The effect of depression and anxiety symptom severity on clinical outcomes and app use in digital mental health treatments: Meta-regression of three trials

2021 ◽  
pp. 103972
Author(s):  
David C. Mohr ◽  
Mary J. Kwasny ◽  
Jonah Meyerhoff ◽  
Andrea K. Graham ◽  
Emily G. Lattie
Keyword(s):  
Mental Health ◽  
Clinical Outcomes ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Depression And Anxiety ◽  
Meta Regression ◽  
Mental Health Treatments

The influence of social support, conflict, and stressful life events on PTSD, depression, and anxiety symptom severity in U.S. army female veterans

2011 ◽  
Vol 26 (S2) ◽  
pp. 1678-1678
Author(s):  
A.M. Nayback-Beebe
Keyword(s):  
Mental Health ◽  
Social Support ◽  
Life Events ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Stressful Life Events ◽  
Stressful Life ◽  
Female Veterans ◽  
Depression And Anxiety ◽  
The Social

IntroductionThere have been prevailing gender differences in negative mental health outcomes for female U.S. veterans returning from combat deployments. Research has validated the importance of post-deployment social support in mitigating the effects of these experiences on mental health; however, the influence of conflict within the social network has not been thoroughly explored.Aims(1)Examine the relationships between social support, conflict, and stressful life events to PTSD, depression, and anxiety symptom severity in female veterans 6–12 months after deployment.(2)Determine whether the absence of social support or the presence of social conflict is more influential in the severity of these symptoms.MethodsDescriptive, correlationalResultsThere were significant positive bivariate correlations (p < .01) between conflict and stressful life events and significant negative bivariate correlations (p < .01) between social support and each of the three outcome variables: PTSD, depression, and anxiety symptoms. Hierarchical linear regression showed that co-morbid depression, greater post-deployment stressful life events, and greater conflict within the social network best explained the presence of greater PTSD symptom severity. Stressful life events did not contribute to greater anxiety symptom severity; however, symptom severity was affected by the absence of social support. In contrast, greater depression symptom severity was best explained by the presence of co-morbid PTSD symptoms and the absence of social support.ConclusionsTreatment programs for PTSD and anxiety in female veterans’ post-deployment must assess and address sources of intrapersonal conflict within their social networks. Family therapy may be integral to treatment success.

Randomized controlled trial of digital cognitive behavior therapy for prenatal insomnia symptoms: Effects on postpartum insomnia and mental health

SLEEP ◽  
2021 ◽  
Author(s):  
Jennifer N Felder ◽  
Elissa S Epel ◽  
John Neuhaus ◽  
Andrew D Krystal ◽  
Aric A Prather
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Behavior Therapy ◽  
Cognitive Behavior Therapy ◽  
Symptom Severity ◽  
Standard Care ◽  
Anxiety Symptom ◽  
Controlled Trial ◽  
Cognitive Behavior ◽  
Insomnia Symptom

Abstract Study objectives To evaluate the effects of digital cognitive behavior therapy for insomnia (dCBT-I) delivered during pregnancy on subjective sleep outcomes, depressive symptoms, and anxiety symptoms through six months postpartum. Methods People up to 28 weeks gestation (N=208) with insomnia were randomized to six weekly sessions of dCBT-I or standard care. We report follow-up data at three and six months postpartum. The primary outcome was insomnia symptom severity. Secondary sleep outcomes included global sleep quality and insomnia caseness. Mental health outcomes included depressive and anxiety symptom severity. We evaluated between-condition differences in change from baseline for each postpartum timepoint and categorical outcomes. Results dCBT-I participants did not experience significantly greater improvements in insomnia symptom severity relative to standard care participants, but they did experience higher rates of insomnia remission and lower rates of insomnia caseness at six months postpartum. dCBT-I participants experienced greater improvements in depressive symptom severity from baseline to both postpartum timepoints, and in anxiety symptom severity from baseline to three months postpartum. The proportion of participants with probable major depression at three months postpartum was significantly higher among standard care (18%) than dCBT-I (4%, p=.006) participants; this between-condition difference was pronounced among the subset (n=143) with minimal depressive symptoms at baseline (18% vs 0%). Conclusion dCBT-I use during pregnancy leads to enduring benefits for postpartum insomnia remission. Findings provide strong preliminary evidence that dCBT-I use during pregnancy may prevent postpartum depression and anxiety, which is notable when considering the high frequency and importance of these problems.

