Adaptive Choice-based Conjoint Analysis Research Articles

Patient Preferences: Results of a German Adaptive Choice-Based Conjoint Analysis (Market Research Study Sponsored by Eli Lilly and Company) in Patients on Palliative Treatment for Advanced Breast Cancer

Introduction: Integration of patient preferences into shared decision making improves disease-related outcomes, but such data from patients with advanced breast cancer (aBC) are limited. The objective of this study was to demonstrate the relative importance of overall survival (OS) and progression-free survival (PFS) in relation to quality of life (QoL) and therapy-associated side effects from the perspective of patients with aBC. Methods: Postmenopausal patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative aBC receiving first- or second-line treatment were recruited throughout Germany. Patient-relevant attributes for aBC therapy assessment were collected using a stepwise multimodal approach. A conjoint matrix was developed, resulting in 2 attributes for therapy goals (OS and PFS), 4 for QoL, and 6 for side effects. An online quantitative survey was then performed using adaptive choice-based conjoint (ACBC) methodology. Results: The quantitative survey included 104 patients: 67 (64.4%) receiving first-line treatment and 37 (35.6%) receiving second-line treatment. The QoL attribute “physical agility and mobility” received the highest utility score (19.4 of 100%), reflecting the greatest importance to patients, followed by treatment goals (OS [15.2%] and PFS [14.4%]). Therapy-related side effects were less important, with nausea/vomiting being the most important (9.3%), followed by infection (6.4%) and hair loss (5.0%). The McFadden pseudo R² (0.805), the root likelihood (0.864), and the χ² test (2,809.041; p < 0.0001) indicated a very good fit of the statistical model. Conclusion: Using ACBC analysis, it appears that QoL, OS, and PFS are most important to postmenopausal patients with aBC in relation to cancer treatment. Side effects seem to be less important if OS or PFS are prolonged and the QoL is maintained. Thus, QoL, OS, and PFS should be considered equally when making treatment decisions in aBC.

Examining sustainability surcharges for outdoor apparel using Adaptive Choice-Based Conjoint analysis

In order to explore the compensatory effects between sustainability aspects and willingness to pay (WTP), the vast majority of studies applies Choice-Based Conjoint analysis (CBC). However, this method suffers from multiple restrictions (e.g., limited number of factors includable) resulting in biased WTP estimations. In contrast, the advanced and more realistic Adaptive Choice-Based Conjoint analysis (ACBC) allows – inter alia – incorporating all facets of sustainability and capturing the nowadays increasingly complex purchase decision process holistically. No other study has measured WTP with ACBC in the context of sustainable clothing yet. Based on expert interviews, we conduct an ACBC utilizing the ‘summed price’ approach and incorporating the insights gained from the Calibration section. While the latter one allows to refine the purchase likelihood and thus, enables more accurate WTP estimations, it has yet been largely neglected by previous sustainability literature. Our findings indicate significant differences in WTP and surcharges for each feature contingent on gender and the ecological orientation of consumers. While very green consumers rather emphasize the impact of sustainability-related features (e.g., materials (18.43%), labels (12.90%), country-of-origin (13.14%)), price represents by far the most influential driver for less green consumers (42.37%), followed by design (12.54%).

Job choice decisions: understanding the role of nonnegotiable attributes and trade-offs in effective segmentation

