Introduction
Smartphone apps to support individuals in recovery from substance use disorders (SUDs) are increasingly available. Although many people with SUDs express interest in recovery support apps, few try them or use them long-term. Strategies like gamification and contingency management are increasingly being considered to sustain engagement. This study sought to describe features of a recovery support app called the Addiction version of the Comprehensive Health Enhancement Support System (A-CHESS) that are most used by individuals in SUD recovery and what makes individuals more likely to use these apps.
Methods
A total of 202 people with A-CHESS accounts completed an online survey assessing their experiences using A-CHESS between April and June 2021. We described app features reported to be most beneficial for managing anxiety, loneliness, and isolation during COVID-19; reasons for not using A-CHESS; and suggested app features for future recovery support apps.
Results
Respondents had a mean age of 41 years, 85% were White, and 61% were female. Respondents reported that app features related to messaging (ie, open discussion boards and private messaging) and informational or motivational resources were the most useful for managing isolation, anxiety, and loneliness. Reasons for not using A-CHESS were not knowing how to use the app and the app not being part of a personalized treatment plan. The most common suggested components for future apps were rewards for meeting goals and a support meeting locator.
Conclusions
Ensuring that health apps are intuitive and include features that appeal to patients and educating patients about features apps already include that help them meet goals may enhance engagement with recovery apps.
Key Words: substance use, mobile health, contingency management, substance use disorder, recovery app
Smartphone apps to support substance use disorder (SUD) treatment and recovery are becoming increasingly used, as they are a relatively low-cost and effective supplemental resource.1–3 In one randomized controlled trial of a smartphone app to support recovery from alcohol use disorder, those randomized to use a recovery support app had significantly fewer drinking days than a group not assigned to use the app.4 Although patients report high interest in using health apps to support their mental health and/or recovery from SUDs, only 10% have actually tried using one.2 Given that the COVID-19 pandemic has exacerbated mental illness and SUDs; increased worry, stress, and loneliness; and decreased access to some treatments, health apps accessible anywhere and at any time may be an especially useful tool.5–9
Across all types of health apps, use tends to significantly decline over time. In one study, app utilization dropped from 69% 1 month postdownload to 32% at 3 months postdownload, despite patients rating the app as useful to them and feasible to use.3 This engagement drop-off is extremely common and is often due to issues like hidden costs in the app or loss of interest.1 Other common concerns that keep individuals from engaging with apps long-term include concerns over data privacy and lack of patient belief in or understanding of the efficacy of health apps to provide support.2
Several strategies may help sustain engagement. One strategy, contingency management, provides rewards (eg, small amounts of money paid in cash or gift cards) to individuals for meeting treatment or app use goals.10 Prior research supports that participants who received contingency management-based treatments are more likely to maintain abstinence from using long-term than are those in other types of comprehensive therapies11 and are more likely to have higher levels of treatment attendance.10 In the context of smartphone apps, contingency management features have also been associated with higher rates of abstinence from smoking and alcohol use as well as with sustained app engagement.12,13 Another strategy to support sustained app engagement is gamification, or adding elements of game playing, like scoring points and competing with others. Previous research has shown that gamification features like adaptive goal setting, receiving rewards like badges or higher levels, and having opportunities for competition, both against personal bests and against others, are particularly useful.14,15 Most of these features are already used in health apps but may be made more engaging through gamification.16–18 Incorporating these strategies in SUD recovery support apps may be a promising avenue for increasing sustained use of effective apps and patient satisfaction.
The study reported here describes the results of a survey of respondents who signed up for a SUD recovery support app called the Addiction version of the Comprehensive Health Enhancement Support System (A-CHESS). A-CHESS allows users to access resources, support, and tracking for their recovery; connect with other app users through discussion boards and private messaging; and connect with providers from their treatment clinic. We surveyed app users to learn more about their views on the benefits of A-CHESS, how A-CHESS could be improved, and how the COVID-19 pandemic affected their recovery and app use.
