scholarly journals Internet-Based Cognitive-Behavioral Therapy for College Students With Anxiety, Depression, Social Anxiety, or Insomnia: Four Single-Group Longitudinal Studies of Archival Commercial Data and Replication of Employee User Study (Preprint)

2020 ◽  
Author(s):  
Mark D Attridge ◽  
Russell C Morfitt ◽  
David J Roseborough ◽  
Edward R Jones

BACKGROUND The growing behavioral health needs of college students have resulted in counseling centers reporting difficulties in meeting student demand. OBJECTIVE This study aims to test the real-world voluntary use by college students of 4 digital, self-directed mental health modules based on a cognitive behavioral therapy clinical model. The findings were also compared with those of employee users. METHODS Archival operational data from Learn to Live were extracted for student users at 4 colleges and universities in the Midwest region of the United States (N=951). The inclusion criteria were having clinical symptoms at established levels of moderate or higher severity and the use of 2 or more of the 8 lessons of a program within a 6-month period. Unique users in each program included 347 for depression; 325 for stress, anxiety, and worry; 203 for social anxiety; and 76 for insomnia. Paired <i>t</i> tests (two-tailed) compared the average level of change over time on a standardized measure of clinical symptoms appropriate to each program. Cohen <i>d</i> statistical effect sizes were calculated for each program. Potential moderator factors (age, gender, preliminary comprehensive assessment, number of lessons, duration, live coach support, and live teammate support) were tested together in repeated measures analysis of variance models with covariates in the full sample. Follow-up survey data (n=136) were also collected to explore user satisfaction and outcomes. Select data from another study of the same 4 programs by employee users meeting the same criteria (N=707) were examined for comparison. RESULTS The percentage of users who improved to a clinical status of no longer being at risk after program use was as follows: stress, anxiety, and worry program (149/325, 45.8%); insomnia program (33/76, 43.4%), depression program (124/347, 35.7%); and social anxiety program (45/203, 22.2%). Significant improvements (all <i>P</i>&lt;.001) over time were found in the mean scores for the clinical measures for each program: stress, anxiety, and worry (<i>t</i><sub>324</sub>=16.21; <i>d</i>=1.25); insomnia (<i>t</i><sub>75</sub>=6.85; <i>d</i>=1.10); depression (<i>t</i><sub>346</sub>=12.71; <i>d</i>=0.91); and social anxiety (<i>t</i><sub>202</sub>=8.33; <i>d</i>=0.80). Tests of the moderating factors across programs indicated that greater improvement was strongly associated with the use of more lessons and it also differed by program, by gender (males demonstrated more improvement than females), and by the use of live support (particularly coaching). Analyses of survey data found high satisfaction, improved academic outcomes, and successful integration into the university counseling ecosystem. The operational profile and outcomes of the college students were also similar to those of employee users of the same programs from our other study of employee users. Thus, this study provides a replication. CONCLUSIONS Self-directed internet-based cognitive behavioral therapy mental health modules are promising as a supplement to traditional in-person counseling services provided by college counseling centers.

10.2196/17712 ◽  
2020 ◽  
Vol 4 (7) ◽  
pp. e17712
Author(s):  
Mark D Attridge ◽  
Russell C Morfitt ◽  
David J Roseborough ◽  
Edward R Jones

Background The growing behavioral health needs of college students have resulted in counseling centers reporting difficulties in meeting student demand. Objective This study aims to test the real-world voluntary use by college students of 4 digital, self-directed mental health modules based on a cognitive behavioral therapy clinical model. The findings were also compared with those of employee users. Methods Archival operational data from Learn to Live were extracted for student users at 4 colleges and universities in the Midwest region of the United States (N=951). The inclusion criteria were having clinical symptoms at established levels of moderate or higher severity and the use of 2 or more of the 8 lessons of a program within a 6-month period. Unique users in each program included 347 for depression; 325 for stress, anxiety, and worry; 203 for social anxiety; and 76 for insomnia. Paired t tests (two-tailed) compared the average level of change over time on a standardized measure of clinical symptoms appropriate to each program. Cohen d statistical effect sizes were calculated for each program. Potential moderator factors (age, gender, preliminary comprehensive assessment, number of lessons, duration, live coach support, and live teammate support) were tested together in repeated measures analysis of variance models with covariates in the full sample. Follow-up survey data (n=136) were also collected to explore user satisfaction and outcomes. Select data from another study of the same 4 programs by employee users meeting the same criteria (N=707) were examined for comparison. Results The percentage of users who improved to a clinical status of no longer being at risk after program use was as follows: stress, anxiety, and worry program (149/325, 45.8%); insomnia program (33/76, 43.4%), depression program (124/347, 35.7%); and social anxiety program (45/203, 22.2%). Significant improvements (all P<.001) over time were found in the mean scores for the clinical measures for each program: stress, anxiety, and worry (t324=16.21; d=1.25); insomnia (t75=6.85; d=1.10); depression (t346=12.71; d=0.91); and social anxiety (t202=8.33; d=0.80). Tests of the moderating factors across programs indicated that greater improvement was strongly associated with the use of more lessons and it also differed by program, by gender (males demonstrated more improvement than females), and by the use of live support (particularly coaching). Analyses of survey data found high satisfaction, improved academic outcomes, and successful integration into the university counseling ecosystem. The operational profile and outcomes of the college students were also similar to those of employee users of the same programs from our other study of employee users. Thus, this study provides a replication. Conclusions Self-directed internet-based cognitive behavioral therapy mental health modules are promising as a supplement to traditional in-person counseling services provided by college counseling centers.


2021 ◽  
Vol 10 (5) ◽  
pp. 915
Author(s):  
Hyu Seok Jeong ◽  
Jee Hyun Lee ◽  
Hesun Erin Kim ◽  
Jae-Jin Kim

Virtual reality (VR) was introduced to maximize the effect of cognitive behavioral therapy (CBT) by efficiently performing exposure therapy. The purpose of this study was to find out whether VR-based individual CBT with relatively few treatment sessions is effective in improving social anxiety disorder (SAD). This therapy was applied to 115 patients with SAD who were retrospectively classified into 43 patients who completed the nine or 10 sessions normally (normal termination group), 52 patients who finished the sessions early (early termination group), and 20 patients who had extended the sessions (session extension group). The Brief Fear of Negative Evaluation Scale (BFNE) scores tended to decrease in all groups as the session progressed, and the slope of decrease was the steepest in the early termination group and the least steep in the session extension group. Severity of social anxiety in the last session and symptom reduction rate showed no significant group difference. Our findings suggest that short-term VR-based individual CBT of nine to 10 sessions may be effective. When the therapeutic effect is insufficient during this period, the additional benefit may be minimal if the session is simply extended. The improvement in the early termination group suggests that even shorter sessions of five or six can also be effective.


2021 ◽  
Vol 56 (S2) ◽  
pp. 40-41
Author(s):  
Alethea Desrosiers ◽  
Carolyn Schafer ◽  
Jordan Freeman ◽  
Alpha Vandi ◽  
Miriam Hinton ◽  
...  

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