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Background: There is a strong link between sleep and major depression. However, so far it has remained unclear whether changes in depression severity are preceding or following changes in sleep and whether shorter or rather longer sleep durations are related to improvements of depression severity. Objective: The aim of this study was to investigate temporal associations between sleep and depression in patients suffering from Major Depression using an idiographic research approach. Methods: In 22 patients diagnosed with recurrent Major Depression Disorder time series data of daily sleep assessments (time in bed and total sleep time) and self-rated depression severity of on average 173 days per patient were analysed using a technique called vector autoregression. Granger causality tests were conducted to test for possible causality. Impulse response analysis and forecast error variance decomposition were calculated to quantify the temporal impact of sleep and depression on each other. Results: 11 positive compared to 5 negative associations between time in bed / total sleep time and depression severity were found. In 9 associations time in bed / total sleep time granger caused depression severity whereas in 7 associations the temporal order was reversed. Most of the variance concerning depression severity could be explained by time in bed (10%). Changes of sleep or depressive symptoms of 1 SD had most of its impact on the other variable in the following 2 to 4 days. Conclusions: Rather longer than shorter bedtimes were associated to more depression severity. The temporal orders of the associations were heterogeneous.
(Toronto, Aug 29, 2019) Clarivate Analytics has now confirmed that JMIR Mental Health has (finally) been admitted to SCIE/JCR, meaning that it will receive its first official 2019 Impact Factor, to be released by Clarivate in June 2020, reflecting the number of citations in 2019 to articles published in 2018 or 2017. We expect the IF to place the journal firmly in the Q1 (top 25% of journals).
JMIR Mental Health (JMH, ISSN 2368-7959, Editor-in-Chief: John Torous MD MBI) is a PubMed-indexed, peer-reviewed journal which has a unique focus on digital health and Internet/mobile interventions, technologies and electronic innovations (software and hardware) for mental health, addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations related to digital psychiatry, e-mental health, and clinical informatics in psychiatry/psychology. The main themes/topics covered by this journal can be found here.
JMIR Mental Health has an international author- and readership and welcomes submissions from around the world.
JMIR Mental Health features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs.
The journal is indexed in PubMed, PubMed Central, and SCIE (Science Citation Index Expanded)/WoS/JCR (Journal Citation Reports).
Background: Mental health is integral to our salubrity, but mental disorders are very debilitating and common. Therefore, it is critical to provide accessible, timely, and inexpensive mental care. This can be done through mobile health (mHealth), namely, mobile medical apps, which are gaining popularity among clinicians and patients. mHealth is a fast-paced field, and there is significant variation in the number of installs among psychiatry apps. However, the factors that influence psychiatry app installs have yet to be studied.
Objective: This study aimed to identify predictors of the number of app installs in psychiatry.
Methods: A literature review identified which factors influence app installs. Psychiatry apps available in the Google Play Store were reviewed, and publicly available data were collected. A multivariate ordinal logistic regression analysis was performed to evaluate the effect of said factors on the number of installs.
Results: Our search identified 128 psychiatry apps: 2.3% (3/128) had never been installed, approximately half (53.1%, 68/128) had less than 500 installs, and only 0.8% (1/128) had over 10,000,000 installs. A multivariate logistic regression analysis identified that apps with a lower price (P<.001), a higher rating (P<.001), optional in-app purchases (P<.001), and age restriction (P=.04) had a higher number of installs. The involvement of a psychiatrist or other health care professional (HCP) had no statistically significant influence on the number of installs. Only data from the Google Play Store and the developers’ websites were available for analysis, and the depth of involvement of HCPs was impossible to document.
Conclusions: Psychiatry apps with a lower price, optional in-app purchases, age restriction, and a higher rating are expected to have a higher number of installs. Unlike other medical fields, in this study, the explicit participation of psychiatrists in app development was not a significant predictor of the number of installs. Research is needed to identify other factors that may influence the number of installs, as that can help mHealth app development.
Background: Cognitive symptoms are common in major depressive disorder and may help to identify patients who need treatment or who are not experiencing adequate treatment response. Digital tools providing real-time data assessing cognitive function could help support patient treatment and remediation of cognitive and mood symptoms.
