Feasibility and Acceptability of a Smartphone App for Daily Reports of Substance Use and Antiretroviral Therapy Adherence among HIV-Infected Adults

Table 1

Demographic, clinical, substance use, and mobile technology use characteristics.

Measure	(%)
Demographic characteristics
Age [M (SD)]	48.4 (9.49)
Sex
Female	4 (15.4)
Male	20 (76.9)
Transgender	2 (7.6)
Sexual identity
Straight/heterosexual	12 (46.2)
Gay/homosexual	9 (34.6)
Bisexual	3 (11.5)
Other	2 (7.7)
Race
African American	14 (53.8)
White	9 (34.6)
American Indian	1 (3.8)
Other	2 (7.7)
Education
High school or less	15 (57.7)
Some college or more	11 (42.3)
Employment
Not employed	21 (80.8)
Full or part-time	5 (19.2)
Annual income
<20,000	22 (84.6)
≥20,000	4 (15.4)
Clinical characteristics
Undetectable viral load	18 (69.2)
Years since diagnosis [M (SD)]	16.92 (8.65)
Substance use characteristics
Cigarette smoking
Daily	16 (61.5)
<Daily	5 (19.2)
None	5 (19.2)
AUDIT score [M (SD)]	17.08 (6.56)
Hazardous drinker (AUDIT score 8–15)	10 (38.5)
Harmful drinker (AUDIT score 16–19)	3 (11.5)
Probable alcohol dependence (AUDIT score ≥20)	4 (15.4)
Marijuana use (past month)	16 (61.5)
Crack use (past month)	7 (26.9)
Mobile technology and Internet use characteristics
Mobile phone ownership	18 (69.2)
Smartphone ownership	9 (34.6)
Mean number of mobile phone numbers in past six months (SD)	1.50 (2.04)
Average number of texts sent on a daily basis
0–9	9 (50)
10–49	7 (38.9)
50+	2 (11.1)
Using apps on phone in past month	11 (61.1)
Using apps on phone on a daily basis	9 (81.8)
Internet use in past month	21 (80.8)
Mean number of hours per day on Internet	3.30 (2.64)

participants who indicate mobile phone ownership.
participants who report any app use in past month.