Automated facial video-based recognition of depression and anxiety symptom severity: cross-corpus validation

2020 ◽  
Vol 31 (4) ◽  
Author(s):  
A. Pampouchidou ◽  
M. Pediaditis ◽  
E. Kazantzaki ◽  
S. Sfakianakis ◽  
I. A. Apostolaki ◽  
...  
Keyword(s):  
Symptom Severity ◽  
Anxiety Symptom ◽  
Depression And Anxiety

Proneness to Boredom Mediates Relationships Between Problematic Smartphone Use With Depression and Anxiety Severity

2017 ◽  
Vol 36 (6) ◽  
pp. 707-720 ◽  
Author(s):  
Jon D. Elhai ◽  
Juanita K. Vasquez ◽  
Samuel D. Lustgarten ◽  
Jason C. Levine ◽  
Brian J. Hall
Keyword(s):  
College Students ◽  
Symptom Severity ◽  
Structural Equation ◽  
Anxiety Symptom ◽  
Equation Modeling ◽  
Depression And Anxiety ◽  
Cross Sectional ◽  
Problematic Smartphone Use ◽  
Smartphone Use ◽  
Boredom Proneness

Research demonstrates that depression and anxiety symptom severity are related to problematic smartphone use (PSU). However, less is known about variables mediating these relationships. This study aimed to test whether proneness to boredom increased PSU. We also tested whether boredom proneness mediates relations between both depression and anxiety symptom severity with PSU. Using a cross-sectional design, we surveyed 298 American college students about their frequency of smartphone use, levels of PSU, depression, anxiety, and boredom proneness. Using structural equation modeling, we modeled depression and anxiety symptom severity predicting boredom proneness, in turn predicting levels of PSU and smartphone use frequency (SUF). Results demonstrate that boredom proneness predicted PSU, but not SUF. Boredom proneness mediated relations between both depression and anxiety symptom severity with PSU levels (but not usage frequency). We discuss the phenomenon in terms of depressed or anxious college students having difficulty attending to their schoolwork, subsequently experiencing boredom, and engaging in PSU to relieve their boredom.

scholarly journals Temporal relationships between happiness and psychiatric disorders and their symptom severity in a large cohort study: the Netherlands Study of Depression and Anxiety (NESDA)

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Philip Spinhoven ◽  
Bernet M. Elzinga ◽  
Brenda W. J. H. Penninx ◽  
Erik J. Giltay
Keyword(s):  
Anxiety Disorder ◽  
Social Anxiety ◽  
Psychiatric Disorders ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Subjective Happiness ◽  
Depression And Anxiety ◽  
Depression Severity ◽  
Interindividual Differences ◽  
Temporal Relationships

Abstract Background Notwithstanding the firmly established cross-sectional association of happiness with psychiatric disorders and their symptom severity, little is known about their temporal relationships. The goal of the present study was to investigate whether happiness is predictive of subsequent psychiatric disorders and symptom severity (and vice versa). Moreover, it was examined whether changes in happiness co-occur with changes in psychiatric disorder status and symptom severity. Methods In the Netherlands Study of Depression and Anxiety (NESDA), happiness (SRH: Self-Rated Happiness scale), depressive and social anxiety disorder (CIDI: Composite Interview Diagnostic Instrument) and depressive and anxiety symptom severity (IDS: Inventory of Depressive Symptomatology; BAI: Beck Anxiety Inventory; and FQ: Fear Questionnaire) were measured in 1816 adults over a three-year period. Moreover, we focused on occurrence and remittance of 6-month recency Major Depressive Disorder (MDD) and Social Anxiety Disorders (SAD) as the two disorders most intertwined with subjective happiness. Results Interindividual differences in happiness were quite stable (ICC of .64). Higher levels of happiness predicted recovery from depression (OR = 1.41; 95% CI = 1.10–1.80), but not social anxiety disorder (OR = 1.31; 95%CI = .94–1.81), as well as non-occurrence of depression (OR = 2.41; 95%CI = 1.98–2.94) and SAD (OR = 2.93; 95%CI = 2.29–3.77) in participants without MDD, respectively SAD at baseline. Higher levels of happiness also predicted a reduction of IDS depression (sr = − 0.08; 95%CI = -0.10 - -0.04), and BAI (sr = − 0.09; 95%CI = -0.12 - -0.05) and FQ (sr = − 0.06; 95%CI = -0.09 - -0.04) anxiety symptom scores. Conversely, presence of affective disorders, as well as higher depression and anxiety symptom severity at baseline predicted a subsequent reduction of self-reported happiness (with marginal to small sr values varying between −.04 (presence of SAD) to −.17 (depression severity on the IDS)). Moreover, changes in happiness were associated with changes in psychiatric disorders and their symptom severity, in particular with depression severity on the IDS (sr = − 0.46; 95%CI = −.50 - -.42). Conclusions Results support the view of rather stable interindividual differences in subjective happiness, although level of happiness is inversely associated with changes in psychiatric disorders and their symptom severity, in particular depressive disorder and depression severity.

