This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
The rates of cannabis use continue to increase among adolescents and the current interventions have modest effects and high rates of relapse following treatment. There is increasing evidence for the efficacy of mobile technology–based interventions for adults with substance use disorders, but there is limited study of this technology in adolescents who use cannabis.
The goal of our study was to elucidate elements of an app-based adjunctive intervention for cannabis cessation that resonate with adolescents who use cannabis.
Adolescents, aged between 14 and 17 years, who used cannabis were recruited from San Diego County high schools. Semistructured focus groups (6 total; N=37) were conducted to examine the ways in which participants used smartphones, including the use of any health behavior change apps, as well as to elicit opinions about elements that would promote engagement with an app-based intervention for adolescent cannabis cessation. An iterative coding structure was used with first cycle structural coding, followed by pattern coding.
Themes that emerged from the analysis included (1) youth valued rewards to incentivize the progressive reduction of cannabis use, which included both nontangible rewards that mimic those obtained on social media platforms and prosocial activity-related rewards, (2) having the ability to self-monitor progression, (3) peer social support, (4) privacy and confidentiality discrete logo and name and usernames within the app, and (5) individualizing frequency and content of notifications and reminders.
Integrating content, language, interfaces, delivery systems, and rewards with which adolescents who use cannabis are familiar, engage with on a day-to-day basis, and identify as relevant, may increase treatment engagement and retention for adolescents in substance use treatment. We may increase treatment effectiveness by adapting and individualizing current evidence-based interventions, so that they target the needs of adolescents and are more easily incorporated into their everyday routines.
Cannabis is the most prevalent drug of abuse among adolescents, with nearly 50% of 12th graders, 30% of 10th graders, and 15% of 8th graders reporting lifetime use [
To date, the evidence for efficacious interventions targeting problematic cannabis use, especially in youth, are sparse, with some behavioral interventions demonstrating short-term abstinence during active treatment, but high rates of relapse at follow-up. Specifically, randomized controlled trials of behavioral interventions for adolescent cannabis use show moderate effect sizes posttreatment for motivational enhancement therapy (MET), cognitive behavioral therapy (CBT), family support therapy, case management, and contingency management (CM), with few adolescents maintaining abstinence through follow-up [
Studies suggest that the effectiveness of interventions may be increased by developing selective, highly specific interventions that are presented on interactive platforms and include content addressing specific risk factors in at-risk youth [
Although, adolescents spend a significant amount of time using technology, are expert users by virtue of exposure and use from childhood, and interactive platforms have been shown to be effective for treatment delivery in youth [
The goal of this study is to increase our understanding of adolescent cannabis use behaviors in the context of near universal availability of mobile, wireless, and wearable technology, with the overall aim of developing a user-informed mHealth intervention for high-risk cannabis-using adolescents engaged in outpatient substance use treatment. Specifically, we aimed to (1) examine adolescent use of various mobile platforms (ie, short message service [SMS] text, apps), social media, and wearable devices to determine the use of mobile technologies as sources of health and substance use related information, and the effect on risk-taking behaviors and behavioral change, and (2) examine salience of components of existing behavioral interventions for youth.
We employed a stratified purposeful sampling strategy. A total of 37 adolescents aged between 14 and 18 years of age were recruited from high schools and substance use treatment centers in San Diego County, and San Diego Unified School District (SDUSD), which serves >130,000 students and is the second largest district in California. The racial/ethnic makeup of the students in the SDUSD is 46.5% Hispanic, 23.4% Caucasian, and 10.2% African American. Eligibility criteria for the focus groups included being 14 to 18 years of age, owning a smartphone and/or having internet access, speaking fluent English, and cannabis use one or more times in the past 30 days. If eligible, adolescents were invited to a focus group held either on their school campus, in the outpatient treatment center, or in the lab.
