Introduction
Diabetes mellitus is a long-term health condition affecting the regulation of blood sugar levels. There are many types of diabetes, with Type 1 and Type 2 as the most common forms. Type 1 diabetes (T1DM) occurs when the body does not produce any insulin at all, whereas Type 2 diabetes (T2DM) occurs when the body does not produce sufficient insulin or when the insulin produced is not effective. Both forms of diabetes lead to overly high blood sugar levels (i.e. hyperglycaemia). Persistent high levels of blood sugar have a range of long-term physical health complications, also known as diabetes-related complications. These include an increased risk of macrovascular complications (e.g. heart disease) and microvascular complications (i.e. damage to small blood vessels leading to retinopathy and neuropathy). If left untreated, high blood glucose levels can lead to acute, life-threatening complications such as diabetic ketoacidosis (DKA). To reduce the risk of long-term complications, individuals must self-manage their diabetes.
Following strict self-management routines can present unique challenges that impact psychological wellbeing. Diabetes self-care requires committing to lifelong lifestyle changes such as daily monitoring of blood glucose levels, carbohydrate-counting, and taking medication. From the burden of these demands, people living with diabetes are more likely to experience mental health difficulties such as diabetes-related distress, depression, and anxiety disorders compared with the general population (Anderson and Mansfield, Reference Anderson, Mansfield and Beaser2007). In fact, a recent report found that around 40% of people living with diabetes in the UK struggle with their psychological wellbeing (Diabetes UK, 2019). Poor mental health was found to be associated with poor adherence to treatment, decreased self-care behaviours, increase in blood sugar levels, and poor quality of life (Goldney et al., Reference Goldney, Phillips, Fisher and Wilson2004; Gonzalez et al., Reference Gonzalez, Delahanty, Safren, Meigs and Grant2008; Polonsky et al., Reference Polonsky, Anderson, Lohrer, Welch, Jacobson, Aponte and Schwartz1995). The bi-directional relationship between diabetes and psychological distress can interfere with an individual’s ability to effectively self-manage their co-occurring conditions (Golden et al., Reference Golden, Lazo, Carnethon, Bertoni, Schreiner, Roux and Lyketsos2008). These challenges highlight the importance of psychological support within diabetes services to ensure the provision of both psychological and physical care for individuals living with diabetes.
Cognitive behavioural therapy (CBT) is a common psychological treatment for psychological distress in long-term health conditions (National Institute for Health and Care Excellence, 2009), targeting cognitions and behaviours related to the problem; alongside emerging evidence for third-wave approaches like acceptance and commitment therapy (ACT) and compassion-focused therapy (CFT) (Graham et al., Reference Graham, Gouick, Krahé and Gillanders2016). Central to ACT (Hayes et al., Reference Hayes, Strosahl and Wilson1999) is the notion that negative internal experiences including our thoughts and feelings are an inevitable part of human life and are not inherently causes of distress (Kashdan and Rottenberg, Reference Kashdan and Rottenberg2010). Instead, it is the context in which internal experiences occur and our responses to them that lead to distress (Collard, Reference Collard2019). In ACT, these responses are psychological processes coined as ‘cognitive fusion’ and ‘experiential avoidance’ (Fletcher and Hayes, Reference Fletcher and Hayes2005). Cognitive fusion refers to becoming attached (or ‘fused’) to internal experiences and believing the content to be reflective of reality. For instance, someone living with diabetes may experience a thought that ‘Nothing I do will make a difference to my diabetes’. If they become ‘fused’ with this thought, they might experience distress including a sense of hopelessness. To cope with this, they might stop following their diabetes self-management routine to avoid triggering this distress. This way of responding is an example of experiential avoidance, which might provide short-term relief, but contributes to exacerbation of hyperglycaemia and/or hypoglycaemia symptoms and can contribute to long-term complications. Experiential avoidance creates a self-perpetuating cycle that feeds into an individual’s distress in the long run (Hayes et al., Reference Hayes, Levin, Plumb-Vilardaga, Villatte and Pistorello2013). Over time, these patterns of behaving dictated by internal experiences take individuals away from living a life that is guided by their values (Levin et al., Reference Levin, MacLane, Daflos, Seeley, Hayes, Biglan and Pistorello2014). This is referred to as ‘psychological inflexibility’ (Levin et al., Reference Levin, MacLane, Daflos, Seeley, Hayes, Biglan and Pistorello2014).