METHODS
Respondents
Individuals using 2 versions of the A-CHESS recovery support app, RISE Iowa and Connections, were invited to complete an online self-administered survey between April and June 2021. A total of 610 individuals who had signed up for an account on RISE Iowa and 905 individuals who had signed up for an account on Connections were invited to complete the survey by email. Connections respondents had additionally shared their phone number and received invitations to participate by text message. To be invited to participate, individuals needed to have created their account on the app at least 2 weeks prior. This analysis includes 202 individuals who completed the survey (66 from RISE, 136 from Connections). This study was reviewed and approved by Advarra's Institutional Review Board (protocol number, 2018-0997). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist was completed for this article.19
Respondents using the RISE Iowa version of A-CHESS were participants in an ongoing implementation trial of A-CHESS occurring in SUD treatment agencies in Iowa that began in September 2019. The parent trial is investigating how external coaching and the NIATx process improvement model can help SUD treatment organizations in Iowa incorporate A-CHESS into treatment (NCT03954184).20 As an implementation trial, treatment providers at each treatment site received training from the research team on the capabilities of the RISE Iowa app. Treatment providers then offered RISE Iowa to patients they deemed may benefit from RISE as a supplement to their ongoing SUD treatment. Initial data suggest that some providers targeted patients who they thought would be more likely to use it, like younger patients or those with internet access, whereas other providers reported offering the app to most or all patients.21 Providers also had discretion in the types of introductory training they provided to their patients about the app. For example, providers reported introducing the app in both group and individual treatment settings and often provided a brief overview of the app and its features to patients.21 Additional funding, through a Helping to End Addiction Long-term supplement, in addition to the parent implementation trial, was received to examine the impact of COVID-19 on patients of participating organizations who had signed up for an A-CHESS account about their experiences with SUD treatment during the COVID-19 pandemic.
Respondents using the Connections app were recruited from 2 sample populations. The majority were involved in a study testing whether A-CHESS was beneficial among criminal justice-referred clients (n = 111),22 and an additional n = 25 were members of the general public who downloaded the Connections app through the Addiction Policy Forum website.23 Individuals using the Connections app received training on use of the app via a provided training manual describing features of the app and how to use it, a video describing parts of the app, and access to a counselor, peer, or social worker who they could ask questions to if needed. Prompts were also regularly posted on the message board of the app explaining how to use specific features. After providing informed consent and completing the survey, respondents received a $25 gift card by email for their participation.
Measures
We determined whether respondents had used A-CHESS in the month before responding to the survey based on app utilization data logged through A-CHESS. Additional measures used for learning more about those who used and did not use A-CHESS are presented in tables hereinafter.
Measures to assess benefits of A-CHESS and reasons for not using it are presented in Supplementary Table 1, http://links.lww.com/JAM/A407.
Demographic measures are presented in Supplementary Table 2, http://links.lww.com/JAM/A407. Housing status, relationship status, employment, education level, criminal justice system involvement, and technology access were made into binary variables for analysis purposes.
Analysis
After describing the sample, sociodemographic differences between those who used A-CHESS in the past month and those who did not were examined using χ2 tests. Benefits of A-CHESS and reasons for not using A-CHESS were examined descriptively among those who had used and who had not used A-CHESS, respectively. Desired functions of A-CHESS were examined among all respondents. Finally, sociodemographic differences between those who chose a desired function of A-CHESS versus those who did not were analyzed for the top two desired app functions to examine whether any specific subpopulations may desire certain functions in A-CHESS. Analyses were completed in SPSS.
