scholarly journals Individual and community factors determining delayed leprosy case detection: A systematic review

2021 ◽  
Vol 15 (8) ◽  
pp. e0009651
Author(s):  
Yudhy Dharmawan ◽  
Ahmad Fuady ◽  
Ida Korfage ◽  
Jan Hendrik Richardus
Keyword(s):  
Health Service ◽  
Meta Analysis ◽  
Common Factor ◽  
Case Detection ◽  
Agricultural Labor ◽  
Related Factors ◽  
Community Factors ◽  
Leprosy Case ◽  
Seeking Behavior ◽  
The Individual

Background The number of new leprosy cases is declining globally, but the disability caused by leprosy remains an important disease burden. The chance of disability is increased by delayed case detection. This review focusses on the individual and community determinants of delayed leprosy case detection. Methods This study was conducted according to the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analysis). The study protocol is registered in PROSPERO (code: CRD42020189274). To identify determinants of delayed detection, data was collected from five electronic databases: Embase.com, Medline All Ovid, Web of Science, Cochrane CENTRAL, and the WHO Global Health Library. Results We included 27 papers from 4315 records assessed. They originated in twelve countries, had been published between January 1, 2000, and January 31, 2021, and described the factors related to delayed leprosy case detection, the duration of the delayed case, and the percentage of Grade 2 Disability (G2D). The median delay in detection ranged from 12 to 36 months, the mean delay ranged from 11.5 to 64.1 months, and the percentage of G2D ranged from 5.6 to 43.2%. Health-service-seeking behavior was the most common factor associated with delayed detection. The most common individual factors were older age, being male, having a lower disease-symptom perception, having multibacillary leprosy, and lack of knowledge. The most common socioeconomic factors were living in a rural area, performing agricultural labor, and being unemployed. Stigma was the most common social and community factor. Conclusions Delayed leprosy case detection is clearly correlated with increased disability and should therefore be a priority of leprosy programs. Interventions should focus on determinants of delayed case detection such as health-service-seeking behavior, and should consider relevant individual, socioeconomic, and community factors, including stigmatization. Further study is required of the health service-related factors contributing to delay.

Root Cause Analyses of Suicides of Mental Health Clients

Crisis ◽  
2015 ◽  
Vol 36 (5) ◽  
pp. 316-324 ◽  
Author(s):  
Donna Gillies ◽  
David Chicop ◽  
Paul O'Halloran
Keyword(s):  
Mental Health ◽  
Suicide Prevention ◽  
Common Factor ◽  
Data Collection Tool ◽  
Related Factors ◽  
Root Cause ◽  
Communication Problems ◽  
The Individual ◽  
Mental Health Clients ◽  
Imminent Risk

Abstract. Background: The ability to predict imminent risk of suicide is limited, particularly among mental health clients. Root cause analysis (RCA) can be used by health services to identify service-wide approaches to suicide prevention. Aims: To (a) develop a standardized taxonomy for RCAs; (b) to quantitate service-related factors associated with suicides; and (c) to identify service-related suicide prevention strategies. Method: The RCAs of all people who died by suicide within 1 week of contact with the mental health service over 5 years were thematically analyzed using a data collection tool. Results: Data were derived from RCAs of all 64 people who died by suicide between 2008 and 2012. Major themes were categorized as individual, situational, and care-related factors. The most common factor was that clients had recently denied suicidality. Reliance on carers, recent changes in medication, communication problems, and problems in follow-through were also commonly identified. Conclusion: Given the difficulty in predicting suicide in people whose expressions of suicidal ideation change so rapidly, services may consider the use of strategies aimed at improving the individual, stressor, support, and care factors identified in this study.

scholarly journals The Experience of Emotional Labor and Its Related Factors among Nurses in General Hospital Settings in Republic of Korea: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 13 (21) ◽  
pp. 11634
Author(s):  
Da-Jung Ha ◽  
Jung-Hyun Park ◽  
Su-Eun Jung ◽  
Boram Lee ◽  
Myo-Sung Kim ◽  
...  
Keyword(s):  
Systematic Review ◽  
General Hospital ◽  
Emotional Labor ◽  
Turnover Intention ◽  
Meta Analysis ◽  
Future Research ◽  
Related Factors ◽  
Cross Sectional ◽  
Targeted Interventions ◽  
The Individual

