[ad_1]
In England, around 15.4 million people live with at least one long-term medical condition (LTCs), and nearly a third of these individuals also experience mental health issues like anxiety and depression, worsening their health outcomes and increasing mortality risks (Naylor et al., 2012; Gold et al., 2020; Machado et al., 2018; Moussavi et al., 2007). These coexisting conditions not only impact personal health but also lead to higher healthcare and societal costs due to increased medical expenses and lost productivity (Hutter et al., 2010; Naylor et al., 2012).
Effective mental health interventions are vital, as they could reduce healthcare costs by 20% (Layard & Clark, 2015). Traditional treatments include psychotherapy and pharmacotherapy, in addition to addressing the LTC itself (Gold et al., 2020), however, practical access to these services is often hampered by cost, availability, contraindications, and logistical challenges (Gandy et al., 2018; Gold et al., 2020; May et al., 2001). Even when psychotherapy is received, people with LTCs tend to have poorer therapy outcomes in anxiety and depression compared to those without (Ewbank et al., 2020; Seaton et al., 2022; Wakefield et al., 2021) indicating a need for something more specific to this patient population.
COMPASS, a digital therapy developed at King’s College London, offers a transdiagnostic approach to address both mental and physical aspects of LTCs (Campbell et al., 2000; Moore et al., 2015) providing a new strategy for enhancing patient care and optimising resource use (Carroll et al., 2022; Seaton et al., 2023). This study tested the efficacy of COMPASS against a control group within a population of people experiencing distress from an LTC (Picariello et al, 2024).
15.4 million people in England live with at least one long-term medical condition and a third of these also experience mental health issues.
Methods
The COMPASS study is a randomised controlled study that tested the efficacy of COMPASS, an online CBT program containing 11 modules and 5 support calls with a therapist, with people experiencing distress related to an LTC. 195 adults scoring a 3 or higher on either the depression or anxiety items of the PHQ-4 (Kroenke, Spitzer, Williams, & Löwe, 2009) were recruited from various UK charities and were assessed three times over a period of 12 weeks. After the baseline assessment, participants were randomly assigned to either the COMPASS treatment group or the treatment as usual, which was the standard charity support group (SCS). The researchers conducted a range of assessments aimed at measuring distress, functioning, quality of life, and LTC-specific symptoms, but the primary outcome measure was the Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS) (Kroenke et al., 2016).
Results
Researchers successfully recruited 194 participants to take part in the randomised controlled study. The sample was predominantly female and white with a mean age of 40.9 (S.D. = 12.7) in the COMPASS treatment group and 41 (S.D. = 13.7) in the control group. At baseline, 72.7% of the sample fell into the moderate or severe anxiety or depression or both based on their scores on PHQ-9 (Kroenke & Spitzer, 2002) and GAD-7 (Spitzer, Kroenke, Williams, & Löwe, 2006) scores, and had at least one LTC, leading to a representation of multiple body systems in the sample.
The follow-up rates showed promising engagement, with 73.7% of participants completing assessments at 6 weeks and 83.5% at 12 weeks. Notably, the COMPASS arm experienced a higher attrition rate at 12 weeks (24.5%) compared to the standard charity support (SCS) arm (9.0%).
The primary outcome measure revealed significant benefits for those in the COMPASS arm, with distress levels at 12 weeks being significantly lower (6.82 points; p < 0.001) compared to the control group, and 88.7% of COMPASS participants reporting a clinically meaningful improvement compared to 45.1% in the SCS arm.
Secondary outcomes further underscored COMPASS’s impact, with medium to large significant treatment effects observed across several measures including depression, anxiety, and illness-related distress. While the improvements in daily functioning and quality of life were modest, they still favoured COMPASS, reinforcing the program’s comprehensive approach to addressing psychological distress in LTCs. Sensitivity analyses confirmed the robustness of these findings, suggesting that the beneficial effects of COMPASS were consistent across different scenarios concerning missing data.
The COMPASS treatment group experienced significant improvements in psychological distress, anxiety, depression, quality of life and functioning.
Conclusions
The COMPASS program, a digital cognitive-behavioural therapy, has been effective in significantly improving mental health outcomes for individuals with long-term conditions. It successfully addresses anxiety, depression, and distress, showcasing its broad applicability across various LTCs. Despite challenges like varied adherence and potential attrition bias, COMPASS demonstrates promising scalability and efficacy, especially for those with moderate to severe symptoms. This advancement highlights a novel approach to mental health care delivery, potentially easing the burden on healthcare services by offering an effective, digital treatment option for psychological distress associated with LTCs.
This is a novel approach to mental health care delivery, potentially easing the burden on healthcare services by offring an effective, digital treatment option for those with long term conditions.
