Mood Monitoring Research Articles

AN EFFECTIVE MANAGEMENT OF BIPOLAR DISORDER: A CLINICAL CASE STUDY

Bipolar disorder is characterized by manic, hypo-manic and depressive episodes. This case study describes how psychosocial factors lead to psychological illnesses, which then impairs individual’s social, occupational and other areas of functioning. The client H.K. was 22 years old boy, unmarried, educated up to middle, was 2nd born among 3 siblings and lived in a nuclear family. He was brought to the Lahore general hospital by the end of May, 2019 with the presenting complaints of self talk, labile mood, forgetfulness, poor sleep and appetite, flight of ideas and anger. Informal assessment was done through behavioral observations, mental status observation, clinical interview, baseline charts, and subjective rating of symptoms. Formal assessment was done through positive and negative syndrome scale, young’s mania rating scale, and beck’s depression inventory. The client was diagnosed with bipolar I disorder according to DSM 5. It took 12 sessions to manage client’s symptoms and Deep Breathing, Progressive Muscle Relaxation, Peripheral Questioning, Energy Channelization, Mood Monitoring etc. were used for this purpose. The client reported overall improvement of 80 % in his symptoms after therapeutic intervention.

Mental health prior to and during the COVID-19 pandemic in individuals with bipolar disorder: Insights from prospective longitudinal data.

ObjectivesMany studies have examined the impact of COVID‐19 on the mental health of the public, but few have focused on individuals with existing severe mental illness with longitudinal data before and during the pandemic. Aims: To investigate the impact of the COVID‐19 pandemic on the mental health of people with bipolar disorder (BD).MethodsIn an ongoing study of people with BD who used an online mood monitoring tool, True Colours, 356 participants provided weekly data on their mental health. Symptoms of depression, mania, insomnia, and suicidal thoughts were compared in 2019 and 2020. From May 2020, participants also provided weekly data on the effect of the COVID‐19 pandemic on anxiety, coping strategies, access to care, and medications.ResultsOn average, symptoms of depression, mania, insomnia, and suicidal thoughts did not significantly differ in 2020 compared to 2019, but there was evidence of heterogeneity. There were high rates of anxiety about the pandemic and its impact on coping strategies, which increased to over 70% of responders in January 2021. A significant proportion of participants reported difficulty accessing routine care (27%) and medications (21%).ConclusionsAlthough mood symptoms did not significantly increase during the pandemic overall, we observed heterogeneity among our BD sample and other impacted areas. Individuals' unique histories and psychosocial circumstances are key and should be explored in future qualitative studies. The significant impacts of the pandemic may take time to manifest, particularly among those who are socioeconomically disadvantaged, highlighting the need for further long‐term prospective studies.

How to make online mood-monitoring in bipolar patients a success? A qualitative exploration of requirements

BackgroundThe Life-Chart Method (LCM) is an effective self-management treatment option in bipolar disorder (BD). There is insufficient knowledge about the consumers’ needs and desires for an e-monitoring solution. The first step towards a new mood monitoring application is an extended inventory among consumers and professionals.MethodsThe aim of the current study was: to identify opinions about online mood monitoring of patients with BD and professionals and to identify preferences on design, technical features and options facilitating optimal use and implementation of online mood monitoring. This study used a qualitative design with focus-groups. Participants were recruited among patients and care providers. Three focus-groups were held with eight consumers and five professionals.ResultsThe focus-group meetings reveal a shared consciousness of the importance of using the Life-Chart Method for online mood monitoring. There is a need for personalization, adjustability, a strict privacy concept, an adjustable graphic report, and a link to early intervention strategies in the design. Due to the fact that this is a qualitative study with a relative small number of participants, so it remains unclear whether the results are fully generalizable. We can’t rule out a selection bias.ConclusionsThis study demonstrates the importance of involving stakeholders in identifying a smartphone-based mood charting applications’ requirements. Personalization, adjustability, privacy, an adjustable graphic report, and a direct link to early intervention strategies are necessary requirements for a successful design. The results of this value specification are included in the follow-up of this project.

