Exploring the interplay of psychological states and outcomes, and the mediating effect of resilience in type 1 and 2 diabetes

Abstract

Type 1 diabetes (T1DM) is a chronic autoimmune disease characterised by the destruction of insulin-producing pancreatic beta cells, which prevents the body from producing sufficient insulin to adequately regulate blood glucose levels. Type 2 diabetes (T2DM) is a result of insufficient insulin secretion and/or insulin resistance, which are strongly correlated with poor diet, sedentary lifestyle habits, and polygenic components (i.e., multiple associated genes). The prevalence of diabetes globally is estimated to be 415 million (90% T2DM) and is expected to rise to 642 million by 2040, placing increased demands on individuals, carers, health systems and society. The relationships between psychological states (e.g., anxiety, fatigue), resilience and diabetes outcomes (e.g., diabetes distress, cognition) are complex, multifaceted, and not well understood. This research focuses on the association between psychological states (anxiety and fatigue) and diabetes outcomes (diabetes distress and cognition), and the potential for resilience to act as a mediator in relation to those relationships. This research is the first to examine all of the aforementioned variables simultaneously, within one model. The overarching aim of this thesis was to develop a novel model to provide recommendations for intervention design, for individuals with T1DM and T2DM. Theoretical understanding and models are important in guiding clinical applications, and are associated with longer lasting intervention changes than those without.

Resilience is a fundamental factor in health psychology and health-based interventions, and so understanding of these underlying relationships in diabetes is necessary to improve health outcomes. Psychological well-being is not only an important outcome, but arguably a pre-requisite for optimal diabetes self-management; Despite this, current UK funding for psychological research in diabetes remains inadequate. Existing findings account for a mediating effect of resilience between variables such as diabetes distress and anxiety, but no studies have examined this mediation effect in these factors simultaneously within one study and therefore, not capturing the complexity of these underlying relationships. This research employed a mixed-methods approach, where correlational and SEM (Structural Equation Modelling; A combination of factor analysis and regression statistical techniques) analyses examined the proposed model, and a combination of deductive and inductive thematic analyses examined the lived experiences behind the relationships/variables within and outside the model. The findings were evaluated against existing research to compile a list of intervention recommendations.

Study 1: This study explored whether resilience mediated the association between psychological states (anxiety, fatigue) and diabetes outcomes (diabetes distress, cognition) within one model, and if any differences existed between diabetes types. Data was collected via an e-survey using the platform Qualtrics. Preliminary correlation analyses followed by SEM revealed a significant mediating effect of resilience between psychological states (anxiety and fatigue) and diabetes outcomes (diabetes distress and cognition), with no difference between T1DM and T2DM groups (n =307; T1 = 129, T2 = 178). These findings supported the proposed model to explain the underlying relationships between resilience and psychological factors.

Study 2: This study explored the lived experience of individuals with T1DM and T2DM in the context of the model variables in study 1 (e.g., anxiety, fatigue, resilience, diabetes distress, cognition), and examined factors outside of the model that were relevant to diabetes self-care (e.g., healthcare experiences). Deductive and inductive thematic analyses were performed on responses from questions relating to the lived experiences of diabetes, in the context of variables within the model. Semi-structured interviews were conducted in T1DM (N=12) and T2DM (N=14) participants. Analyses identified five main themes, three of which were deductive: (a) psychological states: MH (Mental Health; a state of well-being enabling individuals to cope with the stresses of life, identify their abilities and function effectively), anxiety, fatigue, cognition; (b) Resilience: anxiety and fatigue, cognition, diabetes distress, coping styles; (c) diabetes management: glucose monitoring and medication, daily functioning. The remaining two themes were inductive: (d) healthcare experiences and attitudes: healthcare provider interactions, healthcare system; and (e) diabetes education and intervention experiences: education, interventions. Findings here provided some support for the model in study 1. Participants highlighted how resilience was an important part of their diabetes management, and generally helped reduce feelings of anxiety, fatigue and diabetes distress. Over half of participants (T1- 58%; T2- 64%) described how resilience aided cognition (i.e., through planning, decision making), but participants were generally more unsure regarding cognition than other factors. Participants also discussed other prevalent factors in their diabetes healthcare experiences that influenced self-management, such as education and lack of support. Intervention uptake rates and satisfaction of these courses (e.g., content, delivery) were generally low. These findings provided insight for intervention-based research and clinical applications.

Study 3: This study investigated the lived experience of the study 1 model variables in a broader sample, and conducted a closer examination of inductive aspects of living with diabetes outside of the model (identified in study 2), such as mental health, education and interventions. Data was collected via an e-survey using the platform Qualtrics (N= 53; T1=20; T2=33). Deductive Thematic Analysis identified three overarching themes: (a) Mental healthcare: accessibility, approaches, quality of care satisfaction; (b) Psychological correlates of diabetes: MH impact (including model variables), cognition, resilience in diabetes self-management; and (c) Education and interventions: education from healthcare providers, intervention experiences and recommendations. Findings provided some support for the model in study 1, and provided more insight into factors identified outside of the model. Both diabetes groups felt there was: a lack of integration of mental healthcare and support within primary healthcare (i.e., healthcare provider and service issues); participants described a range of psychological difficulties in line with the model; and psychological education regarding living with diabetes is lacking in both the public population (diabetes and non-diabetes) and in healthcare providers. Participants made a range of recommendations for interventions: to raise awareness of MH and psychological difficulties; use more layman-friendly language; and improve certain areas of knowledge (e.g., how individualised diabetes can be regarding symptoms, and how unpredictable blood sugars can be, making them hard to control). These findings support the need to increase psychological and MH-based education as part of diabetes care.

Collectively, the thesis findings provide support for the proposed model, and analyses of lived experiences provide insight into the problems diabetes patients are facing. There is a need to develop research-based models, and a need to integrate psychological and MH-based education in primary care and existing interventions; this will help patients feel supported in further understanding their diabetes symptoms, and to improve self-efficacy in managing their diabetes. Taking account of current findings and existing literature, the following recommendations are suggested for intervention design: 1) Implementing theoretical-based interventions; 2) Incorporating mental health and psychological education into primary care and existing interventions; 3) Addressing care approaches and the need for a holistic understanding of diabetes self-management; 4) Better coordination of diabetes and MH care services and signposting; and 5) Integrating patient recommendations and improving intervention uptake.