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IntroductionAlcohol consumption is a leading global risk factor for ill-health and premature death. Alcohol screening and brief interventions (SBI) delivered in primary care is effective at reducing alcohol consumption, but routine implementation remains problematic. Screening all patients for excessive drinking (universal screening) is resource-intensive and may be at odds with general practitioners' (GPs') perceived professional role. This study aimed to develop a tailored, theory-based training intervention to strengthen GPs' ability to address alcohol and to manage alcohol-related health problems through a pragmatic approach based on clinical relevance.MethodsA qualitative study design involving focus group interviews and a structured questionnaire for free text replies with GPs in Norway. Behavioral analysis assessed factors influencing delivery of SBI according to the ‘capability, opportunity, motivation and behavior' (COM-B) model to inform intervention development using the Behavior Change Wheel. Qualitative data were analyzed using framework analysis and an iterative approach was adopted to develop the training.ResultsA purposive sample of GPs attended the focus groups (n = 25) and completed the questionnaire (n = 55). Four areas required additional support including: understanding the link between alcohol use and health problems; opening up the conversation on alcohol use; addressing alcohol and dealing with obstacles; and following-up and maintaining change. Findings informed the development of a four-session interactive training intervention and a digital intervention for providing support for patients between consultations to address the identified needs.ConclusionThis work highlights the value of pragmatic, relevance-based clinical strategies, as opposed to universal screening approaches to addressing alcohol in primary care. A pragmatic approach is more in line with GPs existing sclinical skill set and holds the potential to improve widespread uptake and implementation of SBI in routine primary care.

BACKGROUND eHealth interventions can help people change behavior (eg, quit smoking). Reminders sent via SMS text messaging or email may improve the adherence to web-based programs and increase the probability of successful behavior change; however, it is unclear whether their efficiency is affected by the modality of the communication channel. OBJECTIVE A 2-armed randomized control trial was conducted to compare the effect of providing reminders via SMS text messaging versus email on the adherence to an eHealth program for smoking cessation and on the probability to initiate a quit attempt. METHODS Smokers were recruited via an internet-based advertisement. A total of 591 participants who diverted from intended use of the program (ie, failed to log on to a session) were automatically randomized to the experimental (SMS text messaging reminder, n=304) or the active comparator (email reminder, n=287) group. RESULTS Unexpectedly, we found that the mode of reminder delivery did not significantly affect either the adherence, namely the number of completed program sessions, with the SMS text messaging reminder group showing a mean of 4.30 (SD 3.24) and the email reminder group showing a mean of 4.36 (SD 3.27) (t586=0.197, P=.84, and Cohen d=0.016), or the outcome, namely the quit smoking attempt rate (34.2% in the SMS text messaging group vs 31.7% in the email group; χ21=0.4, P=.52). Secondary analyses showed that age, gender, and education had significant effects on program adherence and education on the outcome. Moreover, we found a significant interaction effect between the mode of reminder delivery and gender on program adherence, suggesting that the effectiveness of SMS text message reminders might be different for females and males. However, this particular finding should be treated with care as it was based on post hoc subgroup analysis. CONCLUSIONS This study indicates that the modality of user reminders to log on increased neither the program adherence nor the probability of quitting smoking. This suggests that program developers may save costs using emails instead of SMS text messaging reminders. CLINICALTRIAL ClinicalTrials.gov NCT03276767; https://clinicaltrials.gov/ct2/show/ NCT03276767

Health interventions delivered online (self-guided web-based interventions) may become more helpful through a person-to-program “working alliance.” In psychotherapy, the working alliance signifies a therapeutically useful client–therapist relationship and includes an emotional bond. However, there exist no theories of how program users relate to online programs, or that explain a person-to-program bond theoretically. Addressing this gap, we conducted qualitative interviews with and collected program data from users of a self-guided web-based intervention. Taking a grounded theory approach, the analysis arrived at a model of relating based on two relational modes— making come-alive and keeping un-alive. Different combinations of these modes could describe a range of ways of relating to the program, including a nonsocial interaction, a semi-social interaction, and a semi-social relationship. A person-to-program bond is explained by the model as an experienced supportive social presence, enabled by making come-alive and a positive program interaction.