A total of 37 adolescents were enrolled in one of 6 focus groups, as that was the number needed to reach saturation (themes were repeated, no new information obtained) [
Focus groups were conducted in English and followed a semistructured interview guide developed by the study principal investigator, a child and adolescent psychiatrist. Participants answered questions regarding characteristics of their smartphones, how they use their phones, what they use them for (including apps downloaded and native apps), time spent on their phones, use of related mobile technologies such as activity trackers, and use of mobile technology and Web-based platforms for accessing, monitoring, and/or changing health or substance related behaviors. Participants also worked as a group to design, and arrive at a consensus among group members, a mock app-based cannabis intervention for cannabis-using adolescents. They were prompted to discuss aspects of interest, including the following:
Content
Health-related content for in-app messages and/or push notifications
Access to psychoeducation and prior measured personal data (eg, cannabis use/treatment adherence)
Static (same intervention for all users) versus dynamic (individualized/tailored) messaging
Theory: learning (temporal feedback on individual level data to enhance engagement and behavior change) and social cognitive (increased self-efficacy with goal setting and defined expectations, positively reinforce behavior change)
Usage
Frequency of content delivery (exposure) via prompts, cue-related, global positioning system (GPS) location triggered
Format of content: text, video, pictures, and/or links to external sources
Duration: active (brief, extended) with or without continuing care (time limited vs indefinite access)
Contact
Clinicians via SMS text and Skype/video for confirmation of abstinence at routine intervals and in response to psychiatric or high-risk behavioral concerns
Peer supports via in-app social media
Accessibility
Navigational features
Design of user interface
Environments (feasibility of continuous monitoring/access to intervention across academic, social, and familial settings).
Participants were administered 4 self-report questionnaires: the Customary Drinking and Drug Use Record [
Participant characteristics.
Demographic information | Values | ||
|
|
||
|
Female | 22 | |
|
Male | 15 | |
Age (years), mean (SD) | 16.86 (0.82) | ||
|
|
||
|
White/Caucasian | 32 | |
|
Black/African American | 2 | |
|
Not reported | 3 | |
|
|
||
|
Hispanic/Latino | 29 | |
|
Not reported | 1 | |
|
|
||
|
Phone attachment index (1-10) | 6.97 (2.00) | |
|
Number of days cannabis used in past 30 days (n=24) | 3.04 (5.20) |
Qualitative software, ATLAS.ti (Scientific Software Development GmbH) was used to aid in data management for thematic analyses of transcripts and coding [
Group participants spoke about their use of various smartphone apps, including mHealth apps aimed at changing health behaviors such as sleep or nutrition (
Smartphone use: health behavior change technology.
Health behavior change devices and apps | Quotes | ||
Use of wearable devices | “I have the Apple watch that I use for running too. And the Fitbit.”; “I have an Apple watch but I hardly ever go running.”; “[I use] a watch...to track my steps.” | ||
Use of activity tracking apps | “I used to use the health app that [iPhone] comes with...See how much I’ve walked and stuff.”; “It’s called Lifesum...it tracks your calories for the day...I’ve seen some other people using and I was like, ‘that’s pretty cool.’” | ||
|
|||
|
Positive feedback | “All of those big numbers.” | |
Physical training | “Like [if] I’m going to train...”; “[Using a wearable device] depends if I’m doing a sport.” | ||
Interface | “I just liked the way it looked, the layout...when you go on there, they ask you a whole bunch of questions. And then they give you a certain amount of calories for your weight and your height and like your age. And then you put in what you eat throughout the day...And then it’s like a rainbow at the top. And it’s like a sunset at the top and then water—I don't know. it’s just a cool setup, I guess.” | ||
|
|||
|
Pressure to workout | “Because it’s too much exercise...because I would want to get big numbers.” | |
Uncool | “It’s sort of just inherently uncool to me.” | ||
Fear of losing device | “I feel like I’d lose it.” | ||
|
|||
|
Inconvenient/no new insight | “[Sleep app] I don’t like to have my phone by my bed because it lights up and stuff. It had to be like pretty close to you for it to track...I mean like it was [useful]. It told me if I was sleeping good or not. But I’m also a really good sleeper so it always was like deep sleep and I’m like okay.” | |
Not necessary | “I just didn’t feel the need to have it. It was something to do.” | ||
Lost interest | “Well, at first, I would read them because it would just pop up, but then after like I would read them and they would just keep popping up and I wouldn’t care and I would just swipe up. So, I was like oh I didn't even read them. So, I deleted it.” | ||
Perceptions of those who use cannabis | “Fitbit is like a preppy thing. It’s the kids that would be willingly spend $100 for something a phone app can do.”; “I’m just like oh my God, what a nerd. I just do not want to be associated with someone who is like, ‘Oh, I’ve got to get my steps in today.’”; “It’s a little obsessive to me.”; “At least they’re motivated.” |
During the group discussion, the following topics were considered: (1) content, (2) usage, (3) duration, (4) contact, and (5) accessibility. Themes from each area were derived through coding of focus group transcripts and are summarized in the following tables. The most prominent themes among participants were rewards, privacy, self-monitoring, peer social support, and notifications.
