Do baby boomers use more healthcare services than other generations? Longitudinal trajectories of physician service use across five birth cohorts
Bibliographic record
Abstract
OBJECTIVE: In light of concerns for meeting the provision of healthcare services given the large numbers of ageing baby boomers, we compared the trajectories of primary care and specialist services use across the lifecourse of 5 birth cohorts and examined factors associated with birth cohort differences. DESIGN: Longitudinal panel. SETTING: Canadian National Population Health Survey (1994-2011). POPULATION: Sample of 10 186 individuals aged 20-69 years in 1994-1995 and who were from 5 birth cohorts: Generation X (Gen X; born: 1965-1974), Younger Baby Boomers (born: 1955-1964), Older Baby Boomers (born: 1945-1954), World War II (born: 1935-1944) and pre-World War II (born: 1925-1934). MAIN OUTCOMES: Use of primary care and specialist services. RESULTS: Although the overall pattern suggested less use of physician services by each successive recent cohort, this blinded differences in primary and specialist care use by cohort. Multilevel analyses comparing cohorts showed that Gen Xers and younger boomers, particularly those with multimorbidity, were less likely to use primary care than earlier cohorts. In contrast, specialist use was higher in recent cohorts, with Gen Xers having the highest specialist use. These increases were explained by the increasing levels of multimorbidity. Education, income, having a regular source of care, sedentary lifestyle and obesity were significantly associated with physician services use, but only partially contributed to cohort differences. CONCLUSIONS: The findings suggest a shift from primary care to specialist care among recent cohorts, particularly for those with multimorbidity. This is of concern given policies to promote primary care services to prevent and manage chronic conditions. There is a need for policies to address important generational differences in healthcare preferences and the balance between primary and specialty care to ensure integration and coordination of healthcare delivery.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".