Generational Differences in Organizational Culture

As the Baby Boomers exit the workforce, newer and younger generations’ workers will need to be hired and trained to fill these positions. Millennials entering the workforce will require evolving methodologies of leadership to retain talent. Studies to-date have focused on leadership styles and organizational culture and how they affect employee engagement. However, the bulk of these studies use information that may not be relevant to current Gen Z and Millennial workers. To address existing gap in knowledge, this study explores the differences of the current generations in the modern-day workforce leadership and what Millennial and Gen Z leaders will need to focus on to retain and engage future and current top talent in their respective industries.Specifically, this qualitative study seeks to answer the following research questions: Which styles of leadership do Gen Z and Millennials desire in order to obtain maximum engagement and organizational loyalty? What motivates Millennials and GenZ employment seekers to accept a job and stay at their respective organization aside from monetary compensation? Participant sample includes Millennial and Gen Z age individuals currently between the age of 18-37. Data is collected through surveys and interviews; and analyzed for common themes and patterns. The outcome of the study will help leaders determine what they could offer or improve to retain workers from the Millennial and Gen Z workforce and provide insight of how younger leaders can engage their employees

Development, validity and reliability testing of the East Midlands Evaluation Tool (EMET) for measuring impacts on trainees’ confidence and competence following end of life care training

Objectives: To develop, test and validate a versatile questionnaire, the East Midlands Evaluation Tool (EMET), for measuring effects of end of life care training events on trainees’ self-reported confidence and competence. Methods: A paper-based questionnaire was designed on the basis of the English Department of Health's core competences for end of life care, with sections for completion pretraining, immediately post-training and also for longer term follow-up. Preliminary versions were field tested at 55 training events delivered by 13 organisations to 1793 trainees working in diverse health and social care backgrounds. Iterative rounds of development aimed to maximise relevance to events and trainees. Internal consistency was assessed by calculating interitem correlations on questionnaire responses during field testing. Content validity was assessed via qualitative content analysis of (1) responses to questionnaires completed by field tester trainers and (2) field notes from a workshop with a separate cohort of experienced trainers. Test–retest reliability was assessed via repeat administration to a cohort of student nurses. Results: The EMET comprises 27 items with Likert-scaled responses supplemented with questions seeking free-text responses. It measures changes in self-assessed confidence and competence on 5 subscales: communication skills; assessment and care planning; symptom management; advance care planning; overarching values and knowledge. Test–retest reliability was found to be good, as was internal consistency: the questions successfully assess different aspects of the same underlying concept. Conclusions: The EMET provides a time-efficient, reliable and flexible means of evaluating effects of training on self-reported confidence and competence in the key elements of end of life care

Development and evaluation of the Dignity Talk question framework for palliative patients and their families: A mixed-methods study

Background: Effective patient–family communication can reduce patients’ psychosocial distress and relieve family members’ current suffering and their subsequent grief. However, terminally ill patients and their family members often experience great difficulty in communicating their true feelings, concerns, and needs to each other. Aim: To develop a novel means of facilitating meaningful conversations for palliative patients and family members, coined Dignity Talk, explore anticipated benefits and challenges of using Dignity Talk, and solicit suggestions for protocol improvement. Design: A convergent parallel mixed-methods design. Dignity Talk, a self-administered question list, was designed to prompt end-of-life conversations, adapted from the Dignity Therapy question framework. Participants were surveyed to evaluate the Dignity Talk question framework. Data were analyzed using qualitative and quantitative methods. Setting/participants: A total of 20 palliative patients, 20 family members, and 34 healthcare providers were recruited from two inpatient palliative care units in Winnipeg, Canada. Results: Most Dignity Talk questions were endorsed by the majority of patients and families (>70%). Dignity Talk was revised to be convenient and flexible to use, broadly accessible, clearly stated, and sensitively worded. Participants felt Dignity Talk would be valuable in promoting conversations, enhancing family connections and relationships, enhancing patient sense of value and dignity, promoting effective interaction, and attending to unfinished business. Participants suggested that patients and family members be given latitude to respond only to questions that are meaningful to them and within their emotional capacity to broach. Conclusion: Dignity Talk may provide a gentle means of facilitating important end-of-life conversations

The landscape of distress in the terminally ill

Understanding the complexities of distress and knowing who is most vulnerable isfoundational to the provision of quality, palliative end-of-life care. Although prior studieshave examined the prevalence of symptom distress among patients nearing death, thesestudies have tended to largely focus on physical and to a lesser extent, psychologicalchallenges. The aim of this study was to use the Patient Dignity Inventory (PDI), a novel,reliable, and validated measure of end-of-life distress, to describe a broad landscape of distressin patients who are terminally ill. The PDI, a 25-item self-report, was administered to 253patients receiving palliative care. Each PDI item is rated by patients to indicate the degree towhich they experience various kinds of end-of-life distress. Palliative care patients reported anaverage of 5.74 problems (standard deviation, 5.49; range, 0e24), including physical,psychological, existential, and spiritual challenges. Being an inpatient, being educated, andhaving a partner were associated with certain kinds of end-of-life problems, particularlyexistential distress. Spirituality, especially its existential or ??sense of meaning and purpose??dimension was associated with less distress for terminally ill patients. A better appreciationfor the nature of distress is a critical step toward a fuller understanding of the challengesfacing the terminally ill. A clear articulation of the landscape of distress, including insightregarding those who are most at risk, should pave the way toward more effective, dignityconservingend-of-life care

Sympathy, empathy, and compassion: A grounded theory study of palliative care patients’ understandings, experiences, and preferences

