ORCID Profile
0000-0002-3984-277X
Current Organisations
Université Ibn Zohr
,
University of South Australia
,
Parc Sanitari Sant Joan de Deu
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Publications
The Association Between Home Stay and Symptom Severity in Major Depressive Disorder: Preliminary Findings From a Multicenter Observational Study Using Geolocation Data From Smartphones (Preprint)
Publisher: JMIR Publications Inc.
Date: 21-02-2021
Abstract: ost smartphones and wearables are currently equipped with location sensing (using GPS and mobile network information), which enables continuous location tracking of their users. Several studies have reported that various mobility metrics, as well as home stay, that is, the amount of time an in idual spends at home in a day, are associated with symptom severity in people with major depressive disorder (MDD). Owing to the use of small and homogeneous cohorts of participants, it is uncertain whether the findings reported in those studies generalize to a broader population of in iduals with MDD symptoms. he objective of this study is to examine the relationship between the overall severity of depressive symptoms, as assessed by the 8-item Patient Health Questionnaire, and median daily home stay over the 2 weeks preceding the completion of a questionnaire in in iduals with MDD. e used questionnaire and geolocation data of 164 participants with MDD collected in the observational Remote Assessment of Disease and Relapse–Major Depressive Disorder study. The participants were recruited from three study sites: King’s College London in the United Kingdom (109/164, 66.5%) Vrije Universiteit Medisch Centrum in Amsterdam, the Netherlands (17/164, 10.4%) and Centro de Investigación Biomédica en Red in Barcelona, Spain (38/164, 23.2%). We used a linear regression model and a res ling technique (n=100 draws) to investigate the relationship between home stay and the overall severity of MDD symptoms. Participant age at enrollment, gender, occupational status, and geolocation data quality metrics were included in the model as additional explanatory variables. The 95% 2-sided CIs were used to evaluate the significance of model variables. articipant age and severity of MDD symptoms were found to be significantly related to home stay, with older (95% CI 0.161-0.325) and more severely affected in iduals (95% CI 0.015-0.184) spending more time at home. The association between home stay and symptoms severity appeared to be stronger on weekdays (95% CI 0.023-0.178, median 0.098 home stay: 25th-75th percentiles 17.8-22.8, median 20.9 hours a day) than on weekends (95% CI −0.079 to 0.149, median 0.052 home stay: 25th-75th percentiles 19.7-23.5, median 22.3 hours a day). Furthermore, we found a significant modulation of home stay by occupational status, with employment reducing home stay (employed participants: 25th-75th percentiles 16.1-22.1, median 19.7 hours a day unemployed participants: 25th-75th percentiles 20.4-23.5, median 22.6 hours a day). ur findings suggest that home stay is associated with symptom severity in MDD and demonstrate the importance of accounting for confounding factors in future studies. In addition, they illustrate that passive sensing of in iduals with depression is feasible and could provide clinically relevant information to monitor the course of illness in patients with MDD. >
The SOHO (Schizophrenia Outpatient Health Outcome) Study
Publisher: Springer Science and Business Media LLC
Date: 2006
DOI: 10.2165/00023210-200620040-00003
Abstract: The European SOHO (Schizophrenia Outpatient Health Outcome) study is an observational, naturalistic study of the outpatient treatment of schizophrenia. The patient recruitment and assessment began in September 2000 and finished in early 2005. A total of 10 972 adult patients from ten European countries who were initiating or changing antipsychotic medication for the treatment of schizophrenia within the normal course of care have been enrolled. The patients have been followed at regular intervals over the 3-year timeframe of the study. Evaluation includes clinical severity, measured with the Clinical Global Impression (CGI) scale health-related quality of life social functioning and medication tolerability. The 6- and 12-month results have been published so far and have demonstrated that the patients in whom treatment was initiated with olanzapine or clozapine or who were started on more than one antipsychotic of any class at baseline tended to have somewhat greater improvement than patients treated with other atypical or typical antipsychotics, both in terms of symptoms measured with the CGI and quality of life. Numbers of social contacts increased with the treatment, but other aspects of social functioning did not show any significant change. Atypical antipsychotics as a class were associated with a lower frequency of extrapyramidal symptoms (EPS) and anticholinergic use than typical antipsychotics. The frequency of EPS was lowest in the clozapine-, quetiapine- and olanzapine-treated patients, at around 10%. The atypical antipsychotics also conferred a lower risk for tar e dyskinesia than the typical antipsychotics. Weight gain occurred in all treatment cohorts over the first 12 months of treatment and was statistically significantly greater in the patients who started treatment with olanzapine and clozapine. Prolactin- and sexually-related adverse events were frequent at baseline assessment: amenorrhoea was present in around one- third of women, impotence in around 40% of men, and loss of libido in 50% of both male and female patients. Patients treated with olanzapine, clozapine and quetiapine were significantly less likely to have sexual/endocrine-related dysfunctions after 6 months of treatment (the 12-month results of this parameter are yet to be published) than those in the other treatment cohorts (typical antipsychotics, risperidone and amisulpride). Concomitant medication use during the study has been high, ranging from 5% to 29% for anticholinergics, 8% to 23% for antidepressants, 22% to 37% for anxiolytics and 7% to 19% for mood stabilisers, depending on the type of antipsychotic prescribed. Fewer olanzapine-, quetiapine- and clozapine-treated patients used concomitant anticholinergics or anxiolytics/hypnotics. The current results from the SOHO study indicate that differences in effectiveness and tolerability do exist between the antipsychotics. Future results from the study will be published during the coming months and years, and will allow patterns of antipsychotic use in routine clinical practice (including how often and why changes are made) to be determined. This important information is likely to impact on the future use of antipsychotics and will assist clinicians in refining the use of these drugs and improving the outcome of patients to whom they are prescribed.
Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study (Preprint)
Publisher: JMIR Publications Inc.
Date: 11-11-2021
Abstract: he mobility of an in idual measured by phone-collected location data has been found to be associated with depression however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored. e aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time. ata used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse–Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants’ location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility. his study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-in idual level than the between-in idual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, i P /i =.01), Location Entropy (time distribution on different locations) (φ=−0.04, i P /i =.02), and Residential Location Count (reflecting traveling) (φ=0.05, i P /i =.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=−0.07, i P /i & .001) the subsequent periodicity of mobility. everal phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings.
