Using discrete choice experiments to inform the design of complex interventions.
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SUBMITTER: Terris-Prestholt F
PROVIDER: S-EPMC6399844 | biostudies-literature | 2019 Mar
REPOSITORIES: biostudies-literature
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Project description:Although the factors influencing the shortage and maldistribution of health workers have been well-documented by cross-sectional surveys, there is less evidence on the relative determinants of health workers' job choices, or on the effects of policies designed to address these human resources problems. Recently, a few studies have adopted an innovative approach to studying the determinants of health workers' job preferences. In the absence of longitudinal datasets to analyse the decisions that health workers have actually made, authors have drawn on methods from marketing research and transport economics and used Discrete Choice Experiments to analyse stated preferences of health care providers for different job characteristics. We carried out a literature review of studies using discrete choice experiments to investigate human resources issues related to health workers, both in developed and developing countries. Several economic and health systems bibliographic databases were used, and contacts were made with practitioners in the field to identify published and grey literature. Ten studies were found that used discrete choice experiments to investigate the job preferences of health care providers. The use of discrete choice experiments techniques enabled researchers to determine the relative importance of different factors influencing health workers' choices. The studies showed that non-pecuniary incentives are significant determinants, sometimes more powerful than financial ones. The identified studies also emphasized the importance of investigating the preferences of different subgroups of health workers. Discrete choice experiments are a valuable tool for informing decision-makers on how to design strategies to address human resources problems. As they are relatively quick and cheap survey instruments, discrete choice experiments present various advantages for informing policies in developing countries, where longitudinal labour market data are seldom available. Yet they are complex research instruments requiring expertise in a number of different areas. Therefore it is essential that researchers also understand the potential limitations of discrete choice experiment methods.
| S-EPMC2724490 | biostudies-literature
Project description:BackgroundDiscrete choice experiments have become a popular study design to study the labour market preferences of health workers. Discrete choice experiments in health, however, have been criticised for lagging behind best practice and there are specific methodological considerations for those focused on job choices. We performed a systematic review of the application of discrete choice experiments to inform health workforce policy.MethodsWe searched for discrete choice experiments that examined the labour market preferences of health workers, including doctors, nurses, allied health professionals, mid-level and community health workers. We searched Medline, Embase, Global Health, other databases and grey literature repositories with no limits on date or language and contacted 44 experts. Features of choice task and experimental design, conduct and analysis of included studies were assessed against best practice. An assessment of validity was undertaken for all studies, with a comparison of results from those with low risk of bias and a similar objective and context.ResultsTwenty-seven studies were included, with over half set in low- and middle-income countries. There were more studies published in the last four years than the previous ten years. Doctors or medical students were the most studied cadre. Studies frequently pooled results from heterogeneous subgroups or extrapolated these results to the general population. Only one third of studies included an opt-out option, despite all health workers having the option to exit the labour market. Just five studies combined results with cost data to assess the cost effectiveness of various policy options. Comparison of results from similar studies broadly showed the importance of bonus payments and postgraduate training opportunities and the unpopularity of time commitments for the uptake of rural posts.ConclusionsThis is the first systematic review of discrete choice experiments in human resources for health. We identified specific issues relating to this application of which practitioners should be aware to ensure robust results. In particular, there is a need for more defined target populations and increased synthesis with cost data. Research on a wider range of health workers and the generalisability of results would be welcome to better inform policy.
| S-EPMC4161911 | biostudies-literature
Project description:IntroductionWhile plain packaging of tobacco products has emerged as a policy intervention to reduce smoking, regulators in the US have limited ability to implement plain packaging. We sought to identify the impact of subtle changes to cigarette packaging (Study 1) and how packaging design influenced participant choices based on appeal, harm, and style (Study 2).MethodsWe conducted two discrete-choice experiments with US adult smokers online in 2018. In Study 1 (n=285), we assessed participants' selections based on subtle changes to pack design features (dimensions, color saturation, logo size). In Study 2 (n=284), we assessed three choices in which participants selected packs based on appeal, harmfulness, and best match to their personal style. Study 2 packs varied by color hue, design with different levels of organic labeling and natural imagery, and color saturation.ResultsPack designs influenced smokers' choices. In Study 1, pack dimensions and color saturation emerged as the most important features, and, in Study 2, design and color hue were the most influential characteristics.ConclusionsRegulators should consider how the design of cigarette packages may influence consumers' perceptions and choices.
