ArticleHealthcare (Basel, Switzerland)2023
Hidden and Understaffed: Exploring Canadian Medical Laboratory Technologists' Pandemic Stressors and Lessons Learned.
Article in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Moral distress and moral injury in healthcare: A review and instrument analysis.Journal of health psychology · 2026Review
- Workplace bullying among medical laboratory professionals in Ghana: insights from self-reported experiences, challenges to mitigation structures, and coping strategies.BMC health services research · 2025Article
- Exploring the readiness to practice of underrepresented healthcare workers: A scoping review.SAGE open medicine · 2025Article
- Managing Resilience and Exhaustion Among Health Care Workers Through Psychological Self-Care: The Impact of Job Autonomy in Interaction With Role Overload.Journal of healthcare leadership · 2025Article
- A qualitative study examining stressors among Respiratory Therapists in Ontario amidst the COVID-19 pandemic.PloS one · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
(1) Background: The COVID-19 pandemic has highlighted the critical role of medical laboratory technologists (MLTs) in the healthcare system. Little is known about the challenges MLTs faced in keeping up with the unprecedented demands posed by the pandemic, which contributed to the notable staff shortage in the profession. This study aims to identify and understand the stressors of MLTs in Canada and the lessons learned through their lived experiences during the pandemic. (2) Methods: In this descriptive qualitative study, we conducted five semi-structured focus groups with MLTs working during the pandemic. The focus group sessions were audio-recorded and then transcribed verbatim. Thematic analysis was used to inductively code data and identify themes. (3) Results: A total of 27 MLTs across Canada participated in the study. Findings highlighted four key themes: (i) unexpected challenges navigating through the uncertainties of an ever-evolving pandemic; (ii) implications of staff shortage for the well-being of MLTs and quality of patient care; (iii) revealing the realities of the hidden, yet indispensable role of MLTs in predominantly non-patient-facing roles; and (iv) leveraging insights from the COVID-19 pandemic to enhance healthcare practices and preparedness. (4) Conclusion: The study provides in-depth insight into the experiences of MLTs across Canada during the pandemic. Based on our findings, we provide recommendations to enhance the sustainability of the laboratory workforce and ensure preparedness and resiliency among MLTs for future public health emergencies, as well as considerations as to combating the critical staff shortage.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.