RESULTS
Sociodemographic Characteristics
Survey respondents had a mean age of 41 years (SD, 11.1 years; range, 21–72 years), were primarily White (83.6%) and primarily self-identified as female (61.4%, Table 1). No respondents chose a gender identity other than female or male. Nearly half (44.6%) of the total sample had a history of involvement with the criminal justice system in the past 6 months, with 47.8% of the respondents from the Connections sample and 37.9% of the RISE Iowa sample reporting this involvement. Overall, 167 respondents (82.7%) reported having a computer with internet access at the place where they lived. Nearly all (n = 197 [97.5%]) reported having a smartphone in the 30 days before completing the survey. The only difference between those who had used versus those who had not used A-CHESS in the past 30 days was that those who had not used A-CHESS were significantly more likely to be married or a member of an unmarried couple (25% vs 45%, P = 0.009).
TABLE 1.
Sociodemographic Characteristics of Survey Respondents and Comparisons Between A-CHESS Users and Nonusers
| Variable | n (%) | Used A-CHESS, n (%) | Did Not Use A-CHESS, n (%) | P |
|---|---|---|---|---|
| Total | 202 (100) | 68 (33.7) | 134 (66.3) | |
| Age* | 0.76 | |||
| Mean age (41 y or younger) | 114 (57.6) | 39 (59.1) | 75 (56.8) | |
| Above mean age (≥42 y) | 84 (42.4) | 27 (40.9) | 57 (43.2) | |
| Sex | 0.13 | |||
| Female | 124 (61.4) | 47 (69.1) | 77 (57.5) | |
| Male | 78 (38.6) | 21 (30.9) | 57 (42.5) | |
| Race† | 0.96 | |||
| White | 168 (83.6) | 57 (83.8) | 111 (83.5) | |
| Black | 10 (5.0) | 3 (4.4) | 7 (5.2) | |
| Any other race | 23 (11.4) | 8 (11.8) | 15 (11.3) | |
| Income‡ | 0.16 | |||
| Less than $25,000/year | 77 (42.8) | 31 (50.0) | 46 (39.0) | |
| More than $25,001/year | 103 (57.2) | 31 (50.0) | 72 (61.0) | |
| Income change during COVID-19 pandemic§ | 0.43 | |||
| Income is less since start of pandemic | 86 (47.0) | 28 (43.8) | 58 (48.7) | |
| Income is about the same | 71 (38.8) | 24 (37.5) | 47 (39.5) | |
| Income is more since start of pandemic | 26 (14.2) | 12 (18.7) | 14 (11.8) | |
| High school diploma or beyond education level∥ | 171 (93.4) | 59 (92.2) | 112 (94.1) | 0.27 |
| Married or member of an unmarried couple | 77 (38.1) | 17 (25.0) | 60 (44.8) | <0.01 |
| Live in a house, townhouse, or apartment I rent or own | 132 (65.3) | 44 (64.7) | 88 (65.7) | 0.89 |
| Employed full time, part time, or self-employed¶ | 123 (61.2) | 37 (54.4) | 86 (64.7) | 0.17 |
| Have computer with internet access where I live | 167 (82.7) | 56 (82.4) | 111 (82.8) | 0.93 |
| Have a smartphone | 197 (97.5) | 66 (97.1) | 131 (97.8) | 1.00 |
*Four respondents did not answer, giving a total n = 198 for this question.
†One respondent did not answer, giving a total n = 201 for this question.
‡Twenty-two respondents did not answer, giving a total n = 180 for this question.
§Nineteen respondents did not answer, giving a total n = 183 for this question.
∥Nineteen respondents did not answer, giving a total n = 183 for this question.
¶One respondent did not answer, giving a total n = 201 for this question.
Benefits of A-CHESS
Of the 202 respondents included in the final analysis, 13 respondents did not answer the questions about use of A-CHESS, and 13 indicated that they had not heard of RISE Iowa or Connections, so the analysis of these questions included 176 possible respondents.
