Giving and receiving social support in online substance use disorder forums: How self-efficacy moderates effects on relapse.

OBJECTIVE: Individuals in recovery for substance use disorders (SUDs) increasingly use online social support forums, necessitating research on how communicating through these forums can affect recovery. This study examines how giving and receiving support within an SUDs recovery forum predict substance use, and considers whether effects vary according to participants' self-efficacy. METHODS: We applied content analysis to 3440 messages that were posted by 231 participants in an online SUDs forum. Surveys assessed social support reception and substance use at three timepoints. We assessed relationships between giving and receiving support and substance use (risky drinking days, illicit drug use days), and the interactions between self-efficacy and social support in predicting substance use outcomes. RESULTS: Receiving more emotional support was associated with reduced illicit drug use at 6 and 12 months. For those with low self-efficacy, giving more emotional support predicted less risky drinking at month 12, whereas giving more informational support predicted more risky drinking at month 12. CONCLUSION: These results suggest conditional benefits of exchanging support in an online SUDs forum, depending upon type of support (informational versus emotional), the participants' role (giver or receiver), and their self-efficacy. PRACTICE IMPLICATIONS: We discuss implications for designing and using peer-to-peer support platforms.

Interactivity, Presence, and Targeted Patient Care: Mapping e-Health Intervention Effects Over Time for Cancer Patients with Depression.

This study examined the interplay of depression and different types of e-health interventions on breast cancer patients' perceived healthcare competence, emotional processing, and social well-being over time. The three e-health interventions--Internet Only as a control condition, CHESS (Comprehensive Health Enhancement Support System) Only, and CHESS with a Human Mentor, a cancer information specialist--provided varying degrees of interactivity and presence. A total of 328 women with breast cancer participated in one of the three interventions for a 6-month period. Women were further split into two groups based on reported levels of depression. For perceived healthcare competence and social well-being, results revealed significant interaction effects for intervention type by depression over time, such that breast cancer patients with higher levels of depression benefited most from the CHESS with Mentor intervention over the 6-month study period. For emotional processing, depressed cancer patients benefited more from the CHESS with Mentor than the other two interventions, regardless of time. These findings have (a) theoretical implications on how mental health factors can intersect with interactivity and presence to influence psychosocial outcomes, (b) conceptual implications for the role of human interaction within e-health systems, and (c) practical implications for the development of e-health interventions for cancer patients with depression.

Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum.

BACKGROUND: Online discussion forums allow those in addiction recovery to seek help through text-based messages, including when facing triggers to drink or use drugs. Trained staff (or "moderators") may participate within these forums to offer guidance and support when participants are struggling but must expend considerable effort to continually review new content. Demands on moderators limit the scalability of evidence-based digital health interventions. OBJECTIVE: Automated identification of recovery problems could allow moderators to engage in more timely and efficient ways with participants who are struggling. This paper aimed to investigate whether computational linguistics and supervised machine learning can be applied to successfully flag, in real time, those discussion forum messages that moderators find most concerning. METHODS: Training data came from a trial of a mobile phone-based health intervention for individuals in recovery from alcohol use disorder, with human coders labeling discussion forum messages according to whether or not authors mentioned problems in their recovery process. Linguistic features of these messages were extracted via several computational techniques: (1) a Bag-of-Words approach, (2) the dictionary-based Linguistic Inquiry and Word Count program, and (3) a hybrid approach combining the most important features from both Bag-of-Words and Linguistic Inquiry and Word Count. These features were applied within binary classifiers leveraging several methods of supervised machine learning: support vector machines, decision trees, and boosted decision trees. Classifiers were evaluated in data from a later deployment of the recovery support intervention. RESULTS: To distinguish recovery problem disclosures, the Bag-of-Words approach relied on domain-specific language, including words explicitly linked to substance use and mental health ("drink," "relapse," "depression," and so on), whereas the Linguistic Inquiry and Word Count approach relied on language characteristics such as tone, affect, insight, and presence of quantifiers and time references, as well as pronouns. A boosted decision tree classifier, utilizing features from both Bag-of-Words and Linguistic Inquiry and Word Count performed best in identifying problems disclosed within the discussion forum, achieving 88% sensitivity and 82% specificity in a separate cohort of patients in recovery. CONCLUSIONS: Differences in language use can distinguish messages disclosing recovery problems from other message types. Incorporating machine learning models based on language use allows real-time flagging of concerning content such that trained staff may engage more efficiently and focus their attention on time-sensitive issues.

Effects of automated smartphone mobile recovery support and telephone continuing care in the treatment of alcohol use disorder: study protocol for a randomized controlled trial.

