Developing and Testing a Machine Learning Enabled Mindfulness Intervention for Reducing Loneliness Among Hong Kong Chinese Older Adults

Developing and Testing a Machine Learning Enabled Mindfulness Intervention for Reducing Loneliness Among Hong Kong Chinese Older Adults: A Hybrid Experimental Design Study

Develop and test an effective machine learning enabled application-based (app-based) mindfulness intervention for reducing loneliness of Hong Kong Chinese older adults.

This study will utilize a hybrid Sequential Multiple Assignment Randomized Trial-Micro Randomized Trial (Hybrid SMART-MRT) to: 1) evaluate the effectiveness of a single-session intervention (SSI) of mindfulness on reducing loneliness; 2) identify the optimal first-line coaching approach after the SSI of mindfulness; 3) examine whether increasing the intensity of human coaching or adding a telephone-based human-delivered booster session will benefit participants who do not respond to the first-line coaching; 4) determine whether sending push notifications increases the engagement of our app-based coaching, by comparing its results with those of no push notification; 5) determine whether sending a recommended activity increases the engagement of our app-based coaching, by comparing its results with those of no recommended activity; and 6) determine whether sending a personalized motivational message increases the engagement of our app-based coaching, by comparing its results with those of a standard motivational message.

Inclusion Criteria:

• Aged 65 or older
• Possess a smartphone with an Android or iOS operating system
• Communicable in Cantonese
• Lonely (cut-off >/=6 on the three-item UCLA Loneliness Scale)

Exclusion Criteria:

• Cognitive impairment, psychiatric disorder, learning disability
• Active suicide ideation
• Engaged in psychotherapy and psychosocial interventions in the past year