Amy K. Atwood

A Smartphone Application to Support Recovery From Alcoholism A Randomized Clinical Trial

IMPORTANCE Patients leaving residential treatment for alcohol use disorders are not typically offered evidence-based continuing care, although research suggests that continuing care is associated with better outcomes. A smartphone-based application could provide effective continuing care. OBJECTIVE To determine whether patients leaving residential treatment for alcohol use disorders with a smartphone application to support recovery have fewer risky drinking days than control patients. DESIGN, SETTING, AND PARTICIPANTS An unmasked randomized clinical trial involving 3 residential programs operated by 1 nonprofit treatment organization in the Midwestern United States and 2 residential programs operated by 1 nonprofit organization in the Northeastern United States. In total, 349 patients who met the criteria for DSM-IV alcohol dependence when they entered residential treatment were randomized to treatment as usual (n = 179) or treatment as usual plus a smartphone (n = 170) with the Addiction-Comprehensive Health Enhancement Support System (A-CHESS), an application designed to improve continuing care for alcohol use disorders. INTERVENTIONS Treatment as usual varied across programs; none offered patients coordinated continuing care after discharge. A-CHESS provides monitoring, information, communication, and support services to patients, including ways for patients and counselors to stay in contact. The intervention and follow-up period lasted 8 and 4 months, respectively. MAIN OUTCOMES AND MEASURES Risky drinking days--the number of days during which a patients drinking in a 2-hour period exceeded 4 standard drinks for men and 3 standard drinks for women, with standard drink defined as one that contains roughly 14 g of pure alcohol (12 oz of regular beer, 5 oz of wine, or 1.5 oz of distilled spirits). Patients were asked to report their risky drinking days in the previous 30 days on surveys taken 4, 8, and 12 months after discharge from residential treatment. RESULTS For the 8 months of the intervention and 4 months of follow-up, patients in the A-CHESS group reported significantly fewer risky drinking days than did patients in the control group, with a mean of 1.39 vs 2.75 days (mean difference, 1.37; 95% CI, 0.46-2.27; P = .003). CONCLUSIONS AND RELEVANCE The findings suggest that a multifeatured smartphone application may have significant benefit to patients in continuing care for alcohol use disorders. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01003119.

An eHealth system supporting palliative care for patients with non-small cell lung cancer: A randomized trial

In this study, the authors examined the effectiveness of an online support system (Comprehensive Health Enhancement Support System [CHESS]) versus the Internet in relieving physical symptom distress in patients with non–small cell lung cancer (NSCLC).

Integrating addiction treatment into primary care using mobile health technology: protocol for an implementation research study

BackgroundHealthcare reform in the United States is encouraging Federally Qualified Health Centers and other primary-care practices to integrate treatment for addiction and other behavioral health conditions into their practices. The potential of mobile health technologies to manage addiction and comorbidities such as HIV in these settings is substantial but largely untested. This paper describes a protocol to evaluate the implementation of an E-Health integrated communication technology delivered via mobile phones, called Seva, into primary-care settings. Seva is an evidence-based system of addiction treatment and recovery support for patients and real-time caseload monitoring for clinicians.Methods/DesignOur implementation strategy uses three models of organizational change: the Program Planning Model to promote acceptance and sustainability, the NIATx quality improvement model to create a welcoming environment for change, and Rogers’s diffusion of innovations research, which facilitates adaptations of innovations to maximize their adoption potential. We will implement Seva and conduct an intensive, mixed-methods assessment at three diverse Federally Qualified Healthcare Centers in the United States. Our non-concurrent multiple-baseline design includes three periods — pretest (ending in four months of implementation preparation), active Seva implementation, and maintenance — with implementation staggered at six-month intervals across sites. The first site will serve as a pilot clinic. We will track the timing of intervention elements and assess study outcomes within each dimension of the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework, including effects on clinicians, patients, and practices. Our mixed-methods approach will include quantitative (e.g., interrupted time-series analysis of treatment attendance, with clinics as the unit of analysis) and qualitative (e.g., staff interviews regarding adaptations to implementation protocol) methods, and assessment of implementation costs.DiscussionIf implementation is successful, the field will have a proven technology that helps Federally Qualified Health Centers and affiliated organizations provide addiction treatment and recovery support, as well as a proven strategy for implementing the technology. Seva also has the potential to improve core elements of addiction treatment, such as referral and treatment processes. A mobile technology for addiction treatment and accompanying implementation model could provide a cost-effective means to improve the lives of patients with drug and alcohol problems.Trial registrationClinicalTrials.gov (NCT01963234).

