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Record W4401504784 · doi:10.2196/54560

User Experience of a Bespoke Videoconferencing System for Web-Based Family Visitation for Patients in an Intensive Care Unit: 1-Year Cross-Sectional Survey of Nursing Staff

2024· article· en· W4401504784 on OpenAlexvenueno aff
Aoife Murray, Irial Conroy, Frank Kirrane, Leonie Cullen, Hemendra Worlikar, Derek T. O’Keeffe

Bibliographic record

VenueJMIR Human Factors · 2024
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsnot available
Fundersnot available
KeywordsBespokePreprintUnit (ring theory)Cross-sectional studyVideoconferencingNursingPsychologyMedicineMultimediaComputer scienceWorld Wide WebBusiness

Abstract

fetched live from OpenAlex

Background: During the COVID-19 pandemic, in-person visitation within hospitals was restricted and sometimes eliminated to reduce the risk of transmission of SARS-CoV-2. Many health care professionals created novel strategies that were deployed to maintain a patient-centered approach. Although pandemic-related restrictions have eased, these systems, including videoconferencing or web-based bedside visits, remain relevant for visitors who cannot be present due to other reasons (lack of access to transport, socioeconomic restraints, geographical distance, etc). Objective: The aims of this study were (1) to report the experience of intensive care nursing staff using a bespoke videoconferencing system called ICU FamilyLink; (2) to examine the scenarios in which the nursing staff used the system; and (3) to assess the future use of videoconferencing systems to enhance communication with families. Methods: A modified Telehealth Usability questionnaire was administered to the nursing staff (N=22) of an intensive care unit in a model 4 tertiary hospital in Ireland 1 year after implementing the bespoke videoconferencing system. Results: In total, 22 nurses working in the intensive care department at University Hospital Galway, Ireland, responded to the survey. A total of 23% (n=5) of participants were between the ages of 25 and 34 years, 54% (n=12) were between 35 and 44 years, and 23% (n=5) were between 45 and 54 years. Most (n=15, 68%) of the participants reported never using videoconferencing in the intensive care setting to communicate with family members before March 2020. The modified Telehealth Usability Questionnaire showed overall satisfaction scores for each subcategory of ease of use and learnability, interface quality, interaction quality, reliability, satisfaction and future use, and usefulness. In total, 21 (95%) participants agreed or strongly agreed with the statement, "I would use the ICU FamilyLink system in future circumstances in which family members cannot be physically present (ie, pandemics, abroad, inability to travel, etc)," and 1 participant responded neutrally. One participant highlighted a common scenario in intensive care settings in which a videoconferencing system can be used "Even without COVID, web-based communication is important when patients become unexpectedly ill and when families are abroad." Conclusions: This study provides valuable insights into health care professionals' experience using a videoconferencing system to facilitate web-based visits for families. We conclude that videoconferencing systems when appropriately tailored to the environment with the users in mind can be an acceptable solution to maintain communication with family members who cannot be physically present at the bedside. The bespoke videoconferencing system had an overall positive response from 22 nursing staff who interacted with the system at varying frequency levels.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.213
GPT teacher head0.478
Teacher spread0.265 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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