Using blocked fractional factorial designs to construct discrete choice experiments for healthcare studies

Cannabis consumers' preferences for legal and illegal cannabis: evidence from a discrete choice experiment

BACKGROUND

In U.S. states that legalized and commercialized recreational cannabis, cannabis sales in illegal markets are still sizable or even larger than those in legal markets. This study aimed to assess cannabis consumers' preferences for purchasing cannabis from legal and illegal markets and estimate the trade-offs under various policy scenarios.

METHODS

963 adults were recruited, who used cannabis in the past year and lived in a state with recreational cannabis legalization. In a discrete choice experiment, participants chose purchasing cannabis from a legal dispensary or an illegal dealer with varying levels in product attributes including quality, safety, accessibility, potency, and price. Mixed logit models were used to analyze preferences.

RESULTS

The likelihood of choosing legal cannabis increased with a higher quality, the presence of lab test, a shorter distance to seller, a higher tetrahydrocannabinol level, and a lower price. The likelihood of choosing illegal cannabis increased with a higher quality, a shorter distance to seller, and a lower price. Among product attributes, quality and accessibility were perceived to be the most important for legal cannabis and price was perceived to be the most important for illegal cannabis. Policy simulations predicted that improving quality, ensuring safety, allowing delivery services, increasing dispensary density, and lowering prices/taxes of legal cannabis may reduce illegal cannabis market share.

CONCLUSIONS

In the U.S., cannabis consumers' preferences for illegal cannabis were associated with both legal and illegal cannabis product attributes. Policies regulating legal cannabis markets should consider potential spillover effects to illegal markets.

Understanding Clinician Preferences for Treatment Attributes in Oncology: A Discrete Choice Experiment of Oncologists' and Urologists' Preferences for First-Line Treatment of Locally Advanced/Unresectable Metastatic Urothelial Carcinoma in Five European Countries

INTRODUCTION

Prior discrete choice experiments (DCE) in oncology found that, on average, clinicians rank survival as the most important treatment attribute. We investigate heterogeneity in clinician preferences within the context of first-line treatment for advanced urothelial carcinoma in Spain, France, Italy, Germany, and the UK.

METHODS

The online DCE included 12 treatment choice tasks, each comparing two hypothetical therapy profiles defined by treatment attributes: grade 3/4 treatment-related adverse events (TRAEs), induction and maintenance administration schedules, progression-free survival, and overall survival (OS). We used a random parameters logit model to estimate attribute relative importance (RI) (0-100%) and generate preference shares for four treatment profiles. Results were stratified by country. Preference heterogeneity was evaluated by latent class analysis.

RESULTS

In August and September 2022, 498 clinicians (343 oncologists and 155 urologists) completed the DCE. OS had the strongest influence on clinicians' preferences [RI = 62%; range, 51.6% (Germany) to 63.7% (Spain)] followed by frequency of grade 3/4 TRAEs (RI = 27%). Among treatment profiles, the chemotherapy plus immune checkpoint inhibitor maintenance therapy profile had the largest preference share [51%; range, 38% (Italy) to 56% (UK)]. Four latent classes of clinicians were identified (N = 469), with different treatment profile preferences: survival class (30.1%), trade-off class (22.4%), no strong preference class (40.9%), and aggressive treatment class (6.6%). OS was not the most important attribute for 30.0% of clinicians.

CONCLUSION

While average sample results were consistent with those of prior DCEs, this study found heterogeneity in clinician preferences within and across countries, highlighting the diversity in clinician decision making in oncology.

Patients' Preferences for Antiretroviral Therapy Service in Northwest Ethiopia: A Discrete Choice Experiment

