A systematic review on experimental studies about patient adherence to treatment.

A better understanding of patients' adherence to treatment is a prerequisite to maximize the benefit of healthcare provision for patients, reduce treatment costs, and is a key factor in a variety of subsequent health outcomes. We aim to understand the state of the art of scientific evidence about which factors influence patients' adherence to treatment. A systematic literature review was conducted using PRISMA guidelines in five separate electronic databases of scientific publications: PubMed, PsycINFO (ProQuest), Cochrane library (Ovid), Google Scholar, and Web of Science. The search focused on literature reporting the significance of factors in adherence to treatment between 2011 and 2021, including only experimental studies (e.g., randomized controlled trials [RCT], clinical trials, etc.). We included 47 experimental studies. The results of the systematic review (SR) are grouped according to predetermined categories of the World Health Organization (WHO): socioeconomic, treatment, condition, personal, and healthcare-related factors. This review gives an actual overview of evidence-based studies on adherence and analyzed the significance of factors defined by the WHO classification. By showing the strength of certain factors in several independent studies and concomitantly uncovering gaps in research, these insights could serve as a basis for the design of future adherence studies and models.

Preferences in the Willingness to Download an mHealth App: Discrete Choice Experimental Study in Spain, Germany, and the Netherlands.

BACKGROUND: Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits for both patients and health care providers, the adoption of mHealth is low, and only a limited number of studies have examined the intention to download mHealth apps. OBJECTIVE: In this study, we investigated individuals' preferences in the adoption of a health app. METHODS: We conducted a discrete choice experimental study in 3 countries (Spain: n=800, Germany: n=800, and the Netherlands: n=416) with 4 different attributes and levels (ie, price: €1.99 vs €4.99 [a currency exchange rate of €1=US $1.09 is applicable] vs for free, data protection: data protection vs no information, recommendation: patients' association vs doctors, and manufacturer: medical association vs pharmaceutical company). Participants were randomly assigned. For the analyses, we used the conditional logistic model separately for each country. RESULTS: The results showed that price and data protection were considered important factors that significantly increased the probability to download an mHealth app. In general, the source of the recommendation and the manufacturer affected the probability to download the mHealth app less. However, in Germany and the Netherlands, we found that if the app was manufactured by a pharmaceutical company, the probability to download the mHealth app decreased. CONCLUSIONS: mHealth tools are highly promising to reduce health care costs and increase the effectiveness of traditional health interventions and therapies. Improving data protection, reducing costs, and creating sound business models are the major driving forces to increase the adoption of mHealth apps in the future. It is thereby essential to create trustworthy standards for mobile apps, whereby prices, legislation concerning data protection, and health professionals can have a leading role to inform the potential consumers.

Differences in healthcare service utilization in patients with polypharmacy according to their risk level by adjusted morbidity groups: a population-based cross-sectional study.

BACKGROUND: Patients with polypharmacy suffer from complex medical conditions involving a large healthcare burden. This study aimed to describe the characteristics and utilization of primary care (PC) and hospital care (HC) and factors associated in chronic patients with polypharmacy, stratifying by adjusted morbidity groups (AMG) risk level, sex and age, and comparing with non-polypharmacy. METHODS: Cross-sectional study conducted in a Spanish basic healthcare area. Studied patients were those over 18 years with chronic diseases identified by the AMG tool from Madrid electronic clinical record, which was the data source. Sociodemographic, sociofunctional, clinical and healthcare utilization variables were described and compared by risk level, sex, age and having or not polypharmacy. Factors associated with healthcare utilization in polypharmacy patients were determined by a negative binomial regression model. RESULTS: In the area studied, 61.3% patients had chronic diseases, of which 16.9% had polypharmacy vs. 83.1% without polypharmacy. Patients with polypharmacy (vs. non-polypharmacy) mean age was 82.7 (vs. 52.7), 68.9% (vs. 60.7%) were women, and 22.0% (vs. 1.2%) high risk. Their average number of chronic diseases was 4.8 (vs. 2.2), and 95.6% (vs. 56.9%) had multimorbidity. Their mean number of annual healthcare contacts was 30.3 (vs. 10.5), 25.9 (vs. 8.8) with PC and 4.4 (vs. 1.7) with HC. Factors associated with a greater PC utilization in patients with polypharmacy were elevated complexity, high risk level and dysrhythmia. Variables associated with a higher HC utilization were also increased complexity and high risk, in addition to male sex, being in palliative care, having a primary caregiver, suffering from neoplasia (specifically lymphoma or leukaemia) and arthritis, whereas older age and immobilization were negatively associated. CONCLUSIONS: Polypharmacy population compared to non-polypharmacy was characterized by a more advanced age, predominance of women, high-risk, complexity, numerous comorbidities, dependency and remarkable healthcare utilization. These findings could help healthcare policy makers to optimize the distribution of resources and professionals within PC and HC systems, aiming for the improvement of polypharmacy management and rational use of medicines while reducing costs attributed to healthcare utilization by these patients.

