Technology-based mental healthcare models: A systematic review of the literature | Revista Colombiana de Psiquiatría (English Edition)

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Bartels, Carlos Gómez-Restrepo" "autores" => array:8 [ 0 => array:4 [ "nombre" => "Juan Camilo" "apellidos" => "Rosas" "email" => array:1 [ 0 => "rosas.juan@javeriana.edu.co" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "María Camila" "apellidos" => "Gómez-Ayala" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "Arturo Marroquín" "apellidos" => "Rivera" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 3 => array:3 [ "nombre" => "Felipe" "apellidos" => "Botero-Rodríguez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "Magda" "apellidos" => "Cepeda" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 5 => array:3 [ "nombre" => "Fernando" "apellidos" => "Suárez-Obando" "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] ] ] 6 => array:3 [ "nombre" => "Sophie M." "apellidos" => "Bartels" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "d" "identificador" => "aff0020" ] ] ] 7 => array:3 [ "nombre" => "Carlos" "apellidos" => "Gómez-Restrepo" "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] 2 => array:2 [ "etiqueta" => "e" "identificador" => "aff0025" ] ] ] ] "afiliaciones" => array:5 [ 0 => array:3 [ "entidad" => "Departamento de Epidemiología Clínica y Bioestadística, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Instituto de Genética Humana, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Hospital Universitario San Ignacio, Bogotá, Colombia" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Center for Technology and Behavioral Health, Departamento de Psiquiatría, Geisel School of Medicine at Dartmouth College, United States" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Departamento de Psiquiatría y Salud Mental, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia" "etiqueta" => "e" "identificador" => "aff0025" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Modelos de atención en salud mental basados en tecnologías: Revisión sistemática de la literatura" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1697 "Ancho" => 1508 "Tamanyo" => 179038 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "PRISMA flow chart." ] ] ] "textoCompleto" => "IntroductionMental health is essential to well-being; nevertheless, low-income and medium-income countries not only lack trained staff, management guidelines and infrastructure,<a class="elsevierStyleCrossRefs" href="#bib0005">1–3</a> but also face barriers such as inequities in resource distribution.<a class="elsevierStyleCrossRefs" href="#bib0020">4,5</a> Hence, international organisations such as the World Health Organization (WHO) and the Pan American Health Organization (PAHO) have made proposals such as the Mental Health Gap Action Programme (mhGAP)<a class="elsevierStyleCrossRef" href="#bib0030">6</a> in order to raise awareness of mental health. Some countries have leveraged these strategies to launch national care plans specifically for mental health conditions. One example in Latin America is Chile, which has a national model for detection, diagnosis and treatment of depression based on technology use.<a class="elsevierStyleCrossRef" href="#bib0035">7</a>The use of technological tools for health is more than a growing trend around the world. It has demonstrated its potential to improve the efficiency of the use of mental health resources.<a class="elsevierStyleCrossRefs" href="#bib0040">8,9</a> This is primarily due to its contributions to breaking down barriers to access to services, increasing coverage, making treatments more flexible, decreasing perceived stigma and increasing user commitment, among other things. Technology may be involved at different points in care (screening, diagnosis, treatment and follow-up) in both primary care and specialised medicine settings.<a class="elsevierStyleCrossRefs" href="#bib0050">10,11</a> Some examples of such integration are currently under development in Colombia.<a class="elsevierStyleCrossRefs" href="#bib0040">8,10</a>Although the use of technologies has proven quite effective in the management of mental health disorders, these tend to be insufficient interventions when made in isolation from other elements of care.<a class="elsevierStyleCrossRef" href="#bib0060">12</a> Therefore, the proposal of a "care model" incorporating components of technology, mental health and primary care has gained traction as a strategy for addressing shortcomings in and barriers to managing these health conditions.The concept of a model refers to a systematic process that includes actions from the admission of the patient to the healthcare service-providing institution and also includes phases of screening, diagnosis, treatment, follow-up and referral, always in accordance with the needs of the community.<a class="elsevierStyleCrossRef" href="#bib0065">13</a>Taking all of this into account, the main objective of this review was to describe and synthesise the existing evidence on implementing technology-based care models in addressing mental health disorders in the primary care context in order to specifically evaluate the clinical effectiveness of those models, as well as other pertinent outcomes.MethodsInclusion criteria for studiesTypes of studyRandomised controlled trials (RCTs), before-and-after studies (with or without a control group), interrupted time series (ITS) studies and studies with any other type of prospective design that met the eligibility criteria were included. The studies selected could measure outcomes by comparing institutions or examining a single institution before and after implementation. Mixed-methods studies were included if they evaluated any of the outcomes identified. Strictly qualitative studies were excluded. No