The aim of this study was to compare the effectiveness of a brief and an intensive self-help alcohol intervention and to assess the feasibility of recruiting to such interventions in a workplace setting. Employees who screened positive for hazardous drinking (n = 85) received online personalized normative feedback and were randomly assigned to one out of two conditions: either they received an e-booklet about the effects of alcohol or they received a self-help intervention comprising 62 web-based, fully automated, and interactive sessions, plus reminder e-mails, and mobile phone text messages (Short Message Service). Two months after baseline, the responders in the intensive condition drank an average of five to six drinks less per week compared to the responders in the brief condition (B = 5.68, 95% CI = 0.48–10.87, P = .03). There was no significant difference between conditions, using baseline observation carried forward imputation (B = 2.96, 95% CI = −0.50–6.42, P = .09). Six months after baseline, no significant difference was found, neither based on complete cases nor intent-to-treat (B = 1.07, 95% CI = −1.29–3.44, P = .37). Challenges with recruitment are thoroughly reported. The study supports the feasibility and the safety of use for both brief and intensive Internet-based self-help in an occupational setting. The study may inform future trials, but due to recruitment problems and low statistical power, the findings are inconclusive in terms of the intensive program being more effective than brief intervention alone. ClinicalTrials.gov Identifier: NCT01931618

There is a need for knowledge about how self-help materials can be made useful in treatment for Substance Abuse Disorders (SUD), as a supplement to ongoing treatment, or as independent tools for change. In this study, we explored the use of self-help films in early addiction treatment, taking into account both patient and therapist perspectives, as well as dyadic functions. We explored how active mechanisms might be related to intervention format and implementation context. A secondary aim was to examine the potential mechanisms related to the specific content of the intervention: mindfulness and acceptance psychoeducation. A qualitative exploratory research design, including a general inductive analytic approach, constructivist grounded theory, and source triangulation features, was used to code and analyze interview material. Emerging themes were developed into concepts, and finally an operational model. Participants included 12 patients and 22 therapists, in in-/outpatient addiction clinics, all in urban areas of Norway. The purpose of the design was empirical grounding of developed concepts, to promote different potential user perspectives (patients’ and therapists’) and obtain process data. The core concept constructed, “Alliance as experiential process,” gives a description of the data where patients and therapists accept or reject the film as a result of an experience process conceptualized as alliance formation. The alliance process model reflects the observation that patients constructed alliances autonomously, while therapists built alliances indirectly through their patients’ experiences. Use of a self-help film may be a helpful adjunct to face-to-face therapy for patients who create a personally meaningful attachment to the film. Mindfulness/acceptance may offer one basic framework for such connection to take place.

Background: Many best practice smoking cessation programs use fully automated internet interventions designed for nonmobile personal computers (desktop computers, laptops, and tablets). A relatively small number of smoking cessation interventions have been designed specifically for mobile devices such as smartphones. Objective: This study examined the efficacy and usage patterns of two internet-based best practices smoking cessation interventions. Methods: Overall, 1271 smokers who wanted to quit were randomly assigned to (1) MobileQuit (designed for—and constrained its use to—mobile devices, included text messaging, and embodied tunnel information architecture) or (2) QuitOnline (designed for nonmobile desktop or tablet computers, did not include text messages, and used a flexible hybrid matrix-hierarchical information architecture). Primary outcomes included self-reported 7-day point-prevalence smoking abstinence at 3- and 6-month follow-up assessments. Program visits were unobtrusively assessed (frequency, duration, and device used for access). Results: Significantly more MobileQuit participants than QuitOnline participants reported quitting smoking. Abstinence rates using intention-to-treat analysis were 20.7% (131/633) vs 11.4% (73/638) at 3 months, 24.6% (156/633) vs 19.3% (123/638) at 6 months, and 15.8% (100/633) vs 8.8% (56/638) for both 3 and 6 months. Using Complete Cases, MobileQuit’s advantage was significant at 3 months (45.6% [131/287] vs 28.4% [73/257]) and the combined 3 and 6 months (40.5% [100/247] vs 25.9% [56/216]) but not at 6 months (43.5% [156/359] vs 34.4% [123/329]). Participants in both conditions reported their program was usable and helpful. MobileQuit participants visited their program 5 times more frequently than did QuitOnline participants. Consistent with the MobileQuit’s built-in constraint, 89.46% (8820/9859) of its visits were made on an intended mobile device, whereas 47.72% (691/1448) of visits to QuitOnline used an intended nonmobile device. Among MobileQuit participants, 76.0% (459/604) used only an intended mobile device, 23.0% (139/604) used both mobile and nonmobile devices, and 0.1% (6/604) used only a nonmobile device. Among QuitOnline participants, 31.3% (137/438) used only the intended nonmobile devices, 16.7% (73/438) used both mobile and nonmobile devices, and 52.1% (228/438) used only mobile devices (primarily smartphones). Conclusions: This study provides evidence for optimizing intervention design for smartphones over a usual care internet approach in which interventions are designed primarily for use on nonmobile devices such as desktop computers, laptops. or tablets. We propose that future internet interventions should be designed for use on all of the devices (multiple screens) that users prefer. We forecast that the approach of designing internet interventions for mobile vs nonmobile devices will be replaced by internet interventions that use a single Web app designed to be responsive (adapt to different screen sizes and operating systems), share user data across devices, embody a pervasive information architecture, and complemented by text message notifications. Trial Registration: ClinicalTrials.gov NCT01952236; https://clinicaltrials.gov/ct2/show/NCT01952236 (Archived by WebCite at http://www.webcitation.org/6zdSxqbf8)

