Integrated Psychosocial Care in Intensive Care (IPS-Pilot): Protocol for the Systematic, Multimethod Development of a Complex Intervention (Phase A)
Bibliographic record
Abstract
BACKGROUND: There is a high, co-dependent strain on health care professionals (HCPs), patients, and their relatives in intensive care units (ICUs), leading to long-term mental, physical, and occupational consequences. To date, there is no systematic intervention to address this growing problem. OBJECTIVE: The aim of the IPS-Pilot (German: Integrierte Psychosoziale Versorgung; English: "Integrated Psychosocial Care") project is the development (phase A) and pilot testing (phase B) of an integrated and complex psychosocial care intervention for HCPs, patients, and their relatives in ICUs. This study protocol focuses on phase A. A separate protocol for phase B will be published later. METHODS: A structured, multimethod approach was used to gather evidence from the target groups mentioned above on the needs, expected benefits, and necessary conditions for implementation. These methods included (1) a scoping umbrella review conducted by 2 researchers, who independently screened and selected reviews and meta-analyses in the field of needs and demands in the ICU setting, following the Levac framework; (2) web-based and face-to-face interviews and focus group discussions, which were coded independently by 2 researchers and analyzed using qualitative content analysis; the identified categories and codes were then quantified by (3) an online survey conducted with former ICU patients, their relatives, HCPs working in ICUs, and members of the general population. Synthesized results-complemented by the theories of Psychosocial Safety Climate and Conservation of Resources, as well as online and face-to-face stakeholder workshops-were used for intervention development, which was guided by the Intervention Mapping framework. RESULTS: Through the 4 substudies, we aim to gain insights into the psychosocial needs of the aforementioned target groups. Intermediate analyses were conducted to develop both a model of the problem and a model illustrating how these needs can be effectively addressed through a psychosocial intervention that involves integrating a clinically trained psychologist into the HCP team. Data collection and analysis for the intervention development were completed by June 2024, including substudy 1 (n=104 included articles), substudy 2 (n=22 interviews and n=18 participants in focus groups), substudy 3 (n=237 survey participants), and substudy 4 (n=11, n=15, and n=20 participants in 3 consecutive workshops), with further analyses still ongoing beyond the scope of intervention development. The results of the substudies, as well as the final needs-based intervention design, will be published separately. These findings form the basis for the feasibility study (phase B), conducted from July 2024 to July 2025, during which the intervention will be implemented in randomly selected ICU wards and evaluated in terms of feasibility. CONCLUSIONS: Phase B will assess the feasibility of the IPS intervention. The findings will be incorporated into the intervention design and serve as the basis for a future randomized controlled trial to evaluate its efficacy. TRIAL REGISTRATION: OSF Registries 10.17605/OSF.IO/VFXJK; https://osf.io/vfxjk. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/65682.
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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 | 0.096 | 0.090 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.070 | 0.012 |
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".