Response shift in self-rated health after serious health events in old age

Spuling, Svenja M.; Wolff, Julia K.; Wurm, Susanne

doi:10.1016/j.socscimed.2017.09.026

Cited by 28 publications

(27 citation statements)

References 37 publications

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“…We found that the majority of participants expressed stable importance ratings of a preference, whereas the majority had unstable most-important preferences; this may represent different thresholds for change. Response shift theory would deem changes in the importance rating of a preference, and changes in the most important preference to both be types of reprioritization or goal-reordering, which may occur following acute illness events [ 41 ]. The importance rating of a preference may overlap with underlying values, and be linked to social support, (antecedents in response shift) which are stabilising influences.…”

Section: Discussionmentioning

confidence: 99%

The stability of care preferences following acute illness: a mixed methods prospective cohort study of frail older people

et al. 2020

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Background Patient preferences are integral to person-centred care, but preference stability is poorly understood in older people, who may experience fluctuant illness trajectories with episodes of acute illness. We aimed to describe, and explore influences on the stability of care preferences in frail older people following recent acute illness. Methods Mixed-methods prospective cohort study with dominant qualitative component, parallel data collection and six-month follow up. Study population: age ≥ 65, Rockwood Clinical Frailty score ≥ 5, recent acute illness requiring acute assessment/hospitalisation. Participants rated the importance of six preferences (to extend life, improve quality of life, remain independent, be comfortable, support ‘those close to me’, and stay out of hospital) at baseline, 12 and 24 weeks using a 0–4 scale, and ranked the most important. A maximum-variation sub-sample additionally contributed serial in-depth qualitative interviews. We described preference stability using frequencies and proportions, and undertook thematic analysis to explore influences on preference stability. Results 90/192 (45%) of potential participants consented. 82/90 (91%) answered the baseline questionnaire; median age 84, 63% female. Seventeen undertook qualitative interviews. Most participants consistently rated five of the six preferences as important (range 68–89%). ‘Extend life’ was rated important by fewer participants (32–43%). Importance ratings were stable in 61–86% of cases. The preference ranked most important was unstable in 82% of participants. Preference stability was supported by five influences: the presence of family support; both positive or negative care experiences; preferences being concordant with underlying values; where there was slowness of recovery from illness; and when preferences linked to long term goals. Preference change was related to changes in health awareness, or life events; if preferences were specific to a particular context, or multiple concurrent preferences existed, these were also more liable to change. Conclusions Preferences were largely stable following acute illness. Stability was reinforced by care experiences and the presence of family support. Where preferences were unstable, this usually related to changing health awareness. Consideration of these influences during preference elicitation or advance care planning will support delivery of responsive care to meet preferences. Obtaining longer-term data across diverse ethnic groups is needed in future research.

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Section: Discussionmentioning

confidence: 99%

The stability of care preferences following acute illness: a mixed methods prospective cohort study of frail older people

et al. 2020

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“…Participants of this study were older than the populations used in other studies investigating trajectories of SRH. Response shift in SRH is known to occur among older adults 46. Compared with their younger counterparts, older adults are suggested to base their SRH more on psychological and life-style behaviours, and less on functional status and physical health, which might indicate reprioritisation response shift 47 48.…”

Section: Discussionmentioning

confidence: 99%

“…Compared with their younger counterparts, older adults are suggested to base their SRH more on psychological and life-style behaviours, and less on functional status and physical health, which might indicate reprioritisation response shift 47 48. Furthermore, older adults adapt their standards of good health over time, also known as recalibration response shift 46. In addition, cognitive strategies to accept negative outcomes, as well as someone’s beliefs contribute to enhanced levels of well-being, despite negative health outcomes,49 which can explain the stable trajectories of SRH over time in this study sample.…”