Clinical neurological manifestations in patients suffering from peptic ulcer disease in the acute phase and in remission

Objective — to analyze clinical neurological manifestations in patients suffering from peptic ulcer disease in the acute phase and in remission, based on the findings of a comprehensive clinical neurological, neuropsychological and paraclinical study. Methods and subjects. 84 patients suffering from PUD were comprehensively examined while in the acute phase of the disease and then all 84 were reexamined while in remission. The age range of the patients was from 25 to 60 years. The average age of the patient was 39.90 ± 1.29 years. The examined individuals were destributed into two groups based on whether they presented symptoms of an acute phase or remission of the peptic ulcer disease. The comprehensive examination included: interview and complaint analysis, neurological examination focused on the state of the autonomic nervous system, study of the neuropsychological differences (the trait and state anxiety levels monitoring based on the Spielberg‑Khanin scale, depressive state evaluation using Beck Depression Inventory, self‑perceived health assessment, mood and activity monitoring using the SAN questionnaire, cognitive impairment evaluation using the MMSE scale, assessment of the refocusing speeds and performance distribution using Schulte tables), as well as lab tests and procedures. Results. Most often, subjects complained of headache (74 (88.0 %) in the acute stage and 37 (44.0 %) in remission). The second most common was a complaint of pain in the thoracic spine (69 (82.1 %) and 35 (41.6 %), respectively). Complaints of dizziness, pain in the heart, palpitations, «interruptions» in the heart, paresthesia were often recorded. In 11 (12.4 %) patients with duodenal ulcer in the acute stage experienced episodes of syncopal state, while in the remission stage they were absent. Complaints that indicated the presence of psychoemotional disorders were anxiety, decreased memory and attention, and sleep disturbances. In patients with duodenal ulcer disease we revealed lesions of the central and peripheral nervous system. Central nervous system disorders were manifested in the form of vestibulo‑cerebellar syndrome (in 30 (35.7 %) patients in the acute stage and in 14 (16.6 %) in the remission stage), extrapyramidal disorders (respectively in 10 (11.9 %) and 4 (4.76 %)) and signs of pyramidal dysfunction (37 (44.0 %) and 15 (17.8 %)). Clinical and neurological examination of the peripheral nervous system in 68 (80.9 %) patients with peptic ulcer in the acute stage and in 31 (36.9 %) in the remission stage revealed polyneuropathy syndrome of varying degrees. Signs of polyneuropathy were accompanied by complaints of disorders of the peripheral nervous system (45 (53.5 %) and 15 (17.8 %) cases, respectively). In 27.4 % of patients with peptic ulcer disease in the acute stage of the complaint were absent at all, and only a thorough neurological examination revealed signs of polyneuropathy. In 56 (66.6 %) patients with peptic ulcer disease in the acute stage and 28 (33.3 %) in the remission stage, the morbidity of paravertebral points in the lower thoracic spine was revealed. Conclusions. Having analyzed the data obtained through the interviews, as well as the neurological characteristics of patients with peptic ulcer disease of the duodenum in the acute phase and in remission it was concluded that most of the somatic complaints and neurological manifestations were common in both the acute phase and the remission of the disease. However, all of the identified neurological differences were significantly more common in the acute phase of the disease.

Mobile Apps That Promote Emotion Regulation, Positive Mental Health, and Well-being in the General Population: Systematic Review and Meta-analysis.