The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity
Publisher: Cambridge University Press (CUP)
Date: 15-05-2023
DOI: 10.1017/S0033291723001034
Abstract: Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in in iduals with a history of recurrent major depressive disorder (MDD) explored the intra-in idual variations in HR parameters and their relationship with depression severity. Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study. We analysed the relationship between depression severity, assessed every 2 weeks with the Patient Health Questionnaire-8, with HR parameters in the week before the assessment, such as HR features during all day, resting periods during the day and at night, and activity periods during the day evaluated with a wrist-worn Fitbit device. Linear mixed models were used with random intercepts for participants and countries. Covariates included in the models were age, sex, BMI, smoking and alcohol consumption, antidepressant use and co-morbidities with other medical health conditions. Decreases in HR variation during resting periods during the day were related with an increased severity of depression both in univariate and multivariate analyses. Mean HR during resting at night was higher in participants with more severe depressive symptoms. Our findings demonstrate that alterations in resting HR during all day and night are associated with depression severity. These findings may provide an early warning of worsening depression symptoms which could allow clinicians to take responsive treatment measures promptly.
Quantitative Approach Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-ToF) Mass Spectrometry
Publisher: Springer US
Date: 2021
Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: A systematic analysis for the Global Burden of Disease Study 2013
Publisher: Elsevier BV
Date: 2015
Associations between DSM-IV mental disorders and subsequent non-fatal, self-reported stroke
Publisher: Elsevier BV
Date: 08-2015
The Associations Between Preexisting Mental Disorders and Subsequent Onset of Chronic Headaches: A Worldwide Epidemiologic Perspective
Publisher: Elsevier BV
Date: 2015
DOI: 10.1016/J.JPAIN.2014.10.002
Abstract: Although there is a significant association between preexisting depression and later onset of chronic headache, the extent to which other preexisting mental disorders are associated with subsequent onset of headache in the general population is not known. Also unknown is the extent to which these associations vary by gender or by life course. We report global data from the WHO's World Mental Health surveys (n = 52,095), in which, by means of the Composite International Diagnostic Interview-3.0, 16 mental disorders from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, were retrospectively assessed in terms of lifetime prevalence and age of onset. Frequent or severe headaches were assessed using self-reports. After adjustment for covariates, survival models showed a moderate but consistent association between preexisting mood (odds ratios [ORs] = 1.3-1.4), anxiety (ORs = 1.2-1.7), and impulse-control disorders (ORs = 1.7-1.9) and the subsequent onset of headache. We also found a dose-response relationship between the number of preexisting mental disorders and subsequent headache onset (OR ranging from 1.9 for 1 preexisting mental disorder to 3.4 for ≥5 preexisting mental disorders). Our findings suggest a consistent and pervasive relationship between a wide range of preexisting mental disorders and the subsequent onset of headaches. This highlights the importance of assessing a broad range of mental disorders, not just depression, as specific risk factors for the subsequent onset of frequent or severe headaches. This study shows that there is a temporal association between a broad range of preexisting mental disorders and the subsequent onset of severe or frequent headaches in general population s les across the world.
Associations between mental disorders and subsequent onset of hypertension
Publisher: Elsevier BV
Date: 03-2014
Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study (Preprint)
Publisher: JMIR Publications Inc.
Date: 26-09-2020
Abstract: leep problems tend to vary according to the course of the disorder in in iduals with mental health problems. Research in mental health has associated sleep pathologies with depression. However, the gold standard for sleep assessment, polysomnography (PSG), is not suitable for long-term, continuous monitoring of daily sleep, and methods such as sleep diaries rely on subjective recall, which is qualitative and inaccurate. Wearable devices, on the other hand, provide a low-cost and convenient means to monitor sleep in home settings. he main aim of this study was to devise and extract sleep features from data collected using a wearable device and analyze their associations with depressive symptom severity and sleep quality as measured by the self-assessed Patient Health Questionnaire 8-item (PHQ-8). aily sleep data were collected passively by Fitbit wristband devices, and depressive symptom severity was self-reported every 2 weeks by the PHQ-8. The data used in this paper included 2812 PHQ-8 records from 368 participants recruited from 3 study sites in the Netherlands, Spain, and the United Kingdom. We extracted 18 sleep features from Fitbit data that describe participant sleep in the following 5 aspects: sleep architecture, sleep stability, sleep quality, insomnia, and hypersomnia. Linear mixed regression models were used to explore associations between sleep features and depressive symptom severity. The i z /i score was used to evaluate the significance of the coefficient of each feature. e tested our models on the entire dataset and separately on the data of 3 different study sites. We identified 14 sleep features that were significantly ( i P /i & .05) associated with the PHQ-8 score on the entire dataset, among them awake time percentage ( i z /i =5.45, i P /i & .001), awakening times (z=5.53, i P /i & .001), insomnia (z=4.55, i P /i & .001), mean sleep offset time (z=6.19, i P /i & .001), and hypersomnia (z=5.30, i P /i & .001) were the top 5 features ranked by i z /i score statistics. Associations between sleep features and PHQ-8 scores varied across different sites, possibly due to differences in the populations. We observed that many of our findings were consistent with previous studies, which used other measurements to assess sleep, such as PSG and sleep questionnaires. e demonstrated that several derived sleep features extracted from consumer wearable devices show potential for the remote measurement of sleep as biomarkers of depression in real-world settings. These findings may provide the basis for the development of clinical tools to passively monitor disease state and trajectory, with minimal burden on the participant.
Association between mental disorders and subsequent adult onset asthma
Publisher: Elsevier BV
Date: 12-2014
Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study
Publisher: JMIR Publications Inc.
Date: 12-04-2021
DOI: 10.2196/24604
Abstract: Sleep problems tend to vary according to the course of the disorder in in iduals with mental health problems. Research in mental health has associated sleep pathologies with depression. However, the gold standard for sleep assessment, polysomnography (PSG), is not suitable for long-term, continuous monitoring of daily sleep, and methods such as sleep diaries rely on subjective recall, which is qualitative and inaccurate. Wearable devices, on the other hand, provide a low-cost and convenient means to monitor sleep in home settings. The main aim of this study was to devise and extract sleep features from data collected using a wearable device and analyze their associations with depressive symptom severity and sleep quality as measured by the self-assessed Patient Health Questionnaire 8-item (PHQ-8). Daily sleep data were collected passively by Fitbit wristband devices, and depressive symptom severity was self-reported every 2 weeks by the PHQ-8. The data used in this paper included 2812 PHQ-8 records from 368 participants recruited from 3 study sites in the Netherlands, Spain, and the United Kingdom. We extracted 18 sleep features from Fitbit data that describe participant sleep in the following 5 aspects: sleep architecture, sleep stability, sleep quality, insomnia, and hypersomnia. Linear mixed regression models were used to explore associations between sleep features and depressive symptom severity. The z score was used to evaluate the significance of the coefficient of each feature. We tested our models on the entire dataset and separately on the data of 3 different study sites. We identified 14 sleep features that were significantly (P .05) associated with the PHQ-8 score on the entire dataset, among them awake time percentage (z=5.45, P .001), awakening times (z=5.53, P .001), insomnia (z=4.55, P .001), mean sleep offset time (z=6.19, P .001), and hypersomnia (z=5.30, P .001) were the top 5 features ranked by z score statistics. Associations between sleep features and PHQ-8 scores varied across different sites, possibly due to differences in the populations. We observed that many of our findings were consistent with previous studies, which used other measurements to assess sleep, such as PSG and sleep questionnaires. We demonstrated that several derived sleep features extracted from consumer wearable devices show potential for the remote measurement of sleep as biomarkers of depression in real-world settings. These findings may provide the basis for the development of clinical tools to passively monitor disease state and trajectory, with minimal burden on the participant.
Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis
Publisher: JMIR Publications Inc.
Date: 14-08-2023
DOI: 10.2196/45233
Abstract: Major depressive disorder (MDD) affects millions of people worldwide, but timely treatment is not often received owing in part to inaccurate subjective recall and variability in the symptom course. Objective and frequent MDD monitoring can improve subjective recall and help to guide treatment selection. Attempts have been made, with varying degrees of success, to explore the relationship between the measures of depression and passive digital phenotypes (features) extracted from smartphones and wearables devices to remotely and continuously monitor changes in symptomatology. However, a number of challenges exist for the analysis of these data. These include maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold of missing data distinguishing between the cross-sectional and longitudinal relationships for different features to determine their utility in tracking within-in idual longitudinal variation or screening in iduals at high risk and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features. We aimed to address these 3 challenges to inform future work in stratified analyses. Using smartphone and wearable data collected from 479 participants with MDD, we extracted 21 features capturing mobility, sleep, and smartphone use. We investigated the impact of the number of days of available data on feature quality using the intraclass correlation coefficient and Bland-Altman analysis. We then examined the nature of the correlation between the 8-item Patient Health Questionnaire (PHQ-8) depression scale (measured every 14 days) and the features using the in idual-mean correlation, repeated measures correlation, and linear mixed effects model. Furthermore, we stratified the participants based on their behavioral difference, quantified by the features, between periods of high (depression) and low (no depression) PHQ-8 scores using the Gaussian mixture model. We demonstrated that at least 8 (range 2-12) days were needed for reliable calculation of most of the features in the 14-day time window. We observed that features such as sleep onset time correlated better with PHQ-8 scores cross-sectionally than longitudinally, whereas features such as wakefulness after sleep onset correlated well with PHQ-8 longitudinally but worse cross-sectionally. Finally, we found that participants could be separated into 3 distinct clusters according to their behavioral difference between periods of depression and periods of no depression. This work contributes to our understanding of how these mobile health–derived features are associated with depression symptom severity to inform future work in stratified analyses.
Recognition of anxiety disorders by the general practitioner: results from the DASMAP Study
Publisher: Elsevier BV
Date: 05-2012
DOI: 10.1016/J.GENHOSPPSYCH.2012.01.012
Abstract: The objectives were to determine the levels of general practitioner (GP) recognition of anxiety disorders and examine associated factors. An epidemiological survey was carried out in 77 primary care centers representative of Catalonia. A total of 3815 patients were assessed. GPs identified 185 of the 666 in iduals diagnosed as meeting the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) criteria for any anxiety disorder (sensitivity 0.28). Regarding specific anxiety disorders, panic disorder was registered in just three of the patients who, according to the SCID-I, did not meet the criteria for this condition .Generalized anxiety disorder was recorded by the GP in 46 cases, 4 of them being concordant with the SCID-I (sensitivity 0.03). The presence of comorbid hypertension was associated with an increased probability of recognition. Emotional problems as the patients' main complaint and additional appointments with a mental health specialist were associated with both adequate and erroneous recognition. Being female, having more frequent appointments with the GP and having higher levels of self-perceived stress were related to false positives. As disability increased, the probability of being erroneously detected decreased. GPs recognized anxiety disorders in some sufferers but still failed with respect to differentiating between anxiety disorder subtypes and disability assessment.
Predicting Depressive Symptom Severity through Individuals’ Nearby Bluetooth Devices Count Data Collected by Mobile Phones: A Preliminary Longitudinal Study (Preprint)
Publisher: JMIR Publications Inc.
Date: 23-04-2021
DOI: 10.2196/29840
Psychotic experiences and religiosity: data from the WHO World Mental Health Surveys
Publisher: Wiley
Date: 16-02-2018
DOI: 10.1111/ACPS.12859
Health-related quality of life in the Cambridge City over-75s Cohort (CC75C): development of a dementia-specific scale and descriptive analyses
Publisher: Springer Science and Business Media LLC
Date: 10-02-2014
Psychotropic prescribing in Catalonia: results from an epidemiological study
Publisher: Oxford University Press (OUP)
Date: 15-09-2011
Abstract: Mental disorders (MDs) are mainly treated in primary care (PC), where psychotropic drug (PSD) prescribing is highly prevalent. Prescription of PSD is associated with clinical and non-clinical factors. To describe the patterns of PSD prescribing over a 12-month period and to determine the factors associated with this in a PC population. Cross-sectional study. Data were collected on 3815 patients, via patient interview, on sociodemographics and MDs [Diagnostic and Statistical Manual of Mental Disorders (DSM-IV criteria)]. Computerized records provided data on PSD prescribing. Multilevel logistic regressions assessed the factors that influence prescribing. Thirty-four per cent of PC patients were prescribed PSDs >12 months, with anxiolytics being the most commonly prescribed (22%). Fifty-three per cent of patients with any MD in this 12-month period were prescribed PSDs however, 25% of patients without any of these disorders were also prescribed these medications. Higher rates of prescribing were associated with female gender, older age, presence of MD, being a househusband/housewife, consulting about psychological problems, increasing number of consultations and higher self-perceived disability. PSDs were less likely to be prescribed to patients born outside Spain and those consulting about physical conditions. PSD prescribing was higher in patients previously married and antipsychotic prescribing was higher in patients never married. No statistically significant associations were found between PSD prescription and education. PSD prescribing rates are high in Catalonia and are associated with a number of clinical and non-clinical factors. A significant proportion of patients are receiving these drugs in the absence of MD. These findings need to be considered when prescribing in PC.
Associations Between Depression Symptom Severity and Daily-Life Gait Characteristics Derived From Long-Term Acceleration Signals in Real-World Settings: Retrospective Analysis
Publisher: JMIR Publications Inc.