Objective: The aim of this study was to examine feasibility and validity of a wearable high-frequency cognitive and mood assessment app over 6 weeks, corresponding to when antidepressant pharmacotherapy begins to show efficacy.
Methods: A total of 30 patients (aged 19-63 years; 19 women) with mild-to-moderate depression participated in the study. The new Cognition Kit app was delivered via the Apple Watch, providing a high-resolution touch screen display for task presentation and logging responses. Cognition was assessed by the n-back task up to 3 times daily and depressed mood by 3 short questions once daily. Adherence was defined as participants completing at least 1 assessment daily. Selected tests sensitive to depression from the Cambridge Neuropsychological Test Automated Battery and validated questionnaires of depression symptom severity were administered on 3 occasions (weeks 1, 3, and 6). Exploratory analyses examined the relationship between mood and cognitive measures acquired in low- and high-frequency assessment.
Results: Adherence was excellent for mood and cognitive assessments (95% and 96%, respectively), did not deteriorate over time, and was not influenced by depression symptom severity or cognitive function at study onset. Analyses examining the relationship between high-frequency cognitive and mood assessment and validated measures showed good correspondence. Daily mood assessments correlated moderately with validated depression questionnaires (r=0.45-0.69 for total daily mood score), and daily cognitive assessments correlated moderately with validated cognitive tests sensitive to depression (r=0.37-0.50 for mean n-back).
Conclusions: This study supports the feasibility and validity of high-frequency assessment of cognition and mood using wearable devices over an extended period in patients with major depressive disorder.
Background: The therapist-patient therapeutic alliance is known to be an important factor in cognitive behavioral therapy (CBT). However, findings by previous studies for obsessive-compulsive disorder (OCD), panic disorder (PD), and social anxiety disorder (SAD) have not been consistent regarding whether this alliance provides symptomatic improvements.
Objective: This study investigated predictors of symptom improvement in patients receiving CBT via video conferencing.
Methods: A total of 29 patients who participated in a previous clinical trial were recruited for the current study. Therapeutic alliance and clinical background in patients with OCD, PD, and SAD were measured at first session or the eighth session, which were calculated by multiple regression analyses to estimate the impact on therapeutic response percentage change.
Results: The multiple regression analyses showed that, among the independent variables, only patients’ agreement in the therapeutic alliance remained viable, as other variables were a best fit for the excluded model (P=.002). The results show that patients’ agreement on therapeutic goals and tasks explains the prognosis, as the normalization factor beta was 0.54 (SE 32.73; 95% CI 1.23-5.17; P=.002) and the adjusted R2 was .266.
Conclusions: Patients' agreement on therapeutic goals and tasks predicts improvement after CBT via video conferencing.
Background: The privacy of patients with mental health conditions is prominent in health information exchange (HIE) discussions, given that their potentially sensitive personal health information (PHI) may be electronically shared for various health care purposes. Currently, the patient privacy perspective in the mental health context is not well understood because of the paucity of in-depth patient privacy research; however, the evidence suggests that patient privacy perspectives are more nuanced than what has been assumed in the academic and health care community.
Objective: This study aimed to generate an understanding on how patients with mental health conditions feel about privacy in the context of HIE in Canada. This study also sought to identify the factors underpinning their privacy perspectives and explored how their perspectives influenced their attitudes toward HIE.
Methods: Semistructured interviews were conducted with patients at a Canadian academic hospital for addictions and mental health. Guided by the Antecedent-Privacy Concern-Outcome macro-model, interview transcripts underwent deductive and inductive thematic analyses.
Results: We interviewed 14 participants. Their privacy concerns varied, depending on the participant’s privacy experiences and health care perceptions. Media reports of privacy breaches and hackers had little impact on participants’ privacy concerns because of a fatalistic belief that privacy breaches are a reality in the digital age. Rather, direct observations and experiences with the mistreatment of PHI in health care settings caused concern. Decisions to trust others with PHI depended on past experiences with the individual (or institution) and health care needs. Participants had little knowledge of patient privacy rights and legislation but were willing to participate in HIE because of perceived individual and societal benefits.