BackgroundAmong the general public, there appears to be a growing need and interest in receiving digital mental health and well-being support. In response to this, mental health apps (MHapps) are becoming available for monitoring, managing, and promoting positive mental health and well-being. Thus far, evidence supports favorable outcomes when users engage with MHapps, yet there is a relative paucity of reviews on apps that support positive mental health and well-being.ObjectiveWe aimed to systematically review the available research on MHapps that promote emotion regulation, positive mental health, and well-being in the general population aged 18-45 years. More specifically, the review aimed at providing a systematic description of the theoretical background and features of MHapps while evaluating any potential effectiveness.MethodsA comprehensive literature search of key databases, including MEDLINE (via Ovid), EMBASE (via Ovid), PsycINFO (via Ovid), Web of Science, and the Cochrane Register of Controlled Trials (CENTRAL), was performed until January 2021. Studies were included if they described standalone mental health and well-being apps for adults without a formal mental health diagnosis. The quality of all studies was assessed against the Mixed Methods Appraisal Tool. In addition, the Cochrane Risk-of-Bias tool (RoB-2) was used to assess randomized control trials (RCTs). Data were extracted using a modified extraction form from the Cochrane Handbook of Systematic Reviews. A narrative synthesis and meta-analysis were then undertaken to address the review aims.ResultsIn total, 3156 abstracts were identified. Of these, 52 publications describing 48 MHapps met the inclusion criteria. Together, the studies evaluated interventions across 15 countries. Thirty-nine RCTs were identified suggesting some support for the role of individual MHapps in improving and promoting mental health and well-being. Regarding the pooled effect, MHapps, when compared to controls, showed a small effect for reducing mental health symptoms (k=19, Hedges g=–0.24, 95% CI –0.34 to –0.14; P<.001) and improving well-being (k=13, g=0.17, 95% CI 0.05-0.29, P=.004), and a medium effect for emotion regulation (k=6, g=0.49, 95% CI 0.23-0.74, P<.001). There is also a wide knowledge base of creative and innovative ways to engage users in techniques such as mood monitoring and guided exercises. Studies were generally assessed to contribute unclear or a high risk of bias, or to be of medium to low methodological quality.ConclusionsThe emerging evidence for MHapps that promote positive mental health and well-being suggests promising outcomes. Despite a wide range of MHapps, few apps specifically promote emotion regulation. However, our findings may position emotion regulation as an important mechanism for inclusion in future MHapps. A fair proportion of the included studies were pilot or feasibility trials (k=17, 33%), and full-scale RCTs reported high attrition rates and nondiverse samples. Given the number and pace at which MHapps are being released, further robust research is warranted to inform the development and testing of evidence-based programs.

The Use of Task Shifting to Improve Treatment Engagement in an Internet-Based Mindfulness Intervention Among Chinese University Students: Randomized Controlled Trial.

BackgroundTraditional in-person psychotherapies are incapable of addressing global mental health needs. Use of computer-based interventions is one promising solution for closing the gap between the amount of global mental health treatment needed and received.ObjectiveAlthough many meta-analyses have provided evidence supporting the efficacy of self-guided, computer-based interventions, most report low rates of treatment engagement (eg, high attrition and low adherence). The aim of this study is to investigate the efficacy of an adjunctive treatment component that uses task shifting, wherein mental health care is provided by nonspecialist peer counselors to enhance engagement in an internet-based, self-directed, evidence-based mindfulness intervention among Chinese university students.MethodsFrom 3 universities across China, 54 students who reported at least mild stress, anxiety, or depression were randomly assigned to a 4-week internet-based mindfulness intervention (MIND) or to the intervention plus peer counselor support (MIND+), respectively. Be Mindful delivers all the elements of mindfulness-based cognitive therapy in an internet-based, 4-week course. Participants completed daily monitoring of mindfulness practice and mood, as well as baseline and posttreatment self-reported levels of depression, anxiety, stress, and trait mindfulness. We screened 56 volunteer peer counselor candidates who had no former training in the delivery of mental health services. Of these, 10 were invited to participate in a day-long training, and 4 were selected. Peer counselors were instructed to provide 6 brief (15-20 minute) sessions each week, to help encouraging participants to complete the internet-based intervention. Peer counselors received weekly web-based group supervision.ResultsFor both conditions, participation in the internet-based intervention was associated with significant improvements in mindfulness and mental health outcomes. The pre-post effect sizes (Cohen d) for mindfulness, depression, anxiety, and stress were 0.55, 0.95, 0.89, and 1.13, respectively. Participants assigned to the MIND+ (vs MIND) condition demonstrated significantly less attrition and more adherence, as indicated by a greater likelihood of completing posttreatment assessments (16/27, 59% vs 7/27, 26%; χ21=6.1; P=.01) and a higher percentage of course completion (72.6/100, 72.6% vs 50.7/100, 50.7%; t52=2.10; P=.04), respectively. No significant between-group differences in daily frequency and duration of mindfulness practice were observed. Multilevel logistic growth models showed that MIND+ participants reported significantly greater pre-post improvements in daily stress ratings (interaction estimate 0.39, SE 0.18; t317=2.29; P=.02) and depression (interaction estimate 0.38, SE 0.16; t330=2.37; P=.02) than those in the MIND condition.ConclusionsThis study provides new insights into effective ways of leveraging technology and task shifting to implement large-scale mental health initiatives that are financially feasible, easily transportable, and quickly scalable in low-resource settings. The findings suggest that volunteer peer counselors receiving low-cost, low-intensity training and supervision may significantly improve participants’ indices of treatment engagement and mental health outcomes in an internet-based mindfulness intervention among Chinese university students.

