A guide for the utilization of Health Insurance Review and Assessment Service National Patient Samples

The claims data of the Health Insurance Review and Assessment Service (HIRA) is an important source of information for healthcare service research. The claims data of HIRA is collected when healthcare service providers submit a claim to HIRA to be reimbursed for a service that they provided to patients. To improve the accessibility of healthcare service researchers to claims data of HIRA, HIRA has developed the Patient Samples which are extracted using a stratified randomized sampling method. The Patient Samples of HIRA consist of five tables: a table for general information (Table 20) containing socio-demographic information such as gender, age and medical aid, indicators for inpatient and outpatient services; a table for specific information on healthcare services provided (Table 30); a table for diagnostic information (Table 40); a table for outpatient prescriptions (Table 53) and a table for information on healthcare service providers (Table of providers). Researchers who are interested in using the Patient Sample data for research can apply via HIRA's website (https://www.hira.or.kr).

Comparison of methods for the analysis of relatively simple mediation models

Background/aims

Statistical mediation analysis is an often used method in trials, to unravel the pathways underlying the effect of an intervention on a particular outcome variable. Throughout the years, several methods have been proposed, such as ordinary least square (OLS) regression, structural equation modeling (SEM), and the potential outcomes framework. Most applied researchers do not know that these methods are mathematically equivalent when applied to mediation models with a continuous mediator and outcome variable. Therefore, the aim of this paper was to demonstrate the similarities between OLS regression, SEM, and the potential outcomes framework in three mediation models: 1) a crude model, 2) a confounder-adjusted model, and 3) a model with an interaction term for exposure-mediator interaction.

Methods

Secondary data analysis of a randomized controlled trial that included 546 schoolchildren. In our data example, the mediator and outcome variable were both continuous. We compared the estimates of the total, direct and indirect effects, proportion mediated, and 95% confidence intervals (CIs) for the indirect effect across OLS regression, SEM, and the potential outcomes framework.

Results

OLS regression, SEM, and the potential outcomes framework yielded the same effect estimates in the crude mediation model, the confounder-adjusted mediation model, and the mediation model with an interaction term for exposure-mediator interaction.

Conclusions

Since OLS regression, SEM, and the potential outcomes framework yield the same results in three mediation models with a continuous mediator and outcome variable, researchers can continue using the method that is most convenient to them.

Evaluating the relationship between temporal changes in land use and resulting water quality

Changes in land use have a direct impact on receiving water quality. Effective mitigation strategies require the accurate prediction of water quality in order to enhance community well-being and ecosystem health. The research study employed Bayesian Network modelling to investigate the validity of using cross-sectional and longitudinal data on water quality and land use for predicting water quality in a mixed use catchment and the role it plays in the generation of blue-green algae in the receiving marine environment. Bayesian Network modelling showed that cross-sectional and longitudinal data analyses generate contrasting information about the influence of different land uses on surface water pollution. The modelling outcomes highlighted the lack of reliability in cross-sectional data analysis, based on the indication of spurious relationships between water quality and land use. On the other hand, the longitudinal data analysis, which accounted for changes in water quality and land use over a ten-year period, informed how catchment water quality varies in response to temporal changes in land use. The longitudinal data analysis further revealed that the types of anthropogenic activities have a more significant influence on pollutant generation than the change in the area extent of different land uses over time. Therefore, the careful interpretation of the findings derived solely from cross-sectional data analysis is important in the design of long-term strategies for pollution mitigation.

The effect of snacking and eating frequency on dietary quality in British adolescents

PURPOSE

To describe the effects of number of eating occasions and snacks on dietary quality (DQ), defined as adherence to dietary recommendations.