BACKGROUND: New smartphone communication technology provides a novel way to provide personalized continuing care support following alcohol treatment. One such system is the Addiction version of the Comprehensive Health Enhancement Support System (A-CHESS), which provides a range of automated functions that support patients. A-CHESS improved drinking outcomes over standard continuing care when provided to patients leaving inpatient treatment. Effective continuing care can also be delivered via telephone calls with a counselor. Telephone Monitoring and Counseling (TMC) has demonstrated efficacy in two randomized trials with alcohol-dependent patients. A-CHESS and TMC have complementary strengths. A-CHESS provides automated 24/7 recovery support services and frequent assessment of symptoms and status, but does not involve regular contact with a counselor. TMC provides regular and sustained contact with the same counselor, but no ongoing support between calls. The future of continuing care for alcohol use disorders is likely to involve automated mobile technology and counselor contact, but little is known about how best to integrate these services. METHODS/DESIGN: To address this question, the study will feature a 2 × 2 design (A-CHESS for 12 months [yes/no] × TMC for 12 months [yes/no]), in which 280 alcohol-dependent patients in intensive outpatient programs (IOPs) will be randomized to one of the four conditions and followed for 18 months. We will determine whether adding TMC to A-CHESS produces fewer heavy drinking days than TMC or A-CHESS alone and test for TMC and A-CHESS main effects. We will determine the costs of each of the four conditions and the incremental cost-effectiveness of the three active conditions. Analyses will also examine secondary outcomes, including a biological measure of alcohol use, and hypothesized moderation and mediation effects. DISCUSSION: The results of the study will yield important information on improving patient alcohol use outcomes by integrating mobile automated recovery support and counselor contact. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02681406 . Registered on 2 September 2016.

Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study.

BACKGROUND: Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care. OBJECTIVE: The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians. METHODS: In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: The outcomes according to the RE-AIM framework are as follows: Reach-Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness-Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption-Patients sustained high levels of Seva use-between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation-At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance-Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this. CONCLUSIONS: Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge.

SurvivorCHESS to increase physical activity in colon cancer survivors: can we get them moving?

PURPOSE: This randomized controlled trial evaluated the impact of SurvivorCHESS, an eHealth intervention, on physical activity in colon cancer survivors and to explore the impact of SurvivorCHESS on quality of life and distress. METHODS: This was a two-arm single-blinded multi-site randomized controlled trial comparing a control group to an intervention group receiving a smartphone with the SurvivorCHESS program. RESULTS: Participants using SurvivorCHESS (n = 144) increased their moderate to vigorous physical activities from 19.4 min at baseline to 50 min compared to the control group (n = 140) increasing from 15.5 to 40.3 min at 6 months (p = .083) but was not sustained 3 months after the study ended. No significant differences were found between groups over time for quality of life or distress items. Reports of physical symptoms were greater than other categories for distress items. Patients who had a higher body mass index and number of comorbid conditions were less likely to increase their physical activity. Self-determination theory including autonomous motivation and relatedness was not associated with the outcomes. CONCLUSIONS: Physical activity did increase over time in both groups and was not significantly different with the use of the eHealth intervention, SurvivorCHESS, compared to the control group. The amount of SurvivorCHESS use was not associated with physical activity. IMPLICATIONS FOR CANCER SURVIVORS: Increasing physical activity in colon cancer survivors has the potential to improve quality of life and reduce recurrences. Using smartphone-tracking devices may be useful in helping to change this health behavior.

Reducing Symptom Distress in Patients With Advanced Cancer Using an e-Alert System for Caregivers: Pooled Analysis of Two Randomized Clinical Trials.

