Availability and Spatial Inequality of Rural Infrastructure in Jungle Mahal Blocks of Purulia District, India

2021 ◽  
pp. 232102492110082
Author(s):  
Uttam Kumar Patra ◽  
Suman Paul

Rural infrastructure is fundamental and central to the concept of quality of life as well as human development. The major characteristic of regional development is the constant widening of regional disparity in India after different plan period. Various Finance Commissions and Planning Commissions laid emphasis on the objective of achieving balanced regional development. The article identifies a gap in terms of education, health, communication and financial infrastructure in the study of panchayats of Jungle Mahal blocks. Mapping of regional disparities can aid in effective policymaking at the preliminary stage of planning. Panchayat level inequality has been analysing using dimension index and principal component analysis (PCA). Wide disparities in the availability of rural infrastructure have been pointed out and proper recommendation has also been made to minimise the gap in spatial inequality.

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Chadia Haddad ◽  
Hala Sacre ◽  
Sahar Obeid ◽  
Pascale Salameh ◽  
Souheil Hallit

Abstract Background In clinical practice, quality of life measures can be used alongside some types of assessment to give valuable information that can identify areas that influence an individual and help the clinician make the best healthcare choices. This study aimed to investigate the psychometric properties of the Arabic version of the 12-item short-form health survey (SF-12) in a sample of Lebanese adults. Methods This cross-sectional study performed between July and November 2019 recruited 269 participants. Cronbach’s alpha was used to assess the reliability of the SF-12 questionnaire, and a factor analysis using the principal component analysis was performed to confirm its construct validity. Results The mean score for the “physical component summary (PCS-12)” was 50.27 ± 8.94 (95 % CI: 49.18–51.36) and for the “Mental component summary (MCS-12)” was 44.95 ± 12.17 (95 % CI: 43.47–46.43). A satisfactory Cronbach’s alpha was found for the two components: MCS (α = 0.707) and PCS (α = 0.743). The principal component analysis converged over a two-factor solution (physical and mental), explaining a total variance of 55.75 %. Correlations between the SF-12 scales and single items were significant, showing a good construct validity. The “physical functioning”, “role physical”, “bodily pain”, and “general health” subscales were highly associated with “PCS-12”, while the “vitality”, “social functioning”, “role emotional”, and “mental health” subscales were more associated with MCS-12. Conclusions The Arabic version of the SF-12 is a reliable, easy-to-use, and valid tool to measure health-related quality of life in the general population. Future studies using a larger sample size and focusing on questionnaire psychometric properties are necessary to confirm our findings.


2015 ◽  
Vol 22 (1) ◽  
pp. 37-41 ◽  
Author(s):  
Verônica F Parreira ◽  
Renata N Kirkwood ◽  
Megan Towns ◽  
Isabel Aganon ◽  
Lauren Barrett ◽  
...  

BACKGROUND: In addition to symptoms, such as dyspnea and fatigue, patients with chronic obstructive pulmonary disease (COPD) also experience mood disturbances.OBJECTIVE: To explore the relationships between health-related quality of life measures collected from patients with stable COPD and a commonly used measure of depression and anxiety.METHODS: The present analysis was a retrospective study of patients with COPD enrolled in a pulmonary rehabilitation program. Hospital Anxiety and Depression Scale (HADS), Chronic Respiratory Disease Questionnaire (CRQ), Medical Research Council dyspnea scale and 6 min walk test data were collected. Statistical analyses were performed using Spearman’s correlations, and categorical regression and categorical principal component analysis were interpreted using the biplot methodology.RESULTS: HADS anxiety scores retrieved from 80 patients were grouped as ‘no anxiety’ (n=43 [54%]), ‘probable anxiety’ (n=21 [26%]) and ‘presence of anxiety’ (n=16 [20%]). HADS depression scores were similarly grouped. There was a moderate relationship between the anxiety subscale of the HADS and both the emotional function (r=−0.519; P<0.01) and mastery (r=−0.553; P<0.01) domains of the CRQ. Categorical regression showed that the CRQ-mastery domain explained 40% of the total variation in anxiety. A principal component analysis biplot showed that the highest distance between the groups was along the mastery domain, which separated patients without feelings of anxiety from those with anxiety. However, none of the CRQ domains were able to discriminate the three depression groups.CONCLUSIONS: The CRQ-mastery domain may identify symptoms of anxiety in patients with COPD; however, the relationship is not strong enough to use the CRQ-mastery domain as a surrogate measure. None of the CRQ domains were able to discriminate the three depression groups (no depression, probable and presence); therefore, specific, validated tools to identify symptoms of depression should be used.