This systematic review and meta-analysis aimed to investigate the status of emotional labor and its related factors among nurses in general hospital settings in Korea. A total of seven electronic databases were comprehensively searched to find relevant cross-sectional studies published up to 28 January 2021. The meta-analysis was performed using Stata version 13.1. In total, 131 studies were included. The population showed a standardized mean difference of 3.38 (95% confidence interval, 3.34 to 3.42) in emotional labor assessed by a 1–5 Likert scale. The level of emotional labor had significant negative correlations with job satisfaction, social support, organizational engagement, coworker support, resilience, and nurses’ work environment, while it had significant positive correlations with emotional labor and burnout, turnover intention, and job stress. Although the methodological quality of the included studies was generally good, 24 of the included studies (18.32%) were evaluated as lacking generalization potential or otherwise as unclear. In conclusion, nurses in general hospital settings in Korea experience mild-to-moderate levels of emotional labor. There is some evidence that the emotional labor of nurses and its detrimental effects can be buffered at both the individual and hospital levels, and future research should focus on developing targeted interventions and evaluating their effectiveness.

The Orchard Plot: Cultivating a Forest Plot for Use in Ecology, Evolution and Beyond

2019 ◽  
Author(s):  
Shinichi Nakagawa ◽  
Malgorzata Lagisz ◽  
Rose E O'Dea ◽  
Joanna Rutkowska ◽  
Yefeng Yang ◽  
...  
Keyword(s):  
Meta Analysis ◽  
R Package ◽  
Effect Sizes ◽  
Forest Plot ◽  
Point Estimates ◽  
Aggregate Effect ◽  
The Individual ◽  
Meta Analyses ◽  
Heterogeneous Effect ◽  
Intuitive Interpretation

‘Classic’ forest plots show the effect sizes from individual studies and the aggregate effect from a meta-analysis. However, in ecology and evolution meta-analyses routinely contain over 100 effect sizes, making the classic forest plot of limited use. We surveyed 102 meta-analyses in ecology and evolution, finding that only 11% use the classic forest plot. Instead, most used a ‘forest-like plot’, showing point estimates (with 95% confidence intervals; CIs) from a series of subgroups or categories in a meta-regression. We propose a modification of the forest-like plot, which we name the ‘orchard plot’. Orchard plots, in addition to showing overall mean effects and CIs from meta-analyses/regressions, also includes 95% prediction intervals (PIs), and the individual effect sizes scaled by their precision. The PI allows the user and reader to see the range in which an effect size from a future study may be expected to fall. The PI, therefore, provides an intuitive interpretation of any heterogeneity in the data. Supplementing the PI, the inclusion of underlying effect sizes also allows the user to see any influential or outlying effect sizes. We showcase the orchard plot with example datasets from ecology and evolution, using the R package, orchard, including several functions for visualizing meta-analytic data using forest-plot derivatives. We consider the orchard plot as a variant on the classic forest plot, cultivated to the needs of meta-analysts in ecology and evolution. Hopefully, the orchard plot will prove fruitful for visualizing large collections of heterogeneous effect sizes regardless of the field of study.

scholarly journals Prognostic factors for chronic post-surgical pain after lung or pleural surgery: a protocol for a systematic review and meta-analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e051554
Author(s):  
Pascal Richard David Clephas ◽  
Sanne Elisabeth Hoeks ◽  
Marialena Trivella ◽  
Christian S Guay ◽  
Preet Mohinder Singh ◽  
...  
Keyword(s):  
Systematic Review ◽  
Prognostic Factors ◽  
Prognostic Factor ◽  
Meta Analysis ◽  
Case Series ◽  
Related Factors ◽  
Surgical Pain ◽  
Literature Reviews ◽  
Chronic Post Surgical Pain

IntroductionChronic post-surgical pain (CPSP) after lung or pleural surgery is a common complication and associated with a decrease in quality of life, long-term use of pain medication and substantial economic costs. An abundant number of primary prognostic factor studies are published each year, but findings are often inconsistent, methods heterogeneous and the methodological quality questionable. Systematic reviews and meta-analyses are therefore needed to summarise the evidence.Methods and analysisThe reporting of this protocol adheres to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) checklist. We will include retrospective and prospective studies with a follow-up of at least 3 months reporting patient-related factors and surgery-related factors for any adult population. Randomised controlled trials will be included if they report on prognostic factors for CPSP after lung or pleural surgery. We will exclude case series, case reports, literature reviews, studies that do not report results for lung or pleural surgery separately and studies that modified the treatment or prognostic factor based on pain during the observation period. MEDLINE, Scopus, Web of Science, Embase, Cochrane, CINAHL, Google Scholar and relevant literature reviews will be searched. Independent pairs of two reviewers will assess studies in two stages based on the PICOTS criteria. We will use the Quality in Prognostic Studies tool for the quality assessment and the CHARMS-PF checklist for the data extraction of the included studies. The analyses will all be conducted separately for each identified prognostic factor. We will analyse adjusted and unadjusted estimated measures separately. When possible, evidence will be summarised with a meta-analysis and otherwise narratively. We will quantify heterogeneity by calculating the Q and I2 statistics. The heterogeneity will be further explored with meta-regression and subgroup analyses based on clinical knowledge. The quality of the evidence obtained will be evaluated according to the Grades of Recommendation Assessment, Development and Evaluation guideline 28.Ethics and disseminationEthical approval will not be necessary, as all data are already in the public domain. Results will be published in a peer-reviewed scientific journal.PROSPERO registration numberCRD42021227888.