Participants discussed creating a reward system for cannabis use cessation (
Preferences and design recommendations for an mHealth app for cannabis cessation: reward system.
Rewards | Quotes | ||
|
|||
|
In-app rewards | “I don’t think it has to be anything special. You know how like on Snapchat you get the random trophies...No one really cares about them but it’s kind of like I check it. And I’m like oh what did I get? What have I done?”; “...funny pictures.”; “You get cooler stickers.”; “It’s like every time you say you ‘no’ [to using marijuana, you] get a coin...like a game...that you can customize.” | |
Gift card/prepaid debit card | “Yeah, a gift card to Starbucks. Something that you can district you.”; “You can’t go to a [drug dealer] with a credit card.”; “[Gift cards for] Wal-Mart. Target. Regular shit.” | ||
Cash | “Money...Ten bucks or fifteen. Twenty.” | ||
Alternative activities | “I feel like with the app you guys should put in like events are happening around us. So it takes our mind off. You know, if we want to go somewhere else and do something it will take our mind off of wanting to smoke.” | ||
Coupons | “Maybe even tying in stuff from like Groupon where it gives you discounts to places.”; “I like how they did like coupons or I don't know just something small.”; “Or a coupon for like iTunes or something.”; “...you can achieve a discount.” | ||
|
“You should incorporate like the streaks to your app...Streaks make everyone want to have to do, and on Snapchat they have a little hourglass if you’re about to lose your streak. And once you see the hourglass, you’re like, oh you better snap them. It becomes really important.”; “[No marijuana use] then you just get a sticker or something or a streak to like whatever.”; “Streaks make everyone so much more into it.” | ||
|
|||
|
Contingent reward for staying |
“Depending on how many days you stay clean you get certain rewards. And if you report that you did smoke then it will deduct points or deduct rewards.”; “Send you a notification like hey, you’ve been clean for a week. This is what you get, this amount of points. And two weeks you can get like double the points.”; “It probably goes up every month...Every month you stay clean.”; “...if you say two weeks in the app that you’re clean and you haven’t smoked like you could get one...You should get rewarded.” | |
Frequency needed to stay motivated | “Once a week.”; “Every day.”; “I feel like a month is good.”; “Yeah, you guys could do one every week, a different one every week and you get a little bit every day.” |
Several issues were raised about the protection of users’ private information. Privacy considerations are presented in
Attitudes toward the use of location tracking in the app were divided. Supporters of location-based features liked the prospect of regional activity recommendations and a localized social support system. Dissenters argued that privacy was more important than local connection and they felt uncomfortable being monitored. A consensus was reached that the app should allow users to control location permissions.
Preferences and design recommendations for an mHealth app for cannabis cessation: privacy features.