Objective. We aim to evaluate patients' preferences for antiretroviral therapy (ART) to enhance shared decision making in clinical practice in Northwest Ethiopia. Methods. A discrete choice experiment approach was used among adult patients from 36 randomly selected public health facilities from February 6, 2023, to March 29, 2023. A literature review, qualitative work, ranking and rating surveys, and expert consultation were used to identify the attributes. Location, provider, frequency of visit, appointment modality, refill time, and cost of visit were the 6 ART service features chosen. Participants were given the option of choosing between 2 hypothetical differentiated ART delivery models. Mixed logit and latent class analysis were used. Results: Four hundred fifty-six patients completed the choice task. Respondents preferred to receive ART refills alone at health facilities by health care workers without having to have frequent visits and with reduced cost of visit. Overall, the participants valued the cost of the visit the most while they valued the timing of ART refill the least. Participants were willing to pay only for the attributes of frequency of visit and medication refill time. The latent class model with 3 classes provided the best model fit. Location, cost, and frequency were the most important attributes in class 1, class 2, and class 3, respectively. Income and marital status significantly predicted class membership. Conclusions. Respondents preferred to receive refills at health facilities, less frequent visits, individual appointments, service provision by health care workers, and reduced cost of visit. The cost attribute had the greatest impact on the choice of patients. Health care workers should consider the preferences of patients while providing ART services to meet patients' expectations and choices.

Highlights

A discrete choice experiment was used to elicit patient preferences.People living with HIV preferred receiving medication refills at health facilities, less frequent visits, individual appointments, service delivery by health care workers, and lower visit costs.Health care workers should consider the preferences of patients while providing ART service to meet their expectations and choices.Scaling up differentiated HIV treatment services is crucial for patient-centered care.

Multiple Messaging Strategies for Increasing HPV Vaccination Intentions among English- and Spanish-Speaking Parents in the United States and Mexico

The reported study compared the impact of four influence strategies (agency assignment, enhanced active choice, deviance regulation marking, and temporal framing) on English- and Spanish-speaking parents' reported intention to vaccinate their children for HPV. An online experiment was conducted to examine the impact of the strategies. In a fractional factorial design, participating parents (N = 1663) were exposed to combinations of influence strategies in text messages presented as reminders they might receive from a healthcare provider about their child's eligibility for the vaccine series. The results indicated small but significant impacts of agency assignment, enhanced active choice, and deviance regulation marking on parents' reported vaccination intentions. The study adds to the research literature on HPV vaccination communication in two important respects. First, it demonstrated how incorporating evidence-based influence strategies into reminder messages can increase parents' vaccination intentions, an important precursor and predictor of actual vaccine uptake. Second, it sets an important precedent by examining the effects of influence strategies on vaccination intentions across different languages.

Eliciting preferences of persons with dementia and informal caregivers to support ageing in place in the Netherlands: a protocol for a discrete choice experiment

INTRODUCTION

Ageing in place (AIP) for persons with dementia is encouraged by European governments and societies. Healthcare packages may need reassessment to account for the preferences of care funders, patients and informal caregivers. By providing insight into people's preferences, discrete choice experiments (DCEs) can help develop consensus between stakeholders. This protocol paper outlines the development of a Dutch national study to cocreate a healthcare package design methodology built on DCEs that is person-centred and helps support informal caregivers and persons with dementia to AIP. A subpopulation analysis of persons with dementia with a migration background is planned due to their high risk for dementia and under-representation in research and care.

METHODS AND ANALYSIS

The DCE is designed to understand how persons with dementia and informal caregivers choose between different healthcare packages. Qualitative methods are used to identify and prioritise important care components for persons with dementia to AIP. This will provide a list of care components that will be included in the DCE, to quantify the care needs and preferences of persons with dementia and informal caregivers. The DCE will identify individual and joint preferences to AIP. The relative importance of each attribute will be calculated. The DCE data will be analysed with the use of a random parameters logit model.

ETHICS AND DISSEMINATION

Ethics approval was waived by the Amsterdam University Medical Center (W23_112 #23.137). A study summary will be available on the websites of Alzheimer Nederland, Pharos and Amsterdam Public Health institute. Results are expected to be presented at (inter)national conferences, peer-reviewed papers will be submitted, and a dissemination meeting will be held to bring stakeholders together. The study results will help improve healthcare package design for all stakeholders.

Patient Preferences for the Management of Gastrointestinal Symptoms in Kidney Transplantation: a Discrete Choice Experiment

Introduction

Gastrointestinal (GI) symptoms in kidney transplant are common and debilitating. We aimed to ascertain patients' preferences for GI symptom management options to help future interventions align with treatment priorities.

Methods

A discrete choice experiment was conducted with kidney transplant recipients in 3 Australian nephrology units. A multinomial logit model was used to quantify the preferences and trade-offs between 5 characteristics: cost, formulation, symptom burden, dietary changes, and medication quantities.

