Mental Health Crisis: An Evolutionary Concept Analysis
Bibliographic record
Abstract
The term 'mental health crisis' is a widely used concept in clinical practice and research, appearing prominently in mental health literature across healthcare and social science disciplines. Within these contexts, the term is frequently either left undefined or defined rather narrowly, confined to clinical observations or guidelines targeted at healthcare providers and negating the multifaceted nature of crisis as described by those with lived experience. Therefore, the aim of this paper is to explore the characteristics of and provide a conceptual definition for the concept of 'mental health crisis'. Rodgers' method of evolutionary concept analysis was employed and 34 articles, ranging from 1994 to 2021 and a variety of disciplines, were analysed. The results highlighted the contrast between clinically oriented surrogate terms and related concepts and those used by individuals with lived crisis experience. Antecedents of crisis included underlying vulnerabilities, relational dysfunction, collapse of life structure and struggles with activities of daily living. The concept's attributes encompassed the temporality of crisis, signs and symptoms of crisis, functional decline and crisis in family and caregivers. Finally, the consequences comprised looking inward for help, looking outward for help, and opportunities and dangers. This concept analysis serves as a foundational step in understanding 'mental health crisis' and its various dimensions, facilitating more nuanced discussions and interventions in the realm of mental healthcare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".