PurposeThis research draws upon decision-making theory to study job choice decisions. Past studies measured job choice as a single-stage, compositional process addressing the weights and part-worth utilities of a selected number of job and organizational attributes. However, the presence of noncompensatory attributes and whether the utilities and weights attached to the attributes vary among applicants have not been addressed. The authors posit that a conjoint analysis is an accurate methodological technique to explain job choice and overcome these limitations.Design/methodology/approachUsing a random sample of 571 participants, we conducted an adaptive choice-based conjoint analysis to estimate the weighted utilities of eight employer attributes and a cluster analysis to identify differences in preferences among employee profiles.FindingsThe results reveal that the use of the conjoint technique contributes to the literature in two ways. First, the results demonstrate the relevance of nonnegotiable attributes in the design of job offers. The results show that Salary, Flexibility and Ethics serve as cutoff points. Second, the results highlight the importance of considering the latent preferences of applicants in crafting effective job offers and adequately segmenting job applicants. More specifically, the following three groups are identified: Career-seeking applicants, Sustainability-oriented applicants and Pragmatic applicants.Practical implicationsThe managerial implications of this study are relevant for HR and employer brand managers since a better understanding of the job-choice process and implementing a decompositional method to understand applicants' preferences could allow firms to provide more customized and relevant job offers to employees of interest.Originality/valueThis study concludes that to implement efficient employer-attraction branding strategies, employers should understand the attributes considered noncompensatory by their employee target audience, promote the most valued/important attributes to ensure that job offers are customized to fit employees' underlying preferences, and devise trade-off strategies among compensatory attributes.

Examining Treatment Decision-Making Among Patients With Axial Spondyloarthritis: Insights From a Conjoint Analysis Survey.

ObjectiveThe number of therapies for axial spondyloarthritis (axSpA) is increasing. Thus, it has become more challenging for patients and physicians to navigate the risk‐benefit profiles of the various treatment options. In this study, we used conjoint analysis—a form of trade‐off analysis that elucidates how people make complex decisions by balancing competing factors—to examine patient decision‐making surrounding medication options for axSpA.MethodsWe conducted an adaptive choice‐based conjoint analysis survey for patients with axSpA to assess the relative importance of medication attributes (eg, chance of symptom improvement, risk of side effects, route of administration, etc) in their decision‐making. We also performed logistic regression to explore whether patient demographics and disease characteristics predicted decision‐making.ResultsOverall, 397 patients with axSpA completed the conjoint analysis survey. Patients prioritized medication efficacy (importance score 26.8%), cost (26.3%), and route of administration (13.9%) as most important in their decision‐making. These were followed by risk of lymphoma (9.5%), dosing frequency (7.2%), risk of serious infection (6.0%), tolerability of side effects (5.3%), and clinic visit and laboratory test frequency (4.8%). In regression analyses, there were few significant associations between patients’ treatment preferences and sociodemographic and axSpA characteristics.ConclusionsTreatment decision‐making in axSpA is highly individualized, and demographics and baseline disease characteristics are poor predictors of individual preferences. This calls for the development of online shared decision‐making tools for patients and providers, with the goal of selecting a treatment that is consistent with patients’ preferences.

4129 Understanding Treatment Preferences for Hodgkin Lymphoma (HL) among Physicians, Patients and Caregivers

OBJECTIVES/GOALS: Although their 5-year survival &gt;90%, young patients with HL face tradeoffs between near-term disease control and risk of treatment-related adverse effects decades later, so we seek to understand what patients and clinicians value in HL treatment decisions. METHODS/STUDY POPULATION: Leveraging our access to large cohorts of physicians, HL patients/survivors, and caregivers, we will use adaptive choice-based conjoint analysis (ACBC) to elicit treatment preferences when offered scenarios that incorporate tradeoffs, e.g., would a patient rather live 20 years with 10% risk of second malignancy or live 40 years with 30% of second malignancy. To reduce survey fatigue, prior choice responses limit subsequent scenarios. Through ACBC, we will identify variations in preferences and the importance of disease outcomes, treatment characteristics, and late effects for HL by respondent type. RESULTS/ANTICIPATED RESULTS: The goal is a final sample of 200 physicians and 200 patients/caregivers. We will collect demographics from physicians (age, type of physician, years practicing, type of practice, gender, and geography) and patients/caregivers (age at diagnosis, time since treatment, race, gender, smoker, education). We will ask questions about values of disease outcomes, late effects (second cancers, cardiac disease, chronic fatigue and neuropathy), and treatment characteristics (uncertainty of late effects, salvageability). Results will include utilities about participants views on disease-control and late effects. We anticipate participants to value disease control over late effects. DISCUSSION/SIGNIFICANCE OF IMPACT: Our study will elicit how physicians and patients/caregivers value treatment tradeoffs for HL. In an era of multiple treatment choices with varying short- and long-term benefits and harms, identifying values and preferences become critical for patient-centered treatment decisions.