studies were excluded on the basis of language or year of publication.PopulationResearch units corresponded to health centres where technology-based models were implemented. No other restrictions in relation to the sociodemographic characteristics of the population that received care at those centres were applied.InterventionsImplementation of models focused on the use of technological or digital tools such as smartphones, tablets, Internet use or apps on other devices, developed in primary care contexts for screening, diagnosis, treatment or follow-up of mental health conditions.Studies that reported interventions implemented in contexts other than primary care, such as psychiatric hospitals; studies with the main objective of examining outcomes in healthcare professionals; and studies that used technologies solely as a communication medium (e.g. telephone calls) were excluded.Outcomes<ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005">-Clinical effectiveness (measurement of symptoms using validated instruments).</li><li class="elsevierStyleListItem" id="lsti0010">-Treatment adherence (continuity in the use of technological tools provided by the model).</li><li class="elsevierStyleListItem" id="lsti0015">-Costs (change in care before and after implementation or between intervention and control group).</li><li class="elsevierStyleListItem" id="lsti0020">-Reach of the model (number of participants enrolled compared to total number of eligible individuals) and response rate (patients who continued with the recommendations or management proposed by the model).</li></ul>Search for and identification of studies and data extractionThe systematic search was conducted in six electronic databases (CENTRAL, MEDLINE, EMBASE, PsycINFO, Web of Science and Virtual Health Library [VHL]) and updated until August 2019. The search strategy appears in Appendix 1. Studies were also found by reviewing cross-references included in the articles identified.Two review groups, Arturo Marroquín-Rivera and Juan Camilo Rosas (AMR and JCR) and María Gómez-Ayala and Felipe Botero-Rodríguez (MGA and FBR), independently screened the articles found based on their titles and abstracts and selected the studies that met the eligibility criteria based on their full texts. Where they disagreed, they consulted a third-party researcher (MC). To screen and select the articles, the Rayyan QCRI<a class="elsevierStyleCrossRef" href="#bib0070">14</a> web app was used to facilitate the process of classification of references and discussion. Two authors, AMR and JCR, independently extracted the data from the studies selected using a data extraction form specifically for this review and resolved discrepancies by referring to the original text.Data analysisEvaluation of risk of biasDue to the differences in design among the studies included, domains of the Cochrane tool to evaluate risk of bias (RoB 2) and the "Risk Of Bias In Non-randomized Studies - of Interventions" (ROBINS-I) tool to assess non-randomised studies were adapted. The domains considered were: bias due to confounding/randomisation, bias in selection, bias in classification, lost in follow-up, bias in measurement and bias in selection of the reported result.For the heterogeneity analysis, differences among the studies were sought and explained in narrative form.Data synthesisThe studies included varied greatly in terms of study design, target population, interventions and comparators used, instruments of measurement, and points for follow-up and evaluation of outcomes. Taking this into account, the performance of a meta-analysis of the results obtained was not a viable option. As a result, data synthesis was performed based on narrative summaries. In addition, the models identified were summarised in terms of four stages: 1) screening, 2) diagnostic confirmation, 3) treatment and 4) follow-up (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).<elsevierMultimedia ident="fig0005"></elsevierMultimedia>ResultsSearch resultsThe literature search yielded a total of 6753 references; five of them met the eligibility criteria and therefore were included for analysis in the review.<a class="elsevierStyleCrossRefs" href="#bib0075">15–19</a><a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a> summarises the search results. The most common reasons why studies were excluded in the screening process were that they did not meet the definition for a care model sought by the researchers or that they did not report outcomes of interest.<elsevierMultimedia ident="fig0010"></elsevierMultimedia>Evaluation of risk of biasSeveral of the studies included had components in addition to implementation outcomes; hence, in accordance with our objectives, only the evaluation of treatment effectiveness and adherence were taken into account in evaluating bias.Among the five studies included, the sole RCT<a class="elsevierStyleCrossRef" href="#bib0085">17</a> showed various biases due to confounding (participant screening and randomisation), with intervention blinding and bias in measurement of outcomes. In addition, baseline differences were detected among patient groups, including variations in level of education, age and prevalence of depression and post-traumatic stress disorder (PTSD). Taking this into account and adding it to the possible influence of each provider on the outcomes of interest, the study was considered to carry a high risk of bias. The four remaining articles corresponded to non-randomised studies seen to be compromised in their entirety by biases due to confounding and, to a lesser extent, bias in measurement of outcomes.Data extractionGeneral characteristics of the studiesThe five articles selected were published between 2017 and 2019. All of them enrolled elderly individuals only; four screened the general population who visited the health centre<a class="elsevierStyleCrossRefs" href="#bib0075">15–18</a> and one screened patients with a history of psychoactive substance use.