Nursing Competence and its Associated Workplace Factors in a Resource-limited Setting in Garo Hills, Meghalaya, India: A Cross-sectional Study

A short version of the nurse professional competence scale for measuring nurses' self-reported competence

Dual use of instruments for assessing nursing students professional- and clinical competence

Background: Public health emergencies (PHE) caused by natural hazards spread from one particular locality to adjacent geographic areas and then encompass the entire planet in today’s fast global connectivity mode. Each country, including India, has its own set of potential disasters based on the hazards present as well as the unique vulnerabilities of the community and community’s preparedness to respond to particular disasters. Currently, human history is observing a very critical time fighting an invisible enemy—COVID-19. Therefore, in this study, we seek to understand the standardised measures of public hospital preparedness and resilience at times of health emergencies, including a pandemic, the most current one being COVID-19. Methods: We conducted a descriptive, cross-sectional study among health officials of district hospitals (DHs) and community health centres (CHCs) of Rajasthan using a semi-structured online questionnaire, with COVID-19 in mind, and sending it to those who had attended a training programme on disaster preparedness in hospitals. Results: In all, questionnaires were sent to 80 health officials of DHs and CHCs, of which 58 responded, with a response rate of 72.5 per cent. We collected responses on public health emergency preparedness, training-related issues, the capacity to deal with emergencies and prior experience in managing an emergency. Conclusion: The resilience and preparedness of DHs and CHCs in Rajasthan appear to be limited. From the studies it has been revealed that proper training and education on disasters like the current COVID-19, which is of significant importance for healthcare workers, is limited to only 37.9 per cent of healthcare workers. It also emerges that the staff members whenever required could mark and perform in the triage area, but the Isolation room haven’t got the request facilities and equipped to stabilise a critical patient despite availability of emergency stock of medicine. The stated functional status of DHs and CHCs reveals that the level of emergency preparedness is between low and medium and also varies from hospital to hospital and from CHC to CHC. Hence, it is time to reassess and upgrade emergency preparedness plans, which include mitigation, preparedness, response and recovery. Federal-, state- and local-level emergency management agencies’ functioning has to be effective and well-coordinated with the local level of operation.

The relationship between perceived competence and perceived workplace bullying among registered nurses: A cross sectional survey

ABSTRACTAimTo investigate and compare the self‐assessed professional competence of registered nurses, specialist nurses and midwives at a regional teaching hospital in Sweden. Moreover, to explore associations between potential predictive background factors and self‐assessed professional competence.DesignA cross‐sectional study.MethodsConvenience sample of 615 nurses answered a questionnaire; sociodemographic data, 35‐item Nurse Professional Competence Scale, Occupational Self‐Efficacy Scale. Statistical analyses: Fisher's non‐parametric permutation test, Kruskal–Wallis test, Mantel–Haenszel chi‐square test, Spearman rank correlation test, calculating sum score. Multiple linear regressions and reliability testing with Cronbach's alpha.ResultsResponse rate, 58.7%; mean age, 44.7 years; work experience, 0.2 years to 45 years (mean 16.4 years); 83.4% women. 82.4% bachelor's degree; out of these, 34.3% with an additional master's degree. 17.6% nursing diploma without an academic degree. The highest mean scores for the NPC Scale were in Value‐based nursing care, Medical and technical care. The lowest were in Care pedagogics and Development, leadership and organisation of nursing care. Total mean score 84.3, (79.3–90.0). Specialist nurses scored higher in all areas except Care pedagogics. Predictive factors indicated being a woman was positively associated with higher competence scores in all six areas, β coefficients 2.2–5.3 with p < 0.05. Longer nursing experience was positively associated with higher competence in Nursing care (β 0.17 per year, p = 0.01), Medical and technical care (β 0.14 per year, p = 0.01). The occupational self‐efficacy scale was strongly positively associated with higher competence in all areas, β per scale step 0.42–0.63 with p < 0.0001. Nurses without academic degree had lower competence scores in several areas compared to bachelor's degree, β ranges from −3.47 to −2.31, p < 0.05.ConclusionUtilising competence data, the Swedish Enhanced Competence Development Model (vKUM) can effectively support the planning and management of ongoing professional competence development.Reporting MethodStudy methods and results reported in adherence to STROBE checklist.Patient or Public ContributionThe nurses contributed their consent, time and data to this study.

