UK National Schizophrenia Awareness Day 2022 – A mental illness in need of destigmatization

UK National Schizophrenia Awareness Day 2022 – A mental illness in need of destigmatization

by | Jul 25, 2022 | Blog, Children and Adolescents

July 25th is National Schizophrenia Awareness Day in the UK, aiming at shining light on “what it means to live with this much misunderstood and often stigmatized mental health condition”, fighting prejudice surrounding it, as well as seeking to raise awareness of and support for its treatment [1].

What is schizophrenia?
Individuals with schizophrenia experience disruptions in their thought processes and perceptions, as well as in social interactions and emotional responsiveness. The mental illness, usually including psychotic symptoms such as delusions and hallucinations, can be highly disabling to people suffering from it [2].

Economic costs of schizophrenia
Worldwide, around 24 million people are currently diagnosed with schizophrenia [3] – in the UK it is over 685.000 people (approximately 1% of the population) [4].
Schizophrenia has a large economic cost. It accounts for approximately “30% of all spending on adult mental health in the NHS” [5], estimated at 11.8 million GBP in England alone in 2012 [6]. Generally, it costs around 6 times as much to treat an individual with schizophrenia over its lifetime than it costs to treat a heart disease patient [5].

Stigmatization of schizophrenia
Schizophrenia affects all genders and individuals from all social backgrounds, and onsets most often in the late teenage years or in the early twenties [5]. The mental illness severely impacts affected peoples’ quality of life. In the UK, only around 13% of individuals suffering from schizophrenia are working [5], and it has been found that affected people are “2 to 3 times more likely to die early than the general population” [3]. Schizophrenia is also a significant burden that impacts productivity of family caregivers, who on average spend 22 hours a week for 15 years of their life taking care of their relative with schizophrenia.
Additionally, stigma against people suffering from the condition is still “intense and widespread” today [3]. Individuals with schizophrenia oftentimes experience social exclusion, and/or discrimination due to the disease, and some even experience limited “access to general health care, education, housing, and employment” [3]. According to the World Health Organization (2022), these issues often only exacerbate the suffering peoples’ symptoms [3].

What needs to change?
Schizophrenia is not as rare as one might think, and prejudices surrounding the illness unfortunately only further increase the burden of the disease on people suffering from it. It is therefore important to raise awareness about schizophrenia, destigmatize the mental illness, and help to ensure that individuals with schizophrenia are not facing discrimination. Given the high economic costs of schizophrenia, it is also important to continuously work on improving the treatment support provided. This includes seeking for new ways to help individuals suffering from the mental health condition.

How digital solutions for mental health can help
The use of digital platforms for remote patient monitoring and health assessment, as well as real-time patient analytics, could enable personalised treatment and improved quality of care [7]. Digital solutions for mental health could therefore offer the potential to empower and engage individuals with schizophrenia to better manage their mental health, facilitating treatment for clinical professionals and empowering family caregivers to help drive down economic costs and increase productivity.
At Monsenso, we have worked with schizophrenia in both research and clinical settings. Our digital mental health solution has helped many individuals with schizophrenia to better understand their conditions and live a more independent life, as well as helped clinicians to better support their patients. We are proud to support the National Schizophrenia Awareness Day in the UK and will continue to spread knowledge about the mental health condition and offer our support to individuals affected and clinicians providing treatment for the mental illness.
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About Monsenso
Monsenso is an innovative technology company offering a digital health solution used for decentralised trials, remote patient monitoring and treatment support. Our mission is to contribute to improved health for more people at lower costs by supporting treatment digitally and leveraging patient-reported outcomes data. Our solution helps optimise the treatment and gives a detailed overview of an individual’s health through the collection of outcome, adherence, and behavioural data. It connects individuals, carers, and health care providers to enable personalised treatment, remote care, and early intervention. We collaborate with health and social care, pharmaceuticals, and leading researcher worldwide in our endeavours to deliver solutions that fit into the life of patients and health care professionals. To learn more visit  www.monsenso.com.

References:
[1] Awareness Days (n.d.). National Schizophrenia Awareness Day 2022.
https://www.awarenessdays.com/awareness-days-calendar/national-schizophrenia-awareness-day-2022/#:~:text=National%20Schizophrenia%20Awareness%20Day%2C%20marked,with%20a%20diagnosis%20of%20schizophrenia.

[2] National Institute of Mental Health (n.d.). Schizophrenia.
https://www.nimh.nih.gov/health/statistics/schizophrenia#:~:text=Schizophrenia-,Definition,be%20both%20severe%20and%20disabling.