Strengths and limitations
The strengths of the study design and implementation are highlighted by its adherence to the CONSORT guidelines, which ensures a standardised and transparent approach to reporting RCTs. The study’s methodology of two-armed parallel groups, outcomes assessed at multiple time points (baseline, 6-weeks, and 12-weeks), and the use of standardised outcome measures such as the PHQ-ADS, underpins the reliability and validity of its findings. The broad eligibility criteria and the inclusion of participants from a range of LTCs spanning various body systems and different disease progression at presentation add to the generalisability of the results. The randomisation process, which was conducted using an independent Qualtrics randomiser and stratified by LTC, alongside the use of a separate Qualtrics account for randomisation and RedCap for outcome assessment to maintain blinding of the data analyst, are key strengths that minimise bias and enhance the credibility of the study findings.
However, the study’s reliance on self-reported measures for outcomes and adherence, despite being common and unavoidable in psychological research, may be subject to response bias. The drop-out rate being higher in the COMPASS arm compared to the control group could indicate either issues with engagement or satisfaction with the COMPASS intervention, it is left to the reader to make sense of this. The lower adherence rates observed among participants with certain LTCs, such as Chronic Kidney Disease, suggest that while the transdiagnostic approach has broad applicability, it may still benefit from incorporating some disease-specific content to enhance relevance and engagement for all user groups. This points to a potential area for further refinement of COMPASS, ensuring that it fully meets the needs of a diverse patient population and maximises its effectiveness. Furthermore, the study’s sample, predominantly female and white, might limit the applicability of the findings across more diverse populations.
This was a well-conducted RCT that adheres to CONSORT guidelines.
Implications for practice
The transdiagnostic approach of COMPASS represents a significant advantage over mental health disease-specific interventions. By encompassing a wider range of conditions and symptoms, COMPASS offers a more inclusive and potentially more efficient treatment solution that could be more easily integrated into healthcare systems. This approach aligns with the growing recognition of the interconnectedness of mental health symptoms and the need for treatments that can address multiple aspects of a patient’s psychological well-being.
In addition, the program’s online delivery format and the support provided by therapists through a minimal number of sessions, can facilitate access for patients who may face barriers to traditional face-to-face therapy, including geographical limitations, physical mobility constraints, and time constraints.
This study serves as a good example of the potential of a centralised delivery pathway for psychological treatments, which could streamline access to care and enhance treatment delivery efficiency. This model, facilitated through a national hub and self-referral via charities, represents a novel approach to healthcare delivery that not only ensures the continuity of care during challenging times, as the authors suggested, but also offers a blueprint for expanding access to psychological therapies of a similar type in the future. It not only offers an alternative to the traditional primary or secondary care pathways but also provides a solution to the increasing demand for mental health services, particularly in a time when the healthcare sector is stretched thin by crises like the COVID-19 pandemic. Implementing such interventions in similar pathways could alleviate the demand on healthcare services and provide a cost-effective means of delivering psychological support to a wider population. The fact that the intervention is transdiagnostic means that self-referral based on feelings of distress alone is possible to access this programme, rather than a formal diagnosis necessitating the long waitlists of the overstretched NHS and multiple assessments.
The effectiveness of COMPASS across various degrees of psychological distress, including moderate to severe symptoms, suggests that digital therapy can serve a broader demographic than traditionally targeted by low-intensity treatments. This challenges existing treatment thresholds and indicates that individuals with more severe forms of depression and anxiety might also benefit from digital interventions with minimal therapist involvement.
Offering this therapy via self-referral via charities presents a novel approach to healthcare delivery which may alleviate the pressures on the healthcare system at present.
Statement of interests
The author declares having no conflicts of interest that could have influenced the work reported in this paper.
Links
Primary paper
Picariello, F., Hulme, K., Seaton, N., Hudson, J. L., Norton, S., Wroe, A., & Moss-Morris, R. (2024). A randomized controlled trial of a digital cognitive-behavioral therapy program (COMPASS) for managing depression and anxiety related to living with a long-term physical health condition. Psychological Medicine, 1–14. doi:10.1017/S0033291723003756
Other references
Carroll, S., Moon, Z., Hudson, J., Hulme, K., & Moss-Morris, R. (2022). An evidence-based theory of psychological adjustment to long-term physical health conditions: Applications in clinical practice. Psychosomtic Medicine, 84(5), 547–559. doi:10.1097/psy.0000000000001076.
Campbell, M., Fitzpatrick, R., Haines, A., Kinmonth, A. L., Sandercock, P., Spiegelhalter, D., & Tyrer, P. (2000). Framework for design and evaluation of complex interventions to improve health. BMJ: British Medical Journal, 321(7262), 694–696. doi:10.1136/bmj.321.7262.694.