Using Acoustic Speech Patterns From Smartphones to Investigate Mood Disorders: Scoping Review.

BackgroundMood disorders are commonly underrecognized and undertreated, as diagnosis is reliant on self-reporting and clinical assessments that are often not timely. Speech characteristics of those with mood disorders differs from healthy individuals. With the wide use of smartphones, and the emergence of machine learning approaches, smartphones can be used to monitor speech patterns to help the diagnosis and monitoring of mood disorders.ObjectiveThe aim of this review is to synthesize research on using speech patterns from smartphones to diagnose and monitor mood disorders.MethodsLiterature searches of major databases, Medline, PsycInfo, EMBASE, and CINAHL, initially identified 832 relevant articles using the search terms “mood disorders”, “smartphone”, “voice analysis”, and their variants. Only 13 studies met inclusion criteria: use of a smartphone for capturing voice data, focus on diagnosing or monitoring a mood disorder(s), clinical populations recruited prospectively, and in the English language only. Articles were assessed by 2 reviewers, and data extracted included data type, classifiers used, methods of capture, and study results. Studies were analyzed using a narrative synthesis approach.ResultsStudies showed that voice data alone had reasonable accuracy in predicting mood states and mood fluctuations based on objectively monitored speech patterns. While a fusion of different sensor modalities revealed the highest accuracy (97.4%), nearly 80% of included studies were pilot trials or feasibility studies without control groups and had small sample sizes ranging from 1 to 73 participants. Studies were also carried out over short or varying timeframes and had significant heterogeneity of methods in terms of the types of audio data captured, environmental contexts, classifiers, and measures to control for privacy and ambient noise.ConclusionsApproaches that allow smartphone-based monitoring of speech patterns in mood disorders are rapidly growing. The current body of evidence supports the value of speech patterns to monitor, classify, and predict mood states in real time. However, many challenges remain around the robustness, cost-effectiveness, and acceptability of such an approach and further work is required to build on current research and reduce heterogeneity of methodologies as well as clinical evaluation of the benefits and risks of such approaches.

Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study.

BackgroundSelf-reported mood is a valuable clinical data source regarding disease state and course in patients with mood disorders. However, validated, quick, and scalable digital self-report measures that can also detect relapse are still not available for clinical care.ObjectiveIn this study, we aim to validate the newly developed ASERT (Aktibipo Self-rating) questionnaire—a 10-item, mobile app–based, self-report mood questionnaire consisting of 4 depression, 4 mania, and 2 nonspecific symptom items, each with 5 possible answers. The validation data set is a subset of the ongoing observational longitudinal AKTIBIPO400 study for the long-term monitoring of mood and activity (via actigraphy) in patients with bipolar disorder (BD). Patients with confirmed BD are included and monitored with weekly ASERT questionnaires and monthly clinical scales (Montgomery-Åsberg Depression Rating Scale [MADRS] and Young Mania Rating Scale [YMRS]).MethodsThe content validity of the ASERT questionnaire was assessed using principal component analysis, and the Cronbach α was used to assess the internal consistency of each factor. The convergent validity of the depressive or manic items of the ASERT questionnaire with the MADRS and YMRS, respectively, was assessed using a linear mixed-effects model and linear correlation analyses. In addition, we investigated the capability of the ASERT questionnaire to distinguish relapse (YMRS≥15 and MADRS≥15) from a nonrelapse (interepisode) state (YMRS<15 and MADRS<15) using a logistic mixed-effects model.ResultsA total of 99 patients with BD were included in this study (follow-up: mean 754 days, SD 266) and completed an average of 78.1% (SD 18.3%) of the requested ASERT assessments (completion time for the 10 ASERT questions: median 24.0 seconds) across all patients in this study. The ASERT depression items were highly associated with MADRS total scores (P<.001; bootstrap). Similarly, ASERT mania items were highly associated with YMRS total scores (P<.001; bootstrap). Furthermore, the logistic mixed-effects regression model for scale-based relapse detection showed high detection accuracy in a repeated holdout validation for both depression (accuracy=85%; sensitivity=69.9%; specificity=88.4%; area under the receiver operating characteristic curve=0.880) and mania (accuracy=87.5%; sensitivity=64.9%; specificity=89.9%; area under the receiver operating characteristic curve=0.844).ConclusionsThe ASERT questionnaire is a quick and acceptable mood monitoring tool that is administered via a smartphone app. The questionnaire has a good capability to detect the worsening of clinical symptoms in a long-term monitoring scenario.