In a longitudinal study conducted by Kılıç et al. (Reference Kılıç, Hudson, Scott, McCracken and Hughes2022), psychological inflexibility, symptoms of depression and anxiety were measured in a sample of 173 adults with T2DM in the UK at baseline, six months, and 12 months. They found that psychological inflexibility was a significant predictor of anxiety and depression at six months, and anxiety alone at 12 months. It was also strongly associated with symptoms of depression (r=.69–.83, p<.01) and anxiety (r=.74–.80, p<.01) across the three time points. Similar findings were reported in a sample of adolescents with T1DM (e.g. Iina et al., Reference Iina, Mirka, Laura, Joona and Raimo2021). Additionally, psychological inflexibility was found to be associated with poorer control over blood sugar levels among adolescents and adults with T1DM (Berlin et al., Reference Berlin, Keenan, Cook, Ankney, Klages, Semenkovich and Eddington2020; Nicholas et al., Reference Nicholas, Yeap, Cross and Burkhardt2022) or T2DM (Wang et al., Reference Wang, He, Chen and Yi2020). These findings suggest that targeting psychological inflexibility could be helpful for improving the emotional and physical wellbeing of individuals with diabetes (Hadlandsmyth et al., Reference Hadlandsmyth, White, Nesin and Greco2013).
ACT involves supporting individuals to increase their ‘psychological flexibility’ – defined as the willingness to fully be in contact with difficult internal experiences despite the distress that may arise and taking committed action towards chosen values (Hayes et al., Reference Hayes, Strosahl and Wilson2011) . Six inter-related core processes contribute to psychological flexibility: (1) acceptance – embracing all internal experiences both positive or negative without changing them; (2) cognitive de-fusion – observing thoughts rather than believing they are reality; (3) self-as-context – the ability to step back to acknowledge that our internal experiences do not define us and that we are observers of those experiences; (4) contact with the present moment – noticing and being aware of the ‘here and now’ without judgement; (5) values – life principles we take that are personally meaningful; and (6) committed action – willingness to take action towards chosen values (Hayes et al., 2011). Depending on a collaboratively devised formulation, therapists can work with service users to learn techniques and develop skills in any of the six core processes to increase psychological flexibility (Harris, Reference Harris2013).
The evidence base of ACT in chronic health settings is growing. A systematic review of nine studies using ACT-informed interventions reported improvements in distress and disease self-management among individuals with chronic health conditions (Graham et al., Reference Graham, Gouick, Krahé and Gillanders2016). Within diabetes care, a recently conducted meta-analysis of three randomised controlled trials (RCTs) found that compared with non-intervention groups, individuals with T2DM who received ACT-informed interventions had significantly reduced blood sugar levels, improved diabetes self-management abilities (e.g. aspects of dieting, exercise, and medication adherence), and increased acceptance of difficult thoughts related to diabetes (Sakamoto et al., Reference Sakamoto, Ohtake, Kataoka, Matsuda, Hata, Otonari, Yamane, Matsuoka and Yoshiuchi2022). Similar findings were found by Alho and colleagues (Reference Alho, Lappalainen, Muotka and Lappalainen2022) in a sample of adolescents with T1DM. Notably, few studies within the literature investigated the efficacy of ACT-informed therapy for adults with T1DM. While RCTs are gold-standard studies to explore efficacy of psychological therapies, one limitation is the ecological validity of the findings (Rothwell, Reference Rothwell2005). For example, one study within the meta-analysis excluded patients who were not punctual or missed their appointments (Shayeghian et al., Reference Shayeghian, Hassanabadi, Aguilar-Vafaie, Amiri and Besharat2016). The sample of participants might therefore consist of those who were readily motivated and possibly better resourced to engage in therapy. This is not reflective of reality or the experiences of many service users with complex psychosocial needs that act as barriers to engaging in treatment. This highlights a need to explore the effectiveness of ACT-informed interventions in a naturalistic setting. Many studies researching ACT for diabetes investigated protocolised group interventions. Some services may not have the capacity to offer group-based interventions due to limited resources or staff members. Additionally, some service users presenting with greater needs may find individualised and formulation-driven therapy more appealing and beneficial. Therefore, more research on the effectiveness of individual ACT-informed therapy is necessary to support clinical services supporting service users with complex needs.
Service context
This service evaluation project evaluated outcome data from the psychology clinic in a Community Diabetes Service (CDS), which operates across Croydon, a South London borough that is one of the most deprived areas of the UK with high levels of crime and housing deprivation (Office for Health Improvement and Disparities, 2019). It is home to a diverse population (52% racial ethnic minorities, and 48% white or other) and it is currently estimated that 7% of the population have a diabetes diagnosis and 10,000 more are living untreated, which is the highest across London boroughs (Healthwatch Croydon, 2018).
