Mood Monitoring Research Articles

A bespoke mobile application for the longitudinal assessment of depression and mood during pregnancy: protocol of a feasibility study

IntroductionDepression is a common mental health disorder during pregnancy, with important consequences for mothers and their children. Despite this, it goes undiagnosed and untreated in many women attending antenatal care....

Using digital mood monitoring technology to support the assessment, engagement and empowerment of young people presenting to mental health services with mood instability

BackgroundDigital mood-monitoring technology, such as mood-monitoring applications, is increasingly advocated within clinical research and is a potentially effective method to engage and empower youth. However, limited evidence is available on this type of technology.Objectives(1) To assess the evidence for the use of mobile mood-monitoring applications in youth; (2) to explore what available smartphone application would be most suitable to monitor mood from the perspective of young people; (3) to examine whether mood-monitoring applications are useful for investigating mood instability in youth; (4) to explore the utility and acceptability of using the mood-monitoring application from young people's and clinicians’ perspectives.AimTo investigate how mood-monitoring applications can be used to support the assessment, engagement and empowerment of young people presenting to mental health services with a range of diagnoses in which mood instability forms a key component.MethodsA systematic review using a Cochrane methodology was conducted. After obtaining ethical approval, this study will also employ a mixed methods approach, through which quantitative findings (e.g., digital mood-monitoring data) will be furnished with an in-depth understanding of young people's views on digital mood-monitoring technology.ResultsFindings from a systematic review focusing on the evidence for the psychometric properties, usability and clinical impacts of applications in youth will be presented. Preliminary results from consultations groups and plans for future research will also be discussed.ConclusionsEvidence acquired through this research can potentially influence mental health policies and result in more innovative (adjunct) interventions and improved outcomes for young people with mood instability.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Experiences of remote mood and activity monitoring in bipolar disorder: A qualitative study

BackgroundMobile 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. MethodPatients 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. ResultsMonitoring 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. ConclusionsMobile 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.

Программа для мониторинга общественных настроений в России на основе сообщений из Twitter

With the popularization of social media, a vast amount of textual content with additional geo-located and time-stamped information is directly generated by human every day. Both tweet meaning and extended message information can be analyzed in a purpose of exploration of public mood variations within a certain time periods. This paper aims at describing the development of the program for public mood monitoring based on sentiment analysis of Twitter content in Russian. Machine learning (naive Bayes classifier) and natural language processing techniques were used for the program implementation. As a result, the client-server program was implemented, where the server-side application collects tweets via Twitter API and analyses tweets using naive Bayes classifier, and the client-side web application visualizes the public mood using Google Charts libraries. The mood visualization consists of the Russian mood geo chart, the mood changes plot through the day, and the mood changes plot through the week. Cloud computing services were used in this program in two cases. Firstly, the program was deployed on Google App Engine, which allows completely abstracts away infrastructure, so the server administration is not required. Secondly, the data is stored in Google Cloud Datastore, that is, the highly-scalable NoSQL document database, which is fully integrated with Google App Engine.

Comparison of sociodemographic and clinical characteristics of bipolar patients with and without seasonal patterns

Objective: Bipolar disorder (BD) affects 1-4% of the population worldwide and presents with seasonal patterns with an incidence of 20-30%. Limited studies exist on seasonality, its relation to sociodemographic and clinical characteristics, and effects on treatment in BD in Turkey. Methods: This retrospective study included 174 patients with a major diagnosis of BD according to the DSM-IV. Comorbidities were determined using the SCID-I. The study was conducted using a semi-structured interview schedule and a mood monitoring chart. The patients were divided into two groups, those with and those without seasonal patterns, and their sociodemographic and clinical characteristics were compared. Results: We found that 36.2% of patients with BD had seasonal patterns. Regardless of type, first episodes were significantly more frequent in the non-seasonal group. With respect to first-episode types, the manic type was significantly more frequent in the seasonal group and the depressive type in the non-seasonal group. The number of patients with a comorbid anxiety disorder (NOS) or dysthymia was significantly higher in the seasonal group and the hospitalized non-seasonal group. The rate of response to lithium monotherapy, mean duration of the disease, mean total number of episodes, and mean total number of mixed episodes were significantly higher in the seasonal group. Conclusion: The rate of dysthymia was significantly higher in the seasonal group, suggesting that those with seasonality have more depressive aspects. These results indicate that the prognosis for seasonal bipolar patients is poorer than for non-seasonal patients. Another important finding was the presence of a correlation between seasonality and a positive response to lithium protection. It has been established that the first episode of the disorder was manifested in the seasonal pattern. The first episode of BD is known to often develop as a depressive episode. These results suggest that it may be a predictor of seasonality.

