The Caregivers Quality of Life Cancer-Index (CQOL-C) in Spain: An Exploratory and Confirmatory Factor Analysis for Caregivers of Ambulatory and Hospitalized Patients With Cancer

2019 ◽  
Author(s):  
Pablo Brice Lambert de Diesbach ◽  
Maria Cornide Santos ◽  
Margaret F. Clayton
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Hospitalized Patients ◽  
Patients With Cancer ◽  
Confirmatory Factor

scholarly journals Evaluating the measurement properties of the 26-item Expanded Prostate Cancer Index Composite (EPIC-26) with a multicenter cohort

2019 ◽  
Vol 14 (4) ◽  
Author(s):  
R. Trafford Crump ◽  
Alex Peterson ◽  
Camille Charbonneau ◽  
Kevin V. Carlson ◽  
Jason M. Sutherland ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Prostate Cancer ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Construct Validity ◽  
Localized Prostate Cancer ◽  
Measurement Properties ◽  
Confirmatory Factor ◽  
Ceiling Effects

Introduction: We aimed to evaluate the psychometric properties of the 26-item Expanded Prostate Cancer Index Composite (EPIC-26) for measuring the quality of life in patients treated for localized prostate cancer. The EPIC-26 is a patient-reported outcome instrument recommended for use with patients treated for localized prostate cancer. Methods: This study is based on data collected prospectively between September 2014 and February 2017 in Alberta, Canada. Men were treated with either radical prostatectomy or radiation therapy and administered the EPIC-26. Responses to the EPIC-26 were the primary outcome. Construct validity was measured using confirmatory factor analysis. Reliability was measured using Chronbach’s alpha and item-total correlation. Ceiling and floor effects were also investigated. Results: EPIC-26 response data from 205 participants (prostatectomy =138; radiation=60; both=7) were used in this analysis. The EPIC-26 was administered an average of 33.8 weeks after treatment. The confirmatory factor analysis model did not meet the threshold for adequate fit. Several items had near-zero factor loadings and were non-significant. Four out of the EPIC- 26’s five domains met the acceptable reliability threshold based on Cronbach’s alpha. Ceiling effects were observed in four out of five domains. Conclusions: The EPIC-26 demonstrated poor construct validity, adequate reliability, and large ceiling effects. Several issues were observed, suggesting that the instrument’s five domains were not well-defined by their respective items. The original EPIC’s conceptual framework should be reviewed and the shortened instrument revised to improve its performance for measuring post-treatment quality of life.

Components of quality of life in a sample of patients with lupus: a confirmatory factor analysis and Rasch modeling of the LupusQoL

2017 ◽  
Vol 36 (8) ◽  
pp. 1789-1795 ◽  
Author(s):  
Ana-Belén Meseguer-Henarejos ◽  
Juan-José Gascón-Cánovas ◽  
José-Antonio López-Pina
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Rasch Modeling ◽  
Confirmatory Factor

scholarly journals The Unique Relationship between Quality of Life and Consumer Trust in Market-Related Institutions among Financially Constrained Consumers in a Developing Country

2009 ◽  
Vol 28 (1) ◽  
pp. 56-70 ◽  
Author(s):  
Ahmet Ekici ◽  
Mark Peterson
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Developing Country ◽  
Poverty Line ◽  
Consumer Trust ◽  
Subjective Quality Of Life ◽  
Confirmatory Factor ◽  
Unique Relationship

This study focuses on how relationships among constructs representing (1) consumer trust in market-related institutions (CTMRI), (2) distrust for individuals (DFI), and (3) subjective quality of life (QOL) differ across groups separated by the poverty line in a developing country (Turkey). A comparison of models across the two groups using multisample confirmatory factor analysis indicates that there is a correlation only between CTMRI and QOL for consumers below the poverty line (r = .43); there are no correlations between any of the three constructs for consumers above the poverty line. Accordingly, there is a unique relationship between QOL and CTMRI among financially constrained consumers in a developing country. Below the poverty line, consumers with lower trust in market-related institutions tend to report lower QOL, while those with higher trust in market-related institutions tend to report higher QOL.

