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Diabetic foot ulcers (DFUs) are highly prevalent and recurrent complications of diabetes mellitus that have significant health and cost implications. Self-care is critical for preventing or delaying DFU and promoting healing, yet adherence to self-care recommendations is low. Interventions using motivational interviewing (MI) have been effective in supporting behaviour change and emotional adjustment, but evidence for DFU is scarce. This study will assess the acceptability, feasibility and preliminary efficacy of an MI-guided programme, Healing DFU through Empowerment and Active Listening (HEALing), and its integration in usual wound care practice.
This single-arm pilot study adopts a mixed-methods approach to assess the feasibility and acceptability of the HEALing intervention. HEALing is a practical, low-intensity, clinic-integrated personalised self-care support intervention, comprising three 30 min face-to-face sessions delivered over 6 weeks by trained wound care nurses, aiming to enhance self-care behaviours and support emotional adjustment in patients with DFU. Data will be collected from a battery of questionnaire-based surveys with patients (n=30), and in-depth individual interviews with both patients (n=30) and wound care nurse facilitators (n=10) from nurse-led wound clinics in a large primary care sector in Singapore.
The primary feasibility outcomes will include enrolment, retention (≥80%), data completion (≥80% of surveys) and participant satisfaction. Secondary outcomes will include self-report measures of illness perceptions, foot care confidence, diabetes distress, foot self-care behaviour, DFU knowledge, autonomy support and health-related quality of life, taken at baseline and post-intervention. Post-intervention interviews with patients and wound care nurse facilitators will be conducted to collect feedback on the programme and its implementation feasibility.
The study protocol has been approved by the local ethics committee, and written informed consent will be obtained from all participants. Findings will be disseminated through the first author’s PhD thesis, peer-reviewed journals, national and international conferences and public events.
Remote assessment of surgical site infection(SSI) lacks sensitivity for the diagnosis of SSI, but current evidence has not evaluated whether a combination of photographs and questionnaires improves diagnostic accuracy. This study aims to develop a remote diagnostic measure to identify SSI. A two-phase mixed methods study was conducted. In phase I, five clinicians reviewed the Bluebelle wound healing questionnaire(WHQ) on a five-point Likert scale of agreement for inclusion in a remote measure. Discussion generated a hypothesis as to which items should be included. In phase II, a cohort study, whereby clinicians evaluated patient's wound images and patients completed the WHQ, were reviewed for scale structure. Principal component analysis (PCA) with scree plot examination and maximum likelihood of estimation (MLE) for one, two and three factors were evaluated. Internal consistency was assessed with Cronbach's α. Phase I: hypothesis generation estimated a measure containing between 10 and 12 items would include all relevant items without ambiguity or redundancy. Phase II: a combined sample of 570 responses provided clinician reviewed images and patient responses. PCA suggested that a 12-item measure with a combined variance of 60.2% would have the best model fit. Cronbach's α was high at 0.841. One included item was highlighted as potentially ambiguous in phase I (wound pain), providing an additional model with this removed. MLE for one, two and three factors suggested measures with 8, 10 and 11 items, respectively. Total variances were low at 29.7%, 39.8% and 41.4% and Cronbach's α were high at 0.838, 0.827 and 0.823, respectively. Three potential models for a remote diagnostic measure were identified. Each is shorter than alternative available measures, which have not been designed for combined use, ensuring this is easy to use. Further evaluation for reliability and diagnostic accuracy is needed to validate a final measure that can be implemented in clinical practice.
by Jasmine C. Mah, Olga Theou, Mario Ulises Perez-Zepeda, Jodie L. Penwarden, Judith Godin, Kenneth Rockwood, Melissa K. Andrew
BackgroundThe construct of social vulnerability attempts to understand social circumstances not merely as a descriptor, but as a predictor of adverse health events. It can be measured by aggregating social deficits in a social vulnerability index (SVI). We describe a standard procedure for constructing a multi-level SVI using two working examples.
MethodsFirst, we describe a six-step approach to constructing a SVI. Then, we conducted a secondary analysis of a clinical dataset (Canadian Immunization Research Network’s Serious Outcomes Surveillance Network (SOS)) and a population-based dataset (Canadian Longitudinal Study on Aging (CLSA)). In both datasets, we construct SVIs, use descriptive statistics to report distributions by age and sex, and perform a multivariable linear regression of social vulnerability on frailty.
ResultsProcedures for drafting a list of candidate social items, selecting deficits for inclusion, and screening deficits to meet inclusion criteria were applied to yield a 18-deficit SVI for the SOS and 74-deficit SVI for the CLSA. Deficits in each SVI were re-scored between 0 and 1, where 1 indicates the greater risk. Finally, the sum of all deficits is calculated into an index. In the SOS, SVI was associated with age only for females and was weakly associated with frailty (r = 0.26, p Conclusion
We present a standard method of constructing a SVI by incorporating factors from multiple social domains and levels in a social-ecological model. This SVI can be used to improve our understanding of social vulnerability and its impacts on the health of communities and individuals.
A limited understanding of the pathology underlying chronic wounds has hindered the development of effective diagnostic markers and pharmaceutical interventions. This study aimed to elucidate the molecular composition of various common chronic ulcer types to facilitate drug discovery strategies. We conducted a comprehensive analysis of leg ulcers (LUs), encompassing venous and arterial ulcers, foot ulcers (FUs), pressure ulcers (PUs), and compared them with surgical wound healing complications (WHCs). To explore the pathophysiological mechanisms and identify similarities or differences within wounds, we dissected wounds into distinct subregions, including the wound bed, border, and peri-wound areas, and compared them against intact skin. By correlating histopathology, RNA sequencing (RNA-Seq), and immunohistochemistry (IHC), we identified unique genes, pathways, and cell type abundance patterns in each wound type and subregion. These correlations aim to aid clinicians in selecting targeted treatment options and informing the design of future preclinical and clinical studies in wound healing. Notably, specific genes, such as PITX1 and UPP1, exhibited exclusive upregulation in LUs and FUs, potentially offering significant benefits to specialists in limb preservation and clinical treatment decisions. In contrast, comparisons between different wound subregions, regardless of wound type, revealed distinct expression profiles. The pleiotropic chemokine-like ligand GPR15L (C10orf99) and transmembrane serine proteases TMPRSS11A/D were significantly upregulated in wound border subregions. Interestingly, WHCs exhibited a nearly identical transcriptome to PUs, indicating clinical relevance. Histological examination revealed blood vessel occlusions with impaired angiogenesis in chronic wounds, alongside elevated expression of genes and immunoreactive markers related to blood vessel and lymphatic epithelial cells in wound bed subregions. Additionally, inflammatory and epithelial markers indicated heightened inflammatory responses in wound bed and border subregions and reduced wound bed epithelialization. In summary, chronic wounds from diverse anatomical sites share common aspects of wound pathophysiology but also exhibit distinct molecular differences. These unique molecular characteristics present promising opportunities for drug discovery and treatment, particularly for patients suffering from chronic wounds. The identified diagnostic markers hold the potential to enhance preclinical and clinical trials in the field of wound healing.
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