Mental Health Needs of Families of Patients in Intensive Care Units and the Role of Mobile Health: Survey Study
Bibliographic record
Abstract
BACKGROUND: The experiences of patients with COVID-19 and their families manifested the most devastating effects of family separation since the 1918 Spanish influenza pandemic and, with it, a call for solutions to patient isolation and its effect on family mental health. OBJECTIVE: This study examined the recent experiences of families of critical care (intensive care unit; ICU) patients related to anxiety and depression (AD), satisfaction with clinician-family communication, and counseling from mental health and social services. This study explored correlations between these factors and family interest in mobile health (mHealth) designed to improve information flow and communication from patient bedside to remote families. METHODS: Using a 36-question quantitative survey, we collected 97 responses over 6 months. We selected participants by using a convenience sampling strategy. To analyze data, we applied descriptive and inferential statistics. Participants represented a spectrum of ages, relationships to patients, and races (n=78, 80% White; n=17, 18% Black; n=2, 2% other races). Approximately 17% (n=16) of the patients were admitted for cancer, 13% (n=13) were admitted for COVID-19, and 21% (n=20) were admitted for other conditions. RESULTS: The mean score for remote families' satisfaction with patient health updates from the bedside and mental health services was 2.94 (SD 1.31), whereas that for phone communication was lower on average. The mean scores of family AD levels were elevated, and levels were higher among family members during the ICU stay than after discharge. These findings confirmed evidence of a negative correlation between transportation difficulties and satisfaction with the frequency of information provided (r=-0.284; P=.005), suggesting that, with the increase in transportation challenges, families become less satisfied with the frequency of patient health information. Family members expressed strong interest in using mHealth information and communication services (mean 8.34, SD 1.98) and having easy access to social workers to manage AD (mean 8.29, SD 2.03). Families experiencing higher levels of anxiety during patients' ICU stays had significantly greater interest in the use of an mHealth app that would provide direct access to social workers (r=0.326; P<.001), in using an mHealth videoconferencing app (r=0.319; P=.002), and in overall mHealth app use (r=0.322; P<.001). CONCLUSIONS: Family members experienced high levels of AD during patient ICU admission, as well as after discharge even though their mental health challenges were reduced. Families were highly dissatisfied with the frequency of health updates, with lower satisfaction reported among those who faced difficulties arranging transportation or lived further from the hospital. Modest but statistically significant correlations were observed between family members' reported mental health status during ICU stays and an interest in an mHealth app that could provide access to real-time bedside information, facilitate communication with bedside nurses, and support connections with social workers.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".