Emerging evidence suggested that artificial intelligence (AI) may offer particular benefits in resource-limited clinical settings with high patient loads and constrained radiology expertise. The present study aimed to evaluate the diagnostic performance of an AI-assisted decision-making software (DMS) for pulmonary nodules detected on computed tomography (CT) among physicians in a resource-limited clinical setting. In this retrospective multi-reader, multi-case study, three pulmonologists and three radiologists from a secondary hospital independently assessed 200 enriched chest CT scans with and without AI-assisted DMS. The dataset was balanced with 100 benign and 100 malignant nodules to provide a consistent challenge for both physicians and the AI system. Diagnostic performance was measured by comparing the average area under the receiver operating characteristic curves (AUC) with and without AI support. Sensitivity and specificity were evaluated at the 5% and 65% malignancy thresholds, and inter-reader agreement on disease management plans was examined. AI-assisted DMS significantly improved readers' diagnostic performance, with the average AUC increasing from 0.78 to 0.89 (mean difference: 0.11, 95% confidence interval [CI]: 0.08, 0.14). Improvements were consistent across readers' experience levels and specialties. Sensitivity at the 5% malignancy threshold reached 97.3% (95% CI: 95.1%, 99.6%) with AI assistance, while specificity improved by 18.5% (95% CI: 6.5%, 30.5%). At the 65% threshold, sensitivity and specificity increased by 21.2% and 7.8%, respectively. In addition, the overall inter-reader agreement enhanced from 0.19 to 0.40 (p < 0.01), although agreement on non-surgical diagnostic procedures remained relatively lower compared to other categories. AI-assisted DMS showed great potential in improving diagnostic performance for CT pulmonary nodule management in the resource-limited setting. Strengthening referral pathways for intermediate-risk cases might further support appropriate clinical decision-making and help align patient evaluation with available expertise. Continued prospective real-world studies with longitudinal follow-up and histopathological confirmation would contribute to expanding the evidence base and guiding its broader integration into routine clinical practice.

This study analyzes the characteristics of uninsured workers and blind spots in the national pension system. Specifically, it examines trends over time and assesses the explanatory power of job-related factors alongside workplace and individual characteristics. Using microdata from the Supplementary Surveys of the Economically Active Population Survey (2015–2023), the analysis shows that while the uninsured rate remains high in small workplaces with fewer than five employees, the gap narrows substantially when controlling for wages and occupational status. This indicates that employment types—such as low-wage or non-regular work—are more closely linked to non-coverage than workplace size itself. Differences in uninsured rates by age and education also diminish notably when wage and job status are accounted for. Even after controlling for individual and workplace factors, a negative association between average monthly wages and pension non-coverage persists, though additional controls like working hours, tenure, and employment type have limited explanatory power regarding wage levels. Furthermore, indicators of employment formality—such as retirement pay, payment methods, paid leave, and bonuses—are closely associated with non-coverage. These findings highlight the need for policies that address not only workplace characteristics but also qualitative employment factors, including personnel management practices, to effectively reduce pension blind spots. However, as this is a correlation-based empirical analysis, it does not establish strict causal relationships.

ObjectivesFood processing facilities represent critical infrastructure that have stayed open during much of the COVID-19 pandemic. Understanding the burden of COVID-19 in this sector is thus important to help reduce the potential for workplace infection in future outbreaks.MethodsWe undertook a workplace survey in the UK food and drink processing sector and collected information on workplace size, characteristics (e.g. temperature, ventilation), and experience with COVID-19 (e.g. numbers of positive cases). For each site, we calculated COVID-19 case rates per month per 1000 workers. We performed an ecological analysis using negative binomial regression to assess the association between COVID-19 rates and workplace and local risk factors.ResultsRespondents from 33 companies including 66 individual sites completed the survey. COVID-19 cases were reported from the start of the pandemic up to June 2021. Respondents represented a range of industry subgroups, including grain milling/storage (n = 16), manufacture of malt (n = 14), manufacture of prepared meals (n = 12), manufacture of beverages (n = 8), distilling (n = 5), manufacture of baked goods (n = 5), and other (n = 6), with a total of 15 563 workers across all sites. Average monthly case rates per 1000 workers ranged from 0.9 in distilling to 6.1 in grain milling/storage. Incidence rate ratios were partially attenuated after adjusting for several local and workplace factors, though risks for one subgroup (grain milling/storage) remained elevated. Certain local and workplace characteristics were related to higher infection rates, such as higher deprivation (5 km only), a lower proportion of remote workers, lower proportion of workers in close proximity, and higher numbers of workers overall.ConclusionsOur analysis suggests some heterogeneity in the rates of COVID-19 across sectors of the UK food and drink processing industry. Infection rates were associated with deprivation, the proportions of remote workers and workers in close proximity, and the number of workers.