BACKGROUND: Symptom distress in patients toward the end of life can change rapidly. Family caregivers have the potential to help patients manage those symptoms, as well as their own stress, if they are equipped with the proper resources. Electronic health (eHealth) systems may be able to provide those resources. Very sick patients may not be able to use such systems themselves to report their symptoms but family caregivers could. OBJECTIVE: The aim of this paper was to assess the effects on cancer patient symptom distress of an eHealth system that alerts clinicians to significant changes in the patient's symptoms, as reported by a family caregiver. METHODS: A pooled analysis from two randomized clinical trials (NCT00214162 and NCT00365963) compared outcomes at 12 months for two unblinded groups: a control group (Comprehensive Health Enhancement Support System [CHESS]-Only) that gave caregivers access to CHESS, an online support system, and an experimental group (CHESS+CR [Clinician Report]), which also had CHESS but with a CR that automatically alerted clinicians if symptoms exceeded a predetermined threshold of severity. Participants were dyads (n=235) of patients with advanced lung, breast, or prostate cancer and their respective family caregivers from 5 oncology clinics in the United States of America. The proportion of improved patient threshold symptoms was compared between groups using area-under-the-curve analysis and binomial proportion tests. The proportion of threshold symptoms out of all reported symptoms was also examined. RESULTS: When severe caregiver-reported symptoms were shared with clinicians, the symptoms were more likely to be subsequently reported as improved than when the symptoms were not shared with clinicians (P<.001). Fewer symptom reports were completed in the group of caregivers whose reports went to clinicians than in the CHESS-Only group (P<.001), perhaps because caregivers, knowing their reports might be sent to a doctor, feared they might be bothering the clinician. CONCLUSIONS: This study suggests that an eHealth system designed for caregivers that alerts clinicians to worrisome changes in patient health status may lead to reduced patient distress. TRIAL REGISTRATION: Clinicaltrials.gov NCT00214162; https://clinicaltrials.gov/ct2/show/NCT00214162 (Archived by WebCite at http://www.webcitation.org/6nmgdGfuD) and Clinicaltrials.gov NCT00365963; https://clinicaltrials.gov/ct2/show/NCT00365963 (Archived by WebCite at http://www.webcitation.org/6nmh0U8VP).

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.

When support is needed: Social support solicitation and provision in an online alcohol use disorder forum.

BACKGROUND: Obtaining adequate social support presents a challenge for many in addiction recovery. Increasingly, individuals in recovery use online forums to exchange support with peers, yet it is unclear which help-seeking strategies most effectively recruit peer support, and which forms of support are most valued by recipients. METHODS: This study applied quantitative content analysis to examine social support solicitation and delivery in an online forum for alcohol use disorder (AUD). We compared the frequency with which peers provided informational, emotional, and companionship support after solicitations that: (1) were direct or indirect, (2) disclosed positive or negative emotions, and (3) mentioned or did not mention recovery problems. We assessed likelihood that recipients would express gratitude after receiving each type of support, and assessed whether the "match" between solicitation and disclosure styles influenced rates of gratitude expression. RESULTS: Emotional disclosures, whether positive or negative, received the highest volume of supportive replies. Emotional support was the most common response to solicitations overall, and was disproportionately offered after recipients disclosed positive emotions. Informational support was disproportionately offered after recipients disclosed negative emotions or recovery problems, or explicitly requested help. Regardless of their solicitation style, recipients expressed more gratitude after receiving emotional support than other support types. CONCLUSIONS: Providing emotional support was common in an online AUD forum, and precipitated expressing gratitude from recipients to support providers. The results may be helpful in guiding participants to more effectively obtain and provide recovery support in online forums.

The effect of bundling medication-assisted treatment for opioid addiction with mHealth: study protocol for a randomized clinical trial.

BACKGROUND: Opioid dependence has devastating and increasingly widespread consequences and costs, and the most common outcome of treatment is early relapse. People who inject opioids are also at disproportionate risk for contracting the human immunodeficiency virus (HIV) and hepatitis C virus (HCV). This study tests an approach that has been shown to improve recovery rates: medication along with other supportive services (medication-assisted treatment, or MAT) against MAT combined with a smartphone innovation called A-CHESS (MAT + A-CHESS). METHODS/DESIGN: This unblinded study will randomly assign 440 patients to receive MAT + A-CHESS or MAT alone. Eligible patients will meet criteria for having an opioid use disorder of at least moderate severity and will be taking methadone, injectable naltrexone, or buprenorphine. Patients with A-CHESS will have smartphones for 16 months; all patients will be followed for 24 months. The primary outcome is the difference between patients in the two arms in percentage of days using illicit opioids during the 24-month intervention. Secondary outcomes are differences between patients receiving MAT + A-CHESS versus MAT in other substance use, quality of life, retention in treatment, health service use, and, related to HIV and HCV, screening and testing rates, medication adherence, risk behaviors, and links to care. We will also examine mediators and moderators of the effects of MAT + A-CHESS. We will measure variables at baseline and months 4, 8, 12, 16, 20, and 24. At each point, patients will respond to a 20- to 30-min phone survey; urine screens will be collected at baseline and up to twice a month thereafter. We will use mixed-effects to evaluate the primary and secondary outcomes, with baseline scores functioning as covariates, treatment condition as a between-subject factor, and the outcomes reflecting scores for a given assessment at the six time points. Separate analyses will be conducted for each outcome. DISCUSSION: A-CHESS has been shown to improve recovery for people with alcohol dependence. It offers an adaptive and extensive menu of services and can attend to patients nearly as constantly as addiction does. This suggests the possibility of increasing both the effectiveness of, and access to, treatment for opioid dependence. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02712034 . Registered on 14 March 2016.