<a class="elsevierStyleCrossRef" href="#bib0095">19</a>The studies included screened different aspects of mental health, except the Allillanchu study,<a class="elsevierStyleCrossRef" href="#bib0075">15</a> which also evaluated seizure disorder. The most commonly examined diseases were anxiety and depression; these figured in four of the studies.<a class="elsevierStyleCrossRefs" href="#bib0075">15–18</a> Other matters evaluated were psychoactive substance use and alcohol use,<a class="elsevierStyleCrossRefs" href="#bib0075">15,19</a> quality of life,<a class="elsevierStyleCrossRef" href="#bib0095">19</a> PTSD,<a class="elsevierStyleCrossRef" href="#bib0085">17</a> risk of suicide<a class="elsevierStyleCrossRef" href="#bib0075">15</a> and related problems such as stigma, which influences the implementation of, adherence to and impact of interventions.<a class="elsevierStyleCrossRef" href="#bib0090">18</a> Among the symptom evaluation tools used, the most common were the PHQ-9 scale<a class="elsevierStyleCrossRef" href="#bib0090">18</a> and the GAD-7 scale<a class="elsevierStyleCrossRefs" href="#bib0080">16,18</a> (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>Stages of the model and technologies usedScreeningOf the five studies included, four conducted screening through electronic tablets.<a class="elsevierStyleCrossRefs" href="#bib0075">15–18</a> Two of these specified that they used special apps to administer the questionnaires;<a class="elsevierStyleCrossRefs" href="#bib0075">15,18</a> the other two did not.<a class="elsevierStyleCrossRefs" href="#bib0080">16,17</a> Regarding context, three of the studies conducted screening in a clinical/urban environment<a class="elsevierStyleCrossRefs" href="#bib0085">17–19</a> and the fourth conducted screening directly in the homes of potential participants and in a rural setting.<a class="elsevierStyleCrossRef" href="#bib0090">18</a>In the Sorkin et al. study,<a class="elsevierStyleCrossRef" href="#bib0085">17</a> the intervention had three main components: 1) an online tutorial for mental health management focused on trauma; 2) tablet-enhanced screening of all patients prior to medical consultation; and 3) provision of algorithms and guidelines to medical staff through mobile platforms. In the experimental group, healthcare providers were given the score for all patients who completed electronic screening; in the control group, physicians only received scores for cases at high risk of self-aggressiveness or hetero-aggressiveness. The proportion of diagnoses made by medical staff was significantly higher in the experimental group than in the control group, both for depression (OR: 6.5; 95% confidence interval [CI]: 1.48–28,79) and for PTSD (OR: 23.3; 95% CI: 2.99–151.62).<a class="elsevierStyleCrossRef" href="#bib0085">17</a> The three remaining studies corresponded to uncontrolled research lacking comparative measurements in this stage.The Strengthening Mental Health and Research Training in Africa (SMART) project,<a class="elsevierStyleCrossRef" href="#bib0090">18</a> implemented in India, developed a task distribution system in which accredited social health activists (ASHAs) conducted screening for depression and anxiety in the target population and advised patients with positive results to get counselling with physicians in health camps.DiagnosisTwo studies implemented a diagnosis stage in previously screened patients. Both carried out that stage using clinical practice algorithms and guidelines for patient diagnosis, which were available in mobile apps installed on tablets.<a class="elsevierStyleCrossRefs" href="#bib0085">17,18</a> With regard to Sorkin et al.,<a class="elsevierStyleCrossRef" href="#bib0085">17</a> clinical decision-making was based on an 11-point algorithm designed to diagnose major depression and PTSD. At the end of the intervention, the proportion of patients who received a diagnosis of either of the two diseases in the intervention group was compared to the same proportion in the control group. The participants in the intervention group were 2.6 times more likely to have a diagnosis consistent with their screening compared to the control group.TreatmentAll five studies included a stage related to patient treatment linked to a technological/digital strategy. Two used mobile apps with modules and strategies as treatment aids<a class="elsevierStyleCrossRefs" href="#bib0080">16,19</a>; another two used management algorithms through digital platforms<a class="elsevierStyleCrossRefs" href="#bib0005">1,18</a> and one designed an automated system to deliver motivational text messages (SMS) to incentivise consultation with mental health specialists.<a class="elsevierStyleCrossRef" href="#bib0075">15</a>Regarding the two studies that used apps in the treatment stage,<a class="elsevierStyleCrossRefs" href="#bib0080">16,19</a> the study by Quanbeck et al.