ObjectivesThe study aimed to (1) determine if a variety of workplace and supervision factors predict clinical supervision effectiveness; and (2) establish if clinical supervision effectiveness predicts burnout, amongst a variety of mental health staff (medical, allied health, and nursing staff).DesignThe study adopted a multicentre cross‐sectional online survey design.MethodsParticipants included 204 mental health staff (89 allied health staff, 81 nursing staff, and 34 medical staff). The Manchester Clinical Supervision Scale (MCSS‐26) was used to measure clinical supervision effectiveness, and the Maslach Burnout Inventory (MBI‐HSS) was used to measure burnout. Linear regression analyses and multiple regression analyses were conducted.ResultsThe main findings suggested that supervision frequency, supervision duration, choice of supervisor, workplace setting, and supervisee profession, were all significant predictors of clinical supervision effectiveness. Additionally, clinical supervision effectiveness was a significant negative predictor of burnout.ConclusionsWorkplace and supervision factors should be considered in supervision practice across professional groups. Policies need to promote effective clinical supervision practice.

Introduction: Acute rheumatic fever (ARF) remains under diagnosed in low resource settings yet it is associated with dire consequences. Application of Jones criteria, the standard criteria used for diagnosis of ARF in these settings is challenging as many of its features are not readily available. Objective: To determine the performance of readily available information at each level of the healthcare system in Uganda, to determine the sensitivity and specificity of ARF diagnosis in resource limited settings. Methods: Variables that might positively or negatively predict ARF based on typical diagnostic capacity at 3 tiers of Uganda’s health system (community health center, district hospital, and national referral) were selected from a large epidemiological study conducted in northern and central Uganda. These variables were put into three statistical models to determine those that were associated with the disease. Model 1 included those variables commonly found at community health centers (features from history and clinical exam), the second model included all variables from the first model plus laboratory tests that are sometimes available (malaria antigen test, complete blood count and EKG) while the 3 rd model comprised of all variables from the 2 nd model and advanced tests that are not commonly available (ASO titers, acute phase reactants and echocardiography).Youden’s index was used to calculate sensitivity and specificity of the models and ROC curves plotted. Results: Presence of visible joint swelling and heart murmur were associated with ARF in the first and second models while carditis on echocardiogram had the highest odds ratios in the 3 rd model. Sensitivity and specificity for ARF were (51.3%, 81.0%), (60.5%, 84%) and (79.8%, 92.5%) for model 1, 2 and 3 respectively. Conclusions: Our data supports the importance of including echocardiography for the diagnosis of carditis in Jones criteria for ARF. At the same time, Jones criteria are not practical in endemic settings that not have access to definitive diagnostic testing. A new approach that is appropriate for endemic regions is therefore needed.

Efficient referral systems are essential for improving healthcare and patient outcomes, especially in resource-limited settings where access to public specialist care is limited by too few specialists, growing populations and constrained resources impacting non-emergency and emergency referrals. District hospitals (DHs) must ensure that patients receive the appropriate level of care. High-quality referral systems are necessary for the cost-effective flow of patients between district and regional hospitals (RHs). This study aimed to evaluate emergency and non-emergency patient referral processes between DHs and the RH in two districts in South Africa. Ten DHs and the RH in the Garden Route and Central Karoo districts in South Africa. A mixed-methods design incorporated quantitative survey data and qualitative thematic analysis to provide a comprehensive understanding of referral processes. The study population included all doctors working at 10 DHs and the RH, with 120 voluntary participants. Key findings revealed disparities in referral satisfaction between emergency (66%) and non-emergency (59%) referrals. Communication breakdowns and systemic barriers hindered timely access to specialist care, mismatched expectations and understanding, coupled with inconsistent referral guidelines. Inadequate capacity building increased inappropriate referrals. Communication breakdowns and differing expectations between DHs and the RH regarding available resources and services negatively impacted referrals. Improved communication, targeted outreach, capacity-building initiatives, stronger collaborative relationships and standardisation of processes could enhance patient referral efficiency.Contribution:This work adds new knowledge to patient referrals between rural district and regional hospitals in resource-limited contexts, highlighting the complexity of the referral process.

