Phone Conversations Research Articles

Hearing aid benefit in daily life: a qualitative ecological momentary assessment study

IntroductionUnderstanding hearing aid wearer experiences in real-world settings is important to provide responsive and individualized hearing care. This study aimed to describe real-life benefits of hearing aids (HAs), as reported by hearing aid wearers through Ecological Momentary Assessment (EMA) in various listening environments.MethodQualitative content analysis of 1,209 open-text responses, provided through self-initiated EMAs, was conducted. The de-identified data was collected retrospectively via a smartphone app compatible with these HAs. Only text responses reflecting positive hearing aid experiences were analyzed. The 1,209 open-text responses were categorized into 18 pre-determined sub-categories, further organized into five overarching categories: Conversational, Leisure, Device-related aspects, Lifestyle, and Other factors.ResultsAcross these categories, 48 self-generated meaning units highlighted the multifaceted benefits of HAs. In particular, participants reported significant improvements in conversational settings, specifically during phone conversations and meetings, attributed to improved sound quality and speech understanding when wearing their HAs. During leisure activities, particularly TV watching and music listening, clearer sound and ease of Bluetooth streaming contributed to experienced benefits. Lifestyle improvements were reported in occupational and social settings, as hearing aid wearers stated enhanced communication and sound awareness. Device-related factors contributing to positive wearer experiences included extended battery life and the convenience of rechargeable batteries. The most prominent sub-category, other factors, underscored overall satisfaction, comfort with the device, and improved auditory experiences across various environments.ConclusionThis study reveals the diverse benefits of HAs in improving communication, listening experiences, and quality of life across various settings, as captured through EMA. By emphasizing features like direct streaming and rechargeability, the findings highlight the importance of personalized hearing care and the potential of real-time listener feedback to inform device enhancements and support strategies, advancing more tailored and effective hearing rehabilitation.

Two spies: Espionage and empathy

ABSTRACT This essay is a self-psychological exploration of two Israeli field operatives, or spies, and their radically different experiences after retirement. The spies, whom the author calls Ariel and Jonah, worked in the 1970s and 1980s in various locales in the Middle East. Ariel and Jonah shared similarities in their abilities as spies but diverged in the way they were able to integrate into society afterward. One went adrift, while the other integrated and was able to find his place in Israeli society. Based on in-person interviews when the author was living in Israel and subsequent visits and phone conversations, this paper explores the way empathy proved effective for Ariel and Jonah when they were working as spies in the field but functioned differently in their lives afterwards. It incorporates core self-psychological concepts such as rage, mirroring, twinship and idealization, and explores the contrast between Kohut’s early conception of empathy as vicarious introspection, and his later conceptualization of what the author calls loving empathy. It also treats the notion of cultural selfobjects, including one’s country of origin and religious symbols, and the concept of generational trauma as an ancestral narcissistic wound that lies at the heart of insatiable feelings of rage and revenge.

Prevalence and predictors of driver distractions in Cyprus: An observational study

ObjectiveDriver distractions are a significant contributor to road accidents and fatalities worldwide. The present research investigated the prevalence of observable driver distractions on both sides of Nicosia, as well as exploring the effect of drivers’ characteristics and time-related variables on their prevalence. MethodsRoadside observations were conducted at eight randomly selected locations in the city of Nicosia, Cyprus. Four of these sites were located in the area of Nicosia controlled by the Republic of Cyprus, and the other four were in the area that is referred to as the Turkish Republic of Northern Cyprus (TRNC) by its administration. ResultsA total of 16,070 drivers were observed, with 8,948 being in the Republic of Cyprus (South) and 7,122 in the Turkish-controlled section of Nicosia (North). A slightly higher proportion of drivers were observed driving distracted in the South (28.0%) than was found in the northern part of the city (25.7%). The most commonly observed secondary tasks in the South were using headphones (9.2%), talking to a passenger (8.1%) and using a mobile 0.4%, 3.7% talking and 2.7% texting). In contrast, the most commonly observed secondary tasks in the North were talking to passengers (10.2%), wearing headphones (8.4%) and using a mobile 0.6% for talking and 2.5% for texting). Gender-related differences were found for a number of different distractions (i.e., talking to passengers, drinking, and handheld mobile phone conversations), and age emerged as a significant predictor for most secondary tasks, including talking to passengers, smoking, hands-free mobile phone use, handheld mobile phone use, texting/keying numbers, drinking and engagement in any type of distraction (all distractions combined). The overall pattern for age was that middle-aged and older drivers were less likely to be distracted than younger drivers. ConclusionsA relatively high proportion of drivers on both sides of Nicosia were engaged in a secondary task while driving. These findings clearly indicate that younger drivers are more likely to drive distracted, which probably contributes to their higher crash rates.

