MétaCan
Menu
Back to cohort
Record W4226084459 · doi:10.1177/23743735221092555

Impacts of the COVID-19 Pandemic on the Healthcare Provision and Lived Experiences of Patients with Hydrocephalus

2022· article· en· W4226084459 on OpenAlexaff
Diana F. Pricop, Arsenije Subotic, Beatrice Ana-Maria Anghelescu, Matthew E. Eagles, Mark G. Hamilton, Pamela Roach

Bibliographic record

VenueJournal of Patient Experience · 2022
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsSocial distancePandemicTelemedicineHealth careDistancingMedicineCoronavirus disease 2019 (COVID-19)PsychologyNursingPolitical scienceDisease

Abstract

fetched live from OpenAlex

The emergence of COVID-19 (SARS-CoV-2) led to distancing measures which acutely affected healthcare infrastructure, leading to limited in-person clinical visits and an increased number of virtual appointments. This study aimed to examine the effects this had on adults with hydrocephalus by describing the lived experiences of a cohort of patients at an outpatient hydrocephalus clinic. Between early May and early July of 2020, remote structured interviews were conducted with participants. Interviews were in-depth and open-ended, allowing participants to reflect and expand on the effects of the social distancing mandate on their well-being and quality of care. Three themes emerged: (1) impacts of changes in treatment provision, (2) impacts of changes in mitigating activities, and (3) impacts of changes on personal well-being. The comprehensive understanding of lived experiences may inform the future provision of healthcare services and social policy. Improved approaches to remote care telemedicine have the potential to facilitate high-quality care.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.362
Teacher spread0.314 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Patient ExperienceSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207