Are Pakistani homebuyers ready to adopt sustainable housing? An insight into their willingness to pay

The supply side of sustainable housing needs to be complemented with, driven by, and shaped around a willing and committed demand site. This study examines the sustainable housing sector of Pakistan by describing the potential buyers’ profile and quantifying their willingness to pay (WTP) for sustainable housing uptake in the market. WTP is estimated through a survey of 354 potential homebuyers. Furthermore, the hierarchical Bayesian model of adaptive choice-based conjoint analysis is utilized to study the correlation of descriptive determinants on WTP for sustainable housing. The results suggest that demographical factors of age, gender, and literacy level positively correlate with WTP whereas environmental knowledge and income level negatively correlate with WTP. Also, energy saving has the highest relative importance among other housing attributes. The study contributes a vital empirical input to the literature by finding the potential sustainable homebuyers in Pakistan and their characteristics and proposes several policy guidelines to promote the uptake of the sustainable housing sector in the country.

Abstract P1-17-08: Patient preferences: Results of a German adaptive choice-based conjoint analysis study in patients on palliative treatment for advanced breast cancer (aBC)

Abstract Objective: This study aimed to identify patient preferences in aBC related to cancer treatment characteristics, i.e. to determine the relevance of gained lifetime (OS) and time to progression (PFS) in relation to quality of life (QoL) and therapy-associated side effects. Methods: Post-menopausal women with HR+/HER2-aBC receiving 1st or 2nd line treatment were recruited throughout Germany. Patient relevant attributes to assess aBC therapies were collected in a stepwise multi-methodological approach, consisting of desk research, qualitative interviews with patients (n=12), caregivers (n=3) and aBC treating physicians (n=2) and iterative reviews of the empirical findings in a cross-functional team. A draft conjoint matrix was developed which was refined by means of two pre-tests with aBC patients (n=9). The final conjoint matrix consisted of two attributes for therapy goals (OS and PFS), four for QoL and six for side effects. It represented the basis of the subsequent quantitative survey using adaptive choice-based conjoint methodology. Results: In the qualitative phase, QoL emerged as a multidimensional concept, consisting of several factors such as ability to lead a ‘normal’ life, physical capability to do things like before, mobility, carefreeness (not continuously be reminded of the disease), having goals and being able to go for them, and spend quality time with family and friends. Factors limiting QoL were symptom burden, medical controls and side effects, which were considered particularly disturbing if long-lasting, affecting everyday life and when effective management was not available. The quantitative sample consisted of 104 patients (67% 50-64 yrs/33% &amp;gt;65 yrs). Time from aBC diagnosis to survey participation was ≤5 years and &amp;gt;5 years in 50% of patients each. At the time of the survey, 67 patients (64.4%) were receiving 1st line and 37 (35.6%) 2nd line treatment, i.e. regular oral intake in 80%, regular injections in 29% and regular infusions in 15% of patients; the start of the current treatment was ≤1 year in 43% and &amp;gt;1 year in 57% of patients. QoL parameters (physical mobility and flexibility) received the highest value (19.4%), followed by treatment goals (OS 15.2%, PFS 14.4%). Therapy-related side effects turned out to be less important overall with nausea/vomiting being the most relevant side effect (9.3%), followed by infection risk (6.4%), diarrhea (2.9%) and mucosal dryness (1.2%). No significant differences were found between 1st and 2nd line patients. A relation between having experienced a side effect in the past and a desire to avoid it was identified for nausea, vomiting, and dry mucosa. There was no relation between the desire to avoid a side effect and its severity in the past. McFadden pseudo R2 (0.805), Root-Likelihood (0.864) and Chi-square test (2809.041, highly significant (p&amp;lt;0.0001)) demonstrated excellent statistical quality. Conclusions: This study indicated that QoL, PFS and OS are major drivers for therapy selection. Maximizing lifetime may be not an absolute goal and only desirable if no major loss of QoL occurs. Avoiding specific side effects was less relevant than maintaining QoL Citation Format: Mattea Reinisch, Norbert Marschner, Thorsten Otto, Agnieszka Korfel, Clemens Stoffregen, Achim Wöckel. Patient preferences: Results of a German adaptive choice-based conjoint analysis study in patients on palliative treatment for advanced breast cancer (aBC) [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-17-08.

