Collaborative assessment as an intervention in the treatment of mental Illness: a systematic review
dataset posted on 2024-07-01, 19:00 authored by Oliver Rumle Hovmand, Jasmin Rejaye Gryesten, Ole Jakob Storebø, Nina Reinholt, Sidse M. Arnfred. Three meta-analyses suggested that the psychological assessment as a therapeutic intervention approach might have therapeutic effects but had unspecific inclusion criteria. We searched four databases for RCTs that reported on the use of psychological assessment as an intervention. Two reviewers independently selected papers, extracted data, and assessed study quality. We conducted and reported the systematic review following the PRISMA statement. We assessed the Risk of bias in included studies using the Risk of Bias tool and graded the strength of the evidence with GRADE. We included two RCTs: The first study investigated Therapeutic Assessment (TA) combined with Manual-Assisted Cognitive Behavior Therapy (MACT) compared with MACT only in 16 outpatients with personality disorders. The trial found among completers (n = 7) no difference in borderline symptomatology but a possible difference regarding suicidality favoring MACT + TA. The trial did not provide any outcomes relating to readiness for treatment. The other trial investigated TA compared with a Goal-focused Pretreatment Intervention in a sample of 74 outpatients with personality disorders. The results found no intervention effects on symptomatology but suggested that TA might improve patient expectancy for future treatment among completers of the intervention. Both trials were judged at a high risk of bias and with very low certainty of evidence. We found no support for the clinical effect of psychological assessment as a therapeutic intervention due to the high risk of bias and low certainty of the evidence.
HappyDB is a crowd-sourced collection of 100,000 happy moments designed to advance the understanding of happiness through text analysis. The database is publicly available and aims to support research in natural language processing (NLP) and positive psychology. It provides insights into the causes of happiness and suggests sustainable actions for improving well-being.
The data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting
This paper discusses Helply - a synthesized ML training dataset focused on psychology and therapy, created by Alex Scott and published by NamelessAI. The dataset developed by Alex Scott is a comprehensive collection of synthesized data designed to train LLMs in understanding psychological and therapeutic contexts. This dataset aims to simulate real-world interactions between therapists and patients, enabling ML models to learn from a wide range of scenarios and therapeutic techniques.