<a class="elsevierStyleCrossRef" href="#bib0095">19</a> evaluated how mobile health technologies facilitated integration of treatment for addiction into primary care. The Seva app offered patients interactive modules for learning how to solve problems and self-regulate, tools for coping with high-risk situations, and cognitive behavioural therapy strategies, among other things. The Lantern intervention consisted of a mobile app that provided the patient with a cognitive behavioural programme based on protocols for people with generalised anxiety disorder (GAD). Both studies collected data on app use, including logins and use of modules.With regard to the two studies that used management algorithms on digital devices, both were developed based on evidence-based and culturally validated scales and guidelines for management. In the SMART study,<a class="elsevierStyleCrossRef" href="#bib0090">18</a> patients diagnosed with mental illness received psychotherapy from healthcare professionals affiliated with the study or were referred to hospitals able to provide more complex care. Regarding the Sorkin et al. study,<a class="elsevierStyleCrossRef" href="#bib0085">17</a> patients were managed using the digital algorithms designed in the intervention group or were managed as usual in the control group. Participation by physicians could encompass aspects such as pharmacotherapy, active surveillance with psychosocial support and referral to a mental health specialist. Whereas in the SMART study the treatment provided was not evaluated in detail in relation to the management algorithms, in the Sorkin study these were primary outcomes that were evaluated by means of review of medical records after the care model had been implemented for 12 weeks.Finally, the Allillanchu study<a class="elsevierStyleCrossRef" href="#bib0075">15</a> did not include a direct treatment, but did implement a text message system with the aim of increasing specialised medical consultations among patients identified in primary care.Follow-upThe five studies included reported data on patient follow-up during the implementation of the models. Concerning the strategies used, one study conducted interviews with participants to enquire about specialised medical consultations,<a class="elsevierStyleCrossRef" href="#bib0075">15</a> one study optimised the follow-up stage using digital algorithms and automated voice messages,<a class="elsevierStyleCrossRef" href="#bib0090">18</a> another followed up patients by means of messages through a mobile app,<a class="elsevierStyleCrossRef" href="#bib0080">16</a> another study performed follow-up after 12 weeks of intervention using validated scales,<a class="elsevierStyleCrossRef" href="#bib0085">17</a> and one of the studies granted medical staff access to clinical reports on app use with patient-generated data regarding their substance use and general well-being. All follow-up processes were extremely heterogeneous in terms of both methods and objectives of follow-up, which ranged from optimising management continuity to serving as a medium for collecting information.In the SMART study, treatment data were shared among medical providers and ASHAs. ASHAs could use algorithms to better plan follow-up and prioritise patients who required timelier visits to ensure treatment adherence. In parallel, physicians, ASHAs and patients received automated voice messages to facilitate follow-up and treatment continuity.Effect of interventionsSymptom severityAll studies demonstrated effectiveness on the part of the interventions evaluated. Regarding depression, the SMART study<a class="elsevierStyleCrossRef" href="#bib0090">18</a> showed a nine-point reduction in the median in its population, while Sorkin et al.,<a class="elsevierStyleCrossRef" href="#bib0085">17</a> who compared two groups, found a decrease in the score in both. The Allillanchu project,<a class="elsevierStyleCrossRef" href="#bib0075">15</a> for its part, pointed to a benefit of this intervention through a qualitative evaluation. Among interventions for the management of anxiety, there was also a nine-point reduction on the GAD-7 scale subsequent to the intervention.<a class="elsevierStyleCrossRef" href="#bib0090">18</a> This trend was also represented in the study by Yu et al.,<a class="elsevierStyleCrossRef" href="#bib0080">16</a> with a 4.1-point decrease in the average score (®= –2.06; SD=0.77).The impact on behaviour of the Seva strategy<a class="elsevierStyleCrossRef" href="#bib0095">19</a> was demonstrated in the increase in abstinence from alcohol among those who used the app on more days (p=0.02), while those who advanced more in the app also showed a higher rate of abstinence from alcohol and psychoactive substances (p=0.01), and furthermore exhibited fewer risky behaviours for spreading human immunodeficiency virus (HIV) (p=0.02).In addition, positive outcomes were found with regard to seeking professional mental healthcare and stigma, measured using two instruments (the Knowledge, Attitude and Behaviour about mental health instrument and the Barriers to Access to Care Evaluation — treatment stigma subscale). The SMART project<a class="elsevierStyleCrossRef" href="#bib0090">18</a> showed that knowledge, attitudes and behaviours related to mental health improved towards acceptance of the topic subsequent to evaluation using these instruments.Treatment adherenceTwo studies reported data related to treatment adherence,<a class="elsevierStyleCrossRefs" href="#bib0080">16,19</a> although the definition of management adherence differed between the two. The Yu et al. study<a class="elsevierStyleCrossRef" href="#bib0080">16</a> evaluated this outcome taking into account the number of modules completed by each participant, the number of times that each technique was practised and the number of days that each person logged on to the application. A "committed" participant was defined as a participant who completed three or more techniques. On average, during the two months of implementation, the subjects used the Lantern app for 18.4 days (SD=15.8), completed 11.2 units (SD=14.3) out of 40 and practised 16.1 techniques (SD=20.3) out of a total of 26. Although there were significant differences in favour of "committed" patients, longitudinal analyses indicated that the number of units or techniques completed and the days of app use were not related to significant differences in terms of changes in scores on the GAD-7 at the end of the two months. Quanbeck et al.