Despite hospitality and tourism researchers’ recent attempts on examining different aspects of online word-of-mouth [WOM], its impact on hotel sales remains largely unknown in the existing literature. To fill this void, we conduct a study to empirically investigate the impact of online consumer-generated reviews on hotel room sales. Utilizing data collected from the largest travel website in China, we develop a fixed effect log-linear regression model to assess the influence of online reviews on the number of hotel room bookings. Our results indicate a significant relationship between online consumer reviews and business performance of hotels.

The impact of online user reviews on hotel room sales [Summary]

This article reviews the peer-reviewed literature addressing the healthcare information available on YouTube. Inclusion and exclusion criteria were determined, and the online databases PubMed and Web of Knowledge were searched using the search phrases: (1) YouTube* AND Health* and (2) YouTube* AND Healthcare*. In all, 18 articles were reviewed, with the results suggesting that (1) YouTube is increasingly being used as a platform for disseminating health information; (2) content and frame analysis were the primary techniques employed by researchers to analyze the characteristics of this information; (3) YouTube contains misleading information, primarily anecdotal, that contradicts the reference standards and the probability of a lay user finding such content is relatively high; (4) the retrieval of relevant videos is dependent on the search term used; and (5) videos from government organizations and professional associations contained trustworthy and high-quality information. YouTube is used as a medium for promoting unscientific therapies and drugs that are yet to be approved by the appropriate agencies and has the potential to change the beliefs of patients concerning controversial topics such as vaccinations. This review recognizes the need to design interventions to enable consumers to critically assimilate the information posted on YouTube with more authoritative information sources to make effective healthcare decisions.

https://journals.sagepub.com/doi/pdf/10.1177/1460458213512220

Healthcare information on YouTube: A systematic review

The COVID-19 pandemic: The ‘black swan’ for mental health care and a turning point for e-health

Cooperative adaptive cruise control (CACC) systems have the potential to increase traffic throughput by allowing smaller headway between vehicles and moving vehicles safely in a platoon at a harmonized speed. CACC systems have been attracting significant attention from both academia and industry since connectivity between vehicles will become mandatory for new vehicles in the USA in the near future. In this paper, we review three basic and important aspects of CACC systems: communications, driver characteristics, and controls to identify the most challenging issues for their real-world deployment. Different routing protocols that support the data communication requirements between vehicles in the CACC platoon are reviewed. Promising and suitable protocols are identified. Driver characteristics related issues, such as how to keep drivers engaged in driving tasks during CACC operations, are discussed. To achieve mass acceptance, the control design needs to depict real-world traffic variability such as communication effects, driver behavior, and traffic composition. Thus, this paper also discusses the issues that existing CACC control modules face when considering close to ideal driving conditions.

A Review of Communication, Driver Characteristics, and Controls Aspects of Cooperative Adaptive Cruise Control (CACC)