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

BACKGROUND: Millions 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. METHODS: Prior 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. RESULTS: Clinicians 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. CONCLUSIONS: Results 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 REGISTRATION: ClinicalTrials.gov ( NCT01963234 ).

Self-Determination Theory and Computer-Mediated Support: Modeling Effects on Breast Cancer Patient's Quality-of-Life.

A breast cancer diagnosis typically results in dramatic and negative effects on an individual's quality of life. Web-based interactive support systems such as the Comprehensive Health Enhancement Support System (CHESS) offer one avenue for mitigating these negative effects. While evidence supports the efficacy of such systems, evaluations typically fail to provide a true test of the theorized model of effects, treating self-determination theory's constructs of competence, relatedness, and autonomy as outcomes rather than mediators. Using path analysis, this study tests the nature of the proposed mediated relationship between system engagement and quality-of-life indicators utilizing data collected from women (N = 90) who participated in the treatment condition of a CHESS randomized controlled trial. Findings support a latent model, indicating that system effects are mediated through an intertwined measure of autonomy, competence, and relatedness.

The effect of an information and communication technology (ICT) on older adults' quality of life: study protocol for a randomized control trial.

BACKGROUND: This study investigates the use of an information and communication technology (Elder Tree) designed for older adults and their informal caregivers to improve older adult quality of life and address challenges older adults face in maintaining their independence (for example, loneliness and isolation, falling, managing medications, driving and transportation). METHODS/DESIGN: This study, an unblinded randomized controlled trial, will evaluate the effectiveness and cost of Elder Tree. Older adults who are at risk for losing their independence - along with their informal caregivers, if they name them - are randomized to two groups. The intervention group has access to their usual sources of information and communication as well as to Elder Tree for 18 months while the control group uses only their usual sources of information and communication. The primary outcome of the study is older adult quality of life. Secondary outcomes are cost per Quality-Adjusted Life Year and the impact of the technology on independence, loneliness, falls, medication management, driving and transportation, and caregiver appraisal and mastery. We will also examine the mediating effect of self-determination theory. We will evaluate the effectiveness of Elder Tree by comparing intervention- and control-group participants at baseline and months 6, 12, and 18. We will use mixed-effect models to evaluate the primary and secondary outcomes, where pretest score functions as a covariate, treatment condition is a between-subjects factor, and the multivariate outcome reflects scores for a given assessment at the three time points. Separate analyses will be conducted for each outcome. Cost per Quality-Adjusted Life Year will be compared between the intervention and control groups. Additional analyses will examine the mediating effect of self-determination theory on each outcome. DISCUSSION: Elder Tree is a multifaceted intervention, making it a challenge to assess which services or combinations of services account for outcomes in which subsets of older adults. If Elder Tree can improve quality of life and reduce healthcare costs among older adults, it could suggest a promising way to ease the burden that advancing age can place on older adults, their families, and the healthcare system. TRIAL REGISTRATION: ClinicalTrials.gov NCT02128789 . Registered on 26 March 2014.

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

BACKGROUND: Healthcare 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/DESIGN: Our 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. DISCUSSION: If 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 REGISTRATION: ClinicalTrials.gov (NCT01963234).

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 patient's 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.

Predictive modeling of addiction lapses in a mobile health application.

The chronically relapsing nature of alcoholism leads to substantial personal, family, and societal costs. Addiction-comprehensive health enhancement support system (A-CHESS) is a smartphone application that aims to reduce relapse. To offer targeted support to patients who are at risk of lapses within the coming week, a Bayesian network model to predict such events was constructed using responses on 2,934 weekly surveys (called the Weekly Check-in) from 152 alcohol-dependent individuals who recently completed residential treatment. The Weekly Check-in is a self-monitoring service, provided in A-CHESS, to track patients' recovery progress. The model showed good predictability, with the area under receiver operating characteristic curve of 0.829 in the 10-fold cross-validation and 0.912 in the external validation. The sensitivity/specificity table assists the tradeoff decisions necessary to apply the model in practice. This study moves us closer to the goal of providing lapse prediction so that patients might receive more targeted and timely support.

CHESS improves cancer caregivers' burden and mood: results of an eHealth RCT.