<a class="elsevierStyleCrossRef" href="#bib0095">19</a> evaluated management adherence by means of continuity of use of the Seva mobile app. At the start of implementation, app use at the three sites ranged from 94% (90/96) to 99% (69/70); after 12 months of implementation, app use adherence was found to be between 53% (41/78) and 60% (39/65) across the three sites.While one of the studies evaluated adherence through commitment to app use,<a class="elsevierStyleCrossRef" href="#bib0080">16</a> the second assessed this outcome through continuity in the use of the tool at the end of the implementation period.<a class="elsevierStyleCrossRef" href="#bib0095">19</a> Therein lay the first major difference that precluded joint analysis of results obtained. Moreover, although the decrease in the use of the mobile app in the study by Quanbeck et al. could be compared to findings in similar studies, the lack of a control group rendered suitable appreciation of the results impossible.CostsNone of the studies included evaluation of variation in costs due to the implementation of the model; however, Quanbeck et al.<a class="elsevierStyleCrossRef" href="#bib0075">15</a> reported data related to implementation costs. In that study, the costs reported were subdivided into the following categories: operational costs, costs of implementation, costs per patient and total costs for each of the three primary care centres in the study. Operating costs per patient were estimated at 1185 United States dollars (USD), total costs per clinic were on average 124,000 USD among the three clinics and costs per patients were an average of 1400 USD.Reach and response rateAll studies included collected data with respect to the reach or response rate of the intervention, but only in the study by Quanbeck et al. was this explicitly defined as an outcome of interest.<a class="elsevierStyleCrossRef" href="#bib0095">19</a> In the study by Sorkin et al., the patients seen by physicians trained in the digital algorithms were significantly more likely to start on a prescription (44% versus 14%; p<0.001) or begin active surveillance with psychological support (2.6% versus 0%; p=0.008) compared to the patients in the control group. In the Allillanchu study,<a class="elsevierStyleCrossRef" href="#bib0075">15</a> of the 159 subjects eligible due to positive screening, 127 attended the follow-up interview and 92 of them reported having sought help from a specialised professional after being advised to do so by their primary care physician. In the SMART study,<a class="elsevierStyleCrossRef" href="#bib0090">18</a> of the 238 individuals identified as positive in the screening conducted by ASHAs, just 30 (13%) visited a physician, 19 at health camps and 11 at primary care centres. Following implementation of the model, the use of mental health services was seen to increase from 0.8% at the start of the intervention to 12.6% at the end thereof.Regarding the Quanbeck et al. study, out of 3,226 patients eligible to use the Seva app, 238 were enrolled in the study, thus achieving a reach of 8.31% of people with substance use at the three sites of implementation of the study. In this case, the number of patients enrolled was correlated with the total number of mobile phones available at each care site; this was mentioned as a limitation on achieving a greater reach.The response rate achieved by the different studies varied greatly; this variation might have been due to multiple factors. One of them was related to the differences between the implementation sites: models applied in urban areas, as in the Allillanchu study in Lima, Peru, had a higher response rate compared to studies conducted in remote rural areas with limited opportunities for access to healthcare on the part of the target population, as in the SMART project, implemented in Andhra Pradesh, India. The differences in the mental health conditions addressed at each site may also have influenced the scope of the intervention; patients with conditions associated with greater social stigma were less likely to enrol in the proposed care model.DiscussionTo our knowledge, this review is the first to systematically evaluate existing evidence on technology-based care models for addressing mental health. At present, there are studies evaluating similar interventions, but these studies have only evaluated one point in the patient's primary care<a class="elsevierStyleCrossRef" href="#bib0025">5</a> or adherence to a certain technology<a class="elsevierStyleCrossRef" href="#bib0015">3</a>; they have not assessed the structured implementation of an optimised model with digital technologies as a whole from patient identification to patient treatment and follow-up over time. Although RCTs that evaluated technological interventions for mental health disorders were identified,<a class="elsevierStyleCrossRefs" href="#bib0100">20–22</a> they were excluded from the review as they did not take into account the different stages of patient care. Of the five studies included, just one was an RCT; the other four lacked a control or randomisation process. As a result, the quality of the evidence was seriously compromised by a high risk of bias, and this was compounded by small sample sizes and short follow-up periods. The RCT included, for its part, was classified as having a high risk of bias due to compromise in its processes of participant screening, blinding and analysis of outcomes.The studies selected enabled identification of screening of medical disorders, with apps on tablets being the most prevalent technology-enhanced process across the care models, followed by patient treatment through mobile apps. This was consistent with a recent systematic review that identified apps as the most commonly used digital technologies in the treatment of patients with severe mental illness.