Enabling Long-term Predictions and Cost-benefit Analysis Related to Housing Adaptation Needs for a Population Aging in Place: Protocol for a Simulation Study
Bibliographic record
Abstract
BACKGROUND: Policies that promote aging in place are common in Sweden and many other countries. However, the current housing stock cannot sufficiently accommodate a population aging in place considering how functional capacity and housing needs change as people age. To be suitable for all regardless of their functional ability, housing should be designed or adapted to facilitate the performance of activities of daily living. Long-term planning and plausible projections of development 20 to 30 years into the future are needed. OBJECTIVE: The overall aim is to develop simulation models that enable long-term predictions and analysis of potential consequences in terms of societal gains and costs for different large-scale measures and interventions in the ordinary housing stock. METHODS: This study is designed as a simulation study and will broadly apply health impact assessment methods in collaboration with five municipalities in Sweden. Individual interviews and research circles were used to identify current and prioritize potential new policies to improve the accessibility of the housing stock. We will run a series of simulations based on an estimated willingness to pay from discussions with the municipalities. Two to three different prioritized policies will be compared simultaneously using Markov cohort analysis to estimate the potential costs and health impact on the population. Using data from a systematic review and existing population-based data sets with individual-level data on home and health variables, we will calculate parameter estimates for the relations between housing accessibility and health outcomes. The potential impact of selected policy interventions will be estimated in several microsimulations representing people living in the community. Sensitivity analyses will be conducted for each simulation. RESULTS: As of April 2022, open access data was collected, and a systematic review was underway and expected to be completed by November 2022. Collaboration with five municipalities was established in autumn 2020. In spring 2021, the municipalities developed a list of prioritized policy interventions to be tested and used in the simulation models. Inventories of barrier frequencies in ordinary housing started in spring 2022 and are expected to be completed in autumn 2022. Data gathering and analyses for simulation inputs will be completed during 2022 followed by the simulation modeling analyses to be completed in 2023. CONCLUSIONS: Improved accessibility of the ordinary housing stock has the potential to maintain or improve the health of the aging population. This study will generate tools that enable long-term predictions and reliable cost-benefit estimates related to the housing adaptation needs for a population aging in place, thus providing support for the best-informed policy decisions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39032.
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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 | 0.046 | 0.065 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.092 | 0.012 |
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".