The impact of labour market shocks on mental health: evidence from the Covid-19 first wave.

In this study, we estimate the effect of a negative labour market shock on individuals' levels of stress, anxiety, and depression. We use a dataset collected during the first wave of the Covid-19 pandemic, on a representative sample of citizens from Italy, Spain, and the United Kingdom, interviewed on three occasions. We measure stress, anxiety and depression and labour shocks using validated scales. Our research design is a standard difference-in-differences model: we leverage the differential timing of shocks to identify the impact on mental health. In our estimations, a negative labour shock increases the measure of stress, anxiety, and depression by 16% of a standard deviation computed from the baseline.

Preferences in the Willingness to Download a COVID-19 Contact Tracing App in the Netherlands and Turkey: Experimental Study.

BACKGROUND: Despite the worldwide growth in using COVID-19 contact tracing apps (CTAs) and the potential benefits for citizens, governments, health care professionals, businesses, and other organizations, only a few studies have examined the factors affecting the levels of willingness to download a CTA. OBJECTIVE: This study aimed to investigate individuals' preferences in the willingness to download a health app. METHODS: We conducted an experimental study in 2 countries, the Netherlands (N=62) and Turkey (N=83), using 4 different vignettes (ie, data protection, manufacturer, reward, and gaming models) with different attributes. Participants were randomly assigned to 1 of the conditions within the vignettes. RESULTS: The results showed that data protection and gaming elements are factors that influence the willingness to download a COVID-19 CTA. More specifically, we see that data protection is an important factor explaining the willingness to download the app in Turkey, whereas including gaming elements significantly affects the willingness to download the app in the Netherlands. CONCLUSIONS: COVID-19 CTAs are highly promising to reduce the spread of the virus and make it easier to open up society faster, especially because they can be used quickly and share information rapidly. COVID-19 CTA developers must ensure that their apps satisfactorily and sufficiently address ethical considerations, even in times of crisis. Furthermore, integrating gaming elements in the CTA could enhance the willingness to download the CTA.

Reducing non-attendance in outpatient appointments: predictive model development, validation, and clinical assessment.

