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Preference weights are widely used to score generic health states into utility indexes for estimation of quality adjusted life years (QALYs) and to aid health care funding decisions. To date, health state utilities are predominantly derived using stated preference methods based on decision utility. This paper tests an alternative and generates preference weights using experienced utility for children based on the Child Health Utility 9D (CHU9D) descriptive system. We estimate the relative values of the CHU9D health states with regard to experienced utility, where experienced utility is approximated by self-reported happiness. A nationally-representative longitudinal survey was used including 6090 Australian children aged 12–17 years surveyed over 2014–2018. The derived weights were then applied to calculate the utility decrements for a few common child health conditions. We found that the estimated utility decrements are largely similar to those estimated using the published CHU9D Australian adolescent weights based on decision utility, except for pain and depression. A smaller utility decrement for pain and a larger utility decrement for depression were indicated by experienced utility. We contribute to the literature by showing that using experienced utility methods to generate preference weights for health states is possible, and we discuss some important methodological challenges for future studies such as the impracticability of anchoring to 'dead' when utilizing experienced utility. • Established methods of valuing health states rely on decision utility. • We use experienced utility to generate preference weights for children. • The estimated decrements for health conditions are similar to published weights. • We see smaller impact for pain, larger for depression compared to published weights. • Feasibility is demonstrated using child experienced utility for preference weights. [ABSTRACT FROM AUTHOR]

Abstract This paper describes who is most likely to experience household employment insecurity and housing affordability stress – double precarity – and estimates the degree to which housing affordability mediates the effect of employment insecurity on mental health. We use a cohort of 24,201 participants in 2016 Household, Income and Labour Dynamics in Australia survey (6.2 repeated measures on average). We estimate the likelihood of onset of household employment insecurity, housing affordability stress and change in housing costs using longitudinal regression analyses for socio-demographic groups. We assess mediation by estimating how much exposure variable coefficients attenuate with inclusion of a mediator in fixed effects regression models. We also apply causal mediation methods to fixed-effects regression models to better account for exposure-mediator interaction and meet strict model assumptions. If people's households become insecurely employed, there are five times greater odds of them also experiencing housing affordability stress (OR 4.99 95%CI 4.21–5.90). Key cohorts within the population are shown to be especially vulnerable to double precarity – notably single parents (OR 2.91, 95%CI 1.94–4.35) and people who live alone (OR 4.42, 95% CI 3.03–6.45) (compared to couples), and people who are recently separated or divorced (OR 2.59, 95%CI 1.81–3.70). Mediation analysis confirms that household employment insecurity has a small, negative effect on mental health (Beta −0.24, 95%CI -0.38-0.11 on a 1 to 100-point scale with 10-point standard deviation). Estimates from casual mediation analyses suggest housing affordability accounts for 20% of the total effect; likely concentrated in the lowest and highest strata of income. Employment and housing insecurity represent a form of double precarity for people in households with a single income. When we consider the impact on mental health, we find evidence of a causal relationship between insecure employment onset and mental health, around one fifth of which is mediated by changing housing cost and onset of affordability stress. Highlights • Insecurely employed households are five times as likely to have unaffordable housing. • Lone person and lone parent households are more susceptible to double precarity. • Housing costs mediate the impact of insecure employment on mental health. [ABSTRACT FROM AUTHOR]

This paper examines key processes from the social identity model of traumatic identity change in the context of the aftermath of a natural disaster. It focuses on the roles of (i) group membership gain, (ii) group membership continuity, (iii) social identity revitalisation, and (iv) the severity of natural disaster exposure on post-traumatic growth (PTG) and post-traumatic stress (PTS). (N = 410, M age = 53.24 years) comprised adult survivors of the Australian 2019-20 Black Summer bushfires, recruited to complete an online survey via geo-targeted Facebook advertisements. showed that group membership gain was positively correlated with PTG, whilst group membership continuity negatively correlated with PTS, highlighting the different roles played by group gain and continuity in post-trauma recovery. Preliminary evidence for the validity of a new author-developed social identity revitalisation measure was found, which mediated some relationships between group gain and continuity and PTG and PTS. Lastly, the extent that participants were affected by the fires moderated the relationship between group gain and PTS. Specifically, for those most affected, group gain was correlated with lower reported PTS, whilst for those less affected, group gain was correlated with higher reported PTS. We discuss implications for theory and draw attention to the concept of revitalisation, which shows promise as a potentially critical contributor to post-trauma recovery. • Group membership gain and continuity play different roles in post-trauma recovery. • Social identity revitalisation is a critical ingredient that promotes growth. • Disaster damage moderates the relationship between group gain and PTS. [ABSTRACT FROM AUTHOR]

