The number of patient preference studies in health has increased dramatically. There is growing use of patient preferences in a wide variety of contexts, including health technology assessment. Patient preference studies can help inform decision makers on the needs and priorities of patients and the tradeoffs they are willing to make about health technologies.

This International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Task Force included international experts, health preference researchers and others from diverse backgrounds, including regulatory, health technology assessment, medicine, patient advocacy, and the pharmaceutical industry. The report underwent two rounds of written reviews by ISPOR Preferences Special Interest Group members until a final consensus was reached. The Task Force focused on developing a roadmap that would: (i) apply to the wide variety of preference methods, (ii) identify key domains to guide researchers and other stakeholders in making patient preference studies more useful to decision makers, and (iii) detail important questions to guide researchers conducting preference studies and those critically appraising them.

This Task Force report provides a novel roadmap that invites patient-preference researchers to work with decision makers, patients and other stakeholders to do even more to ensure that studies are useful and impactful. The ISPOR Roadmap consists of five key elements: (i) Context; (ii) Purpose; (iii) Population; (iv) Method; and (v) Impact. In this report, we define these five elements and provide good practices on how patient-preference researchers can actively contribute to increasing the usefulness and impact of patient preference studies in decision-making. We also present a set of key questions that can support researchers and other stakeholders in assessing efforts that promote preference studies’ intended and unintended impact.

This roadmap can help increase the usefulness and impact of patient preference studies in decision-making by challenging researchers to engage and partner with decision makers, patients and others, and together consider the intended and unintended impacts of patient preference studies on decision-making while actively fostering positive impact.

To assess convergent validity of stated preference methods in studies where they were used to elicit patient preferences for informing medical product decisions.

In four studies, two stated preference methods were used to elicit preferences of patients with neuromuscular diseases (NMD; n = 140, Discrete Choice Experiment [DCE] and Best-Worst Scaling [BWS] case 2), diabetes (n = 495, DCE and swing weighting [SW]), myocardial infarction (MI; n = 335, DCE and BWS case 1), and rheumatoid arthritis (RA; n = 982, DCE and probabilistic threshold technique [PTT]). In each study, results of the two methods were compared using a normalized preference measure for which confidence intervals (CIs) were estimated using nonparametric bootstrapping of 500 samples. Normalized preference measures comprised of mean relative attribute importance weights (NMD and diabetes studies), attribute uptake probability (MI study), or maximum acceptable risk (RA study).

In all four studies, attribute ranking showed similar patterns between DCE and other methods for the most important attributes. The same attribute had highest importance in three out of four studies. Significant differences were found in ranges of normalized preference measures of each study between DCE and the other methods: 4.1–43.4 versus 8.9–24.7 for DCE and BWS case 2 in NMD; 3.8–49.7 versus 11.9–16.8 for DCE and SW in diabetes; 2.0–85.5 versus 0.2–69.0 for DCE and BWS case 1 in MI; -3.5–49.2 versus 1.1–18.1 for DCE and PTT in RA.

Preferences differed significantly between DCE and other preference methods implying limited convergent validity. The substantially larger ranges in normalized outcome measures in DCE compared to other methods, are likely due to differences in mechanics and bias related to the methods. Since none of the methods is considered the golden standard for measuring stated preferences as true preferences are unknown, further studies are necessary to compare stated preference methods, determine internal validity and data quality, and potentially measure external validity.

To understand the importance of the preference methods criteria to stakeholders at each decision point in the Medical Product Lifecycle (MPLC) and to determine the suitability of commonly applied preference methods (Discrete Choice Experiment [DCE], swing weighting [SW], probabilistic threshold technique [PTT], Best-Worst Scaling case 1 [BWS1], Best-Worst Scaling case 2 [BWS2]) for a given decision-point.

Nineteen preference methods criteria of an existing performance matrix were incorporated in an online survey of industry, regulatory, and health technology assessment (HTA) stakeholders. All methods criteria were given a relative weight based on the SW ranking and point allocation task in the survey. Based on this relative weight and the performance matrix values, an overall suitability score was calculated for each method per critical decision point along the MPLC. Several sensitivity analyses were conducted for which the performance matrix was adapted.

In total 59 industry, 29 regulatory, and 5 HTA representatives completed the survey. In general, ‘estimating trade-offs between characteristics’, and ‘estimating weights for treatment characteristics’ were important preference method criteria throughout all MPLC decision points, while other preference method criteria were most important only for specific MPLC stages. Both BWS1 and BWS2 seem equally suitable across decision points, DCEs seem most suitable during clinical development and regulatory launch, and SW and PTT seem most suitable throughout industry decision points. Sensitivity analysis showed substantial impact of slight changes in the performance matrix.

With rapid changes in preference research, performance matrices of preference methods should continue to be re-evaluated as more and more evidence accumulates. While DCE is the most applied preference elicitation method, other methods should also be considered to address the needs of MPLC stakeholders. Development of evidence-based guidance documents for designing, conducting, and analyzing such methods could enhance their use.

Child welfare and juvenile justice placed youths show high levels of psychosocial burden and high rates of mental disorders. It remains unclear how mental disorders develop into adulthood in these populations. The aim was to present the rates of mental disorders in adolescence and adulthood in child welfare and juvenile justice samples and to examine their mental health trajectories from adolescence into adulthood.

Seventy adolescents in shared residential care, placed by child welfare (n = 52, mean age = 15 years) or juvenile justice (n = 18, mean age = 17 years) authorities, were followed up into adulthood (child welfare: mean age = 25 years; juvenile justice: mean age = 27 years). Mental disorders were assessed based on the International Classification of Diseases 10th Revision diagnoses at baseline and at follow-up. Epidemiological information on mental disorders was presented for each group. Bivariate correlations and structural equation modeling for the relationship of mental disorders were performed.

In the total sample, prevalence rates of 73% and 86% for any mental disorder were found in adolescence (child welfare: 70%; juvenile justice: 83%) and adulthood (child welfare: 83%; juvenile justice: 94%) respectively. General psychopathology was found to be stable from adolescence into adulthood in both samples.

Our findings showed high prevalence rates and a high stability of general psychopathology into adulthood among child welfare and juvenile justice adolescents in Swiss residential care. Therefore, continuity of mental health care and well-prepared transitions into adulthood for such individuals is highly warranted.

The use of psychoactive substances has been frequently associated with cognitive impairment. More and more people, including adolescents, use the plant hallucinogen beverage “ayahuasca” throughout the world. Long-term ayahuasca use by adolescents might eventually result in impaired cognitive performance.

The objective of this study is to assess neuropsychological performance of adolescents who consume ayahuasca within a religious ritual setting.

Forty ayahuasca consuming adolescents and forty adolescents who never used ayahuasca were compared on their performance on a battery of neuropsychological tests. Groups were matched by sex, age, and educational level.

Both groups performed well on all neuropsychological tests. However, there were differences between the groups. Controls outperformed subjects on more complex tests, that is, those requiring more cognitive functions to perform a specific task.

Adolescents who consume ayahuasca performed well on all the neuropsychological tests. However they did not perform as well as the control group whenever extra cognitive strength was required. It is possible that ayahuasca may have some subtle effect on cognition that can only be observed before highly demanding tasks. However, other variables may have interfered with these findings.