Privacy | Quotes |
Connection to other social media accounts | “I definitely think it shouldn’t post [to] Facebook, ‘I haven’t smoked in two months!’”; “And a lot of the times, when you join an app they’re like find your friends on here. And they download your friends from your contacts. I don't think you should do that.”; “You definitely shzould be able to connect through Twitter, Facebook.” |
Concern about global positioning system (GPS) tracking | “It’s just weird to know that somebody could be tracking you wherever you are.”; “Yeah, you could be at like at a club and be like where the fuck are you at?...You work for the FBI or what?”; “I wouldn’t want the GPS for privacy reasons, you know. Some people are weird.” |
Anonymous user account | “Pick a user name...So, you wouldn’t have to use your actual name.”; “I think a user name would be the best. Just somehow it doesn’t track back to actually you, never knowing actually who it is.”; “Yeah, it has to totally be private because if a person sees you are on there and she’s like why is she on there, oh, they’ll tell people about what you’re doing.”; “I think user names, but there should be like one where if you want a person to know who you are, [you could].” |
Passcode/fingerprint access | “Like when you open your phone, you know, like how there’s a password, you can have a password for the app.”; “You can use your fingerprint to open it.”; “That would be kind of gnarly to put your fingerprint for something you want to stop smoking weed...More like a password. Something you remember like a four digit.” |
Discreet app name and logo | “You’d want it to be kind of discreet because a lot of kids have their parents check their apps they download.”; “The logo on the app shouldn’t be a marijuana leaf...it should be a discreet logo if your parents look at your phone, they don’t just see, like—and the name shouldn’t be something like, ‘I’m quitting marijuana.’” |
Participants suggested incorporating a feature for users to track their cannabis use. Various tools for collecting user information were proposed, including pop-up prompts and open-ended journal entries (
A few group members voiced a need for abstinence verification. Solutions included in-person urine screening, remote drug tests, or providing an electronic testing device that directly attaches to the user’s smartphone.
Preferences and design recommendations for an mHealth app for cannabis cessation: self-monitoring cannabis use.
Self-monitoring | Quotes |
Tracking marijuana use | “I think but the main goal is just to have progress, it’s just to know like you’re staying clean. So, I feel like it’s recording if you’ve done it and...like whenever you’re pressured and you said no, because those are skills to build.”; “I think if you did smoke one day it should ask you questions like how you felt differently than when you did.”; “Or even how often you wanted to smoke but didn’t...When it used to be like oh I wanted to smoke three times, but now I only wanted to smoke once. Like either way it’s progress.” |
Journaling | “...you need to know how to...when to say no, and when is the right time to do something.”; “You have like a notepad, where you can write like this thing happened on this certain day and that’s why I did it...and what I could learn from that and what could I change for the next time something that could happen.” |
Personalized feedback | “When you put the questions like how do you feel when you smoke? And they give you a response you could be like...or you could feel that way if you do this? Like I feel relaxed, like stressed out. And then you can be like ‘get a soccer ball and you’ll feel relaxed.’”; “Yeah, maybe put it in there so they could see like your ratio of in a month or like a year like how many times did you smoke? And if it’s affecting your health or anything.” |
Verifying abstinence | “Send in some stuff. You’ve got to send in some, I don’t know, some pee.”; “Or like at the end have a meeting with them...”; “Why not that little detector like the alcohol detector? You get the app and then they send it to you.” |
Providing outside professional resources | “Maybe the app could provide professional help...Like really, really good resources like therapists that they offer or something or that they know of around where they’re at.”; “You know how some apps have the help, you know, like if they really want help. You put that under like oh here’s some places that you can go to get help or something like that...A hotline.”; “If they don’t want to stop or something, that’s when the hotline could come in. And then you like offer that talk. And then you talk to the person. And then if you see no hope then you tell them to talk to somebody else. That’s when you offer the best help.” |
Every group proposed a social network type of messaging to anonymously connect with other app users who were actively trying to stop cannabis use. There was overall approval for the inclusion of social contact with other app users, with precautions taken to protect anonymity and location disclosure. Participants felt that including a social component served as a means of peer encouragement and distraction when cravings arise. Social support features are described in
Participants expressed a desire to have control over the frequency and content of the app notifications (
Preferences and design recommendations for an mHealth app for cannabis cessation: peer social support.
Peer social support | Quotes |
Talking to other app users | “Being able to talk to someone else maybe. But create a user name and you don’t have to use your real name. That way if there’s two people who are trying to quit, they can get together and like text each other.”; “Part of the reason a lot of people don’t stop is because they have a certain group of friends that are doing it. So, if they met someone else who was trying to stop, they would be like oh let’s go do this instead of smoking with other friends. Create new friendships...Learn how to do other stuff with new people.”; “There should be a forum for everyone to be able to join in on. And then separately it’s like users, you can just click on them. And then if they have the option of being able to talk to other people because they want then okay, they should be able to.”; “I think it would be really good to talk anonymously to teenagers, like, about trying to quit...Or you can put you in like a random chat...”; “And maybe you can join, like, a group? Like, a group so if you don’t want to be with the others...” |
Location-based chats | “I think it would actually be pretty cool if we have like location-wise, like, people around you, like in your city, it would even be pretty interesting to add to that.”; “Let’s just say San Diego has its own group chat and then there’s, like, L.A. and there’s, like, basically the big, major cities.”; “There should be a thing like these people are in your location type of thing like when you have your location on...like these people who are also using the app are around you.” |
Preferences and design recommendations for an mHealth app for cannabis cessation: notifications.
