Predictors of quality of life in old age: A cross‐validation study

Low, Gail; Molzahn, Anita

doi:10.1002/nur.20178

Cited by 130 publications

(93 citation statements)

References 49 publications

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“…Again, this makes conceptual sense, as a smaller percentage of the LBC1936 lived alone and so this factor may have more impact in early old age. This is in keeping with previous studies which have suggested a crucial role for social relationships and support in predicting QoL [21].…”

Section: Discussionsupporting

confidence: 93%

“…This therefore restricts the applicability of our models to the general population. However, other studies of the determinants of quality of life have also suggested that models may be population-specific [21]. Another potential limitation is the timing of our measures: the measurement of QoL and personality were not exactly concurrent with each other or the measurement of old age cognition and physical health in the LBC1921, although this was rectified in the LBC1936.…”

Section: Discussionmentioning

confidence: 96%

“…Other studies have argued for a significant role of depressive state in predicting QoL in older adults, over and above life circumstances such as acquired poverty, poor health, loss of independence, and cognitive abilities [6,20]. Others suggest that a key role is played by social relationships [21] and perceived social support [2]. Some have suggested that the processes behind QoL judgements alter with age, arguing that physical impairments are gauged as being less serious when compared with peers, and that the effects of current circumstances on QoL grow weaker with age, especially in women [7].…”

Section: Introductionmentioning

confidence: 99%

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Psychosocial factors and health as determinants of quality of life in community-dwelling older adults

et al. 2011

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Abstract:Purpose It is important to understand the determinants of differences in quality of life in old age, and to include a wide range of possible predictors. The present study investigated the determinants of quality of life in two groups of older adults for whom there was an unusually informative set of possible predictor variables. Results Linear regression analyses revealed that HADS depression had the greatest influence on quality of life. Personality traits, most notably Emotional Stability, also predicted quality of life to varying degrees, along with factors reflecting current life circumstances. There were differences between the two cohorts in the variables which predicted quality of life. There were different, conceptually relevant, contributions to the different QoL facets. MethodConclusions Personality traits and minor depressive symptoms have an important influence on selfreported quality of life in old age. Quality of life may be influenced more by current than past circumstances, and this relationship may change with age.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Psychosocial factors and health as determinants of quality of life in community-dwelling older adults

et al. 2011

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“…Replication studies are rarely undertaken to further validate models of QoL, yet they enable researchers to disentangle sample-dependent findings (Low and Molzahn 2007). In this study, there were cultural differences noted in the patterns found in the BREF measurement model.…”

Section: Discussionmentioning

confidence: 83%

The suitability of the WHOQOL–BREF for Canadian and Norwegian older adults

2008

Self Cite

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The aim of this study was to examine the validity and reliability of the WHOQOL-BREF, a generic quality of life scale, among older people in Canada and Norway. Very similar data from the Canadian and Norwegian Field Trial data (Canada n = 192; Norway, n = 469) were analyzed and compared. Higher negatively skewed mean scores were found for all WHOQOL-BREF domains in Canada. For both study samples, missing values were highest for the sex item from the social domain. Ceiling effects were found (Canada n = 21; Norway n = 11) primarily among items in the physical and environmental domains. In both study samples, a multitrait multimethod procedure indicated items correlated most strongly with their parent domains; however, equally appreciable correlations were observed between physical, psychological, and environmental items (r = 0.33-0.64; p \ 0.01). The social domain had the lowest internal consistency (a = 0.67 Canada, a = 0.55 Norway). Confirmatory factor analyses (CFA) yielded marginal goodness-of-fit between the hypothesized WHOQOL-BREF measurement model and the sample data as well as differing patterns of domain misspecification. Patterns of correlations (p \ 0.01) of WHOQOL-BREF domains with WHOQOL-OLD facets, a global QOL item, the SF-12, and the geriatric depression scale provided evidence of convergent and divergent validity. Domain scores also significantly discriminated between health and unhealthy populations and presence of morbidity. Empirical support was found, in part, for the construct validity of the WHOQOL-BREF in older adults. Despite some different patterns found in the CFA, possibly due to cultural or sampling differences, it appears that the instrument is reliable, valid, and facilitates cross-cultural comparisons.

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“…Differences in QoL among Canadians and Americans are explained by age, gender, education, income, marital status and country of residence [28]. Low G. et al [29] examined whether risk factors were associated directly and positively with QoL.…”

mentioning

confidence: 99%

Quality of life in Lithuanian population: the impact of country residence and socio-economic status

Rėklaitienė¹,

Bacevičienė²,

Andrijauskas

2009

Open Medicine

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AbstractQuality of life (QoL) and individual perception of health has become a subject of great interest in Lithuania. The relationships between country residence, socio-economic status (SES), and QoL have not been well characterized among the Lithuanian urban and rural populations. The aim of the study was to assess the influence of country residence and SES on QoL in Lithuanian urban and rural population adjusting for the influence of other known determinants of QoL. The study population was randomly selected from 1193 urban and 264 rural men and women aged 45–72 years and have been filled in the self-administered the WHOQOL-100 questionnaire. The survey participation rate was 62.8%. Psychometric evaluation of the WHOQOL-100 showed good internal reliability of Cronbach’s α from 0.78 to 0.94. Multiple linear regression models were used to study the influence of country residence and SES on the WHOQOL-100 scores while adjusting for the influence of other determinants of QoL. After adjusting for the influence of these factors, country residence and SES independently influenced QoL. Rural residence negatively affected the overall QoL, psychological domain, level of independence and spirituality. Higher education level and income directly and positively influenced the WHOQOL-100 scores, while retired, unemployed and residents with chronic medical conditions had negative influence WHOQOL-100 scores. The study results conclude that country residence and SES are associated with differences in QoL among urban and rural Lithuanian population.

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Predictors of quality of life in old age: A cross‐validation study

Cited by 130 publications

References 49 publications

Psychosocial factors and health as determinants of quality of life in community-dwelling older adults

Psychosocial factors and health as determinants of quality of life in community-dwelling older adults

The suitability of the WHOQOL–BREF for Canadian and Norwegian older adults

Quality of life in Lithuanian population: the impact of country residence and socio-economic status

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