[This corrects the article DOI: 10.3389/fpsyg.2022.1000043.].

Forest Ecosystem Services (FES) are widely recognised by the society nowadays. However, no study in the literature has analysed a ranking of FES after the pandemic. This paper investigated civil society\'s perception and knowledge toward these services; in addition, the presence of attitudinal or behavioural patterns regarding individual\'s preference, was assessed. A choice experiment was conducted using the Best-Worst Scaling (BWS) method on a sample of 479 individuals intercepted in the Argentera Valley, in the Western Italian Alps. Results, showed a strong interest in biodiversity, aesthetic landscape quality and psychophysical health and a lower interest in provisioning services. Based on the individual preferences, civil society was clustered into five groups for FES, named \"Hedonistic,\" \"Individualist with cultural and health interests,\" \"Sensitive to regulatory and utilitarian functions,\" \"Climate change sensitive\" and \"Livelihood and hedonistic wellbeing.\" In general, there was a growing appreciation by civil society for the intangible services offered by the forest, driven by modern lifestyles and an interest in learning more about the provided services. Based on these elements, we believe that similar research should be extended to other mountain contexts to validate the results or to find new insights, and that it is now necessary to study how to involve civil society in decision-making processes of forest planning and management at a local level.

This research empirically examines the preferences for job-related attributes among rural villagers living close to artisanal and small-scale gold mining (ASGM) in Indonesia. Based on hypothetical scenarios in which a private company collaborates with the local government to establish a food processing industry in these villages, a questionnaire survey designed with best-worst scaling (BWS) was administered to households to determine their preferences. Additionally, the heterogeneity among the villagers was examined by applying a latent class logit (LCL) model. The main household survey was conducted in 2019 in Bone Bolango Regency, Gorontalo Province. The estimation results revealed that villagers are separated into four classes, and each class has different and unique preferences. Creating more job opportunities for society is a highly evaluated attribute; however, the preference for skill acquisition differs among groups. The results indicate that accounting for heterogeneous preferences regarding job opportunities is helpful to delink dependency on ASGM and health hazards and improve the livelihoods of rural villagers. The study yields key information to substantially reduce environmental and health hazards in the poverty-plagued ASGM community by facilitating job opportunities in Indonesia.

Vesicoureteral reflux is a common pediatric urologic condition that often has several reasonable treatment options depending on condition severity. In order to choose the best treatment for their child, parents are expected to make judgements that weigh attributes such as treatment cost, effectiveness, and complication rate. Prior research has shown that factors such as treating hospital and surgeon also influence patient treatment choice.
This study evaluates parental preferences for reflux treatment using profile case best-worst scaling, an emerging technique in both urologic and health care preference estimation. The study also uses latent class analysis (LCA) to identify parental sub-classes with different preferences.
Data were collected from a community sample of parents via a multimedia best-worst scaling survey instrument published to Amazon\'s Mechanical Turk online community. After extensive review of the literature, reflux attributes and attribute levels were selected to correspond with available treatments. The profile case best-worst scaling exercise elicited preferences for granular attributes of reflux treatments. Data were analyzed using multinomial logistic regression and class analysis to distinguish preference heterogeneity. Probability scaled values (PSVs) reflected the order of desirability of the attributes. Attribute preference importance was rescaled into dollar units for comparison as well.
We analyzed data for 248 respondents. The highest treatment effectiveness was more desirable than all other leveled treatment attributes (PSV 17.8, all p < 0.01) (Table). Low complication rate and doctor recommendation were amongst the other most desirable treatment attributes (PSV 11.3 and 9.0, respectively). Latent class analysis identified a class with more extreme preferences, for whom doctor recommendation and avoiding hospitalization were particularly desirable.
In this community-based sample, high treatment effectiveness and low complication rate were the most desirable treatment attributes to parents, though parents likely have heterogenous treatment preference structures. Shared parent-physician decision-making that incorporates parental preferences will likely allow more effective, targeted decision-making in the future.

Best-worst scaling (BWS) is a survey method for assessing individuals\' priorities. It identifies the extremes-best and worst items, most and least important factors, biggest and smallest influences-among sets. In this article, we demonstrate an application of BWS in a primary care setting to illustrate its use in identifying patient priorities for services.
We conducted a BWS survey in 2014 in Boston, Massachusetts, to assess the relative importance of 10 previously identified attributes of Papanicolaou (Pap) testing services among women experiencing homelessness. Women were asked to evaluate 11 sets of 5 attributes of Pap services, and identify which attribute among each set would have the biggest and smallest influence on promoting uptake. We show how frequency analysis can be used to analyze results.
In all, 165 women participated, a response rate of 72%. We identified the most and least salient influences on encouraging Pap screening based on their frequency of report among our sample, with possible standardized scores ranging from+1.0 (biggest influence) to -1.0 (smallest influence). Most important was the availability of support for issues beyond health (+0.39), while least important was the availability of accommodations for personal hygiene (-0.27).
BWS quantifies patient priorities in a manner that is transparent and accessible. It is easily comprehendible by patients and relatively easy to administer. Our application illustrates its use in a vulnerable population, showing that factors beyond those typically provided in health care settings are highly important to women in seeking Pap screening. This approach can be applied to other health care services where prioritization is helpful to guide decisions.

The main objective of this study was to compare and contrast adolescent and adult values for the Child Health Utility-9D (CHU9D), a new generic preference-based measure of health-related quality of life designed for application in the economic evaluation of treatment and preventive programmes for children and adolescents. Previous studies have indicated that there may be systematic differences in adolescent and adult values for identical health states. An online survey including a series of best-worst scaling discrete choice experiment questions for health states defined by the CHU9D was administered to two general population samples comprising adults and adolescents, respectively. The results highlight potentially important age-related differences in the values attached to CHU9D dimensions. Adults, in general, placed less weight upon impairments in mental health (worried, sad, annoyed) and more weight upon moderate to severe levels of pain relative to adolescents. The source of values (adults or adolescents) has important implications for economic evaluation and may impact significantly upon healthcare policy.

Ethical, economic, political, and legitimacy arguments support the consideration of public preferences in health technology decision making. The objective was to assess public preferences for funding new health technologies and to compare a profile case best-worst scaling (BWS) and traditional discrete choice experiment (DCE) method.
An online survey consisting of a DCE and BWS task was completed by 930 adults recruited via an Internet panel. Respondents traded between 7 technology attributes. Participation quotas broadly reflected the population of Queensland, Australia, by gender and age. Choice data were analyzed using a generalized multinomial logit model.
The findings from both the BWS and DCE were generally consistent in that respondents exhibited stronger preferences for technologies offering prevention or early diagnosis over other benefit types. Respondents also prioritized technologies that benefit younger people, larger numbers of people, those in rural areas, or indigenous Australians; that provide value for money; that have no available alternative; or that upgrade an existing technology. However, the relative preference weights and consequent preference orderings differed between the DCE and BWS models. Further, poor correlation between the DCE and BWS weights was observed. While only a minority of respondents reported difficulty completing either task (22.2% DCE, 31.9% BWS), the majority (72.6%) preferred the DCE over BWS task.
This study provides reassurance that many criteria routinely used for technology decision making are considered to be relevant by the public. The findings clearly indicate the perceived importance of prevention and early diagnosis. The dissimilarity observed between DCE and profile case BWS weights is contrary to the findings of previous comparisons and raises uncertainty regarding the comparative merits of these stated preference methods in a priority-setting context.