scholarly journals Addictive Smartphone Behavior, Anxiety Symptom Severity, and Depressive Stress

2020 ◽  
Vol 19 (0) ◽  
pp. 45
Keyword(s):  
Symptom Severity ◽  
Anxiety Symptom

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.

Generalized Anxiety Symptom Severity Inventory

2021 ◽  
Author(s):  
Imelu G. Mordeno ◽  
Ma. Jenina N. Nalipay ◽  
Jelli Grace C. Luzano ◽  
Debi S. Galela ◽  
Michelle Anne L. Ferolino
Keyword(s):  
Symptom Severity ◽  
Anxiety Symptom ◽  
Generalized Anxiety

scholarly journals Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors

10.2196/16875 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e16875 ◽  
Author(s):  
Nicholas C Jacobson ◽  
Berta Summers ◽  
Sabine Wilhelm
Keyword(s):  
Social Anxiety ◽  
Negative Affect ◽  
Positive Affect ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Self Report ◽  
Sensor Data ◽  
Digital Phenotyping ◽  
Passive Sensor ◽  
Digital Biomarkers

Background Social anxiety disorder is a highly prevalent and burdensome condition. Persons with social anxiety frequently avoid seeking physician support and rarely receive treatment. Social anxiety symptoms are frequently underreported and underrecognized, creating a barrier to the accurate assessment of these symptoms. Consequently, more research is needed to identify passive biomarkers of social anxiety symptom severity. Digital phenotyping, the use of passive sensor data to inform health care decisions, offers a possible method of addressing this assessment barrier. Objective This study aims to determine whether passive sensor data acquired from smartphone data can accurately predict social anxiety symptom severity using a publicly available dataset. Methods In this study, participants (n=59) completed self-report assessments of their social anxiety symptom severity, depressive symptom severity, positive affect, and negative affect. Next, participants installed an app, which passively collected data about their movement (accelerometers) and social contact (incoming and outgoing calls and texts) over 2 weeks. Afterward, these passive sensor data were used to form digital biomarkers, which were paired with machine learning models to predict participants’ social anxiety symptom severity. Results The results suggested that these passive sensor data could be utilized to accurately predict participants’ social anxiety symptom severity (r=0.702 between predicted and observed symptom severity) and demonstrated discriminant validity between depression, negative affect, and positive affect. Conclusions These results suggest that smartphone sensor data may be utilized to accurately detect social anxiety symptom severity and discriminate social anxiety symptom severity from depressive symptoms, negative affect, and positive affect.

scholarly journals Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors (Preprint)

2019 ◽  
Author(s):  
Nicholas C Jacobson ◽  
Berta Summers ◽  
Sabine Wilhelm
Keyword(s):  
Social Anxiety ◽  
Negative Affect ◽  
Positive Affect ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Self Report ◽  
Sensor Data ◽  
Digital Phenotyping ◽  
Passive Sensor ◽  
Digital Biomarkers

BACKGROUND Social anxiety disorder is a highly prevalent and burdensome condition. Persons with social anxiety frequently avoid seeking physician support and rarely receive treatment. Social anxiety symptoms are frequently underreported and underrecognized, creating a barrier to the accurate assessment of these symptoms. Consequently, more research is needed to identify passive biomarkers of social anxiety symptom severity. Digital phenotyping, the use of passive sensor data to inform health care decisions, offers a possible method of addressing this assessment barrier. OBJECTIVE This study aims to determine whether passive sensor data acquired from smartphone data can accurately predict social anxiety symptom severity using a publicly available dataset. METHODS In this study, participants (n=59) completed self-report assessments of their social anxiety symptom severity, depressive symptom severity, positive affect, and negative affect. Next, participants installed an app, which passively collected data about their movement (accelerometers) and social contact (incoming and outgoing calls and texts) over 2 weeks. Afterward, these passive sensor data were used to form digital biomarkers, which were paired with machine learning models to predict participants’ social anxiety symptom severity. RESULTS The results suggested that these passive sensor data could be utilized to accurately predict participants’ social anxiety symptom severity (<i>r</i>=0.702 between predicted and observed symptom severity) and demonstrated discriminant validity between depression, negative affect, and positive affect. CONCLUSIONS These results suggest that smartphone sensor data may be utilized to accurately detect social anxiety symptom severity and discriminate social anxiety symptom severity from depressive symptoms, negative affect, and positive affect.

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.