Exploring the Impact of Organizational Initiatives on Work Environment Safety and Health for Public Health

Workplace safety and health efforts in public health are organizational endeavours that include practices, policies, and interventions intended to reduce hazards, enhance well-being, and guarantee adherence to health and safety laws.We provide the findings from a phone conversation and in-person interviews with 286 manufacturing companies.We carried out a cross-sectional study of the attitudes, behaviours, and policies related to health and safety at work. All company types were subjected to analyses using data from the Lost Time Injury frequency rate (LTIFR). Paternalistic efforts, the documentation of occupational safety and public health (OSPH) measures, more worker participation in making decisions, and enhancing managerial perspectives about the importance of OSPH were all linked to very low LTIFR. The results show the advantages of a proactive strategy for developing a culture of wellness and security in public health contexts and emphasize the crucial role that organizational commitment plays in establishing safer and healthier workplaces.In conclusion, safer workplaces are characterized by worker and management engagement in OSPH activities. Additionally, there is a correlation between reduced injury rates and management's overall concern for OSPH, as demonstrated by both attitudes and practical actions.

Mobile phone conversation during nighttime driving: Effects on driving behavior

Objectives This study aims to investigate the impact of mobile phone use (specifically, conversation), considering various use modes, on driving behavior at night. Mobile phone use is a source of driver distraction and has been associated with increased accident risk. Driving at night also entails higher accident risk and severity compared to daytime driving. Several studies have investigated the impact of mobile phone use on driving behavior; however, only a few have explored the differences between the different use modes. Most present studies involved daytime driving, although mobile phone use at night is equally if not more prevalent. Method A driving simulator experiment was designed in which 55 participants drove under nighttime simulator conditions, in different road environments (urban and rural) and under different types of distraction: no distraction, handheld, wired earphone, and speaker mode. The drives were performed during late afternoon and evening hours to resemble nighttime conditions both in the simulator and in the actual environment. Participants also completed a questionnaire for collection of different types of data. Results Results highlight the effect of mobile phone use on driving behavior, through specific indicators. Mobile phone use resulted in reduced 85th percentile driving speed and 85th percentile acceleration and increased reaction time and lateral deviation. However, safer stopping distance was observed in rural roads. Parameters relative to mobile phone use familiarity and exposure were found to mitigate mobile phone use effects. Conclusions Mobile phones affect driving behavior at night in a similar manner to that noted in several different studies considering daytime driving. The hands-free regulation should be revisited, because driver distraction also occurred under this particular use mode. Further research is required considering mobile phone use familiarity and exposure and effects of mobile phone use, because the latter is reduced with an increase in the former. Stopping distance, an understudied but more immediate surrogate measure of road safety, was increased with mobile phone use, mainly as a result of the risk compensation behavior that drivers adopt, indicating that more research is required in this field.