Date: 04-10-2022
DOI: 10.2196/40667
Abstract: Gait is an essential manifestation of depression. However, the gait characteristics of daily walking and their relationships with depression have yet to be fully explored. The aim of this study was to explore associations between depression symptom severity and daily-life gait characteristics derived from acceleration signals in real-world settings. We used two ambulatory data sets (N=71 and N=215) with acceleration signals collected by wearable devices and mobile phones, respectively. We extracted 12 daily-life gait features to describe the distribution and variance of gait cadence and force over a long-term period. Spearman coefficients and linear mixed-effects models were used to explore the associations between daily-life gait features and depression symptom severity measured by the 15-item Geriatric Depression Scale (GDS-15) and 8-item Patient Health Questionnaire (PHQ-8) self-reported questionnaires. The likelihood-ratio (LR) test was used to test whether daily-life gait features could provide additional information relative to the laboratory gait features. Higher depression symptom severity was significantly associated with lower gait cadence of high-performance walking (segments with faster walking speed) over a long-term period in both data sets. The linear regression model with long-term daily-life gait features (R2=0.30) fitted depression scores significantly better (LR test P=.001) than the model with only laboratory gait features (R2=0.06). This study indicated that the significant links between daily-life walking characteristics and depression symptom severity could be captured by both wearable devices and mobile phones. The daily-life gait patterns could provide additional information for predicting depression symptom severity relative to laboratory walking. These findings may contribute to developing clinical tools to remotely monitor mental health in real-world settings.
Erratum to: Associations between DSM-IV mental disorders and diabetes mellitus: a role for impulse control disorders and depression
Publisher: Springer Science and Business Media LLC
Date: 28-03-2014
Gender Differences in Psychotropic Use Across Europe: Results From a Large Cross-Sectional, Population-Based Study
Publisher: Cambridge University Press (CUP)
Date: 04-07-2015
DOI: 10.1016/J.EURPSY.2015.05.001
Abstract: In many epidemiological studies, women have been observed to consume psychotropic medication more often than men. However, the consistency of this relationship across Europe, with differences in mental health care (MHC) resources and reimbursement policies, is unknown. Questions on 12-month psychotropic use (antidepressants, benzodiazepines, antipsychotics, mood stabilizers) were asked to 34,204 respondents from 10 European countries of the EU-World Mental Health surveys. Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) criteria were used to determine 12-month prevalence of mood/anxiety disorders using the Composite International Diagnostic Interview (v3.0). For all participating countries, women were significantly more likely than men to use psychotropic medication within the previous 12 months (overall-OR = 2.04, 95% CI: 1.81–2.31). This relationship remained significant after adjusting for common sociodemographic factors (age, income level, employment status, education, marital status) and country-level indicators (MHC provision, private household out-of-pocket expenditure, and Gender Gap Index). In multivariable gender-stratified risk-factor analysis, both women and men were more likely to have taken psychotropic medication with increasing age, decreasing income level, and mental health care use within the past 12 months, with no significant differences between genders. When only including participants with a mental disorder, gender differences overall were still significant with any 12-month mood disorder but not with any 12-month anxiety disorder, remaining so after adjusting for sociodemographic characteristics and country-level indicators. Women use psychotropic medication consistently more often than men, yet reasons for their use are similar between genders. These differences also appear to be contingent on the specific mental disorder.
Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013
Publisher: Elsevier BV
Date: 09-2014
Proportion of patients without mental disorders being treated in mental health services worldwide
Publisher: Royal College of Psychiatrists
Date: 02-2015
DOI: 10.1192/BJP.BP.113.141424
Abstract: Previous research suggests that many people receiving mental health treatment do not meet criteria for a mental disorder but are rather ‘the worried well’. To examine the association of past-year mental health treatment with DSM-IV disorders. The World Health Organization's World Mental Health (WMH) Surveys interviewed community s les of adults in 23 countries ( n = 62 305) about DSM-IV disorders and treatment in the past 12 months for problems with emotions, alcohol or drugs. Roughly half (52%) of people who received treatment met criteria for a past-year DSM-IV disorder, an additional 18% for a lifetime disorder and an additional 13% for other indicators of need (multiple subthreshold disorders, recent stressors or suicidal behaviours). Dose–response associations were found between number of indicators of need and treatment. The vast majority of treatment in the WMH countries goes to patients with mental disorders or other problems expected to benefit from treatment.
Multi-Country Evaluation of Affective Experience: Validation of an Abbreviated Version of the Day Reconstruction Method in Seven Countries
Publisher: Public Library of Science (PLoS)
Date: 23-04-2013
Essential oil composition, antioxidant and antibacterial activities of wild and cultivated Lavandula mairei Humbert
Publisher: Elsevier BV
Date: 02-2018
Factors predictive of response, disease progression, and overall survival after dabrafenib and trametinib combination treatment: a pooled analysis of individual patient data from randomised trials
Publisher: Elsevier BV
Date: 12-2016
Predicting Depressive Symptom Severity through Individuals’ Nearby Bluetooth Devices Count Data Collected by Mobile Phones: A Preliminary Longitudinal study (Preprint)
Publisher: JMIR Publications Inc.
Date: 23-04-2021
Abstract: he Bluetooth sensor embedded in mobile phones provides an unobtrusive, continuous, and cost-efficient means to capture in iduals’ proximity information, such as the nearby Bluetooth devices count (NBDC). The continuous NBDC data can partially reflect in iduals’ behaviors and status, such as social connections and interactions, working status, mobility, and social isolation and loneliness, which were found to be significantly associated with depression by previous survey-based studies. his paper aims to explore the NBDC data’s value in predicting depressive symptom severity as measured via the 8-item Patient Health Questionnaire (PHQ-8). he data used in this paper included 2,886 bi-weekly PHQ-8 records collected from 316 participants recruited from three study sites in the Netherlands, Spain, and the UK as part of the EU RADAR-CNS study. From the NBDC data two weeks prior to each PHQ-8 score, we extracted 49 Bluetooth features, including statistical features and nonlinear features for measuring periodicity and regularity of in iduals’ life rhythms. Linear mixed-effect models were used to explore associations between Bluetooth features and the PHQ-8 score. We then applied hierarchical Bayesian linear regression models to predict the PHQ-8 score from the extracted Bluetooth features. number of significant associations were found between Bluetooth features and depressive symptom severity. Generally speaking, along with the depressive symptoms worsening, one or more of the following changes were found in the preceding two weeks’ NBDC data: (1) the amount decreased, (2) the variance decreased, (3) the periodicity (especially circadian rhythm) decreased, and (4) the NBDC sequence became more irregular. Compared with commonly used machine learning models, the proposed hierarchical Bayesian linear regression model achieved the best prediction metrics, R^2= 0.526, and root mean squared error (RMSE) of 3.891. Bluetooth features can explain an extra 18.8% of the variance in the PHQ-8 score relative to the baseline model without Bluetooth features (R^2=0.338, RMSE = 4.547). ur statistical results indicate that the NBDC data has the potential to reflect changes in in iduals’ behaviors and status concurrent with the changes in the depressive state. The prediction results demonstrate the NBDC data has a significant value in predicting depressive symptom severity. These findings may have utility for mental health monitoring practice in real-world settings.
