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How low is the ideal first offer? Prior to any negotiation, decision-makers must balance a crucial tradeoff between two opposing effects. While lower first offers benefit buyers by anchoring the price in their favor, an overly ambitious offer increases the impasse risk, thus potentially precluding an agreement altogether. Past research with simulated laboratory or classroom exercises has demonstrated either a first offer's anchoring benefits or its impasse risk detriments, while largely ignoring the other effect. In short, there is no empirical answer to the conundrum of how low an ideal first offer should be. Our results from over 26 million incentivized real-world negotiations on eBay document (a) a linear anchoring effect of buyer offers on sales price, (b) a nonlinear, quartic effect on impasse risk, and (c) specific offer values with particularly low impasse risks but high anchoring benefits. Integrating these findings suggests that the ideal buyer offer lies at 80% of the seller's list price across all products--although this value ranges from 33% to 95% depending on the type of product, demand, and buyers' weighting of price versus impasse risk. We empirically amend the well-known midpoint bias, the assumption that buyer and seller eventually meet in the middle of their opening offers, and find evidence for a "buyer bias." Product demand moderates the (non)linear effects, the ideal buyer offer, and the buyer bias. Finally, we apply machine learning analyses to predict impasses and present a website with customizable first-offer advice configured to different products, prices, and buyers' risk preferences. [ABSTRACT FROM AUTHOR]

Digital guided self-help for eating disorders (GSH-ED) can reduce treatment disparities. Understanding program participants' interests throughout the program can help adapt programs to the service users' needs. Participants were 383 college students receiving a digital GSH-ED, who were each assigned a coach to help them better utilize the intervention through text correspondence. A thematic and affective analysis of the texts participants had sent found they primarily focused on: strategies for changing their ED-related cognitions, behaviors, and relationships; describing symptoms without expressing an active endeavor to change; and participants' relationship with their coach. Most texts also expressed affect, demonstrating emotional engagement with the intervention. Findings suggest that participants in GSH-ED demonstrate high involvement with the intervention, and discuss topics that are similar to those reported in clinician-facilitated interventions. The themes discussed by digital program participants can inform future iterations of GSH-ED, thereby increasing scalability and accessibility of digital evidence-based ED interventions. [ABSTRACT FROM AUTHOR]

While autonomous driving technology made significant progress in the last decade, road damage detection as a relevant challenge for ensuring safety and comfort is still under development. This paper addresses the lack of algorithms for detecting road damages that meet autonomous driving systems' requirements. We investigate the environmental perception systems' architecture and current algorithm designs for road damage detection. Based on the autonomous driving architecture, we develop an end-to-end concept that leverages data from low-cost pre-installed sensors for real-time road damage and damage severity detection as well as cloud- and crowd-based HD Feature Maps to share information across vehicles. In a design science research approach, we develop three artifacts in three iterations of expert workshops and design cycles: the end-to-end concept featuring road damages in the system architecture and two lightweight deep neural networks, one for detecting road damages and another for detecting their severity as the central components of the system. The research design draws on new self-labeled automotive-grade images from front-facing cameras in the vehicle and interdisciplinary literature regarding autonomous driving architecture and the design of deep neural networks. The road damage detection algorithm delivers cutting-edge performance while being lightweight compared to the winners of the IEEE Global Road Damage Detection Challenge 2020, which makes it applicable in autonomous vehicles. The road damage severity algorithm is a promising approach, delivering superior results compared to a baseline model. The end-to-end concept is developed and evaluated with experts of the autonomous driving application domain. [ABSTRACT FROM AUTHOR]

Objective: Scaling an online screen that provides referrals may be key in closing the treatment gap for eating disorders (EDs), but we need to understand respondents' help‐seeking intentions and behaviors after receiving screen results. This study reported on these constructs among respondents to the National Eating Disorders Association online screen who screened positive or at high risk for an ED. Method: Respondents completed the screen over 18 months (February 9, 2018–August 28, 2019). Those screening positive or at high risk for an ED (n = 343,072) had the option to provide data on help‐seeking intentions (after screen completion) and behaviors (2‐month follow‐up). Results: Of eligible respondents, 4.8% (n = 16,396) provided data on help‐seeking intentions, with only 33.7% of those reporting they would seek help. Only 7.6% of eligible respondents opted in to the 2‐month follow‐up, with 10.6% of those completing it (n = 2,765). Overall, 8.9% of respondents to the follow‐up reported being in treatment when they took the screen, 15.5% subsequently initiated treatment, and 75.5% did not initiate/were not already in treatment. Discussion: Preliminary results suggest that among the small minority who provided data, only one‐third expressed help‐seeking intentions and 16% initiated treatment. Online screening should consider ways to increase respondents' motivation for and follow‐through with care. [ABSTRACT FROM AUTHOR]

In recent years, online screens have been commonly used to identify individuals who may have eating disorders (EDs), many of whom may be interested in treatment. We describe a new empirical approach that takes advantage of current evidence on empirically supported, effective treatments, while at the same time, uses modern statistical frameworks and experimental designs, data‐driven science, and user‐centered design methods to study ways to expand the reach of programs, enhance our understanding of what works for whom, and improve outcomes, overall and in subpopulations. The research would focus on individuals with EDs identified through screening and would use continuously monitored data, and interactions of interventions/approaches to optimize reach, uptake, engagement, and outcome. Outcome would be assessed at the population, rather than individual level. The idea worth researching is to determine if an optimization outcome model produces significantly higher rates of clinical improvement at a population level than do current approaches, in which traditional interventions are only offered to the few people who are interested in and able to access them. [ABSTRACT FROM AUTHOR]

