Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis.

BACKGROUND: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. OBJECTIVE: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts. METHODS: Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score. RESULTS: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (ß=-93.61, P<.001), increased sleep variability (ß=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: ß=0.55, P=.001; sleep offset: ß=1.12, P<.001; M10 onset: ß=0.73, P=.003; HR acrophase: ß=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (ß of PHQ-8 × spring = -31.51, P=.002) and summer (ß of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (ß of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer. CONCLUSIONS: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

Antidepressants for the treatment of depression in people with cancer.

BACKGROUND: Major depression and other depressive conditions are common in people with cancer. These conditions are not easily detectable in clinical practice, due to the overlap between medical and psychiatric symptoms, as described by diagnostic manuals such as the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD). Moreover, it is particularly challenging to distinguish between pathological and normal reactions to such a severe illness. Depressive symptoms, even in subthreshold manifestations, have a negative impact in terms of quality of life, compliance with anticancer treatment, suicide risk and possibly the mortality rate for the cancer itself. Randomised controlled trials (RCTs) on the efficacy, tolerability and acceptability of antidepressants in this population are few and often report conflicting results. OBJECTIVES: To evaluate the efficacy, tolerability and acceptability of antidepressants for treating depressive symptoms in adults (aged 18 years or older) with cancer (any site and stage). SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was November 2022. SELECTION CRITERIA: We included RCTs comparing antidepressants versus placebo, or antidepressants versus other antidepressants, in adults (aged 18 years or above) with any primary diagnosis of cancer and depression (including major depressive disorder, adjustment disorder, dysthymic disorder or depressive symptoms in the absence of a formal diagnosis). DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcome was 1. efficacy as a continuous outcome. Our secondary outcomes were 2. efficacy as a dichotomous outcome, 3. Social adjustment, 4. health-related quality of life and 5. dropouts. We used GRADE to assess certainty of evidence for each outcome. MAIN RESULTS: We identified 14 studies (1364 participants), 10 of which contributed to the meta-analysis for the primary outcome. Six of these compared antidepressants and placebo, three compared two antidepressants, and one three-armed study compared two antidepressants and placebo. In this update, we included four additional studies, three of which contributed data for the primary outcome. For acute-phase treatment response (six to 12 weeks), antidepressants may reduce depressive symptoms when compared with placebo, even though the evidence is very uncertain. This was true when depressive symptoms were measured as a continuous outcome (standardised mean difference (SMD) -0.52, 95% confidence interval (CI) -0.92 to -0.12; 7 studies, 511 participants; very low-certainty evidence) and when measured as a proportion of people who had depression at the end of the study (risk ratio (RR) 0.74, 95% CI 0.57 to 0.96; 5 studies, 662 participants; very low-certainty evidence). No studies reported data on follow-up response (more than 12 weeks). In head-to-head comparisons, we retrieved data for selective serotonin reuptake inhibitors (SSRIs) versus tricyclic antidepressants (TCAs) and for mirtazapine versus TCAs. There was no difference between the various classes of antidepressants (continuous outcome: SSRI versus TCA: SMD -0.08, 95% CI -0.34 to 0.18; 3 studies, 237 participants; very low-certainty evidence; mirtazapine versus TCA: SMD -4.80, 95% CI -9.70 to 0.10; 1 study, 25 participants). There was a potential beneficial effect of antidepressants versus placebo for the secondary efficacy outcomes (continuous outcome, response at one to four weeks; very low-certainty evidence). There were no differences for these outcomes when comparing two different classes of antidepressants, even though the evidence was very uncertain. In terms of dropouts due to any cause, we found no difference between antidepressants compared with placebo (RR 0.85, 95% CI 0.52 to 1.38; 9 studies, 889 participants; very low-certainty evidence), and between SSRIs and TCAs (RR 0.83, 95% CI 0.53 to 1.22; 3 studies, 237 participants). We downgraded the certainty of the evidence because of the heterogeneous quality of the studies, imprecision arising from small sample sizes and wide CIs, and inconsistency due to statistical or clinical heterogeneity. AUTHORS' CONCLUSIONS: Despite the impact of depression on people with cancer, the available studies were few and of low quality. This review found a potential beneficial effect of antidepressants against placebo in depressed participants with cancer. However, the certainty of evidence is very low and, on the basis of these results, it is difficult to draw clear implications for practice. The use of antidepressants in people with cancer should be considered on an individual basis and, considering the lack of head-to-head data, the choice of which drug to prescribe may be based on the data on antidepressant efficacy in the general population of people with major depression, also taking into account that data on people with other serious medical conditions suggest a positive safety profile for the SSRIs. Furthermore, this update shows that the usage of the newly US Food and Drug Administration-approved antidepressant esketamine in its intravenous formulation might represent a potential treatment for this specific population of people, since it can be used both as an anaesthetic and an antidepressant. However, data are too inconclusive and further studies are needed. We conclude that to better inform clinical practice, there is an urgent need for large, simple, randomised, pragmatic trials comparing commonly used antidepressants versus placebo in people with cancer who have depressive symptoms, with or without a formal diagnosis of a depressive disorder.

Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis.

BACKGROUND: 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-individual longitudinal variation or screening individuals at high risk; and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features. OBJECTIVE: We aimed to address these 3 challenges to inform future work in stratified analyses. METHODS: 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 individual-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. RESULTS: 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. CONCLUSIONS: 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.

Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study.

BACKGROUND: Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data. METHODS: Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse - Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months. RESULTS: Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types. CONCLUSIONS: RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.

High-frequency follow-up studies in musculoskeletal disorders: a scoping review.

OBJECTIVES: This scoping review identifies research in musculoskeletal disorders that uses high frequency follow-up of symptoms. The aim was to investigate whether symptom variability is investigated as a predictor of disease outcome and how intensive follow-up methods are used in musculoskeletal research. METHODS: Embase, MEDLINE and PsycInfo were searched using OVID, and the Institute of Electrical and Electronic Engineers was also searched using the Institute of Electrical and Electronic Engineers Xplore search engine. Studies were systematically reviewed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses, but no meta-analysis was done because the priority in this study is to identify gaps in available literature. RESULTS: Twenty-one papers were included. There was a mean of 54 patients per study (s.d. of 27.7). Two-thirds of the papers looked at how a symptom influences another in the short-term (subsequent assessment in the same day or next day), but none looked at the long-term. Only one study considered symptom variability investigating how higher variability in pain (defined by the s.d.) is associated with higher average pain severity and lower average sleep quality. CONCLUSION: The methodology of musculoskeletal disorder research has changed from completing paper booklets to using electronic data capture (smartphones). There has also been a trend of collecting more intensive longitudinal data, but very little research utilizes these data to look at how symptom variability affects symptom outcomes. This demonstrates a gap in research where furthering understanding of this will help clinicians decide on the most important symptom to address in future patients.

Adherence, Mental Health and Illness Perceptions in Autoimmune Liver Disease: Looking Beyond Liver Function Tests.

OBJECTIVES: Autoimmune liver disease is commonly diagnosed during adolescence; a period associated with a higher prevalence of non-adherence, mental health concerns and worse health outcomes. The aim of the study was to explore adherence patterns, mental health and illness perceptions in young people with autoimmune liver disease. METHODS: Young people with autoimmune liver disease attending a multidisciplinary young adult clinic (16-25 years) completed an electronically administered questionnaire battery. Demographics and disease-related data were collected. RESULTS: Sixty-eight (37 female), median age 17.9 (range 15-22) years completed the screening. Only 51.5% of patients were in remission (aspartate and alanine aminotransferase <36 IU//l) whereas 73% self-reported their adherence >80%. Compared to patients in remission, those not in remission required more immunosuppression, were more depressed and worried but reported a better understanding of their illness. A small but significant correlation was found between aspartate aminotransferase/alanine aminotransferase and adherence percentage (r = -0.27, P < 0.05 and r = -0.29, P < 0.05 respectively). Age was inversely associated with adherence (r = -0.31, P < 0.05), and older patients were more worried (r = 0.44, P < 0.001) and emotionally affected by the condition (r = 0.32, P < 0.01). Adherence behaviours such as forgetting to take medications (63%), taking medications more frequently before attending appointments (44%) and not having a routine for medications (31%) were prevalent, 7% reported intentional non-adherence. CONCLUSION: Sup-optimal adherence to treatment is common in young people with autoimmune liver disease and associated with mental health problems and certain illness perceptions. Routine exploration of adherence beliefs and barriers to adherence in a non-judgmental, collaborative way is essential to improve outcome in this vulnerable population.

Investigating the impact of COVID-19 lockdown on adults with a recent history of recurrent major depressive disorder: a multi-Centre study using remote measurement technology.