Effects of Cell Phone Conversation on Drivers’ Perceptions of Cyclists’ Intentions

Effects of Cell Phone Conversation on Drivers’ Perceptions of Cyclists’ Intentions

EMPLOYMENT OUTCOMES FOLLOWING THORACOLUMBAR FRACTURES: LONG-TERM FOLLOW-UP GREATER THAN FIVE YEARS

Study designRetrospective study.ObjectivesTo identify patient outcomes, in particular employment, >5-years following traumatic thoracolumbar fracture.Methods235 patients between the ages of 18–65 were identified from the hospital radiology database having sustained a traumatic thoracolumbar fracture on CT or MRI between 01/01/2013 and 31/01/2017. Questionnaires were sent out via post and available emails, with a reminder letter and phone calls. Retrospective data was gathered about employment status pre-fracture and >5-years post injury.Results26 patients had died at follow up leaving 209 patients. 108 (52%) were treated surgically and 101 (48%) conservatively. 106 replies were received with 85 (80%) opting in and 21 (20%) opting out. 68 (80%) patients completed the full questionnaire with 17 (20%) filling out a shortened questionnaire via a phone conversation. 52 (61%) patients underwent surgery and 33 (39%) were treated conservatively. The average follow up was 8 years. Prior to injury 66 (78%) were employed and 19 (22%) unemployed (of which 6 were full time students and 8 were retired). 49 (74%) of the previously employed patients returned to work at follow up with 35 (53%) working the same or increased hours. Regarding employment, there was no significant difference between surgically and conservatively treated patients (P=0.355) or the classification of the fracture (P=0.303). 16 (19%) patients reported back pain prior to their injury whilst 69 (81%) did not. There were 58 (68%) cases of new pain at follow up with the most affected area being the lumbar region in 43 (51%) patients. 32 (38%) patients reported neurological deficit post injury: 19 with subjective symptoms, 9 with objective symptoms and 4 suffered paralysis.Conclusion>5-years following a traumatic thoracolumbar fracture most individuals return to employment. There was no significant difference between the severity of the fracture or how patients are treated on their employment outcomes.

Scam Call Detection Using NLP and Naïve Bayes Classifier

Financial fraud, particularly credit card fraud, is a pressing concern in the realm of digital transactions. The number of phone scams is increasing daily as con artists use phone calls to target victims for nefarious ends. Individuals are falling for con artists' proposals, becoming victims and giving up their personal information, leaving them open to abuse. Effective detection techniques are becoming more and more necessary. In this study, we offer an efficient approach to scam call identification utilizing speech-to-text libraries and the machine learning technique Naïve Bayes classifier. Our technology, which translates voice to text, uses this text to evaluate conversations in real time. It looks for trends and suspicious phrases that point to attempted scams, including asking for credit card numbers, passwords, or other sensitive information. The user will be able to decide whether or not to trust and continue with the call by using the alert prompt that appears as a pop-up message if the words are found to be suspicious. The user will take certain measures, such as ending the conversation right away, blocking the number, and reporting it further, if they don't trust the call. Our strategy is to successfully handle scam calls through ongoing adaptation and learning, boosting user security and confidence in phone conversations. The user will be able to decide whether or not to trust and continue with the call by using the alert prompt that appears as a pop-up message if the words are found to be suspicious. The user will take certain measures, such as ending the conversation right away, blocking the number, and reporting it further, if they don't trust the call. Our strategy is to successfully handle scam calls through ongoing adaptation and learning, boosting user security and confidence in phone conversations. Keyword: Spam Detection, Naïve Bayes, Natural Language Processing, Machine Learning.

CHATBOT: A Comprehensive Review of AI

A chatbot is a computer software that can simulate a conversation with a user. It is sometimes referred to as a dialogue system or a conversational agent. In recent years, the usage of chatbots in entertainment—has advanced quickly. A system that can recognize questions and provide answers to students by utilizing natural language processing methods and domain-specific ontologies has been developed to achieve this goal. Finally, an experimental campaign was run once the designed model was put into use to show how useful it was. In this first we discussed the e-learning how it is important nowadays because of that pandemics it became more useful for the student to study anywhere several industries—including marketing, supporting systems, education, healthcare, cultural heritage, This technological breakthrough was designed to give people rapid and instantaneous responds to the queries they would pose during phone or email conversations, which has been demonstrated to increase user productivity and decrease the amount of time spent on tasks

