Individually Tailored Internet-Based Cognitive-Behavioral Therapy for Daily Functioning in Patients with Parkinson’s Disease: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is often associated with psychological distress and lowered daily functioning. The availability of psychological interventions tailored for people with Parkinson is very limited. OBJECTIVE: To study if guided individually-tailored internet-based cognitive behavioral therapy (ICBT) provide additional value to standard medical treatment for PD. METHODS: Seventy-seven individuals with PD and self-reported problems with general function measured with the Work and Social Adjustment Scale (WSAS > 15) were randomized to 10 weeks of either ICBT combined with standard medical treatment, or standard medical treatment plus being on waitlist to ICBT (CONTROL). Change in the main outcome WSAS, as well as secondary measures such as quality of life, depression, anxiety and insomnia symptoms were investigated post treatment. RESULTS: Participants receiving ICBT reported significantly higher functioning after treatment (WSAS group difference -4.56, controlled effect size g = 0.69, significant group by time interaction, Wχ2= 26.23, p = 0.001). However, only around one third of participants in the treatment group were classified as treatment responders, defined as having a 30% reduction on the WSAS post treatment. Patient involvement and ratings of ICBT credibility were high. Symptoms of anxiety, depression and insomnia symptoms were significantly lower after treatment compared to CONTROL. There were also positive effects on Parkinson-specific function and quality of life in the treatment group. CONCLUSIONS: ICBT as an addition to standard medical treatment was credible and improved functioning for some individuals with PD. Still, the treatment needs further development in order to help a larger proportion of individuals with PD. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT02627885.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".