptability of e-cigarette use (&#x3b2;=0.10, 95% CI: 0.03-0.18, p < .01), while decreasing intentions to vape (RRR = 0.59, 95% CI: 0.36-0.97, p < .05). Notably, these attitudinal shifts occurred even with relatively low ad exposure and over an extended intervention period, while controlling for the e-cigarette use status (never, former, or current) of participants. Discussion These findings support the effectiveness of digital media campaigns in influencing health-related behaviors and attitudes among young adults. Specifically, embedding anti e-cigarette content directly in the feed of young adults is shown to be effective in shifting attitudes in a space where these young adults are already engaged. Limitations include limited ad impressions and minimal change in ad awareness recall, suggesting future research should explore longer interventions and broader nicotine product messaging.

Humans↗
PubMed2026

AI Health message intervention: The role of message customization and message source in breast cancer screening among women of color.

OBJECTIVES: To examine the effectiveness of breast cancer screening messages with varying levels of customization (generic, targeted, and tailored) and to compare AI-generated versus human-generated messages. METHODS: A between-subjects experimental design with a control condition was employed. Message content followed a standardized structure and varied by level of customization: generic, targeted (demographic-based), and tailored (perceived susceptibility- and barrier-based). Messages were developed by either the authors or GenAI (ChatGPT-4o). A total of 391 participants recruited via Prolific were randomly assigned to five groups (generic, targeted-human, targeted-AI, tailored-human, and tailored-AI). Self-efficacy, behavioral intentions, attitudes, and message believability were measured using different scales. RESULTS: Customized (tailoring and targeting) health messages performed comparably to generic messages in shaping positive health outcomes. GenAI-generated messages also produced outcomes comparable to those of human-generated messages under standardized conditions. Significant negative indirect effects through message believability for the human-tailored condition was found relative to the generic condition. CONCLUSIONS: GenAI may be a useful tool for developing and customizing scalable health messages. Its effectiveness depends not only on customization but also on maintaining message quality, including readability, clarity, coherence, naturalness, and credibility. PRACTICAL IMPLICATIONS: GenAI may support health practitioners in developing customized and scalable breast cancer messages. However, professional review remains necessary to ensure that the message is culturally appropriate, responsive to patient concerns, and suitable for use alongside patient-provider communication.

Humans↗
PubMed2026

Global prevalence and associated factors of turnover intention among intensive care nurses: A systematic review and meta-analysis.

OBJECTIVES: To estimate the global prevalence of two distinct turnover intentions among intensive care unit (ICU) nurses-intention to leave the ICU and intention to leave the nursing profession-identify significant sources of heterogeneity, and synthesise associated psychosocial factors. METHODS: Ten databases were systematically searched from inception to September 28, 2025. Two reviewers independently conducted study selection, data extraction, and quality appraisal using Joanna Briggs Institute checklists. Random-effects meta-analyses were performed to estimate pooled prevalence and associated factors. Subgroup and meta-regression analyses explored potential sources of heterogeneity. Associated factors were pooled as odds ratios (ORs) and interpreted within an integrated Job Demands-Resources and Theory of Planned Behavior framework. RESULTS: Forty-six studies published between 2007 and 2025, involving 39,246 ICU nurses, were included. The pooled prevalence was 30.7% for intention to leave the ICU and 27.5% for intention to leave the nursing profession. Significant sources of heterogeneity included ICU type, geographic region, publication year, study design, measurement tool, and sampling method. Depression, burnout, high workload, and unsafe patient-to-nurse ratios were associated with increased turnover intention, whereas positive work environments, perceived organisational support, and nursing competence were protective factors. No significant publication bias was detected. CONCLUSIONS: Turnover intention affects approximately one-third of ICU nurses globally and varies across clinical and geographical contexts. Excessive workload, inadequate organisational support, and unfavourable work environments appear to be important contributors to turnover intention among ICU nurses. IMPLICATIONS FOR CLINICAL PRACTICE: Strategies to reduce turnover intention among ICU nurses should focus on reducing excessive workload, improving staffing conditions, strengthening organisational support, and fostering positive work environments. Promoting supportive and sustainable ICU work environments may help improve nurse retention and maintain the quality of critical care services.

Humans↗