Consumer insights on prepackaged Cheddar cheese shreds using focus groups, conjoint analysis, and qualitative multivariate analysis

This study established attractive attributes and drivers of purchase for prepackaged Cheddar cheese shreds. Seven focus groups of Cheddar cheese shred consumers (n = 61) were conducted to probe consumer beliefs regarding packaging, ingredients, label claims, and applications of prepackaged Cheddar cheese shreds. Subsequently, an online survey was developed utilizing the key attributes from the focus groups. The survey (n = 1,288) included maximum difference scaling, Kano questions, and adaptive choice-based conjoint analysis. Additionally, 9 different commercial Cheddar cheese shreds varying in color, shred thickness, brand, and price were selected for a follow-up qualitative multivariate analysis to gain further consumer insight on attribute importance. Consumers (n = 13) were provided with commercial packages of shreds to evaluate over a 4-week period. Consumers journaled their likes and dislikes after use of each cheese shred and subsequently participated in a final 2.5-h focus group and projective mapping exercise. Consumers placed highest importance on price, followed by nutrition claims, color, sharpness, thickness, and label claims. Four consumer clusters were identified from conjoint utility scores. One consumer cluster exhibited preference for value-added features such as nutrition claims and brand, and another consumer cluster placed importance on shred color, whereas the other 2 groups were driven primarily by price. The qualitative multivariate analysis results confirmed the focus group and survey results: meltability, orange color, lack of clumps, ability to reseal the bag, and desirable "Cheddar" flavor were also preferred Cheddar shred qualities.

Quantifying the value teachers place on non-monetary factors when evaluating job opportunities

The way in which working conditions, personal characteristics, and school factors influence teacher recruitment and retention is an oft-studied topic in the field of education finance and policy. Through decades of research, it has become increasingly clear that teachers respond to a set of monetary and non-monetary factors when making decisions in the teacher labor market. What is less clear is the relative or absolute value teachers place on factors such as salary, student demographic factors, school conditions, and other working conditions such as class size, curricular autonomy, and principal support, to name a few. This project introduces the use of a novel survey methodology to the field to aim to answer these questions. This study utilizes Adaptive Choice-Based Conjoint (ACBC) analysis to quantify the relative importance of various monetary and non-monetary job factors to practicing teachers as they consider the desirability of various hypothetical schools. The use of ACBC in an estimate of the value placed on various working condition factors by secondary teachers in Utah and an analysis of how those valuations vary with personal and demographic factors. The results of this research provide practical recommendations for administrators and policymakers that aim to make schools more desirable for teachers and demonstrates the use of a novel methodology to answer outstanding questions in the field of teacher recruitment and retention.

Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis

In “Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis,” D. Saure and J. P. Vielma study adaptive questionnaire design for choice-based conjoint analysis, a popular survey-based prefer...

Academic Success is in the Eye of the Beholder: Appointment Preferences in Higher Education

Because scholarly performance is multidimensional, many different criteria may influence appointment decisions. Previous studies on appointment preferences do not reveal how appointment committee members consider and weigh up different criteria when they evaluate candidates. We used adaptive choice-based conjoint analysis to identify scholars’ implicit appointment preferences. Junior and senior scholars (N = 721) from different scientific fields and countries took part in a hypothetical appointment procedure. In contrast to previous studies, we found that the criterion ‘acquired grants’ strongly influences scholars’ decisions. Multiple regressions showed how several factors contribute to differences in appointment preferences. Scholars from the U.S., for example, attach less importance to grants and international orientation and more importance to number of publications than scholars from other countries. Furthermore, we provide evidence for homophily effects, that is, scholars prefer candidates who are s...

