Defining continuity of care from the perspectives of mental health service users and professionals: an exploratory, comparative study
Bibliographic record
Abstract
BACKGROUND: Continuity of care (COC) is central to the organization and delivery of mental health services. Traditional definitions have excluded service users, and this lack of involvement has been linked to poor conceptual clarity surrounding the term. Consequently, very little is known about the differences and similarities in the conceptualization of COC by mental health service users and professionals. OBJECTIVE: To explore and compare mental health service users' and professionals' definitions of COC. METHODS: Using an exploratory, qualitative design, five focus groups with 32 service users each met twice. Data were analysed thematically to generate a service user-defined model of COC. In a cross-sectional survey, health and social care professionals (n = 184) defined COC; responses were analysed thematically. Service user and professional definitions were conceptually mapped and compared to identify similarities and differences. RESULTS: There was crossover between the service user and professional derived models of COC. Both contained temporal, quality, systemic, staff, hospital and needs-related elements of COC. Service users prioritized access, information, peer support and avoiding services; health professionals most frequently referred to staff, cross-sectional and temporal COC. Service users alone identified service avoidance, peer support and day centres as COC elements; professionals alone identified cross-sectional working. CONCLUSIONS: Important similarities and differences exist in service user and professional conceptualizations of COC. Further research is necessary to explore these differences, prior to integrating service user and professional perspectives in a validated COC framework which could enable the development and evaluation of interventions to improve COC, informing policy and practice.
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 | 0.025 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 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".