Safety climate and related factors in rehabilitation nurses of hospitals in Iran

Work ◽  
2021 ◽  
pp. 1-8
Author(s):  
Javad vatani ◽  
Zahra Khanikosarkhizi ◽  
Mohammad Ali Shahabi Rabori ◽  
mohammad khandan ◽  
Mohsen aminizadeh ◽  
...  
Keyword(s):  
Safety Climate ◽  
Cross Sectional Study ◽  
P Value ◽  
Related Factors ◽  
Cross Sectional ◽  
Climate Assessment ◽  
Safety Work ◽  
Significant Difference ◽  
Training Courses ◽  
The Individual

BACKGROUND: Safety climate is a common insight of staff that indicates individuals’ attitudes toward safety and priority of safety at work. OBJECTIVES: Nursing is a risky job where paying attention to safety is crucial. The assessment of the safety climate is one of the methods to measure the safety conditions in this occupation. The aim of this study was to assess the safety climate of rehabilitation nurses working in hospitals in Tehran. METHODS: This is a cross-sectional study which was carried out on 140 rehabilitation nurses selected from all hospitals and clinics in Tehran in 2019. To collect the required data, a two-section questionnaire was used. The first section was related to demographic factors and the second part (22 statements) was to measure the safety climate using nurses’ safety climate assessment questionnaire. The collected data were analyzed by SPSS V16 using independent t-test, ANOVA, Kruskal-Wallis and Mann-Whitney U test at the 5% level. RESULTS: Findings showed that the total mean of safety climate was 3.06±0.56. According to the results, a significant difference was found between the positive and negative satisfaction of nurses with safety climates (P-value = 0.03), communication with nurses (P-value = 0.01) and supervisors’ attitude (P-value = 0.02). Furthermore, a significant difference in safety climate between the individual with the second job and the individual without second could be observed (P-value = 0.01). CONCLUSIONS: The results indicated that the safety climate was not at an acceptable level. Thus, it is essential to introduce safety training courses (e.g. safety, work-rest balance, and so on) and to improve the safety performance at work.

scholarly journals Identification and inclusion of gender factors in retrospective cohort studies: the GOING-FWD framework

2021 ◽  
Vol 6 (4) ◽  
pp. e005413
Author(s):  
Valeria Raparelli ◽  
Colleen M. Norris ◽  
Uri Bender ◽  
Maria Trinidad Herrero ◽  
Alexandra Kautzky-Willer ◽  
...  
Keyword(s):  
Outcome Measurement ◽  
Meta Analysis ◽  
Synthetic Data ◽  
Well Being ◽  
Pooled Analysis ◽  
Research Network ◽  
Local Analysis ◽  
Related Factors ◽  
Measurement Framework ◽  
Definition Of

Gender refers to the socially constructed roles, behaviours, expressions and identities of girls, women, boys, men and gender diverse people. Gender-related factors are seldom assessed as determinants of health outcomes, despite their powerful contribution. The Gender Outcomes INternational Group: to Further Well-being Development (GOING-FWD) project developed a standard five-step methodology applicable to retrospectively identify gender-related factors and assess their relationship to outcomes across selected cohorts of non-communicable chronic diseases from Austria, Canada, Spain, Sweden. Step 1 (identification of gender-related variables): Based on the gender framework of the Women Health Research Network (ie, identity, role, relations and institutionalised gender), and available literature for a certain disease, an optimal ‘wish-list’ of gender-related variables was created and discussed by experts. Step 2 (definition of outcomes): Data dictionaries were screened for clinical and patient-relevant outcomes, using the International Consortium for Health Outcome Measurement framework. Step 3 (building of feasible final list): a cross-validation between variables per database and the ‘wish-list’ was performed. Step 4 (retrospective data harmonisation): The harmonisation potential of variables was evaluated. Step 5 (definition of data structure and analysis): The following analytic strategies were identified: (1) local analysis of data not transferable followed by a meta-analysis combining study-level estimates; (2) centrally performed federated analysis of data, with the individual-level participant data remaining on local servers; (3) synthesising the data locally and performing a pooled analysis on the synthetic data and (4) central analysis of pooled transferable data. The application of the GOING-FWD multistep approach can help guide investigators to analyse gender and its impact on outcomes in previously collected data.