Novel technical developments in mass spectrometry imaging in 2020: A mini review
Publisher: Wiley
Date: 16-03-2021
Abstract: The applicability of mass spectrometry imaging (MSI) has exponentially increased with the improvement of s le preparation, instrumentation (spatial resolution) and data analysis. The number of MSI publications listed in PubMed continues to grow with 378 published articles in 2020‐2021. Initially, MSI was just sensitive enough to identify molecular features correlating with distinct tissue regions, similar to the resolution achieved by visual inspection after standard immunohistochemical staining. Although the spatial resolution was limited compared with other imaging modalities, the molecular intensity mapping added a new exciting capability. Over the past decade, significant improvements in every step of the workflow and most importantly in instrumentation were made, which now enables the molecular analysis at a cellular and even subcellular level. Here, we summarize the latest developments in MSI, with a focus on the latest approaches for tissue‐based imaging described in 2020.
Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis (Preprint)
Publisher: JMIR Publications Inc.
Date: 21-12-2022
Abstract: ajor depressive disorder (MDD) affects millions of people worldwide, but timely treatment is not often received owing in part to inaccurate subjective recall and variability in the symptom course. Objective and frequent MDD monitoring can improve subjective recall and help to guide treatment selection. Attempts have been made, with varying degrees of success, to explore the relationship between the measures of depression and passive digital phenotypes (features) extracted from smartphones and wearables devices to remotely and continuously monitor changes in symptomatology. However, a number of challenges exist for the analysis of these data. These include maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold of missing data distinguishing between the cross-sectional and longitudinal relationships for different features to determine their utility in tracking within-in idual longitudinal variation or screening in iduals at high risk and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features. e aimed to address these 3 challenges to inform future work in stratified analyses. sing smartphone and wearable data collected from 479 participants with MDD, we extracted 21 features capturing mobility, sleep, and smartphone use. We investigated the impact of the number of days of available data on feature quality using the intraclass correlation coefficient and Bland-Altman analysis. We then examined the nature of the correlation between the 8-item Patient Health Questionnaire (PHQ-8) depression scale (measured every 14 days) and the features using the in idual-mean correlation, repeated measures correlation, and linear mixed effects model. Furthermore, we stratified the participants based on their behavioral difference, quantified by the features, between periods of high (depression) and low (no depression) PHQ-8 scores using the Gaussian mixture model. e demonstrated that at least 8 (range 2-12) days were needed for reliable calculation of most of the features in the 14-day time window. We observed that features such as sleep onset time correlated better with PHQ-8 scores cross-sectionally than longitudinally, whereas features such as wakefulness after sleep onset correlated well with PHQ-8 longitudinally but worse cross-sectionally. Finally, we found that participants could be separated into 3 distinct clusters according to their behavioral difference between periods of depression and periods of no depression. his work contributes to our understanding of how these mobile health–derived features are associated with depression symptom severity to inform future work in stratified analyses.
Assessment of yeast physiology during industrial‐scale brewing practices using the redox‐sensitive dye resazurin
Publisher: Wiley
Date: 18-04-2023
DOI: 10.1002/YEA.3851
Abstract: Beer refermentation in bottles is an industrial process utilized by breweries where yeast and fermentable extract are added to green beer. The beer is refermented for a minimum of 2 weeks before distribution, with the physiological state of the yeast a critical factor for successful refermentation. Ideally, fresh yeast that is propagated from a dedicated propagation plant should be used for refermentation in bottles. Here, we explored the applicability of the fluorescent and redox‐sensitive dye, resazurin, to assess cellular metabolism in yeast and its ability to differentiate between growth stages. We applied this assay, with other markers of yeast physiology, to evaluate yeast quality during a full‐scale industrial propagation. Resazurin allowed the discrimination between the different growth phases in yeast and afforded a more in‐depth understanding of yeast metabolism during propagation. This assay can be used to optimize the yeast propagation process and cropping time to improve beer quality.
Chemical characterization and antifungal activities of four Thymus species essential oils against postharvest fungal pathogens of citrus
Publisher: Elsevier BV
Date: 08-2016
Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global
Publisher: Elsevier BV
Date: 08-2015
Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19
Publisher: JMIR Publications Inc.
Date: 25-09-2020
DOI: 10.2196/19992
Abstract: In the absence of a vaccine or effective treatment for COVID-19, countries have adopted nonpharmaceutical interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of passively monitoring the impact and response of these interventions at a local level is needed. We aim to explore the utility of the recently developed open-source mobile health platform Remote Assessment of Disease and Relapse (RADAR)–base as a toolbox to rapidly test the effect and response to NPIs intended to limit the spread of COVID-19. We analyzed data extracted from smartphone and wearable devices, and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the United Kingdom, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, the maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post hoc Dunn tests to assess differences in these features among baseline, prelockdown, and during lockdown periods. We also studied behavioral differences by age, gender, BMI, and educational background. We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between prelockdown and during lockdown periods (P .001 for all five countries). We saw reduced sociality as measured through mobility features and increased virtual sociality through phone use. People were more active on their phones (P .001 for Italy, Spain, and the United Kingdom), spending more time using social media apps (P .001 for Italy, Spain, the United Kingdom, and the Netherlands), particularly around major news events. Furthermore, participants had a lower heart rate (P .001 for Italy and Spain P=.02 for Denmark), went to bed later (P .001 for Italy, Spain, the United Kingdom, and the Netherlands), and slept more (P .001 for Italy, Spain, and the United Kingdom). We also found that young people had longer homestay than older people during the lockdown and fewer daily steps. Although there was no significant difference between the high and low BMI groups in time spent at home, the low BMI group walked more. RADAR-base, a freely deployable data collection platform leveraging data from wearables and mobile technologies, can be used to rapidly quantify and provide a holistic view of behavioral changes in response to public health interventions as a result of infectious outbreaks such as COVID-19. RADAR-base may be a viable approach to implementing an early warning system for passively assessing the local compliance to interventions in epidemics and pandemics, and could help countries ease out of lockdown.
