Measurement-based and data-informed psychological therapy

W Lutz, B Schwartz, J Delgadillo - Annual Review of Clinical …, 2022 - annualreviews.org
Outcome measurement in the field of psychotherapy has developed considerably in the last
decade. This review discusses key issues related to outcome measurement, modeling, and …

Modern views of machine learning for precision psychiatry

ZS Chen, IR Galatzer-Levy, B Bigio, C Nasca, Y Zhang - Patterns, 2022 - cell.com
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …

Prospective evaluation of a clinical decision support system in psychological therapy.

W Lutz, AK Deisenhofer, J Rubel… - Journal of consulting …, 2022 - psycnet.apa.org
Objective: Thus far, most applications in precision mental health have not been evaluated
prospectively. This article presents the results of a prospective randomized-controlled trial …

Measuring, predicting, and tracking change in psychotherapy

W Lutz, K de Jong, JA Rubel… - Bergin and Garfield's …, 2021 - books.google.com
This chapter addresses fundamental issues of change in psychotherapy: how to measure,
monitor, predict change, and provide feedback on treatment outcome. The chapter starts …

Deep learning and machine learning in psychiatry: a survey of current progress in depression detection, diagnosis and treatment

M Squires, X Tao, S Elangovan, R Gururajan, X Zhou… - Brain Informatics, 2023 - Springer
Informatics paradigms for brain and mental health research have seen significant advances
in recent years. These developments can largely be attributed to the emergence of new …

[HTML][HTML] Machine learning-based proactive social-sensor service for mental health monitoring using twitter data

S Hinduja, M Afrin, S Mistry, A Krishna - International Journal of Information …, 2022 - Elsevier
The social media platforms are considered an ecosystem of social sensors where each
social media platform user is treated as a social sensor cloud. To overcome the limitations of …

What is the current and future status of digital mental health interventions?

RM Baños, R Herrero, MD Vara - The Spanish Journal of Psychology, 2022 - cambridge.org
The prevalence of mental disorders continues to increase, especially with the advent of the
COVID-19 pandemic. Although we have evidence-based psychological treatments to …

A survey on wearable sensors for mental health monitoring

N Gomes, M Pato, AR Lourenco, N Datia - Sensors, 2023 - mdpi.com
Mental illness, whether it is medically diagnosed or undiagnosed, affects a large proportion
of the population. It is one of the causes of extensive disability, and f not properly treated, it …

[HTML][HTML] Machine learning methods for predicting postpartum depression: scoping review

K Saqib, AF Khan, ZA Butt - JMIR mental health, 2021 - mental.jmir.org
Background Machine learning (ML) offers vigorous statistical and probabilistic techniques
that can successfully predict certain clinical conditions using large volumes of data. A review …

Attitudes and perspectives towards the preferences for artificial intelligence in psychotherapy

ME Aktan, Z Turhan, I Dolu - Computers in Human Behavior, 2022 - Elsevier
The use of artificial intelligence (AI) in psychotherapy has been increased in recent years.
While these technologies in psychotherapy are growing, the circumstances of accepting …