Effect of Artificial Intelligent-based Training and Benson Relaxation Exercises on Caregiver Burden and Stress Levels in Caregivers of Patients With Parkinson's Disease

Given the progressive nature of Parkinson's disease, individuals experience a progressive decline in their ability to perform daily activities. In such cases, they require support and assistance. People with Parkinson's are generally cared for by spouses, adult children, close relatives, or other family members. Caregivers are exposed to stress and the burden of care. It has been noted that providing caregivers with regular training on managing the disease process, along with follow-up support after the training, can reduce the caregiver's anxiety and facilitate the management of the patient's care. The use of complementary and alternative methods has been steadily increasing in recent years. The Benson relaxation technique, one of the most useful and well-known non-pharmacological interventions, is a reliable method that can alleviate various physical and mental symptoms such as anxiety, stress, and pain.

The aim of this study is to evaluate the effect of artificial intelligence-supported training and the Benson relaxation exercise on the care burden and stress levels of caregivers of people with Parkinson's disease.

In this study, caregivers in the experimental group will receive training on Parkinson's disease care and the Benson relaxation exercise. 1. The experimental group will receive training on Parkinson's disease and on managing common issues associated with the disease. The training content was prepared by the researcher through a review of the literature and consultation with experts in the field. 2. The training for the experimental group, which includes the Benson relaxation exercise, will cover the definition, benefits, and steps for performing the Benson relaxation exercise.

To enable participants to continue the training and the Benson relaxation exercise module at home, the AI-based module will be downloaded to their phones via a link sent by the researcher. The training provided to the experimental groups will last 4 weeks. Throughout the 4 weeks, the researcher will monitor participants' engagement with the training via the AI module. No training will be provided to the control group.

• artificial intelligent-based training (Behavioral): experimental group
• artificial intelligent-based Benson's relaxation exercise (Behavioral): experimental group

Primary outcomes

• Zarit Caregiver Burden Scale [The scale will be completed at the start of the study and 4 weeks after the completion of training and exercise.]: This is a measure used to assess the stress experienced by caregivers of individuals requiring care or the elderly. The measurement tool consists of 22 items. The items are Likert-type, and each item is rated on a scale of 0 to 4, using the response options "never," "rarely," "sometimes," "often," or "almost always." A score ranging from 0 to 88 is possible on this scale. A high scale score indicates a high level of distress.
• Caregiver Stress Scale [The scale will be completed at the start of the study and 4 weeks after the completion of training and exercise.]: It was developed to measure the caregiving burden. It consists of 13 items. There is at least one item for each category: physical, social, work, financial, and time. On the scale, a score of 7 or higher indicates a higher level of stress.

Sex: All, ages: 18 Years to any, accepts healthy volunteers

Inclusion Criteria:

* Be 18 years of age or older
* Be a family member of the patient (spouse, daughter, son, etc.)
* Living in the same household as the patient
* Having cared for the patient for at least 6 months
* Being the primary caregiver responsible for the patient's care
* There being no paid staff member in the home to assist the caregiver
* Having no health issues that prevent communication
* Being able to read and write
* Having access to a phone for communication

Exclusion Criteria:

* Having visual, auditory, or cognitive communication barriers

• MEHTAP TAN, PROFESSOR DOCTOR, Principal investigator, Ataturk University