| S-EPMC8445337 | biostudies-literature
Project description:In this paper we provide a detailed description of the methodological steps involved in conducting a Service Design study in combination with Discrete Choice Experiments (DCEs). It complements the conceptual and epistemological argument developed for this methodological combination in Osborne et al. (2021, World Development, in review WD-19535). Service Design for the co-creative development of policy interventions in complex adaptive systems involves an iterative process of moving between the six methodological stages of (1) problem co-definition, (2) actor-centred mapping, (3) experience-based problem diagnosis, (4) rapid prototyping, (5) design and testing and (6) upscaling. We suggest using DCEs as a quantitative method that is contextually adaptable and comparatively fast and cheap to implement, as part of stage (6) design and testing. Whilst both methods can operate independently with their own strengths and limitations, we find their combination to add value to the processes and outcomes of each. We illustrate the general methodological approach with a step-by-step description of its application to Weather Index Insurance in eastern Uganda. Bullet points: • Service Design co-creatively develops well-targeted solutions in complex adaptive systems. • Discrete Choice Experiments quantitatively elicit actors' preferences over the design of goods or services. • Their combination can bring deeply contextualised, user-centred, operational and experimentally verified ideas for development interventions prior to their implementation.
| S-EPMC8563645 | biostudies-literature
Project description:Discrete choice experiments (DCEs) are increasingly used for studying and quantifying subjects preferences in a wide variety of healthcare applications. They provide a rich source of data to assess real-life decision-making processes, which involve trade-offs between desirable characteristics pertaining to health and healthcare and identification of key attributes affecting healthcare. The choice of the design for a DCE is critical because it determines which attributes' effects and their interactions are identifiable. We apply blocked fractional factorial designs to construct DCEs and address some identification issues by utilizing the known structure of blocked fractional factorial designs. Our design techniques can be applied to several situations including DCEs where attributes have different number of levels. We demonstrate our design methodology using two healthcare studies to evaluate (i) asthma patients' preferences for symptom-based outcome measures and (ii) patient preference for breast screening services. Copyright © 2016 John Wiley & Sons, Ltd.
| S-EPMC4893005 | biostudies-literature
Project description:ObjectivesThis study reviews simulation studies of discrete choice experiments to determine (i) how survey design features affect statistical efficiency, (ii) and to appraise their reporting quality.OutcomesStatistical efficiency was measured using relative design (D-) efficiency, D-optimality, or D-error.MethodsFor this systematic survey, we searched Journal Storage (JSTOR), Since Direct, PubMed, and OVID which included a search within EMBASE. Searches were conducted up to year 2016 for simulation studies investigating the impact of DCE design features on statistical efficiency. Studies were screened and data were extracted independently and in duplicate. Results for each included study were summarized by design characteristic. Previously developed criteria for reporting quality of simulation studies were also adapted and applied to each included study.ResultsOf 371 potentially relevant studies, 9 were found to be eligible, with several varying in study objectives. Statistical efficiency improved when increasing the number of choice tasks or alternatives; decreasing the number of attributes, attribute levels; using an unrestricted continuous "manipulator" attribute; using model-based approaches with covariates incorporating response behaviour; using sampling approaches that incorporate previous knowledge of response behaviour; incorporating heterogeneity in a model-based design; correctly specifying Bayesian priors; minimizing parameter prior variances; and using an appropriate method to create the DCE design for the research question. The simulation studies performed well in terms of reporting quality. Improvement is needed in regards to clearly specifying study objectives, number of failures, random number generators, starting seeds, and the software used.ConclusionThese results identify the best approaches to structure a DCE. An investigator can manipulate design characteristics to help reduce response burden and increase statistical efficiency. Since studies varied in their objectives, conclusions were made on several design characteristics, however, the validity of each conclusion was limited. Further research should be conducted to explore all conclusions in various design settings and scenarios. Additional reviews to explore other statistical efficiency outcomes and databases can also be performed to enhance the conclusions identified from this review.