Objective: The treatment gap between those who need and those who receive care for eating disorders is wide. Scaling a validated, online screener that makes individuals aware of the significance of their symptoms/behaviors is a crucial first step for increasing access to care. The objective of the current study was to determine the reach of disseminating an online eating disorder screener in partnership with the National Eating Disorders Association (NEDA), as well to examine the probable eating disorder diagnostic and risk breakdown of adult respondents. We also assessed receipt of any treatment. Method: Participants completed a validated eating disorder screen on the NEDA website over 6 months in 2017. Results: Of 71,362 respondents, 91.0% were female, 57.7% 18–24 years, 89.6% non‐Hispanic, and 84.7% White. Most (86.3%) screened positive for an eating disorder. In addition, 10.2% screened as high risk for the development of an eating disorder, and only 3.4% as not at risk. Of those screening positive for an eating disorder, 85.9% had never received treatment and only 3.0% were currently in treatment. Discussion: The NEDA online screen may represent an important eating disorder detection tool, as it was completed by >71,000 adult respondents over just 6 months, the majority of whom screened positive for a clinical/subclinical eating disorder. The extremely high percentage of individuals screening positive for an eating disorder who reported not being in treatment suggests a wide treatment gap and the need to offer accessible, affordable, evidence‐based intervention options, directly linked with screening. [ABSTRACT FROM AUTHOR]

Background: Recently, internet-based interventions have been proposed as effective treatments for people with panic disorder (PD). However, little is known about the clinical effects of integrating mobile technology into these interventions. Because users carry their smartphones with them throughout the day, we hypothesize that this technology can be used to significantly support individuals with monitoring and overcoming their PD symptoms. The aim of the present study is to evaluate the efficacy and cost-effectiveness of a newly developed hybrid intervention that combines internet/PC with smartphone delivery to treat the symptoms of PD. The intervention is based on cognitive behavioral therapy and consists of six modules over a total of six weeks. Methods/Design: A two-arm randomized controlled trial (RCT) will be conducted to evaluate the effects of a hybrid online training module for PD. Based on a power calculation (d =0.60; 1-β of 80%; α =0.05), 90 participants with mild to moderate panic symptoms with or without agoraphobia (as assessed by the Panic and Agoraphobia Scale) will be recruited from the general population and randomly assigned to either the intervention group or a six-month waitlist control group. The primary outcome measure will be the severity of panic symptoms. Secondary outcomes will include depression, quality of life, and an observer-based rating of panic severity. Furthermore, data regarding acceptance and the usability of the smartphone app will be assessed. Assessments will take place at baseline as well as eight weeks, three months, and six months after randomization. Moreover, a cost-effectiveness analysis will be performed from a societal perspective. Data will be analyzed on an intention-to-treat basis and per protocol. Discussion: To our knowledge, this RCT is one of the first to examine the efficacy of a hybrid online training for adult PD. This study seeks to contribute to the emerging field of hybrid online training. If the intervention is efficacious, then research on this hybrid online training should be extended. The cost-effectiveness analysis will also indicate whether online training is an economical tool for treating PD among adults. [ABSTRACT FROM AUTHOR]

Background: Recently, internet-based interventions have been proposed as effective treatments for people with panic disorder (PD). However, little is known about the clinical effects of integrating mobile technology into these interventions. Because users carry their smartphones with them throughout the day, we hypothesize that this technology can be used to significantly support individuals with monitoring and overcoming their PD symptoms. The aim of the present study is to evaluate the efficacy and cost-effectiveness of a newly developed hybrid intervention that combines internet/PC with smartphone delivery to treat the symptoms of PD. The intervention is based on cognitive behavioral therapy and consists of six modules over a total of six weeks.Methods/design: A two-arm randomized controlled trial (RCT) will be conducted to evaluate the effects of a hybrid online training module for PD. Based on a power calculation (d =0.60; 1-β of 80%; α =0.05), 90 participants with mild to moderate panic symptoms with or without agoraphobia (as assessed by the Panic and Agoraphobia Scale) will be recruited from the general population and randomly assigned to either the intervention group or a six-month waitlist control group. The primary outcome measure will be the severity of panic symptoms. Secondary outcomes will include depression, quality of life, and an observer-based rating of panic severity. Furthermore, data regarding acceptance and the usability of the smartphone app will be assessed. Assessments will take place at baseline as well as eight weeks, three months, and six months after randomization. Moreover, a cost-effectiveness analysis will be performed from a societal perspective. Data will be analyzed on an intention-to-treat basis and per protocol.Discussion: To our knowledge, this RCT is one of the first to examine the efficacy of a hybrid online training for adult PD. This study seeks to contribute to the emerging field of hybrid online training. If the intervention is efficacious, then research on this hybrid online training should be extended. The cost-effectiveness analysis will also indicate whether online training is an economical tool for treating PD among adults.Trial Registration: German Clinical Trial Register: DRKS00005223 (registered on 15 August 2013). [ABSTRACT FROM AUTHOR]