BACKGROUND: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes a clinical illness Covid-19, has had a major impact on mental health globally. Those diagnosed with major depressive disorder (MDD) may be negatively impacted by the global pandemic due to social isolation, feelings of loneliness or lack of access to care. This study seeks to assess the impact of the 1st lockdown - pre-, during and post - in adults with a recent history of MDD across multiple centres. METHODS: This study is a secondary analysis of an on-going cohort study, RADAR-MDD project, a multi-centre study examining the use of remote measurement technology (RMT) in monitoring MDD. Self-reported questionnaire and passive data streams were analysed from participants who had joined the project prior to 1st December 2019 and had completed Patient Health and Self-esteem Questionnaires during the pandemic (n = 252). We used mixed models for repeated measures to estimate trajectories of depressive symptoms, self-esteem, and sleep duration. RESULTS: In our sample of 252 participants, 48% (n = 121) had clinically relevant depressive symptoms shortly before the pandemic. For the sample as a whole, we found no evidence that depressive symptoms or self-esteem changed between pre-, during- and post-lockdown. However, we found evidence that mean sleep duration (in minutes) decreased significantly between during- and post- lockdown (- 12.16; 95% CI - 18.39 to - 5.92; p <  0.001). We also found that those experiencing clinically relevant depressive symptoms shortly before the pandemic showed a decrease in depressive symptoms, self-esteem and sleep duration between pre- and during- lockdown (interaction p = 0.047, p = 0.045 and p <  0.001, respectively) as compared to those who were not. CONCLUSIONS: We identified changes in depressive symptoms and sleep duration over the course of lockdown, some of which varied according to whether participants were experiencing clinically relevant depressive symptoms shortly prior to the pandemic. However, the results of this study suggest that those with MDD do not experience a significant worsening in symptoms during the first months of the Covid - 19 pandemic.

Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19.

BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Common mental disorders within chronic inflammatory disorders: a primary care database prospective investigation.

OBJECTIVE: There is inconsistent evidence about the association between inflammatory disorders and depression and anxiety onset in a primary care context. The study aimed to evaluate the risk of depression and anxiety within multisystem and organ-specific inflammatory disorders. METHODS: This is a prospective cohort study with primary care patients from the UK Clinical Practice Research Datalink diagnosed with an inflammatory disorder between 1 January 2001 and 31 December 2016. These patients were matched on age, gender, practice and index date with patients without an inflammatory disorder. The study exposures were seven chronic inflammatory disorders. Clinical diagnosis of depression and anxiety represented the outcome measures of interest. RESULTS: Among 538 707 participants, the incidence of depression ranged from 14 per 1000 person-years (severe psoriasis) to 9 per 1000 person-years (systemic vasculitis), substantively higher compared with their comparison group (5-7 per 1000 person-years). HRs of multiple depression and anxiety events were 16% higher within inflammatory disorders (HR, 1.16, 95% CI 1.12 to 1.21, p<0.001) compared with the matched comparison group. The incidence of depression and anxiety was strongly associated with the age at inflammatory disorder onset. The overall HR estimate for depression was 1.90 (95% CI 1.66 to 2.17, p<0.001) within early-onset disorder (<40 years of age) and 0.93 (95% CI 0.90 to 1.09, p=0.80) within late-onset disorder (≥60 years of age). CONCLUSIONS: Primary care patients with inflammatory disorders have elevated rates of depression and anxiety incidence, particularly those patients with early-onset inflammatory disorders. This finding may reflect the impact of the underlying disease on patients' quality of life, although the precise mechanisms require further investigation.

Patient perspectives on the acceptability of mHealth technology for remote measurement and management of epilepsy: A qualitative analysis.

BACKGROUND: Innovative uses of mobile health (mHealth) technology for real-time measurement and management of epilepsy may improve the care provided to patients. For instance, seizure detection and quantifying related problems will have an impact on quality of life and improve clinical management for people experiencing frequent and uncontrolled seizures. Engaging patients with mHealth technology is essential, but little is known about patient perspectives on their acceptability. The aim of this study was to conduct an in-depth qualitative analysis of what people with uncontrolled epilepsy think could be the potential uses of mHealth technology and to identify early potential barriers and facilitators to engagement in three European countries. METHOD: Twenty people currently experiencing epileptic seizures took part in five focus groups held across the UK, Italy, and Spain. Participants all completed written consent and a demographic questionnaire prior to the focus group commencing, and each group discussion lasted 60-120 min. A coding frame, developed from a systematic review of the previous literature, was used to structure a thematic analysis. We extracted themes and subthemes from the discussions, focusing first on possible uses of mHealth and then the barriers and facilitators to engagement. RESULTS: Participants were interested in mHealth technology as a clinical detection tool, e.g., to aid communication about seizure occurrence with their doctors. Other suggested uses included being able to predict or prevent seizures, and to improve self-management. Key facilitators to engagement were the ability to raise awareness, plan activities better, and improve safety. Key barriers were the potential for increased stigma and anxiety. Using familiar and customizable products could be important moderators of engagement. CONCLUSION: People with uncontrolled epilepsy think that there is a scope for mHealth technology to be useful in healthcare as a detection or prediction tool. The costs will be compared with the benefits when it comes to engagement, and ongoing work with patients and other stakeholders is needed to design practical resources.