BACKGROUND: Non-attendance to scheduled hospital outpatient appointments may compromise healthcare resource planning, which ultimately reduces the quality of healthcare provision by delaying assessments and increasing waiting lists. We developed a model for predicting non-attendance and assessed the effectiveness of an intervention for reducing non-attendance based on the model. METHODS: The study was conducted in three stages: (1) model development, (2) prospective validation of the model with new data, and (3) a clinical assessment with a pilot study that included the model as a stratification tool to select the patients in the intervention. Candidate models were built using retrospective data from appointments scheduled between January 1, 2015, and November 30, 2018, in the dermatology and pneumology outpatient services of the Hospital Municipal de Badalona (Spain). The predictive capacity of the selected model was then validated prospectively with appointments scheduled between January 7 and February 8, 2019. The effectiveness of selective phone call reminders to patients at high risk of non-attendance according to the model was assessed on all consecutive patients with at least one appointment scheduled between February 25 and April 19, 2019. We finally conducted a pilot study in which all patients identified by the model as high risk of non-attendance were randomly assigned to either a control (no intervention) or intervention group, the last receiving phone call reminders one week before the appointment. RESULTS: Decision trees were selected for model development. Models were trained and selected using 33,329 appointments in the dermatology service and 21,050 in the pneumology service. Specificity, sensitivity, and accuracy for the prediction of non-attendance were 79.90%, 67.09%, and 73.49% for dermatology, and 71.38%, 57.84%, and 64.61% for pneumology outpatient services. The prospective validation showed a specificity of 78.34% (95%CI 71.07, 84.51) and balanced accuracy of 70.45% for dermatology; and 69.83% (95%CI 60.61, 78.00) for pneumology, respectively. The effectiveness of the intervention was assessed on 1,311 individuals identified as high risk of non-attendance according to the selected model. Overall, the intervention resulted in a significant reduction in the non-attendance rate to both the dermatology and pneumology services, with a decrease of 50.61% (p<0.001) and 39.33% (p=0.048), respectively. CONCLUSIONS: The risk of non-attendance can be adequately estimated using patient information stored in medical records. The patient stratification according to the non-attendance risk allows prioritizing interventions, such as phone call reminders, to effectively reduce non-attendance rates.

Effect of Source Type and Protective Message on the Critical Evaluation of News Messages on Facebook: Randomized Controlled Trial in the Netherlands.

BACKGROUND: Disinformation has become an increasing societal concern, especially due to the speed that news is shared in the digital era. In particular, disinformation in the health care sector can lead to serious casualties, as the current COVID-19 crisis clearly shows. OBJECTIVE: The main aim of this study was to experimentally examine the effects of information about the source and a protective warning message on users' critical evaluation of news items, as well as the perception of accuracy of the news item. METHODS: A 3 (unreliable vs reliable vs no identified source) × 2 (with protective message vs without) between-subject design was conducted among 307 participants (mean age 29 (SD 10.9] years). RESULTS: The results showed a significant effect of source information on critical evaluation. In addition, including a protective message did not significantly affect critical evaluation. The results showed no interaction between type of source and protective message on critical evaluation. CONCLUSIONS: Based on these results, it is questionable whether including protective messages to improve critical evaluation is a way to move forward and improve critical evaluation of health-related news items, although effective methodologies to tackle the spread of disinformation are highly needed. TRIAL REGISTRATION: ClinicalTrials.gov NCT05030883; https://clinicaltrials.gov/ct2/show/NCT05030883.

Cost-Effectiveness Assessment of Internet of Things in Smart Cities.

With the ongoing rapid urbanization of city regions and the growing need for (cost-)effective healthcare provision, governments need to address urban challenges with smart city interventions. In this context, impact assessment plays a key role in the decision-making process of assessing cost-effectiveness of Internet of Things-based health service applications in cities, as it identifies the interventions that can obtain the best results for citizens' health and well-being. We present a new methodology to evaluate smart city projects and interventions through the MAFEIP tool, a recent online tool for cost-effectiveness analysis that has been used extensively to test information and communications technology solutions for healthy aging. Resting on the principles of Markov models, the purpose of the MAFEIP tool is to estimate the outcomes of a large variety of social and technological innovations, by providing an early assessment of the likelihood of achieving anticipated impacts through interventions of choice. Thus, the analytical model suggested in this article provides smart city projects with an evidence-based assessment to improve their efficiency and effectivity, by comparing the costs and the efforts invested, with the corresponding results.

Restarting "Normal" Life after Covid-19 and the Lockdown: Evidence from Spain, the United Kingdom, and Italy.