METHODS

A sample of 884 adolescents (11-18 years) in the UK National Diet and Nutrition Survey (NDNS) were included. The Diet Quality Index for Adolescents (DQI-A) was implemented. The total number of eating occasions and snacks was frequency of food or beverages consumed over 24 h and frequency of foods or beverages consumed outside of the three mealtimes, respectively. Results were generated with and without low-energy food under 210 kJ (50 kcal). Regression models were generated with DQ score as the outcome variable and number of eating occasions and snacks as predictors.

RESULTS

The mean (95 % CI) DQ score was 31.1 % (30.2, 32.0). The mean number of eating occasions and snacks was 7.5 (7.3, 7.7) and 2.6 (2.6, 2.7) times/day, respectively. When low-energy events were excluded, the mean number of eating occasions and snacks reduced to 6.2 (6.1, 6.4) and 2.0 (2.0, 2.1) times/day, respectively. DQ score increased by 0.74 points (0.42, 1.05; p < 0.01) and 0.55 points (-0.08, 0.69; p = 0.17) for total eating occasions and snacks, respectively. When low-energy events were excluded, DQ score increased by 0.30 points (-0.84, 0.69; p = 0.13) for each eating occasion and decreased by 1.20 points (-2.1, -0.3; p < 0.01) for each snack.

CONCLUSION

Eating more frequently improves dietary quality especially if some eating occasions are low in energy. A focus on replacing high-energy snacks with low-energy alternatives rather than reducing the number of eating occasions may result in improved dietary quality in adolescents.

Self-esteem across adulthood: the role of resources

It is still not well understood how and why developmental trajectories of self-esteem change, particularly in late life. We investigated the role of resources for self-esteem change across adulthood. In detail, we explored between-person differences in self-esteem levels and change in relation to resources with participants who ranged in age from 17 to 100 years. Study 1 consisted of a cross-sectional representative German sample of 12,609 participants, where we observed few age differences in mean levels of self-esteem across adulthood. Being married or in a relationship and positive subjective health were associated with higher levels of self-esteem. In addition, relations of resources of subjective health as well as neuroticism with self-esteem appeared to be smaller in late compared to young adulthood. Longitudinal studies including young (N = 338) and older adults (N = 325) indicated both reasonably high stability regarding rank-order and mean levels of self-esteem across 4 and 8 years. Again, age-differential resources appeared to be important for higher levels of self-esteem with education being related to self-esteem in young adults and subjective health in late life. However, no resource was associated with changes in self-esteem in either young or late adulthood. Overall, findings suggest that self-esteem levels are reflective of age-specific constraints and risks.

Increasing the quantity of separated post-consumer plastics for reducing combustible household waste: The case of rigid plastics in Flanders

In Flanders, Belgium, rigid and soft plastics represent an interesting fraction of residual household waste as a potential 80 000 Gg a^-1 can be recycled instead of incinerated. Removing a large amount of rigid packaging and non-packaging plastics from the residual household waste fraction could contribute to the goal to reduce the amount of residual household waste to less than 150 kg capita^-1 a^-1 for the Flemish region, where currently only 20% of plastics are collected selectively in drop-off facilities. Given the wide range of plastic separation schemes across the region, it is the aim of this paper to identify whether the applied separation options have an impact on the quantity of separated plastics, and, moreover, which scheme is able to separate most plastics. Cross-sectional data for the period 2008-2012 were collected for all 308 Flemish municipalities to conduct a regression analysis. The results of the analysis show that the quantity of separated plastics differs significantly between the different separation schemes used. If municipalities change their separation schemes, Flanders as a whole would be able to collect more plastic waste to better comply with its own objectives and EU regulation on recycling. Improved separation-at-source recycling initiatives, by applying the appropriate separation scheme for plastics, may increase recycling growth.

Adult low-risk drinkers and abstainers are not the same

Background

Alcohol consumption, even at low-levels, can not be guaranteed as safe or risk free. Specifically, the 2009 Australian National Health and Medical Research Council drinking guidelines recommend that adults should not drink more than two standard drinks on any day on average, and no more than four drinks on a single occasion. Nearly 40% of Australians aged 12 years and older drink alcohol but don’t exceed these recommended limits, yet adult low-risk drinkers have been largely overlooked in Australian alcohol survey research, where they are usually grouped with abstainers. This paper examines the socio-demographic profile of low-risk drinking adults (18+ years old), compared to those who abstain.