A promising tool for bettering people’s health is eHealth (or “mHealth”) programs: fully automated, web-based health interventions. However, we know surprisingly little about eHealth’s working mechanisms. One possible working mechanism is that program users benefit from a collaborative “relationship”—a “working alliance”—with the program. Although evidence support the existence of a person-to-program alliance it is unclear if and how it influences change. Therefore, we conducted a grounded theory study of how relating to an eHealth program for quitting smoking influenced the participants’ change processes. The ensuing model focuses on how participants got change-space—feeling free from social forcing and able to work constructively on changing—and how the relational processes “making come-alive” and “keeping un-alive” were instrumental in this process. By presenting evidence that relating may influence change in automated therapy, this study supports the person-to-program alliance as a working mechanism in eHealth. This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

Background Face-to-face brief interventions for problem drinking are effective, but they have found limited implementation in routine care and the community. Internet-based interventions could overcome this treatment gap. We investigated effectiveness and moderators of treatment outcomes in internet-based interventions for adult problem drinking (iAIs). Methods and findings Systematic searches were performed in medical and psychological databases to 31 December 2016. A one-stage individual patient data meta-analysis (IPDMA) was conducted with a linear mixed model complete-case approach, using baseline and first follow-up data. The primary outcome measure was mean weekly alcohol consumption in standard units (SUs, 10 grams of ethanol). Secondary outcome was treatment response (TR), defined as less than 14/21 SUs for women/men weekly. Putative participant, intervention, and study moderators were included. Robustness was verified in three sensitivity analyses: a two-stage IPDMA, a one-stage IPDMA using multiple imputation, and a missing-not-at-random (MNAR) analysis. We obtained baseline data for 14,198 adult participants (19 randomised controlled trials [RCTs], mean age 40.7 [SD = 13.2], 47.6% women). Their baseline mean weekly alcohol consumption was 38.1 SUs (SD = 26.9). Most were regular problem drinkers (80.1%, SUs 44.7, SD = 26.4) and 19.9% (SUs 11.9, SD = 4.1) were binge-only drinkers. About one third were heavy drinkers, meaning that women/men consumed, respectively, more than 35/50 SUs of alcohol at baseline (34.2%, SUs 65.9, SD = 27.1). Post-intervention data were available for 8,095 participants. Compared with controls, iAI participants showed a greater mean weekly decrease at follow-up of 5.02 SUs (95% CI −7.57 to −2.48, p < 0.001) and a higher rate of TR (odds ratio [OR] 2.20, 95% CI 1.63–2.95, p < 0.001, number needed to treat [NNT] = 4.15, 95% CI 3.06–6.62). Persons above age 55 showed higher TR than their younger counterparts (OR = 1.66, 95% CI 1.21–2.27, p = 0.002). Drinking profiles were not significantly associated with treatment outcomes. Human-supported interventions were superior to fully automated ones on both outcome measures (comparative reduction: −6.78 SUs, 95% CI −12.11 to −1.45, p = 0.013; TR: OR = 2.23, 95% CI 1.22–4.08, p = 0.009). Participants treated in iAIs based on personalised normative feedback (PNF) alone were significantly less likely to sustain low-risk drinking at follow-up than those in iAIs based on integrated therapeutic principles (OR = 0.52, 95% CI 0.29–0.93, p = 0.029). The use of waitlist control in RCTs was associated with significantly better treatment outcomes than the use of other types of control (comparative reduction: −9.27 SUs, 95% CI −13.97 to −4.57, p < 0.001; TR: OR = 3.74, 95% CI 2.13–6.53, p < 0.001). The overall quality of the RCTs was high; a major limitation included high study dropout (43%). Sensitivity analyses confirmed the robustness of our primary analyses. Conclusion To our knowledge, this is the first IPDMA on internet-based interventions that has shown them to be effective in curbing various patterns of adult problem drinking in both community and healthcare settings. Waitlist control may be conducive to inflation of treatment outcomes., In this meta-analysis using