Types of Knowledge, Beliefs, Behaviors of Reducing Dementia Risk in Middle-aged and Elderly Adults in Community and Difference Analysis of Cognitive Function
Bibliographic record
Abstract
Background Lifestyle is an important modifiable risk factor for dementia. Knowledge and beliefs are important factors affecting lifestyle. However, there is a lack of research on the types of knowledge, beliefs, behaviors of reducing dementia risk, and it remains unclear whether there are differences in dementia risk and cognitive function among residents with different types of knowledge, belief, and behavior. Objective To understand the current situation of knowledge, beliefs, behaviors of reducing dementia risk in the middle-aged and elderly adults in the community, explore and analyze the types of knowledge, beliefs and behaviors and the differences of cognitive function, and provide a basis for the development of targeted dementia prevention measures in the community. Methods From March 2021 to February 2022, middle-aged and elderly adults who participated in free health checkups at community health centers and established health management files in five communities in Shapingba District of Chongqing were selected as the survey objects by convenience sampling method. The general information questionnaire, Dementia Knowledge Assessment Scale (DKAS), Motivation to Change Lifestyle and Health Behaviors for Dementia Risk Reduction (MCLHB-DRR), Dementia Risk Reduction Lifestyle Scale (DRRLS), Beijing version of Montreal Cognitive Assessment (MoCA) and Cardiovascular Risk Factors, Aging and Dementia (CAIDE) scores were used for the investigation. K-means cluster analysis was used to classify the knowledge, beliefs, behaviors of reducing dementia risk of residents, and the differences in demographic characteristics, cognitive function and dementia risk among different types were compared and analyzed. Results A total of 232 questionnaires distributed and 211 valid questionnaires were recovered, with an effective recovery rate of 90.9%. The cluster analysis results showed that the knowledge, beliefs and behaviors of reducing dementia risk of the middle-aged and elderly adults in the community could be divided into three types of good knowledge, beliefs and behaviors type, low knowledge-poor behaviors type, low beliefs-poor behaviors type, which accounted for 39.8% (84/211), 37.4% (79/211), and 22.8% (48/211), respectively. The average years of education of middle-aged and elderly residents in good knowledge, beliefs and behaviors type were significantly higher than those in low knowledge-poor behaviors type (t=2.703, P<0.001), and low beliefs-poor behaviors type (t=1.524, P=0.022). The CAIDE scores of residents in low knowledge-poor behaviors type (t=1.431, P<0.001) and low beliefs-poor behaviors type (t=1.080, P=0.002) were significantly higher than those in good knowledge, beliefs and behaviors type. The MoCA scores of residents in low knowledge-poor behaviors type were lower than those in good knowledge, beliefs and behaviors type (t=-2.529, P<0.001) and low beliefs-poor behaviors type (t=-1.869, P=0.018) . Conclusion The knowledge, beliefs, behaviors of reducing dementia risk of the middle-aged and elderly adults in the community could be divided into three types of good knowledge, beliefs and behaviors type, low knowledge-poor behaviors type, low beliefs-poor behaviors type, and there are significant differences in years of education, dementia risk and cognitive function scores among the different types. Developing targeted dementia prevention measures based on the characteristics of different types of knowledge, beliefs, behaviors of reducing dementia risk, may be effective in reducing the risk of dementia and maintaining or slowing cognitive decline.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".