Section: Discussionmentioning

confidence: 99%

Trajectories of self-rated health in an older general population and their determinants: the Lifelines Cohort Study

et al. 2020

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ObjectivesPoor self-rated health (SRH) is a strong predictor of premature mortality in older adults. Trajectories of poor SRH are associated with multimorbidity and unhealthy behaviours. Whether trajectories of SRH are associated with deviating physiological markers is unclear. This study identified trajectories of SRH and investigated the associations of trajectory membership with chronic diseases, health risk behaviours and physiological markers in community-dwelling older adults.Study design and settingProspective general population cohort.ParticipantsTrajectories of SRH over 5 years were identified using data of 11 600 participants aged 65 years and older of the Lifelines Cohort Study.Outcome measuresTrajectories of SRH were the main outcome. Covariates included demographics (age, gender, education), chronic diseases, health-risk behaviour (physical activity, smoking, drinking) and physiological markers (body mass index, cardiovascular function, lung function, glucose metabolism, haematological condition, endocrine function, renal function, liver function and cognitive function).ResultsFour stable trajectories were identified, including excellent (n=607, 6%), good (n=2111, 19%), moderate (n=7677, 65%) and poor SRH (n=1205, 10%). Being women (OR: 1.4; 95% CI: 1.0 to 1.9), low education (OR: 2.1; 95% CI: 1.5 to 3.0), one (OR: 10.4; 95% CI: 7.4 to 14.7) or multiple chronic diseases (OR: 37.8; 95% CI: 22.4 to 71.8), smoking (OR: 1.8; 95% CI: 1.0 to 3.2), physical inactivity (OR: 3.1; 95% CI: 1.8 to 5.2), alcohol abstinence (OR: 2.2; 95% CI: 1.4 to 3.2) and deviating physiological markers (OR: 1.5; 95% CI: 1.1 to 2.0) increase the odds for a higher probability of poor SRH trajectory membership compared with excellent SRH trajectory membership.ConclusionSRH of community-dwelling older adults is stable over time with the majority (65%) having moderate SRH. Older adults with higher probabilities of poor SRH often have unfavourable health status.

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“…31 It has been suggested that CMCs and PDs may differently impact SRH of population sub-groups. 27 The perception of SRH may also shift as a result of the developmental stage and age, 24,25 leading to differences in reference groups of various subpopulations, which is well demonstrated in the literature. 32 Similarly, non-health determinants of SRH vary across race and gender groups.…”

Section: Introductionmentioning

confidence: 87%

“…24 A large body of evidence suggests that poor SRH may not reflect the same health status for various populations by age, gender, ethnicity, and health status. 24,25 Such information would introduce a significant challenge toward the application of SRH in diverse populations. 23,26 For example, age and gender, social factors, health behaviors, and chronic medical conditions (CMCs) differently impact the SRH of people across countries.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Predictors of Self-rated Health of Economically Disadvantaged African American Men and Women: Evidence for Sponge Hypothesis

Cobb

Assari

2020

Int J Epidemiol Res

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Background and aims: According to the sponge hypothesis, compared to men’s self-rated health (SRH), women’s SRH is more likely to reflect conditions other than chronic medical conditions (CMCs) such as psychiatric disorders (PDs). As a result, poor SRH is a weaker predictive factor for mortality risk for women than men. Most of this literature, however, is done in samples that are predominantly middleclass White. To test the sponge hypothesis among economically disadvantaged African Americans (AAs), this study compared low-income AA men and women for the effects of the number of PDs and CMCs on SRH. Materials and Methods: This cross-sectional study recruited a non-random sample (n=150) of economically disadvantaged AA adults with PD(s). Structured face-to-face interviews were used to collect data. SRH was measured using a single-item measure. PDs and CMCs were also self-reported. We applied linear regression models to test the interactions between SRH and the number of PDs and CMC as well as gender. Results: The number of PDs and CMCs were associated with SRH in the pooled sample of low-income AA adults with PD(s). However, we found a significant interaction between the number of PDs and gender. This interaction suggested a stronger association between PDs and SRH for AA women than AA men. Gender did not alter the association between the number of CMCs and SRH. Conclusion: The number of PDs is a determinant of SRH for low-income AA women but not AA men, supporting the sponge hypothesis.

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Response shift in self-rated health after serious health events in old age

Cited by 28 publications

References 37 publications

The stability of care preferences following acute illness: a mixed methods prospective cohort study of frail older people

The stability of care preferences following acute illness: a mixed methods prospective cohort study of frail older people

Trajectories of self-rated health in an older general population and their determinants: the Lifelines Cohort Study

Investigation of the Predictors of Self-rated Health of Economically Disadvantaged African American Men and Women: Evidence for Sponge Hypothesis

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