How Professional Development in Project Lead the Way: Changes High School STEM Teachers' Beliefs about Engineering Education.

This quasiexperimental study measured the impact of Project Lead the Way (PLTW) instruction and professional development training on the views and expectations regarding engineering learning, instruction and career success of nascent precollege engineering teachers. PLTW teachers’ initial and changing views were compared to the views exhibited by a matching group of high school STEM teachers. The primary instrument was the Engineering Beliefs and Expectation Instruments for Teachers (EEBEIT), which included Likert scale items, contextualized judgments about fictional student vignettes, and demographic items. Teachers’ baseline survey responses, on average, revealed the importance of academic achievement on teachers’ decision making about who should enroll in future engineering classes and their predictions of who would be most likely to succeed in an engineering career. When making implicit comparisons between students who differed by SES, teachers generally favored enrollment and predicted more career success of high SES students. SES was excluded as a factor in the judgments of all participating teachers when explicitly probed, however. Preexisting group differences showed that budding PLTW teachers reported on STEM integration in their classes with greater frequency than control teachers, while control teachers agreed more strongly about the prerequisite role of high scholastic achievement for engineering studies. Finally, an analysis of teachers’ changing views indicated that nascent PLTW teachers increased their reporting of effective STEM integration over time, above and beyond preexisting group differences and retesting effects. In light of these data we explore the challenges of implementing effective STEM integration in high school classrooms, examine issues of attracting underrepresented students to engineering, and discuss some of the inherent tensions of engineering education at the K12 level.

Implementing an mHealth system for substance use disorders in primary care: a mixed methods study of clinicians’ initial expectations and first year experiences

BackgroundMillions of Americans need but don’t receive treatment for substance use, and evidence suggests that addiction-focused interventions on smart phones could support their recovery. There is little research on implementation of addiction-related interventions in primary care, particularly in Federally Qualified Health Centers (FQHCs) that provide primary care to underserved populations. We used mixed methods to examine three FQHCs’ implementation of Seva, a smart-phone app that offers patients online support/discussion, health-tracking, and tools for coping with cravings, and offers clinicians information about patients’ health tracking and relapses. We examined (a) clinicians’ initial perspectives about implementing Seva, and (b) the first year of implementation at Site 1.MethodsPrior to staggered implementation at three FQHCs (Midwest city in WI vs. rural town in MT vs. metropolitan NY), interviews, meetings, and focus groups were conducted with 53 clinicians to identify core themes of initial expectations about implementation. One year into implementation at Site 1, clinicians there were re-interviewed. Their reports were supplemented by quantitative data on clinician and patient use of Seva.ResultsClinicians anticipated that Seva could help patients and make behavioral health appointments more efficient, but they were skeptical that physicians would engage with Seva (given high caseloads), and they were uncertain whether patients would use Seva. They were concerned about legal obligations for monitoring patients’ interactions online, including possible “cries for help” or inappropriate interactions. One year later at Site 1, behavioral health care providers, rather than physicians, had incorporated Seva into patient care, primarily by discussing it during appointments. Given workflow/load concerns, only a few key clinicians monitored health tracking/relapses and prompted outreach when needed; two researchers monitored the discussion board and alerted the clinic as needed. Clinician turnover/leave complicated this approach. Contrary to clinicians’ initial concerns, patients showed sustained, mutually supportive use of Seva, with few instances of misuse.ConclusionsResults suggest the value of (a) focusing implementation on behavioral health care providers rather than physicians, (b) assigning a few individuals (not necessarily clinicians) to monitor health tracking, relapses, and the discussion board, (c) anticipating turnover/leave and having designated replacements. Patients showed sustained, positive use of Seva.Trial registrationClinicalTrials.gov (NCT01963234).

