Web-based CBT for the prevention of anxiety symptoms among medical and health science graduate students

ABSTRACT

Medical and health science graduate students report greater anxiety problems than the general population, but they are less likely to seek treatment due to cultural and logistical barriers. One preventative approach that overcomes these barriers is web-based cognitive behavioral therapy (webCBT). It is unknown whether webCBT is effective for preventing anxiety escalation within this population. A randomized controlled trial was conducted, comparing the effects of webCBT versus a control group (CG). Medical university students (n=594; Mage=27; 67% female; 80% Caucasian) completed online baseline measures and four assigned online activities. Measures were re-administered after approximately three months. There was a small interaction effect between time of assessment and treatment condition. Anxiety severity was lower in the webCBT (M[SD]=2.88[3.36]) versus CG condition (M[SD]=3.69 [3.35]) at follow-up. This effect was moderate for students with mild, versus minimal, anxiety at baseline. The proportion of students with possible anxiety disorder was lower in the webCBT (4.5%) versus CG (8.5%) condition, and the proportion of mildly anxious students with a clinically significant increase in symptoms was lower in the webCBT (10%) versus CG (20%) condition. WebCBT may aid in preventing anxiety escalation in this population, particularly for at-risk students who report mild anxiety symptoms.

KEYWORDS:

• CBT
• internet
• web
• anxiety
• prevention
• medical students
• graduate students

Acknowledgments

The authors would like to acknowledge and thank the students for taking part in this study. The authors would also like to thank and acknowledge Helen Christensen, PhD., Professor at the Black Dog Institute, University of New South Wales, Sydney, Australia, who generously provided access to MoodGym to allow the conduct of this study. The authors would also like to acknowledge the assistance of Ms. Kylie Bennett, e hub manager, and Mr Anthony Bennett, software engineer, at the Centre for Mental Health Research. Dr Christensen, Ms. Bennett, and Mr. Bennett provided no financial support and were not involved in the design, analysis or interpretation of the study results.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The pattern of results held when not including covariates, F (1, 592) = 3.91, η² _p = .01, p = .048.

2. These results were consistent when analyses were conducted only among follow-up assessment completers (i.e. per-protocol analysis), multivariate F (1, 481) = 4.80, p = .03.

3. The pattern of results held when not including covariates, (M[SD] = 2.97[3.16]) versus CG (M[SD] = 3.62[3.67]) condition, t(598.83) = 2.31, p = .02, d = .19, CI(95)_d = .03—.35. Cohen’s d was corrected for dependence between the means, using Morris and DeShon’s (2002) equation 8.

4. Results neared significance and the pattern of results held among follow-up assessment completers (i.e. per-protocol analysis), χ² (1) = 2.72, p = .13; φ = .07.

5. Gender did not moderate the strength of the time-treatment condition interaction found in the RM ANCOVA results, F(1,471) = .33, η² _p = .001, p =.57.

6. Results were consistent when analyses were conducted only among follow-up assessment completers (i.e. per-protocol analysis), χ² (1) = 6.21, p = .045; LR = 6.27, p = .04, φ = .19 (minimal: p = .78, φ = .78).

Additional information

Funding

This work was supported by the Department of Health and Human Services (DHHS) and the Substance Abuse and Mental Health Services Administration (SAMHSA) Garrett Lee Smith Memorial Act, under Grant [1U79SM060490-01]; and the National Institute on Drug Abuse (NIDA) under Grant [1K23DA039318-01]; and the National Institute of Mental Health (NIMH) under Grant [T32MH018869-30].