27 research outputs found

    Autonomic response to walk tests is useful for assessing outcome measures in people with multiple sclerosis

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    Objective: The aim of this study was to evaluate the association between changes in the autonomic control of cardiorespiratory system induced by walk tests and outcome measures in people with Multiple Sclerosis (pwMS). Methods: Electrocardiogram (ECG) recordings of 148 people with Relapsing-Remitting MS (RRMS) and 58 with Secondary Progressive MS (SPMS) were acquired using a wearable device before, during, and after walk test performance from a total of 386 periodical clinical visits. A subset of 90 participants repeated a walk test at home. Various MS-related symptoms, including fatigue, disability, and walking capacity were evaluated at each clinical visit, while heart rate variability (HRV) and ECG-derived respiration (EDR) were analyzed to assess autonomic nervous system (ANS) function. Statistical tests were conducted to assess differences in ANS control between pwMS grouped based on the phenotype or the severity of MS-related symptoms. Furthermore, correlation coefficients (r) were calculated to assess the association between the most significant ANS parameters and MS-outcome measures. Results: People with SPMS, compared to RRMS, reached higher mean heart rate (HRM) values during walk test, and larger sympathovagal balance after test performance. Furthermore, pwMS who were able to adjust their HRM and ventilatory values, such as respiratory rate and standard deviation of the ECG-derived respiration, were associated with better clinical outcomes. Correlation analyses showed weak associations between ANS parameters and clinical outcomes when the Multiple Sclerosis phenotype is not taken into account. Blunted autonomic response, in particular HRM reactivity, was related with worse walking capacity, yielding r = 0.36 r = 0.29 (RRMS) and r > 0.5 (SPMS). A positive strong correlation r > 0.7 r > 0.65 between cardiorespiratory parameters derived at hospital and at home was also found. Conclusion: Autonomic function, as measured by HRV, differs according to MS phenotype. Autonomic response to walk tests may be useful for assessing clinical outcomes, mainly in the progressive stage of MS. Participants with larger changes in HRM are able to walk longer distance, while reduced ventilatory function during and after walk test performance is associated with higher fatigue and disability severity scores. Monitoring of disorder severity could also be feasible using ECG-derived cardiac and respiratory parameters recorded with a wearable device at home

    Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol

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    BACKGROUND: There is a growing body of literature highlighting the role that wearable and mobile remote measurement technology (RMT) can play in measuring symptoms of major depressive disorder (MDD). Outcomes assessment typically relies on self-report, which can be biased by dysfunctional perceptions and current symptom severity. Predictors of depressive relapse include disrupted sleep, reduced sociability, physical activity, changes in mood, prosody and cognitive function, which are all amenable to measurement via RMT. This study aims to: 1) determine the usability, feasibility and acceptability of RMT; 2) improve and refine clinical outcome measurement using RMT to identify current clinical state; 3) determine whether RMT can provide information predictive of depressive relapse and other critical outcomes. METHODS: RADAR-MDD is a multi-site prospective cohort study, aiming to recruit 600 participants with a history of depressive disorder across three sites: London, Amsterdam and Barcelona. Participants will be asked to wear a wrist-worn activity tracker and download several apps onto their smartphones. These apps will be used to either collect data passively from existing smartphone sensors, or to deliver questionnaires, cognitive tasks, and speech assessments. The wearable device, smartphone sensors and questionnaires will collect data for up to 2-years about participants' sleep, physical activity, stress, mood, sociability, speech patterns, and cognitive function. The primary outcome of interest is MDD relapse, defined via the Inventory of Depressive Symptomatology- Self-Report questionnaire (IDS-SR) and the World Health Organisation's self-reported Composite International Diagnostic Interview (CIDI-SF). DISCUSSION: This study aims to provide insight into the early predictors of major depressive relapse, measured unobtrusively via RMT. If found to be acceptable to patients and other key stakeholders and able to provide clinically useful information predictive of future deterioration, RMT has potential to change the way in which depression and other long-term conditions are measured and managed. KEYWORDS: M-health; Major depressive disorder; Observational cohort; Outcome measurement; Passive sensing; Prospective study; Remote measurement technolog

    Neurodevelopmental and psychosocial risk factors in serial killers and mass murderers

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    Multiple and serial murders are rare events that have a very profound societal impact. We have conducted a systematic review, following PRISMA guidelines, of both the peer reviewed literature and of journalistic and legal sources regarding mass and serial killings. Our findings tentatively indicate that these extreme forms of violence may be a result of a highly complex interaction of biological, psychological and sociological factors and that, potentially, a significant proportion of mass or serial killers may have had neurodevelopmental disorders such as autism spectrum disorder or head injury. Research into multiple and serial murders is in its infancy: there is a lack of rigorous studies and most of the literature is anecdotal and speculative. Specific future study of the potential role of neurodevelopmental disorders in multiple and serial murders is warranted and, due to the rarity of these events, innovative research techniques may be required