scholarly journals Psychometric properties of the WHOQOL-BREF(PT) in a sample of elderly citizens

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Margarida Goes ◽  
Manuel Lopes ◽  
João Marôco ◽  
Henrique Oliveira ◽  
César Fonseca
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Psychometric Properties ◽  
Structural Equation ◽  
First Order ◽  
Confirmatory Factor ◽  
Average Variance ◽  
Correlation Level

Abstract Background The goal of this article was to research the psychometric properties of the WHOQOL-BREF(PT) instrument in a sample of elderly citizens residing in a rural area in their own homes or at family members’ or friends’ homes and to compare the results: (i) to those reported by the team of Portuguese researchers that undertaken the instrument's translation/validation to the Portuguese language and (ii) to those reported internationally by the World Health Organization Quality of Life group. An overall quality of life scoring (QOL24—all facets) is also proposed in this article as novelty. The correlation level between QOL24 and the instrument’s general facet was also investigated. Methods This was a cross-sectional study with a sample of 351 elderly citizens (46.4% males and 53.6% females) randomly selected from the official dataset of the Local Health Unit of Baixo Alentejo. All the data were collected by health professionals at the participants’ homes following the structured interview methodology and using the WHOQOL-BREF(PT) instrument. Three different structural equation models were developed: (i) a first-order confirmatory factor analysis, to assess the instrument’s psychometric properties; (ii) a hierarchical second-order confirmatory factor analysis model, to allow determining the QOL24 scoring; and (iii) a more generic structural equation model, to investigate the correlation level between QOL24 and the instrument’s general facet. Results The WHOQOL-BREF(PT) showed an “almost very good” goodness of fit (comparative fit index of 0.949 and Tucker-Lewis index of 0.943), an adequate internal consistency (Cronbach’s alpha: from 0.64 to 0.90; composite reliability: from 0.59 to 0.88) and tolerable convergent validity (average variance extracted: from 0.374 to 0.614). However, discriminant validity was not reached because strong correlations between the first-order factors (four QOL domains) were obtained, together with low values of the average variance extracted. The scoring of QOL domains and QOL24, determined as weighted averages (proposed in this article as novelty) were significantly different than those determined as unweighted averages. The standardized correlation coefficient between QOL24 and the instrument’s general facet was of 0.89 (statistically highly significant). Conclusions The WHOQOL-BREF(PT) is a psychometrically sound instrument to assess the QOL of the considered population sample. However, the QOL domains were found strongly intertwined. More studies are necessary to validate the weighted average scoring strategy of QOL domains and QOL24. Concurrent validity between QOL24 and the instrument’s general facet was considered as “strong”.

scholarly journals A Revised Version of Diabetes Quality of Life Instrument Maintaining Domains for Satisfaction, Impact, and Worry

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Mohamad Adam Bujang ◽  
Tassha Hilda Adnan ◽  
Nur Khairul Bariyyah Mohd Hatta ◽  
Mastura Ismail ◽  
Chien Joo Lim
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Missing Values ◽  
Health Clinic ◽  
Structure Matrix ◽  
Confirmatory Factor ◽  
Satisfaction Domain ◽  
Diabetes Patients