Knowledge of the health personnel involved in the fluoride varnish therapy programs of primary schools in Tehran, Iran

IntroductionThe World Health Organization (WHO) places great importance on oral health promotion programs in schools, given that approximately one billion people worldwide are students. This demographic not only includes the students themselves, but also extends to school staff, their families, and the broader community, all of whom are interconnected. The objectives of this study were firstly to assess the knowledge of health personnel conducting fluoride varnish treatment (FVT) in schools, and secondly to solicit their views on the effectiveness of their training methods.MethodsData was collected from health personnel involved in FVT in schools, supervised by medical universities in Tehran province, using a questionnaire. The questionnaire was divided into four sections: demographic information, methods of receiving FVT training, respondents’ knowledge regarding FVT, and opinions about the effectiveness of FVT training methods. The questionnaire was distributed via social media, phone conversations, and email. The collected data was analyzed using Mann-Whitney in SPSS Version 26. A regression model was also fitted to the data.ResultsThe present study included 403 participants. Among various educational methods, it was found that participation in previous workshops (P = 0.001) and FVT workshops (P = 0.013) was significantly correlated with a higher FVT knowledge score. Additionally, participation in previous oral health promotion programs was significantly associated with a higher knowledge score (P < 0.05). Therefore, a history of participating in previous health promotion programs significantly contributed to the participants’ knowledge.ConclusionParticipation in previous oral health programs was found to be significantly correlated with a higher knowledge score. The effectiveness of training programs can be attributed to participation in previous workshops and FVT workshops. This study provided insights into potential strategies for enhancing personnel training in national oral health programs.

Use of a mobile application to monitor drain sites and surgical wounds after discharge from acute care - a feasibility study in Singapore

PurposeThis study aimed to demonstrate the compliance, feasibility, and acceptability of telehealth monitoring among surgical patients discharged with wounds or drains. MethodologyThis is a cross-sectional feasibility study. Post- surgical breast, plastic, and hepatobiliary patients with wounds and/or surgical drains were recruited using convenience sampling. The control group received conventional care which consisted of daily telephone follow-up. The intervention group used a mobile wound application to take wound and drain images, report drainage amount and symptoms. Compliance was assessed by measuring the percentage of actual to expected patient entries, feasibility was assessed by comparing detection of abnormalities and unexpected hospital visits, and acceptability was assessed by subjective feedback from nurses and patients from the intervention group. Results59 patients were recruited, with 30 patients in the control group and 29 patients in the intervention group. 9 specialty nurses were involved in the patients’ post- discharge care. The mean compliance rate for the hepatobiliary, breast and plastic patients were 89.9%, 89.5% and 75.9% respectively. 4 patients from the intervention group (13.8%) and 6 patients from the control group (20.1%) were flagged as having potential abnormalities. As for unexpected hospital visits, there were 2 (6.9%) in the intervention group and 1 (3.4%) in the control group. 25 patients and 9 specialty nurses responded to the feedback survey. 22 patients (88%) did not face any application issues. 18 patients (72%) preferred to self-report symptoms via the application rather than to call the nurses and reported feeling safe knowing that they are remotely monitored. Most nurses found the app convenient and timesaving (n=7, 78%), with monitoring through pictures as more accurate than phone conversation (n=8, 89%). ConclusionThe results suggest that use of a mobile application by surgical patients discharged with wounds or drains is feasible and serves as a viable monitoring tool.

VIII—Situational Dependence and Blame’s Arrow

Abstract A looming deadline. A difficult situation at home. A heated phone conversation that redirects our attention. Certain features of our circumstances can be (at least partially) excusing; sometimes, agents who act wrongly in the face of circumstantial pressures are not (that) blameworthy for having done so. But we’re rather bad at detecting these factors that excuse others from blame. When put together, these two observations yield an under-appreciated problem: we fall short of procedural norms of blame in fairly systematic ways.