Implementation of the Wolverine Mental Health Program, Part 2: Implementation Phase

To enhance mental health care for youth in a midwestern residential treatment facility, Wolverine Human Services partnered with the Beck Institute (an intermediary) and an implementation research team to implement cognitive-behavioral therapy (CBT). CBT has strong evidence supporting effectiveness for treating youth internalizing and externalizing problems, but it is a complex psychosocial intervention that demands a thoughtful implementation approach. This study outlines the implementation phase (2.5 years) of a 5-year collaborative effort. The implementation phase focused on (a) adapting CBT to fit the complex youth needs and the roles of the multidisciplinary team members resulting in a new comprehensive and coordinated care model, and (b) the strategies utilized to support its competent integration by all team members. Six blended implementation strategies were deployed in this phase: forging implementation teams, installing progress monitoring, adapting CBT, training, providing supervision and consultation, and training the trainers. A components-based approach to CBT yielded six core skills: active listening, problem solving, mood monitoring and intervention mapping, activity scheduling, distress tolerance, and cognitive restructuring. By the end of this phase, all staff had robust exposure to and experience with the adapted form of CBT. The work of our academic–community partnership has both research and clinical implications, with respect to integrating an adapted version of CBT for residential environments (CBT-RE).

Discovering different profiles in the dynamics of depression based on real–time monitoring of mood: a first exploration

BackgroundAlthough depression is typically characterized by a persistent depressed mood, mood dynamics do seem to vary across a depressed population. Heterogeneity of mood variability (magnitude of changes) and emotional inertia (speed at which mood shifts) is seen in clinical practice. However, studies investigating the heterogeneity of these mood dynamics are still scarce. The aim of the present study is to explore different distinctive profiles in real-time monitored mood dynamics among depressed persons. MethodsAfter completing baseline measures, mildly-to-moderately depressed persons (n = 37) were prompted to rate their current mood (1–10 scale) on their smartphones, 3 times a day for 7 consecutive days. Latent profile analyses were applied to identify profiles based on average mood, variability of mood and emotional inertia as reported by the participants. ResultsTwo profiles were identified in this sample. The overwhelming majority of the sample belonged to profile 1 (n = 31). Persons in profile 1 were characterized by a mood just above the cutoff for positive mood (M = 6.27), with smaller mood shifts (lower variability [SD = 1.05]) than those in profile 2 (n = 6), who displayed an overall negative mood (M = 4.72) and larger mood shifts (higher variability [SD = 1.95]) but at similar speed (emotional inertia) (AC = 0.19, AC = 0.26, respectively). ConclusionsThe present study provides preliminary indications for patterns of average mood and mood variability, but not emotional inertia, among mildly-to-moderately depressed persons.