Electronic monitoring of self-reported mood: the return of the subjective?

This narrative review describes recent developments in the use of technology for utilizing the self-monitoring of mood, provides some relevant background, and suggests some promising directions. Subjective experience of mood is one of the valuable sources of information about the state of an integrated mind/brain system. During the past century, psychiatry and psychology moved away from subjectivity, emphasizing external observation, precise measurement, and laboratory techniques. This shift, however, provided only a limited improvement in the understanding of mood disorders, and it appears that self-monitoring of mood has the potential to enrich our knowledge, particularly when combined with the advances in technology. Modern technology, with its ability to transfer information from the individual directly to the researcher via electronic applications, enables us now to study mood regulation more thoroughly. Frequent subjective ratings can be helpful in identifying individualized treatment with effective mood stabilizers and recognizing subtypes of mood disorders. The variability of subjective ratings may also help us estimate the increased risk of recurrence and guide a tailored treatment.

SMS4dads: Providing information and support to new fathers through mobile phones – a pilot study

ABSTRACTObjective: The objective of this paper was to inform the development of a mobile phone-optimised, SMS-based, informative and interactive telephone-linked support system for new fathers.Methods: The SMS4dads intervention was designed to support fathers with helpful and encouraging text messages, links to relevant web resources, mood monitoring and connection to a crisis telephone support if needed. Forty-six participants were recruited through clinics and social media across Australia. Outcome measures evaluated uptake, user engagement and acceptability.Results: Forty men (87%) remained engaged with the SMS4dads intervention for the full six-week period. Users' feedback indicated that SMS4dads had good acceptability and that the content was helpful. An embedded tool to allow tracking of users' mood was utilised by slightly less than half of the study participants. Concerning levels of psychological distress may have been detected in several participants.Conclusion: The results provide tentative support for the use of mobile phone technology to deliver parenting and mental health information to men in the perinatal period. Participants' engagement and positive responses suggest that this technology could provide a welcome conduit for essential information and support for new fathers, and could potentially be further developed as a feasible medium for collecting information on fathers' levels of psychological distress.

Adherence to a depression self-care intervention among primary care patients with chronic physical conditions: A randomised controlled trial

Objective: Among primary care patients with chronic physical conditions and comorbid depressive symptoms, to assess (1) the effect of lay telephone coaching on adherence to a psycho-educational intervention for depression, (2) demographic characteristics that predict adherence and (3) the association between adherence and 6-month outcomes. Design: Single blind randomised pragmatic trial of a lay telephone-supported depression self-care intervention compared to an unsupported intervention. Methods: All patients received a multimedia toolkit of paper and audiovisual materials on depression that provided education on depression and on self-care for depression. Core tools included a cognitive-behavioural therapy (CBT)-based workbook and a mood monitoring notebook, with opportunities for written exercises and notes, and a video. Intervention group patients were additionally offered telephone coaching. Self-reported use of the materials was assessed at 3 and 6 months post-randomisation; 6-month outcomes were patient satisfaction and change from baseline in depression severity. Results: In all, 223 patients were randomised; 165 (74.0%) completed follow-up. Coached versus uncoached patients reported significantly greater use of the workbook, but not of other tools. Men used more audiovisual tools; women used more paper tools. Self-reported completion of written exercises and a greater number of coach contacts were associated with greater satisfaction, but not with improvement in depression. Conclusion: Telephone coaching can increase adherence to CBT-based tools for depression self-care; however, use of these tools may not improve depression outcomes. Many patients are capable of self-directed use of self-care educational materials. Sex differences in patterns of tool use may be helpful in the targeting of tools.

Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring

Traditional wearable devices have various shortcomings, such as uncomfortableness for long-term wearing, and insufficient accuracy, etc. Thus, health monitoring through traditional wearable devices is hard to be sustainable. In order to obtain healthcare big data by sustainable health monitoring, we design "Smart Clothing", facilitating unobtrusive collection of various physiological indicators of human body. To provide pervasive intelligence for smart clothing system, mobile healthcare cloud platform is constructed by the use of mobile internet, cloud computing and big data analytics. This paper introduces design details, key technologies and practical implementation methods of smart clothing system. Typical applications powered by smart clothing and big data clouds are presented, such as medical emergency response, emotion care, disease diagnosis, and real-time tactile interaction. Especially, electrocardiograph signals collected by smart clothing are used for mood monitoring and emotion detection. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make smart clothing ubiquitous for a wide range of applications.

Psychoeducation and online mood tracking for patients with bipolar disorder: A randomised controlled trial

BackgroundPsychoeducation is an effective adjunct to medications in bipolar disorder (BD). Brief psychoeducational approaches have been shown to improve early identification of relapse. However, the optimal method of delivery of psychoeducation remains uncertain. Here, our objective was to compare a short therapist-facilitated vs. self-directed psychoeducational intervention for BD. MethodsBD outpatients who were receiving medication-based treatment were randomly assigned to 5 psychoeducation sessions administered by a therapist (Facilitated Integrated Mood Management; FIMM; n=60), or self-administered psychoeducation (Manualized Integrated Mood Management; MIMM; n=61). Follow-up was based on patients’ weekly responses to an electronic mood monitoring programme over 12 months. ResultsOver follow-up, there were no group differences in weekly self-rated depression symptoms or relapse/readmission rates. However, knowledge of BD (assessed with the Oxford Bipolar Knowledge questionnaire (OBQ)) was greater in the FIMM than the MIMM group at 3 months. Greater illness knowledge at 3 months was related to a higher proportion of weeks well over 12 months. LimitationsFeatures of the trial may have reduced the sensitivity to our psychoeducation approach, including that BD participants had been previously engaged in self-monitoring. ConclusionsImproved OBQ score, while accelerated by a short course of therapist-administered psychoeducation (FIMM), was seen after both treatments. It was associated with better outcome assessed as weeks well. When developing and testing a new psychosocial intervention, studies should consider proximal outcomes (e.g., acquired knowledge) and their short-term impact on illness course in bipolar disorder.

The Youth-Mental Health Engagement Network: An Exploratory Pilot Study of a Smartphone and Computer-Based Personal Health Record for Youth Experiencing Depressive Symptoms