Importance The coronavirus disease 2019 (COVID-19) pandemic has required a shift in health care delivery platforms, necessitating a new reliance on telemedicine. Objective To evaluate whether inequities are present in telemedicine use and video visit use for telemedicine visits during the COVID-19 pandemic. Design, Setting, and Participants In this cohort study, a retrospective medical record review was conducted from March 16 to May 11, 2020, of all patients scheduled for telemedicine visits in primary care and specialty ambulatory clinics at a large academic health system. Age, race/ethnicity, sex, language, median household income, and insurance type were all identified from the electronic medical record. Main Outcomes and Measures A successfully completed telemedicine visit and video (vs telephone) visit for a telemedicine encounter. Multivariable models were used to assess the association between sociodemographic factors, including sex, race/ethnicity, socioeconomic status, and language, and the use of telemedicine visits, as well as video use specifically. Results A total of 148 402 unique patients (86 055 women [58.0%]; mean [SD] age, 56.5 [17.7] years) had scheduled telemedicine visits during the study period; 80 780 patients (54.4%) completed visits. Of 78 539 patients with completed visits in which visit modality was specified, 35 824 (45.6%) were conducted via video, whereas 42 715 (54.4%) had telephone visits. In multivariable models, older age (adjusted odds ratio [aOR], 0.85 [95% CI, 0.83-0.88] for those aged 55-64 years; aOR, 0.75 [95% CI, 0.72-0.78] for those aged 65-74 years; aOR, 0.67 [95% CI, 0.64-0.70] for those aged ≥75 years), Asian race (aOR, 0.69 [95% CI, 0.66-0.73]), non-English language as the patient’s preferred language (aOR, 0.84 [95% CI, 0.78-0.90]), and Medicaid insurance (aOR, 0.93 [95% CI, 0.89-0.97]) were independently associated with fewer completed telemedicine visits. Older age (aOR, 0.79 [95% CI, 0.76-0.82] for those aged 55-64 years; aOR, 0.78 [95% CI, 0.74-0.83] for those aged 65-74 years; aOR, 0.49 [95% CI, 0.46-0.53] for those aged ≥75 years), female sex (aOR, 0.92 [95% CI, 0.90-0.95]), Black race (aOR, 0.65 [95% CI, 0.62-0.68]), Latinx ethnicity (aOR, 0.90 [95% CI, 0.83-0.97]), and lower household income (aOR, 0.57 [95% CI, 0.54-0.60] for income Conclusions and Relevance In this cohort study of patients scheduled for primary care and medical specialty ambulatory telemedicine visits at a large academic health system during the early phase of the COVID-19 pandemic, older patients, Asian patients, and non–English-speaking patients had lower rates of telemedicine use, while older patients, female patients, Black, Latinx, and poorer patients had less video use. Inequities in accessing telemedicine care are present, which warrant further attention.

/pdf/patient-characteristics-associated-with-telemedicine-access-2j08qziwnm.pdf

Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic.

Background: One area where telemedicine may prove to be highly effective is in providing medical care to the geriatric population, an age group predicted to account for 20% of the population in the near future. However, even though telemedicine has certain advantages, the usability of these systems with this population merits investigation. Materials and Methods: This article reviews the literature published from 2000 to 2016 with the goal of analyzing the characteristics of usability-related studies conducted using geriatric participants and the subsequent usability challenges identified. Articles were found using Web of Knowledge and PubMed citation indexing portals using the keywords (1) Telemedicine* AND Geriatrics* (2) Telemedicine* AND Usability* (3) Telemedicine* AND Usability* AND Older Adults*. Results: A total of 297 articles were obtained from the initial search. After further detailed screening, 16 articles were selected for review based on the inclusion criteria. Of these, 60% of the...

Designing Telemedicine Systems for Geriatric Patients: A Review of the Usability Studies

A survey of automation-enabled human-in-the-loop systems for infrastructure visual inspection

Lessons learned from the usability assessment of home-based telemedicine systems.

Human-Robot Collaboration (HRC) on the factory floor has opened a new realm of manufacturing in real-world settings. In such applications, a human and robot work together with each other as coworkers while HRC plays a critical role in safety, productivity, and flexibility. In particular, human-robot trust determines his/her acceptance and hence allocation of autonomy to a robot, which alter the overall task efficiency and human workload. Inspired by well-known human factors research, we develop a time-series trust model for human-robot collaboration tasks, which is a function of prior trust, robot performance, and human performance. The robot performance is evaluated by its flexibility to keep pace with the human coworker and is molded as the difference between human and robot speed. The human performance in doing physical tasks is directly related to his/her muscle fatigue level. We use the muscle fatigue and recovery dynamics to capture the fatigue level of the human body when performing repetitive kinesthetic tasks, which are typical types of human motions in manufacturing. The robot speed can be controlled in three different modes: manually by the associate, autonomously through robust intelligence algorithms, or collaboratively by the combination of manual and autonomous inputs. We first simulate a typical 9-h work day for human robot collaborative tasks and implement the proposed trust model and the three control schemes. Furthermore, we experimentally validate our model and control schemes by conducting a series of human-in-the-loop experiments using the Rethink Robotics Baxter robot.

Kapil Chalil Madathil

Papers

Healthcare information on YouTube: A systematic review

Designing Telemedicine Systems for Geriatric Patients: A Review of the Usability Studies

A survey of automation-enabled human-in-the-loop systems for infrastructure visual inspection

Lessons learned from the usability assessment of home-based telemedicine systems.

Modeling and Control of Trust in Human-Robot Collaborative Manufacturing