Associations between DSM-IV mental disorders and diabetes mellitus: a role for impulse control disorders and depression
Publisher: Springer Science and Business Media LLC
Date: 02-02-2014
The association between psychotic experiences and disability: results from the WHO World Mental Health Surveys
Publisher: Wiley
Date: 25-05-2017
DOI: 10.1111/ACPS.12749
Abstract: While psychotic experiences ( PE s) are known to be associated with a range of mental and general medical disorders, little is known about the association between PE s and measures of disability. We aimed to investigate this question using the World Mental Health surveys. Lifetime occurrences of six types of PE s were assessed along with 21 mental disorders and 14 general medical conditions. Disability was assessed with a modified version of the WHO Disability Assessment Schedule. Descriptive statistics and logistic regression models were used to investigate the association between PE s and high disability scores (top quartile) with various adjustments. Respondents with PE s were more likely to have top quartile scores on global disability than respondents without PE s (19.1% vs. 7.5% χ 2 = 190.1, P 0.001) as well as greater likelihood of cognitive, social, and role impairment. Relationships persisted in each adjusted model. A significant dose–response relationship was also found for the PE type measures with most of these outcomes. Psychotic experiences are associated with disability measures with a dose–response relationship. These results are consistent with the view that PE s are associated with disability regardless of the presence of comorbid mental or general medical disorders.
Treatment adequacy of anxiety and depressive disorders: Primary versus specialised care in Spain
Publisher: Elsevier BV
Date: 11-2006
DOI: 10.1016/J.JAD.2006.05.005
Abstract: Literature suggests that a high proportion of the population with mental disorders remains either untreated or poorly treated. This study aimed to describe the adequacy of treatment for Anxiety and Depressive disorders in Spain, how this differs between providers (primary versus specialised care) and which factors are associated with appropriate care. Data were derived from the Spanish s le (N=5473) of the European Study of the Epidemiology of Mental Disorders (ESEMeD), a cross sectional study in a representative s le of adults. The subs le analyzed was composed by the 133 subjects with a mental disorder in the year prior to the interview who received treatment. Treatment adequacy was evaluated in two different ways: (1) considering definitions of minimally adequate treatment evidence based guidelines and criteria used in other epidemiological studies (2) considering experts rating of treatment appropriateness based on the information contained in the case vignettes created from the CIDI answers. Generalised Estimating Equation (GEE) models and simple logistic regression were conducted to assess the correlates of adequate treatment. Similar proportions of patients in specialty and general medical treatment received a minimally adequate treatment (31.8% and 30.5%, respectively). Associated factors to appropriateness were living in a large city, having a high educational level, and having a good self rated health state. Treatment adequacy was based on simple information and criteria. Only one third of the mental health treatment in Spain met minimal adequacy criteria. More research is needed in order to find out reasons for these low rates.
Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19 (Preprint)
Publisher: JMIR Publications Inc.
Date: 08-05-2020
Abstract: n the absence of a vaccine or effective treatment for COVID-19, countries have adopted nonpharmaceutical interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of passively monitoring the impact and response of these interventions at a local level is needed. e aim to explore the utility of the recently developed open-source mobile health platform Remote Assessment of Disease and Relapse (RADAR)–base as a toolbox to rapidly test the effect and response to NPIs intended to limit the spread of COVID-19. e analyzed data extracted from smartphone and wearable devices, and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the United Kingdom, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, the maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post hoc Dunn tests to assess differences in these features among baseline, prelockdown, and during lockdown periods. We also studied behavioral differences by age, gender, BMI, and educational background. e were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between prelockdown and during lockdown periods ( i P /i & .001 for all five countries). We saw reduced sociality as measured through mobility features and increased virtual sociality through phone use. People were more active on their phones ( i P /i & .001 for Italy, Spain, and the United Kingdom), spending more time using social media apps ( i P /i & .001 for Italy, Spain, the United Kingdom, and the Netherlands), particularly around major news events. Furthermore, participants had a lower heart rate ( i P /i & .001 for Italy and Spain i P /i =.02 for Denmark), went to bed later ( i P /i & .001 for Italy, Spain, the United Kingdom, and the Netherlands), and slept more ( i P /i & .001 for Italy, Spain, and the United Kingdom). We also found that young people had longer homestay than older people during the lockdown and fewer daily steps. Although there was no significant difference between the high and low BMI groups in time spent at home, the low BMI group walked more. ADAR-base, a freely deployable data collection platform leveraging data from wearables and mobile technologies, can be used to rapidly quantify and provide a holistic view of behavioral changes in response to public health interventions as a result of infectious outbreaks such as COVID-19. RADAR-base may be a viable approach to implementing an early warning system for passively assessing the local compliance to interventions in epidemics and pandemics, and could help countries ease out of lockdown.
La carga de la enfermedad en España 2010: trastornos neurológicos, mentales y re: trastornos neurológicos, mentales y relacionados con el consumo de sustancias
Publisher: Elsevier BV
Date: 10-2015
DOI: 10.1016/J.RPSM.2014.09.001
Abstract: We used data from the Global Burden of Disease, Injuries, and Risk Factors Study 2010 to report on the burden of neuropsychiatric disorders in Spain. The summary measure of burden used in the study was the disability-adjusted life-year (DALY), which sums of the years of life lost due to premature mortality (YLLs) and the years lived with disability (YLDs). DALYs were adjusted for comorbidity and estimated with 95% uncertainty intervals. The burden of neuropsychiatric disorders accounted for 18.4% of total all-cause DALYs generated in Spain for 2010. Within this group, the top five leading causes of DALYs were: depressive disorders, Alzheimer's disease, migraine, substance-use disorders, and anxiety disorder, which accounted for 70.9% of all DALYs due to neuropsychiatric disorders. Neurological disorders represented 5.03% of total all cause YLLs, whereas mental and substance-use disorders accounted for 0.8%. Mental and substance-use disorders accounted for 22.4% of total YLDs, with depression being the most disabling disorder. Neurological disorders represented 8.3% of total YLDs. Neuropsychiatric disorders were one of the leading causes of disability in 2010. This finding contributes to our understanding of the burden of neuropsychiatric disorders in the Spanish population and highlights the importance of prioritising neuropsychiatric disorders in the Spanish public health system.
Rapid separation and identification of beer spoilage bacteria by inertial microfluidics and MALDI-TOF mass spectrometry
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C9LC00152B
Abstract: Microfluidics and MALDI-TOF MS is a rapid, high-throughput, and accurate method for the identification of beer spoilage bacteria.
