Living With Ambiguity: A Metasynthesis of Qualitative Research on Mild Cognitive Impairment
Bibliographic record
Abstract
PURPOSE OF THE STUDY: Mild Cognitive Impairment (MCI) is a diagnosis proposed to describe an intermediate state between normal cognitive aging and dementia. MCI has been criticised for its conceptual fuzziness, its ambiguous relationship to dementia, and the tension it creates between medical and sociological understandings of "normal aging". DESIGN AND METHODS: We examined the published qualitative literature on experiences of being diagnosed and living with MCI using metasynthesis as the methodological framework. RESULTS: Two overarching conceptual themes were developed. The first, MCI and myself-in-time, showed that a diagnosis of MCI could profoundly affect a person's understanding of their place in the world. This impact appears to be mediated by multiple factors including a person's social support networks, which daily activities are affected, and subjective interpretations of the meaning of MCI. The second theme, Living with Ambiguity, describes the difficulties people experienced in making sense of their diagnosis. Uncertainty arose, in part, from lack of clarity and consistency in the information received by people with MCI, including whether they are even told MCI is the diagnosis. IMPLICATIONS: We conclude by suggesting an ethical tension is always at play when a MCI diagnosis is made. Specifically, earlier support and services afforded by a diagnosis may come at the expense of a person's anxiety about the future, with continued uncertainty about how his or her concerns and needs can be addressed.
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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 | 0.063 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.006 |
| 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".