A total of 95 respondents reported using A-CHESS in the 30 days before survey participation and thus were asked what features of the app were most helpful for managing loneliness/isolation and anxiety during the COVID-19 pandemic. The most helpful features respondents identified were messaging functions (ie, posting on the open app discussion board and private messaging other users), with 32.2% of respondents reporting that these were helpful for managing loneliness and isolation during the pandemic and 21.8% reporting that these were helpful for managing anxiety. Approximately one quarter of respondents reported that the informational and motivational resources available on the app were helpful to them (25.7% for managing their isolation/loneliness and 26.7% for anxiety). A total of 20.8% of respondents reported that completing a weekly survey about their recovery strengths was helpful for managing isolation and loneliness, and 14.9% reported that this was helpful for anxiety. Having the ability to contact a treatment provider or community-based support resource was helpful to 6.9% for managing loneliness and 5.0% for anxiety.
Reasons for Not Using A-CHESS
Among the 81 respondents who had not used A-CHESS in the 30 days before survey completion, the most common reasons reported for not using A-CHESS were that they had trouble using the app or did not know how to use it (21%) or that using the app was not part of their treatment plan (21%, Fig. 1). Other reasons were finding the app boring (17.3%), feeling the app was not relevant to them (14.8%), using another app for recovery (4.9%), concerns about data or phone minute use (4.9%), and lack of internet access (1.2%).
FIGURE 1.
Percentages of respondents indicating different features as reasons that they had not used A-CHESS in the past 30 days.
Desired A-CHESS Functions
Among 184 respondents who answered a question about the A-CHESS functions that would make them more likely to use a recovery support app in the future, the most commonly desired app function was receiving rewards for meeting sobriety or other goals that they have (44.6%, Fig. 2). Other reported functions included if the app could be used to find self-help meetings (eg, Alcoholics Anonymous, 34.2%), if the app was part of their treatment plan (30.2%), if they could contact a counselor or treatment provider through the app (29.7%), and if the app helped to provide reminders of medications and appointments (26.2%). Only 8.4% indicated that having access to a smartphone, internet, or a data plan would make them more likely to use a recovery app. Notably, app users are able to locate self-help meetings through the A-CHESS app and are able to contact their counselor or other treatment provider through the messaging features.
FIGURE 2.
Percentage of respondents indicating each feature would make them more likely to use a recovery app in the future.
Sociodemographic Correlates of Desired A-CHESS Functions
Sociodemographic correlates of selecting the 2 most frequently desired A-CHESS functions (receiving rewards for meeting goals and being able to find self-help meetings through the app) were analyzed (Table 2). Desiring to receive rewards for meeting sobriety or other goals through the app was associated with being younger (69.3% of those who desired rewards were 41 years and younger vs 48.2% of those who did not desire rewards, P = 0.003), making less than $25,000/year (51.1% of those who desired rewards made <$25,000/year vs 34.8% of those who did not desire rewards, P = 0.027), and being unemployed (53.3% of those who desired rewards were employed vs 67.6% of those who did not desire rewards, P = 0.039). There were no sociodemographic variables that were statistically significantly related to reporting a preference for the ability to find self-help meetings through the app.
TABLE 2.