Conclusions: This study introduces evidence that patients with mental health conditions would support HIE. Participants were pragmatic, supporting HIE because they wanted the best care possible. They also understood that their PHI was critical in supporting the single-payer Canadian health care system. Participant health care experiences informed their privacy perspectives, trust, and PHI sharing attitudes—all accentuating the importance of the patient experience in building trust in HIE. Their lack of knowledge about patient rights and PHI uses highlights the degree of trust they have in the health care system to protect their privacy. These findings suggest that the patient privacy discourse should extend beyond the oft-cited barrier of patient privacy concerns to include discussions about building trust, communicating the benefits of HIE, and improving patient experiences. Although our findings are in the Canadian context, this study highlights the importance of engaging patients in privacy policy discussions, regardless of jurisdiction, to ensure their nuanced perspectives are reflected in policy decisions on their PHI.
Background: Depression is a common disorder that still remains underdiagnosed and undertreated in the UK National Health Service. Charities and voluntary organizations offer mental health services, but they are still struggling to promote these services to the individuals who need them. By analyzing social media (SM) content using machine learning techniques, it may be possible to identify which SM users are currently experiencing low mood, thus enabling the targeted advertising of mental health services to the individuals who would benefit from them.
Objective: This study aimed to understand SM users’ opinions of analysis of SM content for depression and targeted advertising on SM for mental health services.
Methods: A Web-based, mixed methods, cross-sectional survey was administered to SM users aged 16 years or older within the United Kingdom. It asked participants about their demographics, their usage of SM, and their history of depression and presented structured and open-ended questions on views of SM content being analyzed for depression and views on receiving targeted advertising for mental health services.
Results: A total of 183 participants completed the survey, and 114 (62.3%) of them had previously experienced depression. Participants indicated that they posted less during low moods, and they believed that their SM content would not reflect their depression. They could see the possible benefits of identifying depression from SM content but did not believe that the risks to privacy outweighed these benefits. A majority of the participants would not provide consent for such analysis to be conducted on their data and considered it to be intrusive and exposing.
Conclusions: In a climate of distrust of SM platforms’ usage of personal data, participants in this survey did not perceive that the benefits of targeting advertisements for mental health services to individuals analyzed as having depression would outweigh the risks to privacy. Future work in this area should proceed with caution and should engage stakeholders at all stages to maximize the transparency and trustworthiness of such research endeavors.
Background: Chronic stress is a major public health concern. Mobile health (mHealth) apps can help promote coping skills in daily life and prevent stress-related issues. However, little is known about the determinant factors of public acceptance of stress management in relation to preferences for psychological services.
Objective: The aim of this survey study was to (1) assess determinant factors of public acceptance (behavioral use intention) of stress management apps based on an adapted and extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and (2) explore preferences for mHealth apps compared with other mental health services.
Methods: Using convenience sampling, participants completed a multiscale 54-item Web-based survey. Based on significant correlations with acceptance, hierarchical stepwise regression analysis was performed within three blocks: (1) background and stress-related control variables, (2) beliefs and attitudes toward using mHealth, and (3) the core UTAUT determinants. The preference for mHealth apps in comparison with nine other mental health services (operationalized as readiness to use) was analyzed using paired t tests.
Results: Of 141 participants, nearly half (69/141, 48.9%) indicated prior mHealth use. Acceptance of stress coping apps was moderate (mean 3.10, SD 1.03, range 1-5). Hierarchical stepwise regression including four of 11 variables (R2=.62; P=.01, f2=1.63) identified positive attitudes toward using mHealth for stress coping (beta=0.69, P<.001, 46% R2 increase above block 1, f2=0.85), skepticism/perceived risks (beta=−0.14, P=.01, f2=0.16), and stress symptoms (beta=0.12, P=.03, f2=0.14) as significant predictors of acceptance. UTAUT determinants added no predictive contribution beyond attitudes (all P>.05, R2 increase of 1%), whereas post hoc analysis showed significant R2 increases of attitudes and skepticism/perceived risks beyond UTAUT determinants (all P<.001, R2 increase of 13%). The readiness to use apps was equivalent to or significantly higher than most service types, but lower than information websites.
Conclusions: Attitudes may be at least as predictive for the acceptance of stress management apps as for more elaborated outcome beliefs. Efforts aimed at improving the public adoption of mHealth could put more emphasis on the pleasant aspects of app use, address misconceptions, offer stress screening tools on health websites, and increase options to try high-quality apps.