On Hindsight: Intersections of Heritage and COVID-19 in the Philippines Pandemic Experience

The centenary cycle of pandemics has produced structural and systemic changes in society. The pandemics of cholera (1820s) and Spanish flu (1920s) forcibly adjusted policies and practices in medicine, health, nutrition, aesthetics, architecture and town planning. When the COVID-19 (2020) pandemic impacted the Philippines with lockdowns and quarantines, Filipinos were socially straightjacketed, but they creatively evolved the ways of survival. This study introduced a mapping matrix that wove heritage attributes into the cycle of a pandemic. Documenting COVID-19 coping narratives in social media, the objective was to plot the intersections of heritage taxonomy (natural, built, intangible and movable) against Shah’s (2016, Pandemic: Tracking contangions from cholera to Ebola and beyond) cycle of pandemic (origin, transmission, condition, community, management, scapegoat, cure and recurrence). With the stringent physical limitations imposed by the government, data were generated for 2020–2021 through social media accounts, personal observations and mobile phone conversations. This contextualization captured compelling heritage case studies on survival and resilience mechanisms that emerged across the country. On hindsight, the pandemic was a dramatic rupture in the Philippine society that innovated heritage-based programmes of sustainability and revived Filipino values of nobleness and humanity.

TELECUORE: FEASIBILITY OF A HOSPITAL–TERRITORIAL TELEMEDICINE PROJECT IN CHRONIC HEART FAILURE

Abstract Background Since February 2023, Cardiology department of AUSL Piacenza has started a telemedicine project named “TeleCuore,” aimed at exploring the impact of a multiparametric telemonitoring system on the management of patients affected by chronic heart failure (CHF). OBJECTIVES assess organizational sustainability, satisfaction among involved figures, and the clinical impact at 9 months of an extensive telemonitoring project targeting patients with CHF. Materials and Methods 250 patients with CHF and recent clinical instability were recruited and equipped with the Adilife device to monitor and transmit weight, temperature, blood pressure, heart and respiratory rate, oxygen saturation, and single–lead ECG. These data are managed by case manager (CM), cardiologists, respiratory and perfusion pathophysiology technicians (TFCPC), general practitioner to optimize patient therapy, empowerment, and reduce acute admissions through timely teleconsultations/televisits. Every 6 months, patients are asked to complete a Quality of Life questionnaire (KCCQ–23) and a satisfaction questionnaire regarding the project, which is also administered to healthcare professionals. Results Over 9 months, positive patient engagement is confirmed, with over 92,000 total transmitted measurements. The most monitored parameter is heart rate (4 times/week). At questionnaire analysis, 80% of patients believes TeleCuore helps them remember parameter measurements, and 70% adopt a correct lifestyle through phone conversations with CM. For over 50%of them the project contributes improving their relationship with healthcare professionals. For 90%of healthcare professionals there is better team collaboration and patient education. Both clinicians and patients (100%) believe that TeleCuore improves the effectiveness of follow–up visits: patients arrive more prepared (30%), and staff can dedicate more time to patients (30%) and access information before the visit (10%). The patients KCCQ score varies from a medium of 71 at baseline to a medium of 78 at 6 months analisys. Conclusions TeleCuore project demonstrates that telemedicine can facilitate patient management and empowerment. Professional figures (CM and TFCPC) are crucial for project execution, working alongside clinical cardiologists for proper alert management, patient education on therapy adherence, and correct lifestyle. An ongoing analysis aims to quantify whether TeleCuore can reduce hospitalizations related to acute heart failure.

Conversational technology and reactions to withheld information.