[3] World Health Organization (2022). Schizophrenia.
https://www.who.int/news-room/fact-sheets/detail/schizophrenia#:~:text=Schizophrenia%20affects%20approximately%2024%20million,%25

[4] Royal College of Psychiatrists (2015). Schizophrenia.
https://www.rcpsych.ac.uk/mental-health/problems-disorders/schizophrenia

[5] Living With Schizophrenia (2017). Facts and Figures.
https://livingwithschizophreniauk.org/facts-and-figures/

[6] Ride, J., Kasteridis, P., Gutacker, N., Aragon Aragon, MJ., Jacobs, R. (2020). Healthcare Costs for People with Serious Mental Illness in England: An Analysis of Costs Across Primary Care, Hospital Care, and Specialist Mental Healthcare. Appl Health Econ Health Policy 18(2):177-188.
doi: 10.1007/s40258-019-00530-2.

[7] Elsevier Health (2022). Clinician of the Future Report 2022.
https://www.elsevier.com/connect/clinician-of-the-future

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Top pain points in the delivery of mental healthcare and how digital technology can help

Top pain points in the delivery of mental healthcare and how digital technology can help

by | Jun 29, 2022 | Blog, Mental Illness, mHealth, Patient Engagement

Close to 1 in 7 people suffer from a mental health condition [1], a leading cause of disability globally [2].
However, 75% of people with mental illnesses do not receive any treatment [3], highlighting the issue of access to mental healthcare, which has only been exacerbated by Covid.

The shortage of trained professionals in mental healthcare is a key contributor to the issue of access [4]. Patients are faced with long waiting queues to receive care [5], with no promise of quality care, given clinicians’ heavy caseload [4]. It is not uncommon that patients only receive 5 mins of clinicians’ time after months of waiting for the appointment [6]. Indeed, a large study by Elsevier Health (2022), involving over 2800 clinicians and nurses from 111 markets, found that almost 1 in 2 of clinicians globally (69% in Europe) admit that time they are able to devote to each individual patient is insufficient “to give them good care” [4].

Clearly, there are plenty of opportunities to improve patients’ access, speed to, and quality of care globally. Promisingly, the same study found that over half of the clinicians (56%) state that patients have become more empowered to manage their own conditions, and that clinicians (62%) expect a change in role towards being more in partnership with patients over the next decade. Given that mental health costs a whopping $16 trillion to the global economy by 2030 [7] and growing, there is an urgent need for solutions that are designed to tackle these issues in a scalable and cost-effective way.

The use of digital technology offers the potential to address this matter. In particular, the use of digital platforms for remote patient monitoring and health assessment could improve access and speed to care, and real-time patient analytics could enable personalised treatment and improved quality of care [4]. Ultimately, to fully benefit from such technology, patient data needs to be managed securely, the design of the solution should focus on the needs of its users, and it should be continually assessed on its ability to deliver value to patients and clinicians.

About Monsenso:
Monsenso is an innovative technology company offering a digital health solution used for decentralised trials, remote patient monitoring and treatment support. Our mission is to contribute to improved health for more people at lower costs by supporting treatment digitally and leveraging patient-reported outcomes data. Our solution helps optimise the treatment and gives a detailed overview of an individual’s health through the collection of outcome, adherence, and behavioural data. It connects individuals, carers, and health care providers to enable personalised treatment, remote care, and early intervention. We collaborate with health and social care, pharmaceuticals, and leading researcher worldwide in our endeavours to deliver solutions that fit into the life of patients and health care professionals. To learn more visit  www.monsenso.com.

References:
[1] World Health Organization (2020). World Mental Health Day: an opportunity to kick-start a massive scale-up in investment in mental health.
https://www.who.int/news/item/27-08-2020-world-mental-health-day-an-opportunity-to-kick-start-a-massive-scale-up-in-investment-in-mental-health#:~:text=Mental%20health%20is%20one%20of,every%2040%20seconds%20by%20suicide.

[2] Wainberg, M. L., Scorza, P., Shultz, J. M., Helpman, L., Mootz, J. J., Johnson, K. A., Neria, Y., Bradford, J. E., Oquendo, M. A., & Arbuckle, M. R. (2017). Challenges and Opportunities in Global Mental Health: a Research-to-Practice Perspective. Current psychiatry reports 19(5): 28. https://doi.org/10.1007/s11920-017-0780-z.

[3] Marchildon, J. (2020). 4 Barriers to Accessing Mental Health Services Around the World.
https://www.globalcitizen.org/en/content/barriers-to-mental-health-around-the-world/.

[4] Elsevier Health (2022). Clinician of the Future Report 2022.
https://www.elsevier.com/connect/clinician-of-the-future.

[5] Royal College of Psychiatrist (2020). Two-fifths of patients waiting for mental health treatment forced to resort to emergency or crisis services.
https://www.rcpsych.ac.uk/news-and-features/latest-news/detail/2020/10/06/two-fifths-of-patients-waiting-for-mental-health-treatment-forced-to-resort-to-emergency-or-crisis-services.