| S-EPMC5898574 | biostudies-literature
Project description:IntroductionDespite the recognised importance of participant understanding for valid and reliable discrete choice experiment (DCE) results, there has been limited assessment of whether, and how, people understand DCEs, and how 'understanding' is conceptualised in DCEs applied to a health context.ObjectivesOur aim was to identify how participant understanding is conceptualised in the DCE literature in a health context. Our research questions addressed how participant understanding is defined, measured, and used.MethodsSearches were conducted (June 2019) in the MEDLINE, EMBASE, PsychINFO and Econlit databases, as well as hand searching. Search terms were based on previous DCE systematic reviews, with additional understanding keywords used in a proximity-based search strategy. Eligible studies were peer-reviewed journal articles in the field of health, related to DCE or best-worst scaling type 3 (BWS3) studies, and reporting some consideration or assessment of participant understanding. A descriptive analytical approach was used to chart relevant data from each study, including publication year, country, clinical area, subject group, sample size, study design, numbers of attributes, levels and choice sets, definition of understanding, how understanding was tested, results of the understanding tests, and how the information about understanding was used. Each study was categorised based on how understanding was conceptualised and used within the study.ResultsOf 306 potentially eligible articles identified, 31 were excluded based on titles and abstracts, and 200 were excluded on full-text review, resulting in 75 included studies. Three categories of study were identified: applied DCEs (n = 52), pretesting studies (n = 7) and studies of understanding (n = 16). Typically, understanding was defined in relation to either the choice context, such as attribute terminology, or the concept of choosing. Very few studies considered respondents' engagement as a component of understanding. Understanding was measured primarily through qualitative pretesting, rationality or validity tests included in the survey, and participant self-report, however reporting and use of the results of these methods was inconsistent.ConclusionsThose conducting or using health DCEs should carefully select, justify, and report the measurement and potential impact of participant understanding in their specific choice context. There remains scope for research into the different components of participant understanding, particularly related to engagement, the impact of participant understanding on DCE validity and reliability, the best measures of understanding, and methods to maximise participant understanding.
| S-EPMC7794102 | biostudies-literature
Project description:IntroductionApproximately one million undiagnosed persons living with HIV in Southern and Eastern Africa need to test for HIV. Novel approaches are necessary to identify HIV testing options that match the heterogeneous testing preferences of high-risk populations. This pragmatic randomised controlled trial (PRCT) will evaluate the efficacy of a preference-informed, heterogeneity-focused HIV counselling and testing (HCT) offer, for improving rates of HIV testing in two high-risk populations.Methods and analysisThe study will be conducted in Moshi, Tanzania. The PRCT will randomise 600 female barworkers and 600 male Kilimanjaro mountain porters across three study arms. All participants will receive an HIV testing offer comprised of four preference-informed testing options, including one 'common' option-comprising features that are commonly available in the area and, on average, most preferred among study participants-and three options that are specific to the study arm. Options will be identified using mixed logit and latent class analyses of data from a discrete choice experiment (DCE). Participants in Arm 1 will be offered the common option and three 'targeted' options that are predicted to be more preferred than the common option and combine features widely available in the study area. Participants in Arm 2 will be offered the common option and three 'enhanced' options, which also include HCT features that are not yet widely available in the study area. Participants in Arm 3, an active control arm, will be offered the common option and three predicted 'less preferred' options. The primary outcome will be uptake of HIV testing.Ethics and disseminationEthical approval was obtained from the Duke University Health System IRB, the University of South Carolina IRB, the Ethics Review Committee at Kilimanjaro Christian Medical University College, Tanzania's National Institute for Medical Research, and the Tanzania Food & Drugs Authority (now Tanzania Medicines & Medical Devices Authority). Findings will be published in peer-reviewed journals. The use of rigorous DCE methods for the preference-based design and tailoring of interventions could lead to novel policy options and implementation science approaches.Trial registration numberNCT02714140.
| S-EPMC7651730 | biostudies-literature
Project description:BackgroundWhile involving users in healthcare decision-making has become increasingly common and important, there is a lack of knowledge about how to best design community-based health screening programs. Reviews of methods that incorporate discrete choice experiments (DCEs) are scarce, particularly for non-cancer illnesses like cardiovascular disease, diabetes and liver disease. We provide an overview of currently available applications and methods available by using DCEs in health screening programs, for chronic conditions.MethodsA scoping review was undertaken, where four electronic databases were searched for key terms to identify eligible DCE studies related to community health screening. We included studies that met a pre-determined criteria, including being published between 2011 and 2021, in English and reported findings on human participants. Data were systematically extracted, tabulated, and summarised in a narrative review.ResultsA total of 27 studies that used a DCE to elicit preferences for cancer (n = 26) and cardiovascular disease screening (n = 1) programmes were included in the final analysis. All studies were assessed for quality, against a list of 13 criteria, with the median score being 9/13 (range 5-12). Across the 27 studies, the majority (80%) had the same overall scores. Two-thirds of included studies reported a sample size calculation, approximately half (13/27) administered the survey completely online and over 75% used the general public as the participating population.ConclusionOur review has led to highlighting several areas of current practice that can be improved, particularly greater use of sample size calculations, increased use of qualitative methods, better explanation of the chosen experimental design including how choice sets are generated, and methods for analysis.
| S-EPMC9400308 | biostudies-literature
Project description:ObjectivesDiscrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990-2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges.MethodsA systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated.ResultsOf the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels.ConclusionsThe use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers' confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research.
| S-EPMC6386055 | biostudies-literature