Prevalencia y factores de riesgo de las ideas, planes e intentos de suicidio en la población general española. Resultados del estudio ESEMeD
Publisher: Elsevier BV
Date: 10-2007
DOI: 10.1157/13111370
Abstract: Suicide is a public health problem and it is increasing in Spain. The objective of this study is to analyze the prevalence and risk factors of suicide related outcomes (ideation, plan and attempt) using data from the ESEMeD-Spain project. This is a face-to-face household survey carried out in a probability representative s le of the adult general population of Spain. 5,473 subjects were interviewed using the Composite International Diagnostic Interview (CIDI 3.0), developed by the World Mental Health Survey Initiative. Lifetime prevalence of suicide ideation and attempts was 4.4% and 1.5%, respectively. Risk of suicide related outcomes was significantly higher among women (odds ratio [OR] = 2.3-2.7), younger cohorts (OR = 21.3-86), and lower education levels (OR = 5.3-6.4). Having a mental disorder was associated to an increased risk in all diagnostic categories, but especially in major depressive episode (OR = 5.3-6.8). Risk of suicide attempt was higher during the first year since the onset of ideation (OR = 30.2), decreasing thereafter. The prevalence of suicide related outcomes is low when compared with other countries. Results identified groups with higher risk (women, young, subjects with a mental disorder, psychiatric comorbidity and recent suicidal ideation) in which suicide prevention could show benefits.
A framework for evidence‐based mental health care and policy
Publisher: Wiley
Date: 07-11-2006
DOI: 10.1111/J.1600-0447.2006.00914.X
Abstract: Care planning integrates a growing number of disciplines, research fields and analysis techniques. A framework of the main areas of interest with regard to evidence-based health care in mental health is provided here. The framework is based on the experience of working with data analysts and health and social decision makers at the PSICOST/RIRAG network, a Spanish research association which includes psychiatrists, health economists and health policy experts, as well as on a review of the literature. Three main areas have been identified and described here: outcomes management, knowledge discovery from data, and decision support systems. Their use in mental health care is reviewed. It is important to promote bridging strategies among these new fields in order to enhance communication and information transfer between the different parts involved in mental health decision making: i) clinicians and epidemiologists, ii) data analysts, iii) care policy makers and other end-users.
Utilisation of mental health services and costs of patients with schizophrenia in three areas of Spain
Publisher: Royal College of Psychiatrists
Date: 10-1998
Abstract: The analysis of the costs of schizophrenia and its treatment under different mental health care structures will facilitate the improved allocation of the limited resources available for the treatment of schizophrenia. The research we present compares health service use and total health care costs of three cohorts of subjects with schizophrenia which are representative of three areas of Spain (Burlada in Navarra, Cantabria and the Eix le of Barcelona). We selected first-time contacts with any psychiatric service who received a diagnosis of schizophrenia. Subjects were evaluated in the third year after onset. The mean number of out-patient visits per patient per year was 10.7 and the mean in-patient days were 9.5. The mean direct cost per patient in the third year of treatment was US$2243. Costs were higher for single subjects and for people who had a relapse. Costs of subjects with better functioning were lower than costs of subjects with a worse state. Direct costs of care in Spain were lower than the reported figures from other western European countries. Costs were greater in the two centres with greater community mental health service development. Some of the findings may be explained by service availability.
Assessment of service use patterns in out‐patients with schizophrenia: a Spanish study
Publisher: Wiley
Date: 07-11-2006
DOI: 10.1111/J.1600-0447.2006.00915.X
Abstract: The objective is to describe and characterize patterns of service use by out-patients with schizophrenia in Spain. A representative treated prevalence s le of cases with schizophrenia was selected from four Spanish health areas. The evaluation included health service use, clinical severity, functioning and disability. Statistical analysis was based on hierarchical clustering methods. A total of 356 patients were included in the analysis. Five patterns of health service use were defined: heavy out-patient mental health users mental health and general health service users heavy hospital service users nursing service users low users of mental health services. Patients in each group showed differences in clinical and disability status. Patterns of health service use showed consistency, but also variability, among the geographical areas. Development and organization of mental health services should take into account the combinations of services patients most frequently use.
Treatment adequacy for anxiety and depressive disorders in six European countries
Publisher: Royal College of Psychiatrists
Date: 02-2007
DOI: 10.1192/BJP.BP.106.023507
Abstract: The aims of this study areto describe the adequacy of treatment for anxiety and depressive disorders in Europe and how it differs between providers, using data from the ESEMeD study The overall proportion of adequate treatment was 45.8% (57.4% in the specialised sector and 23.3% in the general medical care sector). Between-country differences were found in treatment adequacy in the specialised setting. Organisational and political aspects may explain these findings.
Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study
Publisher: JMIR Publications Inc.
Date: 11-03-2022
DOI: 10.2196/34898
Abstract: The mobility of an in idual measured by phone-collected location data has been found to be associated with depression however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored. We aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time. Data used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse–Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants’ location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility. This study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-in idual level than the between-in idual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=−0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=−0.07, P .001) the subsequent periodicity of mobility. Several phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings.
The Association Between Home Stay and Symptom Severity in Major Depressive Disorder: Preliminary Findings From a Multicenter Observational Study Using Geolocation Data From Smartphones
Publisher: JMIR Publications Inc.
Date: 28-01-2022
DOI: 10.2196/28095
Abstract: Most smartphones and wearables are currently equipped with location sensing (using GPS and mobile network information), which enables continuous location tracking of their users. Several studies have reported that various mobility metrics, as well as home stay, that is, the amount of time an in idual spends at home in a day, are associated with symptom severity in people with major depressive disorder (MDD). Owing to the use of small and homogeneous cohorts of participants, it is uncertain whether the findings reported in those studies generalize to a broader population of in iduals with MDD symptoms. The objective of this study is to examine the relationship between the overall severity of depressive symptoms, as assessed by the 8-item Patient Health Questionnaire, and median daily home stay over the 2 weeks preceding the completion of a questionnaire in in iduals with MDD. We used questionnaire and geolocation data of 164 participants with MDD collected in the observational Remote Assessment of Disease and Relapse–Major Depressive Disorder study. The participants were recruited from three study sites: King’s College London in the United Kingdom (109/164, 66.5%) Vrije Universiteit Medisch Centrum in Amsterdam, the Netherlands (17/164, 10.4%) and Centro de Investigación Biomédica en Red in Barcelona, Spain (38/164, 23.2%). We used a linear regression model and a res ling technique (n=100 draws) to investigate the relationship between home stay and the overall severity of MDD symptoms. Participant age at enrollment, gender, occupational status, and geolocation data quality metrics were included in the model as additional explanatory variables. The 95% 2-sided CIs were used to evaluate the significance of model variables. Participant age and severity of MDD symptoms were found to be significantly related to home stay, with older (95% CI 0.161-0.325) and more severely affected in iduals (95% CI 0.015-0.184) spending more time at home. The association between home stay and symptoms severity appeared to be stronger on weekdays (95% CI 0.023-0.178, median 0.098 home stay: 25th-75th percentiles 17.8-22.8, median 20.9 hours a day) than on weekends (95% CI −0.079 to 0.149, median 0.052 home stay: 25th-75th percentiles 19.7-23.5, median 22.3 hours a day). Furthermore, we found a significant modulation of home stay by occupational status, with employment reducing home stay (employed participants: 25th-75th percentiles 16.1-22.1, median 19.7 hours a day unemployed participants: 25th-75th percentiles 20.4-23.5, median 22.6 hours a day). Our findings suggest that home stay is associated with symptom severity in MDD and demonstrate the importance of accounting for confounding factors in future studies. In addition, they illustrate that passive sensing of in iduals with depression is feasible and could provide clinically relevant information to monitor the course of illness in patients with MDD.