Results

Seventy patients participated (mean age ± SD: 47 ± 15 years, 56% female), 57% had GI symptoms. Patients preferred interventions that will achieve complete resolution of GI symptoms compared to no improvement (odds ratio [95% confidence interval]: 15.3 [1.80, 129.50]), were delivered as a tablet rather than a sachet (1.6 [1.27, 2.08]), retained their current diet compared to eliminating food groups (6.0 [2.19, 16.27]), reduced medication burden (1.4 [1.06, 1.79]), and had lower costs (0.98 [0.96, 1.00]). Participants would be willing to pay AUD$142.20 [$83.90, $200.40] monthly to achieve complete resolution of GI symptoms or AUD$100.90 [$9.60, $192.10] to have moderate improvement in symptoms.

Conclusions

Interventions that are highly effective in relieving all GI symptoms without the need for substantive dietary changes, and in tablet form, are most preferred by kidney transplant recipients.

Discrete choice experiments: An overview on constructing D-optimal and near-optimal choice sets

Discrete choice experiments (DCEs) are frequently used to estimate and forecast the behavior of an individual's choice. DCEs are based on stated preference; therefore, underlying experimental designs are required for this type of study. According to psychologists, DCE designs consist of a small number of choice sets with a limited size in the number of alternatives within a choice set to increase the response efficiency in the questionnaire. Even though algorithmic constructions (known as efficient designs) become quite common for practitioners, optimal designs (sometimes so-called orthogonal designs) continue to be used in choice experiment studies, particularly in the case that prior information about the extent of the population preference is not available. Various approaches have been developed to construct DCE designs with fewer choice sets. However, the question in many practitioners' minds is which techniques perform better (i.e. given small designs with high efficiency) in a given circumstance. In this paper and to address these concerns, we conducted an overview of the constructions of discrete choice experiments in the literature for models with only main effects. The various ways of constructing optimal and near-optimal designs were compared in terms of their ability to minimize the number of choice sets in the survey. Our findings shed light on the optimal sample sizes needed for efficient experimentation which then can help the researchers to design more effective experiments in this area.

Preferences for first-line treatment of advanced urothelial carcinoma among US practicing oncologists and patients

Aim: Investigate oncologist and patient preferences for the first-line treatment of advanced urothelial carcinoma. Materials & methods: A discrete-choice experiment was used to elicit treatment attribute preferences, including patient treatment experience (number and duration of treatments and grade 3/4 treatment-related adverse events), overall survival and treatment administration frequency. Results: The study included 151 eligible medical oncologists and 150 patients with urothelial carcinoma. Both physicians and patients appeared to prefer treatment attributes related to overall survival, treatment-related adverse events and the number and duration of the medications in a regimen over frequency of administration. Overall survival had the most influence in driving oncologists' treatment preferences, followed by the patient's treatment experience. Patients found the treatment experience the most important attribute when considering options, followed by overall survival. Conclusion: Patient preferences were based on treatment experience, while oncologists preferred treatments that prolong overall survival. These results help to direct clinical conversations, treatment recommendations and clinical guideline development.

Which Factors Are Considered by Patients When Considering Total Joint Arthroplasty? A Discrete-choice Experiment

BACKGROUND

TKA and THA are major surgical procedures, and they are associated with the potential for serious, even life-threatening complications. Patients must weigh the risks of these complications against the benefits of surgery. However, little is known about the relative importance patients place on the potential complications of surgery compared with any potential benefit the procedures may achieve. Furthermore, patient preferences may often be discordant with surgeon preferences regarding the treatment decision-making process. A discrete-choice experiment (DCE) is a quantitative survey technique designed to elicit patient preferences by presenting patients with two or more hypothetical scenarios. Each scenario is composed of several attributes or factors, and the relative extent to which respondents prioritize these attributes can be quantified to assess preferences when making a decision, such as whether to pursue lower extremity arthroplasty.

QUESTIONS/PURPOSES

In this DCE, we asked: (1) Which patient-related factors (such as pain and functional level) and surgery-related factors (such as the risk of infection, revision, or death) are influential in patients' decisions about whether to undergo lower extremity arthroplasty? (2) Which of these factors do patients emphasize the most when making this decision?

