The concept of positive health: a review and commentary on its application in oral health research
Bibliographic record
Abstract
Although the concept of positive health has been around for more than 60 years, acceptable measures of this construct have yet to emerge. Potential explanations are that there is no consensus on how it is to be defined and its ambiguous status with respect to medical and socioenvironmental models of health. In this paper we review definitions of positive health, the origins of these definitions, the way the concept of positive outcomes has been used in research on the outcomes of oral and orofacial conditions and assess whether the concept of positive health has any merit in terms of applied oral health research. This literature reveals many competing and imprecise definitions, many of which are similar to other constructs, such as well-being. Most are lacking empirical referents or indicators. In examining the literature on oral health we found five distinct, although overlapping, ways in which the concept of positive health has been framed: (i) positive health as the absence of negative health states; (ii) positive health as positively worded items; (iii) the positive outcomes of oral health; (iv) positive oral health as a set of psychological and social attributes, and (v) the positive outcomes of chronic conditions such as oro- and craniofacial differences. Each of these ways can be challenged on conceptual or methodological grounds. For example, the states that comprise the upper end of the negative-positive health continuum have not been defined and health states and determinants of health are often confused. Moreover, the meaning of responses to health status questionnaires and the interpretation of accounts of the illness experience is often unclear. Nevertheless, the notion of positive health, irrespective of its merits and public policy implications, provides a context for methodological and theoretical debate that can only serve to enrich theory and practice with respect to measures of health and quality of life and therapeutic interventions at the individual and population.
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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 | 0.030 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".