Responding to foot health needs of people experiencing homelessness: the role of a publicly funded community‐based podiatry service
Bibliographic record
Abstract
BACKGROUND: People experiencing homelessness are known to suffer from poor health and can be reluctant to seek healthcare except in crisis. Foot and ankle problems are a concern; as well as causing discomfort and pain, they may escalate from a minor problem to a very serious one without timely and appropriate treatment. Little is known about the foot and ankle problems of people experiencing homelessness. This paper describes a podiatric service specifically for people experiencing homelessness, which includes a fixed site as well as outreach services. The service operates as part of the Homelessness Team program at Cohealth, a large community health service in Melbourne. METHODS: The study used routinely collected data. Every person who was seen by the podiatrist in the Cohealth Homelessness Team in 2019, whether on site or on outreach, was included in the study (n = 295). Of these, 156 were attending for the first time and 139 were returning clients. People who used the service were predominantly rough sleeping (45.2%), with 32.2% in unstable or insecure housing and 22.6% recently housed. RESULTS: Skin and nail pathologies (68.1%), inadequate footwear (51.9%) and biomechanical issues (44.1%) were the most common presentations. People sleeping rough were particularly likely to present with biomechanical issues (50.8%), acute wound care needs (17.4%) or traumatic injury (10.6%). Most people presented with more than one issue (mean = 2.4), and new clients (mean = 2.53) and those rough sleeping (mean = 2.69) had more issues than others. Outreach was the most effective way to reach clients in the most difficult circumstances (48.9% of those in unstable housing, 34.8% of rough sleepers). Most of the clients (81.4%) had connections with other services offered by Cohealth, such as social work or physiotherapy. CONCLUSIONS: This study demonstrated that reaching and intervening on foot and ankle problems of people experiencing homelessness who may not seek care on their own could be achieved through a publicly funded health service, using simplified pathways to care including outreach. In addition to the long- and short- term benefits of the immediate podiatric treatment, building trust and connections through footcare may provide an entry point into accepting other health and welfare services.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".