The CDS started at Croydon University Hospital on 1 July 2020, in response to the growing needs of service users living with diabetes to access community-based support. The CDS consists of a multi-disciplinary team (MDT) including diabetes specialist nurses (DSNs), dieticians, diabetes consultants, clinical psychologist, and a team administrator. The psychology clinic was set up by a part-time clinical psychologist in October 2020 and offers individual and group psychological therapy. The clinic accepts referrals from other healthcare professionals on behalf of individuals experiencing psychological distress related to, or impacting, their diabetes diagnosis or management. Individuals are referred to other psychological therapy services such as NHS Talking Therapies for anxiety and depression if their difficulties are not directly related to or impacting their diabetes or self-management. In line with the evidence base, psychological interventions draw on the principles of ACT but integrate aspects from other approaches, particularly CBT, to meet the needs of service users.
Aims of the service evaluation
The aim was to evaluate the effectiveness of individual ACT-informed therapy delivered in a community-based NHS diabetes clinic setting for service users experiencing psychological distress as a direct result of their diabetes, or psychological distress that was impacting on their diabetes management. This was via analysis of quantitative routine outcome measures collected pre- and post-therapy for generalised anxiety, depression, general psychological distress, as well as diabetes-related distress. As a secondary outcome, HbA1C data was evaluated from pre-therapy to the most recent follow-up post-therapy.
Method
Design and participants
Adults aged 18 and over with Type 1 and Type 2 diabetes who completed treatment under Croydon Diabetes Psychology service during the first three years of operation (October 2020 to December 2023), were included in this service evaluation project. Implied consent for data to be used in research was obtained as part of individuals’ access to the service. The project was registered as a quality improvement project with Croydon Health Services NHS Trust (Project Number: 151298). A within-subjects design was used to evaluate the effectiveness of an ACT-informed intervention for participants with complete outcome data (pre- and post-therapy) that were routinely collected. Statistical analyses evaluated individual change before and after treatment. Participant demographics and treatment duration are reported, as well as change in HbA1c results pre- and post-therapy. Age, gender and ethnicity data were collected from clinical notes where available.
Intervention
In this service evaluation project, the sample of people accessing the service were assessed by a clinical psychologist and two trainee clinical psychologists. The assessment explored physical health with a focus on diabetes self-management, history of difficulties, current presenting difficulty, coping strategies, experience of therapy, social circumstances (e.g. housing and relationships with others), risk, and therapy goals. A range of outcome measures (see below) were completed as part of the assessment process. Following assessment, a person-centred formulation was devised to inform the treatment plan. All interventions were formulated from an ACT perspective, such as the use of the Choice Point model (Harris, Reference Harris2019) and guided by the core tenet of ACT which is the lack of psychological flexibility when managing diabetes-related distress. However, aspects of CBT, such as developing specific maintenance cycles, were drawn to support the intervention when necessary. Further to this, service users’ treatment plans were centred on their most pressing difficulty, given the short-term nature of the intervention. Goals surrounding their difficulty were generated collaboratively and were integral to treatment planning. Following treatment, if it became clear that longer term psychological support would be helpful, people were then signposted or supported in being referred to other services.
Interventions were delivered predominantly by a clinical psychologist, who also supervised the work of two trainee clinical psychologists. Trainees attended regular weekly supervision to discuss individual formulation and treatment plan. The supervisor would also listen back to recorded sessions and complete in vivo observations to provide further feedback on trainees’ therapy work. See Table S1 in the Supplementary material for examples of content covered in sessions according to key ACT processes. The amount of time spent on the processes depended on the person’s progress and individualised formulation. Adaptations were made in line with faith and cultural norms (e.g. management of diabetes during Ramadan).
Treatment descriptives
The average number of sessions delivered was seven, with a range from four sessions to 16 sessions. The median and most common number of sessions delivered was six. Each session lasted approximately one hour.
Psychological wellbeing outcome measures
Patient Health Questionnaire (PHQ-9)
The PHQ-9 is a brief self-reported measure consisting of 9 items to explore severity of depressive symptoms over the last 2 weeks. A cut-off score of >9 indicates presence of depression (Kroenke et al., Reference Kroenke, Spitzer and Williams2001). Severity is indicated by the total score which ranges from 0 to 27 with clinical cut-off points at minimal (0–4), mild (5–9), moderate (10–14), moderately severe (15–19), and severe (20–27). The measure has high internal reliability with Cronbach’s alpha ranging between .85 and .89 (Spitzer et al., Reference Spitzer, Williams and Kroenke2014) and has been validated to be suitable for use in diabetic patients with moderate sensitivity and high specificity (de Joode et al., Reference de Joode, van Dijk, Walburg, Bosmans, van Marwijk and de Boer2019; van Steenbergen-Weijenburg et al., Reference van Steenbergen-Weijenburg, de Vroege, Ploeger, Brals, Vloedbeld, Veneman, Hakkaart-van Roijen, Rutten, Beekman and van der Feltz-Cornelis2010).