In this article, we examine the expectations of the economic outlook, fear of the future, and behavioural change during the first Covid-19 wave, for three European countries (Spain, the United Kingdom, and Italy) that have been severely hit. We use a novel dataset that we collected to monitor the three countries during the crisis. As outcome variables, we used expectations (e.g., economic outlook, labour market situation, recovery), fear (e.g., scenario of new outburst, economic depression, restriction to individual rights and freedom), and behavioural change across the following dimensions: savings, cultural consumption, social capital, and risky behaviour. We provide descriptive evidence that is representative of the population of interest, and we estimate the impact of exposure to shock occurred during the crisis on the same outcome variables, using matching techniques. Our main findings are the following: we detected systematically negative expectations regarding the future and the recovery, majoritarian fears of an economic depression, a new outbreak, and a permanent restriction on freedom, a reduction in saving and in social capital. Exposure to shocks decreased expected job prospects, increased withdrawal from accumulated savings, and reduced contacts with the network relevant to job advancement, whereas it had inconclusive effects over fears. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11205-021-02697-5.

Guided Internet-Based Cognitive Behavioral Therapy for Depression: Implementation Cost-Effectiveness Study.

BACKGROUND: Major depressive disorder is a chronic condition; its prevalence is expected to grow with the aging trend of high-income countries. Internet-based cognitive-behavioral therapy has proven efficacy in treating major depressive disorder. OBJECTIVE: The objective of this study was to assess the cost-effectiveness of implementing a community internet-based cognitive behavioral therapy intervention (Super@, the Spanish program for the MasterMind project) for treating major depressive disorder. METHODS: The cost-effectiveness of the Super@ program was assessed with the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing tool, using a 3-state Markov model. Data from the cost and effectiveness of the intervention were prospectively collected from the implementation of the program by a health care provider in Badalona, Spain; the corresponding data for usual care were gathered from the literature. The health states, transition probabilities, and utilities were computed using Patient Health Questionnaire-9 scores. RESULTS: The analysis was performed using data from 229 participants using the Super@ program. Results showed that the intervention was more costly than usual care; the discounted (3%) and nondiscounted incremental cost-effectiveness ratios were €29,367 and €26,484 per quality-adjusted life-year, respectively (approximately US $35,299 and $31,833, respectively). The intervention was cost-effective based on the €30,000 willingness-to-pay threshold typically applied in Spain (equivalent to approximately $36,060). According to the deterministic sensitivity analyses, the potential reduction of costs associated with intervention scale-up would reduce the incremental cost-effectiveness ratio of the intervention, although it remained more costly than usual care. A discount in the incremental effects up to 5% exceeded the willingness-to-pay threshold of €30,000. CONCLUSIONS: The Super@ program, an internet-based cognitive behavioral therapy intervention for treating major depressive disorder, cost more than treatment as usual. Nevertheless, its implementation in Spain would be cost-effective from health care and societal perspectives, given the willingness-to-pay threshold of €30,000 compared with treatment as usual.

Cost-utility analysis of a consensus and evidence-based medication review to optimize and potentially reduce psychotropic drug prescription in institutionalized dementia patients.

BACKGROUND: Growing evidence shows the effects of psychotropic drugs on the evolution of dementia. Until now, only a few studies have evaluated the cost-effectiveness of psychotropic drugs in institutionalized dementia patients. This study aims to assess the cost-utility of intervention performed in the metropolitan area of Barcelona (Spain) (MN) based on consensus between specialized caregivers involved in the management of dementia patients for optimizing and potentially reducing the prescription of inappropriate psychotropic drugs in this population. This analysis was conducted using the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing (MAFEIP) tool. METHODS: The MAFEIP tool builds up from a variety of surrogate endpoints commonly used across different studies in order to estimate health and economic outcomes in terms of incremental changes in quality adjusted life years (QALYs), as well as health and social care utilization. Cost estimates are based on scientific literature and expert opinion; they are direct costs and include medical visits, hospital care, medical tests and exams and drugs administered, among other concepts. The healthcare costs of patients using the intervention were calculated by means of a medication review that compared patients' drug-related costs before, during and after the use of the intervention conducted in MN between 2012 and 2014. The cost-utility analysis was performed from the perspective of a health care system with a time horizon of 12 months. RESULTS: The tool calculated the incremental cost-effectiveness ratio (ICER) of the intervention, revealing it to be dominant, or rather, better (more effective) and cheaper than the current (standard) care. The ICER of the intervention was in the lower right quadrant, making it an intervention that is always accepted even with the lowest given Willingness to Pay (WTP) threshold value (€15,000). CONCLUSIONS: The results of this study show that the intervention was dominant, or rather, better (more effective) and cheaper than the current (standard) care. This dominant intervention is therefore recommended to interested investors for systematic application.