individual patient data from 19 randomised controlled trials, Heleen Riper and colleagues investigate which internet-based interventions for decreasing problem drinking work best and how participant and intervention characteristics moderate the effectiveness of these interventions., Author summary Why was this study done? Global estimations continue to show increasing morbidity, mortality, and social harm caused by all types of problem drinking. Face-to-face brief interventions for problem drinking are effective but rarely used. Internet-based interventions could overcome this treatment gap. We investigated effectiveness and moderators of treatment outcomes in internet-based interventions for adult problem drinking. What did the researchers do and find? We conducted a one-stage individual patient data meta-analysis (IPDMA). This is, to our knowledge, the first study to identify moderators at the participant, intervention, and study design levels that are associated with treatment outcomes in internet-based interventions for adult problem drinking. Our IPDMA included 14,198 adults at baseline from 19 randomised controlled trials who exhibited various profiles of problem drinking. We obtained posttreatment data for 8,095 participants. Our results show that internet-based alcohol interventions in both community and healthcare populations are effective in reducing mean weekly alcohol consumption and in achieving adherence to low-risk drinking limits. We did not find differences in impact related to drinking profiles, meaning that people exceeding risk limits to a smaller or a larger degree benefited from the interventions, as did binge-only drinkers. Human-guided interventions showed a stronger impact on treatment outcome than fully automated ones, but waitlist design controls may inflate outcomes. What do these findings mean? The health gains of internet-based alcohol interventions could be substantial, because such programmes can reach high numbers of problem drinkers by virtue of their swift entry procedures and their easy scalability. Future research should seek to identify categories of people for whom such interventions work best, to analyse how the interventions work and to determine what delivery contexts are most favourable. It should explore which patient populations could benefit most from referral to unguided forms and which would be more amenable to guidance by GPs or other professionals.

UNSTRUCTURED Future development of electronic health (eHealth) programs (automated Web-based health interventions) will be furthered if program design can be based on the knowledge of eHealth’s working mechanisms. A promising and pragmatic method for exploring potential working mechanisms is qualitative interview studies, in which eHealth working mechanisms can be explored through the perspective of the program user. Qualitative interview studies are promising as they are suited for exploring what is yet unknown, building new knowledge, and constructing theory. They are also pragmatic, as the development of eHealth programs often entails user interviews for applied purposes (eg, getting feedback for program improvement or identifying barriers for implementation). By capitalizing on these existing (applied) user interviews to also pursue (basic) research questions of how such programs work, the knowledge base of eHealth’s working mechanisms can grow quickly. To be useful, such interview studies need to be of sufficient quality, which entails that the interviews should generate enough data of sufficient quality relevant to the research question (ie, rich data). However, getting rich interview data on eHealth working mechanisms can be surprisingly challenging, as several of the authors have experienced. Moreover, when encountering difficulties as we did, there are few places to turn to, there are currently no guidelines for conducting such interview studies in a way that ensure their quality. In this paper, we build on our experience as well as the qualitative literature to address this need, by describing 5 challenges that may arise in such interviews and presenting methodological tools to counteract each challenge. We hope the ideas we offer will spark methodological reflections and provide some options for researchers interested in using qualitative interview studies to explore eHealth’s working mechanisms.