Methods

Data from the 2013 National Drug Strategy Household Survey were used. In the past 12 months, 4796 Australians had not consumed alcohol and 8734 had consumed alcohol at low-risk levels, accounting for both average volume and episodic drinking (hereafter low-risk).

Results

Multivariate logistic regression results indicated that low-risk drinkers were more likely to be older, married, Australian-born, and reside in a less disadvantaged neighbourhood compared with abstainers. There was no significant difference by sex between low-risk drinkers and abstainers.

Conclusions

The socio-demographic profile of low-risk drinkers differed from that of abstainers. Combining low-risk drinkers and abstainers into a single group, which is often the practice in survey research, may mask important differences. The study may support improved targeting of health promotion initiatives that encourage low-risk drinkers not to increase consumption or, in view of increasing evidence that low-risk drinking is not risk free, to move towards abstinence.

Estimating Transitional Probabilities with Cross-Sectional Data to Assess Smoking Behavior Progression: A Validation Analysis

BACKGROUND AND OBJECTIVE

New analytical tools are needed to advance tobacco research, tobacco control planning and tobacco use prevention practice. In this study, we validated a method to extract information from cross-sectional survey for quantifying population dynamics of adolescent smoking behavior progression.

METHODS

With a 3-stage 7-path model, probabilities of smoking behavior progression were estimated employing the Probabilistic Discrete Event System (PDES) method and the cross-sectional data from 1997-2006 National Survey on Drug Use and Health (NSDUH). Validity of the PDES method was assessed using data from the National Longitudinal Survey of Youth 1997 and trends in smoking transition covering the period during which funding for tobacco control was cut substantively in 2003 in the United States.

RESULTS

Probabilities for all seven smoking progression paths were successfully estimated with the PDES method and the NSDUH data. The absolute difference in the estimated probabilities between the two approaches varied from 0.002 to 0.076 (p>0.05 for all) and were highly correlated with each other (R² =0.998, p<0.01). Changes in the estimated transitional probabilities across the 1997-2006 reflected the 2003 funding cut for tobacco control.

CONCLUSIONS

The PDES method has validity in quantifying population dynamics of smoking behavior progression with cross-sectional survey data. The estimated transitional probabilities add new evidence supporting more advanced tobacco research, tobacco control planning and tobacco use prevention practice. This method can be easily extended to study other health risk behaviors.

Multinomial additive hazard model to assess the disability burden using cross-sectional data

Population aging is accompanied by the burden of chronic diseases and disability. Chronic diseases are among the main causes of disability, which is associated with poor quality of life and high health care costs in the elderly. The identification of which chronic diseases contribute most to the disability prevalence is important to reduce the burden. Although longitudinal studies can be considered the gold standard to assess the causes of disability, they are costly and often with restricted sample size. Thus, the use of cross-sectional data under certain assumptions has become a popular alternative. Among the existing methods based on cross-sectional data, the attribution method, which was originally developed for binary disability outcomes, is an attractive option, as it enables the partition of disability into the additive contribution of chronic diseases, taking into account multimorbidity and that disability can be present even in the absence of disease. In this paper, we propose an extension of the attribution method to multinomial responses, since disability is often measured as a multicategory variable in most surveys, representing different severity levels. The R function constrOptim is used to maximize the multinomial log-likelihood function subject to a linear inequality constraint. Our simulation study indicates overall good performance of the model, without convergence problems. However, the model must be used with care for populations with low marginal disability probabilities and with high sum of conditional probabilities, especially with small sample size. For illustration, we apply the model to the data of the Belgian Health Interview Surveys.