Ewbank, M. P., Cummins, R., Tablan, V., Bateup, S., Catarino, A., Martin, A. J., & Blackwell, A. D. (2020). Quantifying the association between psychotherapy content and clinical outcomes using deep learning. JAMA Psychiatry, 77(1), 35–43. doi:10.1001/jamapsychiatry.2019.2664.
Gandy, M., Karin, E., Fogliati, V. J., Meares, S., Nielssen, O., Titov, N., & Dear, B. F. (2018). Emotional and cognitive difficulties, help-seeking, and barriers to treatment in neurological disorders. Rehabilitation Psychology, 63(4), 563–574. doi:10.1037/rep0000241.
Gold, S. M., Köhler-Forsberg, O., Moss-Morris, R., Mehnert, A., Miranda, J. J., Bullinger, M., … Otte, C. (2020). Comorbid depression in medical diseases. Nature Reviews Disease Primers, 6(1), 1–22. doi:10.1038/s41572-020-0200-2.
Hutter, N., Schnurr, A., & Baumeister, H. (2010). Healthcare costs in patients with diabetes mellitus and comorbid mental disorders—a systematic review. Diabetologia, 53(12), 2470–2479. doi:10.1007/s00125-010-1873-y.
Kroenke, K., & Spitzer, R. L. (2002). The PHQ-9: A new depression diagnostic and severity measure. Psychiatric Annals, 32(9), 509–515.
Kroenke, K., Spitzer, R. L., Williams, J. B., & Löwe, B. (2009). An ultra-brief screening scale for anxiety and depression: The PHQ–4. Psychosomatics, 50(6), 613–621.
Kroenke, K., Wu, J., Yu, Z., Bair, M. J., Kean, J., Stump, T., & Monahan, P. O. (2016). The patient health questionnaire anxiety and depression scale (PHQ-ADS): Initial validation in three clinical trials. Psychosomatic Medicine, 78(6), 716–727. doi:10.1097/PSY.0000000000000322.
Layard, R., & Clark, D. M. (2015). Why more psychological therapy would cost nothing. Frontiers in Psychology, 6, 1713. doi:10.3389/fpsyg.2015.01713.
Machado, M. O., Veronese, N., Sanches, M., Stubbs, B., Koyanagi, A., Thompson, T., … Schuch, F. B. (2018). The association of depression and all-cause and cause-specific mortality: An umbrella review of systematic reviews and meta-analyses. BMC Medicine, 16(1), 1–13. doi:10.1186/s12916-018-1101-z.
May, C., Gask, L., Atkinson, T., Ellis, N., Mair, F., & Esmail, A. (2001). Resisting and promoting new technologies in clinical practice: The case of telepsychiatry. Social Science & Medicine, 52(12), 1889–1901. doi:10.1016/s0277-9536(00)00305-1.
Moore, G., Audrey, S., Barker, M., Bond, L., Bonell, C., Hardeman, W., … Wight, D. (2015). Process evaluation of complex interventions: Medical Research Council guidance. British Medical Journal, 350, h1258. doi:10.1136/bmj.h1258.
Moussavi, S., Chatterji, S., Verdes, E., Tandon, A., Patel, V., & Ustun, B. (2007). Depression, chronic diseases, and decrements in health: Results from the World Health Surveys. The Lancet, 370(9590), 851–858. doi:10.1016/S0140-6736(07)61415-9.
Naylor, C., Parsonage, M., McDaid, D., Knapp, M., Fossey, M., & Galea, A. (2012, February 01). Long-term conditions and mental health: the cost of co-morbidities.
Seaton, N., Moss-Morris, R., Hulme, K., Macaulay, H., & Hudson, J. (2023). A cognitive–behavioural therapy programme for managing depression and anxiety in long-term physical health conditions: Mixed-methods real-world evaluation of the COMPASS programme. BJPsych Open, 9(5), e153. doi:10.1192/bjo.2023.519.
Seaton, N., Moss-Morris, R., Norton, S., Hulme, K., & Hudson, J. (2022). Mental health outcomes in patients with a long-term condition: Analysis of an Improving Access to Psychological Therapies service. BJPsych Open, 8(4), e101. doi:10.1192/bjo.2022.59.
Spitzer, R. L., Kroenke, K., Williams, J. B., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. doi:10.1001/archinte.166.10.1092.
Wakefield, S., Kellett, S., Simmonds-Buckley, M., Stockton, D., Bradbury, A., & Delgadillo, J. (2021). Improving Access to Psychological Therapies (IAPT) in the United Kingdom: A systematic review and meta-analysis of 10-years of practice-based evidence. British Journal of Clinical Psychology, 60(1), 1–37. doi:10.1111/bjc.12259.
Photo credits
[ad_2]
Source link