<a class="elsevierStyleCrossRef" href="#bib0115">23</a>Moreover, these studies showed an improvement in endpoints; it was unclear, however, whether this was due solely to the implementation of a new model, or to the implementation of the model added to the use of technological tools. Psychotherapy and rehabilitation approaches start from the assumption that the individual is willing and able to dedicate time to this treatment, allocate around one hour per session and engage in a longer-lasting type of treatment than other types of clinical intervention. The use of technologies to facilitate application and adaptation of interventions has arisen as a result, since it does not depend on office hours or hospital settings.<a class="elsevierStyleCrossRef" href="#bib0120">24</a> On the other hand, it does involve more active participation on the part of the patient; it also entails subsequent legal and professional responsibility in services and treatments provided or indicated through these platforms, which might alter the communication between the two players.<a class="elsevierStyleCrossRef" href="#bib0125">25</a>With this in mind, this review did not find sufficient evidence to support the use of a technology-based mental healthcare model over other existing models.Strengths and limitationsOne of the greatest strengths of this review was the spectrum of models sought: no mental health disorder, time of care or technology used was excluded. The search was also not limited by year, location, or language, which ensured that it would encompass a larger quantity of pertinent articles. In focusing on studies that assessed interventions linked to the development of a care model, we arrived at a better evaluation of the use of technologies as tools intended to optimise care processes for patients with mental disorders and the effectiveness of interventions in a care context closer to reality.However, this review did have some limitations, which could not be separated from its greatest strengths. Given that we did not limit our searches according to the above-mentioned criteria, we found a great deal of heterogeneity among studies. This made it impossible to conduct a quantitative synthesis of the results for disorders across studies such as depression and anxiety. Although individual findings with respect to these interventions were favourable across all studies, their low methodological quality undermined confidence in the results obtained. First and foremost, the absence of randomisation and a control group due to confounding factors, added to other previously mentioned factors, seriously affected the quality of the evidence.In addition, the small number of eligible studies restricted the robustness of the conclusions of this study. This limitation can be attributed in part to the process of determining the definition of a "care model". Given that the existing literature on this topic is scant, the review team adapted a set of characteristics considered essential when determining whether the studies retrieved featured mental healthcare models. This contributed in large part to the limited number of eligible studies identified and the lack of homogeneity among those studies.Moreover, there was likely some publication bias, bearing in mind that the search was primarily focused on the most important electronic databases and did not delve into grey literature. Added to this was the fact that the low number of studies included did not allow for an analysis using funnel diagrams or statistical methods to evaluation publication bias.Implications for practice and future researchFor implementation research on healthcare models to result in learning processes on a national or global level, studies of good methodological quality that evaluate both the implementation of models and the effectiveness of the interventions derived from them must be conducted. Regarding evaluation of effectiveness, the way in which confounding factors are controlled for must always be assessed, either through randomisation processes or through analysis of baseline characteristics in groups and possible factors that could end up influencing outcomes. The conduct of hybrid implementation/effectiveness studies could help to address this divide, in particular hybrid type 2 studies since they are focused on simultaneous evaluation of clinical interventions and implementation outcomes.<a class="elsevierStyleCrossRef" href="#bib0130">26</a> In addition, as we did not find studies done in a context similar to Colombia, we believe it is important to conduct feasibility studies adapted to the needs and capacities of the Colombian population and health system.Among the studies identified, those that evaluated the use of digital apps during the treatment phase did so by creating and testing their own apps. However, none of the studies developed these apps according to pre-established recommendations or consensuses. Although scant literature exists to date, a recent review set out multiple considerations in creating mental health apps in order to improve the functionality of these digital tools.