[6]. Becker, G., Kempf, D.E., Xander, C.J. et al. (2010). Four minutes for a patient, twenty seconds for a relative – an observational study at a university hospital. BMC Health Serv Res 10(94).
https://bmchealthservres.biomedcentral.com/articles/10.1186/1472-6963-10-94.

[7] Lancet Commission. (2018). Report: Mental illness will cost the world $16 trillion (USD) by 2030. Mental Health Weekly 28(39): 1–8. https://doi.org/10.1002/mhw.31630.

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New research: Can smartphone data be a digital marker for discriminating bipolar disorder from unipolar disorder?

New research: Can smartphone data be a digital marker for discriminating bipolar disorder from unipolar disorder?

by | Apr 13, 2022 | Bipolar, Blog, mHealth

Unipolar disorder (UD) refers to individuals suffering from depression without experiencing mania, whereas individuals suffering from bipolar disorder (BD) usually face episodes of mania in addition to their depression [1]. Clinicians often encounter difficulties identifying whether depressed patients suffer from BD or UD. Given that the course of illness and related treatments vary for patients with BD and UD, the discrimination between these two disorders is critical [2].

A new research paper has just been published on “Differences in mobility patterns according to machine learning models in patients with bipolar disorder and patients with unipolar disorder” in the Journal of Affective Disorders [2].

This new research investigated whether using the information on activity and mobility of patients with BD and UD as supplementary objective measure could assist in the discrimination between the two conditions [2]. Data for this study has been collected as part of the RADMIS trials, two similarly composed randomized controlled trials (RCTs) that investigated the effect of daily smartphone-based monitoring including a clinical feedback loop in individuals suffering from BD and UD. The Monsenso digital health solution was used for the collection of smartphone-based patient data in the intervention group of the trials [3].

The present study included gathering both passively collected smartphone-based location data and patient-reported smartphone-based data on mood from 65 patients with BD and 75 patients with UD [2]. Smartphone-based self-assessments of mood were completed by all patients, and smartphone data on location reflecting mobility patterns, routine and location entropy (chaos) was collected passively from all patients on a continuous basis over the course of six months [2]. The data collection was followed by an extensive data analysis, comparing differences between the two groups.

Results of the study show patients suffering from BD have significantly lower mobility in, e.g., their total time of daily movement during depressive periods (eB 0.74, 95% CI 0.57; 0.97, p = 0.027). Additionally, the area under the curve (AUC) of location data was rather high in classifying patients with BD compared with patients with UD, although results of the study may be limited by relatively low symptom severity of the participating patients contributing to the dimension of the AUC [2].

The study results suggest alterations in location data may be a promising digital diagnostic marker in patients with BD and UD, and smartphone data on mobility patterns could hence help in discriminating between the two disorders. 

Mads Frost, PhD, Co-Founder & Chief Information Security Officer at Monsenso, who has contributed to the research says: “The work on comparing mobility patterns between patients with bipolar disorder and patients with unipolar disorder has been highly interesting, and we look forward to further explore our data looking for potential digital diagnostic markers”.

 “We are excited that Monsenso is a part of promising new research on digital diagnostic markers, and contributes to the research in and the treatment of mental health and neurological disorders”, says Thomas Lethenborg, CEO at Monsenso.

About Monsenso:
Monsenso is an innovative technology company offering a medical grade digital health solution. Our mission is to help provide better mental health to more people at lower costs. Our solution helps optimise the treatment of mental disorders and gives a detailed overview of an individual’s mental health through the collection of outcome, adherence, and behavioural data. It connects individuals, carers, and health care providers to enable personalised treatment, remote care, and early intervention. Based on continuous research and development, our team is committed to developing solutions that fit seamlessly into the lives of individuals, increase their quality of life and improve the efficacy of mental health treatment. To learn more, visit www.monsenso.com

Research publication:
You can find the research publication in the Journal of Affective disorders here.

References:
[1] Quilty, L., Pelletier, M., DeYoung, C.G. & Bagby, M. (2013). Hierarchical personality traits and the distinction between unipolar and bipolar disorders. Journal of Affective Disorders 147(1-3): 247-254. https://www.sciencedirect.com/science/article/pii/S0165032712007604#bib2

[2] Faurholt-Jepsen, M., Busk, J., Rohani D.A., Frost, M. Tønning, M.L., Bardram, J.E. & Kessing, L.V. (2022). Differences in mobility patterns according to machine learning models in patients with bipolar disorder and patients with unipolar disorder. Journal of Affective Disorders 306: 246-253. https://www.sciencedirect.com/science/article/pii/S0165032722003019?dgcid=author

