Hacia una base normativa mexicana en la medición de calidad de vida relacionada con la salud, mediante el Formato Corto 36
Bibliographic record
Abstract
OBJECTIVE: To present the results of the application of the short format 36 instrument (SF-36) in the Mexican states of Sonora and Oaxaca. The levels of quality of life were compared with those from Canada and the United States. MATERIAL AND METHODS: The data were obtained using a survey on health service access, usage, and quality. The SF-36 is composed of 36 questions, which represent eight different domains on the health-related quality of life. These domains are used to estimate the physical and mental components of health. Data analysis was performed to calculate the average scores for each domain for the total sample, by gender and age groups in each state. The regional differences were assessed by the difference of means. RESULTS: The total response was 98.5% of the 4200 selected households. The percent response values were similar between the two states. A total of 5961 subjects older than 25 years of age completed the questionnaire. Males scored higher than females in all domains and in both components. Regardless of sex, the highest variation was observed in adults up to 64 years of age mainly in three domains: overall health, social function, and mental health; in the 65-74 year age group occurred mostly in social function and mental health; and in adults older than 75 year only in mental health. The young adult age group (25 to 44 years) showed variation in a greater number of domains, while women exhibited more variation in the "extreme" age groups, 25 to 34 years and 75 years and older. The mean scores in our sample were higher than those found in Canada and the United States in five domains and in the two summary components. Canada showed higher scores in the other three domains (overall health, social function, and mental health). CONCLUSIONS: SF-36 data are not available at the national level; hence, the authors recommend that their study results may serve as the normative reference for SF-36 in Mexico. Researchers using the SF-36 could compare their results with our reference, adjusted by gender and age in population-based studies. Considering that the study regions have contrasting social and economic characteristics, the data from the more developed state, Sonora, may be used as the normative standard. Data from Oaxaca would be used as the reference for less-developed states. The English version of this paper is available at: http://www.insp.mx/salud/index.html.
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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 | 0.043 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".