The relationship between depression and biologic treatment response in rheumatoid arthritis: An analysis of the British Society for Rheumatology Biologics Register.

Objective: To investigate the relationship between depressive symptoms and treatment response and disease activity in RA over a 1-year follow-up. Methods: Data from the British Society for Rheumatology Biologics Register were used, representing 18 421 RA patients receiving biologic treatment. Depressive symptoms were identified through one of three assessments: reporting a history of depression, the Medical Outcomes Survey 36-item Short Form or the EuroQol five-dimension scale. Logistic regression analyses examined the relationship between baseline depressive symptoms and odds of good treatment response by 1 year. Multilevel models addressed the association between baseline depressive symptoms and disease activity outcomes over 1-year follow-up, adjusting for age, gender, disease duration, comorbidities and baseline disease activity and physical disability. Results: Depression symptoms at biologic treatment initiation were associated with 20-40% reduced odds of achieving a good treatment response at 1 year. Depressive symptoms at baseline also associated with reduced improvement in disease activity over the course of follow-up. Patients with a history of depression or reporting symptoms of depression according to the EuroQol five-dimension scale showed reduced improvement in tender and swollen joints, patient global assessment and ESR over 1-year follow-up. Patients with depression symptoms according to the 36-item Short Form showed reduced improvement in tender and swollen joints, but not ESR or patient global assessment. Conclusion: Experiencing symptoms of depression at the start of biologics treatment may reduce the odds of achieving a good treatment response, and reduce improvement in disease activity over time. Depression should be managed as part of routine clinical care to optimize treatment outcomes.

Antidepressants for the treatment of depression in people with cancer.