Exploring the Dimensions of Recovery and User Experience

2014 ◽  
Vol 3 (4) ◽  
pp. 305-311
Author(s):  
Peter Jones
Keyword(s):  
Mental Health ◽  
Mental Health Service ◽  
Health Service ◽  
Health Service Provision ◽  
Domain Specific ◽  
The Past ◽  
Economic Climate ◽  
Health And Social Care ◽  
The Individual ◽  
Mental Health Service Provision

The concept of recovery is widely applied within service delivery in the field of mental health. The dimensions of recovery were explored using a singular conceptual framework known as Hodges’ model, which is shown to be suited to this particular task. This arises from the model’s structure, in that it encompasses the individual-group and a care domain specific to the political aspects of both health and social care. The evidence was found by relating recovery to the model’s care domains, which is also relevant to the experience of mental health service users and developments over the past decade in mental health service provision. Particular attention is given to the ‘Recovery Star’. This can be used as a key-working and outcomes tool. The discussion is also placed in a context of the current socio-economic climate, notably the ‘politics of recovery’ at a time of austerity.

Metastudie industrieller Energieflexibilität*/Meta-analysis of industrial energy flexibility - An approach for optimizing the identification of energy flexibility potentials

2017 ◽  
Vol 107 (09) ◽  
pp. 610-616
Author(s):  
S. Eisenhauer ◽  
F. Zimmermann ◽  
M. Reichart ◽  
P. Accordi ◽  
A. Prof. Sauer
Keyword(s):  
Production System ◽  
Meta Analysis ◽  
German Industry ◽  
Wird Eine ◽  
Bottom Up ◽  
Systematic Analysis ◽  
Industry Level ◽  
Large Spread ◽  
Industrial Energy ◽  
The Individual

Bisherige Studien über energetische Flexibilität in der deutschen Industrie weisen das vorhandene Flexibilitätspotenzial mit hoher Streuung aus. Diese Arbeit analysiert relevante Studien in Bezug auf deren Annahmen und Vorgehensweise. Aufbauend auf den bisherigen Vorgehensweisen wird ein Ansatz zur Erhebung der Daten im Produktionssystem vorgestellt. Des Weiteren wird eine Methode zur Aggregation der Daten hoch bis auf Branchenebene entwickelt.   Previous studies on the energetic flexibility of German industry show potentials with a large spread. Therefore, in this article, a systematic analysis of the individual studies and an evaluation of the indicated flexibility potentials are carried out. Based on the existing methods, a bottom-up approach for collecting the data in the production system and the aggregation up to the industry level is presented.

Feedback-Seeking Behavior in Organizations: A Meta-Analysis and Systematical Review of Longitudinal Studies

2021 ◽  
Vol 24 ◽  
Author(s):  
Alexandra Bălăceanu ◽  
Delia Vîrgă ◽  
Laurentiu Maricuțoiu
Keyword(s):  
Systematic Review ◽  
Longitudinal Studies ◽  
Structural Equation ◽  
Longitudinal Design ◽  
Meta Analysis ◽  
Equation Modeling ◽  
Personal Resources ◽  
Feedback Seeking ◽  
Eligibility Criteria ◽  
Seeking Behavior

Abstract Based on the Job Demands-Resources theory, this meta‐analysis investigates the role of resources in predicting feedback-seeking behavior (FSB) over time. We also examine the relationship between FSB and its outcomes from a systematic review perspective. The eligibility criteria were: (a) to measure feedback-seeking behavior, (b) to have a longitudinal design, and (c) to have employees as target groups. Thirteen studies met these criteria (Ntotal= 1,527). We combined the meta-analysis procedures and structural equation modeling (metaSEM) and used the systematic review. The methodological quality of the available longitudinal studies is assessed. Our findings indicated that job resources predict future feedback-seeking behavior and between feedback-seeking behavior and personal resources is significant relationship. More research is needed to clarify the reciprocal relationships between personal resources and feedback-seeking behavior and the influences of feedback-seeking behavior on performance.

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