Treatment seeking as a mechanism of change in a randomized controlled trial of a mobile health intervention to support recovery from alcohol use disorders

BACKGROUND We estimated the efficacy of the Addiction-Comprehensive Health Enhancement Support System (A-CHESS) in increasing the use of services for addiction and examined the extent to which this use of services mediated the effects of A-CHESS on risky drinking days and abstinence from drinking. METHODS We conducted secondary data analyses of the A-CHESS randomized controlled trial. Recruitment occurred in five residential treatment programs operated by two addiction treatment organizations. Participants were 349 adults with alcohol use disorders recruited two weeks before discharge from residential treatment. We provided intervention arm participants with a smartphone, the A-CHESS application, and an 8-month service plan. Control arm participants received treatment as usual. Telephone interviews at 4, 8, and 12-month follow-ups assessed past-month risky drinking days, past-month abstinence, and post-discharge service utilization (past-month outpatient addiction treatment and past-week mutual help including Alcoholics Anonymous and Narcotics Anonymous). Using mixed effects latent variable models, we estimated the indirect effects of A-CHESS on drinking outcomes, as mediated by post-discharge service utilization. RESULTS Approximately 50.5% of participants reported outpatient addiction treatment and 75.5% reported mutual help at any follow-up interview in the year following randomization. Assignment to the A-CHESS intervention was associated with an increased odds of outpatient addiction treatment across follow-ups, but not mutual help. This use of outpatient addiction treatment mediated the effect of A-CHESS on risky drinking days, but not abstinence. The effect of A-CHESS through outpatient addiction treatment appeared to reduce the expected number of risky drinking days across follow-ups by 11%. CONCLUSIONS The mobile health (mHealth) intervention promoted the use of outpatient addiction treatment, which appeared to contribute to its efficacy in reducing risky drinking. Future research should investigate how mHealth interventions could link patients to needed treatment services and promote the sustained use of these services.

Using the NIATx Model to Implement User-Centered Design of Technology for Older Adults

What models can effectively guide the creation of eHealth and mHealth technologies? This paper describes the use of the NIATx model as a framework for the user-centered design of a new technology for older adults. The NIATx model is a simple framework of process improvement based on the following principles derived from an analysis of decades of research from various industries about why some projects fail and others succeed: (1) Understand and involve the customer; (2) fix key problems; (3) pick an influential change leader; (4) get ideas from outside the field; (5) use rapid-cycle testing. This paper describes the use of these principles in technology development, the strengths and challenges of using this approach in this context, and lessons learned from the process. Overall, the NIATx model enabled us to produce a user-focused technology that the anecdotal evidence available so far suggests is engaging and useful to older adults. The first and fourth principles were especially important in developing the technology; the fourth proved the most challenging to use.

Online support: Impact on anxiety in women who experience an abnormal screening mammogram

OBJECTIVES To determine whether an online support tool can impact anxiety in women experiencing an abnormal mammogram. MATERIALS AND METHODS We developed an online support system using the Comprehensive Health Enhancement Support System (CHESS) designed for women experiencing an abnormal mammogram as a model. Our trial randomized 130 of these women to online support (the intervention group) or to a list of five commonly used Internet sites (the comparison group). Surveys assessed anxiety and breast cancer worry, and patient satisfaction at three important clinical time points: when women were notified of their abnormal mammogram, at the time of diagnostic imaging, and at the time of biopsy (if biopsy was recommended). RESULTS Study participants in the intervention group showed a significant decrease in anxiety at the time of biopsy compared to the comparison group (p = 0.017). However, there was no significant difference in anxiety between the intervention group and the comparison group at the time of diagnostic work-up. We discontinued assessment of patient satisfaction after finding that many women had substantial difficulty answering the questions that referenced their physician, because they did not understand who their physician was for this process of care. CONCLUSION The combination of the inability to identify the physician providing care during the mammography work-up and anxiety effects seen only after an interaction with the breast imaging team may indicate that online support only decreases the anxiety of women in concert with direct interpersonal support from the healthcare team.

Surveying Older Adults About a Recommender System for a Digital Library

We present results from a survey of adults, 63 and older, about the potential implementation of a recommender system within a digital library of health-related content. We studied how these older adults perceive the idea of a recommender system and different aspects of its design. We presented four different types of recommender systems in the survey and our results indicate that this group would prefer a system based on explicit feedback in the form of ratings that measure the helpfulness of content. Reinforcing previous research, we learned this group is interested in a system that explains why it recommended content and they do not want to spend much time creating a profile of interests to warm the system. We discuss where we would use this recommender system, how we designed the survey for our audience, and plans for future studies on this subject.