Background: Distorted perception of one’s body and appearance, in general, is a core feature of several psychiatric disorders including anorexia nervosa and body dysmorphic disorder and is operative to varying degrees in nonclinical populations. Yet, body image perception is challenging to assess, given its subjective nature and variety of manifestations. The currently available methods have several limitations including restricted ability to assess perceptions of specific body areas. To address these limitations, we created Somatomap, a mobile tool that enables individuals to visually represent their perception of body-part sizes and shapes as well as areas of body concerns and record the emotional valence of concerns. Objective: This study aimed to develop and pilot test the feasibility of a novel mobile tool for assessing 2D and 3D body image perception. Methods: We developed a mobile 2D tool consisting of a manikin figure on which participants outline areas of body concern and indicate the nature, intensity, and emotional valence of the concern. We also developed a mobile 3D tool consisting of an avatar on which participants select individual body parts and use sliders to manipulate their size and shape. The tool was pilot tested on 103 women: 65 professional fashion models, a group disproportionately exposed to their own visual appearance, and 38 nonmodels from the general population. Acceptability was assessed via a usability rating scale. To identify areas of body concern in 2D, topographical body maps were created by combining assessments across individuals. Statistical body maps of group differences in body concern were subsequently calculated using the formula for proportional z-score. To identify areas of body concern in 3D, participants’ subjective estimates from the 3D avatar were compared to corresponding measurements of their actual body parts. Discrepancy scores were calculated based on the difference between the perceived and actual body parts and evaluated using multivariate analysis of covariance. Results: Statistical body maps revealed different areas of body concern between models (more frequently about thighs and buttocks) and nonmodels (more frequently about abdomen/waist). Models were more accurate at estimating their overall body size, whereas nonmodels tended to underestimate the size of individual body parts, showing greater discrepancy scores for bust, biceps, waist, hips, and calves but not shoulders and thighs. Models and nonmodels reported high ease-of-use scores (8.4/10 and 8.5/10, respectively), and the resulting 3D avatar closely resembled their actual body (72.7% and 75.2%, respectively). Conclusions: These pilot results suggest that Somatomap is feasible to use and offers new opportunities for assessment of body image perception in mobile settings. Although further testing is needed to determine the applicability of this approach to other populations, Somatomap provides unique insight into how humans perceive and represent the visual characteristics of their body.
Background:
Cognitive biases refer to automatic attentional or interpretational tendencies, which result in individuals with addictive disorders to automatically attend to substance-related stimuli and those with anxiety disorders to attend to threatening stimuli. To date, several studies have examined the efficacy of cognitive bias modification, and meta-analytical studies have synthesized the evidence for overall efficacy. The clinical utility of cognitive bias modification interventions has previously been limited to the confines of a laboratory, but recent advances in Web technologies can change this.
Methods:
Databases (PubMed and MEDLINE, EMBASE, PsycINFO, ScienceDirect, and Cochrane Central) were searched from inception to December 5, 2017. The following search terminologies were used: (“attention bias” OR “cognitive bias” OR “approach bias” OR “avoidance bias” OR “interpretative bias”) AND (“Internet” OR “Web” OR “Online”). The methods for this scoping review are based on the previously published protocol. For the synthesis of the evidence, a narrative synthesis was undertaken, as a meta-analysis was not appropriate, given the lack of reported effect sizes and the heterogeneity in the outcomes reported.
Results:
Of the 2674 unique articles identified, we identified 22 randomized controlled studies that met our inclusion criteria: alcohol use disorder (n=2), tobacco use disorder (n=2), depressive disorder (n=3), anxiety and depressive symptoms in adolescents (n=3), obsessive-compulsive disorder (OCD; n=2), social anxiety disorder (n=9), and anxiety disorder (n=1). The sample sizes of these studies ranged from 16 to 434 participants. There is preliminary evidence to suggest that Web-based interventions could reduce biases among adolescents with heightened symptoms of anxiety and depression and among individuals with OCD.
Conclusions:
This is the first scoping review that mapped out the scope of cognitive bias modification interventions for psychiatric disorders. Web-based interventions have been applied predominantly for social anxiety and addictive disorders. Larger cohorts must be used in future studies to better determine the effectiveness of Web-based cognitive bias interventions.