    Investigating a psychological model of mental conditions and coping during the COVID-19 pandemic driven by participatory methods

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    BACKGROUND: There is evidence of increased mental health problems during the early stages of the COVID-19 pandemic. We aimed to identify the factors that put certain groups of people at greater risk of mental health problems. METHODS: We took a participatory approach, involving people with lived experience of mental health problems and/or carers, to generate a set of risk factors and potential moderators of the effects of COVID on mental health. An online cross-sectional survey was completed by 1464 United Kingdom residents between 24th April and 27th June 2020. The survey had questions on whether respondents were existing mental health service users and or carers, level of depression (PHQ9) and anxiety (GAD7), demographics, threat and coping appraisals, perceived resilience (BRS), and specific coping behaviours (validated as part of this study). The relationship between responses and coping strategies was measured using tetrachoric correlations. Structural equation modelling was used to test the model. RESULTS: A model significantly fit our data (rel χ(2) = 2.05, RMSEA = 0.029 95%, CI (0.016, 0.042), CFI = 0.99, TLI = 0.98, SRMR = 0.014). Age and coping appraisal predicted anxiety and depression. Whereas, threat appraisal and ethnicity only predicted anxiety, and resilience only predicted depression. Additionally, specific coping behaviours predicted anxiety and depression, with overlap on distraction. CONCLUSIONS: Some, but not all, risk factors significantly predict anxiety and depression. While there is a relationship between anxiety and depression, different factors may put people at greater risk of one or the other during the pandemic

    Emotional outcomes in clinically isolated syndrome and early phase multiple sclerosis: a systematic review and meta-analysis

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    Objective: To study depression, anxiety, suicide risk, and emotional health-related quality of life (HRQoL) in people with clinically isolated syndrome (CIS) and in early phase multiple sclerosis (MS). Methods: A systematic literature review was conducted with inclusion criteria of observational studies on outcomes of depression, anxiety, suicide risk, and emotional HRQoL in CIS and within five years since diagnosis of MS. Studies were screened using the Preferred Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, and study quality was determined for included studies. Meta-analysis and meta-regression were performed if applicable. Results: Fifty-one studies were included in the systematic review. In early phase MS, meta-analyses of the Hospital Anxiety Depression Scale (HADS) indicated prevalence levels of 17% (95% confidence interval (CI): 9 to 25%; p < .001) for depressive and 35% (95% CI: 28 to 41%; p < .001) for anxiety symptoms. Meta-regression analyses revealed an increase in mean HADS-D and HADS-A associated with larger sample size, and higher HADS-D mean with increased study quality. Similar depressive and anxiety symptoms were observed in CIS, and increased suicide risk and low emotional HRQoL was associated with depressive symptoms in early phase MS. The methodological quality of the studies was considered fair. Conclusions: Findings suggest that mild-to-moderate symptoms of depression and anxiety might be prevalent in CIS and in early phase MS. Future research on both clinical populations are needed, especially longitudinal monitoring of emotional outcomes

    Barriers to and facilitators of engagement with mHealth technology for remote measurement and management of depression: Qualitative analysis

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    Background: Mobile technology has the potential to provide accurate, impactful data on the symptoms of depression, which could improve health management or assist in early detection of relapse. However, for this potential to be achieved, it is essential that patients engage with the technology. Although many barriers to and facilitators of the use of this technology are common across therapeutic areas and technology types, many may be specific to cultural and health contexts. Objective: This study aimed to determine the potential barriers to and facilitators of engagement with mobile health (mHealth) technology for remote measurement and management of depression across three Western European countries. Methods: Participants (N=25; 4:1 ratio of women to men; age range, 25-73 years) who experienced depression participated in five focus groups held in three countries (two in the United Kingdom, two in Spain, and one in Italy). The focus groups investigated the potential barriers to and facilitators of the use of mHealth technology. A systematic thematic analysis was used to extract themes and subthemes. Results: Facilitators and barriers were categorized as health-related factors, user-related factors, and technology-related factors. A total of 58 subthemes of specific barriers and facilitators or moderators emerged. A core group of themes including motivation, potential impact on mood and anxiety, aspects of inconvenience, and ease of use was noted across all countries. Conclusions: Similarities in the barriers to and facilitators of the use of mHealth technology have been observed across Spain, Italy, and the United Kingdom. These themes provide guidance on ways to promote the design of feasible and acceptable cross-cultural mHealth tools
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