Is exposure to secondhand smoke associated with current depression (PHQ-8) among never-smokers? Results from a survey among German adults

Background

Findings on the association between exposure to secondhand smoke (SHS) and depression are contradictory. Comparability of existing research is limited due to varied methods and measures. This study examines the potential association between exposure to SHS and depression and a potential moderation by sex using representative data from Germany.

Methods

For our study, we used data from the German Health Update (GEDA) 2014/2015 on n = 10,274 never-smokers. We calculated a logistic regression model with an interaction term for potential sex-exposure interactions. We used the self-reported duration of exposure to predict current depression of any type as defined by the Patient Health Questionnaire PHQ-8 (score ≥ 10), accounting for a large number of confounders.

Results

In our sample, prevalence of depression was 8.8% in women and 5.3% in men. 90.4% were never or almost never exposed to SHS, while 7.1% were exposed < 1 h per day and around 2.5% reported being exposed for ≥1 h per day. While SHS exposure for < 1 h per day was not associated with current depression (OR = 1.54; 95%-CI: 0.93–1.61), SHS exposure for at least 1 h per day was associated with increased odds for current depression (OR = 1.59; 95%-CI: 1.08–2.35). No sex-specific differences were found.

Conclusions

Higher levels of SHS exposure are associated with current depression, although the nature and direction of the association are still unclear. We identified no differences in the association between men and women. More studies, particularly using longitudinal data, are needed to determine the nature of the association.

Self-reported hearing impairment among Greenlandic adolescents: Item development and findings from the Health Behaviour in School-aged Children study 2018

OBJECTIVES

Ear infections are the leading cause of hearing impairment among children worldwide and a major public health problem in many indigenous populations, yet representative studies of self-reported hearing impairment are currently scarce. The purpose of the present study was therefore two-sided; first to develop an item bank for the collection of data on hearing impairment among Greenlandic adolescents, and second to report data on the child reports on hearing impairment from a national questionnaire-based survey.

METHODS

The study describes the process of developing items measuring hearing impairment among schoolchildren, and reports data for their inclusion into a national questionnaire survey. The data formed part of the Health Behaviour in School-aged Children (HBSC Greenland) 2018 survey including 2,273 students, corresponding to 47.6% of all Greenlandic schoolchildren in the age range from 10 to 16 years. Data analyses performed describe the data characteristics and the frequency of self-reported hearing impairment among Greenlandic schoolchildren. Binary logistic regression examined the associations of hearing impairment on school-related (risk) factors and self-rated health.

RESULTS

An average of 4% reported experiencing ear pain almost daily, and almost 10% reported ear pain at least weekly. Moreover, 3% reported having inflammation in the ear at least weekly, and 5% reported to have such impaired hearing that they were not at all able to follow what happened in school. Logistic regression showed that girls had significantly higher odds of low self-rated health, poor school environment and academic achievement below average when they had experienced impaired hearing. All ORs were statistically significant, varying from 1.85 (95% CI: 1.16-2.94) for low self-rated health, to 3.05 (95% CI 1.83-5.11) for feeling pressured by schoolwork. For boys the only significant association with impaired hearing was an academic achievement below average of 1.73 (95% CI 1.08-2.77).

CONCLUSIONS

The study confirms clinical knowledge and case studies that there are a significant proportion of Greenlandic adolescents who have experienced impaired hearing. Future studies may use questionnaire data to follow up on children with hearing impairment to be able to report changes over time and associations to school-related and social factors.

Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar

As the national reference laboratory for febrile illness in Madagascar, we processed samples from the first epidemic wave of COVID-19, between March and September 2020. We fit generalized additive models to cycle threshold (C_t) value data from our RT-qPCR platform, demonstrating a peak in high viral load, low-C_t value infections temporally coincident with peak epidemic growth rates estimated in real time from publicly-reported incidence data and retrospectively from our own laboratory testing data across three administrative regions. We additionally demonstrate a statistically significant effect of duration of time since infection onset on C_t value, suggesting that C_t value can be used as a biomarker of the stage at which an individual is sampled in the course of an infection trajectory. As an extension, the population-level C_t distribution at a given timepoint can be used to estimate population-level epidemiological dynamics. We illustrate this concept by adopting a recently-developed, nested modeling approach, embedding a within-host viral kinetics model within a population-level Susceptible-Exposed-Infectious-Recovered (SEIR) framework, to mechanistically estimate epidemic growth rates from cross-sectional C_t distributions across three regions in Madagascar. We find that C_t-derived epidemic growth estimates slightly precede those derived from incidence data across the first epidemic wave, suggesting delays in surveillance and case reporting. Our findings indicate that public reporting of C_t values could offer an important resource for epidemiological inference in low surveillance settings, enabling forecasts of impending incidence peaks in regions with limited case reporting.

Factors affecting the livestock herd size among smallholder households in Zambia

Structural changes in the economic and demographic landscapes in the developing countries create a host of opportunities for smallholder livestock producers to tap into the economic growth from which they have largely been excluded. However, small livestock herd sizes limit the opportunities available to farmers to commercialize and benefit from the growing demand for livestock and livestock products. Therefore, understanding what it takes to build and maintain the herd size is a critical step in addressing the problem of low market participation. The study used five cross-sectional nationally representative data sets to arrive at the following conclusions. While purchases are a primary source for the initial stock, births are the principal way of increasing the herd size. Livestock deaths as reflected by high mortality rates are the major outflow channel through which livestock leaves the herd, and reducing the mortality rates has a positive effect on the livestock population as evidenced within the cattle sub-sector. Thus, provision of adequate animal health services is key to addressing the high mortality rates which subsequently can lead to increased herd size. As births are the primary means of increasing the herd size, it is necessary to implement interventions that address the reproduction rates. The interventions include adequate feeding of livestock on high-quality feed and strategic feeding to address the dry season challenges. These interventions can facilitate the growth of the young livestock into mature breeding stock and thus increase the herd size.

Impacts of grandparenting on older Chinese adults' mental health: a cross-sectional study

BACKGROUND

The practice of grandparenting has been growing in popularity worldwide, particularly in Asian societies. Nevertheless, there is a lack of thorough studies investigating the mental health effects of grandchild care on grandparents, particularly within the family context. The present study aimed to explore the impact of grandparenting on depressive symptoms in older Chinese adults, taking into account the functional role of intergenerational support.

METHODS

Using the China Longitudinal Aging Social Survey (CLASS, 2014 and 2018, N = 9,486), we employed the Pooled Ordinary Least Square method (POLS) to explore the association between depressive symptoms and grandparenting intensity as well as include the interaction terms to investigate the role of intergenerational support among grandparents aged from 60 to 80.

RESULTS

After adjusting for control variables, both non-intensive (-0.17; 95% CI: -0.30, -0.03) and intensive (-0.69; 95% CI: -0.95, -0.43) childcare, as well as giving financial support to adult children (-0.06; 95% CI: -0.08, -0.04) and emotional closeness with them (-0.94; 95% CI: -1.15, -0.72), were found to have a positive impact on the mental health of grandparents. Giving financial support (non-intensive: -0.04, 95% CI: -0.07, -0.01; intensive: -0.06, 95% CI: -0.13, -0.01) and providing instrumental support to adult children (non-intensive: -0.12, 95% CI: -0.24, -0.01; intensive: -0.19, 95% CI: -0.37, -0.02) moderated the association between grandparenting and the mental health of older adults, regardless of care intensity. However, the moderating role of receiving financial support (-0.07; 95% CI: -0.12, -0.02) only existed when non-intensive childcare was provided.