Negative shocks predict change in cognitive function and preferences: assessing the negative affect and stress hypothesis.

In the context of the current COVID-19 pandemic, households throughout the world have to cope with negative shocks. Previous research has shown that negative shocks impair cognitive function and change risk, time and social preferences. In this study, we analyze the results of a longitudinal multi-country survey conducted in Italy (N = 1652), Spain (N = 1660) and the United Kingdom (N = 1578). We measure cognitive function using the Cognitive Reflection Test and preferences traits (risk, time and social preferences) using an experimentally validated set of questions to assess the differences between people exposed to a shock compared to the rest of the sample. We measure four possible types of shocks: labor market shock, health shock, occurrence of stressful events, and mental health shock. Additionally, we randomly assign participants to groups with either a recall of negative events (more specifically, a mild reinforcement of stress or of fear/anxiety), or to a control group (to recall neutral or joyful memories), in order to assess whether or not stress and negative emotions drive a change in preferences. Results show that people affected by shocks performed worse in terms of cognitive functioning, are more risk loving, and are more prone to punish others (negative reciprocity). Data do not support the hypotheses that the result is driven by stress or by negative emotions.

Assessing concerns for the economic consequence of the COVID-19 response and mental health problems associated with economic vulnerability and negative economic shock in Italy, Spain, and the United Kingdom.

Many different countries have been under lockdown or extreme social distancing measures to control the spread of COVID-19. The potentially far-reaching side effects of these measures have not yet been fully understood. In this study we analyse the results of a multi-country survey conducted in Italy (N = 3,504), Spain (N = 3,524) and the United Kingdom (N = 3,523), with two separate analyses. In the first analysis, we examine the elicitation of citizens' concerns over the downplaying of the economic consequences of the lockdown during the COVID-19 pandemic. We control for Social Desirability Bias through a list experiment included in the survey. In the second analysis, we examine the data from the same survey to predict the level of stress, anxiety and depression associated with being economically vulnerable and having been affected by a negative economic shock. To accomplish this, we have used a prediction algorithm based on machine learning techniques. To quantify the size of this affected population, we compare its magnitude with the number of people affected by COVID-19 using measures of susceptibility, vulnerability and behavioural change collected in the same questionnaire. We find that the concern for the economy and for "the way out" of the lockdown is diffuse and there is evidence of minor underreporting. Additionally, we estimate that around 42.8% of the populations in the three countries are at high risk of stress, anxiety, and depression, based on their level of economic vulnerability and their exposure to a negative economic shock.

BeyondSilos, a Telehealth-Enhanced Integrated Care Model in the Domiciliary Setting for Older Patients: Observational Prospective Cohort Study for Effectiveness and Cost-Effectiveness Assessments.