Generalised Anxiety Disorder (GAD-7)
The GAD-7 is a brief self-reported measure consisting of 7 items that screens for generalised anxiety disorder and severity of anxiety symptoms over the last 2 weeks. A cut-off score of >7 suggests clinically relevant anxiety (Kroenke et al., Reference Kroenke, Spitzer, Williams, Monahan and Löwe2007). Severity of anxiety symptoms is indicated by the total score ranging from 0 to 21, and the cut-off points include minimal (0–4), mild (5–9), moderate (10–14), and severe (15–21). The measure has high internal reliability with Cronbach’s alpha of 0.89 (Löwe et al., Reference Löwe, Decker, Müller, Brähler, Schellberg, Herzog and Herzberg2008) and has been extensively used in diabetes psychological research (e.g. Schmitt et al., Reference Schmitt, McSharry, Speight, Holmes-Truscott, Hendrieckx, Skinner and Byrne2021; Stahl-Pehe et al., Reference Stahl-Pehe, Selinski, Bächle, Castillo, Lange, Holl and Rosenbauer2022).
Clinical Outcomes in Routine Evaluation 10 (CORE-10)
CORE-10 is a brief self-reported scale consisting of 10 items measuring general psychological distress over the last week. The items explore a range of issues including depression, anxiety, trauma, physical health problems, functioning, and risk to self. The recommended clinical cut-off score for general psychological distress is >10 (Barkham et al., Reference Barkham, Bewick, Mullin, Gilbody, Connell, Cahill and Evans2013). Severity of general psychological distress is indicated by the total score ranging from 0–40. The cut off points include healthy (0–4), low (6–10), mild (11–14), moderate (15–19), moderate-to-severe (20–24), severe (>25). Based on a UK sample, the reported internal reliability of CORE-10 is 0.90 (Barkham et al., Reference Barkham, Bewick, Mullin, Gilbody, Connell, Cahill and Evans2013). However, no studies have thus far evaluated the use of CORE-10 in a sample of individuals with diabetes.
Diabetes specific outcome measures
Problem Areas in Diabetes Scale (PAID)
The PAID is a 20-item self-report scale that measures diabetes-related distress. The items cover a range of commonly reported issues that people with a diabetes diagnosis might face. Based on a factor analysis, the items on the scale can be considered under four factors including treatment problems, food-related problems, emotional problems, and lack of social support (Snoek et al., Reference Snoek, Pouwer, Welch and Polonsky2000). Severity of diabetes-related distress is indicated by the total score ranging from 0 to 100. The clinically relevant cut-off score is >40, indicating severe diabetes-related distress. A score between 17 and 39 indicates moderate diabetes distress and a score between 0 and 16 indicates low diabetes distress (de Wit et al., Reference de Wit, Pouwer and Snoek2022). The PAID has high internal reliability, with Cronbach’s alpha ranging from 0.90 to 0.95 (e.g. Polonsky et al., Reference Polonsky, Anderson, Lohrer, Welch, Jacobson, Aponte and Schwartz1995; Welch et al., Reference Welch, Jacobson and Polonsky1997).
Diabetes Distress Scale (DDS)
The DDS is another commonly used self-report scale consisting of 17 items that measure diabetes-related distress (Polonsky et al., Reference Polonsky, Fisher, Earles, Dudl, Lees, Mullan and Jackson2005). It consists of four subscales examining different kinds of diabetes-specific distress including emotional burden, interpersonal, physician, and regimen distress. A total score of the DDS is obtained by adding all responses and divided by the total number of items, giving a range of 0 to 6. The clinically relevant cut off score is >2.0, indicating moderate distress (Fisher et al., Reference Fisher, Hessler, Polonsky and Mullan2012). Individuals can be classified into three groups: little or no distress (<2.0), moderate distress (2.0–2.9), and high distress (≥3.0). The DDS has high internal reliability, with Cronbach’s alpha of 0.88 (Polonsky et al., Reference Polonsky, Fisher, Earles, Dudl, Lees, Mullan and Jackson2005).
HbA1c
The haemoglobin A1C test (HbA1c) measures the amount of glycated haemoglobin (i.e. amount of glucose attached to haemoglobin in red blood cells). When glucose is not used up from the blood, it is more likely to bind to haemoglobin so high levels of HbA1c can show sustained hyperglycaemia. As blood cells are replaced every 2–3 months, HbA1c tests provide an indication to diabetes management across this timespan. NICE recommends HbA1c is measured every 3–6 months in adults with T1DM, and for T2DM until HbA1c level is stable on unchanging therapy then it should be measured every 6 months (National Institute for Health and Care Excellence, 2015). Target HbA1c levels may vary from person to person but are typically recommended to be below 48 mmol/mol (6.5%) to reduce the risk of long-term complications. Only HbA1c readings that were collected 3–12 months post-therapy were included. This is because HbA1c readings within 0–3 months following the end of treatment may be representative of diabetes management before therapy and/or during the therapy window due to the rate at which blood cells are replaced.