Notifications | Quotes | ||
|
|
||
|
Frequency | “[...once a day would be the most frequent?] Or two times a day maybe.”; “Maybe three. When you wake up, before you go to sleep and the middle of the day.”; “I don’t think it should be like constant reminder of like you’ve been clean for this amount because that will keep you thinking of like still weed. So, it should have it probably once every couple of weeks. And then probably have other motivational things.” | |
Timing | “Like when you’re out partying or something like that. You know, you’re just in the moment of feeling good. Sometimes people smoke when they’re in the vibe too...Or maybe get more notifications at that point on.” | ||
User control | “There should be a setting where you can like say you can press I want to check my own notifications. Or I want notifications every two weeks or like every day. Something like that.”; “[You want control over the content of the notifications…] And how often you get them.” | ||
|
|
||
|
Reminders of progress | “It would be kind of cool if every three or so days or if it got like a long time like every five like how many days you’re clean because it’s kind of like a reminder. Like okay I’m clean I can’t mess this up, I need to keep on this...it’s three days. Let’s get to five.”; “There should be two different types of reminders and one of them is just to motivate you not to. And then the other one is just check in for tonight and it reminds you at night.” | |
User control | “I would want independent control...cause I would know I could change it if I wanted to.”; “They should also have the option of what kind of information the notification they're giving out. So, for example, some people probably don’t...wouldn’t want for the app to be telling them how bad it is to smoke or something. But some others would find it more motivational too, for the app to tell you oh, this is bad for you because of this or whatever.”; “Maybe for inspirational...Maybe it could be designed into how you want it be. Because reminder quotes people will find irrelevant. So, when you’re getting an inspirational quote you can kind of design it to how you want it to be.” | ||
Location-based notifications | “You’ll get a notification like oh there’s a concert happening in the park. Or like oh this museum is not charging today. Something like that. It all depends on where you’re at. So it’s around your surroundings.” |
We queried adolescents who use cannabis about specific aspects of a mobile technology–based intervention, including content, duration, user interface, accessibility, support (peer and clinician), and current/past use of health behavior change apps, to inform development of a cannabis cessation intervention that would increase treatment engagement by youth in substance use treatment.
Thetwomost common themes in intervention development that were expressed by participants were (1) monitoring reduction of cannabis use over time and (2) providing rewards for successful reduction and cessation. Adolescents indicated that integration of CM would be appealing. Previous research suggests that CM can improve effectiveness of substance use treatment for youth and increase engagement in treatment [
Privacy was an interesting theme that emerged in an isolated context, but also within discussion of other content areas. When asked directly about privacy and others’ potential to have access to participants’ data, knowledge of their involvement in the intervention, or location-based information available to researchers/clinicians for intervention delivery, participants almost uniformly had negative views. However, with regard to rewards and peer resources, participants voluntarily and spontaneously proposed offering personal information and inclusion of location-based services to gain psychosocial and other intangible rewards, as well as tangible rewards.
The theme of individualizing the app was also discussed in other domains. Individualization of mHealth interventions has been identified in previous studies as important to high-risk adolescents seeking treatment [
Themes identified by adolescents who use cannabis, the target population for this app-based cannabis use intervention, are consistent with research suggesting that intervention efficacy may be increased by developing selective, highly specific interventions incorporating content that addresses risk factors in at-risk youth and are presented on interactive platforms [
There are several limitations to this study. As we sampled adolescents who use cannabis from one city in Southern California, it was not representative of the broader adolescent population. In addition, we had a low number of racial and ethnic minorities in our sample, further limiting generalizability. With regard to uses of mobile technology, we did not query adolescents about alternate platforms for intervention other than an app delivered via smartphone. Although the literature shows that adolescents’ primary mode of mobile technology use are smartphones, we did not query participants about use or acceptability of other types of technologies. Finally, we did not query youth on general methods of access to the app, as the goal is to integrate this into extant treatment paradigms for users engaged in substance use treatment. Despite these limitations, the qualitative approach allowed us to further probe the complexities and context of components of intervention development to understand adolescent technology use, and motivations for appeal of component content, more in-depth.
