A Thematic Analysis of Intensive Care Unit Diaries Content
Bibliographic record
Abstract
BACKGROUND: Intensive care unit (ICU) diaries are an intervention used in the critical care setting to provide patients with a cohesive narrative of their ICU stay and can have a positive impact on patient and family outcomes. Few studies have examined the content of the diaries as written by family members and healthcare staff, and further information on this is important in understanding how and why diaries can be of benefit. AIM: Content analysis of diaries completed in a medical-surgical ICU within an academic medical centre in Manitoba, Canada. STUDY DESIGN: This was a secondary qualitative analysis of ICU diaries that were completed in 2014-2016 as part of a prior pilot randomized controlled trial (RCT) with adult patients, admitted for more than 72 h and ventilated for more than 24 h. We used a reflexive thematic analytic approach to qualitative analysis, resulting in major themes and subthemes of the diary content. RESULTS: Thirty diaries were analysed. Themes identified (1) Connection (staff subthemes: personhood and personal investment, family subthemes: connection to patient and connection to family/friends), (2) Information provision (subthemes: type of information shared, how information was shared and family-specific information sharing) and (3) Coping (subthemes: expressing emotions, use of humour, spirituality). CONCLUSIONS: This is the first study exploring the content of ICU diaries in a North American context and adds to the existing small body of literature demonstrating how families and healthcare staff use diaries. The findings are beneficial in designing future diary programmes, as understanding how diaries are used in a real-world setting can guide future implementation and resource allocation. ICU diaries are an increasingly common tool used in ICU settings to provide patients with a narrative of their critical illness. Diaries conveyed a connection between healthcare professionals, family and patient, were used to provide information and appeared to be used to help family members cope. RELEVANCE TO CLINICAL PRACTICE: This study provides information regarding how ICU diaries are used by healthcare providers and what information is conveyed, which is useful in guiding future implementation as this intervention becomes more widespread (e.g., utilization, feasibility and instructions).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".