Background: Internet-based cognitive behavioral therapy (iCBT) for children and adolescents is a persuasive system that combines 3 major components to therapy—therapeutic content, technological features, and interactions between the user and program—intended to reduce users’ anxiety symptoms. Several reviews report the effectiveness of iCBT; however, iCBT design and delivery components differ widely across programs, which raise important questions about how iCBT effects are produced and can be optimized. Objective: The objective of this study was to review and synthesize the iCBT literature using a realist approach with a persuasive systems perspective to (1) document the design and delivery components of iCBT and (2) generate hypotheses as to how these components may explain changes in anxiety symptoms after completing iCBT. Methods: A multi-strategy search identified published and gray literature on iCBT for child and adolescent anxiety up until June 2019. Documents that met our prespecified inclusion criteria were appraised for relevance and methodological rigor. Data extraction was guided by the persuasive systems design (PSD) model. The model describes 28 technological design features, organized into 4 categories that help users meet their health goals: primary task support, dialogue support, system credibility support, and social support. We generated initial hypotheses for how PSD (mechanisms) and program delivery (context of use) features were linked to symptom changes (outcomes) across iCBT programs using realist and meta-ethnographic techniques. These hypothesized context-mechanism-outcome configurations were refined during analysis using evidence from the literature to improve their explanatory value. Results: A total of 63 documents detailing 15 iCBT programs were included. A total of 6 iCBT programs were rated high for relevance, and most studies were of moderate-to-high methodological rigor. A total of 11 context-mechanism-outcome configurations (final hypotheses) were generated. Configurations primarily comprised PSD features from the primary task and dialogue support categories. Several key PSD features (eg, self-monitoring, simulation, social role, similarity, social learning, and rehearsal) were consistently reported in programs shown to reduce anxiety; many features were employed simultaneously, suggesting synergy when grouped. We also hypothesized the function of PSD features in generating iCBT impacts. Adjunct support was identified as an important aspect of context that may have complemented certain PSD features in reducing users’ anxiety. Conclusions: This synthesis generated context-mechanism-outcome configurations (hypotheses) about the potential function, combination, and impact of iCBT program components thought to support desired program effects. We suggest that, when delivered with adjunct support, PSD features may contribute to reduced anxiety for child and adolescent users. Formal testing of the 11 configurations is required to confirm their impact on anxiety-based outcomes. From this we encourage a systematic and deliberate approach to iCBT design and evaluation to increase the pool of evidence-based interventions available to prevent and treat children and adolescents with anxiety.
Background: Preventing and reducing risky alcohol use and its side effects remains a public health priority. Discussing alcohol use with patients can be difficult; dedicated training for health care providers is needed to facilitate these conversations. A Web-based alcohol screening and brief intervention (alcohol SBI), comprising didactic and skills application training, was designed for physician assistant (PA) students. Objective: This paper details experiences and outcomes in developing an alcohol SBI training curriculum and coordinating virtual encounters with standardized patients (SPs). We also explain challenges faced with developing an alcohol SBI training and a Web-based learning management site to fit the needs of 5 different PA programs. Methods: Training development comprised 3 phases—precourse, development, and implementation. The precourse phase included developing the initial training curriculum, building a website, and testing with a pilot group. The development phase refined the training curriculum based on user feedback and moved into a three-component module: didactic training module, guided interactive encounter with a simulated patient, and live encounter with an SP. A learning management system website was also created. In the implementation phase, 5 PA schools incorporated the Web-based training into curricula. Each school modified the implementation method to suit their organizational environment. Evaluation methods included pre- and postchange over time on trainee attitudes, knowledge, and skills (confidence) on talking to patients about alcohol use, trainee self-reported proficiency on the SP encounter, SP evaluation of the trainee proficiency during the alcohol use conversation, user evaluation of the type of technology mode for the SP conversation, and overall trainee satisfaction with the Web-based training on alcohol SBI. Results: Final evaluation outcomes indicated a significant (P<.01) change over time in trainee knowledge and skills (confidence) in the conduct of the alcohol SBI with an SP, regardless of the program implementation method. Trainees were generally satisfied with the Web-based training experience and rated the use of the videoconference medium as most useful when conducting the alcohol SBI conversation with the SP. Training that included a primer on the importance of screening, individual participation in the Web-based didactic alcohol SBI modules, and virtual encounters with SPs through a university-based simulation center was the most widely accepted. Successful implementation included program investment and curriculum planning. Implementation barriers involved technical challenges with SP encounters and simulation center logistics, and varying PA school characteristics. Conclusions: Development and implementation of Web-based educational modules to educate health care professionals on alcohol SBI is effective, easy to reproduce, and readily accessible. Identifying challenges affecting development, implementation, and utilization of learned techniques in practice, enhances facilitation of learning and training efficacy. As the value of technology-based learning becomes more apparent, reports detailing what has worked versus what has not may help guide the process.