METHODS

A DCE was designed with the following attributes: pain; physical function; return to work; and infection risks, reoperation, implant failure leading to premature revision, deep vein thrombosis, and mortality. From October 2021 to March 2022, we recruited all new patients to two arthroplasty surgeons' clinics who were older than 18 years and scheduled for a consultation for knee- or hip-related complaints who had no previous history of a primary TKA or THA. A total of 56% (292 of 517) of new patients met the inclusion criteria and were approached with the opportunity to complete the DCE. Among the cohort, 51% (150 of 292) of patients completed the DCE. Patients were administered the DCE, which consisted of 10 hypothetical scenarios that had the patient decide between a surgical and nonsurgical outcome, each consisting of varying levels of eight attributes (such as infection, reoperation, and ability to return to work). A subsequent demographic questionnaire followed this assessment. To answer our first research question about the patient-related and surgery-related factors that most influence patients' decisions to undergo lower extremity arthroplasty, we used a conditional logit regression to control for potentially confounding attributes from within the DCE and determine which variables shifted a patient's determination to pursue surgery. To answer our second question, about which of these factors received the greatest priority by patients, we compared the relevant importance of each factor, as determined by each factor's beta coefficient, against each other influential factor. A larger absolute value of beta coefficient reflects a relatively higher degree of importance placed on a variable compared with other variables within our study. Of the respondents, 57% (85 of 150) were women, and the mean age at the time of participation was 64 ± 10 years. Most respondents (95% [143 of 150]) were White. Regarding surgery, 38% (57 of 150) were considering THA, 59% (88 of 150) were considering TKA, and 3% (5 of 150) were considering both. Among the cohort, 49% (74 of 150) of patients reported their average pain level as severe, or 7 to 10 on a scale from 0 to 10, and 47% (71 of 150) reported having 50% of full physical function.

RESULTS

Variables that were influential to respondents when deciding on lower extremity total joint arthroplasty were improvement from severe pain to minimal pain (β coefficient: -0.59 [95% CI -0.72 to -0.46]; p < 0.01), improvement in physical function level from 50% to 100% (β: -0.80 [95% CI -0.9 to -0.7]; p < 0.01), ability to return to work versus inability to return (β: -0.38 [95% CI -0.48 to -0.28]; p < 0.01), and the surgery-related factor of risk of infection (β: -0.22 [95% CI -0.30 to -0.14]; p < 0.01). Improvement in physical function from 50% to 100% was the most important for patients making this decision because it had the largest absolute coefficient value of -0.80. To improve physical function from 50% to 100% and reduce pain from severe to minimal because of total joint arthroplasty, patients were willing to accept a hypothetical absolute (and not merely an incrementally increased) 37% and 27% risk of infection, respectively. When we stratified our analysis by respondents' preoperative pain levels, we identified that only patients with severe pain at the time of their appointment found the risk of infection influential in their decision-making process (β: -0.27 [95% CI -0.37 to -0.17]; p = 0.01) and were willing to accept a 24% risk of infection to improve their physical functioning from 50% to 100%.

CONCLUSION

Our study revealed that patients consider pain alleviation, physical function improvement, and infection risk to be the most important attributes when considering total joint arthroplasty. Patients with severe baseline pain demonstrated a willingness to take on a hypothetically high infection risk as a tradeoff for improved physical function or pain relief. Because patients seemed to prioritize postoperative physical function so highly in our study, it is especially important that surgeons customize their presentations about the likelihood an individual patient will achieve a substantial functional improvement as part of any office visit where arthroplasty is discussed. Future studies should focus on quantitatively assessing patients' understanding of surgical risks after a surgical consultation, especially in patients who may be the most risk tolerant.

CLINICAL RELEVANCE

Surgeons should be aware that patients with the most limited physical function and the highest baseline pain levels are more willing to accept the more potentially life-threatening and devastating risks that accompany total joint arthroplasty, specifically infection. The degree to which patients seemed to undervalue the harms of infection (based on our knowledge and perception of those harms) suggests that surgeons need to take particular care in explaining the degree to which a prosthetic joint infection can harm or kill patients who develop one.