CONCLUSION

Grandchild care predicted better mental health in grandparents, mainly when they engaged in intensive grandparenting. Emotional closeness and providing financial support to adult children brought mental health benefits to grandparents involved in childcare. Giving financial support and providing instrumental support to adult children moderated the association between grandparenting and the mental health of older adults. However, the moderating role of receiving financial support from adult children only existed when non-intensive childcare was provided.

Identifying Keystone Species in the Microbial Community Based on Cross- Sectional Data

BACKGROUND

In microbial communities, the keystone species have a greater impact on the performance and dynamics of ecosystem than that of other species, in which we can see from the results that losing gut microbiome causes some specific diseases. A number of ongoing studies aim at identifying links between microbial community structure and human diseases.

METHOD

In this paper, we have introduced a valid keystone species identification method, in which a new Spread Intensity (SI) algorithm is used. Because the accuracies of current keystone species identification algorithms are difficult to evaluate for the high diversity and uncultivated status of microbial communities, we simulated cross-sectional data of microbial communities with known interactions and set up standard keystoneness rankings using Generalized Lotka-Volterra (GLV) model. Subsequently, we compared the SI algorithm with existing methods by using simulated data and obtained an obvious better performance of SI algorithm than other methods. Also, we applied this method to gut microbiota datasets and identified some microbes having the potential association with body weight. We first assembled three correlation metrics to calculate the interspecies correlation. Then we applied network deconvolution to remove indirect correlations. Finally, we used Molecular Ecological Network Analysis (MENA) to construct the co-occurrence network. According to experimental results, SI algorithm has an excellent performance in identifying highly correlated species in gut microbiome to body weight.

RESULT

This result provides an effective indicator for modulating gut microbiota and thus enables the gene therapy and other gene-level treatments for losing-weight and other gut-associated diseases.

A GAN based approach for inferring progression trajectories of costal cartilage calcification from cross-sectional data at image level

BACKGROUND

Costal cartilage calcification (CCC) increases with age and presents differently for men and women. In individuals, however, the cross-sectional studies that show such trends do not reveal the geometric trajectories through which calcification might accumulate across a lifetime. Generative adversarial networks have the potential to reveal such trajectories from cross-sectional data by learning population trends and synthesizing individualized images at progressive levels of calcification.

METHODS

Chest wall mid-surface CT images with normalized cartilage morphologies were produced for 379 subjects aged 6 to 90, and labeled by sex and calcification severity. A conditional GAN with added loss terms to favor one-way accumulation of CCC was trained using organized image batches. GAN performance was assessed by comparing the distributions of images between the training and synthetic groups.

RESULTS

Synthetic images generated from a common seed for a given sex and at successive calcification severity levels showed incremental and regional growth of calcification sites. CCC patterns for synthetic male and female images matched known sex-based differences, and individual CCC growth in synthetic images was consistent with previously observed population trends. These trends in the synthetic images were also quantified by structural similarity scores. Synthetic images generated from different input seeds further showed individual variance in specific regions and trajectories of CCC accumulation.

CONCLUSION

This study inferred individual progression of CCC accumulation from uncalcified to severely calcified using cross-sectional image data. This information can inform computational models of the changing chest wall biomechanics with age, and the GAN-based technique shows potential for inferring longitudinal data from population trends in other clinical areas.

A taxonomy of multiple regression methods for immunologists

Multiple regression is a powerful tool in the immunologist's toolbox. This paper defines multiple regression, discusses availability and accessibility, provides some additional helpful definitions, treats the topics of transformation and extreme value screening, and establishes the paper's scope and philosophy. Then eleven methods of multiple regression are detailed, giving strengths and limitations. Throughout an emphasis is placed on application to immunological assays. A flowchart to guide selection of multiple regression methods is provided.

