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Single-facility observational study compares UWB proximity with monitoring-based and self-reported contact records in a Japanese LTCFDoes how you count close contacts in a care home match what sensors actually see?

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Key Takeaway
Note that contact identification strategies should align with facility-specific workflows rather than assuming a single optimal threshold.

This single-facility observational study examined discrepancies between contact-list generation processes and ultra-wideband (UWB)-derived proximity under multiple distance-time thresholds. The investigation involved 27 participants, including 16 residents and 11 staff members, who wore UWB tags, while 10 staff members completed questionnaires. The setting was a Japanese long-term care facility where monitoring-based and self-reported close-contact records were compared to UWB-derived proximity over a five-day observational period.

The analysis revealed that questionnaire-based records and UWB-derived proximity exhibited different patterns of discrepancy across contact types. Resident-related monitoring-based proxy records demonstrated relatively small directional discrepancies. In contrast, staff self-reports tended to identify additional resident-staff contacts under the baseline threshold of ≤1.0 m for ≥15 min. Discrepancies associated with alternative thresholds were noted to be closer to zero than the baseline.

The study acknowledges limitations inherent to a single-facility design and notes that different contact-list generation processes are associated with different patterns of discrepancy rather than a single universally optimal threshold. No adverse events, discontinuations, or tolerability issues were reported. The authors suggest that findings should not be interpreted as supporting a single universally optimal threshold for all settings.

Practice relevance supports aligning contact identification strategies with facility-specific workflows to improve the feasibility and effectiveness of infection prevention and control practices in long-term care facilities. Given the observational nature of the evidence, causal inferences are not supported, and the results may not generalize beyond this specific context.

Imagine trying to count every hug and handshake in a busy care home. Now imagine doing that with a pen on a clipboard versus a tiny sensor that knows exactly where everyone is. A recent study in Japan did exactly this. Twenty-seven residents and eleven staff members wore ultra-wideband tags that tracked their movements. At the same time, staff filled out questionnaires about who they thought was close to whom. The results showed a clear gap between what people remembered and what the sensors recorded.

When staff reported their own contacts, they tended to find more close interactions than the sensors detected at the standard distance setting. However, when researchers changed the distance rules used by the sensors, the differences between the two methods shrank. This suggests that the way we set up our tracking tools matters just as much as the tools themselves. The study did not report any safety issues or side effects from wearing the devices.

This is a single-facility study, meaning it happened in just one location. Because different ways of recording contacts led to different patterns of error, there is no single perfect setting that works everywhere. The takeaway is practical: care homes should align their contact identification strategies with their own specific workflows. This approach improves the feasibility and effectiveness of infection prevention without promising a magic fix that works for every facility instantly.

What this means for you:
Tracking tools and human reports often disagree, so care homes should tailor their methods to their own daily routines.

Study Details

EvidenceLevel 5
PublishedApr 2026
View Original Abstract ↓
BackgroundIn long-term care facilities (LTCFs), close-contact identification often relies on staff recall and monitoring records because residents may be unable to self-report reliably. How these different record-generation processes relate to proximity-based sensor measurements in routine LTCF workflow remain unclear, and how such differences may influence contact-based decision-making in outbreak response is not well understood. MethodsWe conducted a five-day observational study in a Japanese LTCF using ultra-wideband (UWB) indoor positioning. Twenty-seven participants wore UWB tags, including 16 residents and 11 staff members; 10 staff members completed questionnaires. We compared UWB-derived proximity with questionnaire-derived contacts from staff self-report and monitoring-based proxy records, and assessed directional discrepancies under multiple distance-time thresholds. ResultsQuestionnaire-based records and UWB-derived proximity showed different patterns of discrepancy across contact types. Within this facility, resident-related monitoring-based proxy records showed relatively small directional discrepancies, whereas staff self-reports tended to identify additional resident-staff contacts under the baseline threshold ([≤]1.0 m for [≥]15 min). Several alternative thresholds were associated with discrepancies closer to zero than the baseline, although the apparent ranking varied by summary metric. ConclusionsIn this single-facility observational study, different contact-list generation processes were associated with different patterns of discrepancy relative to a proximity-based operational measure. These findings support interpretation in terms of workflow-specific contact-list generation rather than a single universally optimal threshold and may help inform facility-level review of contact identification practices in LTCFs. These findings support aligning contact identification strategies with facility-specific workflows to improve the feasibility and effectiveness of IPC practices in LTCFs.
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