Sociodemographic Correlates of Desired A-CHESS Functions
| Variable | Function: Rewards for Meeting Goals | Function: Find Self-Help Meetings | ||||
|---|---|---|---|---|---|---|
| Desired, n (%) | Did Not Desire, n (%) | P | Desired, n (%) | Did Not Desire, n (%) | P | |
| Total | 90 (100.0) | 112 (100.0) | 69 (100.0) | 133 (100.0) | ||
| Age* | <0.01 | 0.18 | ||||
| Mean age (41 y or younger) | 61 (69.3) | 53 (48.2) | 43 (64.2) | 71 (54.2) | ||
| Above mean age (≥42 y) | 27 (30.7) | 57 (51.8) | 24 (35.8) | 60 (45.8) | ||
| Sex | 0.61 | 0.91 | ||||
| Female | 57 (63.3) | 67 (59.8) | 42 (60.9) | 82 (61.7) | ||
| Male | 33 (36.7) | 45 (40.2) | 27 (39.1) | 51 (38.3) | ||
| Race† | 0.23 | 0.55 | ||||
| White | 71 (78.9) | 97 (87.4) | 55 (79.7) | 113 (85.6) | ||
| Black | 5 (5.6) | 5 (4.5) | 4 (5.8) | 6 (4.5) | ||
| Any other race | 14 (15.6) | 9 (8.1) | 10 (14.5) | 13 (9.9) | ||
| Income‡ | 0.03 | 0.25 | ||||
| Less than $25,000/year | 45 (51.1) | 32 (34.8) | 25 (37.3) | 52 (46.0) | ||
| More than $25,001/year | 43 (48.9) | 60 (65.2) | 42 (62.7) | 61 (54.0) | ||
| Income change during COVID-19 pandemic§ | 0.13 | 0.03 | ||||
| Income is less since start of pandemic | 46 (51.7) | 40 (42.6) | 41 (59.4) | 45 (39.5) | ||
| Income is about the same | 28 (31.5) | 43 (45.7) | 22 (31.9) | 49 (43.0) | ||
| Income is more since start of pandemic | 15 (16.8) | 11 (11.7) | 6 (8.7) | 20 (17.5) | ||
| High school diploma or beyond education level∥ | 79 (96.3) | 92 (91.1) | 0.20 | 60 (95.2) | 111 (92.5) | 0.75 |
| Married or member of an unmarried couple | 29 (32.2) | 48 (42.9) | 0.12 | 27 (39.1) | 50 (37.6) | 0.83 |
| Live in a house, townhouse, or apartment I rent or own | 54 (60.0) | 78 (69.6) | 0.15 | 41 (59.4) | 91 (68.4) | 0.20 |
| Employed full time, part time, or self-employed¶ | 48 (53.3) | 75 (67.6) | 0.04 | 43 (63.2) | 80 (60.2) | 0.67 |
| Have computer with internet where I live | 75 (83.3) | 92 (82.1) | 0.82 | 62 (89.9) | 105 (78.9) | 0.05 |
| Have a smartphone | 90 (100.0) | 107 (95.5) | 0.07 | 69 (100.0) | 128 (96.2) | 0.17 |
*Four respondents did not answer, giving a total n = 198 for this question.
†One respondent did not answer, giving a total n = 201 for this question.
‡Twenty-two respondents did not answer, giving a total n = 180 for this question.
§Nineteen respondents did not answer, giving a total n = 183 for this question.
∥Nineteen respondents did not answer, giving a total n = 183 for this question.
¶One respondent did not answer, giving a total n = 201 for this question.
DISCUSSION
Smartphone apps can be effective supports for recovery, yet long-term app engagement remains a challenge. In this study, we characterized the most useful aspects of a recovery app to inform future app development. Overall, we found that providing the opportunity for rewards when app users meet goals, helping users find support group meetings, and incorporating the use of apps into SUD treatment plans were the most desired features of recovery apps, suggesting priorities for future development and key features to point out to app users during account creation and throughout app use so that they can take full advantage of existing features.
Incorporating patient suggestions for recovery apps will likely promote greater engagement with this type of support in the future. We found that respondents, especially those who were younger, unemployed, or had a lower income, desired an app with the capacity for rewards, consistent with the strategy of contingency management. Prior research suggests that this strategy could improve treatment retention and outcomes.12,13 Dallery et al.12 studied the impact of a cash reward on smoking cessation and found that 90% of breath samples submitted during an app-based contingency management intervention were negative for smoking (relative to only 4% of at baseline). In addition, compliance with providing breath samples to measure smoking cessation was very high, with 85% of samples requested during the study received.12 Similar results were seen in an alcohol use disorder treatment trial, with high rates of compliance for testing and an association between receiving contingency management and longer engagement with other forms of treatment, including in-person care treatment app use.13 Furthermore, app-based contingency management may be particularly effective in rural or low-income areas with less access to traditional forms of treatment.12 Our results add to prior studies, indicating that embedding rewards within apps may improve engagement with recovery apps in the future and that this may be particularly effective for certain populations.
