Towards a conceptual consensus of continuity in mental healthcare: focused literature search and theory analysis
Bibliographic record
Abstract
AIM: While continuity of care is an important component in the provision of mental health services, a universally accepted definition is missing. There is a need to identify areas of consensus and discrepancy in continuity theory and provide a foundation for advancing measurement capabilities. The purpose of this study was to systematically identify and examine scholarship on continuity in mental healthcare. METHODS: Using a focused literature review modelled on the Joanna Briggs Methodology for systematic reviews, MEDLINE, CINAHL, Embase, PsycINFO and Health STAR were searched from 1950 to 2011 for articles on the theoretical nature of continuity in mental healthcare. Included conceptualisations were subject to a theory analysis to critically examine similarities and differences. Next, a content analysis on the extracted data was used to identify a global understanding and set of theoretically defined concepts for the whole. Finally, the identified global concepts were compared with the original documents and to items identified on existing quantitative measurement tools to assess areas of consensus and discrepancy. RESULTS: Seven documents describing the conceptualisation of continuity in mental healthcare were identified. From these, a deductive theoretical summary is proposed and theoretical consensus exists to support nine global concepts of continuity in mental healthcare. These global concepts include Longitudinality, Input & Individuality, Comprehensiveness, Flexible Consistency, Stability & Relationship, Accessibility, Information & Sharing, Realities, and Responsibility/Accountability. The original theories proposed by Dr Bachrach and colleagues and Dr Joyce and colleagues, as well as the ACSS-MH measurement tool, provide the best coverage of the proposed concepts. CONCLUSIONS: Consensus exists across conceptualisations of continuity in mental healthcare, yet it is obscured by inconsistent use of language. Existing tools capture many of the associated concepts and elements, but none do so entirely. Further tool development and psychometric testing is needed. This study provides the foundational work required to advance research priorities in this area.
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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 | 0.122 | 0.170 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.061 | 0.044 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".