Exploring the features of an app-based just-in-time intervention for depression

BackgroundTechnological advancements make it possible to deliver depression interventions via smartphone applications (“Apps”), including those that deliver content “just-in-time” (e.g., in response to acute negative mood states). This study examined whether an app-based just-in-time intervention (ImproveYourMood+) decreased depressive symptoms, and whether the following features were related to symptom improvement: micro-intervention content, mood monitoring, and just-in-time prompts to use content. MethodsParticipants (n = 235) from the general population who self-identified as wanting to improve their negative mood were randomised to a waitlist control group (n = 55) or one of three intervention groups: MoodTracker (monitoring-only, n = 58), ImproveYourMood (monitoring and content; n = 62), or ImproveYourMood+ (monitoring, content, and prompts; n = 60). The active intervention phase was 3 weeks. Depressive and anxiety symptoms, and negative automatic thoughts were assessed at baseline, immediately post-intervention, and one month following post-intervention. ResultsLinear mixed modelling revealed greater declines over time in depressive and anxiety symptoms and negative automatic thoughts for the ImproveYourMood group (standardized mean differences [SMDs] ranged from .32 to .40) and improves for the ImproveYourMood+ group for negative automatic thoughts (SMDs ≥ .37) compared to the waitlist control group. No between-group differences were observed between the MoodTracker and control groups (SMDs = .04–.23). User experience appeared to be superior in more comprehensive/multi-modal versions. LimitationsThe study employed a naturalistic design, whereby participants self-selected to utilise the program, did not complete eligibility assessments, and did not receive compensation. The study therefore attained considerable drop-out rate (~50% by the follow-up timepoints), potentially reflecting the usage patterns of real-world mental health apps. ConclusionsThe findings suggest that micro-interventions can be an effective way to reduce depressive symptoms both in the moment and 1–2 months later. Integration of micro-interventions with full treatment programs is a viable next step in micro-intervention research.

Mental Health Consequences of Adversity in Australia: National Bushfires Associated With Increased Depressive Symptoms, While COVID-19 Pandemic Associated With Increased Symptoms of Anxiety.

High quality monitoring of mental health and well-being over an extended period is essential to understand how communities respond to the COVID-19 pandemic and how to best tailor interventions. Multiple community threats may also have cumulative impact on mental health, so examination across several contexts is important. The objective of this study is to report on changes in mental health and well-being in response to the Australian bushfires and COVID-19 pandemic. This study utilized an Experience-Sampling-Method (ESM), using the smartphone-based mood monitoring application, MoodPrism. Participants were prompted once a day to complete a brief survey inquiring about symptoms of depression and anxiety, and several well-being indices, including arousal, emotional valence, self-esteem, motivation, social connectedness, meaning and purpose, and control. Participants were N = 755 Australians (aged 13 years and above) who downloaded and used MoodPrism, between 2018 and 2020. Results showed that anxiety symptoms significantly increased during the COVID-19 pandemic, but not during the bushfires. This may be explained by concurrent feelings of social connectedness maintained during the bushfires but not during the pandemic. In contrast, depressive symptoms increased significantly during the bushfires, which maintained during the pandemic. Most indices of well-being decreased significantly during the bushfires, and further again during the pandemic. Study findings highlight the unique responses to the bushfire and COVID-19 crises, revealing specific areas of resilience and vulnerability. Such information can help inform the development of public health interventions or individual clinical treatment, to improve treatment approaches and preparedness for potential future community disasters.

Do promotion and prevention focus influence impulse buying: The role of mood regulation, shopping values, and impulse buying tendency

Earlier researchers have observed that an individual consumer's mood plays a significant role in increasing the impulsiveness, which leads to impulsive buying. The literature on shoppers' motivational traits has profoundly acknowledged the impact of these traits and mood regulation constructs on individual shopping values. The present study is a pioneer attempt proposing a comprehensive model, which incorporates three main antecedents (motivation, mood and value) of buying behaviour that influence the consumer purchasing decision. The paper empirically explores the liaison between the regulatory focus (promotion-focused and prevention-focused motivations), mood regulation (mood monitoring, mood clarity and mood repair), shopping values (hedonic and utilitarian), and impulsive buying behaviour. The outcomes suggest that two regulatory focus motives influence mood clarity. Mood repairing and mood monitoring impact hedonic shopping values, which has a substantial impact on consumers' impulsive buying tendency. The paper closes with theoretical and practical inferences, limitations, and discussion on the potential scope for future research.

Migraine and Mood in Children.

