RH10
Participant Engagement in Online Computer-Assisted Cognitive Rehabilitation

Thursday, May 31, 2018
Exhibit Hall A (Nashville Music City Center)
Taylor Moulton, BSN Student , School of Nursing, The University of Texas at Austin, Austin, TX
Janet Morrison, RN, PhD, MSCN , School of Nursing, The University of Texas at Austin, Austin, TX
Alexa Stuifbergen, RN, PhD, FAAN , School of Nursing, The University of Texas at Austin, Austin, TX



Background: Recent developments in research suggest a link between computer-assisted cognitive rehabilitation and improvements in cognition; however, little is known about methods to achieve participant adherence to a computer brain-training regimen.

Objectives: To explore relationships among participant engagement and communication patterns (type and frequency) between study facilitator and participants.

Methods: Persons with MS who met inclusion criteria and self-reported cognitive concerns (scored >10 on the 20-item Perceived Deficits Questionnaire) were recruited. This 8-week intervention had 2 arms: 1. home-based computer training + weekly in-person group sessions (2 hours/week) [n=8]; or 2. home-based computer training + weekly remote support [n=12]. Those in the group sessions received face-to-face support during sessions while those in the remote support group were contacted weekly via phone/text/email. Participants were instructed to complete 45 minutes of brain-training, 3 days per week for 8 weeks (~ 373 exercises). Data was collected through a study-specific administrative portal, which logged the number of exercises completed by participant ID. The average age of the twenty participants was 49.42 +/- 6.77; 85% of participants were female, 68.4% were White (non-Hispanic) and 68.3% had been diagnosed with MS for over 10 years.

Results: Eighty percent of the participants attended sessions or were reached by phone/email/text ≥ 6 times during the 8-week intervention. The average number of exercises completed by participants was 226.5 +/- 173.3. Three levels of engagement were identified: poor [n=6], moderate [n=10], and high [n=4]. While there was no significant relationship between type of support and level of engagement, there was a moderate/strong correlation between frequency of support and the level of engagement (r=0.495). ANOVA and post-hoc tests confirmed a significant difference in communication frequency between the poor engagement group and the moderate and high engagement groups (p<.01).

Conclusions: Findings from this study indicate that consistent communication, whether in-person or remote, is related to participant engagement up to a certain point; however, great variation in the number of completed exercises existed among participants. This highlights the need for implementing multiple methods of support to maximize intervention engagement.

Acknowledgement: This project was supported by a grant from the NIH, NINR (Grant R01NR014362).