Author(s):  
Julie Poláčková ◽  
Andrea Jindrová

The paper is focused on the methodological approaches to assess subjective aspects of the quality of life in the various regions. Besides, directly measurable indicators, which may not always correspond with the quality of life of the individuals in the regions, the subjective aspects of well-being are also in the spotlight. The pilot analysis examined the answers to questions such as: Are you satisfied with the health and social services, the cost of living, safety of public spaces, affordability of housing, or your personal job situation? These answers were used for an assessment of the quality of life in the different regions of the Czech Republic. We used multivariate modeling to explicitly account for the hierarchical structure of respondents within the Czech Republic, and for understanding patterns of variation between regions. The principal component analysis (PCA) was used for the general analysis of regional differences. The overall goal of principal component analysis is to reduce the dimensionality of a data set, while simultaneously retaining the information present in the data. The differences were illustrated by cartographic visualization and by scatter plots of the first three principal components. The cluster analysis was used to discover similarities and differences of the quality of life within various regions of the Czech Republic.


2019 ◽  
Vol 13 ◽  
pp. 117822341983554 ◽  
Author(s):  
Laura Curr Beamer ◽  
Marcia Grant

Purpose: The purpose of this study is to report the initial validation process for using the Dermatology Life Quality Index (DLQI) for radiodermatitis of the breast. Methods: This is an additional analysis of a study designed to report a longitudinal study in skin-related and global quality of life in women with breast radiodermatitis. A total of 40 participants completed the DLQI instrument weekly while receiving external radiotherapy of the female breast. At week 5 on treatment, 31 (78%) participants provided narrative feedback on how each DLQI item affected her life. Agreement between participant DLQI numerical ratings and narrative feedback on items was assessed. Construct validity was estimated using principal component analysis (PCA). Internal consistency of the DLQI was assessed using Cronbach alpha. Results: Percentage of agreement between participant DLQI ratings and narratives ranged from 71% to 98%. Each participant responded “no” to the work and study item leading to zero variance and removal from our analyses. Principal component analysis supported the inclusion of all of the remaining items. The DLQI with nine remaining items demonstrated moderately good internal consistency (α = .69). Conclusions: The results of our examination of the DLQI when used for breast radiodermatitis are promising. Next steps include additional larger studies among more diverse populations.


Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1155
Author(s):  
Mark Farrugia ◽  
Han Yu ◽  
Sung Jun Ma ◽  
Austin J. Iovoli ◽  
Kristopher Attwood ◽  
...  

Background: Health-related quality of life (HRQOL) metrics can be associated with survival in head and neck cancer (HNC); however, the impact of HRQOL recovery and the relevant HRQOL domains regarding outcome are unclear. Methods: Using a single-institution database, we retrospectively reviewed HNC patients treated with definitive or postoperative radiation therapy between 2013 and 2018. The recovery of individual HRQOL domains were determined by the ratio of the post-treatment to baseline scores. Univariate and Multivariate Cox regression were used to analyze survival outcomes. Principal component analysis was used to adjust for multicollinearity of HRQOL domains. Results: In 218 HNC patients who received radiation therapy, median follow-up was 24.8 months (interquartile range (IQR) 14.5–32.0). Principal component analysis evaluating the recovery of HRQOL domains revealed two independent principal components (PC), PC1 and PC2. PC1, which received contributions from the functional domains; physical (PF), role (RF), emotional (EF), cognitive (CF), and global health status (GQOL) was significantly associated with disease-free (HR = 0.77, 95% CI 0.61–0.98, p = 0.034) and overall survival (HR = 0.76, 95% CI 0.65–0.91, p = 0.004) on multivariate analysis and PC2, had no correlation with outcome and was mainly represented by social functioning. Unplanned hospitalization was significantly associated with lower PC1 scores (β = −0.997, Std. Error = 0.244, p < 0.001). Conclusion: Our study provides evidence that post-treatment recovery of HRQOL domains were associated with overall survival (OS) in HNC. PC1 is an attractive clinical tool to assess the recovery across multiple different HRQOL and the relationship with survival. Future prospective studies may identify patients who could benefit from additional rehabilitation based on PC1 score.


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