In contrast to the recent proliferation of studies incorporating ordinal methods to generate health state values from adults, to date relatively few studies have utilised ordinal methods to generate health state values from adolescents. This paper reports upon a study to apply profile case best worst scaling methods to derive a new adolescent specific scoring algorithm for the Child Health Utility 9D (CHU9D), a generic preference based instrument that has been specifically designed for the estimation of quality adjusted life years for the economic evaluation of health care treatment and preventive programs targeted at young people. A survey was developed for administration in an on-line format in which consenting community based Australian adolescents aged 11–17 years (N = 1982) indicated the best and worst features of a series of 10 health states derived from the CHU9D descriptive system. The data were analyzed using latent class conditional logit models to estimate values (part worth utilities) for each level of the nine attributes relating to the CHU9D. A marginal utility matrix was then estimated to generate an adolescent-specific scoring algorithm on the full health = 1 and dead = 0 scale required for the calculation of QALYs. It was evident that different decision processes were being used in the best and worst choices. Whilst respondents appeared readily able to choose ‘best’ attribute levels for the CHU9D health states, a large amount of random variability and indeed different decision rules were evident for the choice of ‘worst’ attribute levels, to the extent that the best and worst data should not be pooled from the statistical perspective. The optimal adolescent-specific scoring algorithm was therefore derived using data obtained from the best choices only. The study provides important insights into the use of profile case best worst scaling methods to generate health state values with adolescent populations. [ABSTRACT FROM AUTHOR]

Chronic pain is associated with significant costs to individuals directly affected by this condition, their families, the healthcare system, and the society as a whole. This paper investigates the relationship between chronic pain and life satisfaction using a sample of around 90,000 observations from the first ten waves of the Household, Income and Labour Dynamics of Australia Survey (HILDA), which is a representative survey of the Australian population that started in 2000. We estimate the negative impact on life satisfaction and examine the persistence of the effect over multiple years. Chronic pain is associated with poor health conditions, disability, decreased participation in the labour market and lower quality of life. We calculate the compensating income variation of chronic pain, based on the measurement of chronic pain, the life satisfaction of individuals and the income of households. Panel data models with random and fixed effects are used to control for characteristics of individuals that do not vary over time. Further, we investigate whether individuals who experience chronic pain exhibit adaptation and recovery in life satisfaction after 3 years. Overall, we find that chronic pain has a large negative association with life satisfaction, and that the compensating income variation is substantial (around 640 US$ per day). [ABSTRACT FROM AUTHOR]

Self-assessed general health (SAH) is one of the most frequently employed health measures in social science research. Its generic nature means it captures elements of health that more guided measures cannot, and its brevity makes it possible for health information to be included in crowded multifaceted surveys. However, a shortcoming of SAH is that it provides little guidance to researchers as to what individuals are thinking of when they assess their health – when a survey respondent reports that their health is “poor”, is it because they are in pain, tired, depressed, unable to climb stairs, or something else entirely? This limits the possible inference from empirical research. It also means that important determinants and consequences of health can be missed if they are only weakly reflected in SAH. Given the continued use of SAH, it is important to better understand its structure. In this paper we use household panel data from Australia to answer two related questions: (i) what components of health does SAH most strongly represent? and (ii) does the use of SAH conceal important health effects? To answer the first question, we use a detailed health instrument and take a rigorous econometric approach to identify the health dimensions most strongly reflected in SAH. To answer the second question, we estimate the causal effects of income on SAH and on disaggregated health measures using instrumental-variables models. We find that some health dimensions – especially vitality – are consistently important to an individual when they assess their health, while other dimensions are inconsequential. We demonstrate that this fact provides insight in to why some studies find weak income gradients in SAH. Instrumental-variable regression results show that shocks to household income have no effect on SAH, but strongly improve several dimensions of health that are less commonly measured. [ABSTRACT FROM AUTHOR]