BACKGROUND: Major depression and other depressive conditions are common in people with cancer. These conditions are not easily detectable in clinical practice, due to the overlap between medical and psychiatric symptoms, as described by diagnostic manuals such as the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD). Moreover, it is particularly challenging to distinguish between pathological and normal reactions to such a severe illness. Depressive symptoms, even in subthreshold manifestations, have been shown to have a negative impact in terms of quality of life, compliance with anti-cancer treatment, suicide risk and likely even the mortality rate for the cancer itself. Randomised controlled trials (RCTs) on the efficacy, tolerability and acceptability of antidepressants in this population are few and often report conflicting results. OBJECTIVES: To assess the efficacy, tolerability and acceptability of antidepressants for treating depressive symptoms in adults (aged 18 years or older) with cancer (any site and stage). SEARCH METHODS: We searched the following electronic bibliographic databases: the Cochrane Central Register of Controlled Trials (CENTRAL 2017, Issue 6), MEDLINE Ovid (1946 to June week 4 2017), Embase Ovid (1980 to 2017 week 27) and PsycINFO Ovid (1987 to July week 4 2017). We additionally handsearched the trial databases of the most relevant national, international and pharmaceutical company trial registers and drug-approving agencies for published, unpublished and ongoing controlled trials. SELECTION CRITERIA: We included RCTs comparing antidepressants versus placebo, or antidepressants versus other antidepressants, in adults (aged 18 years or above) with any primary diagnosis of cancer and depression (including major depressive disorder, adjustment disorder, dysthymic disorder or depressive symptoms in the absence of a formal diagnosis). DATA COLLECTION AND ANALYSIS: Two review authors independently checked eligibility and extracted data using a form specifically designed for the aims of this review. The two authors compared the data extracted and then entered data into Review Manager 5 using a double-entry procedure. Information extracted included study and participant characteristics, intervention details, outcome measures for each time point of interest, cost analysis and sponsorship by a drug company. We used the standard methodological procedures expected by Cochrane. MAIN RESULTS: We retrieved a total of 10 studies (885 participants), seven of which contributed to the meta-analysis for the primary outcome. Four of these compared antidepressants and placebo, two compared two antidepressants, and one three-armed study compared two antidepressants and placebo. In this update we included one additional unpublished study. These new data contributed to the secondary analysis, while the results of the primary analysis remained unchanged.For acute-phase treatment response (6 to 12 weeks), we found no difference between antidepressants as a class and placebo on symptoms of depression measured both as a continuous outcome (standardised mean difference (SMD) -0.45, 95% confidence interval (CI) -1.01 to 0.11, five RCTs, 266 participants; very low certainty evidence) and as a proportion of people who had depression at the end of the study (risk ratio (RR) 0.82, 95% CI 0.62 to 1.08, five RCTs, 417 participants; very low certainty evidence). No trials reported data on follow-up response (more than 12 weeks). In head-to-head comparisons we only retrieved data for selective serotonin reuptake inhibitors (SSRIs) versus tricyclic antidepressants, showing no difference between these two classes (SMD -0.08, 95% CI -0.34 to 0.18, three RCTs, 237 participants; very low certainty evidence). No clear evidence of a beneficial effect of antidepressants versus either placebo or other antidepressants emerged from our analyses of the secondary efficacy outcomes (dichotomous outcome, response at 6 to 12 weeks, very low certainty evidence). In terms of dropouts due to any cause, we found no difference between antidepressants as a class compared with placebo (RR 0.85, 95% CI 0.52 to 1.38, seven RCTs, 479 participants; very low certainty evidence), and between SSRIs and tricyclic antidepressants (RR 0.83, 95% CI 0.53 to 1.30, three RCTs, 237 participants). We downgraded the certainty (quality) of the evidence because the included studies were at an unclear or high risk of bias due to poor reporting, imprecision arising from small sample sizes and wide confidence intervals, and inconsistency due to statistical or clinical heterogeneity. AUTHORS' CONCLUSIONS: Despite the impact of depression on people with cancer, the available studies were very few and of low quality. This review found very low certainty evidence for the effects of these drugs compared with placebo. On the basis of these results, clear implications for practice cannot be deduced. The use of antidepressants in people with cancer should be considered on an individual basis and, considering the lack of head-to-head data, the choice of which agent to prescribe may be based on the data on antidepressant efficacy in the general population of individuals with major depression, also taking into account that data on medically ill patients suggest a positive safety profile for the SSRIs. To better inform clinical practice, there is an urgent need for large, simple, randomised, pragmatic trials comparing commonly used antidepressants versus placebo in people with cancer who have depressive symptoms, with or without a formal diagnosis of a depressive disorder.

Barriers to and Facilitators of Engagement With Remote Measurement Technology for Managing Health: Systematic Review and Content Analysis of Findings.

BACKGROUND: Remote measurement technology refers to the use of mobile health technology to track and measure change in health status in real time as part of a person's everyday life. With accurate measurement, remote measurement technology offers the opportunity to augment health care by providing personalized, precise, and preemptive interventions that support insight into patterns of health-related behavior and self-management. However, for successful implementation, users need to be engaged in its use. OBJECTIVE: Our objective was to systematically review the literature to update and extend the understanding of the key barriers to and facilitators of engagement with and use of remote measurement technology, to guide the development of future remote measurement technology resources. METHODS: We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines involving original studies dating back to the last systematic review published in 2014. We included studies if they met the following entry criteria: population (people using remote measurement technology approaches to aid management of health), intervention (remote measurement technology system), comparison group (no comparison group specified), outcomes (qualitative or quantitative evaluation of the barriers to and facilitators of engagement with this system), and study design (randomized controlled trials, feasibility studies, and observational studies). We searched 5 databases (MEDLINE, IEEE Xplore, EMBASE, Web of Science, and the Cochrane Library) for articles published from January 2014 to May 2017. Articles were independently screened by 2 researchers. We extracted study characteristics and conducted a content analysis to define emerging themes to synthesize findings. Formal quality assessments were performed to address risk of bias. RESULTS: A total of 33 studies met inclusion criteria, employing quantitative, qualitative, or mixed-methods designs. Studies were conducted in 10 countries, included male and female participants, with ages ranging from 8 to 95 years, and included both active and passive remote monitoring systems for a diverse range of physical and mental health conditions. However, they were relatively short and had small sample sizes, and reporting of usage statistics was inconsistent. Acceptability of remote measurement technology according to the average percentage of time used (64%-86.5%) and dropout rates (0%-44%) was variable. The barriers and facilitators from the content analysis related to health status, perceived utility and value, motivation, convenience and accessibility, and usability. CONCLUSIONS: The results of this review highlight gaps in the design of studies trialing remote measurement technology, including the use of quantitative assessment of usage and acceptability. Several processes that could facilitate engagement with this technology have been identified and may drive the development of more person-focused remote measurement technology. However, these factors need further testing through carefully designed experimental studies. TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42017060644; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=60644 (Archived by WebCite at http://www.webcitation.org/70K4mThTr).

