Experiences of healthcare interactions before and after suicidal behaviour among older adults attending geropsychiatric services: an interpretative phenomenological analysis
Bibliographic record
Abstract
OBJECTIVES: Physical illness and functional disability are common in older adult populations and strongly linked to suicidal behaviour. The aim was to explore how older adults who engaged in a suicidal act experienced their interactions with healthcare providers. DESIGN: This study re-examined transcripts from a broader study involving experiences of older adults who took part in two separate semi-structured interviews focusing on their experiences before and after a suicidal act. Interpretative phenomenological analysis was applied. SETTING: A geriatric psychiatric outpatient clinic in a large Swedish city. PARTICIPANTS: Participants (70+) were recruited among consecutive Swedish-speaking patients in outpatient treatment following a suicidal act within the last 3-36 months. Exclusion criteria were personality disorder, ongoing psychosis, aphasia, delirium, clinical dementia or Montreal Cognitive Assessment score indicating moderate/severe cognitive impairment. Out of 22 eligible, nine accepted participation (four women and five men, age range 71-92 years). Prior to the suicidal act, all had their main care contact in primary care, and all but one were on antidepressants. RESULTS: Participants described interactions with healthcare services that amplified their feelings of alienation, loneliness, worthlessness and self-stigma. Difficulties accessing care increased their sense of powerlessness. Some participants were cognizant of their mental health needs but experienced obstacles that hindered them from managing their illness, which reduced their sense of agency. These situations increased frustration and hopelessness and contributed to the development of suicidal behaviour. On the contrary, feeling listened to in trustful and validating relationships helped restore self-respect and agency and fostered engagement in their individual suicide preventative strategies. CONCLUSIONS: The findings can inform educational interventions and clinical approaches to the care and management of older adults with symptoms of common mental disorders. Exploring experiences of care interactions before and after suicidal acts across different clinical settings and cultures could be areas for future research.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".