A Theoretical Approach to Measuring Quality of Life

The purpose of this article is to discuss conceptual issues surrounding health-related quality of life (HRQOL) and to provide an example of how structural equation modeling can address some of these conceptual issues. This article reports the development of the measurement model for overall quality of life, a dimension of HRQOL as conceptualized by Wilson and Cleary (1995). The sample (N = 1410) is from the AIDS Time-Oriented Health Outcome Study (ATHOS) databank, a longitudinal observational database of persons with HIV-associated illness. The hypothesized second-order factor model consists of 5 latent variables and 17 measured items. The fit indicators (RMSEA = .0717; SRMR = .0450; CFI = .951) suggest that the model provides an adequate description of the pattern of relationships in the data. A theoretical approach to HRQOL will expand its clinical use as an outcome measure and increase its relevance.

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Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients

PLoS ONE ◽

10.1371/journal.pone.0252205 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0252205

Author(s):

Mahalingam Vasantha ◽

Malaisamy Muniyandi ◽

Chinnaiyan Ponnuraja ◽

Ramalingam Srinivasan ◽

Perumal Venkatesan

Keyword(s):

Quality Of Life ◽

Latent Variables ◽

Structural Equation ◽

Well Being ◽

Monte Carlo Algorithm ◽

Equation Modeling ◽

Health Related Quality ◽

Related Quality ◽

Health Related

Background The use of Bayesian Structural Equation Model (BSEM) to evaluate the impact of TB on self-reported health related quality of life (HRQoL) of TB patients has been not studied. Objective To identify the factors that contribute to the HRQoL of TB patients using BSEM. Methods This is a latent variable modeling with Bayesian approach using secondary data. HRQoL data collected after one year from newly diagnosed 436 TB patients who were registered and successfully completed treatment at Government health facilities in Tiruvallur district, south India under the National TB Elimination Programme (NTEP) were used for this analysis. In this study, the four independent latent variables such as physical well–being (PW = PW1-7), mental well-being (MW = MW1-7), social well-being (SW = SW1-4) and habits were considered. The BSEM was constructed using Markov Chain Monte Carlo algorithm for identifying the factors that contribute to the HRQoL of TB patients who completed treatment. Results Bayesian estimates were obtained using 46,300 observations after convergence and the standardized structural regression estimate of PW, MW, SW on HRQoL were 0.377 (p<0.001), 0.543 (p<0.001) and 0.208 (p<0.001) respectively. The latent variables PW, MW and SW were significantly associated with HRQoL of TB patients. The age was found to be significantly negatively associated with HRQoL of TB patients. Conclusions The current study demonstrated the application of BSEM in evaluating HRQoL. This methodology may be used to study precise estimates of HRQoL of TB patients in different time points.

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Response shift in health-related quality of life measures in the presence of formative indicators

Health and Quality of Life Outcomes ◽

10.1186/s12955-020-01663-y ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Silvia Testa ◽

Daniela Di Cuonzo ◽

Giuliana Ritorto ◽

Laura Fanchini ◽

Sara Bustreo ◽

...

Keyword(s):

Quality Of Life ◽

Latent Variable ◽

Structural Equation ◽

Response Shift ◽

Measurement Model ◽

Equation Modeling ◽

Related Quality ◽

Health Related ◽

Formative Indicators

Abstract Background Response shift (RS) has been defined as a change in the meaning of an individual’s self-evaluation that needs to be accounted for when assessing longitudinal changes in health-related quality of life (HRQoL). RS detection through structural equation modeling is accomplished by adopting Oort’s procedure based on a measurement model in which the observed variables are defined as reflective indicators of the HRQoL latent variable; that is, the latent variable causes the variation in the reflective indicators. This study aims to propose a procedure that assesses RS when formative indicators are used in measuring HRQoL; in this last case, the latent variable is considered to be a function of some formative indicators. A secondary aim is to compare the new procedure with Oort’s procedure to highlight similarities and differences. Methods The data were retrieved from a consecutive series of 258 patients newly diagnosed with colorectal cancer and undergoing chemotherapy and/or surgery. The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QOL-C30) was administered twice, once before and once six months after treatment. Structural equation modeling was used to evaluate RS and true change with the newly proposed method (in which fatigue and pain were defined as formative indicators) and with Oort’s procedure (in which fatigue and pain were defined as reflective indicators). Results According to the new procedure, there was no measurement bias, and on average, patients’ quality of life improved by 3.53 points (on a scale ranging from 0 to 100) at the 6-month follow-up. With Oort’s procedure, the loading of the pain indicator was not invariant across the two time points, suggesting the presence of reprioritization, whereas the estimation of true change was very similar to the previous one: 3.87. Conclusions RS and true change in HRQoL can be evaluated in the presence of formative indicators. Defining a measurement model by formative or reflective indicators can lead to different results.

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Diabetes in women and health-related quality of life in the whole family: a structural equation modeling

Health and Quality of Life Outcomes ◽

10.1186/s12955-019-1252-4 ◽

2019 ◽

Vol 17 (1) ◽

Cited By ~ 1

Author(s):

Mina Moeineslam ◽

Parisa Amiri ◽

Mehrdad Karimi ◽

Sara Jalali-Farahani ◽

Niloofar Shiva ◽

...

Keyword(s):

Quality Of Life ◽

Structural Equation ◽

Diabetes Type 2 ◽

Equation Modeling ◽

Health Related Quality ◽

Related Quality ◽

Health Related ◽

Mental Hrqol

Abstract Background Although several studies indicate the effects of diabetes type 2 on health-related quality of life (HRQoL) in female subjects, the related impact of the disease on HRQoL in their family members has rarely been the focus of the empirical research. In this study we aim to investigate associations between diabetes in women and the HRQoL in these women and their family members, using the structural equation modeling (SEM). Methods This family-based study was conducted on 794 women (11.1% with diabetes) as well as their spouses and children who participated in the Tehran Lipid and Glucose Study (TLGS) from 2014 to 2016. Data on HRQoL were collected using the Iranian version of the Short-Form 12-Item Health Survey version 2 (SF-12v2) and the Pediatric Quality of Life Inventory version™ 4.0 (PedsQL). SEM was conducted to evaluate the network of associations among studied variables. Data were analyzed using IBM SPSS Statistics & AMOS version 23 software. Results Mean age of women was 41.37 ± 5.32 years. Diabetes in women significantly affected their mental HRQoL (β = − 0.11, P < 0.01) but showed no significant direct associations with physical and mental HRQoL in their spouses or their children. However, poor mental HRQoL in women with diabetes was associated with decrease in both physical (β = − 0.02, P = 0.013) and mental (β = − 0.03, P < 0.01) HRQoL in their spouses and total HRQoL score in children (β = − 0.02, P < 0.01). Conclusions Among women with diabetes type 2, beyond its effect on their mental HRQoL per se, demonstrated a negative association with the self-assessment of health status in their spouses and children. Such familial consequences are mainly attributed to the negative effect of the disease on the mental rather than the physical HRQoL in women with diabetes.

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