Objective Directly observed therapy is recommended worldwide for monitoring tuberculosis (TB) treatment; yet transportation and personnel requirements limit its use. We evaluated the feasibility and acceptability of “Video DOT” (VDOT), which allowed patients to record and transmit medication ingestion videos that were watched remotely by healthcare providers to document adherence. Methods We conducted a single-arm trial among TB patients in San Diego, CA (n=43) and Tijuana, B.C., Mexico (n=9) to represent high- and low-resources settings. Pre/post treatment interviews assessed participant characteristics and experiences. Adherence was defined as the proportion of observed doses to expected doses. Results Mean age was 34 years (range: 18–86), 54% were male, and 77% were non-Caucasian. Mean duration of VDOT use was 5.5 months (range: 1–11). Adherence was similar in San Diego (93%) and Tijuana (96%). Compared to time on in-person DOT, 92% preferred VDOT; 81% thought VDOT was more confidential; 89% never/rarely had problems recording videos; and 100% would recommend VDOT to others. Overall, 7 (13%) participants were returned to in-person DOT and 6 (12%) separate participants had their phone lost, broken or stolen. Conclusions VDOT was feasible and acceptable with high adherence in high- and low-resource settings. Efficacy and cost-effectiveness studies are needed.

We assessed video directly observed therapy (VDOT) for monitoring tuberculosis treatment in 5 health districts in California, USA, to compare adherence between 174 patients using VDOT and 159 patients using in-person directly observed therapy (DOT). Multivariable linear regression analyses identified participant-reported sociodemographics, risk behaviors, and treatment experience associated with adherence. Median participant age was 44 (range 18–87) years; 61% of participants were male. Median fraction of expected doses observed (FEDO) among VDOT participants was higher (93.0% [interquartile range (IQR) 83.4%–97.1%]) than among patients receiving DOT (66.4% [IQR 55.1%–89.3%]). Most participants (96%) would recommend VDOT to others; 90% preferred VDOT over DOT. Lower FEDO was independently associated with US or Mexico birth, shorter VDOT duration, finding VDOT difficult, frequently taking medications while away from home, and having video-recording problems (p<0.05). VDOT cost 32% (range 6%–46%) less than DOT. VDOT was feasible, acceptable, and achieved high adherence at lower cost than DOT.

A recent innovation to help patients adhere to daily tuberculosis (TB) treatment over many months is video (or virtually) observed therapy (VOT). VOT is becoming increasingly feasible as mobile telephone applications and tablet computers become more widely available. Studies of the effectiveness of VOT in improving TB patient outcomes are being conducted.

Background Mobile health (mHealth) interventions have the potential to improve health through patient education and provider engagement while increasing efficiency and lowering costs. This raises the question of whether disparities in access to mobile technology could accentuate disparities in mHealth mediated care. This study addresses whether programs planning to implement mHealth interventions risk creating or perpetuating health disparities based on inequalities in smartphone ownership. Methods Video Directly Observed Therapy (VDOT) is an mHealth intervention for monitoring tuberculosis (TB) treatment adherence through videos sent by patients to their healthcare provider using smartphones. We conducted secondary analyses of data from a single-arm trial of VDOT for TB treatment monitoring by San Diego, San Francisco, and New York City health departments. Baseline and follow-up treatment interviews were used to assess participant smartphone ownership, sociodemographics and TB treatment perceptions. Univariate and multivariable logistic regression analyses were used to identify correlates of smartphone ownership. Results Of the 151 participants enrolled, mean age was 41 years (range: 18–87 years) and 41.1% were female. Participants mostly identified as Asian (45.0%) or Hispanic/Latino (29.8%); 57.8% had at most a high school education. At baseline, 30.4% did not own a smartphone, which was similar across sites. Older participants (adjusted odds ratio [AOR] = 1.09 per year, 95% confidence interval [CI]: 1.05–1.12), males (AOR = 2.86, 95% CI: 1.04–7.86), participants having at most a high school education (AOR = 4.48, 95% CI: 1.57–12.80), and those with an annual income below $10,000 (AOR = 3.06, 95% CI: 1.19, 7.89) had higher odds of not owning a smartphone. Conclusions Approximately one-third of TB patients in three large United States of America (USA) cities lacked smartphones prior to the study. Patients who were older, male, less educated, or had lower annual income were less likely to own smartphones and could be denied access to mHealth interventions if personal smartphone ownership is required.

Background New and innovative methods of delivering interventions are needed to further reduce risky behaviors and increase overall health among persons who inject drugs (PWID). Mobile health (mHealth) interventions have potential for reaching PWID; however, little is known about mobile technology use (MTU) in this population. In this study, the authors identify patterns of MTU and identified factors associated with MTU among a cohort of PWID. Methods Data were collected through a longitudinal cohort study examining drug use, risk behaviors, and health status among PWID in San Diego, California. Latent class analysis (LCA) was used to define patterns of MTU (i.e., making voice calls, text messaging, and mobile Internet access). Multinomial logistic regression was then used to identify demographic characteristics, risk behaviors, and health indicators associated with mobile technology use class. Results In LCA, a 4-class solution fit the data best. Class 1 was defined by low MTU (22%, n = 100); class 2, by PWID who accessed the Internet using a mobile device but did not use voice or text messaging (20%, n = 95); class 3, by primarily voice, text, and connected Internet use (17%, n = 91); and class 4, by high MTU (41%, n = 175). Compared with low MTU, high MTU class members were more likely to be younger, have higher socioeconomic status, sell drugs, and inject methamphetamine daily. Conclusion The majority of PWID in San Diego use mobile technology for voice, text, and/or Internet access, indicating that rapid uptake of mHealth interventions may be possible in this population. However, low ownership and use of mobile technology among older and/or homeless individuals will need to be considered when implementing mHealth interventions among PWID.