“It's something we're connected to”: Acceptability and adoption of overdose detection technologies implemented in San Francisco permanent supportive housing
Bibliographic record
Abstract
INTRODUCTION: The transition from homelessness to permanent supportive housing (PSH) is associated with solitary drug use, which heightens the risk for fatal overdose. Overdose detection technologies show promise in reducing fatal overdose in supportive housing environments. We conducted a longitudinal, mixed-methods study in a 50-unit single-room occupancy PSH building in San Francisco, California-tracing the implementation of wall-mounted, push-activated technologies (Brave Buttons) that alert designated responders to potential onsite emergencies, including overdose. METHODS: Between May 2021 and February 2022, we conducted 35 days of naturalistic observation as well as serial, semi-structured interviews with 8 building staff (e.g., housing services coordinators, front desk clerks, custodians) and 5 tenant specialists, who promoted and sensitized residents to Brave Buttons prior to their installation. We administered surveys to all residents, assessing acceptability and uses of Brave Buttons. We calculated descriptive statistics regarding Brave Button installations and activations using administrative device data. Through inductive, iterative thematic analysis, we synthesized participant narratives to identify early expectations, implementation determinants, and adaptive strategies to bolster acceptability and adoption of Brave Buttons. RESULTS: Despite high demand for overdose prevention solutions, staff and tenant specialists initially expressed doubts towards the adoption potential of Brave Buttons in the PSH building, citing resident mistrust of novel technologies with surveillance properties, liability related to (failed) overdose responses, and building staff capacity and willingness to respond to Button activations. Responding to these anticipated implementation constraints, a group of staff and tenant specialists hosted "engagement sessions" to build resident affinity/trust with Brave Buttons and leveraged tenant specialists' rapport with residents for technology sensitization. By December 2021, Buttons were voluntarily installed in 72 % of resident rooms and were used for multiple purposes, including overdoses and safety/wellness checks. The Buttons also helped formalize informal systems of care among residents and strengthened connections between residents and building staff. CONCLUSION: Adaptive strategic planning, responsive to emerging sources of implementation opposition, was critical to addressing perceived barriers to Brave Button acceptability and adoption in the PSH building.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".