Adding gamification features is another potential avenue to promote engagement with recovery apps. Given that one of the primary reasons cited by respondents for not using A-CHESS was finding the app boring, incorporating gamified features may make the app more engaging for patients to use and encourage higher levels of use in the future.16,24 In addition, gamification is one potential avenue to implement contingency management, as respondents were especially interested in receiving rewards for meeting their goals via the app. However, gamification could also include nonmonetary rewards, like stars or points, which may bolster motivation for continued app use despite these rewards not having value outside of the app.24 Incorporating additional gamified features that have been shown to be useful in other health apps, like competition and goal setting, may also help to make apps like A-CHESS more engaging in the future.14,15 In A-CHESS, features like leaderboards for days of use or engagement with certain features of the app, like podcasts or other resources, could be added to incorporate elements of competition, whereas allowing users to set goals for amount of use per day could incorporate goal-setting features.
Notably, research conducted in the RISE Iowa parent trial with clinicians found that they also wanted to add gamification features to make the app more engaging to patients and colleagues.21 However, other prior literature has highlighted the potential negative consequences of gamification, including punishment for productive behaviors when individuals do not log them into the app, rewards that are meaningless or feel out of proportion to the work required to receive them, and increased likelihood of cheating on tasks that earn rewards.25 Trials of gamified recovery support apps are needed to gather information about their effectiveness and the potential for unintended harms.
In general, aspects of A-CHESS that were reported as most helpful were those that created community and those that allowed users to track their recovery. These features likely enabled app users to feel connected to peers during the COVID-19 pandemic, when this study was conducted and at a time of heightened feelings of loneliness and isolation.8,9 A-CHESS was developed from self-determination theory, which emphasizes the importance of relatedness and social connectedness to support recovery.4,26 Future recovery apps may wish to further develop community-building capacity to promote greater app engagement.
Many of the suggestions patients provided for improving A-CHESS (eg, finding self-help meetings, contacting a counselor or treatment provider) are features that already exist in the app. This indicates that more time needs to be devoted to teaching patients how to use the app, with particular attention to training focused on the features patients want. Training could be accomplished in multiple ways, including through in-app tutorials, demonstrations from treatment providers, and peer support from other app users, and these techniques would likely be most effective if used in tandem. Many studies on the use of mobile technologies in mental health and substance use treatment have provided training to patients on the use of the app as part of the intervention, but nearly all have used study staff to provide this training.3,27–29 In this implementation trial, clinicians provided training to patients, which may have ultimately resulted in variable training methods and information provided depending on factors like the clinicians' comfort with technology and workload. For apps to be successfully implemented outside the context of a research study or clinical trial, ensuring that they are designed to be easy and intuitive to use is vital to maximizing engagement, as this will minimize burden on clinicians. Indeed, individuals are more likely to sustain their engagement with an app that is easy to understand, even without training.30 In addition, because the most reported reason for nonuse of A-CHESS from those who had not used the app was not knowing how to use it, designing recovery apps with an explicit focus on ease of use and user-centeredness and/or identifying effective training strategies may bolster app use in the future even among those who did not use apps in this study.
The other most common reason for not using the app that individuals cited was that the app was not a part of their treatment plan. The parent RISE Iowa trial is currently studying the impact of implementation strategies such as coaching and a process improvement model called NIATx on organizational uptake of recovery apps.20 As part of this study, we are examining how treatment providers decide whether to incorporate A-CHESS as a part of individualized treatment plans once it is made available at their organization. Our early results suggest that providers may be hesitant to incorporate an app as part of the treatment plan because of a perceived lack of potential benefit to the patient and because of concerns over forcing respondents to use an app. Nonetheless, our findings also highlight the importance of clinician engagement with A-CHESS as a way to strengthen client interest. Clinicians have further reported concerns over lack of internet access or access to cell phone data. Although our study found that lack of access to internet or smartphones were infrequently cited as reasons for not using the app, our sample may not be representative of phone access across populations, and this barrier will need to be assessed individually.
