Understanding the Risks of Recent Discharge: The Phenomenological Experiences
Bibliographic record
Abstract
BACKGROUND: Evidence indicates that people whose mental health problems lead them to require psychiatric hospitalization are at a significantly increased risk of suicide, and the period of time immediately following discharge after such hospitalizations appears to be a particularly high-risk time. AIMS: This paper reports on phenomenological findings from a federally funded, mixed-methods study that sought to better understand the observed increased risk for suicide following discharge from an inpatient psychiatric service. METHODS: A purposive sample of 20 recently discharged former suicidal inpatients was obtained. Data were collected from the participants in hermeneutic interviews lasting between 1 h and 2 h and analyzed according to van Manen's (1997) interpretation of hermeneutic phenomenology. RESULTS: Two key themes were induced: "Existential Angst at the Prospect of Discharge" and "Trying to Survive While Living Under the Proverbial 'Sword of Damocles'." Each of these was comprised of five themes with the second key theme - the focus of this paper - encompassing the following: "Needing Postdischarge Support," "Feeling Lost, Uncertain and Disorientated," "Feeling Alone and Isolated," "Suicide Remains an Option," and "Engaging in Soothing, Comforting Behaviors." CONCLUSIONS: The authors conclude that early exploration of and reconciling patients' expectations regarding inpatient care for their suicidality would appear to be an empirically based intervention that could diminish the postdischarge risk for further suicide attempts.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".