The Relationship Between Mental Health, Disease Severity, and Genetic Risk for Depression in Early Rheumatoid Arthritis.

OBJECTIVE: Reduced mental health (MH) is prevalent in rheumatoid arthritis (RA). Although longitudinal studies are limited, there is evidence that depression is associated with worse disease outcomes. We evaluated reciprocal relationships between MH, RA severity, and genetic risks for depression for 2 years in a well-characterized cohort of RA patients. METHODS: We evaluated 520 early RA patients previously enrolled to two clinical trials. MH was measured using the short form-36 MH domain and mental component summary scores (MCS). MCS/MH associations over 2 years with disease activity (disease activity score on a 28-joint count), disability (health assessment questionnaire), pain visual analog scale scores, and a weighted genetic risk score for depression were tested using linear mixed-effects and regression models. RESULTS: Poorer MH was associated with worse RA outcomes. Lower MCS scores (indicating worse MH) were seen in patients with a greater genetic risk for depression (weighted genetic risk score: coefficient = -1.21, p = .013). Lower baseline MCS was associated with lower 2-year improvements in disease activity score on a 28-joint count (coefficient = -0.02, p < .001), pain (coefficient = -0.33, p < .001), and health assessment questionnaire (coefficient = -0.01, p = .006). Baseline MCS was associated with changes in the swollen joint count (coefficient = -0.09, p < .001) and patient global assessment (coefficient = -0.28, p < .001) but not the tender joint count (p = .983) and erythrocyte sedimentation rate (p = .973). Only baseline pain visual analog scale (coefficient = -0.07, p = .002) was associated with 2-year changes in MCS. CONCLUSIONS: Reduced baseline MH was associated with lower improvements in disease activity, disability, and pain for 2 years, supporting current national guidelines recommending screening for depression in RA. Pain had a bidirectional relationship with MH. Depression genetic risk had a significant association with MH.

Liver transplantation and adolescence: The role of mental health.

Young people (YP) with chronic illness have higher rates of mental health problems than the general population, with psychosocial complexity associated with nonadherence and poorer health outcomes. This study aimed to describe the prevalence of anxiety and depression in YP after liver transplantation, with autoimmune liver disease and other chronic liver diseases, identify the factors YP attribute their distress to and the relationship between anxiety/depression, and describe YP's beliefs about their illness and treatment. An electronically administered questionnaire battery was given routinely to YP attending an outpatient liver transition clinic; 187 YP participated, of which 17.7% screened positive for anxiety or depression. There were no significant differences between disease groups. This is significantly higher than the prevalence of common mental health problems in the general adolescent population. Patients most frequently attributed their distress to fatigue, sleep difficulties, financial concerns, problems at work/school, worry, and low self-esteem. Higher levels of depression and anxiety were significantly associated with specific illness and treatment beliefs but not with perceived understanding of illness or treatment control. In conclusion, the increased prevalence of mental health problems in YP and the intertwined nature of these with their physical health outcomes provide evidence that holistic care should be delivered as standard for this age group. Liver Transplantation 22 1544-1553 2016 AASLD.

Symptoms of depression and anxiety predict treatment response and long-term physical health outcomes in rheumatoid arthritis: secondary analysis of a randomized controlled trial.

OBJECTIVE: The aim of this analysis is to examine the longitudinal impact of symptoms of depression/anxiety on treatment response, long-term disease activity and physical disability in RA. METHODS: Secondary analysis of clinical trial data was performed. Data were collected at baseline and at 6-monthly intervals for 2 years. The EuroQoL (EQ-5D(TM)) indicated depression/anxiety symptom severity. Our primary outcomes of interest were (i) DAS-28 and (ii) physical disability measured via the HAQ. Secondary outcomes were: tender and swollen joint counts, patient global assessment, ESR and odds of reaching clinical remission. Multilevel models were used to assess the impact of baseline and persistent depression/anxiety on outcomes over 2 years. RESULTS: Data from 379 patients were included. After adjusting for covariates, baseline depression/anxiety symptoms were associated with increased DAS-28 outcomes and increased tender joint counts. Persistent depression/anxiety symptoms were associated with increased DAS-28 scores, HAQ scores, tender joint counts and patient global assessment of disease activity, and reduced odds of reaching clinical remission. Patients with symptoms of depression/anxiety at baseline also showed a 50% reduction in prednisolone treatment effect, in comparison with patients with no symptoms of depression/anxiety at baseline. CONCLUSION: Baseline and persistent symptoms of depression/anxiety are associated with poorer health outcomes over time, as well as reduced treatment response. Mental health should be routinely measured both in clinical practice and in research, and managed alongside rheumatological disease to optimize health outcomes. Further research is required to examine whether treatment of mental disorders can improve rheumatological outcomes.