Data analyses
The data was inputted into Microsoft Excel and was organised to identify participants with complete and missing data. Participants with complete data from pre- to post-intervention were then inputted to IBM SPSS version 28 for statistical analyses. Descriptive statistics were obtained. A priori power analyses were run on G*Power, which highlighted a sample size of 35 to detect medium effect (α=0.05, power=0.80, effect size d=0.5). This was met for the analysis of psychological outcomes and HbA1c data. Furthermore, a test of normality was carried out which indicated a non-normal distribution. Thus, non-parametric tests (Wilcoxon’s signed rank test) were used. Due to change of outcome measure, the diabetes-related distress analyses were not powered to detect a moderate effect so descriptive statistics were reported. The effect size was calculated based on Cohen’s r from Pallant (Reference Pallant2007) recommendations.
Results
Participant demographics
Only participants who were recorded to have completed treatment were included in the study. To be included, they must have completed routine outcome measures and/or had a HbA1c reading at the start of treatment, and between 3 and 12 months after treatment; n=56 had complete data on psychological routine outcome measures, and n=38 of those had additional diabetes specific related outcomes. The mean age of this sample was 49.75 years (SD=15.97), and was composed of 20 males and 36 females, with both T1DM (n=24) and T2DM (n=32). The ethnicity of the sample was: White=23%, Black, Black British, Caribbean or African=21%, mixed or other mixed ethnic group=14%, Asian/Asian British=12.5%, other ethnic category=18% and unknown ethnicity =11%. There were n=39 people who completed treatment with the service with available HbA1c data. The mean age of the HbA1c sample was 50.37 years (SD=13.56) and was composed of six males (15%) and 33 females (85%), with both T1DM (n=9, 23%) and T2DM (n=30, 77%). The ethnicity of the sample was: White=21%, Black, Black British, Caribbean or African=23%, mixed or other mixed ethnic group=5%, Asian/Asian British=12.8%, other ethnic category=15%, and unknown ethnicity=23%.
Psychological outcome measures
Full data of all pre- and post-outcomes was available for n=56 individuals (Year 1, n=23; Year 2, n=20, Year 3, n=13) who were included in the analysis. At assessment, the mean sample score for psychological distress using the CORE-10 was 17.79 (SD=7.06), anxiety on the GAD-7 was 12.83 (SD=5.09) and depression on the PHQ-9 was 15.18 (SD=6.3). These scores correspond to moderate levels of depression, anxiety, and general psychological distress at start of treatment.
A Wilcoxon’s signed rank test was used to evaluate differences in scores on outcome measures pre-intervention and post-intervention. The test revealed statistically significant overall reductions in PHQ-9 scores from pre (median=15.50, n=56) to post-intervention (median=8.50 n=56, z=–5.78, p<.001) with an effect size of r=0.55. Forty-six people reported decrease in scores on the PHQ-9, 19 of whom had reductions in scores from clinically significant levels to below clinically significant levels at post-intervention. There were four ranked ties, indicating that four people demonstrated no change in scores. Six people reported increased score post-intervention.
There were statistically significant overall reductions in GAD-7 scores from pre- (median=13.5, n=56) to post-intervention (median=7.00, n=56), z=–5.25, p<.001) with an effect size of r=0.50. Forty-four people reported decreased scores from pre- to post-intervention, 21 of whom had reductions in scores from clinically significant to below clinically significant levels at post-intervention. Four people experienced no change. Eight people reported higher scores post-intervention.
Finally, we observed statistically significant reductions in general distress, as measured by the CORE-10 from pre- (median=19.0, n=56) to post-intervention (median=10.5, n=56, z=–5.55, p<.001) with an effect size of r=0.52. Six people reported increased distress from pre- to post-intervention. Nobody reported the same level of distress before and after treatment. The remaining 50 people reported decreases in levels of general distress, 18 of whom had a reduction in score from clinically significant to below clinically significant levels post-intervention. Table 1 shows the symptom severity changes as a percentage of the sample pre- and post-intervention.
Table 1. Percentage change in outcome measures from pre- to post-treatment
Diabetes specific outcome measures
Full data of pre- and post-intervention outcomes for diabetes-related distress was available for n=38 (Year 1, n=16; Year 2, n=9; Year 3, n=13) who were included in the analysis. The mean age of the sample was 48 years (SD=18.23) and included 13 males (34%) and 25 females (66%), with both T1DM (n=19, 50%) and T2DM (n=19, 50%). The ethnicity of the sample was: White=24%, Black, Black British, Caribbean or African=18%, mixed or other mixed ethnic group=18%, Asian/Asian British=8%, other ethnic category=21%, and unknown ethnicity=11%. Seventeen people had completed the PAID at pre- and post-intervention, and 21 completed the DDS.