scholarly journals Trends in depression & anxiety symptom severity among mental health service attendees during the COVID-19 pandemic

2021 ◽  
Author(s):  
Rob Saunders ◽  
Joshua Eusty Jonathan Buckman ◽  
Judy Leibowitz ◽  
John Cape ◽  
Stephen Pilling
Keyword(s):  
Mental Health ◽  
Anxiety Symptom ◽  
Psychological Treatment ◽  
Depression And Anxiety ◽  
Treatment Services ◽  
Symptom Scores ◽  
Potential Benefits ◽  
Community Transmission ◽  
The Uk ◽  
Residual Confounding

BackgroundGeneral population surveys have shown that some groups, particularly young women experienced increased distress during nationally mandated restrictions to control the spread of COVID-19. However, there has been limited research on such trends among people with pre-existing mental health conditions, leaving mental health services ill equipped to plan for currents and future lockdowns.MethodsMean weekly scores on the GAD-7 and PHQ-9 between 01/01/2020-22/06/2020 (n=9,538 individuals) for all patients of two psychological treatment services in London, were compared to mean weekly scores from the same time periods in 2017-2019 (n=37,849). The proportion of scores which were above the clinical thresholds for ‘caseness’ each week were compared, and scores between groups based on gender, age group, and ethnicity, were also compared. ResultsConfirmed community transmission in the UK (26/02/2020-03/03/2020) and the announcement of the national ‘lockdown’ (23/03/2020) were associated with significant increases in anxiety symptom scores. ‘Lockdown’ was associated with a decrease in depression scores. These changes were not maintained during lockdown. Significant increases in depression and anxiety were observed at week 23, as restrictions were eased.LimitationsThis was an exploratory analysis in two services only. Residual confounding and selection biases cannot be ruled out.ConclusionsDifferences in the weekly average symptom scores were short-term; they did not continue throughout ‘lockdown’ as might have been expected, except among older people. Replication of this study in other settings and investigating the potential benefits of more regular reviews or more intensive treatments for older adults seeking support, are warranted.

scholarly journals Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study

10.2196/15644 ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. e15644 ◽  
Author(s):  
Renwen Zhang ◽  
Jennifer Nicholas ◽  
Ashley A Knapp ◽  
Andrea K Graham ◽  
Elizabeth Gray ◽  
...  
Keyword(s):  
Mental Health ◽  
Mixed Methods ◽  
Clinical Outcomes ◽  
Goal Setting ◽  
Meaningful Use ◽  
Health Interventions ◽  
Depression Symptoms ◽  
User Engagement ◽  
Depression And Anxiety ◽  
Health Apps

