Elsa Rojas, PhD

All Publications

• Capitalizing on natural language processing (NLP) to automate the evaluation of coach implementation fidelity in guided digital cognitive-behavioral therapy (GdCBT). Psychological medicine Zainal, N. H., Eckhardt, R., Rackoff, G. N., Fitzsimmons-Craft, E. E., Rojas-Ashe, E., Barr Taylor, C., Funk, B., Eisenberg, D., Wilfley, D. E., Newman, M. G. 2025; 55: e106

  Abstract

  As the use of guided digitally-delivered cognitive-behavioral therapy (GdCBT) grows, pragmatic analytic tools are needed to evaluate coaches' implementation fidelity.We evaluated how natural language processing (NLP) and machine learning (ML) methods might automate the monitoring of coaches' implementation fidelity to GdCBT delivered as part of a randomized controlled trial.Coaches served as guides to 6-month GdCBT with 3,381 assigned users with or at risk for anxiety, depression, or eating disorders. CBT-trained and supervised human coders used a rubric to rate the implementation fidelity of 13,529 coach-to-user messages. NLP methods abstracted data from text-based coach-to-user messages, and 11 ML models predicting coach implementation fidelity were evaluated.Inter-rater agreement by human coders was excellent (intra-class correlation coefficient = .980-.992). Coaches achieved behavioral targets at the start of the GdCBT and maintained strong fidelity throughout most subsequent messages. Coaches also avoided prohibited actions (e.g. reinforcing users' avoidance). Sentiment analyses generally indicated a higher frequency of coach-delivered positive than negative sentiment words and predicted coach implementation fidelity with acceptable performance metrics (e.g. area under the receiver operating characteristic curve [AUC] = 74.48%). The final best-performing ML algorithms that included a more comprehensive set of NLP features performed well (e.g. AUC = 76.06%).NLP and ML tools could help clinical supervisors automate monitoring of coaches' implementation fidelity to GdCBT. These tools could maximize allocation of scarce resources by reducing the personnel time needed to measure fidelity, potentially freeing up more time for high-quality clinical care.

  View details for DOI 10.1017/S0033291725000340

  View details for PubMedID 40170669

• Harnessing mobile technology to reduce mental health disorders in college populations: A randomized controlled trial study protocol. Contemporary clinical trials Fitzsimmons-Craft, E. E., Taylor, C. B., Newman, M. G., Zainal, N. H., Rojas-Ashe, E. E., Lipson, S. K., Firebaugh, M., Ceglarek, P., Topooco, N., Jacobson, N. C., Graham, A. K., Kim, H. M., Eisenberg, D., Wilfley, D. E. 2021: 106320

  Abstract

  About a third of college students struggle with anxiety, depression, or an eating disorder, and only 20-40% of college students with mental disorders receive treatment. Inadequacies in mental health care delivery result in prolonged illness, disease progression, poorer prognosis, and greater likelihood of relapse, highlighting the need for a new approach to detect mental health problems and engage college students in services. We have developed a transdiagnostic, low-cost mobile mental health targeted prevention and intervention platform that uses population-level screening to engage college students in tailored services that address common mental health problems. We will test the impact of this mobile mental health platform for service delivery in a large-scale trial across 20+ colleges. Students who screen positive or at high-risk for clinical anxiety, depression, or an eating disorder and who are not currently engaged in mental health services (N = 7884) will be randomly assigned to: 1) intervention via the mobile mental health platform; or 2) referral to usual care (i.e., campus health or counseling center). We will test whether the mobile mental health platform, compared to referral, is associated with improved uptake, reduced clinical cases and disorder-specific symptoms, and improved quality of life and functioning. We will also test mediators, predictors, and moderators of improved mental health outcomes, as well as stakeholder-relevant outcomes, including cost-effectiveness and academic performance. This population-level approach to service engagement has the potential to improve mental health outcomes for the millions of students enrolled in U.S. colleges and universities.

  View details for DOI 10.1016/j.cct.2021.106320

  View details for PubMedID 33582295

• Psychosocial interventions and support programs for fathers of NICU infants - A comprehensive review. Early human development Ocampo, M. J., Tinero, J. A., Rojas-Ashe, E. E. 2020: 105280

  Abstract

  The experience of having a child in the neonatal intensive care unit (NICU) is often unexpected, traumatic, and presents numerous stressors for new fathers. Past research has shown that parents of all genders with children in the NICU experience clinically significant psychological symptoms, yet the bulk of research and intervention efforts to date have focused on the needs of mothers. This paper will provide a review of the literature, outline current knowledge about the specific needs of men with children in the NICU, and recommend areas of focus for future research. The paper will also highlight the need to tailored interventions that specifically address the unique needs of fathers.

  View details for DOI 10.1016/j.earlhumdev.2020.105280

  View details for PubMedID 33221029

• A Social Justice Approach to Measuring Bystander Behavior: Introducing the Critically Conscious Bystander Scale SEX ROLES Johnson, N. L., Walker, R. V., Rojas-Ashe, E. E. 2019; 81 (11-12): 731–47

  View details for DOI 10.1007/s11199-019-01028-w

  View details for Web of Science ID 000496328600005

• Toward a More Complete Understanding of Bystander Willingness to Help: What Role Does Critical Consciousness Play? SEX ROLES Rojas-Ashe, E. E., Walker, R. V., Holmes, S. C., Johnson, D. M. 2019; 81 (7-8): 415–27

  View details for DOI 10.1007/s11199-019-1007-z

  View details for Web of Science ID 000485310900002