Background: Innovative moments (IMs), defined as moments in psychotherapy when patients' problematic patterns change toward more elaborated and adaptive patterns, have been shown to be associated with a clinical change in patients with depression. Thus, far IMs have been studied in face-to-face settings but not in telephone-based cognitive-behavioral therapy (t-CBT). This study investigates whether IMs occur in t-CBT and examines the association between IMs and symptom improvement, and reconceptualization and symptom improvement.
Methods: The therapy transcripts of = 10 patients with mild to moderate depression (range: 7-11 sessions, in total 94 sessions) undergoing t-CBT were qualitatively and quantitatively analyzed. Symptom severity (Patient Health Questionnaire-9) and IMs (levels and proportions) were assessed for each therapy session. Hierarchical linear models were used to test the prediction models.
Results: The rating of IMs was shown to be feasible and reliable using the Innovative Moments Coding System (IMCS) (84.04% agreement in words coded), which is indicative of the applicability of the concept of IMs in t-CBT. Only reconceptualization IMs were shown to have a predictive value for treatment success ( = 0.05, = 0.01).
Discussion: The results should be interpreted with caution due to the exploratory nature of this study. Due to the telephone setting, it was necessary to adapt the IMCS. Nonetheless, the extent of IMs identified in the low-intensity t-CBT investigated was comparable to IMs in face-to-face therapy. Further studies are needed to clarify the association between IMs and treatment success as a change process, especially for low-intensity treatments.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10409642 | PMC |
http://dx.doi.org/10.3389/fpsyg.2023.1165899 | DOI Listing |
PLoS One
January 2025
School of Computer Science and Engineering, Changchun University of Technology, Changchun, Jilin, China.
Parkinson's disease (PD) is a common disease of the elderly. Given the easy accessibility of handwriting samples, many researchers have proposed handwriting-based detection methods for Parkinson's disease. Extracting more discriminative features from handwriting is an important step.
View Article and Find Full Text PDFJ Multidiscip Healthc
January 2025
Department of Neurobiology, Care Science and Society (NVS), Division of Occupational Therapy, Karolinska Institutet, Stockholm, Sweden.
Background: The care of older persons is facing several challenges, especially as care tasks are becoming increasingly rationalized with less opportunity for relational engagement between nurse assistants and older persons. Evidence suggests this engagement is needed to promote well-being and satisfaction among the older persons with whom they work. The aim of this study was to explore how care, in the context of worker perspectives, is understood and experienced in home or residential care facilities.
View Article and Find Full Text PDFNat Commun
January 2025
State Key Laboratory of Precision Geodesy, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China.
Interplay between seismic and aseismic slip could shed light on the frictional properties and seismic potential of faults. The well-recorded 2023 Kahramanmaraş earthquake doublet provides an excellent opportunity to understand their partitioning on strike-slip faults. Here, we utilize InSAR and strong motion data to derive the coseismic rupture during the doublet, ~4-month postseismic afterslip, and slip distributions of two Mw>6.
View Article and Find Full Text PDFGait Posture
January 2025
Department of Biomechanics and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE 68182, USA; Department of Surgery and Research Service, Nebraska-Western Iowa Veterans Affairs Medical Center, Omaha, NE 68105, USA. Electronic address:
Background: This study leverages Artificial Neural Networks (ANNs) to predict lower limb joint moments and electromyography (EMG) signals from Ground Reaction Forces (GRF), providing a novel perspective on human gait analysis. This approach aims to enhance the accessibility and affordability of biomechanical assessments using GRF data, thus eliminating the need for costly motion capture systems.
Research Question: Can ANNs use GRF data to accurately predict joint moments in the lower limbs and EMG signals?
Methods: We employed ANNs to analyze GRF data and to use them to predict joint moments (363-trials; 4-datasets) and EMG signals (63-trials; 2-datasets).
JMIR Hum Factors
January 2025
Department of Value Improvement, St. Antonius Hospital, Nieuwegein, Netherlands.
Background: Patients with cerebrovascular accident (CVA) should be involved in setting their rehabilitation goals. A personalized prediction of CVA outcomes would allow care professionals to better inform patients and informal caregivers. Several accurate prediction models have been created, but acceptance and proper implementation of the models are prerequisites for model adoption.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!