Barriers and Facilitators to Healthcare Access Among Adults with Type 2 Diabetes in Remote Island Settings
Introduction and Research Topic
Type 2 diabetes mellitus is a major global public health concern, associated with significant morbidity and mortality. Effective management relies heavily on consistent access to healthcare services, medication adherence, and patient self-management. However, in geographically isolated settings such as Saint Helena, access to healthcare may be constrained by structural, economic, and social factors. This study focuses on exploring the barriers and facilitators to healthcare access among adults living with type 2 diabetes in remote island settings and how these influence glycaemic control.
The conceptual research hypothesis is:
Adults with type 2 diabetes living in remote island settings who experience fewer barriers and more facilitators to healthcare access will demonstrate better glycaemic control compared to those facing greater barriers.
This hypothesis adheres to the FINER criteria. It is feasible, given the defined and accessible population; interesting, as it addresses a critical healthcare challenge; novel, due to the limited research in isolated island contexts; ethical, as it involves minimal risk observational methods; and relevant, particularly to improving local healthcare delivery and outcomes.
Definitions of Key Concepts
Barriers to healthcare access refer to any obstacles that limit an individual’s ability to obtain appropriate medical care. These may include transportation difficulties, cost, limited healthcare workforce, or availability of medication. Facilitators are factors that enhance access, such as community support, effective primary care systems, or outreach services.
Healthcare access is defined as the timely use of personal health services to achieve optimal health outcomes. Type 2 diabetes is a chronic metabolic disorder characterised by insulin resistance and impaired glucose metabolism. Glycaemic control refers to the management of blood glucose levels, typically assessed using glycated haemoglobin (HbA1c). Remote island settings are geographically isolated areas with limited infrastructure and healthcare resources.
Expected Outcomes and Measurement
The expected outcome of this study is that individuals experiencing fewer barriers and more facilitators will demonstrate better glycaemic control. This will be measured using HbA1c levels obtained from clinical records. A clinically meaningful difference of at least 1% in HbA1c is anticipated between groups. This expectation is supported by guidance from the American Diabetes Association, which recognises a 1% reduction in HbA1c as significant in reducing complications.
While the study incorporates quantitative measures, it also acknowledges the importance of qualitative insights to understand lived experiences. Therefore, the research adopts a mixed-methods approach.
Operational Research Hypothesis (PICOT Framework)
The operational research hypothesis is structured using the PICOT framework:
Population (P)-Adults aged 18 years and older with type 2 diabetes living in Saint Helena
Intervention/Exposure (I)- Lower levels of barriers and higher levels of facilitators to healthcare access
Comparison (C)-Higher levels of barriers and fewer facilitators
Outcome (O)- Glycaemic control measured by HbA1c levels
Time (T)-Previous 12 months
The hypothesis states that individuals with fewer barriers will have significantly lower HbA1c levels over a 12-month period.
The ideal quantitative design for this hypothesis is an analytical cross-sectional study, potentially supplemented by retrospective clinical data. This design allows for the comparison of HbA1c levels across groups with differing levels of healthcare access.
In addition, a qualitative component will be incorporated using a phenomenological or interpretive descriptive approach. Semi-structured interviews will be conducted to explore participants’ lived experiences, perceptions of barriers, and enabling factors.
The mixed-methods approach is particularly appropriate in this context. Quantitative data provides measurable associations, while qualitative data offers depth and context, explaining why such associations exist.
Advantages and Disadvantages of the Design
The cross-sectional design is efficient, cost-effective, and suitable for small populations such as those found in remote islands. It enables the identification of associations between access and health outcomes. However, it cannot establish causality and may be affected by confounding variables.
The qualitative component provides rich, detailed insights into patient experiences and contextual factors influencing healthcare access. Nevertheless, qualitative research may involve smaller sample sizes and subjective interpretation.
Despite these limitations, the mixed-methods design is optimal, as it combines the strengths of both approaches and enhances the overall validity and applicability of findings.
Study Planning
The research question and hypothesis have been clearly defined. The study design has been selected and justified. The study population will include adults aged 18 years and above with a confirmed diagnosis of type 2 diabetes residing in Saint Helena.
Inclusion criteria will consist of diagnosed adults who have been residents for at least one year. Exclusion criteria include individuals with type 1 diabetes, gestational diabetes, or severe cognitive impairment.
Measurement of exposure (barriers and facilitators) will be conducted באמצעות structured questionnaires assessing factors such as transport access, cost, service availability, and social support. The outcome measure, HbA1c, will be obtained from standardised laboratory records.
Potential confounders such as age, gender, socioeconomic status, duration of diabetes, and comorbidities will be collected and adjusted for during analysis.
Bias and Validity Considerations
Several forms of bias may affect the study. Selection bias may arise due to the small population size, but this can be minimised by including all eligible individuals. Recall bias may occur in self-reported measures, which can be mitigated using validated questionnaires. Measurement bias will be reduced by using standardised HbA1c data.
Confounding is a significant concern, particularly with lifestyle and socioeconomic factors. Statistical adjustment using regression models will be employed to address this.
Data Analysis Plan
Quantitative data will be analysed using descriptive statistics to summarise participant characteristics. Inferential statistics, such as t-tests or ANOVA, will be used to compare HbA1c levels between groups. Multivariable regression analysis will be conducted to adjust for confounders.
Qualitative data will be analysed using thematic analysis, involving coding and identification of recurring themes related to barriers and facilitators.
Timeframe and Ethical Considerations
The study is expected to be conducted over a period of 6–9 months, including data collection and analysis. Ethical considerations include obtaining informed consent, ensuring confidentiality, and securing approval from an appropriate ethics committee.
Limitations
The study may be limited by its cross-sectional design, which prevents causal inference. The small sample size may reduce statistical power. Self-reported data may introduce bias. These limitations will be mitigated through methodological rigour, triangulation of data, and careful interpretation of findings.
Conclusion
This study addresses a critical gap in understanding how healthcare access influences diabetes outcomes in remote island settings. By employing a mixed-methods approach, it provides both measurable evidence and contextual insight. The findings have the potential to inform targeted interventions and improve healthcare delivery for individuals living with type 2 diabetes in isolated communities.