Due to the small sample size and consequential lack of power to detect any meaningful differences on both measures, we present below descriptive statistics in Table 2 and the noted trends.
Table 2. Descriptive statistics (mean, standard deviation and range) of the available scores on the DDS and PAID at pre- and post-intervention
At assessment, the mean score for diabetes-related distress as measured on the PAID was 51.54 (SD=15.13), and 3.67 (SD=0.51) for the DDS. All service users were in the severe range of diabetes related distress as measured by the DDS, but varied in severity according to the PAID (severe: n=13; moderate: n=4).
All 21 individuals reported overall reductions in scores on the DDS from pre- to post-intervention; six of those individuals reported reductions in scores from clinically significant levels (i.e. a score >2.00) to little or no diabetes-related distress (i.e. a score <2.00). Fourteen individuals reported overall reductions in scores from pre- to post-intervention, eight of whom reported reductions in scores from significant (i.e. a score >40) to moderate or little diabetes distress (i.e. <40). Three individuals reported an increase in scores (see Table 1).
HbA1c
For analysis of HbA1c data, only people who had HbA1C readings at least 3 months post-therapy were included (n=39). The average HbA1c reading at the beginning of treatment was 92 mmol/mol (range: 50–145 mmol/mol). Following treatment, the average HbA1c reading was 77 mmol/mol (range: 36–121 mmol/mol). The post-intervention reading was taken on average 5.85 months after treatment was completed, ranging from 3 to 12 months.
To evaluate whether there were meaningful differences in scores on the HbA1c reading from pre- to post-intervention, a Wilcoxon’s signed rank test was used. This test was selected due to non-normality. There was a statistically significant reduction in HbA1c levels from pre-intervention (median=92, n=39) to post-intervention (median=73, n=39; z=–3.85, p<.001) with an effect size of r=0.44. Twenty-eight individuals experienced a reduction in HbA1c levels, whereas 11 individuals had an increase in HbA1c levels from pre- to post-intervention. Table 1 shows the percentage of the sample who had a lower glycated haemoglobin level post-intervention and those who increased.
Discussion
Overall, there were two main aims of this service evaluation project. Firstly, we aimed to explore the effectiveness of individual ACT-informed psychological intervention for addressing both psychological and diabetes-specific outcomes. Secondly, we looked to examine if the intervention reduced HbA1c readings, delivered in a naturalistic setting. The aims were achieved by analysing secondary quantitative outcome measures collected at pre- and post-intervention, and through regular blood test results documented on clinical notes.
There were statistically significant reductions in reported levels of depression, generalised anxiety and general psychological distress, with large effect sizes as highlighted by Cohen (Reference Cohen1988). This indicates individualised ACT-informed interventions had a large effect on reducing depression, anxiety and general psychological distress levels amongst people attending the service living with diabetes. The majority of the sample reported a decrease in scores, with 30–40% of individuals showing clinical improvements. Reduction in the level of diabetes distress from pre- to post-intervention as measured by the DDS or the PAID was also observed. Around 92% of the sample reported a decrease in distress, and 76% of those dropped below the clinical cut-off. However, causal inference cannot be drawn as the data are descriptive. It is also important to note that our sample of people with T1DM was smaller than that of people with T2DM. We combined both groups for analysis which in turn led to losing sensitivity in detecting any group differences in relation to outcomes following intervention. A bigger sample size of people living with T1DM and separate group analyses are both necessary to further understand group differences. Given that T1DM and T2DM have different aetiologies and management, further investigation is required to tease apart the impact of ACT interventions on managing associated distress. Our findings were consistent with other studies exploring the effectiveness of ACT-informed therapy for people with diabetes (e.g. Ahmadsaraei et al., Reference Ahmadsaraei, Doost, Manshaee and Nadi2017; Fayazbakhsh and Mansouri, Reference Fayazbakhsh and Mansouri2019). Despite the smaller sample size, our study has scope to add to the research base by providing preliminary evidence that individualised ACT-informed therapy is associated with improvements in psychological wellbeing in our sample of people living with T1DM and T2DM in a naturalistic setting within the context of a community-based NHS service.