Are depression and anxiety associated with disease activity in rheumatoid arthritis? A prospective study.

BACKGROUND: This study aimed to investigate the impact of depression and anxiety scores on disease activity at 1-year follow-up in people with Rheumatoid Arthritis (RA). METHODS: The Hospital Anxiety Depression Scale (HADS) was used to measure depression and anxiety in a cross-section of RA patients. The primary outcome of interest was disease activity (DAS28), measured one-year after baseline assessment. Secondary outcomes were: tender joint count, swollen joint count, erythrocyte sedimentation rate and patient global assessment, also measured one-year after baseline assessment. We also examined the impact of baseline depression and anxiety on odds of reaching clinical remission at 1-year follow-up. RESULTS: In total, 56 RA patients were eligible for inclusion in this analysis. Before adjusting for key demographic and disease variables, increased baseline depression and anxiety were associated with increased disease activity at one-year follow-up, although this was not sustained after adjusting for baseline disease activity. There was a strong association between depression and anxiety and the subjective components of the DAS28 at 12-month follow-up: tender joint count and patient global assessment. After adjusting for age, gender, disease duration and baseline tender joint count and patient global assessment respectively, higher levels of depression and anxiety at baseline were associated with increased tender joint count and patient global assessment scores at 1-year follow-up. CONCLUSIONS: Symptoms of depression and anxiety have implications for disease activity, as measured via the DAS28, primarily due to their influence on tender joints and patient global assessment. These findings have implications for treatment decision-making as inflated DAS28 despite well controlled inflammatory disease markers may indicate significant psychological morbidity and related non-inflammatory pain, rather than true disease activity.

Usefulness of the SF-36 Health Survey in screening for depressive and anxiety disorders in rheumatoid arthritis.

BACKGROUND: This study aimed to assess the accuracy of the Short-Form Health Survey (SF-36) mental health subscale (MH) and mental component summary (MCS) scores in identifying the presence of probable major depressive or anxiety disorder in patients with rheumatoid arthritis. METHODS: SF-36 data were collected in 100 hospital outpatients with rheumatoid arthritis. MH and MCS scores were compared against depression and anxiety data collected using validated measures as part of routine clinical practice. Sensitivity and specificity of the SF-36 were established using receiver operating characteristic (ROC) curve analysis, and area under the curve (AUC) compared the performance of the SF-36 components with the 9-item Patient Health Questionnaire (PHQ9) for depression and the 7-item Generalised Anxiety Disorder (GAD7) questionnaire for anxiety. RESULTS: The MH with a threshold of ≤52 had sensitivity and specificity of 81.0 and 71.4 % respectively to detect anxiety, correctly classifying 73.5 % of patients with probable anxiety disorder. A threshold of ≤56 had sensitivity and specificity of 92.6 and 73.2 % respectively to detect depression, correctly classifying 78.6 % of patients, and the same threshold could also be used to detect either depression or anxiety with a sensitivity of 87.9 %, specificity of 76.9 % and accuracy of 80.6 %. The MCS with a threshold of ≤35 had sensitivity and specificity of 85.7 and 81.9 % respectively to detect anxiety, correctly classifying 82.8 % of patients with probable anxiety disorder. A threshold of ≤40 had sensitivity and specificity of 92.3 and 70.2 % respectively to detect depression, correctly classifying 76.3 % of patients. A threshold of ≤38 could be used to detect either depression or anxiety with a sensitivity of 87.5 %, specificity of 80.3 % and accuracy of 82.8 %. CONCLUSION: This analysis may increase the utility of a widely-used questionnaire. Overall, optimal use of the SF-36 for screening for mental disorder may be through using the MCS with a threshold of ≤38 to identify the presence of either depression or anxiety.

Antidepressants for the treatment of depression in people with cancer.

