Abstract
OBJECTIVES: Off periods in Parkinson's disease are associated with a worsening of nonmotor symptoms and acute psychological distress. The relationship between motor fluctuations and episodic distress in naturalistic settings remains unclear, particularly the role of individual psychological factors. This study aimed to identify those factors through real-life, real-time assessment using ecological momentary assessment (EMA).
METHOD: Twenty participants (seven female) completed multiple brief prompted surveys over a 7-day period assessing current motor and medication state, social situation, episodic distress, and cognitive processes (rumination, symptom focus, and worry). Baseline depression and anxiety were measured using validated questionnaires, as were positive and negative beliefs and attitudes (metacognitions) regarding cognitive processes. The feasibility of EMA via smartphones was assessed at the end of the study.
RESULTS: Across participants, 496 complete data sets were collected. Generalized linear mixed-model regression analyses showed that episodic distress was predicted by a combination of cognitive processes, F(1, 483) = 41.14, p <.001, momentary motor state, F(3, 483) = 10.40, p <.001, time of day, F(1, 23) = 12.42, p = .002, and trait negative metacognitions, F(1, 6) = 7.21, p = .037). EMA was judged acceptable by the majority of participants.
CONCLUSIONS: Time of day, cognitive processes, and negative metacognitions predict episodic distress independent of motor state. This indicates potential targets for nonpharmacological interventions aimed at alleviating episodic distress in patients with motor fluctuations. EMA is a feasible methodology for Parkinson's disease research and potential tool for delivering such interventions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
METHOD: Twenty participants (seven female) completed multiple brief prompted surveys over a 7-day period assessing current motor and medication state, social situation, episodic distress, and cognitive processes (rumination, symptom focus, and worry). Baseline depression and anxiety were measured using validated questionnaires, as were positive and negative beliefs and attitudes (metacognitions) regarding cognitive processes. The feasibility of EMA via smartphones was assessed at the end of the study.
RESULTS: Across participants, 496 complete data sets were collected. Generalized linear mixed-model regression analyses showed that episodic distress was predicted by a combination of cognitive processes, F(1, 483) = 41.14, p <.001, momentary motor state, F(3, 483) = 10.40, p <.001, time of day, F(1, 23) = 12.42, p = .002, and trait negative metacognitions, F(1, 6) = 7.21, p = .037). EMA was judged acceptable by the majority of participants.
CONCLUSIONS: Time of day, cognitive processes, and negative metacognitions predict episodic distress independent of motor state. This indicates potential targets for nonpharmacological interventions aimed at alleviating episodic distress in patients with motor fluctuations. EMA is a feasible methodology for Parkinson's disease research and potential tool for delivering such interventions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
| Original language | English |
|---|---|
| Pages (from-to) | 518-526 |
| Number of pages | 9 |
| Journal | Health psychology : official journal of the Division of Health Psychology, American Psychological Association |
| Volume | 38 |
| Issue number | 6 |
| Early online date | 11 Apr 2019 |
| DOIs | |
| Publication status | Published - 1 Jun 2019 |
Keywords
- Distress
- Ecological momentary assessment
- Metacognition
- Motor fluctuations
- Parkinson's disease