Migraine is one of the most prevalent headache disorders in children and negatively influences their quality of life. Physical, social, and school functioning are negatively affected. Mood changes are common in migraineurs and may happen before, during, or after a migraine headache. Children with migraine are not exempt from mood swings. The majority of mood changes occur during the prodromal phase, manifesting as a psychobiological response, e.g., difficulty thinking, trouble concentrating, irritability, higher or lower energy, confusion, and depression. A bi-directional relationship between migraine and mood has been proposed, but mechanisms are not clear. Collectively, a maladaptive stress response has been suggested to explain the inability to balance homoeostatic changes when facing various stressors. Recognizing mood changes and monitoring mood patterns in children with migraine, for example, by various apps and so-called mood monitors, is valuable for better management. A multidisciplinary intervention has been recommended to reduce migraine disability, improve coping strategies, and reduce chronification risks in children with migraine. Pharmacological and non-pharmacological strategies are both available and effective. Biofeedback, relaxation, and cognitive-behavioral therapy yield positive outcomes in pediatric migraine. Developing healthy lifestyle habits (diet, exercise, sleep) also seems to improve migraine in this population.

An examination of the direct and indirect effect of self-objectification and disordered eating

IntroductionObjectification theory argues that self-objectification confers risk for disordered eating (DE) both directly, and indirectly through a cascade of negative psychological consequences (e.g. low mood and self-conscious body monitoring). Robust cross-sectional evidence supports these relationships. However, these cross-sectional studies do not provide evidence for the complex intraindividual psychological processes outlined in objectification theory which purportedly contribute to DE.ObjectivesUsing an ecological momentary assessment design, the current study investigated the direct within-person effect between state self-objectification and DE and examined the indirect within-person effect of negative mood and body comparisons, on the relationship between state self-objectification and DE.MethodsTwo-hundred female participants (M=20.43 years, SD=4.60) downloaded a smartphone app which assessed momentary experiences of self-objectification, mood, body comparisons, and DE six times per day at random intervals for seven days.ResultsIndicated that self-objectification significantly predicted DE behaviours [95% CI 0.01, 0.03] and body comparisons [95% CI 0.32, 0.41]. However, the indirect effect of body comparisons on the relationship between state self-objectification and DE was not significant [95% CI -0.01, 0.00]. In the second mediation model, self-objectification significantly predicted DE behaviours [95% CI 0.01, 0.03], but did not significantly predict mood [95% CI -0.06, 0.03]. Similarly, the indirect effect of mood on the relationship between state self-objectification and DE was not significant [95% CI -0.00, 0.00].ConclusionsThese results enhance our understanding of objectification theory and suggest that self-objectification confers risk to DE directly. However, our findings do not support the indirect effect of self-objectification on DE through low mood or body comparisons.DisclosureNo significant relationships.

Prospective early warning signals to detect transitions to manic and depressive episodes in bipolar disorder

IntroductionFor patients with bipolar disorder, early recognition of impending mood episodes is crucial to enable timely intervention. Longitudinal digital mood monitoring using ecological momentary assessment (EMA) enable prospective study of early warning signals (EWS) in momentary affective estates prior to symptom transitions.ObjectivesThe present study examined in a unique longitudinal EMA data set whether EWS prospectively signal transitions to manic or depressive episodes.MethodsTwenty bipolar type I/II patients completed EMA questionnaires five times a day for four months (average 491 observations per person), as well as weekly symptom questionnaires concerning depressive (Quick Inventory for Depressive Symptomatology) and manic (Altman Self-Rating Mania Scale) symptoms. Weekly data was used to determine transitions (i.e., abrupt increase in symptoms). Prior to these transitions, EWS (autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective EMA states. Kendall’s tau was calculated to detect significant rises in the EWS indicator prior to the transition.ResultsEleven patients reported one or two transitions to a mood episode. All transitions were preceded by at least one EWS. Average sensitivity for detecting EWS was slightly higher for manic episodes (36%) than for depressive episodes (25%). For manic episodes, EWS in thoughts racing, being full of ideas, and feeling agitated showed the highest sensitivity and specificity, whereas for depression, only feeling tired showed high sensitivity and specify.ConclusionsEWS show promise in anticipating transitions to mood episodes in bipolar disorder. Further investigation is warranted.DisclosureNo significant relationships.

Optimizing Engagement in an Online Dietary Intervention for Depression (My Food & Mood Version 3.0): Cohort Study.

