Aging with Diabetes: Sense of Coherence and Satisfaction with Life in European Older Adults with Type 2 Diabetes
Bibliographic record
Abstract
Objectives: The population’s increased longevity is leading to a worldwide concern about older adults’ well-being and about the incidence of chronic diseases such as diabetes. The present research intends to: (a) determine significant differences among three groups of older adults with diverse diabetes diagnosis, namely, participants with only type 2 diabetes, participants with diabetes and other chronic diseases and the remaining without any chronic disease, regarding the satisfaction with life (SWL) and sense of coherence (SOC) scores, and (b) to assess the association of SWL with SOC in these groups.Method: We recruited 304 non-institutionalized older adults aged between 74-100 years (M=82.9; SD= 6.71), who were allocated to three groups, according to their diagnosed medical condition. Measures were completed, including demographics, the Satisfaction with Life Scale and the Orientation to Life Questionnaire. Results: Significant differences were found regarding the SWL and SOC among the three groups. The lowest SOC and SWL scores were found in the ‘only diabetes’ group. Findings also indicated the existence of an association between SOC and SWL scores in the with ‘only diabetes’ group. No correlations were found between SOC and SWL scores in the ‘without diabetes’ and ‘with diabetes and other’ groups.Conclusions: Findings suggest that chronic diseases such as diabetes, as well as the existence of comorbidities, differently influence both SWL and SOC. Furthermore, this study discloses the importance of SWL and SOC for the elderly, in particular when in the presence of diabetes, and their relevance in the context of healthy aging in older populations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".