Food Choices and Hypertension Among Rural Thais: Evidence From a Discrete Choice Experiment

Objective: The rural northern region of Thailand exhibits the highest rate of hypertension. This study explored hypertensive-related food choices between normotensive and hypertensive people residing in rural northern Thailand to determine which food attributes influence their choices. Methods: The study conducted a discrete choice experiment (DCE) survey among Thai adults residing in rural northern Thailand (n = 403) to estimate the relative importance of four food attributes, including food preparation, price, taste, and amount of salt. A mixed logit model was used to analyze the data from the DCE. Results: The first and second most important attributes in both hypertensive and normotensive groups were the amount of salt and food preparation at home, respectively, followed by price and taste. Specifically, the normotensive group was more attentive to the amount of salt in their food than their hypertensive counterparts. Conclusion: Intervention programs in rural communities may benefit from focusing their attention on embracing low-salt cultural foods and providing guidance on how to add flavor without additional salt or reduce high sodium seasonings without losing flavor when cooking.

Nonurgent Patients' Preferences for Emergency Department Versus General Practitioner and Effects of Incentives: A Discrete Choice Experiment

Objective. This study investigates potential of a new financial incentive policy, the GP-referral discount scheme introduced in Singapore, in reducing nonurgent emergency department (ED) visits, and compares it with alternative interventions. Methods. A discrete choice experiment (DCE) was designed to elicit patients’ preferences for ED and general practitioner (GP) under hypothetical nonurgent medical conditions. Through latent class multinomial logistic regression, choice models were estimated to quantify how patients’ choices are influenced by GP-referral discount, other ED/GP attributes (waiting time, test facilities, and payment), patient demographics, and their perception of severity. The choice models were used to predict uptake of the GP-referral discount scheme and other countermeasures suggested by these models. Results. Survey responses from 849 respondents recruited from a public hospital in Singapore were included in the study. The choice model identified two prominent classes of patients, one of which was highly sensitive to GP-referral discount and the other to test-facility-availability. Patients’ perceptions of severity (“critical” v. “not critical” enough to go to ED directly) were highly significant in influencing preference heterogeneity. Predictive analysis based on the choice model showed that GP-referral discount is more effective when patients visit ED expecting “shorter” waits, as opposed to test-facility provision at GPs and perception-correction measures that showed stronger effects under “longer” expected waits. Conclusions. The new GP-referral financial incentive introduced in Singapore can be effective in reducing nonurgent ED visits, if it reasonably covers the (extra) cost of visiting a GP. It may serve as a complement to test-facility provision at GPs or perception-correction measures, as the financial incentive and the latter two measures appear to influence distinct classes (discount-sensitive and facility-sensitive) of patients.

Patients' Preferences Regarding Osteoarthritis Medications: An Adaptive Choice-Based Conjoint Analysis Study

BACKGROUND AND OBJECTIVE

Osteoarthritis (OA) patients consider ranges of harms and benefits offered by alternative pharmaceutical treatments. Choice-based experiments provide a mechanism to value outcomes, but they can pose a significant burden on respondents. Thus, the number of attributes studied is typically artificially restricted. We used an adaptive choice-based conjoint (ACBC) method that allows the inclusion of more attributes affecting patients' preferences regarding non-invasive pharmaceutical treatment for OA than traditional choice-based technique to better understand the trade-offs that OA patients consider, without increasing respondents' burden.

METHODS

After consulting with OA patients and public involvement (PPI) group, we constructed an online ACBC survey consisting of 9 attributes and a total of 31 levels (two benefits, four harms and three concerning the availability and modality of treatment). A cohort of patients with a diagnosis of OA and reporting joint pain within the last 12 months were recruited.

RESULTS

Our study (n 43) showed that the most important factor in choosing OA medication was the risk of heart attacks and strokes (19.5%), followed by the risk of addiction (18.4%), risk of kidney and liver side effects (17.5%), risk stomach side effects (14.6%), availability (11.6%), frequency of use (5.3%), pain reduction (5%), way of taking medication (4.6%) and mobility improvement (3.5%).

CONCLUSION

ACBC provides a mechanism for understanding patient preferences that address the limitations of traditional choice-based experiments. For OA patients, avoidance of the risk of side effects were the most affecting medication choices, and reductions in pain and mobility were the least. Clinicians discussing options for medication with OA patients should discuss the potential trade-offs in terms of risks and benefits.