<a class="elsevierStyleCrossRef" href="#bib0135">27</a> Future research should focus on standardising app development according to evidence-based recommendations, then validating these tools by means of experimental studies. In addition, longer follow-up times are desirable to evaluate patient adherence to such digital tools, the use of which is essentially self-regulated.ConclusionThis review provides clinicians and decision-makers with a synthesis of the evidence existing to date on technology-based care models for the broad spectrum of disorders in mental health. Implementation of technological models that address the different stages of patient care, as seen in the five studies included, is a viable strategy that could optimise processes of screening, diagnosis, treatment and follow-up of patients with this type of disorder. However, the evidence existing to date and the quality thereof are insufficient for determining whether a technology-enhanced care model is superior to other similar models in addressing mental health. Studies with good methodological quality that evaluate the implementation and effectiveness of these models must be conducted before the best technology-based mental healthcare model can be identified.FundingThe research reported in this publication was funded by the National Institute of Mental Health (NIMH) of the National Institutes of Health (NIH) of the United States with Grant Number 1U19MH109988 (multiple principal investigators: Lisa A. Marsch, PhD, and Carlos Gómez-Restrepo, MD, PhD). Juan Camilo Rosas and Arturo Marroquín Rivera participated as Young Researchers, funded by the Jóvenes Investigadores e Innovadores program by the Colombian Ministry of Science, Technology and Innovation (Contract 829, 2018).Conflicts of interestThe authors declare that they have no conflicts of interest." 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] 4 => array:2 [ "identificador" => "abst0050" "titulo" => "Conclusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1443211" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Methods" "secciones" => array:2 [ 0 => array:3 [ "identificador" => "sec0015" "titulo" => "Inclusion criteria for studies" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0020" "titulo" => "Types of study" ] 1 => array:2 [ "identificador" => "sec0025" "titulo" => "Population" ] 2 => array:2 [ "identificador" => "sec0030" "titulo" => "Interventions" ] 3 => array:2 [ "identificador" => "sec0035" "titulo" => "Outcomes" ] 4 => array:2 [ "identificador" => "sec0040" "titulo" => "Search for and identification of studies and data extraction" ] ] ] 1 => array:3 [ "identificador" => "sec0045" "titulo" => "Data analysis" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0050" 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array:3 [ "identificador" => "sec0110" "titulo" => "Effect of interventions" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0115" "titulo" => "Symptom severity" ] 1 => array:2 [ "identificador" => "sec0120" "titulo" => "Treatment adherence" ] 2 => array:2 [ "identificador" => "sec0125" "titulo" => "Costs" ] 3 => array:2 [ "identificador" => "sec0130" "titulo" => "Reach and response rate" ] ] ] ] ] 7 => array:3 [ "identificador" => "sec0135" "titulo" => "Discussion" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0140" "titulo" => "Strengths and limitations" ] 1 => array:2 [ "identificador" => "sec0145" "titulo" => "Implications for practice and future research" ] ] ] 8 => array:2 [ "identificador" => "sec0150" "titulo" => "Conclusion" ] 9 => array:2 [ "identificador" => "sec0155" "titulo" => "Funding" ] 10 => array:2 [ "identificador" => "sec0160" "titulo" => "Conflicts of interest" ] 11 => array:2 [ "identificador" => "xack569490" "titulo" => "Acknowledgements" ] 12 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2020-12-18" "fechaAceptado" => "2021-01-18" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1443212" "palabras" => array:5 [ 0 => "Implementation science" 1 => "Mental health" 2 => "Primary healthcare" 3 => "Systematic review" 4 => "Healthcare model" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1443211" "palabras" => array:5 [ 0 => "Ciencia de la implementación" 1 => "Salud mental" 2 => "Atención primaria de salud" 3 => "Revisión sistemática" 4 => "Modelos de atención en salud" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "IntroductionThis systematic review summarises the existing evidence on the implementation of technology-based mental healthcare models in the primary care setting. MethodsA systematic search was conducted (MEDLINE, Embase, CENTRAL) in August 2019 and studies were selected according to predefined eligibility criteria. The main outcomes were clinical effectiveness, adherence to primary treatment and cost of implementation. Selection criteriaStudies with an experimental or quasi-experimental design that evaluated the implementation of technology-based mental healthcare models were included. ResultsFive articles met the inclusion criteria. The models included technological devices such as tablets, cellphones and computers, with programs and mobile apps that supported decision-making in the care pathway. These decisions took place at different times, from the universal screening phase to the follow-up of patients with specific conditions. In general, the studies showed a decrease in the reported symptoms. However, there was great heterogeneity in both the health conditions and the outcomes, which hindered a quantitative synthesis. The assessment of risk of bias showed low quality of evidence. ConclusionThere is not enough evidence to support the implementation of a technology-based mental healthcare model. High quality studies that focus on implementation and effectiveness outcomes are needed to evaluate the impact of technology-based mental healthcare models in the primary care setting." "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Selection criteria" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "IntroducciónEsta revisión sistemática resume la evidencia existente sobre los modelos de implementación basados en tecnologías para el abordaje de la salud mental en el contexto de la atención primaria. MétodosSe realizó una búsqueda sistemática en las principales bases de datos electrónicas (MEDLINE, Embase, CENTRAL) en agosto del 2019 y se eligieron estudios según criterios de selección predefinidos. Los desenlaces principales fueron efectividad clínica, adherencia al tratamiento y costos de implementación. Criterios de selecciónSe incluyeron estudios con diseños experimentales o cuasiexperimentales que evaluaran la implementación de modelos basados