1,849 research outputs found
Predicting missing quality of life data that were later recovered : an empirical comparison of approaches
Peer reviewedPostprin
Investigating the missing data mechanism in quality of life outcomes: a comparison of approaches
Background: Missing data is classified as missing completely at random (MCAR), missing at
random (MAR) or missing not at random (MNAR). Knowing the mechanism is useful in identifying
the most appropriate analysis. The first aim was to compare different methods for identifying this
missing data mechanism to determine if they gave consistent conclusions. Secondly, to investigate
whether the reminder-response data can be utilised to help identify the missing data mechanism.
Methods: Five clinical trial datasets that employed a reminder system at follow-up were used.
Some quality of life questionnaires were initially missing, but later recovered through reminders.
Four methods of determining the missing data mechanism were applied. Two response data
scenarios were considered. Firstly, immediate data only; secondly, all observed responses
(including reminder-response).
Results: In three of five trials the hypothesis tests found evidence against the MCAR assumption.
Logistic regression suggested MAR, but was able to use the reminder-collected data to highlight
potential MNAR data in two trials.
Conclusion: The four methods were consistent in determining the missingness mechanism. One
hypothesis test was preferred as it is applicable with intermittent missingness. Some inconsistencies between the two data scenarios were found. Ignoring the reminder data could potentially give a distorted view of the missingness mechanism. Utilising reminder data allowed the possibility of MNAR to be considered.The Chief Scientist Office of the Scottish Government Health Directorate.
Research Training Fellowship (CZF/1/31
Penetrating facial injury from angle grinder use: management and prevention
Injuries resulting from the use of angle grinders are numerous. The most common sites injured are the head and face. The high speed disc of angle grinders does not respect anatomical boundaries or structures and thus the injuries produced can be disfiguring, permanently disabling or even fatal. However, aesthetically pleasing results can be achieved with thorough debridement, resection of wound edges and careful layered functional closure after reduction and fixation of facial bone injuries. A series of penetrating facial wounds associated with angle grinder use are presented and the management and prevention of these injuries discussed
The episodic random utility model unifies time trade-off and discrete choice approaches in health state valuation
ABSTRACT:
BACKGROUND: To present an episodic random utility model that unifies time trade-off and discrete choice approaches in health state valuation.
METHODS: First, we introduce two alternative random utility models (RUMs) for health preferences: the episodic RUM and the more common instant RUM. For the interpretation of time trade-off (TTO) responses, we show that the episodic model implies a coefficient estimator, and the instant model implies a mean slope estimator. Secondly, we demonstrate these estimators and the differences between the estimates for 42 health states using TTO responses from the seminal Measurement and Valuation in Health (MVH) study conducted in the United Kingdom. Mean slopes are estimates with and without Dolan's transformation of worse-than-death (WTD) responses. Finally, we demonstrate an exploded probit estimator, an extension of the coefficient estimator for discrete choice data that accommodates both TTO and rank responses.
RESULTS: By construction, mean slopes are less than or equal to coefficients, because slopes are fractions and, therefore, magnify downward errors in WTD responses. The Dolan transformation of WTD responses causes mean slopes to increase in similarity to coefficient estimates, yet they are not equivalent (i.e., absolute mean difference = 0.179). Unlike mean slopes, coefficient estimates demonstrate strong concordance with rank-based predictions (Lin's rho = 0.91). Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results.
CONCLUSION: The episodic RUM expands upon the theo
Bridging the reality gap in quantum devices with physics-aware machine learning
The discrepancies between reality and simulation impede the optimization and scalability of solid-state quantum devices. Disorder induced by the unpredictable distribution of material defects is one of the major contributions to the reality gap. We bridge this gap using physics-aware machine learning, in particular, using an approach combining a physical model, deep learning, Gaussian random field, and Bayesian inference. This approach enables us to infer the disorder potential of a nanoscale electronic device from electron-transport data. This inference is validated by verifying the algorithm’s predictions about the gate-voltage values required for a laterally defined quantum-dot device in AlGaAs/GaAs to produce current features corresponding to a double-quantum-dot regime
A review of RCTs in four medical journals to assess the use of imputation to overcome missing data in quality of life outcomes
Background: Randomised controlled trials (RCTs) are perceived as the gold-standard method for evaluating healthcare interventions, and increasingly include quality of life (QoL) measures. The observed results are susceptible to bias if a substantial proportion of outcome data are missing. The review aimed to determine whether imputation was used to deal with missing QoL outcomes. Methods: A random selection of 285 RCTs published during 2005/6 in the British Medical Journal, Lancet, New England Journal of Medicine and Journal of American Medical Association were identified. Results: QoL outcomes were reported in 61 (21%) trials. Six (10%) reported having no missing data, 20 (33%) reported ≤ 10% missing, eleven (18%) 11%–20% missing, and eleven (18%) reported >20% missing. Missingness was unclear in 13 (21%). Missing data were imputed in 19 (31%) of the 61 trials. Imputation was part of the primary analysis in 13 trials, but a sensitivity analysis in six. Last value carried forward was used in 12 trials and multiple imputation in two. Following imputation, the most common analysis method was analysis of covariance (10 trials). Conclusion: The majority of studies did not impute missing data and carried out a complete-case analysis. For those studies that did impute missing data, researchers tended to prefer simpler methods of imputation, despite more sophisticated methods being available.The Health Services Research Unit is funded by the Chief Scientist Office of the Scottish Government Health Directorate. Shona Fielding is also currently funded by the Chief Scientist Office on a Research Training Fellowship (CZF/1/31)
A review of RCTs in four medical journals to assess the use of imputation to overcome missing data in quality of life outcomes
Peer reviewedPublisher PD
Self-perception of people who stutter regarding their experiences and results of stuttering treatments
Can programme theory be used as a 'translational tool’ to optimise health service delivery in a national early years’ initiative in Scotland: a case study
Background
Theory-based evaluation (TBE) approaches are heralded as supporting formative evaluation by facilitating increased use of evaluative findings to guide programme improvement. It is essential that learning from programme implementation is better used to improve delivery and to inform other initiatives, if interventions are to be as effective as they have the potential to be. Nonetheless, few studies describe formative feedback methods, or report direct instrumental use of findings resulting from TBE. This paper uses the case of Scotland’s, National Health Service, early years’, oral health improvement initiative (Childsmile) to describe the use of TBE as a framework for providing feedback on delivery to programme staff and to assess its impact on programmatic action.<p></p>
Methods
In-depth, semi-structured interviews and focus groups with key stakeholders explored perceived deviations between the Childsmile programme 'as delivered’ and its Programme Theory (PT). The data was thematically analysed using constant comparative methods. Findings were shared with key programme stakeholders and discussions around likely impact and necessary actions were facilitated by the authors. Documentary review and ongoing observations of programme meetings were undertaken to assess the extent to which learning was acted upon.<p></p>
Results
On the whole, the activities documented in Childsmile’s PT were implemented as intended. This paper purposefully focuses on those activities where variation in delivery was evident. Differences resulted from the stage of roll-out reached and the flexibility given to individual NHS boards to tailor local implementation. Some adaptations were thought to have diverged from the central features of Childsmile’s PT, to the extent that there was a risk to achieving outcomes. The methods employed prompted national service improvement action, and proposals for local action by individual NHS boards to address this.<p></p>
Conclusions
The TBE approach provided a platform, to direct attention to areas of risk within a national health initiative, and to agree which intervention components were 'core’ to its hypothesised success. The study demonstrates that PT can be used as a 'translational tool’ to facilitate instrumental use of evaluative findings to optimise implementation within a complex health improvement programme.<p></p>
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