Acceptance or change: Treating socially anxious college students with ACT or CBGT.

2000 ◽  
Vol 1 (2) ◽  
pp. 3-10 ◽  
Author(s):  
Jennifer A. Block ◽  
Edelgard Wulfert
Keyword(s):  
College Students ◽  
Socially Anxious

Daily heterosocial interactions of high and low socially anxious college students: A diary study

1987 ◽  
Vol 18 (1) ◽  
pp. 90-96 ◽  
Author(s):  
Cynthia S. Dodge ◽  
Richard G. Heimberg ◽  
David Nyman ◽  
Gerald T. O'Rien
Keyword(s):  
College Students ◽  
Diary Study ◽  
Socially Anxious

Determinants of psychotherapy outcome expectations: Qualitative accounts from socially anxious college students

2021 ◽  
Author(s):  
Nicholas R. Morrison ◽  
Michael J. Constantino ◽  
Gennarina D. Santorelli ◽  
Erin L. McVicar ◽  
Rebecca M. Ametrano
Keyword(s):  
College Students ◽  
Outcome Expectations ◽  
Psychotherapy Outcome ◽  
Socially Anxious

scholarly journals Think, Pair, Freeze: The Association between Social Anxiety and Student Discomfort in the Active Learning Environment

2020 ◽  
Author(s):  
Steven G. Buzinski ◽  
Emma Armstrong-Carter ◽  
Jenna Clark
Keyword(s):  
College Students ◽  
Social Anxiety ◽  
Active Learning ◽  
Learning Environment ◽  
Student Performance ◽  
Course Performance ◽  
Socially Anxious ◽  
College Classrooms ◽  
Social Nature ◽  
The Social

Active learning instructional techniques, often characterized by paired or small group work (e.g., problem solving, discussion), are typically associated with improved student performance. Socially anxious students may, however, experience unique interpersonal and learning challenges due to the social nature of these techniques. Despite its prevalence among college students, little research has examined how social anxiety relates to students experience of active learning, and whether socially anxious students derive the same benefits from it. Across three studies conducted in college classrooms (combined N = 569), we found that many college students met clinical thresholds for social anxiety (30.1%, 58.9%, and 61.3%), social anxiety was positively associated with discomfort in the active learning environment (r = .52, β = .61, and β = .65), early course performance did not moderate the social anxiety and active learning discomfort relationship (β = -.01 and β = .11), and even after controlling for GPA, social anxiety and active learning discomfort interacted to predict final course grades (β = -.22). These studies add nuance to the active learning literature, and suggest the need for further research on how to best utilize these techniques for socially anxious students.

Self-Consciousness and Locus of Control

1978 ◽  
Vol 46 (3) ◽  
pp. 801-802 ◽  
Author(s):  
Warren C. Lowe ◽  
Gregory K. Gormanous ◽  
Ray Kersey
Keyword(s):  
College Students ◽  
Locus Of Control ◽  
Socially Anxious

179 college students were classified as internal or external in locus of control on the basis of I-E scores. Self-consciousness scores showed external subjects were more socially anxious than internal subjects.

Effects of Brief Acceptance and Cognitive Reappraisal Interventions on Experiential Avoidance in Socially Anxious Individuals: A Preliminary Investigation

2019 ◽  
Vol 44 (6) ◽  
pp. 841-864
Author(s):  
Samuel D. Spencer ◽  
Jeffrey A. Buchanan ◽  
Akihiko Masuda
Keyword(s):  
College Students ◽  
Mechanism Of Action ◽  
Experiential Avoidance ◽  
Public Speaking ◽  
Preliminary Investigation ◽  
Cognitive Reappraisal ◽  
Socially Anxious ◽  
To Receive ◽  
Shed Light ◽  
Speaking Task

The current study compared the effects of 15-min acceptance-based and cognitive reappraisal–based interventions on experiential avoidance (EA) in socially anxious college students who participated in an experimental public speaking task. Participants were randomly assigned to receive one of the two interventions designed to aid in preparation for a 5-min laboratory-based public speaking task. Results indicated that participants receiving the acceptance-based intervention reported significantly lower levels of EA at the post–public speaking task measurement time, indicating that this brief acceptance–based intervention yielded the proposed mechanism of action in the sample used for this study. These findings highlight the importance of process-based accounts of cognitive-behavioral psychotherapy and shed light on the importance of developing interventions for alleviating social anxiety.

scholarly journals Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study

10.2196/10101 ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. e10101 ◽  
Author(s):  
Mehdi Boukhechba ◽  
Philip Chow ◽  
Karl Fua ◽  
Bethany A Teachman ◽  
Laura E Barnes
Keyword(s):  
College Students ◽  
Social Anxiety ◽  
Global Positioning System ◽  
Prediction Method ◽  
Anxiety Symptoms ◽  
Self Report ◽  
Positioning System ◽  
Socially Anxious ◽  
Global Positioning ◽  
Anxiety Levels