BackgroundCommunity health workers are the main providers of community health services in China and have been important in the process of health system reform that has been in place since 2009. Therefore, it is critical that healthcare managers and policy decision makers motivate current staff and improve their job satisfaction. This study examined workplace characteristics and their contribution to job satisfaction in community health workers in Heilongjiang Province, China.MethodsA cross-sectional survey of 448 community health workers, from three cities in Heilongjiang province, was conducted between October 1, 2012 and December 31, 2012. Multistage sampling procedures were used to measure socioeconomic and demographic status, job satisfaction, and both actual and desired workplace characteristics. Factor analysis was conducted to determine the main factors contributing to workplace characteristics, and multiple linear regression analysis was performed to assess the key determinants of job satisfaction.ResultsEight groups of factors were identified as the most important workplace characteristics. These comprised system and policy; fringe benefits; work itself; work relationships; professional development; recognition; work environment; and remuneration. In all cases, all desired workplace characteristics were higher than the associated actual workplace characteristics. The main determinants of job satisfaction were occupation, years worked in health service institution, and five subscales representing the gap between desired and actual workplace characteristics, which were system and policy; fringe benefits; working relationship; professional development; and remuneration.ConclusionsThese findings suggested that managers wishing to enhance job satisfaction should assess workplace characteristics comprehensively and design mechanisms that reduce the gap between actual and desired workplace characteristics.

Objective: To understand the elements influencing the maternal deaths in the Limpopo province, South Africa.Methods: A retrospective review of all maternal deaths which occurred at the Pietersburg Hospital, Limpopo province was done over a five-year period (January 2011 to December 2015). The hospital death register was used to collate a list of maternal deaths occurring during the study period. The medical records of maternal deaths were reviewed. The total deliveries and live births for each year were obtained from the delivery registers. The data collected included maternal age, parity, referring facility, date of admission, date and time of death, ward where death occurred, and cause of death.Results: There were 14 685 live births and 232 maternal deaths between 2011 and 2015, resulting in an institutional Maternal Mortality Ratio (iMMR) of 1579/100 000 live births. The mean age of the patients was 29 years. Forty-three per cent of deaths occurred within 24 hours of admission, 35% died in ICU and 89% were referred from regional and district hospitals and community health centres. Of the referred patients, 83% were from district hospitals. Obstetric haemorrhage and pre-eclampsia, or eclampsia, were the main causes of death.Conclusion: The iMMR at Pietersburg Hospital remains unacceptably high. Most of the maternal deaths are due to obstetric haemorrhage, pre-eclampsia or eclampsia, medical and surgical disorder and non-pregnancy related infections.

Our study aims to measure outpatient waiting times at Vietnam health facilities according to the socioeconomic characteristics. We employed the 2015 Vietnam District and Commune Health Facility Survey which was a cross-sectional study designed by the World Bank in collaboration with the Vietnam Health Strategy and Policy Institute. This survey was designed to be representative of six provinces (Dien Bien, Hanoi, Binh Dinh, Dak Lak, Dong Nai, and Dong Thap) drawn from six distinct geographical regions of Vietnam. Data from 4949 outpatients at district hospitals (DHs) and 1724 outpatients at commune health centers (CHCs) were extracted for final analysis. We recorded average outpatient waiting times of 32.58 min at DHs and of 11.58 min at CHCs. Four hundred and forty-five outpatients at DHs (9.0%) and 720 those at CHCs (42.8%) were examined immediately (waiting time = 0 min). Outpatient waiting times were various in six distinct geographical regions. With an investigation according to several socioeconomic characteristics, significant differences in outpatient waiting times were observed at both two levels of health facilities as measured by province, age, self-reported health status, patient’s wealth, ethnicity, and health insurance. Conclusions. Outpatient waiting times from arrival at health facility until receiving care were significantly distinct amongst two health facility levels, revealing longer at DHs compared to at CHCs. There was significantly higher proportion of outpatients examined immediately at CHCs compared to at DHs. Our study suggests that, vulnerable populations, with longer outpatient waiting time, should be dealt with in appropriate models towards each medical facility according to key socioeconomic factors to contribute to simplify the process of medical examination and treatment for outpatients.

The purpose of this study was to assess the prevalence of psychological distress in employees in the metalliferous mining industry in Australia, and to examine associated demographic, health, and workplace characteristics. A cross sectional survey was conducted among 1,799 participants from four metalliferous mines. Psychological distress was measured by the Kessler Psychological Distress Scale (K10), alongside other measures of personal demographics, health history, health behaviour, and workplace characteristics. Univariate and multivariate statistical methods were used to examine associations between psychological distress and personal and workplace characteristics. Levels of moderate to very high psychological distress were significantly higher in this sample (44.4%) compared to the general population (27.2%). Moderate to very high psychological distress was significantly associated with younger age; individual health factors (a prior history of depression, anxiety, or drug/alcohol problems); health behaviours (using illicit drugs in the last month); and a range of workplace factors (concern about losing their job; lower satisfaction with work; working shifts of over 12 hours duration; working in mining for financial reasons and social factors (poorer social networks). The identification of a number of social, personal and workplace factors associated with high psychological distress present useful targets to inform the development of tailored workplace interventions to reduce distress in metalliferous mine employees.