Managing addictions via mobile applications: a smartphone app to assist management of cannabis use

Transcription

1 Managing addictions via mobile applications: a smartphone app to assist management of cannabis use Jan Copeland (PhD) Lisa Gibson Sally Rooke (PhD) UNSW Medicine

2 Rationale 10.2% of Australians used cannabis in 2013 and use is again increasing after a decade of reduction; 1 in 5 recent cannabis users use weekly & 13% are daily users Rates of specialist treatment seeking are increasing but secondary prevention largely ignored The Centre has developed successful web and telephone delivered brief interventions for cannabis use disorders but the majority of RCT participants were dependent and had used >20 years The authors have no conflict of interest to declare

3 Rationale Potentially well-suited for delivering advice and information to cannabis users: Very popular greater reach Convenient and accessible (always at hand and turned on) Private delivery via mobile phone avoids stigma of face-toface treatment Allow users to make thoughtful, evidence-based decision about making changes in their cannabis use

4 Rationale The vast majority of cannabis-related apps are to facilitate sale and use with only one related to addiction & treatment (Ramo et al., 2015 JMIR) The market for ME-Health services has now entered the commercialization phase and will reach $ 26 billion globally by 2017 (research2guidance, 2013) So far, the majority of studies have looked at the usability of health-related apps (acceptance, usability, user satisfaction)

5 Apps evidence? Very few studies have looked at the effectiveness of apps in terms of behaviour change ME-Health App for diabetes management: study found app use improved blood glucose monitoring significantly but had no effect on glycaemic control (Cafazzo, 2012)

6 An ME-Health App for Cannabis Users? There are currently no evidence-based apps for cannabis users aimed at supporting change Iterative development and pilot testing: Would cannabis users be interested in using an ME-Health app to evaluate and/or reduce/quit their use? What type of feedback and features would be of most interested? How would it impact patterns of cannabis use and related problems

7 Developing an evidence-based smartphone app for the selfmanagement of cannabis use (Norberg et al, 2014)

8 Modules based on principles of CBT and MET: 1.ASSESS: assessment and feedback 2.PLAN: goal setting and planning for change 3.TRACK: monitoring progress 4.TIPS: strategies for success 5.Joint Effort: quit with a buddy (post testing)

9 The current study AIM DESIGN To test a newly developed smartphone app designed to assist people to quit or reduce their cannabis use Single-group repeated measures study HYPOTHESI S Participants using the app would show significant reductions in their cannabis use and related problems after 4 weeks use of the app and at 1month follow-up

10 The current study PARTICIPANT S PROCEDURE 16 years+ Owned an iphone with internet access Reported past month cannabis use Expressed a desire to quit or reduce use Participants used the app for 4 weeks Online assessments were conducted at: Baseline Post-app use (4 weeks) 1 month follow-up

11 The current study OUTCOME MEASURES Primary Cannabis use (quantity and frequency) Cannabis dependence (SDS) Cannabis-related problems (CPQ) Mental health (DASS-21) Self-efficacy (DTCQ-8) App usage and usability Secondary Readiness to change; coping; emotional distress; and disability.

12 Participants n=111 Table 1: Selected participant characteristics (n = 111): Mean Age 26.7 (SD = 7.8) % Male 64 % Married 25 % Employed (full or part-time) 76 % Completed high school or higher education 89 % Born in Australia 79 Mean quit attempts 2.3 (SD = 2.1) % Received treatment 11

13 Results Measure Cannabis use days (past month) Cannabis dependence (SDS) Cannabis-related problems (CPQ) Baseline Mean (SD) Post-App (n = 94) Mean (SD) Follow-up (n = 76) Mean (SD) 23.0 (8.8) 18.6 (10.5)* 13.4 (11.7)* 5.8 (3.3) 5.4 (3.8) 4.3 (3.7)* 7.1 (3.5) 4.8 (3.7)* 5.0 (4.3)* DASS-21 total score 16.8 (9.2) 14.2 (11.5)* 13.2 (11.4)* Self-efficacy (DTCQ-8) 328 (171) 368 (197)* 391 (203)*

14 Results Baseline to post-aptt, p <.001 Baseline to FU p <.001 Baseline to FU p =.001

15 Results Baseline to post-aptt p <.001 Baseline to FU p <.001 Baseline to post-aptt p =.002 Baseline to FU p =.002

16 Results Baseline to post-aptt, p <.001 Baseline to FU, p <.001

17 Feedback: usability & helpfulness APTT was rated by participants as somewhat helpful 41% would prefer an app over face-toface treatment Users were fairly satisfied with the quality of APTT

18 Feedback: improvements Feedback and notifications about progress Improved functionality Increased interactivity Personalised facts, tips, and information

19 Future directions The original 4 part Assess Plan Track & Tips version tested had an added module in final development of Joint Effort Quit with a Buddy Now available free of charge at Apple store and android (but not advertised) Seeking to conduct a RCT of basic versus full versions of the app

20 Contact information