We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure [email protected]
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Edited by
Allan Young, Institute of Psychiatry, King's College London,Marsal Sanches, Baylor College of Medicine, Texas,Jair C. Soares, McGovern Medical School, The University of Texas,Mario Juruena, King's College London
This chapter outlines some of the most widely used clinician-rated (e.g., HAM-D, MADRS, YMRS) and self-rated (e.g., BDI, PHQ-9, QIDS, ISS, ASRM) tools for depression and bipolar disorder and summarises the evidence to date on their psychometric properties and practicality for use in research and clinical practice. The chapter also discusses the emerging research surrounding affective instability (AI), a core trait-like feature known to underpin the development and emergence of mood disorder symptoms and describes how digital technologies can aid in the monitoring of both mood and AI. A novel mood-monitoring methodology, called experience sampling method, is introduced and its benefits over traditional approaches are discussed. The chapter concludes with a summary of the current and upcoming mood rating tools, as well as their future role and potential applications in clinical practice.
True Colours is an automated symptom monitoring programme used by National Health Service psychiatric services. This study explored whether patients with unipolar treatment-resistant depression (TRD) found this a useful addition to their treatment regimes. Semi-structured qualitative interviews were conducted with 21 patients with TRD, who had engaged in True Colours monitoring as part of the Lithium versus Quetiapine in Depression study. A thematic analysis was used to assess participant experiences of the system.
Results
Six main themes emerged from the data, the most notable indicating that mood monitoring increased patients' insight into their disorder, but that subsequent behaviour change was absent.
Clinical implications
Patients with TRD can benefit from mood monitoring via True Colours, making it a worthwhile addition to treatment. Further development of such systems and additional support may be required for patients with TRD to experience further benefits as reported by other patient groups.
Mobile mood-monitoring applications are increasingly used by mental health providers, widely advocated within research, and a potentially effective method to engage young people. However, little is known about their efficacy and usability in young populations.
Method
A systematic review addressing three research questions focused on young people: (1) what are the psychometric properties of mobile mood-monitoring applications; (2) what is their usability; and (3) what are their positive and negative clinical impacts? Findings were synthesised narratively, study quality assessed and compared with evidence from adult studies.
Results
We reviewed 25 articles. Studies on the psychometric properties of mobile mood-monitoring applications were sparse, but indicate questionable to excellent internal consistency, moderate concurrent validity and good usability. Participation rates ranged from 30% to 99% across studies, and appeared to be affected by methodological factors (e.g. payments) and individual characteristics (e.g. IQ score). Mobile mood-monitoring applications are positively perceived by youth, may reduce depressive symptoms by increasing emotional awareness, and could aid in the detection of mental health and substance use problems. There was very limited evidence on potential negative impacts.
Conclusions
Evidence for the use of mood-monitoring applications in youth is promising but limited due to a lack of high-quality studies. Future work should explicate the effects of mobile mood-monitoring applications on effective self-regulation, clinical outcomes across disorders and young people's engagement with mental health services. Potential negative impacts in this population should also be investigated, as the adult literature suggests that application use could potentially increase negativity and depression symptoms.
Mobile technology enables high frequency mood monitoring and automated passive collection of data (e.g. actigraphy) from patients more efficiently and less intrusively than has previously been possible. Such techniques are increasingly being deployed in research and clinical settings however little is known about how such approaches are experienced by patients. Here, we explored the experiences of individuals with bipolar disorder engaging in a study involving mood and activity monitoring with a range of portable and wearable technologies.
Method
Patients were recruited from a wider sample of 50 individuals with Bipolar Disorder taking part in the Automated Monitoring of Symptom Severity (AMoSS) study in Oxford. A sub-set of 21 patients participated in a qualitative interview that followed a semi-structured approach.
Results
Monitoring was associated with benefits including increased illness insight, behavioural change. Concerns were raised about the potential preoccupation with, and paranoia about, monitoring. Patients emphasized the need for personalization, flexibility, and the importance of context, when monitoring mood.
Conclusions
Mobile and electronic health approaches have potential to lend new insights into mental health and transform healthcare. Capitalizing on the perceived utility of these approaches from the patients’ perspective, while addressing their concerns, will be essential for the promise of new technologies to be realised.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.