mHealth interventions that deliver content via mobile phones represent a burgeoning area of health behavior change. The current paper examines two themes that can inform the underlying design of mHealth interventions: (1) mobile device functionality, which represents the technological toolbox available to intervention developers; and (2) the pervasive information architecture of mHealth interventions, which determines how intervention content can be delivered concurrently using mobile phones, personal computers, and other devices. We posit that developers of mHealth interventions will be able to better achieve the promise of this burgeoning arena by leveraging the toolbox and functionality of mobile devices in order to engage participants and encourage meaningful behavior change within the context of a carefully designed pervasive information architecture.

Purpose This paper reports expert opinion on e-health intervention characteristics that enable effective communication of characteristics across the diverse field of e-health interventions. The paper presents a visualization tool to support communication of the defining characteristics. Methods An initial list of e-health intervention characteristics was developed through an iterative process of item generation and discussion among the 12 authors. The list was distributed to 123 experts in the field, who were emailed an invitation to assess and rank the items. Participants were asked to evaluate these characteristics in three separate ways. Results A total of 50 responses were received for a response rate of 40.7%. Six respondents who reported having little or no expertise in e-health research were removed from the dataset. Our results suggest that 10 specific intervention characteristics were consistently supported as of central importance by the panel of 44 e-intervention experts. The weight and perceived relevance of individual items differed between experts; oftentimes, this difference is a result of the individual theoretical perspective and/or behavioral target of interest. Conclusions The first iteration of the visualization of salient characteristics represents an ambitious effort to develop a tool that will support communication of the defining characteristics for e-health interventions aimed to assist e-health developers and researchers to communicate the key characteristics of their interventions in a standardized manner that facilitates dialog.

PURPOSE: This paper reports expert opinion on e-health intervention characteristics that enable effective communication of characteristics across the diverse field of e-health interventions. The paper presents a visualization tool to support communication of the defining characteristics.METHODS: An initial list of e-health intervention characteristics was developed through an iterative process of item generation and discussion among the 12 authors. The list was distributed to 123 experts in the field, who were emailed an invitation to assess and rank the items. Participants were asked to evaluate these characteristics in three separate ways.RESULTS: A total of 50 responses were received for a response rate of 40.7%. Six respondents who reported having little or no expertise in e-health research were removed from the dataset. Our results suggest that 10 specific intervention characteristics were consistently supported as of central importance by the panel of 44 e-intervention experts. The weight and perceived relevance of individual items differed between experts; oftentimes, this difference is a result of the individual theoretical perspective and/or behavioral target of interest.CONCLUSIONS: The first iteration of the visualization of salient characteristics represents an ambitious effort to develop a tool that will support communication of the defining characteristics for e-health interventions aimed to assist e-health developers and researchers to communicate the key characteristics of their interventions in a standardized manner that facilitates dialog.

Aims To compare a brief versus a brief plus intensive self-help version of ‘Balance’, a fully automated online alcohol intervention, on self-reported alcohol consumption. Design A pragmatic randomized controlled trial. Participants in both conditions received an online single session screening procedure including personalized normative feedback. The control group also received an online booklet about the effects of alcohol. The treatment group received the online multi-session follow-up program, Balance. Setting Online study in Norway. Participants At-risk drinkers were recruited by internet advertisements and assigned randomly to one of the two conditions (n = 244). Measurements The primary outcome was self-reported alcohol consumption the previous week measured 6 months after screening. Findings Regression analysis, using baseline carried forward imputation (intent-to-treat), with baseline variables as covariates, showed that intervention significantly affected alcohol consumption at 6 months (B = 2.96; 95% confidence interval = 0.02–5.90; P = 0.049). Participants in the intensive self-help group drank an average of three fewer standard alcohol units compared with participants in the brief self-help group. Conclusions The online Balance intervention, added to a brief online screening intervention, may aid reduction in alcohol consumption compared with the screening intervention and an educational booklet.