Understanding the dynamics of sexual and reproductive health outcomes in sub-Saharan Africa using the Demographic and Health Survey: the need for longitudinal studies

Sub-Saharan Africa has considerable obstacles in sexual and reproductive health, encompassing unwanted pregnancies, unsafe abortions, sexually transmitted illnesses, and sexual assault. Although cross-sectional data, like the Demographic and Health Survey, offer useful insights, they are constrained in their ability to capture the dynamic aspects of sexual and reproductive health issues. This perspective contends that a thorough comprehension of sexual and reproductive health necessitates the incorporation of longitudinal studies to guide evidence-based practices. Longitudinal studies can monitor temporal changes, identify risk factors, assess intervention efficacy, and offer a more nuanced comprehension of sexual and reproductive health dynamics in sub-Saharan Africa. Notwithstanding the difficulties inherent in longitudinal research, commitment to this methodology is crucial for formulating effective policies and programmes aimed at enhancing sexual and reproductive health outcomes in the region.

Utilizing Artificial Neural Networks for Establishing Hearing-Loss Predicting Models Based on a Longitudinal Dataset and Their Implications for Managing the Hearing Conservation Program

Background

Though the artificial neural network (ANN) technique has been used to predict noise-induced hearing loss (NIHL), the established prediction models have primarily relied on cross-sectional datasets, and hence, they may not comprehensively capture the chronic nature of NIHL as a disease linked to long-term noise exposure among workers.

Methods

A comprehensive dataset was utilized, encompassing eight-year longitudinal personal hearing threshold levels (HTLs) as well as information on seven personal variables and two environmental variables to establish NIHL predicting models through the ANN technique. Three subdatasets were extracted from the afirementioned comprehensive dataset to assess the advantages of the present study in NIHL predictions.

Results

The dataset was gathered from 170 workers employed in a steel-making industry, with a median cumulative noise exposure and HTL of 88.40 dBA-year and 19.58 dB, respectively. Utilizing the longitudinal dataset demonstrated superior prediction capabilities compared to cross-sectional datasets. Incorporating the more comprehensive dataset led to improved NIHL predictions, particularly when considering variables such as noise pattern and use of personal protective equipment. Despite fluctuations observed in the measured HTLs, the ANN predicting models consistently revealed a discernible trend.

Conclusions

A consistent correlation was observed between the measured HTLs and the results obtained from the predicting models. However, it is essential to exercise caution when utilizing the model-predicted NIHLs for individual workers due to inherent personal fluctuations in HTLs. Nonetheless, these ANN models can serve as a valuable reference for the industry in effectively managing its hearing conservation program.

[Organizational measures to increase work satisfaction in residential long-term care: A cross-sectional survey from Austria]

BACKGROUND

With increasing care needs and a decline in nursing staff, measures must be found to make long-term care (LTC) attractive for nursing staff and at the same time encourage them to remain in the care sector. For this reason, the question is answered: "How do organizational measures, identified by nursing staff, contribute to improving job satisfaction?".

METHOD

In a non-proportional quota sample along the federal state distribution, the implementation of measures was surveyed in a cross-sectional survey in LTC facilities. The effect of the measures on job satisfaction was analyzed using multiple linear regression.

RESULTS

The bundles of measures show a high internal consistency of 0.771 to 0.863. Regression analyses revealed that the bundles of measures, like making LTC more attractive (B = 0.244; p < 0.05), integrating interns (B = 0.222, p < 0.05), duty scheduling and working hours (B = 0.324, p < 0.05), and strengthening relationships (B = 0.078), explain more than 60% of the variance in job satisfaction. Overtime has a negative effect but can be mitigated by duty scheduling (B = -0.017, p < 0.05). Women report higher levels of job satisfaction than men. The type of organization, age and vocational training have no influence on job satisfaction.

DISCUSSION

Duty scheduling and working hours are important factors. Loss in job satisfaction can be cushioned by focusing on these measures.

CONCLUSIONS

The bundles of measures "Making LTC more attractive", "Duty scheduling and working hours", "Integrating interns", and "Strengthening relationships" are positively associated with job satisfaction. Accordingly, care facilities that implement these bundles of measures have higher job satisfaction rates.