People frequently face decisions that require making inferences about withheld information. The advent of large language models coupled with conversational technology, e.g., Alexa, Siri, Cortana, and the Google Assistant, is changing the mode in which people make these inferences. We demonstrate that conversational modes of information provision, relative to traditional digital media, result in more critical responses to withheld information, including: (1) a reduction in evaluations of a product or service for which information is withheld and (2) an increased likelihood of recalling that information was withheld. These effects are robust across multiple conversational modes: a recorded phone conversation, an unfolding chat conversation, and a conversation script. We provide further evidence that these effects hold for conversations with the Google Assistant, a prominent conversational technology. The experimental results point to participants' intuitions about why the information was withheld as the driver of the effect.

Automatic Classification of Stegano files using the Features of Natural Language Processing and Hybrid Deep Learning Algorithms

The corporate sector has adopted communication as its principal medium due to the improvements of the digital era. In the past, in-person meetings, purchases, settlements, business talks, and profile-taking were all done. However, everything has gone digital in the present period. Over the last several years, there has been a noticeable exponential rise in the amount of complicated texts and documents that require a deeper comprehension of machine learning techniques in order to recognize languages in a variety of applications. Outstanding results in the processing of natural languages have been obtained by a number of Artificial Intelligent techniques. A key component of machine learning and deep learning techniques' efficacy is their capacity to understand intricate models and non-linear connections in data. Choosing the right architecture, frameworks, and algorithms for classifying input, like text files, managing audio and video files, however, is a difficult undertaking. The proposed work's goal is to identify text, audio messages, chatbots, and smart records using natural language processing. Using a hybrid deep learning approach, text, voice, and video recordings are used as inputs to be classified. Problem Synopsis: With contact becoming more and more important to business, companies have created advanced NLP programs. Through chatbots, digital records, phone conversations, and messages, these NLP swiftly fulfil human desires. Customer preferences, desires, and demands have been found to be more strongly impacted by the ease of communication and connection. Today's service providers use chatbots, digital records, messaging apps, email, and phone conversations as their main methods of communication for almost all of their trade channels of preference, client queries, and transactions. Proposed Method: The study shows how input stegano file is processed automatically based on user reactions, text message replies, and audio record identification during communications using text content, voice messages, and audio using the features of Natural Language Processing and hybrid Deep Learning Algorithms

Reducing Discharge Medication Reconciliation Errors at a Pediatric Neurology Inpatient Unit.

Medication reconciliation errors are a common problem in health care, particularly during transitions of care. Discharge medication reconciliation (DMR) errors in a pediatric setting can range from 26% to 42.2%. We conducted a quality improvement project to decrease DMR error rate at Dayton Children's Hospital in Dayton, Ohio. We conducted 2 interventions, each with 3 Plan-Do-Study-Act cycles from September 2021 through February 2023. The first intervention focused on using current specialty neurology nurses as scribes and creating a template note to include the plan of care and review of DMR before discharge. Our second intervention consisted of standardizing the seizure rescue medication order by creating an order panel within our electronic medical record system for all the rescue medications presently available. Medication errors were documented by the specialty neurology nurse during a phone conversation on the next business day post discharge. DMR error rates were calculated for each week using a control chart. Medication errors and patient harm were classified according to the National Coordinating Council for Medication Error Reporting and Prevention Index. One hundred six errors were noted. Of these, 98 (92%) occurred in patients with seizure and 64 (60%) were related to prescription of seizure rescue medication specifically. The baseline error rate was calculated at 15.7% or 7 errors per month (January 2021 through June 2021). The average error rate dropped from 15.7% to 5.3% (2 errors per month) after initiation of our first intervention (September 2021). Twelve weeks after initiation of the second intervention, a 2.9% (1 error per month) was noted. Afterward, there was a ten-week period of 0% errors. Sustainable reduction of DMR errors in pediatric patients with epilepsy was achieved by using specialty neurology nurses to scribe the care plan and creating order panels to facilitate accuracy of discharge medication orders without additional cost to the hospital.