Background: The use of conversational agent interventions in mental health is growing at a fast pace. Recent existing reviews have focused exclusively on a subset of embodied conversational agent interventions despite other modalities aiming to achieve the common goal of improved mental health. Objective: This study aimed to review the use of conversational agent interventions in the treatment of mental health problems. Methods: We performed a systemic search using relevant databases (MEDLINE, EMBASE, PsycINFO, Web of Science, and Cochrane library). We included studies if they reported on an autonomous conversational agent that simulated conversation and reported on a mental health outcome. Results: A total of 13 studies were included in the review. Among them, 4 full-scale randomized controlled trials (RCTs) were included. The rest were feasibility, pilot RCTs and quasi-experimental studies. Interventions were diverse in design and targeted a range of mental health problems using a wide variety of therapeutic orientations. All included studies reported reductions in psychological distress postintervention. Furthermore, 5 controlled studies demonstrated significant reductions in psychological distress compared with inactive control groups. In addition, 3 controlled studies comparing interventions with active control groups failed to demonstrate superior effects. Broader utility in promoting well-being in nonclinical populations was unclear. Conclusions: The efficacy and acceptability of conversational agent interventions for mental health problems are promising. However, a more robust experimental design is required to demonstrate efficacy and efficiency. A focus on streamlining interventions, demonstrating equivalence to other treatment modalities, and elucidating mechanisms of action has the potential to increase acceptance by users and clinicians and maximize reach.
Background:
Mental health and substance use disorders are the main causes of disability among adolescents and young adults yet fewer than half experiencing these problems seek professional help. Young people frequently search the Web for health information and services, suggesting that Web-based modalities might promote help-seeking among young people who need it. To support young people in their help-seeking, we developed a Web-based mental health service navigation website called Link. Link is based on the Theory of Planned Behavior and connects young people with treatment based on the type and severity of mental health symptoms that they report.
Methods:
Young people, aged between 18 and 25 years, were recruited on the Web from an open access website to participate in a randomized controlled trial. Participants were stratified by gender and psychological distress into either the intervention arm (Link) or the control arm (usual help-seeking strategies). Baseline, immediate postintervention, 1-month, and 3-month surveys were self-reported and administered on the Web. Measures included the PA and NA scales, Kessler psychological distress scale (K10), barriers to adolescent help-seeking scale (BASH), and the general help-seeking questionnaire (GHSQ).
Results:
In total 413 young people were recruited to the trial (intervention, n=205; control, n=208) and 78% (160/205) of those randomized to the intervention arm visited the Link website. There was no evidence to support a difference between the intervention and control arms on the primary outcome, with PA increasing equally by approximately 30% between baseline and 3 months in both arms. NA decreased for the intervention arm compared with the control arm with a difference of 1.4 (95% CI 0.2-2.5) points immediately after the intervention and 2.6 (95% CI 1.1-4.1) at 1 month. K10 scores were unchanged and remained high in both arms. No changes were found on the BASH or GHSQ; however, participants in the intervention arm appeared more satisfied with their help-seeking process and outcomes at 1 and 3 months postintervention.
Conclusions:
The process of prompting young people to seek mental health information and services appears to improve their affective state and increase help-seeking intentions, regardless of whether they use a Web-based dedicated youth-focused tool, such as Link, or their usual search strategies. However, young people report greater satisfaction using tools designed specifically for them, which may encourage future help-seeking. The ability of Web-based tools to match mental health needs with appropriate care should be explored further.
Background: There is a strong link between sleep and major depression. However, so far it has remained unclear whether changes in depression severity are preceding or following changes in sleep and wh...
