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The 12-item General Health Questionnaire (GHQ-12) is widely used to measure mental health and well-being; however, it is not possible to estimate values on the full health = 1, dead = 0 scale used to construct quality-adjusted life-years (QALYs) from GHQ-12 responses as it is not preference-based.The aim of this study was to create an item-response mapping between GHQ-12 and EQ-5D-3L health states, for which several value sets exist.Data from the 2012 Health Survey for England with complete GHQ-12 and EQ-5D-3L descriptive system responses were used for analysis. Data were split 70/30 into estimation/test samples. Four modelling approaches, with EQ-5D-3L levels on each dimension as dependent variables and GHQ-12 responses as independent variables were assessed: non-parametric, simple ordered logit (OL), extended OL, and least absolute shrinkage and selection operator (LASSO). Approaches were assessed using Akaike and Bayesian information criteria, predictive accuracy measured using root mean squared error (RMSE), and simplicity.A total of 8114 responses became 6924 after discarding missing values, with 4847 used in estimation and 2077 used for testing. LASSO had a better model fit on the pain/discomfort dimension, but no model had markedly superior predictive accuracy. The non-parametric approach was chosen for the mapping algorithm based on simplicity. Predicted and observed EQ-5D-3L values for the test sample had a correlation of 0.488. Prediction accuracy was better for GHQ-12 scores below 20 than scores above 20.The mapping allows EQ-5D-3L responses to be predicted using GHQ-12 responses, which may be useful in estimating utility values and QALYs. An R script and Microsoft Excel spreadsheet are provided to facilitate calculations.

Background We investigate whether and how general population health state values were influenced by the initial stages of the COVID-19 pandemic. Changes could have important implications, as general population values are used in health resource allocation. Data In Spring 2020, participants in a UK general population survey rated 2 EQ-5D-5L states, 11111 and 55555, as well as dead, using a visual analogue scale (VAS) from 100 = best imaginable health to 0 = worst imaginable health. Participants answered questions about their pandemic experiences, including COVID-19’s effect on their health and quality of life, and their subjective risk/worry about infection. Analysis VAS ratings for 55555 were transformed to the full health = 1, dead = 0 scale. Tobit models were used to analyse VAS responses, as well as multinomial propensity score matching (MNPS) to create samples balanced according to participant characteristics. Results Of 3021 respondents, 2599 were used for analysis. There were statistically significant, but complex associations between experiences of COVID-19 and VAS ratings. For example, in the MNPS analysis, greater subjective risk of infection implied higher VAS ratings for dead, yet worry about infection implied lower ratings. In the Tobit analysis, people whose health was affected by COVID-19 rated 55555 higher, whether the effect on health was positive or negative. Conclusion The results complement previous findings that the onset of the COVID-19 pandemic may have impacted EQ-5D-5L health state valuation, and different aspects of the pandemic had different effects.

Little is known about what features of AAC systems are regarded by AAC professionals as more suitable for children with different characteristics. A survey was conducted in which participants rated the suitability of hypothetical AAC systems on a Likert scale from 1 (very unsuitable) to 7 (very suitable) alongside a discrete choice experiment. The survey was administered online to 155 AAC professionals in the United Kingdom of Great Britain and Northern Ireland. Statistical modeling was used to estimate how suitable 274 hypothetical AAC systems were for each of 36 child vignettes. The proportion of AAC systems rated at least 5 out of 7 for suitability varied from 51.1% to 98.5% for different child vignettes. Only 12 out of 36 child vignettes had any AAC systems rated at least 6 out of 7 for suitability. The features of the most suitable AAC system depended on the characteristics of the child vignette. The results show that, while every child vignette had several systems that had a good suitability rating, there were variations, that could potentially lead to inequalities in provision.

Relapsing-remitting multiple sclerosis (RRMS) is an incurable disease characterised by relapses (periods of function loss) followed by full or partial recovery, and potential permanent disability over time. Many disease-modifying treatments (DMTs) exist that help reduce relapses and slow disease progression. Most are contraindicated during conception/pregnancy and some require a discontinuation period before trying to conceive. Although around three-quarters of people with RRMS are women, there is limited knowledge about how reproductive issues impact DMT preference.The aim of this study was to measure the preferences for DMTs of women with RRMS who are considering pregnancy.An online discrete choice experiment (DCE).Participants chose between two hypothetical DMTs characterised by a set of attributes, then indicated if they preferred their choice to no treatment. Attributes were identified from interviews and focus groups with people with RRMS and MS professionals, as well as literature reviews, and included the probability of problems with pregnancy, discontinuation of DMTs, and breastfeeding safety. In each DCE task, participants were asked to imagine making decisions in three scenarios: now; when trying to conceive; and when pregnant.Two mixed logit models were estimated, one to assess the statistical significance between scenarios and one in maximum acceptable risk space to allow comparison of the magnitudes of parameters between scenarios.Women with RRMS who were considering having a child in the future, recruited from a UK MS patient register.Sixty respondents completed the survey. Participants preferred no treatment in 12.6% of choices in the 'now' scenario, rising significantly to 37.6% in the 'trying to conceive' scenario and 60.3% in the 'pregnant' scenario (Kruskal-Wallis p 0.001). This pattern corresponds with results from models that included a no-treatment alternative-specific constant (ASC) capturing differences between taking and not taking a DMT not specified by the attributes. The ASC was lower in the trying to conceive scenario than in the now scenario, and lower still in the pregnant scenario, indicating an intrinsic preference for no treatment. Participants also placed relatively less preference on reducing relapses and avoiding disease progression in the trying to conceive and pregnant scenarios compared with a lower risk of problems with pregnancy. In the trying to conceive scenario, participants' preference for treatments with shorter washout periods increased.Women with RRMS considering having a child prefer DMTs with more favourable reproduction-related attributes, even when not trying to conceive. Reproductive issues also influenced preferences for DMT attributes not directly related to pregnancy, with preferences dependent on the life circumstances in which choices were made. The design of the DCE highlights the benefits of considering the scenario in which participants make choices, as they may change over time.