This app, incorporating mobile CBT, is being developed as an adjunct to TAU for adolescent cannabis users aged between 13 and 18 years who have 9 to 12 weeks of substance use treatment remaining at the time of study entry (to ensure we enroll youth before TAU impacts substance use). Participants will be recruited from local adolescent substance use treatment clinics. The youth clinics provide case management and individual and group counseling intwotracks, outpatient drug-free groups (meet daily, Monday-Friday for 1.5 hours after school) and day care habilitative groups (intensive daily, Monday-Friday, half-day program), with adjunctive family therapy, parent and youth support meetings, and aftercare counseling, as needed. Random urine toxicology is done to confirm abstinence. Youth are enrolled in treatment for 3 months, with 1 month added to treatment length for each positive urine toxicology screen. An active cohort (TAU+biosensor) will be matched by primary substance of use to a cohort receiving TAU alone (matched comparison cohort data collected through electronic medical record [EMR]/chart review) in an external control design. We will assess and compare groups on the primary outcome of point prevalence abstinence (total number throughout treatment and number of consecutive weeks) for primary substance of use (substance for which the youth meets criteria for SUD), and secondary outcome of point prevalence abstinence for total number of substances used. These outcomes will be collected for the TAU group by reviewing their medical records. Collecting primary outcome comparison data through EMR/chart review will provide us with an important opportunity to identify systems-related considerations of cross-database information sharing, privacy, confidentiality, and other issues that must be resolved before launching a larger-scale study, in which obtaining collateral EMR/chart data will be essential to supporting treatment outcomes research trials.
Adolescent cannabis use initiation is linked to negative long-term health effects [
We have presented novel end user–informed data about the content, format, structure, privacy, and accessibility of an app-based substance use treatment for adolescents that may inform more successful interventions among this high-risk population. In this study, the sample of adolescents who use cannabis indicated a desire for an individualized app, with highly visual components consistent with apps that they already use and escalating rewards associated with individual progress. Furthermore, although response to use of geolocation services in the context of discussion of privacy was mixed, adolescents endorsed approval of sharing GPS information in the context of discussion pertaining to individualized rewards and connecting with peers. Identifying and developing intervention content on platforms highly utilized by target population, incorporating skill development (eg, saying no, coping with negative feeling, engagement in prosocial activities) via novel technological means, and integrating salient environmental rewards may increase intervention efficacy, and thus may improve substance use treatment outcomes. Further study of ethical and privacy implications of novel technological approaches are needed in this population. However, methods of ensuring that data are transmitted and stored in a manner that complies with Health Insurance Portability and Accountability (HIPAA) requirements are possible by ensuring that (1) all information from mobile to server will be via https/SSL (secure sockets layer), (2) stored data are encrypted and deleted when no longer required, (3) servers on the cloud are HIPAA compliant and regularly patched with security updates, stored in a secure facility, and (4) provision of a clear privacy policy and (5) strong passwords with expiration periods are mandated.
cognitive behavioral therapy
contingency management
cannabis use disorder
electronic medical record
global positioning system
Health Insurance Portability and Accountability
motivational enhancement therapy
mobile health
San Diego Unified School District
short message service
treatment-as-usual
Susan Tapert, PhD; Suchitra Krishnan-Sarin, PhD; Dana Cavallo, PhD; Alexander Chang, MD; Emily Springfield, BA; 5K12 DA000357-17 (PIs: KB, EB); R25DA035163 (PIs: Carmen Masson, PhD, James Sorensen, PhD; subaward PI: KB).
This work was supported by the National Institutes on Drug Abuse—American Academy of Child and Adolescent Psychiatry Physician Scientist Program in Substance Abuse K12 Award (5K12 DA00035717) awarded to KB.
None declared.