The median number of sessions offered was six, which is in keeping with the service’s short-term, brief intervention model. The number of sessions offered was also in line with research that found brief ACT interventions consisting of four sessions resulted in long-term maintenance of decreased depressive symptoms and increased psychological flexibility 5 years post-therapy (Kohtala et al., Reference Kohtala, Muotka and Lappalainen2017). Further robust research is required to understand the effect of brief ACT interventions for other diabetes-related difficulties that people might experience such as diabetes distress. On occasions, treatment length was short due to people dropping out of therapy. Unfortunately, we do not have the data to understand the reasons for why people dropped out. It is important to note that a higher drop-out rate from therapy in a physical health psychological setting can be due to the demands of managing diabetes, as well as general poor physical health that can be barriers to attending appointments (Akhter et al., Reference Akhter, Dockray and Simmons2012). In qualitative studies, people living with T2DM described that non-attendance of structured diabetes education sessions was due to avoidance and experiences of fear, shame, or stigma surrounding diabetes outcomes (Findlay-White et al., Reference Findlay-White, Slevin, Carey and Coates2020; Winkley et al., Reference Winkley, Evwierhoma, Amiel, Lempp, Ismail and Forbes2015). These barriers may also apply to non-attendance and dropping out of psychological therapy. Future studies, or services offering psychological treatment for diabetes related distress, should prioritise keeping up-to-date records of reasons for therapy drop-out.
A small percentage of people reported no changes in symptoms or an increase in symptom severity across the psychological wellbeing and diabetes specific measures following therapy. This could be attributed to the fact that short-term, brief sessions of diabetes-specific ACT-informed therapy were not sufficient to address the accompanying psychosocial stressors that many people living in Croydon experience. Further to this, an increase in distress post-therapy may also be accounted for by the fact that a proportion of the data collected was during the period of ongoing global events, for example, continued restrictions, isolation from social support, and anxiety surrounding the COVID-19 pandemic. For those who self-rated higher scores on outcome measures post-intervention, this could be an increase in symptoms or awareness of symptoms. Another possibility for this could be the increase in ‘psychological flexibility’ – a primary aim of ACT that is actively encouraged (Hayes et al., 2011). An aspect of developing psychological flexibility is increased contact with the present moment, acting in line with values, and willingness to be in contact with difficult internal experiences without changing them, which could explain the increase in self-rated awareness of psychological distress. Therefore, measuring frequency of symptoms may not have fully captured therapeutic progress in ACT (Ong et al., Reference Ong, Sheehan and Haaga2023) and it may be more helpful to incorporate other questionnaires in the future that would measure acceptance-based processes such as the Acceptance and Action Diabetes Questionnaire (AADQ; Gregg et al., Reference Gregg, Callaghan, Hayes and Glenn-Lawson2007) or other measures of psychological flexibility.
Where people became more distressed, the psychologists would bring the case to be discussed in MDT meetings to provide an update of therapy and reflect with the team on other possible contributing factors to deterioration. Depending on the service user’s need, MDT colleagues would offer review appointments to ensure other aspects of their diabetes care are also managed. Further onward referral to other psychological services were made depending on the person’s need and re-referral to our psychology service was considered in the future.
HbA1c results demonstrated a high clinical average on entry to the psychology service and post-treatment compared with the recommended range of below 48 mmol/mol. These results demonstrate a high clinical risk factor for developing long-term complications for people living in Croydon that are accessing community health support. Following intervention, there was a statistically significant decrease in HbA1c readings with moderate effect size outlined by Cohen (Reference Cohen1988). This implies diabetes management improved since starting treatment resulting in a sustained reduction in average blood sugar levels, with most of the sample decreasing (72%). However, 28% of the sample saw an increase in average blood sugar levels which implies a worsening of diabetes management. However, treatment effects on both psychological outcomes and HbA1c readings must be interpreted with caution. Causation cannot be assumed, and patients may have also received input from dieticians, consultant doctors, and specialised diabetes nurses to assist with advice on diet, diabetes education and medication review – that may contribute to an overall improvement in diabetes management and in turn, psychological wellbeing. Additionally, the sample with available HbA1c data was mostly people with T2DM so this may not be representative of people accessing the service with T1DM. Across the study there was a large amount of missing data on clinical notes for HbA1c results within 3 to 12 months post-treatment. Based on NICE guidelines (National Institute for Health and Care Excellence, 2015), people living with diabetes should have blood tests every 3–6 months. This highlights that people who attended the service may not be routinely having blood tests, or it may be evident of potential service issues where blood test results may not be being routinely uploaded to all clinical note systems.
One issue within existing literature is that research studies have largely investigated group-based ACT protocols, thus findings from those studies may not necessarily generalise to the context of individual and formulation driven therapy. In contrast with group-based therapies, individual therapy lacks the aspects of having a community and peer-support. Both aspects are crucial for individuals living with diabetes as it provides a sense of camaraderie, normalises difficult experiences, and provides an opportunity for people to broaden their social network (Penckofer et al., Reference Penckofer, Ferrans, Mumby, Byrn, Emanuele, Harrison and Lustman2012). These in turn could improve mental and physical wellbeing of individuals with diabetes. Furthermore, groups are more cost-effective, which is an important factor to consider given the current NHS context. Despite this, a key advantage of individual over group-based interventions is that they are formulation driven. This allows clinicians to deliver flexible and person-centred interventions that could better account for the needs of individuals presenting with multiple physical health and/or mental health difficulties, including those living with diabetes (Persons et al., Reference Persons, Roberts, Zalecki and Brechwald2006). Evidently, there are benefits and disadvantages to each mode of therapy. Future research could consider comparing the effectiveness of individual ACT-based interventions and group-based interventions for people with diabetes.