The antidepressant duloxetine reduces anxiety symptom severity

2002 ◽  
Vol 12 ◽  
pp. 213 ◽  
Author(s):  
D.J. Goldstein ◽  
M. Detke ◽  
Y. Lu ◽  
M.A. Demitrack
Keyword(s):  
Symptom Severity ◽  
Anxiety Symptom

scholarly journals Blended Acceptance and Commitment Therapy Versus Face-to-face Cognitive Behavioral Therapy for Older Adults With Anxiety Symptoms in Primary Care: Pragmatic Single-blind Cluster Randomized Trial

10.2196/24366 ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. e24366
Author(s):  
Maartje Witlox ◽  
Nadia Garnefski ◽  
Vivian Kraaij ◽  
Margot W M de Waal ◽  
Filip Smit ◽  
...  
Keyword(s):  
Older Adults ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Behavioral Therapy ◽  
Later Life ◽  
Anxiety Symptoms ◽  
Face To Face ◽  
Acceptance And Commitment ◽  
Secondary Outcomes ◽  
Cluster Randomized

Background Anxiety symptoms in older adults are prevalent and disabling but often go untreated. Most trials on psychological interventions for anxiety in later life have examined the effectiveness of face-to-face cognitive behavioral therapy (CBT). To bridge the current treatment gap, other treatment approaches and delivery formats should also be evaluated. Objective This study is the first to examine the effectiveness of a brief blended acceptance and commitment therapy (ACT) intervention for older adults with anxiety symptoms, compared with a face-to-face CBT intervention. Methods Adults aged between 55-75 years (n=314) with mild to moderately severe anxiety symptoms were recruited from general practices and cluster randomized to either blended ACT or face-to-face CBT. Assessments were performed at baseline (T0), posttreatment (T1), and at 6- and 12-month follow-ups (T2 and T3, respectively). The primary outcome was anxiety symptom severity (Generalized Anxiety Disorder-7). Secondary outcomes were positive mental health, depression symptom severity, functional impairment, presence of Diagnostic and Statistical Manual of Mental Disorders V anxiety disorders, and treatment satisfaction. Results Conditions did not differ significantly regarding changes in anxiety symptom severity during the study period (T0-T1: B=.18, P=.73; T1-T2: B=−.63, P=.26; T1-T3: B=−.33, P=.59). Large reductions in anxiety symptom severity (Cohen d≥0.96) were found in both conditions post treatment, and these were maintained at the 12-month follow-up. The rates of clinically significant changes in anxiety symptoms were also not different for the blended ACT group and CBT group (χ21=0.2, P=.68). Regarding secondary outcomes, long-term effects on positive mental health were significantly stronger in the blended ACT group (B=.27, P=.03, Cohen d=0.29), and treatment satisfaction was significantly higher for blended ACT than CBT (B=3.19, P<.001, Cohen d=0.78). No other differences between the conditions were observed in the secondary outcomes. Conclusions The results show that blended ACT is a valuable treatment alternative to CBT for anxiety in later life. Trial Registration Netherlands Trial Register TRIAL NL6131 (NTR6270); https://www.trialregister.nl/trial/6131

scholarly journals Exercise Addiction and Its Relationship with Health Outcomes in Indoor Cycling Practitioners in Fitness Centers

2020 ◽  
Vol 17 (11) ◽  
pp. 4159
Author(s):  
Javier Bueno-Antequera ◽  
Carmen Mayolas-Pi ◽  
Joaquin Reverter-Masià ◽  
Isaac López-Laval ◽  
Miguel Ángel Oviedo-Caro ◽  
...  
Keyword(s):  
Physical Activity ◽  
High Risk ◽  
Health Outcomes ◽  
Effect Size ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Short Form ◽  
Low Risk ◽  
Exercise Addiction ◽  
Main Determinants

We studied the prevalence and possible association between exercise addiction and health in indoor cycling practitioners. In 1014 (492 women) adult indoor cyclists and 926 (597 women) controls with low levels of physical activity according to the short form of the International Physical Activity Questionnaire, we examined the risk of exercise addiction according to the Exercise Addiction Inventory and several health outcomes through a web-based experiment. The prevalence of a high risk of exercise addiction in cyclists was 13.3%, and it was higher in men than in women (16.5% vs. 10.0%, p = 0.002). Women cyclists with a high risk of exercise addiction had higher levels of physical activity (p < 0.001; effect size = −0.62, 95% CI: (−0.91, −0.32)) and anxiety symptom severity (p = 0.001; Effect Size (ES) = −0.59 (−0.89, −0.30)) than those with a low risk. For both sexes, cyclists with a low risk of exercise addiction had better social function, emotional role, and anxiety symptom severity compared with the controls (all p < 0.002; ES ranged from 0.25 to 0.47). Higher anxiety symptom severity and cardiorespiratory fitness were the main determinants of exercise addiction in cyclists (both p < 0.001). Our data suggest the importance of considering exercise addiction in indoor cyclists.

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