Digital Communication at End-of-Life: Exploring Attitudes and Experiences Before and After the End of the COVID-19 Pandemic (Preprint)
Bibliographic record
Abstract
BACKGROUND End-of-life communication is a complex and sensitive topic that necessitates careful consideration. The advent of digital technology has transformed the landscape of end-of-life communication, offering new possibilities and challenges. From video calls to online memorials, technology has revolutionized how we approach death and dying. However, there is a limited understanding of the attitudes and experiences surrounding digital communication at the end of life, particularly between individuals and their loved ones as existing research mainly focuses on communication between patients and clinicians, overlooking the broader aspects of communication at end of life. OBJECTIVE This study aims to explore individuals' attitudes and experiences regarding digital communication during end-of-life situations through an interactive installation. The study also includes an examination of changes in people's perceptions and behaviors toward digital communication during times of dying before and towards the end of the COVID 19 pandemic [1]. The research aims to provide insights into the role of technology in facilitating meaningful connections, supporting the grieving process, and supporting end-of-life experiences. METHODS In this qualitative study, data on participants' sentiments regarding digital communication during end-of-life situations were collected through an interactive installation "Time Moving", mounted in the exhibit “Dying.exhibits” before (January 2020) and towards the end of the COVID-19 pandemic (January 2023), in Toronto, Canada as part of the DesignTO festival. DesignTO is an annual design festival held in Toronto, Canada organized by a non-profit arts organization dedicated to celebrating design's role in creating a better world [2]. Participants were encouraged to share their thoughts by writing responses on postcards in response to the question: "How do you feel about communicating digitally during times of dying?" Data analysis involved an inductive approach, with a sample size of 80 postcards gathered from 2020 and 51 postcards from 2023. RESULTS Participants had a range of perspectives on digital communication in end-of-life situations. Some found it helpful and appreciated the ability to connect virtually, especially when physical presence was not possible. Others expressed concerns about the performative nature and lack of emotional depth of digital interactions. The findings reveal the complex nature of acceptance, adoption, and the impact of digital communication on end-of-life experiences. There was, however, a pattern which suggests that the Covid-19 pandemic influenced a shift towards increased acceptance of digital communication as a practical option, accompanied by feelings of sadness and resignation. These findings contribute to our understanding of the evolving use and attitudes towards digital communication in end-of-life experiences. CONCLUSIONS In conclusion, this study highlights the complex role of digital communication in end-of-life situations and its impact on the evolving nature of these experiences. The results highlight the need for sensitivity towards diverse perspectives in introducing or using digital communication at end of life. The study enhances our understanding of technology's influence on end-of-life communication, considering both the benefits and limitations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".