:The Youth-Mental Health Engagement Network study explored the use of mobile technology to support youth in managing their mental health. The Lawson SMART record (LSR) is a web-based application that allows individuals to create and manage an electronic personal health record (ePHR). Through this record, individuals can store their personal health information (e.g., list of medications, family history, immunization records, allergies, care provider contact information, care plans, and crisis plans) and use interactive tools to manage their health care (e.g., mood monitor, reminder prompts, alerts, and mental health assessments). The purpose of this study was to evaluate the usability and acceptability of using an ePHR in providing mental health care to youth with mental illnesses who were experiencing depressive symptoms, from the perspectives of both the patients and their care providers. This 6-month study employed an exploratory descriptive design. Mixed methods research methodology was used to determine the uptake of the LSR as part of their mental health treatment by youth experiencing depressive symptoms. Participants included 41 patients, aged 16 to 21, receiving outpatient services from one of 9 care providers employed within a hospital-based youth mental health care program. Focus groups were held with participating care providers and patients throughout the study to explore youth and care provider perceptions of using the LSR for mental health care management. In addition, both patients and care providers completed surveys to elaborate on their use of and comfort with the technology. This study found that the majority of patients used a phone (90.6%) and computer (70.7%) daily and felt extremely comfortable using cell phones (71.9%) and computers (58.5%). Of the 41 patients, 9 (22%) had their smartphone lost, stolen, broken, or given away. Qualitative analysis of focus group discussions with patients and care providers revealed 6 themes: 1) extent of LSR use was related to the severity of illness and treatment intensity; 2) symptom tracking was the most common use of the LSR; 3) patients reported increased self-awareness and autonomy with LSR use; 4) use of the LSR changed and had the potential to enhance the therapeutic relationship; 5) use of the LSR was a good fit with Cognitive Behavioural Therapy and Dialectical Behaviour Therapy treatment requirements; and 6) the LSR should be personalized and simplified. In a population of youth with mental illnesses who were experiencing depressive symptoms, the LSR was found to be useful and to fit well with standard treatment practices. However, youth would prefer a simpler tool. Future research should evaluate the clinical- and cost-effectiveness of using an ePHR in a larger sample of youth with mixed clinical presentations and over a longer period of time. This additional research would be valuable in understanding the usability and acceptability of smart technologies as an integral part of usual mental health care for youth.

HIGH-FREQUENCY MONITORING OF COGNITION, MOOD AND BEHAVIOUR USING COMMERCIALLY AVAILABLE WEARABLE DEVICES

HIGH-FREQUENCY MONITORING OF COGNITION, MOOD AND BEHAVIOUR USING COMMERCIALLY AVAILABLE WEARABLE DEVICES

Cloud-assisted Industrial Systems and Applications

In recent years, cloud systems can provide flexible and onneed basis processing of vast amounts of data, as well as provisioning of other value-added services using Internet technologies. Cloud-based approaches will be applicable to all aspects of modern industrial systems, their applications and interactions in the large-scale systems. It is very necessary that more flexible infrastructure is designed to enhance performance, reliability and scalability in complex industrial systems. However, the majority of current cloud systems and the corresponding techniques primarily aim at the internet-based applications. The complex industrial systems give rise to some new issues and challenges to cloud computing since they are significantly different from those service-oriented and internet-based applications due to their inherent features (e.g., workload variations, process control, environment configurations, resource requirements, and life-cycle management, etc.). This special issue features six selected papers with high quality related to cloud-assisted industrial systems and applications. In the first article entitled BSmart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring^, Chen et al., investigate the novel sustainable health monitoring via smart clothing, one of development trends in healthcare industry. The innovative design of smart clothing facilitates unobtrusive collection of various physiological indicators of human body. In order to provide pervasive intelligence for smart clothing system, mobile healthcare cloud platform is constructed by the use of mobile internet, cloud computing and big data analytics. The authors introduce various design details, key technologies and practical implementation methods of smart clothing system. The paper also provides some novel applications powered by the proposed architecture, such as medical emergency response, emotion care, disease diagnosis and real-time tactile interaction. Especially, the ECG signals collected by smart clothing are used for mood monitoring and emotion detection. Finally, the authors highlight some of the design challenges and open issues that still need to be addressed to make smart clothing ubiquitous for a wide range of applications. External resource allocation is a very important issue in cloud-assisted industrial systems and applications because of that to solve the internal resource allocation problem, the user’s needs must first be ascertained to provide the required amount of resources. In previous work, the authors have proposed DEA to analyze the various parameters in the cloud resource allocation problem. However this method is too idealistic. In the paper entitled BLearning-based Data Envelopment Analysis for External Cloud Resource Allocation^, Cho et al. use Q-learning to train the input and output of DEA items so that DEA does not run the whole user’s data for a user every time. In this way, the authors proposed approach can provide an acceptable policy as well as much computation time can be reduced. * Jiafu Wan jiafuwan_76@163.com