Investigating the segment specific preferences for hedonic and utilitarian online-shop characteristics: the case of German online wine shops

Recently the market for grocery online-shopping is expanding. Therefore, this study analyse the influencing factors of online shoppers' preferences for online wine shops with an adaptive choice-based conjoint analysis (ACBC). As these factors in general differ for hedonic and utilitarian goods, we investigated what characteristics presented in the online-shop are most important to customers of a primarily hedonic product like wine. Surprisingly, respondents in general favoured utilitarian over hedonic characteristic levels. In addition, we identified two distinct customer groups by applying a preference-based market segmentation (CCEA). The price/efficiency-seeking group favoured utilitarian characteristics. The quality-seeking group favoured hedonic over utilitarian characteristics, but with a strong importance of some utilitarian website characteristics. Finally management implications are presented.

Patient preferences for the pharmacological treatment of osteoarthritis using adaptive choice-based conjoint (ACBC) analysis: A pilot study

Background: Patient preferences for pharmaceutical treatment of osteoarthritis have been investigated using Conjoint Analysis. Studies have identified the importance of side effects in determining preferences, but noted that methodological limitations precluded further investigation of additional attributes such as hepatic and renal toxicity.Objective: Following on from a feasibility study of adaptive choice-based conjoint (ACBC) analysis, the aim of this study was to evaluate 8 medication attributes for the pharmaceutical treatment of osteoarthritis (OA).Setting and Participants: Eleven participants were recruited from members of a Research Users’ Group (RUG) who had been diagnosed with osteoarthritis. RUG members individually complete the ACBC task. Main outcome measures: The relative importance of each attribute and the utilities (part-worth) of each level of each attribute were estimated using ACBC built-in Hierarchical Bayes (HB).Results: The combined relative importance of the 4 risk side-effect attributes when selecting osteoarthritis medication (kidney and liver side effects, heart attack and stroke side effects, stomach side effects and addiction) was 66% while the effectiveness attribute accounted for 8% of the relative importance of the medication decision.Conclusions: In this study, the gap between relative importance of 4 side-effect attributes and expected benefit was 66% vs 8%. These preliminary findings indicate that OA patients are most concerned with the avoidance of adverse events and that there is a threshold above which expected benefit has little impact on patients’ medication preferences. The study highlights methodological features of ACBC that may be useful more generally in health services research, but the results must be interpreted in conjunction with the study limitations.

Generating Individual Patient Preferences for the Treatment of Osteoarthritis Using Adaptive Choice-Based Conjoint (ACBC) Analysis.

IntroductionTo explore how adaptive choice-based conjoint (ACBC) analysis could contribute to shared decision-making in the treatment of individual patients with osteoarthritis (OA).MethodsIn-depth case study of three individuals randomly selected from patients with OA participating in an ACBC analysis exercise. Eleven members of a research users’ group participated in developing an ACBC task on medication preferences for OA. Individual medication priorities are illustrated by the detailed analysis of ACBC output from three randomly selected patients from the main sample.ResultsThe case study analysis illustrates individual preferences. Participant 1’s priority was avoidance of the four high-risk side effects of medication, which accounted for 90% of the importance of all attributes, while the remaining attributes (expected benefit; way of taking medication; frequency; availability) accounted only for 10% of the total influence. Participant 3 was similar to participant 1 but would accept a high risk of one of the side effects if the medication were available by prescription. In contrast, participant 2’s priority was the avoidance of Internet purchase of medication; this attribute (availability) accounted for 52% of the importance of all attributes.ConclusionsIndividual patients have preferences that likely lead to different medication choices. ACBC has the potential as a tool for physicians to identify individual patient preferences as a practical basis for concordant prescribing for OA in clinical practice. Future research needs to establish whether accurate knowledge of individual patient preferences for treatment attributes and levels translates into concordant behavior in clinical practice.