Background. Diabetes quality of life (DQoL) instrument has been widely used to measure quality of life among diabetes patients. This study aimed to develop a revised version of DQoL instrument that incorporated issues of redundancies in the items and strengthen the basis of validity of the instrument. Methods. This was a cross-sectional study where diabetes patients were recruited from December 1, 2014, until end of March 2015 at a public health clinic in Peninsular Malaysia. A questionnaire that included patients’ information and DQoL instrument was distributed to patients. Item selection of DQoL instrument was conducted to screen and finalize the items based on issues of missing values and redundancy. Validity testing was conducted for the revised DQoL instrument based on exploratory factor analysis, confirmatory factor analysis, and Rasch analysis. Results. The pattern structure matrix yielded three domains similar to the original version with 18 items. The minimum factor loading from the structure matrix was 0.358. The item’s and person’s reliability was excellent with 0.92 and 0.84 for “satisfaction” domain, 0.98 and 0.60 for “impact” domain, and 0.99 and 0.57 for “worry” domain, respectively. Confirmatory factor analysis has dropped 5 items and the revised version of DQoL contained 13 items. Composite reliability of the revised version was computed for “satisfaction” domain (0.922; 95% CI: 0.909–0.936), “impact” domain (0.781; 95% CI: 0.745–0.818), and “worry” domain (0.794; 95% CI: 0.755–0.832). Conclusion. A revised version of DQoL that maintains the conceptualization of “satisfaction,” “impact,” and “worry” with 13 items was successfully developed.

Validation of the WHOQOL-BREF quality of life questionnaire for general use in New Zealand: confirmatory factor analysis and Rasch analysis

2012 ◽  
Vol 22 (6) ◽  
pp. 1451-1457 ◽  
Author(s):  
Christian U. Krägeloh ◽  
Paula Kersten ◽  
D. Rex Billington ◽  
Patricia Hsien-Chuan Hsu ◽  
Daniel Shepherd ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
New Zealand ◽  
Confirmatory Factor Analysis ◽  
Rasch Analysis ◽  
Life Questionnaire ◽  
Quality Of Life Questionnaire ◽  
Confirmatory Factor

Measuring the quality of life of people at the end of life: The McGill Quality of Life Questionnaire–Revised

2016 ◽  
Vol 31 (2) ◽  
pp. 120-129 ◽  
Author(s):  
S Robin Cohen ◽  
Richard Sawatzky ◽  
Lara B Russell ◽  
Javad Shahidi ◽  
Daren K Heyland ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Life Questionnaire ◽  
Quality Of Life Questionnaire ◽  
Global Quality ◽  
Global Quality Of Life ◽  
Confirmatory Factor ◽  
Life Threatening

Background: The McGill Quality of Life Questionnaire has been widely used with people with life-threatening illnesses without modification since its publication in 1996. With use, areas for improvement have emerged; therefore, various minor modifications were tested over time. Aim: To revise the McGill Quality of Life Questionnaire (McGill Quality of Life Questionnaire–Revised) while maintaining or improving its psychometric properties and length, keeping it as close as possible to the McGill Quality of Life Questionnaire to enable reasonable comparison with existing McGill Quality of Life Questionnaire literature. Design: Data sets from eight studies were used (four studies originally used to develop the McGill Quality of Life Questionnaire, two to develop new McGill Quality of Life Questionnaire versions, and two with unrelated purposes). The McGill Quality of Life Questionnaire–Revised was developed using analyses of measurement invariance, confirmatory factor analysis, and calculation of correlations with the McGill Quality of Life Questionnaire’s global quality of life item. Setting/Participants: Data were from 1702 people with life-threatening illnesses recruited from acute and palliative care units, palliative home care services, and oncology and HIV/AIDS outpatient clinics. Results: The McGill Quality of Life Questionnaire–Revised consists of 14 items (plus the global quality of life item). A new Physical subscale was created combining physical symptoms and physical well-being and a new item on physical functioning. The Existential subscale was reduced to four items. The revised Support subscale, renamed Social, focuses more on relationships. The Psychological subscale remains unchanged. Confirmatory factor analysis results provide support for the measurement structure of the McGill Quality of Life Questionnaire–Revised. The overall scale has good internal consistency reliability ( α = 0.94). Conclusion: The McGill Quality of Life Questionnaire–Revised improves on and can replace the McGill Quality of Life Questionnaire since it contains improved wording, a somewhat expanded repertoire of concepts with fewer items, and a single subscale for the physical domain, while retaining good psychometric properties.

Sign in / Sign up

Export Citation Format

Share Document