Automatic Classification of Stegano files using the features of Natural Language Processing and hybrid Deep Learning Algorithms

The corporate sector has adopted communication as its principal medium due to the improvements of the digital era. In the past, in-person meetings, purchases, settlements, business talks, and profile-taking were all done. However, everything has gone digital in the present period. Over the last several years, there has been a noticeable exponential rise in the amount of complicated texts and documents that require a deeper comprehension of machine learning techniques in order to recognize languages in a variety of applications. Outstanding results in the processing of natural languages have been obtained by a number of Artificial Intelligent techniques. A key component of machine learning and deep learning techniques' efficacy is their capacity to understand intricate models and non-linear connections in data. Choosing the right architecture, frameworks, and algorithms for classifying input, like text files, managing audio and video files, however, is a difficult undertaking. The proposed work's goal is to identify text, audio messages, chatbots, and smart records using natural language processing. Using a hybrid deep learning approach, text, voice, and video recordings are used as inputs to be classified. Problem Synopsis: With contact becoming more and more important to business, companies have created advanced NLP programs. Through chatbots, digital records, phone conversations, and messages, these NLP swiftly fulfil human desires. Customer preferences, desires, and demands have been found to be more strongly impacted by the ease of communication and connection. Today's service providers use chatbots, digital records, messaging apps, email, and phone conversations as their main methods of communication for almost all of their trade channels of preference, client queries, and transactions. Proposed Method: The study shows how input stegano file is processed automatically based on user reactions, text message replies, and audio record identification during communications using text content, voice messages, and audio using the features of Natural Language Processing and hybrid Deep Learning Algorithms

Leading with compassion and passion: A case study on servant leadership at the Crisis Center of Tampa Bay

Research methodology This case was written using primary data through various channels, including in-depth structured interviews with the CEO and other individuals at the Crisis Center of Tampa Bay (CCTB), as well as exchanging email messages and phone conversations with employees at CCTB. All interviews were recorded and transcribed. In addition, one of the authors took a tour of the main offices of CCTB and took notes on the physical facilities as well as the information provided by the tour guide. Public information from CCTB was used to enhance the information and provide background. All accounts presented in this case are real, and no information was altered or fabricated. Case overview/synopsis Clara Reynolds had been CEO of CCTB for over eight years. The agency had almost tripled its budget in the time she had been there. Her leadership style had positively impacted the culture of the organization. Employees valued her open and transparent leadership style. Employees saw her commitment to training employees, creating work–life balance and helping employees be exceptional at their jobs. There was an issue, however, with Transcare, the organization’s ambulatory service. The performance of the business was declining, and Clara wanted to update the board within 60 days at the next quarterly board meeting. She was not sure what she could do to increase engagement with Transcare’s staff, which would show the board that the staff was fully willing to do what was necessary. Complexity academic level This case is appropriate for teaching undergraduate or graduate-level courses in leadership, organizational behavior or principles of management. It is designed to be discussed during one class period. It will save time and improve the flow if the students read the case before class and are prepared when they arrive. Any information needed for the case discussion has been presented in the case; no further research by the students is necessary. Students should think about the role of leadership in a nonprofit. They should put themselves in the protagonist’s shoes throughout the reading of the case.

Discourse markers in small talk and tasks

Discourse markers help people navigate conversations. We tested how the use of five discourse markers – so, but, oh, I think, and like – was influenced by communication medium (text, phone, videoconferencing) and conversation type (task-related conversation or small talk). Additionally, we tested whether these discourse markers influenced the amount of words contributed throughout the conversation and how interlocutors felt about their conversations. These discourse markers were used more while working on a task compared to casual chat during a phone conversation, but less while working on a task compared to casual chat during instant messaging and videoconferencing conversations. We observed no relationships between discourse marker use and the amount participants contributed to their conversations, nor did we observe relationships between discourse marker use and conversational appraisals in the phone or videoconferencing conversations. We observed a trending relationship in instant messaging conversations where the more discourse markers used, the more communicators enjoyed their conversations. The work presented here expands understanding of discourse markers by documenting variation by setting and task type. The findings support the argument that discourse markers are used to negotiate conversations.