PATIENT PREFERENCES FOR THE PHARMACOLOGICAL TREATMENT OF OSTEOARTHRITIS: A FEASIBILITY STUDY USING ADAPTIVE CHOICE-BASED CONJOINT ANALYSIS (ACBCA)

Rationale, aims and objectives Patient preferences are an important part of optimizing the pharmacological treatment of osteoarthritis (OA). Recent choice experiments have explored this issue using two types of conjoint analysis: choice-based conjoint analysis (CBCA) and adaptive conjoint analysis (ACA). The aim of this study was to examine the feasibility of using adaptive choice-based conjoint analysis (ACBCA) methods to determine patient preferences for pharmacological treatment of OA. The specific outcomes were patient evaluations of a) eight attributes in an ACBCA task, b) the computer skills required to complete the task, and c) the perceived utility of the results. Method Participants were drawn from members of a Research Users’ Group (RUG) who had been diagnosed with osteoarthritis. Participants took part in two feasibility studies. In the first feasibility study, four RUG members critically examined the implementation of a computerized ACBCA task. In the second feasibility study, 11 RUG members completed an ACBCA task on medication preferences for osteoarthritis. The ACBCA task was evaluated by a set of self-completed questions and through semi-structured interviews. ResultsThe first feasibility study helped to shape the design and contents of the ACBCA task. In the second feasibility study, no participants reported the ACBCA task to be hard to read or understand. Most participants agreed that the task was adjusting appropriately as the session proceeded and that it helped them in making decisions about preferences. Older patients and patients with little computer experience appeared to find no substantial challenges in using this interactive computer-based technique. ConclusionsThese studies indicate that, with the involvement of patients, face and content validity of an ACBCA task can be achieved through a developmental process taking account of participants’ requirements.

Evaluating the Military Retirement System: An Adaptive Choice-Based Conjoint Analysis Approach

As the U.S. Government moves into an era of fiscal responsibility, addressing national spending goes hand-in-hand with addressing the specific programs in place that accrue the greatest costs in the future. Reducing these expenses is paramount in dealing with the budget strategy and finding the means to make programs more efficient should be the forward focus. From the realm of National Defense, the Military Retirement System is a growing expenditure that threatens both current and future benefits for the Service Member it is designed to service. The issue is sensitive in that its stakeholders encompass the men and women of the U.S. Armed Forces, but simultaneously the growing costs threaten the strategic defense of the United States. This study looks to address the inefficiencies of the current Military Retirement System by evaluating which attributes of the retirement plan that the Service Member finds most attractive. Using Adaptive Choice-Based Conjoint Analysis a resourceful, unadorned surveying technique to evaluate the potential military retiree, this study demonstrates an effective methodology at evaluating consumer (the Service Member) preferences and provides an examination of potential policy changes to combat the growing financial dilemma.

Adaptive Hybrid Methods for Choice-Based Conjoint Analysis: A Comparative Study

Adaptive choice-based conjoint analysis (ACBC) and hybrid individualized two-level choice-based conjoint analysis (HIT-CBC) were developed to improve standard choice-based conjoint analysis through additional interviewing techniques. Both methods have demonstrated their applicability in comparison to standard choice-based conjoint methods. The objective of our study was a direct comparison of the two adaptive hybrid methods ACBC and HIT-CBC. Therefore, we analysed the previous comparative literature on the methods and used the results to conduct both a Monte Carlo simulation study and an empirical study for validity comparisons. The simulation study confirms the vulnerability of HIT-CBC to produce incorrect ratings of respondents in the last part of the questionnaire. The empirical findings reveal an advantage of ACBC in comparison to the current version of HIT-CBC. We conclude that the rating tasks in the last section of HIT-CBC questionnaires reduce the predictive validity of the method and suggest an improvement to HIT-CBC.