Background Social anxiety is highly prevalent among college students. Current methodologies for detecting symptoms are based on client self-report in traditional clinical settings. Self-report is subject to recall bias, while visiting a clinic requires a high level of motivation. Assessment methods that use passively collected data hold promise for detecting social anxiety symptoms and supplementing self-report measures. Continuously collected location data may provide a fine-grained and ecologically valid way to assess social anxiety in situ. Objective The objective of our study was to examine the feasibility of leveraging noninvasive mobile sensing technology to passively assess college students’ social anxiety levels. Specifically, we explored the different relationships between mobility and social anxiety to build a predictive model that assessed social anxiety from passively generated Global Positioning System (GPS) data. Methods We recruited 228 undergraduate participants from a Southeast American university. Social anxiety symptoms were assessed using self-report instruments at a baseline laboratory session. An app installed on participants’ personal mobile phones passively sensed data from the GPS sensor for 2 weeks. The proposed framework supports longitudinal, dynamic tracking of college students to evaluate the relationship between their social anxiety and movement patterns in the college campus environment. We first extracted the following mobility features: (1) cumulative staying time at each different location, (2) the distribution of visits over time, (3) the entropy of locations, and (4) the frequency of transitions between locations. Next, we studied the correlation between these features and participants’ social anxiety scores to enhance the understanding of how students’ social anxiety levels are associated with their mobility. Finally, we used a neural network-based prediction method to predict social anxiety symptoms from the extracted daily mobility features. Results Several mobility features correlated with social anxiety levels. Location entropy was negatively associated with social anxiety (during weekdays, r=−0.67; and during weekends, r=−0.51). More (vs less) socially anxious students were found to avoid public areas and engage in less leisure activities during evenings and weekends, choosing instead to spend more time at home after school (4 pm-12 am). Our prediction method based on extracted mobility features from GPS trajectories successfully classified participants as high or low socially anxious with an accuracy of 85% and predicted their social anxiety score (on a scale of 0-80) with a root-mean-square error of 7.06. Conclusions Results indicate that extracting and analyzing mobility features may help to reveal how social anxiety symptoms manifest in the daily lives of college students. Given the ubiquity of mobile phones in our society, understanding how to leverage passively sensed data has strong potential to address the growing needs for mental health monitoring and treatment.

scholarly journals Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study (Preprint)

2018 ◽  
Author(s):  
Mehdi Boukhechba ◽  
Philip Chow ◽  
Karl Fua ◽  
Bethany A Teachman ◽  
Laura E Barnes
Keyword(s):  
College Students ◽  
Social Anxiety ◽  
Global Positioning System ◽  
Prediction Method ◽  
Anxiety Symptoms ◽  
Self Report ◽  
Positioning System ◽  
Socially Anxious ◽  
Global Positioning ◽  
Anxiety Levels

BACKGROUND Social anxiety is highly prevalent among college students. Current methodologies for detecting symptoms are based on client self-report in traditional clinical settings. Self-report is subject to recall bias, while visiting a clinic requires a high level of motivation. Assessment methods that use passively collected data hold promise for detecting social anxiety symptoms and supplementing self-report measures. Continuously collected location data may provide a fine-grained and ecologically valid way to assess social anxiety in situ. OBJECTIVE The objective of our study was to examine the feasibility of leveraging noninvasive mobile sensing technology to passively assess college students’ social anxiety levels. Specifically, we explored the different relationships between mobility and social anxiety to build a predictive model that assessed social anxiety from passively generated Global Positioning System (GPS) data. METHODS We recruited 228 undergraduate participants from a Southeast American university. Social anxiety symptoms were assessed using self-report instruments at a baseline laboratory session. An app installed on participants’ personal mobile phones passively sensed data from the GPS sensor for 2 weeks. The proposed framework supports longitudinal, dynamic tracking of college students to evaluate the relationship between their social anxiety and movement patterns in the college campus environment. We first extracted the following mobility features: (1) cumulative staying time at each different location, (2) the distribution of visits over time, (3) the entropy of locations, and (4) the frequency of transitions between locations. Next, we studied the correlation between these features and participants’ social anxiety scores to enhance the understanding of how students’ social anxiety levels are associated with their mobility. Finally, we used a neural network-based prediction method to predict social anxiety symptoms from the extracted daily mobility features. RESULTS Several mobility features correlated with social anxiety levels. Location entropy was negatively associated with social anxiety (during weekdays, r=−0.67; and during weekends, r=−0.51). More (vs less) socially anxious students were found to avoid public areas and engage in less leisure activities during evenings and weekends, choosing instead to spend more time at home after school (4 pm-12 am). Our prediction method based on extracted mobility features from GPS trajectories successfully classified participants as high or low socially anxious with an accuracy of 85% and predicted their social anxiety score (on a scale of 0-80) with a root-mean-square error of 7.06. CONCLUSIONS Results indicate that extracting and analyzing mobility features may help to reveal how social anxiety symptoms manifest in the daily lives of college students. Given the ubiquity of mobile phones in our society, understanding how to leverage passively sensed data has strong potential to address the growing needs for mental health monitoring and treatment.

Sign in / Sign up

Export Citation Format

Share Document