Strengths and limitations
One strength of this project is that it is naturalistic. This increases the ecological validity of the findings as we did not include any additional exclusion criteria further to the service’s own referral criteria. Another strength of this project is that it is a realistic reflection of conducting research while setting up a community psychology clinic as a part time clinical psychologist with two trainees on placement. As such, there were difficulties with collecting and managing the magnitude of data that might be routinely collected in more robust research designs such as an RCT. The authors hope that other practitioner psychologists who are in similar positions with increasingly fewer service resources can use both reflected strengths and limitations of this project as a learning point to evaluate their own service; helping them to prioritise which data to routinely collect.
The limitation of a naturalistic design is the lack of controlling for any confounding variables which may lead to an under- or over-estimation of treatment effect. In other words, we were only able to estimate the gross effect of the intervention, and we cannot fully attribute the reduction in symptoms post-therapy as solely the effect of the psychological intervention. Any improvements experienced could be due to a wide range of confounding variables due to the MDT input during treatment phase. To better delineate the ‘noise’ from the data, a waitlist-control group design could be used in the future. Within similarly resourced services, clinicians should consider introducing a tracking sheet to monitor content of each session to help evaluate therapy delivery. This could better measure treatment effectiveness rather than between therapist effects. Additionally, psychologists could keep track of the type of support people received from the MDT during the treatment phase to establish how this predicts improvements in wellbeing.
Analysis of treatment effects was conducted on available data, which is not fully representative of all who accessed the service. Those who completed outcome measures might represent a subset of the client population who are likely to have attended all sessions, whilst those who missed the final sessions where outcome measures were collected, were not included. Those experiencing greater levels of diabetes-related distress and burnout are more likely to be less engaged with clinical services, which might mean that the sample is biased towards those who have greater engagement with services. Similarly, the sample was only representative of those who live in Croydon and cannot be generalised to the wider population.
Conclusions
Overall, the service evaluation project highlighted that individualised ACT-informed interventions delivered in a naturalistic setting were associated with improved symptoms of depression, generalised anxiety, psychological distress, as well as descriptive evidence that interventions were associated with reduced specific diabetes-related distress. The service evaluation showed that treatment was associated with lower HbA1C readings; however, this is observational data and cannot imply direct effects. Further research would need to be conducted to control for additional factors to further understand combined treatment effects from different medical modalities that help improve diabetes management and overall levels of distress.
Key practice points
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(1) This service evaluation project reflected on a range of learning points based on its strengths and limitations. Practitioner psychologists can use these learning points to identify outcomes and data to collect when setting up a new service. For example, we recommend careful consideration of routine outcome measures such as therapy process measures that might shed light on the mechanisms of change even within a naturalistic design study, which might be more realistic of strengthening NHS service evaluation.
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(2) It provides a brief description of the approach across six sessions that can give guidance to clinicians who intend to use an ACT-informed approach to treat people experiencing diabetes-related distress.
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(3) The service evaluation project adds to the gap in literature by evaluating individualised ACT-informed therapy for people living with diabetes. Individualised ACT-informed therapy was associated with improvements in psychological wellbeing and diabetes-related distress for people living with Type 1 or Type 2 diabetes accessing a community NHS diabetes psychology clinic.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S1754470X24000461
Data availability statement
The data that support the findings of this study will be available upon request to the lead author.
Acknowledgements
We would like to thank all service users of the Diabetes Psychology clinic over the last few years and for taking the time to complete outcome measures. We would also like to thank the MDT at Croydon Community Diabetes Service for their continued openness and willingness to learn more about psychology and referring service users to the clinic.
Author contributions
Jason Kai Yu Ho: Formal analysis (equal), Writing - original draft (lead), Writing - review & editing (equal); Kira Williams: Formal analysis (equal), Writing - original draft (supporting), Writing - review & editing (equal); Gemma Knight: Conceptualization (lead), Data curation (lead), Formal analysis (supporting), Methodology (lead), Supervision (lead), Writing - original draft (supporting), Writing - review & editing (supporting).
Financial support
None.
Competing interests
The authors declare none.
Ethical standards
The authors have abided by the Ethical Principles of Psychologists and Code of Conduct as set out by the BABCP and BPS. The project was registered and approved as a Quality Improvement project by Croydon Health Services NHS Trust (Project Number: 151298). Anonymised data from routine outcome measures were collected as part of service users’ entry to service and receiving psychological therapy. This project was a service evaluation utilizing secondary data analysis methodology on an existing data set, thereby not warranting NHS ethics application.
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