BACKGROUND: Major depression and other depressive conditions are common in people with cancer. These conditions are not easily detectable in clinical practice, due to the overlap between medical and psychiatric symptoms, as described by diagnostic manuals such as the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD). Moreover, it is particularly challenging to distinguish between pathological and normal reactions to such a severe illness. Depressive symptoms, even in subthreshold manifestations, have been shown to have a negative impact in terms of quality of life, compliance with anti-cancer treatment, suicide risk and likely even the mortality rate for the cancer itself. Randomised controlled trials (RCTs) on the efficacy and tolerability of antidepressants in this population group are few and often report conflicting results. OBJECTIVES: To assess the effects and acceptability of antidepressants for treating depressive symptoms in adults (18 years or older) with cancer (any site and stage). SEARCH METHODS: We searched the following electronic bibliographic databases: the Cochrane Central Register of Controlled Trials (CENTRAL 2014, Issue 3), MEDLINE Ovid (1946 to April week 3, 2014), EMBASE Ovid (1980 to 2014 week 17) and PsycINFO Ovid (1987 to April week 4, 2014). We additionally handsearched the trial databases of the most relevant national, international and pharmaceutical company trial registers and drug-approving agencies for published, unpublished and ongoing controlled trials. SELECTION CRITERIA: We included RCTs allocating adults (18 years or above) with any primary diagnosis of cancer and depression (including major depressive disorder, adjustment disorder, dysthymic disorder or depressive symptoms in the absence of a formal diagnosis) comparing antidepressants versus placebo, or antidepressants versus other antidepressants. DATA COLLECTION AND ANALYSIS: Two review authors independently checked eligibility and extracted data using a form specifically designed for the aims of this review. The two authors compared the data extracted and then entered data into RevMan 5 with a double-entry procedure. Information extracted included study and participant characteristics, intervention details, outcome measures for each time point of interest, cost analysis and sponsorship by a drug company. We used the standard methodological procedures expected by The Cochrane Collaboration. MAIN RESULTS: We retrieved a total of nine studies (861 participants), with seven studies contributing to the meta-analysis for the primary outcome. Four of these compared antidepressants and placebo, two compared two antidepressants and one-three armed study compared two antidepressants and a placebo arm. For the acute phase treatment response (6 to 12 weeks), we found very low quality evidence for the effect of antidepressants as a class on symptoms of depression compared with placebo when measured as a continuous outcome (standardised mean difference (SMD) -0.45, 95% confidence interval (CI) -1.01 to 0.11, five RCTs, 266 participants) or as a proportion of people who had depression (risk ratio (RR) 0.82, 95% CI 0.62 to 1.08, five RCTs, 417 participants). No trials reported data on the follow-up response (more than 12 weeks). In head-to-head comparisons we only retrieved data for selective serotonin reuptake inhibitors (SSRIs) versus tricyclic antidepressants, providing very low quality evidence for the difference between these two classes (SMD -0.08, 95% CI -0.34 to 0.18, three RCTs, 237 participants). No clear evidence of an effect of antidepressants versus either placebo or other antidepressants emerged from the analyses of the secondary efficacy outcomes (dichotomous outcome, response at 6 to 12 weeks, very low quality evidence). We found very low quality evidence for the effect of antidepressants as a class in terms of dropouts due to any cause compared with placebo (RR 0.87, 95% CI 0.49 to 1.53, six RCTs, 455 participants), as well as between SSRIs and tricyclic antidepressants (RR 0.83, 95% CI 0.53 to 1.30, three RCTs, 237 participants). We downgraded the quality of the evidence because the included studies were at an unclear or high risk of bias due to poor reporting, imprecision arising from small sample sizes and wide confidence intervals, and inconsistency due to statistical or clinical heterogeneity. AUTHORS' CONCLUSIONS: Despite the impact of depression on people with cancer, available studies were very few and of low quality. This review found very low quality evidence for the effects of these drugs compared with placebo. On the basis of these results clear implications for practice cannot be made. The use of antidepressants in people with cancer should be considered on an individual basis and, considering the lack of head-to-head data, the choice of which agent should be prescribed may be based on the data on antidepressant efficacy in the general population of individuals with major depression, also taking into account that data on medically ill patients suggest a positive safety profile for the SSRIs. Large, simple, randomised, pragmatic trials comparing commonly used antidepressants versus placebo in people with cancer with depressive symptoms, with or without a formal diagnosis of a depressive disorder, are urgently needed to better inform clinical practice.