The digital therapy intervention for smoking cessation, ‘Happy Ending’, has been shown to be efficacious in two previous randomised controlled trials. The aim of the current article is to disentangle the rationale of the intervention and describe its development. For this purpose, Intervention Mapping is used as a descriptive tool. The intervention is fully automated and delivered by means of the Internet and mobile phones. It is based on self-regulation theory, social cognitive theory, cognitive–behaviour therapy, motivational interviewing and relapse prevention. The ordering of the content is based on a reasoned chronology, modelled according to psychological processes that people experience at certain time points in a process of therapy-supported self-regulation. The design of the intervention is innovative in that it combines four media channels (SMS, IVR, e-mail, and web), and in the combination of just-in-time therapy and a tunnelling strategy based on the natural chronology of quitting. The two forms of just-in-time therapy are a craving helpline (mainly targeting negative affect), and the provision of relapse therapy based on a daily assessment of the target behaviour. The present article meets the recent calls for more thorough descriptions of interventions, and may inform systematic reviews and the development of interventions.

Aims To assess the long-term efficacy of a fully automated digital multi-media smoking cessation intervention. Design Two-arm randomized control trial (RCT). Setting World Wide Web (WWW) study based in Norway. Participants Subjects (n = 396) were recruited via internet advertisements and assigned randomly to conditions. Inclusion criteria were willingness to quit smoking and being aged 18 years or older. Intervention The treatment group received the internet- and cell-phone-based Happy Ending intervention. The intervention programme lasted 54 weeks and consisted of more than 400 contacts by e-mail, web-pages, interactive voice response (IVR) and short message service (SMS) technology. The control group received a self-help booklet. Additionally, both groups were offered free nicotine replacement therapy (NRT).Measurements Abstinence was defined as ‘not even a puff of smoke, forthelast7days’,andassessedbymeansof internetsurveysortelephoneinterviews.Themainoutcomewasrepeated pointabstinenceat1,3,6and12 monthsfollowingcessation.Findings Participantsinthetreatmentgroupreported clinically and statistically significantly higher repeated point abstinence rates than control participants [22.3% versus 13.1%; odds ratio (OR) = 1.91, 95% confidence interval (CI): 1.12‐3.26, P = 0.02; intent-to-treat). Improved adherence to NRT and a higher level of post-cessation self-efficacy were observed in the treatment group compared with the control group. Conclusions As the first RCT documenting the long-term treatment effects of such an intervention, this study adds to the promise of digital media in supporting behaviour change.

Background: eHealth programs may be better understood by breaking down the components of one particular program and discussing its potential for interactivity and tailoring in regard to concepts from face-to-face counseling. In the search for the efficacious elements within eHealth programs, it is important to understand how a program using lapse management may simultaneously support working alliance, internalization of motivation, and behavior maintenance. These processes have been applied to fully automated eHealth programs individually. However, given their significance in face-to-face counseling, it may be important to simulate the processes simultaneously in interactive, tailored programs. Objective: We propose a theoretical model for how fully automated behavior change eHealth programs may be more effective by simulating a therapist’s support of a working alliance, internalization of motivation, and managing lapses. Methods: We show how the model is derived from theory and its application to Endre, a fully automated smoking cessation program that engages the user in several “counseling sessions” about quitting. A descriptive case study based on tools from the intervention mapping protocol shows how each therapeutic process is simulated. Results: The program supports the user’s working alliance through alliance factors, the nonembodied relational agent Endre and computerized motivational interviewing. Computerized motivational interviewing also supports internalized motivation to quit, whereas a lapse management component responds to lapses. The description operationalizes working alliance, internalization of motivation, and managing lapses, in terms of eHealth support of smoking cessation. Conclusions: A program may simulate working alliance, internalization of motivation, and lapse management through interactivity and individual tailoring, potentially making fully automated eHealth behavior change programs more effective. [J Med Internet Res 2016;18(6):e176]

Background Women in opioid maintenance treatment (OMT) have a past characterized by drug abuse, which is a challenging start for parenthood. Studies of mothers in OMT are typically limited to pregnancy and early infancy. Knowledge about how they cope with substance use and related problems in the years following birth is therefore important. The aims of the study were to examine changes in mothers’ substance use, psychological problems, and other challenges; from one to four years after their children were born, and describe kindergarten attendance and prevalence and type of child protective services involvement when the children were four years old. Method A four-year prospective cohort study of mothers in OMT. The European severity index was used to map substance use and related problems during the third trimester of pregnancy, one and four years after birth. Results At the four-year follow-up, use of illegal substances remained low (4%) and use of legal substances (39%) was similar to the one-year follow-up. The proportion of women with psychological problems was significantly higher than at one-year follow-up (69 vs. 39%, P = .009). At age four, most children (89%) attended kindergarten, and the child protective services were following 73% of the families, mostly with voluntary measures. Conclusion Mothers in OMT cope well with substance use over time, given access to sufficient support. The findings imply that a preventive governmental strategy with close support of mother and child, have a positive impact contributing to making OMT and motherhood more compatible.

