Table 1.
Video characteristics, content, and speaker’s characteristics of videos related to Alzheimer’s disease on YouTube.
| Variables | n (%) | |||
| Video Characteristicsa | ||||
| Video Format | ||||
| Informal presentation | 70 (25.8) | |||
| Nonnews interview | 52 (19.2) | |||
| News story and interview | 50 (18.5) | |||
| Formal presentation | 26 (9.6) | |||
| Testimonial | 20 (7.4) | |||
| Public service announcement | 15 (5.5) | |||
| Other | 38 (14.0) | |||
| Video Authorship | ||||
| Nonprofit organization/university | 69 (25.5) | |||
| Layperson | 57 (21.0) | |||
| For-profit organization/company | 51 (18.8) | |||
| News source | 39 (14.4) | |||
| Researcher | 9 (3.3) | |||
| Government agency | 5 (1.8) | |||
| Others | 41 (15.1) | |||
| Video Contenta,b | ||||
| AD symptoms | 83 (30.6) | |||
| Causes of AD | 80 (29.5) | |||
| Treatment | 76 (28.0) | |||
| Protective and risk factors | 50 (18.5) | |||
| AD awareness | 45 (16.6) | |||
| Resources of support | 41 (15.1) | |||
| Caregiving experience | 35 (12.9) | |||
| Quality of life of people with AD | 34 (12.5) | |||
| Screening/diagnosis | 33 (12.2) | |||
| Clinical trials | 32 (11.8) | |||
| Others | 41 (15.1) | |||
| Speaker Characteristicsc | ||||
| Sex | ||||
| Female | 124 (66.3) | |||
| Male | 126 (67.4) | |||
| Age Group | ||||
| Adult (aged 20 years to early 60s) | 164 (87.7) | |||
| Older adult (aged 65 years or older) | 55 (29.4) | |||
| Race | ||||
| White | 168 (89.8) | |||
| African American | 11 (5.9) | |||
| Asian/Pacific Islander | 10 (5.3) | |||
| Other | 12 (6.4) | |||
| Speaker Role | ||||
| Researcher | 72 (38.5) | |||
| Informal caregiver | 43 (23.0) | |||
| Journalist/interviewer | 43 (23.0) | |||
| Healthcare professional | 42 (22.5) | |||
| Organization representative | 39 (20.9) | |||
| Individual with AD | 23 (12.3) | |||
| Actor | 7 (3.7) | |||
| Other | 24 (12.8) | |||
aPercentage was calculated for 271 videos
bSum may not be 100%, because more than one content area was often covered in a video
cOne video may include more than one speaker; each speaker was coded separately for his/her sex, race, age group, and role; percentage was calculated for 187 videos with speakers