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Record W4382313050 · doi:10.1111/nicc.12926

A study protocol to develop and test an e‐health intervention in follow‐up service for intensive care survivors' relatives

2023· article· en· W4382313050 on OpenAlexaff
Margo van Mol, Erwin J. O. Kompanje, Jasper van Bommel, Jos M. Latour

Bibliographic record

VenueNursing in Critical Care · 2023
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsMinnow Environmental (Canada)
FundersZonMw
KeywordsIntervention (counseling)Protocol (science)MedicineNursingFocus groupIntensive care unitPopulationHealth careTest (biology)Qualitative researchFamily medicinePsychologyPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The negative impact on long-term health-related outcomes among relatives of critically ill patients in the intensive care unit (ICU) has been well described. High-quality ICU specialized follow-up care, which is easily accessible with digital innovation and which is designed by and with relevant stakeholders (i.e., ICU patients' relatives and nurses), should be considered to reduce these impairments in the psychological and social domains. AIM: The programme's aim is to develop and test an e-health intervention in a follow-up service to support ICU patients' relatives. Here, the protocol for the overall study programme will be described. STUDY DESIGN: The overall study comprises a mixed-methods, multicentre research design with qualitative and quantitative study parts. The study population is ICU patients' adult relatives and ICU nurses. The main outcomes are the experiences of these stakeholders with the newly developed e-health intervention. There will be no predefined selection based on age, gender, and level of education to maximize diversity throughout the study programme. After the participants provide informed consent, data will be gathered through focus groups (n = 5) among relatives and individual interviews (n = 20) among nurses exploring the needs and priorities of a digital follow-up service. The findings will be explored further for priority considerations among members of the patient/relative organization (aiming n = 150), which will serve as a basis for digital prototypes of the e-health intervention. Assessment of the intervention will be followed during an iterative process with investigator-developed questionnaires. Finally, symptoms of anxiety and depression will be measured with the 14-item Dutch version of the 'Hospital Anxiety and Depression Scale', and symptoms of posttraumatic stress will be measured with the 21-item Dutch version of the 'Impact of Events Scale-Revised' to indicate the effectiveness of digital support among ICU patients' relatives. RELEVANCE TO CLINICAL PRACTICE: The e-health intervention to be developed during this research programme can possibly bridge the gap in integrated ICU follow-up care by providing relevant information, self-monitoring and stimulating self-care among ICU patients' relatives.

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)0.001
metaresearch head score (Gemma)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.286
GPT teacher head0.566
Teacher spread0.280 · 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.

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

Citations6
Published2023
Admission routes1
Has abstractyes

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