BackgroundCurrently, 10-15% of women giving birth suffer from symptoms of postpartum depression. Due to a lack of knowledge of this condition and the stigma associated with it, as well as few treatment options, a large proportion of postpartum women with depression remain untreated. Internet-based interventions have been found effective in treating depression, anxiety, phobias, and addictions. Hence, we developed such program (“Mamma Mia”) with the aim of reducing the risk for postpartum depression and enhance subjective well-being. Mamma Mia is based on positive psychology, metacognitive therapy, and couples therapy. It starts in gestational week 22, and lasts until 6 months after birth. During pregnancy, Mamma Mia is delivered weekly (every Monday). After birth, Mamma Mia is delivered three times per week for six weeks. The remaining weeks, the program is delivered more sporadically. In total, Mamma Mia consists of 44 sessions. The program is individualized, interactive, and tunneled (ie, the user is guided through the program in a pre-determined manner). ObjectiveThe purpose of the present study was to pilot test the intervention in order to assess the feasibility and acceptance among program users. MethodsThe present paper reports a feasibility study that combined quantitative survey data with semi-structured interviews. Participants (N=103) were recruited via hospitals, well-baby clinics, and Facebook. Due to time constraint in completing the current study, our results were based on participation in one of the two phases: pregnancy or maternity. Participants in the pregnancy phase were surveyed 4 and 8 weeks after intervention enrollment, and participants in the postnatal phase were surveyed 2 and 4 weeks after intervention enrollment. The survey assessed perceived usefulness, ease-of-use, credibility, and unobtrusiveness. All measures were filled in by participants at both measurement occasions. Data were analyzed by running descriptives and frequencies with corresponding percentages. Binomial tests were carried out to investigate whether demographics differed significantly from a 50/50 distribution. Paired sample t tests were used to examine differences between time 1 and 2. Four participants were interviewed in the qualitative follow-up study, where they were given the opportunity to address and elaborate on similar aspects as assessed in the survey. ResultsMore than two-thirds of users found Mamma Mia to be of high quality and would recommend Mamma Mia to others. By far, most also found the amount of information and frequency of the intervention schedule to be appropriate. Mamma Mia was perceived as a user-friendly and credible intervention. ConclusionsOverall, the user acceptance of Mamma Mia was good and our findings add to the feasibility of the program. The effect of Mamma Mia on depression and subjective well-being will be evaluated in a large randomized controlled trial, and if found to be effective, Mamma Mia could serve as a low-threshold prevention program.

To compare a brief versus a brief plus intensive self-help version of 'Balance', a fully automated online alcohol intervention, on self-reported alcohol consumption.A pragmatic randomized controlled trial. Participants in both conditions received an online single session screening procedure including personalized normative feedback. The control group also received an online booklet about the effects of alcohol. The treatment group received the online multi-session follow-up program, Balance.Online study in Norway.At-risk drinkers were recruited by internet advertisements and assigned randomly to one of the two conditions (n = 244).The primary outcome was self-reported alcohol consumption the previous week measured 6 months after screening.Regression analysis, using baseline carried forward imputation (intent-to-treat), with baseline variables as covariates, showed that intervention significantly affected alcohol consumption at 6 months (B = 2.96; 95% confidence interval = 0.02-5.90; P = 0.049). Participants in the intensive self-help group drank an average of three fewer standard alcohol units compared with participants in the brief self-help group.The online Balance intervention, added to a brief online screening intervention, may aid reduction in alcohol consumption compared with the screening intervention and an educational booklet.