Background: Compassion is considered an essential element in quality patient care. One of the conceptual challenges in healthcare literature is that compassion is often confused with sympathy and empathy. Studies comparing and contrasting patients’ perspectives of sympathy, empathy, and compassion are largely absent. Aim: The aim of this study was to investigate advanced cancer patients’ understandings, experiences, and preferences of “sympathy,” “empathy,” and “compassion” in order to develop conceptual clarity for future research and to inform clinical practice. Design: Data were collected via semi-structured interviews and then independently analyzed by the research team using the three stages and principles of Straussian grounded theory. Setting/participants: Data were collected from 53 advanced cancer inpatients in a large urban hospital. Results: Constructs of sympathy, empathy, and compassion contain distinct themes and sub-themes. Sympathy was described as an unwanted, pity-based response to a distressing situation, characterized by a lack of understanding and self-preservation of the observer. Empathy was experienced as an affective response that acknowledges and attempts to understand individual’s suffering through emotional resonance. Compassion enhanced the key facets of empathy while adding distinct features of being motivated by love, the altruistic role of the responder, action, and small, supererogatory acts of kindness. Patients reported that unlike sympathy, empathy and compassion were beneficial, with compassion being the most preferred and impactful. Conclusion: Although sympathy, empathy, and compassion are used interchangeably and frequently conflated in healthcare literature, patients distinguish and experience them uniquely. Understanding patients’ perspectives is important and can guide practice, policy reform, and future research

Meta-Reinforcement Learning for the Tuning of PI Controllers: An Offline Approach

Meta-learning is a branch of machine learning which trains neural network models to synthesize a wide variety of data in order to rapidly solve new problems. In process control, many systems have similar and well-understood dynamics, which suggests it is feasible to create a generalizable controller through meta-learning. In this work, we formulate a meta reinforcement learning (meta-RL) control strategy that can be used to tune proportional--integral controllers. Our meta-RL agent has a recurrent structure that accumulates "context" to learn a system's dynamics through a hidden state variable in closed-loop. This architecture enables the agent to automatically adapt to changes in the process dynamics. In tests reported here, the meta-RL agent was trained entirely offline on first order plus time delay systems, and produced excellent results on novel systems drawn from the same distribution of process dynamics used for training. A key design element is the ability to leverage model-based information offline during training in simulated environments while maintaining a model-free policy structure for interacting with novel processes where there is uncertainty regarding the true process dynamics. Meta-learning is a promising approach for constructing sample-efficient intelligent controllers.Comment: 23 pages; postprin

Meta-Reinforcement Learning for Adaptive Control of Second Order Systems

Meta-learning is a branch of machine learning which aims to synthesize data from a distribution of related tasks to efficiently solve new ones. In process control, many systems have similar and well-understood dynamics, which suggests it is feasible to create a generalizable controller through meta-learning. In this work, we formulate a meta reinforcement learning (meta-RL) control strategy that takes advantage of known, offline information for training, such as a model structure. The meta-RL agent is trained over a distribution of model parameters, rather than a single model, enabling the agent to automatically adapt to changes in the process dynamics while maintaining performance. A key design element is the ability to leverage model-based information offline during training, while maintaining a model-free policy structure for interacting with new environments. Our previous work has demonstrated how this approach can be applied to the industrially-relevant problem of tuning proportional-integral controllers to control first order processes. In this work, we briefly reintroduce our methodology and demonstrate how it can be extended to proportional-integral-derivative controllers and second order systems.Comment: AdCONIP 2022. arXiv admin note: substantial text overlap with arXiv:2203.0966

The applicability of a weight loss grading system in cancer cachexia: a longitudinal analysis

Background A body mass index (BMI) adjusted weight loss grading system (WLGS) is related to survival in patients with cancer. The aim of this study was to examine the applicability of the WLGS by confirming its prognostic validity, evaluating its relationship to cachexia domains, and exploring its ability to predict cachexia progression. Methods An international, prospective observational study of patients with incurable cancer was conducted. For each patient, weight loss grade was scored 0–4. Weight loss grade 0 represents a high BMI with limited weight loss, progressing through to weight loss grade 4 representing low BMI and a high degree of weight loss. Survival analyses were used to confirm prognostic validity. Analyses of variance were used to evaluate the relationship between the WLGS and cachexia domains [anorexia, dietary intake, Karnofsky performance status (KPS), and physical and emotional functioning]. Cox regression was used to evaluate if the addition of cachexia domains to the WLGS improved prognostic accuracy. Predictive ability of cachexia progression was assessed by estimating proportion of patients progressing to a more advanced weight loss grade. Results One thousand four hundred six patients were analysed (median age 66 years; 50% female, 63% KPS ≤ 70). The overall effect of the WLGS on survival was significant as expressed by change in −2 log likelihood (P < 0.001) and persisted after adjustment for age, sex, and cancer type and stage (P < 0.001). Median survival decreased across the weight loss grades ranging from 407 days (95% CI 312–502)—weight loss grade 0 to 119 days (95% CI 93–145)—weight loss grade 4. All cachexia domains significantly deteriorated with increasing weight loss grade, and deterioration was greatest for dietary intake, with a difference corresponding to 0.87 standard deviations between weight loss grades 0 and 4. The addition of KPS, anorexia, and physical and emotional functioning improved the prognostic accuracy of the WLGS. Likelihood of cachexia progression was greater in patients with weight loss grade 2 (39%) than that with weight loss grade 0 (19%) or 1 (22%). Conclusions The WLGS is related to survival, cachexia domains, and the likelihood of progression. Adding certain cachexia domains to the WLGS improves prognostic accuracy