PS225. High-frequency monitoring of cognition, mood and behaviour using wearable devices: proof of concept and applications

PS225. High-frequency monitoring of cognition, mood and behaviour using wearable devices: proof of concept and applications

Development of political culture of Kazakhstani students: Political and cultural determinants

Nowadays the problem of political activity and political culture of students has assumed some current character. The following article considers the degree of interest and participation of Kazakhstani youth in the politics and their political orientation in accordance with the results of content- analysis. The content-analysis was held within the framework of scientific project "The development of political culture in students of Kazakhstan as a strategic resource of the country ". The research and the analysis were fulfilled on the base of materials and publications in 15 associations with social-political direction registered in social network. The research period is March - May 2015, in the period of preparations and conducting the extraordinary president elections in the RK. According to the results of the research it was revealed that most Kazakhstani students are equally interested in political processes and show interest in social-political life of the country. Also the results let us reveal the level of social state and students' attitude towards different directions of the government policy, the level of possibility of students' protesting mood. In conclusion the author gives recommendations for organs of government authority to think of the system of organisation of social monitoring of Kazakhstani youth's election mood. By organisation it could be realised on the level of helding social interviewing, focus-teaming and expert interviewing, also by content-analysis of communities registered in social network.Keywords: Kazakhstan student youth, political culture, political activity, determinants of youth political culture, elections, modernization.

Oxford Lithium Trial (OxLith) of the early affective, cognitive, neural and biochemical effects of lithium carbonate in bipolar disorder: study protocol for a randomised controlled trial.

BackgroundDespite lithium’s being the most effective drug for bipolar disorder and in clinical use for decades, we still know very little about its early effects relevant to its mode of action.Methods/designThe Oxford Lithium Trial is a double-blind, randomised, placebo-controlled study of 6-week lithium treatment in participants with bipolar disorder and mood instability. Its aim is to identify early clinical, neurocognitive and biological effects. Participants (n = 40) will undergo an intensive battery of multi-modal investigations, including remote monitoring of mood, activity and physiology, as well as cognitive testing, fMRI and magnetoencephalography, together with biochemical and gene expression measurements to assess renal, inflammatory and circadian effects.DiscussionThe findings derived from this trial may be of value in predicting subsequent therapeutic response or side effects, not only relevant to the use of lithium but also providing a potential signature to help in more rapid evaluation of novel mood stabilisers. In this respect, OxLith is a step towards the development of a valid experimental medicine model for bipolar disorder.Trial registrationISRCTN91624955. Registered on 22 January 2015.

Opportunities for smartphones in clinical care: the future of mobile mood monitoring.

Article AbstractBecause this piece does not have an abstract, we have provided for your benefit the first 3 sentences of the full text.Every day, people are reliant on smartphones to stay connected, organized, and entertained. Every year, smartphones are equipped with more processing power, digital storage, and sensors. As a result of their growing ubiquity and technical advances, there are now exciting opportunities for leveraging these devices in clinical health research, care, and intervention.

Development of political culture of Kazakhstani students: Political and cultural determinants

Nowadays the problem of political activity and political culture of students has assumed some current character. following article considers the degree of interest and participation of Kazakhstani youth in the politics and their political orientation in accordance with the results of content- analysis. content-analysis was held within the framework of scientific project The development of political culture in students of Kazakhstan as a strategic resource of the country . research and the analysis were fulfilled on the base of materials and publications in 15 associations with social-political direction registered in social network. research period is March - May 2015, in the period of preparations and conducting the extraordinary president elections in the RK. According to the results of the research it was revealed that most Kazakhstani students are equally interested in political processes and show interest in social-political life of the country. Also the results let us reveal the level of social state and students' attitude towards different directions of the government policy, the level of possibility of students' protesting mood. In conclusion the author gives recommendations for organs of government authority to think of the system of organisation of social monitoring of Kazakhstani youth's election mood. By organisation it could be realised on the level of helding social interviewing, focus-teaming and expert interviewing, also by content-analysis of communities registered in social network. Keywords: Kazakhstan student youth, political culture, political activity, determinants of youth political culture, elections, modernization.

