A precision treatment model for internet-delivered cognitive behavioral therapy provides a low-cost, accessible, and effective alternative for treating anxiety and depression, according to a study published in JAMA Psychiatry. The intervention was developed by researchers from the United States, Mexico, and Colombia and studied in undergraduate university students.
The research included 1319 students with anxiety and depression. The students were randomly assigned to three groups that received either remote (internet-based) cognitive behavioral therapy guided by a therapist, self-guided cognitive behavioral therapy (without support from a therapist), or standard treatment provided by the healthcare services within their community (the control condition).
Students who received guided cognitive behavioral therapy had higher combined rates of remission of these disorders (51.8%) than students who received self-guided therapy (37.8%) or conventional therapy (40%). These differences were not significant for remission of anxiety, however.
Guided cognitive behavioral therapy was associated with the highest probability of remission of anxiety and depression in 91.7% of students, the highest probability of remission of anxiety in all students, and the highest probability of remission of depression in 71.5% of participants.
The results of this analysis could be used to improve psychological care by optimizing how different treatment methods are assigned, especially in mental health institutions where available technical and human resources are limited, according to the investigators.
“We started designing this study before COVID-19 with the idea of optimizing care for these mental health problems,” study author Corina Benjet Miner, PhD, an epidemiological and psychosocial researcher at the Ramón de la Fuente National Institute of Psychiatry in Mexico City, told Medscape‘s Spanish edition. “We wanted to find additional strategies to achieve better care. The pandemic helped us because, even though this has been undergoing research for many years, internet-delivered interventions were not as well accepted. But during the pandemic, there weren’t any other options.”
Given the high prevalence of mental disorders before and after the pandemic, no healthcare system in the world would be able to provide in-person care to each patient with depression or anxiety, said Benjet Miner. “So, the idea is to look for other cost-effective strategies that can ramp up our interventions and reach a greater number of people without negatively impacting the quality of care,” she explained.
“I believe that [the precision model] is an excellent proposal that can save financial resources and avoid transfers,” said Juana Olvera Méndez, research professor working with the cognitive behavioral approach at the Iztacala Faculty of Higher Studies (FESI) of the National Autonomous University of Mexico in Mexico City. “It also makes it possible to provide patients with immediate care, in contrast to when someone has to go in for [in-person] therapy, which will depend a lot on how the therapist approaches the situation.”
Students from seven universities in Colombia and Mexico were included in the study. They were aged 18 years or older and had a score of 10 or greater on the self-administered Generalized Anxiety Disorder scale-7 test, or had depression with scores of 10 or greater on the nine-item Patient Health Questionnaire, which is also self-administered.
The study’s exclusion criteria included a history of bipolar disorder, nonaffective psychosis, or suicidal ideation with suicide attempts. The investigators used 284 prescription predictors to anticipate the differential response to antianxiety and antidepression therapy.
By grouping these predictors into 11 conceptual categories (such as demographic characteristics, COVID-19-linked stressors, or mental disorder comorbidities) and using machine learning algorithms, the investigators were able to predict in an individualized manner the probability of remission for participants in each of the groups.
“For depression, we found that 28.5% of patients could experience better or equivalent effects from the self-guided program (in comparison to the guided program). Once you have this program, it doesn’t cost anything, so there could be a massive number of people who could benefit from a cost-free therapy,” said Benjet Miner.
While numerous studies in precision medicine have tried to determine the most appropriate treatment for each patient, “they don’t have the high number of predictors that we used in this research, and I feel like this gives us a significant edge,” she added.
She also explained that they found no differences in user satisfaction between the guided and unguided version of the therapy, so now they must now discover why the guided version works better. One notable point is that patients accessed (online) the guided program twice as many times as those who used the self-guided version, but the number of times used is not enough to explain the better outcomes.
“We believe that patients develop some sort of connection with the guides, who are not providing therapy but only making recommendations in brief interactions with patients once a week. It has something to do with that connection, in addition to the longer time spent interacting with the platform, which provides better results with the guided version,” stated Benjet Miner.
One of the main limitations of this study is that, though it compares three treatment methods, the third one (standard care) is not homogeneous, because each of the seven universities from which the students were selected has different resources for this purpose. “Some universities, like the National Autonomous University of Mexico, have very formal services, with teams of psychologists and psychiatrists, while others don’t have this type of service, or they cover additional aspects, like vocational counseling. So, it’s very difficult to determine exactly what kind of care patients are receiving, because it’s not homogeneous,” she said.
As many as nine assessments using psychometric tests are sometimes required before the intervention can be evaluated, said Méndez. “This study doesn’t go into too much detail in that area, focusing rather on treatment. So, it would be important to know the diagnoses of the users, who may be experiencing different degrees of depression or anxiety. It would be worth asking what happens if a user requires psychiatric treatment or support.”
Méndez, who provides psychological therapy in person and online at the Student Support and Counselling Center at FESI, pointed out that it would be important to provide close follow-up on these results to see whether they are sustained in the short and long terms. In her opinion, this model could be presented to other users requiring treatment for anxiety or depression, provided that they can use information and communication technologies.
This precision model, which can also be supported on mobile phones or tablets, could be transferred to primary care facilities or vulnerable populations in rural areas, said Benjet Miner. “The idea is to reach a point where these algorithms become accurate enough and have a really strong predictive power so that clinicians can use them. The goal is always to find the best treatment at the lowest cost, so that it’s sustainable,” she concluded.
This study was funded by grant number R01MH120648 from the National Institute of Mental Health and the Fogarty International Center. Benjet Miner reports no relevant financial relationships; the declarations of the remaining authors can be found at the publication’s website.
This article was translated from Medscape’s Spanish edition.
Source link : https://www.medscape.com/viewarticle/996191?src=rss
Publish date : 2023-09-07 14:27:00
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