US Privacy Laws Go Against Public Preferences: Impeding Public Health and Research (Preprint)

Background

Reaping the benefits from massive volumes of data collected in all sectors to improve population health, inform personalized medicine, and transform biomedical research requires the delicate balance between the benefits and risks of using individual-level data. There is a patchwork of US data protection laws that vary depending on the type of data, who is using it, and their intended purpose. Differences in these laws challenge big data projects using data from different sources. The decisions to permit or restrict data uses are determined by elected officials; therefore, constituent input is critical to finding the right balance between individual privacy and public benefits.

Objective

This study explores the US public’s preferences for using identifiable data for different purposes without their consent.

Methods

We measured data use preferences of a nationally representative sample of 504 US adults by conducting a web-based survey in February 2020. The survey used a choice-based conjoint analysis. We selected choice-based conjoint attributes and levels based on 5 US data protection laws (Health Insurance Portability and Accountability Act, Family Educational Rights and Privacy Act, Privacy Act of 1974, Federal Trade Commission Act, and the Common Rule). There were 72 different combinations of attribute levels, representing different data use scenarios. Participants were given 12 pairs of data use scenarios and were asked to choose the scenario they were the most comfortable with. We then simulated the population preferences by using the hierarchical Bayes regression model using the ChoiceModelR package in R.

Results

Participants strongly preferred data reuse for public health and research than for profit-driven, marketing, or crime-detection activities. Participants also strongly preferred data use by universities or nonprofit organizations over data use by businesses and governments. Participants were fairly indifferent about the different types of data used (health, education, government, or economic data).

Conclusions

Our results show a notable incongruence between public preferences and current US data protection laws. Our findings appear to show that the US public favors data uses promoting social benefits over those promoting individual or organizational interests. This study provides strong support for continued efforts to provide safe access to useful data sets for research and public health. Policy makers should consider more robust public health and research data use exceptions to align laws with public preferences. In addition, policy makers who revise laws to enable data use for research and public health should consider more comprehensive protection mechanisms, including transparent use of data and accountability.

Which snack factors and nutritional ingredients influence college students' snack choices? Evidence from discrete choice experiments

Objective: The study examined which snack factors and nutritional ingredients influence college students' snack choices using a discrete choice experiment (DCE). Participants: In November 2016, a total of 1,624 undergraduate students participated in the study. Methods: Two DCEs were constructed using a unique approach of block fractional factorial designs. The first DCE examined four three-level snack factors: healthiness, taste, convenience, and price. The second DCE focused on six two-level nutritional ingredients: sugar, salt, calories, fat, all natural, and fiber. Results: Students preferred quick and cheap snacks, but higher prices on healthy snacks did not affect their decision significantly. Healthiness and sugar had the highest relative importance of snack factors and nutritional ingredients, respectively. High-sugar snacks were less favored if students considered themselves educated in nutrition. Conclusion: Thus, potential ways to improve the snack choices for college students are to offer healthier snacks on college campuses and to promote nutrition education.

The impacts of potency, warning messages, and price on preferences for Cannabis flower products

BACKGROUND

Recreational cannabis has been legalized in 11 states and Washington DC in the US. However, little is known about individual preferences for legal cannabis products. This study estimated the impacts of tetrahydrocannabinol (THC), cannabidiol (CBD), warning messages, and price on preferences for cannabis flowers.

METHODS

A cross-sectional online survey with discrete choice experiments was implemented in October 2017. A sample of 2400 adults aged 21 years or older were recruited from 6 US states with recreational cannabis legalization, consisting of 1200 past-year nonusers and 1200 past-year users. Each respondent was randomly assigned to 12 discrete choice scenarios, each asking them to choose from an opt-out option and 3 cannabis flower products with varying levels in THC, CBD, warning messages, and price. The impacts of product attributes on individual choices were analyzed with nested logit regressions.