BackgroundOnline interventions can be a cost-effective and efficient way to deliver programs to large numbers of people regardless of geographic location. However, attrition in web-based interventions is often an issue. Developing ways to keep participants engaged is important for ensuring validity and limiting potential biases. We developed a web-based dietary intervention as part of The My Food & Mood study which aimed to optimize ways to engage participants with low mood or depressive symptoms to promote dietary behavior change. Different versions of the My Food & Mood program were tested during optimization. Iterations were developed based on user feedback and usage analysis.ObjectiveThe purpose of this study was to compare engagement and nonusage attrition across 4 program iterations—which differed by platform format, delivery mode, and activity type—to create an optimized version.MethodsEach program version contained modular videos with key activities with respect to implementing behavior change techniques of equivalent levels of required participation and length: version 1.0, desktop program and smartphone app; version 2.1, desktop or smartphone program; version 2.2, desktop program; and version 3.0, smartphone app. Adults with PHQ-8 scores of 5 or greater were recruited online and assigned to 1 of the 4 versions. Participants were asked to use the program for 8 weeks and complete measures at weeks 4 and 8. Engagement data were collected from the web-based platform system logs and customized reports. Cox regression survival analysis examined nonusage attrition and Kruskal-Wallis tests compared engagement across each cohort.ResultsA total of 614 adults participated. Kruskal-Wallis tests showed significant differences across the 4 cohorts in all engagement measures. The smartphone app (version 3.0) had the greatest engagement as measured by weeks engaged, total usage time, total time key activities, number of active sessions, percentage of activities completed against protocol, goals completed, and percentage of videos watched. Cox regression multivariate survival analysis showed referral from a health practitioner (hazard ratio [HR] 0.344, P=.001) and greater proficiency with computers (HR 0.796, P=.049) reduced the risk of nonusage attrition. Computer confidence was associated with an increased risk of nonusage attrition.ConclusionsMy Food & Mood version 3.0, a dietary intervention delivered via smartphone app with self-monitoring tools for diet quality and mood monitoring, was the version with greatest engagement in a population with low mood or depression. The iterative design techniques employed and analysis of feedback from participants resulted in a program that achieved lower rates of nonusage attrition and higher rates of intensity of use.

Mood monitoring in bipolar disorder: Is it always helpful?

Mood monitoring is widely used in the treatment and self-management of bipolar mood swings. Typically, service-users record their affective states in a paper or electronic diary over an extended period (e.g. weeks, months). The aim is to help people to achieve greater awareness and understanding of their affective states, which then enables them to better prepare and account for problematic changes in their mood, preventing escalation to mood episodes and relapse.

СТРУКТУРА ПРОГРАММНОГО ПРОДУКТА ДЛЯ СЕМАНТИЧЕСКОГО АНАЛИЗА ТЕКСТОВОЙ ИНФОРМАЦИИ

The article is devoted to the development of software for semantic text analysis. Describes the General logic of the developed web application, which implements the classification of textual information by previously predefined semantic categories. This article provides usage and deployment diagrams, as well as a General diagram of the algorithm. The methods implemented in the app allow you to increase the speed of processing text information. The use of the developed software product allows you to quickly process text information of any content, as well as conduct a deeper semantic analysis of the text. The implemented method is relevant in many areas of activity where you have to work with text information: monitoring of emotional mood towards the company, marketing, social network analysis.

WITHDRAWN: Cognitive psychology for monitoring the amateur athletes training activities and depressive mood

Abstract Sports psychologists give athletes powerful tools to help them reach peak performance and personal growth. Over the years, numerous strategies have been developed to help athletes transcend their self-imposed psychological constraints and help create athletic environments that encourage their development. The definition of elite/expert athletes as sport psychology research has shown considerable inconsistency and confusion, which has implications for studies in this field. In this paper, the Heuristic Probabilistic Mathematical model (HPMM) has been proposed to monitor the sports amateur athlete's training activities and determine all the athlete's behaviors in an actual-look training environment with accuracy the correlations between shifts in depressed moods. This paper reviews the issues in consultation with athletes and trainers, develops and modifies interventions, and aims to create an experimental single-case design to evaluate this procedure's usefulness. However, the design has good reliability and validity and proved useful information from behavioral observations and subjective ratings. In the current sports scenario, improvements in the intervention and evaluation process may be required. The experimental results show the effective solution in cognitive psychology to enhance amateur athletes' performance and depressive mood monitoring on cognitive sport psychology.