Background Happy Ending (HE) is an intense 1-year smoking cessation program delivered via the Internet and cell phone. HE consists of more than 400 contacts by email, Web pages, interactive voice response, and short message service technology. HE includes a craving helpline and a relapse prevention system, providing just-in-time therapy. All the components of the program are fully automated. Objective The objectives were to describe the rationale for the design of HE, to assess the 12-month efficacy of HE in a sample of smokers willing to attempt to quit without the use of nicotine replacement therapy, and to explore the potential effect of HE on coping planning and self-efficacy (prior to quitting) and whether coping planning and self-efficacy mediate treatment effect. Methods A two-arm randomized controlled trial was used. Subjects were recruited via Internet advertisements and randomly assigned to condition. Inclusion criteria were willingness to quit on a prescribed day without using nicotine replacement and being aged 18 years or older. The intervention group received HE, and the control group received a 44-page self-help booklet. Abstinence was defined as “not even a puff of smoke, for the last seven days” and was assessed by means of Internet surveys or telephone interviews 1, 3, 6, and 12 months postcessation. The main outcome was repeated point abstinence (ie, abstinence at all four time points). Coping planning and self-efficacy were measured at baseline and at the end of the preparation phase (ie, after 2 weeks of treatment, but prior to cessation day). ResultsA total of 290 participants received either the HE intervention (n=144) or the control booklet (n=146). Using intent-to-treat analysis, participants in the intervention group reported clinically and statistically significantly higher repeated point abstinence rates than control participants (20% versus 7%, odds ratio [OR] = 3.43, 95% CI = 1.60-7.34, P = .002). Although no differences were observed at baseline, by the end of the preparation phase, significantly higher levels of coping planning (t261 = 3.07, P = .002) and precessation self-efficacy (t261 = 2.63, P = .01) were observed in the intervention group compared with the control group. However, neither coping planning nor self-efficacy mediated long-term treatment effect. For point abstinence 1 month after quitting, however, coping planning and self-efficacy showed a partial mediation of the treatment effect. Conclusions This 12-month trial documents a long-term treatment effect of a fully automated smoking cessation intervention without the use of nicotine replacement therapy. The study adds to the promise of using digital media in supporting behavior change.

By mapping critical psychological processes involved in an attempt at behavioral change, we can design digital programs to deliver specific cognitive therapy at the right moments, increasing the probability of successful behavioral change in a variety of domains. This breakthrough, named Digital Therapy, has been proven in random clinical trials to be a cost-effective way for people to achieve lasting behavioral change, with the help of modern psychological science, but without seeing a therapist.

Background As much as 10-15% of new mothers experience depression postpartum. An Internet-based intervention (Mamma Mia) was developed with the primary aims of preventing depressive symptoms and enhancing subjective well-being among pregnant and postpartum women. A secondary aim of Mamma Mia was to ease the transition of becoming a mother by providing knowledge, techniques, and support during pregnancy and after birth. Objective The aim of the paper is to provide a systematic and comprehensive description of the intervention rationale and the development of Mamma Mia. Methods For this purpose, we used the intervention mapping (IM) protocol as descriptive tool, which consists of the following 6 steps: (1) a needs assessment, (2) definition of change objectives, (3) selection of theoretical methods and practical strategies, (4) development of program components, (5) planning adoption and implementation, and (6) planning evaluation. Results Mamma Mia is a fully automated Internet intervention available for computers, tablets, and smartphones, intended for individual use by the mother. It starts in gestational week 18-24 and lasts up to when the baby becomes 6 months old. This intervention applies a tunneled design to guide the woman through the program in a step-by-step fashion in accordance with the psychological preparations of becoming a mother. The intervention is delivered by email and interactive websites, combining text, pictures, prerecorded audio files, and user input. It targets risk and protective factors for postpartum depression such as prepartum and postpartum attachment, couple satisfaction, social support, and subjective well-being, as identified in the needs assessment. The plan is to implement Mamma Mia directly to users and as part of ordinary services at well-baby clinics, and to evaluate the effectiveness of Mamma Mia in a randomized controlled trial and assess users’ experiences with the program. Conclusions The IM of Mamma Mia has made clear the rationale for the intervention, and linked theories and empirical evidence to the contents and materials of the program. This meets the recent calls for intervention descriptions and may inform future studies, development of interventions, and systematic reviews.