BACKGROUND: Information and communication technology may provide domiciliary care programs with continuity of care. However, evidence about the effectiveness and cost-effectiveness of information and communication technology in the context of integrated care models is relatively scarce. OBJECTIVE: The objective of our study was to provide evidence on the clinical effectiveness and cost-effectiveness of the BeyondSilos project for patients enrolled in the Badalona city pilot site in Spain. METHODS: A quasi-experimental study was used to assess the cost-effectiveness of information and communication technology-enhanced integration of health and social care, including the third sector (intervention), compared to basic health and social care coordination (comparator). The study was conducted in Badalona between 2015 and 2016. Participants were followed for 8 months. RESULTS: The study included 198 patients: 98 in the intervention group and 100 in the comparator group. The mean Barthel index remained unchanged in the intervention group (mean change 0.14, 95% CI -4.51 to 4.78; P=.95) but decreased in the comparator group (mean change -3.23, 95% CI -5.34 to -1.11; P=.003). Instrumental Activities of Daily Living significantly decreased in both groups: mean changes of -0.23 (95% CI -0.44 to -0.02; P=.03) and -0.33 (95% CI -0.46 to -0.20; P<.001) in the intervention and comparator groups, respectively. No differences were found in the Geriatric Depression Scale (intervention: mean change 0.28, 95% CI -0.44 to 1.01, P=.44; comparator: mean change -0.29, 95% CI -0.59 to 0.01, P=.06). The intervention showed cost-effectiveness (incremental cost-effectiveness ratio €6505.52, approximately US $7582). CONCLUSIONS: The information and communication technology-enhanced integrated domiciliary care program was cost-effective. The beneficial effects of this approach strongly rely upon the commitment of the professional staff involved. TRIAL REGISTRATION: ClinicalTrials.gov NCT03111004; http://clinicaltrials.gov/ct2/show/ NCT03111004.

Changing the Health Behavior of Patients With Cardiovascular Disease Through an Electronic Health Intervention in Three Different Countries: Cost-Effectiveness Study in the Do Cardiac Health: Advanced New Generation Ecosystem (Do CHANGE) 2 Randomized Controlled Trial.

BACKGROUND: During the last few decades, preventing the development of cardiovascular disease has become a mainstay for reducing cardiovascular morbidity and mortality. It has been suggested that interventions should focus more on committed approaches of self-care, such as electronic health techniques. OBJECTIVE: This study aimed to provide evidence to understand the financial consequences of implementing the "Do Cardiac Health: Advanced New Generation Ecosystem" (Do CHANGE 2) intervention, which was evaluated in a multisite randomized controlled trial to change the health behavior of patients with cardiovascular disease. METHODS: The cost-effectiveness analysis of the Do CHANGE 2 intervention was performed with the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing tool, based on a Markov model of five health states. The following two types of costs were considered for both study groups: (1) health care costs (ie, costs associated with the time spent by health care professionals on service provision, including consultations, and associated unplanned hospitalizations, etc) and (2) societal costs (ie, costs attributed to the time spent by patients and informal caregivers on care activities). RESULTS: The Do CHANGE 2 intervention was less costly in Spain (incremental cost was -€2514.90) and more costly in the Netherlands and Taiwan (incremental costs were €1373.59 and €1062.54, respectively). Compared with treatment as usual, the effectiveness of the Do CHANGE 2 program in terms of an increase in quality-adjusted life-year gains was slightly higher in the Netherlands and lower in Spain and Taiwan. CONCLUSIONS: In general, we found that the incremental cost-effectiveness ratio strongly varied depending on the country where the intervention was applied. The Do CHANGE 2 intervention showed a positive cost-effectiveness ratio only when implemented in Spain, indicating that it saved financial costs in relation to the effect of the intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT03178305; https://clinicaltrials.gov/ct2/show/NCT03178305.

Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study.