User Acceptance and Willingness to Pay for Connected Vehicle Technologies: Adaptive Choice-Based Conjoint Analysis

The preferences of drivers and their willingness to pay (WTP) for connected vehicle (CV) technologies were estimated with the use of adaptive choice-based conjoint (ACBC) analysis, the newest such method available. More than 500 usable surveys were collected through an online survey. Respondents were asked to choose from variously priced CV technology bundles (e.g., collision prevention, roadway information system). The study found that the acceptance level of the CV technologies was high, given that an absolute majority of survey respondents had the highest preferences for the most comprehensive technology bundle in each attribute. However, a comparison of the average importance of each attribute, including bundle prices, implied that price would be an important constraint and would influence CV deployment rates. At the attribute level, collision prevention technology received the highest importance score (i.e., the safety benefits most appealed to drivers). The ACBC analysis seemed to mimic well the trade-offs that people would consider in their actual purchasing decisions. The difference between WTP and self-explicated prices obtained before preferences were estimated was statistically significant (i.e., participants chose bundles after they considered product attributes and prices). This finding also affirmed that the ACBC analysis was a more appropriate method than the direct questioning methods used in past studies. Finally, certain socioeconomic characteristics were positively related to WTP. Those respondents that were knowledgeable about CV technologies and showed more innovativeness had higher WTP as well.

Modeling the anti-cyberbullying preferences of university students: Adaptive choice-based conjoint analysis.

Adaptive choice-based conjoint analysis was used to study the anti-cyberbullying program preferences of 1,004 university students. More than 60% reported involvement in cyberbullying as witnesses (45.7%), victims (5.7%), perpetrator-victims (4.9%), or perpetrators (4.5%). Men were more likely to report involvement as perpetrators and perpetrator-victims than were women. Students recommended advertisements featuring famous people who emphasized the impact of cyberbullying on victims. They preferred a comprehensive approach teaching skills to prevent cyberbullying, encouraging students to report incidents, enabling anonymous online reporting, and terminating the internet privileges of students involved as perpetrators. Those who cyberbully were least likely, and victims of cyberbullying were most likely, to support an approach combining prevention and consequences. Simulations introducing mandatory reporting, suspensions, or police charges predicted a substantial reduction in the support of uninvolved students, witnesses, victims, and perpetrators.

Clinical factors and the decision to transfuse chronic dialysis patients.

Red blood cell transfusion was previously the principle therapy for anemia in CKD but became less prevalent after the introduction of erythropoiesis-stimulating agents. This study used adaptive choice-based conjoint analysis to identify preferences and predictors of transfusion decision-making in CKD. A computerized adaptive choice-based conjoint survey was administered between June and August of 2012 to nephrologists, internists, and hospitalists listed in the American Medical Association Masterfile. The survey quantified the relative importance of 10 patient attributes, including hemoglobin levels, age, occult blood in stool, severity of illness, eligibility for transplant, iron indices, erythropoiesis-stimulating agents, cardiovascular disease, and functional status. Triggers of transfusions in common dialysis scenarios were studied, and based on adaptive choice-based conjoint-derived preferences, relative importance by performing multivariable regression to identify predictors of transfusion preferences was assessed. A total of 350 providers completed the survey (n=305 nephrologists; mean age=46 years; 21% women). Of 10 attributes assessed, absolute hemoglobin level was the most important driver of transfusions, accounting for 29% of decision-making, followed by functional status (16%) and cardiovascular comorbidities (12%); 92% of providers transfused when hemoglobin was 7.5 g/dl, independent of other factors. In multivariable regression, Veterans Administration providers were more likely to transfuse at 8.0 g/dl (odds ratio, 5.9; 95% confidence interval, 1.9 to 18.4). Although transplant eligibility explained only 5% of decision-making, nephrologists were five times more likely to value it as important compared with non-nephrologists (odds ratio, 5.2; 95% confidence interval, 2.4 to 11.1). Adaptive choice-based conjoint analysis was useful in predicting influences on transfusion decisions. Hemoglobin level, functional status, and cardiovascular comorbidities most strongly influenced transfusion decision-making, but preference variations were observed among subgroups.