Limitations
This analysis had a relatively modest sample size despite inviting 1515 individuals who had downloaded A-CHESS to complete the survey. This low response rate (13%) may limit the generalizability of our findings, as those who responded to the survey may differ from those who did not. In addition, the individuals using RISE Iowa and Connections may be different from one another, as Connections users were located across the United States and the majority were justice-referred clients, whereas those using RISE Iowa were located only in Iowa and had a lower rate of criminal justice system involvement. Although our survey found that 48% of Connections users had criminal justice involvement versus 38% of the RISE Iowa users, differences between the samples may persist given the different recruitment strategies used for each parent study.
CONCLUSION
Recovery support apps, like A-CHESS, have numerous features that can support individuals as they navigate their recovery, including providing access to a community of support that understands the challenges they are experiencing and access to resources that can provide additional needed support, especially during crises like the COVID-19 pandemic. However, these features alone are not enough to encourage significant engagement with recovery support apps. Adding features like contingency management may support app use, particularly for patients who are younger or have lower incomes. Understanding what features of recovery apps are most and least beneficial for managing common concerns related to recovery and what improvements are most desired by populations designed to use apps will be needed to continue improving to provide better support and improve treatment outcomes using app-based systems.
Supplementary Material
Footnotes
Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal’s Web site (www.journaladdictionmedicine.com).
Kathryn Fleddermann (https://orcid.org/0000-0001-7937-693X)
Todd Molfenter (https://orcid.org/0000-0003-3033-416X)
Olivia Vjorn (https://orcid.org/0000-0002-3085-6067)
Julie Horst (https://orcid.org/0000-0003-1679-2674)
Jessica Hulsey (https://orcid.org/0000-0002-0338-0411)
Braeden Kelly (https://orcid.org/0000-0003-1624-3448)
Kayla Zawislak (https://orcid.org/0000-0002-8312-1638)
David H. Gustafson (https://orcid.org/0000-0002-0660-1902)
Rachel E. Gicquelais (https://orcid.org/0000-0002-7022-6385)
Dr Molfenter is a faculty member at CHESS. In addition to his academic affiliation, Dr Molfenter has a less than 0.1% ownership with CHESS Health, the organization responsible for making the A-CHESS addiction recovery app commercially available to the public. Dr Molfenter has worked extensively with his institution to manage any conflicts of interest. Dr Gustafson is a part owner of CHESS Health, devoted to marketing information technologies to agencies that deliver addiction treatment. He is also on the board of directors of the not-for-profit NIATx Foundation, as well as a small consulting company doing business as David H. Gustafson and Associates. These relationships do not carry with them any restrictions on publication, and any associated intellectual property will be disclosed and processed according to his institution's policies. The remaining authors for this article have no conflicts of interest.
Supported by the National Institute on Drug Abuse of the National Institutes of Health under award number R01DA044159 (D.H. Gustafson, PI, and T. Molfenter, PI). It was conducted as part of a Helping to End Addiction Long-term (HEAL) supplement (3R01DA044159-02S1). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Author Contributions: KF, JH, BK, and KZ collected the data. KF led the analysis and wrote the first draft of the paper. REG conceptualized the study and supervised data collection, analysis, and writing the paper. JH contributed to the data collection and supervision. OV collated the data and assisted in writing the paper. DHG and TM obtained funding for the study and conceptualization of the analysis. All authors reviewed the paper before submission.
Contributor Information
Todd Molfenter, Email: todd.molfenter@wisc.edu.
Olivia Vjorn, Email: ocody@wisc.edu.
Julie Horst, Email: jhorst@wisc.edu.
Jessica Hulsey, Email: jhulsey@addictionpolicy.org.
Braeden Kelly, Email: bkelly@addictionpolicy.org.
Kayla Zawislak, Email: kzawislak@addictionpolicy.org.
David H. Gustafson, Email: dhgustaf@wisc.edu.
Rachel E. Gicquelais, Email: gicquelais@wisc.edu.
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