OBJECTIVE: Informal caregivers (family and friends) of people with cancer are often unprepared for their caregiving role, leading to increased burden or distress. Comprehensive Health Enhancement Support System (CHESS) is a Web-based lung cancer information, communication, and coaching system for caregivers. This randomized trial reports the impact on caregiver burden, disruptiveness, and mood of providing caregivers access to CHESS versus the Internet with a list of recommended lung cancer websites. METHODS: A total of 285 informal caregivers of patients with advanced nonsmall cell lung cancer were randomly assigned to a comparison group that received Internet or a treatment group that received Internet and CHESS. Caregivers were provided a computer and Internet service if needed. Written surveys were completed at pretest and during the intervention period bimonthly for up to 24 months. Analyses of covariance (ANCOVAs) compared the intervention's effect on caregivers' disruptiveness and burden (CQOLI-C), and negative mood (combined Anxiety, Depression, and Anger scales of the POMS) at 6 months, controlling for blocking variables (site, caregiver's race, and relationship to patient) and the given outcome at pretest. RESULTS: Caregivers randomized to CHESS reported lower burden, t(84) = 2.36, p = .021, d = .39, and negative mood, t(86) = 2.82, p = .006, d = .44, than those in the Internet group. The effect on disruptiveness was not significant. CONCLUSIONS: Although caring for someone with a terminal illness will always exact a toll on caregivers, eHealth interventions like CHESS may improve caregivers' understanding and coping skills and, as a result, ease their burden and mood.

The effects of expression: how providing emotional support online improves cancer patients' coping strategies.

BACKGROUND: Emotional support has traditionally been conceived as something a breast cancer patient receives. However, this framework may obscure a more complex process, facilitated by the emerging social media environment, which includes the effects of composing and sending messages to others. Accordingly, this study explores the effects of expression and reception of emotional support messages in online groups and the importance of bonding as a mediator influencing the coping strategies of breast cancer patients. METHODS: Data were collected as part of two National Cancer Institute-funded randomized clinical trials. Eligible subjects were within 2 months of diagnosis of primary breast cancer or recurrence. Expression and reception of emotionally supportive messages were tracked and coded for 237 breast cancer patients. Analysis resulted from merging 1) computer-aided content analysis of discussion posts, 2) action log analysis of system use, and 3) longitudinal survey data. RESULTS: As expected, perceived bonding was positively related to all four coping strategies (active coping: ß = 0.251, P = .000; positive reframing: ß = 0.288, P = .000; planning: ß = 0.213, P = .006; humor: ß = 0.159, P = .009). More importantly, expression (γ = 0.138, P = .027), but not reception (γ = -0.018, P = .741), of emotional support increases perceived bonding, which in turn mediates the effects on patients' positive coping strategies. CONCLUSIONS: There is increasing importance for scholars to distinguish the effects of expression from reception to understand the processes involved in producing psychosocial benefits. This study shows that emotional support is more than something cancer patients receive; it is part of an active, complex process that can be facilitated by social media.

Predictors of Online Health Information Seeking Among Women with Breast Cancer: The Role of Social Support Perception and Emotional Well-Being.

This study attempts to examine the role of social support perception and emotional well-being on online information seeking among cancer patients within the context of CHESS, a well-established Interactive Cancer Communication System (ICCS). Factor and regression analyses conducted among 231 breast cancer patients revealed that social support perception and emotional well-being interacted with each other to influence online health information seeking. Patients with low social support perception and high emotional well-being were most likely to seek health information, whereas patients with high social support perception and high emotional well-being sought out the same information least. Practical implications of the study findings were further discussed.

The effect of a computer-based intervention on adult children of alcoholics.

OBJECTIVES: People who grow up with a family member who has a substance use disorder (SUD) are at risk for serious problems, and yet support for family members focuses mainly on the individual with the SUD. Technology may offer a way to make support widely available to family members of those with SUDs. This small randomized trial examined an online system of resources called CHESS (Comprehensive Health Enhancement Support System) for adult children of alcoholics (ACOAs), a population at greater risk for SUDs, depression, and other difficulties than adults whose parents were not alcoholics. METHODS: The study randomized 23 self-identified ACOAs to 3 interventions for 8 weeks. The goal was to increase participants' treatment compliance and psychological health. The interventions were therapy only, CHESS only, and CHESS plus therapy. We used 2 measures: compliance with treatment, gauged by attendance in group therapy for the 2 groups assigned to therapy, and aspects of psychological health or distress, measured by a survey with items from 7 scales. RESULTS: The CHESS-plus-therapy group had an attendance rate in group therapy of 81.5% compared to 42.8% for the therapy-only group. The CHESS-only intervention had the largest effect size on 5 of the 7 measures of psychological health or distress. In 4 of the 5 cases, the effect size was large; in 1 case, it was moderate. CONCLUSIONS: The findings of this pilot study are based on a small sample, but they suggest the need for more research and the potentially important role of technology in behavioral health treatment.