Adjustment disorders in primary care: prevalence, recognition and use of services
Publisher: Royal College of Psychiatrists
Date: 08-2012
DOI: 10.1192/BJP.BP.111.096305
Abstract: Within the ICD and DSM review processes there is growing debate on the future classification and status of adjustment disorders, even though evidence on this clinical entity is scant, particularly outside specialised care. To estimate the prevalence of adjustment disorders in primary care to explore whether there are differences between primary care patients with adjustment disorders and those with other mental disorders and to describe the recognition and treatment of adjustment disorders by general practitioners (GPs). Participants were drawn from a cross-sectional survey of a representative s le of 3815 patients from 77 primary healthcare centres in Catalonia. The prevalence of current adjustment disorders and subtypes were assessed face to face using the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I). Multilevel logistic regressions were conducted to assess differences between adjustment disorders and other mental disorders. Recognition and treatment of adjustment disorders by GPs were assessed through a review of patients' computerised clinical histories. The prevalence of adjustment disorders was 2.94%. Patients with adjustment disorders had higher mental quality-of-life scores than patients with major depressive disorder but lower than patients without mental disorder. Self-perceived stress was also higher in adjustment disorders compared with those with anxiety disorders and those without mental disorder. Recognition of adjustment disorders by GPs was low: only 2 of the 110 cases identified using the SCID-I were detected by the GP. Among those with adjustment disorders, 37% had at least one psychotropic prescription. Adjustment disorder shows a distinct profile as an intermediate category between no mental disorder and affective disorders (depression and anxiety disorders).
Degree of cognitive impairment and mortality: a 17-year follow-up in a community study
Publisher: Cambridge University Press (CUP)
Date: 06-06-2014
DOI: 10.1017/S2045796014000390
Abstract: To test the hypothesis that cognitive impairment in older adults is associated with all-cause mortality risk and the risk increases when the degree of cognitive impairment augments and then, if this association is confirmed, to report the population-attributable fraction (PAF) of mortality due to cognitive impairment. A representative random community s le of in iduals aged over 55 was interviewed, and 4557 subjects remaining alive at the end of the first year of follow-up were included in the analysis. Instruments used in the assessment included the Mini-Mental Status Examination (MMSE), the History and Aetiology Schedule (HAS) and the Geriatric Mental State (GMS)-AGECAT. For the standardised degree of cognitive impairment Perneczky et al 's MMSE criteria were applied. Mortality information was obtained from the official population registry. Multivariate Cox proportional hazard models were used to test the association between MMSE degrees of cognitive impairment and mortality risk. We also estimated the PAF of mortality due to specific MMSE stages. Cognitive impairment was associated with mortality risk, the risk increasing in parallel with the degree of cognitive impairment (Hazard ratio, HR: 1.18 in the ‘mild’ degree of impairment HR: 1.29 in the ‘moderate’ degree and HR: 2.08 in the ‘severe’ degree). The PAF of mortality due to severe cognitive impairment was 3.49%. A gradient of increased mortality-risk associated with severity of cognitive impairment was observed. The results support the claim that routine assessment of cognitive function in older adults should be considered in clinical practice.
Biopsychosocial response to the COVID-19 lockdown in people with major depressive disorder and multiple sclerosis
Publisher: Cold Spring Harbor Laboratory
Date: 10-05-2022
DOI: 10.1101/2022.05.10.22274890
Abstract: Changes in lifestyle, finances and work status during COVID-19 lockdowns may have led to biopsychosocial changes in people with pre-existing vulnerabilities such as Major Depressive Disorders (MDD) and Multiple Sclerosis (MS). Data were collected as a part of the RADAR-CNS (Remote Assessment of Disease and Relapse – Central Nervous System) programme. We analyzed the following data from long-term participants in a decentralized multinational study: symptoms of depression, heart rate (HR) during the day and night social activity sedentary state, steps and physical activity of varying intensity. Linear mixed-effects regression analyses with repeated measures were fitted to assess the changes among three time periods (pre, during and post-lockdown) across the groups, adjusting for depression severity before the pandemic and gender. Participants with MDD (N=255) and MS (N=214) were included in the analyses. Overall, depressive symptoms remained stable across the three periods in both groups. Lower mean HR and HR variation were observed between pre and during lockdown during the day for MDD and during the night for MS. HR variation during rest periods also decreased between pre-and post-lockdown in both clinical conditions. We observed a reduction of physical activity for MDD and MS upon the introduction of lockdowns. The group with MDD exhibited a net increase in social interaction via social network apps over the three periods. Behavioral response to the lockdown measured by social activity, physical activity and HR may reflect changes in stress in people with MDD and MS.
Health-related quality-of-life instruments for Alzheimer's disease and mixed dementia
Publisher: Cambridge University Press (CUP)
Date: 11-01-2013
DOI: 10.1017/S1041610212002293
Abstract: Background: Over the last 20 years, a number of instruments developed for the assessment of health-related quality of life (HRQL) in dementia have been introduced. The aim of this review is to synthesize evidence from published reviews on HRQL measures in dementia and any new literature in order to identify dementia specific HRQL instruments, the domains they measure, and their operationalization. Methods: An electronic search of PsycINFO and PubMed was conducted, from inception to December 2011 using a combination of key words that included quality of life and dementia. Results: Fifteen dementia-specific HRQL instruments were identified. Instruments varied depending on their country of development/validation, dementia severity, data collection method, operationalization of HRQL in dementia, psychometric properties, and the scoring. The most common domains assessed include mood, self-esteem, social interaction, and enjoyment of activities. Conclusions: A number of HRQL instruments for dementia are available. The suitability of the scales for different contexts is discussed. Many studies do not specifically set out to measure dementia-specific HRQL but do include related items. Determining how best to operationalize the many HRQL domains will be helpful for mapping measures of HRQL in such studies maximizing the value of existing resources.
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