BACKGROUND: Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits of mHealth for patients and health care providers, scientific research examining factors explaining the adoption level of mHealth tools remains scarce. OBJECTIVE: We performed an experimental vignette study to investigate how four factors related to the business model of an mHealth app affect its adoption and users' willingness to pay: (1) the revenue model (ie, sharing data with third parties vs accepting advertisements); (2) the data protection model (General Data Protection Regulation [GDPR]-compliant data handling vs nonGDPR-compliant data handling); (3) the recommendation model (ie, doctor vs patient recommendation); and (4) the provider model (ie, pharmaceutical vs medical association provider). In addition, health consciousness, health information orientation, and electronic health literacy were explored as intrapersonal predictors of adoption. METHODS: We conducted an experimental study in three countries, Spain (N=800), Germany (N=800), and the Netherlands (N=416), to assess the influence of multiple business models and intrapersonal characteristics on the willingness to pay and intention to download a health app. RESULTS: The revenue model did not affect willingness to pay or intentions to download the app in all three countries. In the Netherlands, data protection increased willingness to pay for the health app (P<.001). Moreover, in all three countries, data protection increased the likelihood of downloading the app (P<.001). In Germany (P=.04) and the Netherlands (P=.007), a doctor recommendation increased both willingness to pay and intention to download the health app. For all three countries, apps manufactured in association with a medical organization were more likely to be downloaded (P<.001). Finally, in all three countries, men, younger individuals, those with higher levels of education, and people with a health information orientation were willing to pay more for adoption of the health app and had a higher intention to download the app. CONCLUSIONS: The finding that people want their data protected by legislation but are not willing to pay more for data protection suggests that in the context of mHealth, app privacy protection cannot be leveraged as a selling point. However, people do value a doctor recommendation and apps manufactured by a medical association, which particularly influence their intention to download an mHealth app.

An mHealth intervention for the treatment of patients with an eating disorder: A multicenter randomized controlled trial.

OBJECTIVE: The current multicentre randomized controlled trial assessed the clinical efficacy of a combined mHealth intervention for eating disorders (EDs) based on cognitive behavioral therapy (CBT). METHOD: A total of 106 ED patients from eight different public and private mental health services in Spain were randomly assigned to two parallel groups. Patients of the experimental group (N = 53) received standard face-to-face CBT plus a mobile intervention through an application called "TCApp," which provides self-monitoring and an online chat with the therapist. The control group (N = 53) received standard face-to-face CBT only. Patients completed self-report questionnaires on ED symptomatology, anxiety, depression, and quality of life, before and after treatment. RESULTS: Significant reductions in primary and secondary outcomes were observed for participants of both groups, with no differences between groups. Results also suggested that the frequency with which patients attended their referral mental health institution after the intervention was lower for patients in the experimental group than for those in the control group. DISCUSSION: The current study showed that CBT can help to reduce symptoms relating to ED, regardless of whether its delivery includes online components in addition to traditional face-to-face treatment. Besides, the additional component offered by the TCApp does not appear to be promising from a purely therapeutic perspective but perhaps as a cost-effective tool, reducing thus the costs and time burden associated with weekly visits to health professionals.

Mobile Health Adoption in Mental Health: User Experience of a Mobile Health App for Patients With an Eating Disorder.

BACKGROUND: Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits for both patients and health care providers, the overall adoption levels of mHealth tools by health professionals remain relatively low. OBJECTIVE: This study aimed (1) to investigate attitudes of health care providers and mHealth experts toward mHealth tools in the health context in general, and this study aimed (2) to test the acceptability and feasibility of a specific mHealth tool for patients with an eating disorder (ED), called TCApp, among patients and ED specialists. METHODS: To this purpose, we conducted an explorative qualitative study with 4 in-depth group discussions with several groups of stakeholders: our first focus group was conducted with 11 experts on mHealth from the Catalan Association of Health Entities; the second focus group included 10 health care professionals from the Spanish College of Doctors of Barcelona; the third focus group involved 9 patients with an ED who had used the TCApp over a 12-week period, and the fourth and last focus group involved 8 ED specialists who had monitored such ED patients on the Web. RESULTS: The focus groups showed that health care providers and mHealth experts reported barriers for mHealth adoption more often than facilitators, indicating that mHealth techniques are difficult to obtain and use. Most barriers were attributed to external factors relating to the human or organizational environment (ie, lack of time because of workload, lack of direct interest on a legislative or political level) rather than being attributed to internal factors relating to individual obstacles. The results of the mHealth intervention study indicate that the TCApp was considered as easy to use and useful, although patients and the ED specialists monitoring them on the Web reported different adoption problems, such as the inability to personalize the app, a lack of motivational and interactive components, or difficulties in adhering to the study protocol. CONCLUSIONS: In general, this paper indicates that both health professionals and patients foresee difficulties that need to be addressed before comprehensive adoption and usage of mHealth techniques can be effectively implemented. Such findings are in line with previous studies, suggesting that although they acknowledge their possible benefits and cost-effectiveness, health care providers are quite resistant and conservative about integrating mHealth technologies in their daily practice.