Applications of time-series analysis to mood fluctuations in bipolar disorder to promote treatment innovation: a case series.

Treatment innovation for bipolar disorder has been hampered by a lack of techniques to capture a hallmark symptom: ongoing mood instability. Mood swings persist during remission from acute mood episodes and impair daily functioning. The last significant treatment advance remains Lithium (in the 1970s), which aids only the minority of patients. There is no accepted way to establish proof of concept for a new mood-stabilizing treatment. We suggest that combining insights from mood measurement with applied mathematics may provide a step change: repeated daily mood measurement (depression) over a short time frame (1 month) can create individual bipolar mood instability profiles. A time-series approach allows comparison of mood instability pre- and post-treatment. We test a new imagery-focused cognitive therapy treatment approach (MAPP; Mood Action Psychology Programme) targeting a driver of mood instability, and apply these measurement methods in a non-concurrent multiple baseline design case series of 14 patients with bipolar disorder. Weekly mood monitoring and treatment target data improved for the whole sample combined. Time-series analyses of daily mood data, sampled remotely (mobile phone/Internet) for 28 days pre- and post-treatment, demonstrated improvements in individuals' mood stability for 11 of 14 patients. Thus the findings offer preliminary support for a new imagery-focused treatment approach. They also indicate a step in treatment innovation without the requirement for trials in illness episodes or relapse prevention. Importantly, daily measurement offers a description of mood instability at the individual patient level in a clinically meaningful time frame. This costly, chronic and disabling mental illness demands innovation in both treatment approaches (whether pharmacological or psychological) and measurement tool: this work indicates that daily measurements can be used to detect improvement in individual mood stability for treatment innovation (MAPP).

Daily mood monitoring of symptoms using smartphones in bipolar disorder: A pilot study assessing the feasibility of ecological momentary assessment

BackgroundPersonal device technology has facilitated gathering data in real-time using Ecological momentary assessment (EMA). We hypothesized that using smartphones to measure symptoms in auto-generated surveys twice a day would be feasible in a group with bipolar disorder (BD). A second exploratory objective of this study was to compare potential differences in core symptoms between BD and healthy control (HC) groups. MethodsA two-arm, parallel group, observational study was designed to measure completion rates of surveys of symptoms of mood, energy, speed of thought, impulsivity, and social stress in BD (N=10) and HC (N=10) participants. The surveys were auto-generated twice a day for fourteen days, and subjects could also perform self-generated surveys. Completion rates were compared between BD and HC groups. Scores were averaged for each participant over the 14 day period, and group medians were compared. ResultsMedian completion rates did not differ between groups: 95% in BD, 88% in HC (p=0.68); the median completion rate of auto-generated surveys in the BD group was 79% and in the HC group was 71% (p=0.22). The BD group had significantly lower median mood score (p=0.043) and energy score (p=0.007) than the HC group. Median scores of speed of thoughts (p=0.739), impulsivity (p=0.123) and social stress (p=0.056) did not significantly differ between BD and HC. The BD group had significantly higher range of variability of group median mood (p=0.043), speed of thoughts (p=0.002) and impulsivity (p=0.005) scores over the course of 14 days than HC, while range of variability of energy (p=0.218) and social stress (p=0.123) scores did not differ. Results were not significantly different between auto-generated and self-generated surveys for BD or HC. LimitationsThis pilot study was conducted for a short time and with a small sample. ConclusionsThis study demonstrates feasibility of using EMA with a smartphone to gather data on BD symptoms.