RESULTS

Both cannabis nonusers and users preferred higher CBD and lower price. Users also preferred higher THC. The results on warning messages were mixed: graphic warning on drugged driving and text warning message had positive impacts on nonusers' and users' preferences for cannabis flowers, respectively, whereas FDA disapproval disclaimer had negative impacts on nonusers' preferences. Heterogeneities in preferences were revealed among nonusers by former use status and among users by reason of use. Particularly, medical cannabis users were not as responsive to THC as recreational cannabis users or dual users were. Regarding relative importance of the attributes, all respondents but medical cannabis users perceived price as the most important attribute (relative importance 51-64%), whereas medical cannabis users perceived CBD as the most important attribute (relative importance 47%).

CONCLUSION

The findings indicated that product characteristics may have influences on US adults' choices of legal cannabis flower products and may deserve consideration for cannabis regulatory framework.

Orthogonal Array composite design to study and optimize antioxidant combinations in the prevention of UVB-induced HSF damage

Excessive exposure to ultraviolet (UV) B radiation may lead to skin damage, photosensitivity, or even tumorigenesis via induction of oxidative stress. Naturally derived antioxidants could play significant roles in cancer therapy due to their multi-targeted actions and lack of substantial toxicity. Drug combinations target at diverse pathway of cells and make cells export meticulous biological outcomes through the multifaceted signaling network. The UVB protective effects of combinations of naturally derived antioxidants- curcumin, resveratrol, proanthocyanidins, baicalein, and beta-nicotinamide adenine dinucleotide (NADH) were investigated. An oxidative cell damage model was established to study the ultraviolet irradiation system. An orthogonal array composite design (OACD) was employed in the optimization of antioxidants combinations. Combination of resveratrol (0.1μM) and baicalein in medium concentration (0.2μM), with NADH in high concentration (0.8μM) was found to be the most efficacious combination among all the 30 runs performed using OACD. The findings suggested that UVB exposure-inflicted cell apoptosis can be significantly reduced by naturally-derived antioxidant combinations. These results provide an insight into the discovery of synergistic antioxidant combinations in skin cancer, using orthogonal array composite design (OACD). The results also have practical implications in the understanding of drug mechanisms in skin cancer, which can assist clinical practice by recommending better drug combinations.

A Bayesian hierarchical model for discrete choice data in health care

In discrete choice experiments, patients are presented with sets of health states described by various attributes and asked to make choices from among them. Discrete choice experiments allow health care researchers to study the preferences of individual patients by eliciting trade-offs between different aspects of health-related quality of life. However, many discrete choice experiments yield data with incomplete ranking information and sparsity due to the limited number of choice sets presented to each patient, making it challenging to estimate patient preferences. Moreover, methods to identify outliers in discrete choice data are lacking. We develop a Bayesian hierarchical random effects rank-ordered multinomial logit model for discrete choice data. Missing ranks are accounted for by marginalizing over all possible permutations of unranked alternatives to estimate individual patient preferences, which are modeled as a function of patient covariates. We provide a Bayesian version of relative attribute importance, and adapt the use of the conditional predictive ordinate to identify outlying choice sets and outlying individuals with unusual preferences compared to the population. The model is applied to data from a study using a discrete choice experiment to estimate individual patient preferences for health states related to prostate cancer treatment.

Application of sequential factorial design and orthogonal array composite design (OACD) to study combination of 5 prostate cancer drugs

Prostate cancer is one of the most common cancers among men in the United States. It is also a major leading cause of cancer death among men of all races. In order to treat prostate cancer, drug combinations are often applied. Drug combinations target at different pathways of cells can potentially lead to higher efficacy and lower toxicity due to drug synergy. In this paper, we sequentially applied a two-level design and a follow-up orthogonal array composite design (OACD) to investigate combinations of five anti-cancer drugs, namely, doxorubicin, docetaxel, paclitaxel, cis-dichlorodiamine platinum and dihydroartemisinin. Our initial screening using a two-level full factorial design identified doxorubicin and docetaxel as the most significant drugs. A follow-up experiment with an OACD revealed more complicated drug interactions among these 5 anti-cancer drugs. Quadratic effects of doxorubicin and paclitaxel appeared to be significant. A further investigation on contour plots of all the two-drug pairs indicated that combination of doxorubicin and docetaxel are the most effective companion, while the combination of cis-dichlorodiamine platinum and dihydroartemisinin showed unknown antagonistic effects which diminished the individual drug anti-cancer efficacy. These observations have significant practical implications in the understanding of anti-cancer drug mechanism that can facilitate clinical practice of better drug combinations.