A systematic review of mHealth interventions for the support of eating disorders.

OBJECTIVE: To systematically review the existing evidence of mobile health (mHealth) tools for the treatment of eating disorders (ED). METHOD: Electronic databases (Pubmed, PsycInfo, and SCOPUS) were searched, and PRISMA guidelines were followed. Selected studies were divided into three categories according to the intended purpose of the mHealth tools used: (a) sole means of support, (b) complementary to standard face-to-face treatment, and (c) for relapse prevention. Additionally, studies were assessed on efficacy, qualitative information, and methodological quality. RESULTS: Fifteen studies were identified. Most studies using mHealth as a sole means of intervention or adjunct to traditional therapy showed no effects, although an improvement at postassessment was present in vodcast, smartphone application, and text-messaging interventions. Between group effects were only found for a text-messaging intervention for relapse prevention. Qualitative analyses showed that most mHealth interventions were considered as acceptable, supporting, and motivating by patients and therapists, although different important problems were observed in individual studies. CONCLUSIONS: Limited effects were found for mHealth interventions to reduce ED-related symptoms. A common evaluation framework for ED mHealth interventions should be proposed to assess the validity of interventions before implementing them on a larger scale in clinical practice.

Electronic Health Use in the European Union and the Effect of Multimorbidity: Cross-Sectional Survey.

BACKGROUND: Multimorbidity is becoming increasingly common and is a leading challenge currently faced by societies with aging populations. The presence of multimorbidity requires patients to coordinate, understand, and use the information obtained from different health care professionals, while simultaneously striving to distinguish the symptoms of different diseases and self-manage their sometimes conflicting health problems. Electronic health (eHealth) tools provide a means to disseminate health information and education for both patients and health professionals and hold promise for more efficient and cost-effective care processes. OBJECTIVE: The aim of this study was to analyze the use of eHealth tools, taking into account the citizens' sociodemographic and clinical characteristics, and above all, the presence of multimorbidity. METHODS: Cross-sectional and exploratory research was conducted using online survey data from July 2011 to August 2011. Participants included a total of 14,000 citizens from 14 European countries aged 16 to 74 years, who had used an eHealth tool in the past 3 months. The variables studied were sociodemographic variables of the participants, the questionnaire items assessing the frequency of using eHealth tools, the degree of morbidity, and the eHealth adoption gradient. Chi-square tests were conducted to examine the relationship between the sociodemographic and clinical variables of participants and the group the participants were assigned to according to their frequency of eHealth use (eHealth user group). A one-way analysis of variance (ANOVA) allowed for assessing the differences in the eHealth adoption gradient average between different groups of individuals according to their morbidity level. A two-way between-groups ANOVA was performed to explore the effects of multimorbidity and age group on the eHealth adoption gradient. RESULTS: According to the eHealth adoption gradient, most participants (68.15%, 9541/14,000) were labeled as rare users, with the majority of them (55.1%, 508/921) being in the age range of 25 to 54 years, with upper secondary education (50.3%, 464/921), currently employed (49.3%, 454/921), and living in medium-sized cities (40.7%, 375/921). Results of the one-way ANOVA showed that the number of health problems significantly affected the use of eHealth tools (F2,13996=11.584; P<.001). The two-way ANOVA demonstrated that there was a statistically significant interaction between the effects of age and number of health problems on the eHealth adoption gradient (F4,11991=7.936; P<.001). CONCLUSIONS: The eHealth adoption gradient has proven to be a reliable way to measure different aspects of eHealth use. Multimorbidity is associated with a more intense use of eHealth, with younger Internet users using new technologies for health purposes more frequently than older groups with the same level of morbidity. These findings suggest the need to consider different strategies aimed at making eHealth tools more sensitive to the characteristics of older populations to reduce digital disadvantages.