Background: There is a strong link between sleep and major depression. However, so far it has remained unclear whether changes in depression severity are preceding or following changes in sleep and whether shorter or rather longer sleep durations are related to improvements of depression severity. Objective: The aim of this study was to investigate temporal associations between sleep and depression in patients suffering from Major Depression using an idiographic research approach. Methods: In 22 patients diagnosed with recurrent Major Depression Disorder time series data of daily sleep assessments (time in bed and total sleep time) and self-rated depression severity of on average 173 days per patient were analysed using a technique called vector autoregression. Granger causality tests were conducted to test for possible causality. Impulse response analysis and forecast error variance decomposition were calculated to quantify the temporal impact of sleep and depression on each other. Results: 11 positive compared to 5 negative associations between time in bed / total sleep time and depression severity were found. In 9 associations time in bed / total sleep time granger caused depression severity whereas in 7 associations the temporal order was reversed. Most of the variance concerning depression severity could be explained by time in bed (10%). Changes of sleep or depressive symptoms of 1 SD had most of its impact on the other variable in the following 2 to 4 days. Conclusions: Rather longer than shorter bedtimes were associated to more depression severity. The temporal orders of the associations were heterogeneous.
Background:
In-person motivational interventions increase engagement with evidence-based cessation treatments among smokers with schizophrenia, but access to such interventions can be limited due...
Background:
In-person motivational interventions increase engagement with evidence-based cessation treatments among smokers with schizophrenia, but access to such interventions can be limited due to workforce shortages and competing demands in mental health clinics. Use of digital technology to deliver interventions can increase access, but cognitive impairments in schizophrenia may impede use of standard digital interventions. We developed an interactive, multimedia, digital motivational decision support system for smokers with schizophrenia (Let’s Talk About Smoking). We also digitalized a standard educational pamphlet from the National Cancer Institute (NCI Education). Both were tailored to reduce cognitive load during use. Objective: We conducted a randomized trial of Let's Talk About Smoking vs. NCI Education to test whether the interactive motivational intervention was more effective and more appealing than the static educational intervention for increasing use of smoking cessation treatment, quit attempts and abstinence among smokers with schizophrenia, accounting for level of cognitive functioning. Methods: Adult smokers with schizophrenia (n=162) were enrolled in 2014-2015, randomly assigned to intervention condition, and assessed in person at 3- and 6-month follow-ups. Interventions were delivered on a laptop computer in a single session. All participants had access to standard, community-delivered cessation treatments during follow-up. Multivariate models were used to evaluate outcomes. Results: All participants completed their assigned intervention. Treatment initiation outcomes were not different between intervention conditions (32.1% Let’s Talk About Smoking vs. 46.2% NCI Education; OR = 0.71 [0.37-1.33]); 38.9% of all participants initiated treatment. Older age (OR=1.03 [1.00-1.07], P=.05), higher education (OR=1.21 [1.04-1.41], P=.03), and fewer positive symptoms (OR=.87 [0.80-0.96], P=.01) predicted cessation treatment initiation, whereas level of cognition did not, suggesting that tailoring the digital interventions to reduce cognitive load was effective. The mean satisfaction/usability index score was higher for Let’s Talk About Smoking vs. NCI Education (8.9±1.3 vs. 8.3±2.1, df= 120.7, t= 2.0, P=.045).
Quit attempts and abstinence were not different between intervention conditions Cognitive functioning at baseline (Est=1.47, SE=0.47, P=.002) and use of any behavioral or medication cessation treatment (Est=1.43, SE=.47, P=.003) predicted quit attempts with self-reported abstinence over the 6-months follow-up, indicating that smokers with schizophrenia required additional treatment after brief education or motivational interventions, and that treatment should be adjusted for people with cognitive impairment. Conclusions: The interactive, multimedia intervention was not more effective than the static, text-based intervention among smokers with schizophrenia. Both tailored digital interventions resulted in levels of treatment engagement and quit attempts that were similar to findings from previous studies of in-person interventions, confirming the potential role of digital interventions to educate and motivate smokers with schizophrenia to use cessation treatment and to quit smoking. The interactive, multimedia intervention was rated as more appealing, suggesting the potential for better uptake of interactive, multi-media interventions in non-research environments. Clinical Trial: ClinicalTrials.gov NCT02086162