[3] Faurholt-Jepsen, M., Tønning, M.L., Frost, M., Martiny, K., Tuxen, N., Rosenberg, N., Busk, J., Winther, O., Thaysen-Petersen, D., Aamund, K.A. & Tolderlund, L., Bardram, J.E. & Kessing, L.V. (2020). Reducing the rate of psychiatric re-admissions in bipolar disorder using smartphones—The RADMIS trial. Acta Psychiatrica Scandinavia, 143(5): 453-465. https://onlinelibrary.wiley.com/doi/10.1111/acps.13274

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Improving the treatment of bipolar disorder with mobile health technology

Improving the treatment of bipolar disorder with mobile health technology

by | Dec 3, 2015 | Bipolar, mHealth

Bipolar disorder, also known as manic-depressive illness, is a brain disorder that causes unusual shifts in mood, energy, activity levels, and the ability to carry out day-to-day tasks. [1]

People suffering from bipolar disorder will have periods or episodes of depression – where they feel very low and lethargic mania – where they feel high and overactive. [2]

Unlike simple mood swings, each episode of bipolar disorder can last for several weeks and some people may not experience a “normal” mood very often. [2]

Getting an accurate diagnosis is the first step in bipolar disorder treatment. However, this isn’t always easy. The mood swings of bipolar disorder can be difficult to distinguish from other problems such as major depression, ADHD, and borderline personality disorder. For many people suffering from bipolar disorder, it takes years and numerous doctor visits before the problem is correctly identified and treated. [3]

Indicators of bipolar disorder:

  • Repeated episodes of major depression
  • First episode of major depression was experienced before age 25
  • First-degree relative suffering from bipolar disorder
  • Mood and energy levels are higher than most people’s when not depressed
  • Oversleeping and overeating when depressed
  • Episodes of major depression are shorter than 3 months
  • Lost contact with reality while depressed
  • Suffered from postpartum depression in the past
  • Developed mania or hypomania while taking antidepressants
  • Antidepressants stopped working after several months
  • Tried three or more antidepressants without success [3]

If a person is not treated, episodes of bipolar-related mania can last for between three to six months. Episodes of depression tend to last longer, for between six and twelve months. However, with effective treatment, episodes usually improve within about three months. [2]

Most people with bipolar disorder can be treated using a combination of different treatments that can include:

  • Medication such as mood stabilisers and antidepressants
  • Learning to recognize triggers and early warning signs of an episode of depression or mania
  • Psychotherapy to deal with depression and provide advice on how to improve relationships
  • Lifestyle advice such as doing regular exercise, planning activities you enjoy that give you a sense of achievement, and advice on improving your diet and getting more sleep [2]

Mobile health technology

The Monsenso mHealth platform is based on The MONARCA Research Project, aimed at developing and validating a solution for multi-parametric, long-term monitoring of behavioral and physiological information relevant to bipolar disorder.

The Monsenso solution can help predict and prevent episodes by training patients to recognize their early warning signs, which are symptoms that indicate an oncoming episode [4].

In particular, during the research project, it was discovered that these three parameters are crucial in keeping a bipolar patient stable:

  • Adherence to prescribed medication: Taking all medications on a daily basis, exactly as prescribed.
  • Stable sleep patterns: Sleeping eight hours every night and maintaining a consistent routine of going to bed, waking up.
  • Staying active both physically and socially: Getting out of the house every day, going to work, and engaging in social interaction.

Therefore, the Monsenso solution includes five core features that support a patient’s self-management:

  • Self-assessments – Reminded by an alarm, patients enter subjective data directly into the system through their smartphones. This data includes mood, sleep, level of activity, and medication. Some items can be customized to accommodate a patient’s specific needs, while others are consistent to provide statistical analysis.
  • Activity monitoring – Through a GPS and accelerometer, objective data is collected to monitor a patient’s level of engagement in daily activities. The system can also measure the amount of social activity based on phone calls and text messages.
  • Historical overview of data – On the web portal, patients and clinicians can obtain a two-week snapshot of a patient’s basic data for immediate feedback. The portal also gives them access to a detailed historical overview of the data, enabling them to explore it in depth by going back in time, and focusing on specific variables.
  • Coaching and self-treatment – The MONARCA systems supported psychotherapy in two ways. Firstly, through customizable triggers that notify the patient and clinician when the data potentially indicates a warning sign. Second, since the patients have access to their own Early Warning Signs, it empowers them to learn more about them.
  • Data sharing – To strengthen the relationship between patients and clinicians, important information and treatment decisions are shared.

Resources:

[1] What is bipolar disorder? National Institute of Mental Health. http://www.nimh.nih.gov/health/topics/bipolar-disorder/index.shtml

[2] Bipolar disorder. National Health Service (NHS) UK. http://www.nhs.uk/Conditions/Bipolar-disorder/Pages/Introduction.aspx

[3] Bipolar disorder treatment. HelpGuide.org http://www.helpguide.org/articles/bipolar-disorder/bipolar-disorder-treatment.htm