Background User engagement is key to the effectiveness of digital mental health interventions. Considerable research has examined the clinical outcomes of overall engagement with mental health apps (eg, frequency and duration of app use). However, few studies have examined how specific app use behaviors can drive change in outcomes. Understanding the clinical outcomes of more nuanced app use could inform the design of mental health apps that are more clinically effective to users. Objective This study aimed to classify user behaviors in a suite of mental health apps and examine how different types of app use are related to depression and anxiety outcomes. We also compare the clinical outcomes of specific types of app use with those of generic app use (ie, intensity and duration of app use) to understand what aspects of app use may drive symptom improvement. Methods We conducted a secondary analysis of system use data from an 8-week randomized trial of a suite of 13 mental health apps. We categorized app use behaviors through a mixed methods analysis combining qualitative content analysis and principal component analysis. Regression analyses were used to assess the association between app use and levels of depression and anxiety at the end of treatment. Results A total of 3 distinct clusters of app use behaviors were identified: learning, goal setting, and self-tracking. Each specific behavior had varied effects on outcomes. Participants who engaged in self-tracking experienced reduced depression symptoms, and those who engaged with learning and goal setting at a moderate level (ie, not too much or not too little) also had an improvement in depression. Notably, the combination of these 3 types of behaviors, what we termed “clinically meaningful use,” accounted for roughly the same amount of variance as explained by the overall intensity of app use (ie, total number of app use sessions). This suggests that our categorization of app use behaviors succeeded in capturing app use associated with better outcomes. However, anxiety outcomes were neither associated with specific behaviors nor generic app use. Conclusions This study presents the first granular examination of user interactions with mental health apps and their effects on mental health outcomes. It has important implications for the design of mobile health interventions that aim to achieve greater user engagement and improved clinical efficacy.

scholarly journals Variation in common preschool sleep problems as an early predictor for depression and anxiety symptom severity across time

2016 ◽  
Vol 58 (2) ◽  
pp. 151-159 ◽  
Author(s):  
Diana J. Whalen ◽  
Kirsten E. Gilbert ◽  
Deanna M. Barch ◽  
Joan L. Luby ◽  
Andy C. Belden
Keyword(s):  
Symptom Severity ◽  
Anxiety Symptom ◽  
Sleep Problems ◽  
Depression And Anxiety ◽  
Early Predictor

scholarly journals Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study (Preprint)

2019 ◽  
Author(s):  
Renwen Zhang ◽  
Jennifer Nicholas ◽  
Ashley A Knapp ◽  
Andrea K Graham ◽  
Elizabeth Gray ◽  
...  
Keyword(s):  
Mental Health ◽  
Mixed Methods ◽  
Clinical Outcomes ◽  
Goal Setting ◽  
Meaningful Use ◽  
Health Interventions ◽  
Depression Symptoms ◽  
User Engagement ◽  
Depression And Anxiety ◽  
Health Apps

BACKGROUND User engagement is key to the effectiveness of digital mental health interventions. Considerable research has examined the clinical outcomes of overall engagement with mental health apps (eg, frequency and duration of app use). However, few studies have examined how specific app use behaviors can drive change in outcomes. Understanding the clinical outcomes of more nuanced app use could inform the design of mental health apps that are more clinically effective to users. OBJECTIVE This study aimed to classify user behaviors in a suite of mental health apps and examine how different types of app use are related to depression and anxiety outcomes. We also compare the clinical outcomes of specific types of app use with those of generic app use (ie, intensity and duration of app use) to understand what aspects of app use may drive symptom improvement. METHODS We conducted a secondary analysis of system use data from an 8-week randomized trial of a suite of 13 mental health apps. We categorized app use behaviors through a mixed methods analysis combining qualitative content analysis and principal component analysis. Regression analyses were used to assess the association between app use and levels of depression and anxiety at the end of treatment. RESULTS A total of 3 distinct clusters of app use behaviors were identified: learning, goal setting, and self-tracking. Each specific behavior had varied effects on outcomes. Participants who engaged in self-tracking experienced reduced depression symptoms, and those who engaged with learning and goal setting at a moderate level (ie, not too much or not too little) also had an improvement in depression. Notably, the combination of these 3 types of behaviors, what we termed “clinically meaningful use,” accounted for roughly the same amount of variance as explained by the overall intensity of app use (ie, total number of app use sessions). This suggests that our categorization of app use behaviors succeeded in capturing app use associated with better outcomes. However, anxiety outcomes were neither associated with specific behaviors nor generic app use. CONCLUSIONS This study presents the first granular examination of user interactions with mental health apps and their effects on mental health outcomes. It has important implications for the design of mobile health interventions that aim to achieve greater user engagement and improved clinical efficacy.

Sign in / Sign up

Export Citation Format

Share Document