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Record W4280607752 · doi:10.34067/kid.0000182022

Lived Experiences of Patients Receiving Hemodialysis during the COVID-19 Pandemic: A Qualitative Study from the Quebec Renal Network

2022· article· en· W4280607752 on OpenAlexafffundabout
Marie‐Françoise Malo, Aliya Affdal, Dan Blum, Fabián Ballesteros, William Beaubien‐Souligny, Marie-Line Caron, Annie‐Claire Nadeau‐Fredette, Murray Vasilevsky, Norka Rios, Marie‐Chantal Fortin, Rita S. Suri

Bibliographic record

VenueKidney360 · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcGill University Health CentreMcGill UniversityCentre Hospitalier de l’Université de MontréalJewish General HospitalHôpital Maisonneuve-RosemontUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Qualitative researchHemodialysis2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Lived experienceMedicineIntensive care medicinePsychologyVirologyInternal medicineSociologyDiseasePsychotherapistSocial scienceOutbreak

Abstract

fetched live from OpenAlex

Background: Hemodialysis patients have faced unique challenges during the COVID-19 pandemic. They face high risk of death if infected and have unavoidable exposure to others when they come to hospital three times weekly for their life-saving treatments. The objective of this study was to gain a better understanding of the scope and magnitude of the effects of the pandemic on the lived experience of patients receiving in-center hemodialysis. Methods: We conducted semi-structured interviews with 22 patients who were undergoing dialysis treatments in five hemodialysis centers in Montreal from November 2020 to May 2021. Interviews were transcribed and then analyzed using thematic content analysis. Results: Most participants reported no negative effects of the COVID-19 pandemic on their hemodialysis care. Several patients had negative feelings related to forced changes in their dialysis schedules, and this was especially pronounced for indigenous patients in a shared living situation. Some patients were concerned about contracting COVID-19, especially during public transportation, whereas others expressed confidence that the physical distancing and screening measures implemented at the hospital would protect them and their loved ones. Some participants reported that masks negatively affected their interactions with health care workers, and for many others, the pandemic was associated with feelings of loneliness. Finally, some respondents reported some positive effects of the pandemic, including use of telemedicine and creating a sense of solidarity. Conclusions: Patients undergoing hemodialysis reported no negative effects on their medical care but faced significant disruptions in their routines and social interactions due to the COVID-19 pandemic. Nevertheless, they showed great resilience in their ability to adapt to the new reality of their hemodialysis treatments. We also show that studies focused on understanding the lived experiences of indigenous patients and patients from different ethnic backgrounds are needed in order reduce inequities in care during public health emergencies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.525

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0120.006
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.096
GPT teacher head0.405
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2022
Admission routes3
Has abstractyes

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