en tecnologías para el abordaje de la salud mental. ResultadosCinco artículos cumplieron con los criterios de selección. Los modelos incluían dispositivos tecnológicos como tabletas, celulares y computadores con programas y aplicativos móviles que ayudaban con la toma de decisiones en la ruta de atención. Estas tenían lugar en diferentes momentos, desde el tamizaje a la población general, hasta el seguimiento de los pacientes con alguna condición específica. De forma general, en los estudios se evidencia una disminución de los síntomas reportados, sin embargo, tanto las condiciones de salud como los desenlaces muestran gran heterogeneidad, lo que impidió realizar una síntesis cuantitativa. La evaluación del riesgo de sesgo mostró baja calidad de la evidencia. ConclusiónNo hay suficiente evidencia para determinar la superioridad de un modelo de atención optimizado por tecnologías para el abordaje de la salud mental. Es necesario realizar estudios primarios con una adecuada calidad metodológica que evalúen desenlaces relevantes de implementación y efectividad." "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Criterios de selección" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Resultados" ] 4 => array:2 [ "identificador" => "abst0050" "titulo" => "Conclusión" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: Rosas JC, Gómez-Ayala MC, Rivera AM, Botero-Rodríguez F, Cepeda M, Suárez-Obando F, et al. Modelos de atención en salud mental basados en tecnologías: revisión sistemática de la literatura. Rev Colomb Psiquiat. 2021;50:30–41." ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "PubMed: (implementation OR model of care OR "Health Plan Implementation" [Mesh] OR "Implementation Science" [Mesh] OR "Regional Health Planning" [Mesh] OR "Social Planning" [Mesh] OR "Risk Evaluation and Mitigation" [Mesh] OR "Health Services" [Mesh] OR "United States Public Health Service" [Mesh] OR "Women's Health Services" [Mesh] OR "Student Health Services" [Mesh] OR "Child Health Services" [Mesh] OR "School Health Services" [Mesh] OR "United States Indian Health Service" [Mesh] OR "Preventive Health Services" [Mesh] OR "Adolescent Health Services" [Mesh] OR "Personal Health Services" [Mesh] OR "Rural Health Services" [Mesh] OR "Suburban Health Services" [Mesh] OR "Urban Health Services" [Mesh] OR "Delivery of Health Care" [Mesh] OR "Quality Indicators, Health Care" [Mesh] OR "Health Care Sector" [Mesh] OR "Health Care Surveys" [Mesh] OR "Delivery of Health Care, Integrated" [Mesh] OR "Health Care Reform" [Mesh] OR "Peer Review, Health Care" [Mesh] OR "Health Care Evaluation Mechanisms" [Mesh] OR "Health Care Quality, Access, and Evaluation" [Mesh] OR "Process Assessment (Health Care)" [Mesh] OR "Outcome Assessment (Health Care)" [Mesh] OR "Health Care Costs" [Mesh] OR "Health Care Rationing" [Mesh] OR "Quality of Health Care" [Mesh] OR "Quality Assurance, Health Care" [Mesh] AND ("Primary Health Care" [Mesh]) AND (mental health OR mental diseases OR mental disorders OR "Mental Health" [Mesh] OR "Mental Health Services" [Mesh] OR "Mental Health Associations" [Mesh] OR "Community Mental Health Services" [Mesh] OR "Community Mental Health Centers" [Mesh] OR "Mental Health Recovery" [Mesh] OR "Health Plan Implementation" [Mesh] AND (Mobile Applications" [Mesh] OR Electronics" [Mesh] OR Electronic Health Records" [Mesh] OR Electronic Data Processing" [Mesh] OR Technology" [Mesh] OR "Wireless Technology" [Mesh] OR "Remote Sensing Technology" [Mesh] OR "Biomedical Technology" [Mesh] OR "Educational Technology" [Mesh] OR "Technology, High-Cost" [Mesh] OR "Technology Assessment, Biomedical" [Mesh] OR "Information Technology" [Mesh] OR "Cell Phone" [Mesh] OR "Cell Phone Use" [Mesh] OR "Smartphone" [Mesh] OR "Text Messaging" [Mesh] OR "Computers, Handheld" [Mesh] OR e-medicine OR mhealth OR emedicine OR telemedicine OR ipad* OR "Personal Digital Assistant*" OR pda* OR palmtop* OR "videotape" [All Fields] OR "recording" [All Fields] OR "videotape recording" [All Fields] OR "video"[All Fields] OR "telecoaching" [All Fields] OR "teleconference" [All Fields] OR "educational technology" [All Fields] OR "internet" [MeSH Terms]). Web of science: ("implementation" OR "care model" OR "Health plan implementation" OR "implementation science" OR "regional health planning" OR "social planning") AND ("mental health" OR "mental disease" OR "mental disorders therapy" OR "mental health service" OR "community mental health" OR "mental health recovery") AND ("mobile application" OR "electronics" OR "electronic medical record" OR "information processing" OR "technology" OR "wireless communication" OR "medical technology" OR "educational technology" OR "biomedical technology assessment" OR "information technology device" OR "mobile phone" OR "wireless communication" OR "medical technology" OR "wireless technology" OR "cell phone" OR "smartphone" OR "text messaging" OR "handheld computers" OR "mhealth" OR "palmtop" OR "video" OR "telecoaching" OR "internet"). EMBASE: ('implementation science'/exp OR 'health care planning'/exp OR 'social aspect'/exp OR 'risk evaluation and mitigation strategy'/exp OR 'health service'/exp OR 'public health service'/exp OR 'preventive health service'/exp OR 'health care delivery'/exp) AND ('primary health care'/exp) AND ('mental health'/exp OR 'mental disease'/exp OR 'mental disorders therapy'/exp OR 'mental health service'/exp OR 'community mental health'/exp OR 'mental health recovery'/exp OR 'health care planning'/exp) AND ('mobile application'/exp OR 'electronics'/exp OR 'electronic medical record'/exp OR 'information processing'/exp OR 'technology'/exp OR 'wireless communication'/exp OR 'medical technology'/exp OR 'educational technology'/exp OR 'biomedical technology assessment'/exp OR 'information technology device'/exp OR 'mobile phone'/exp OR 'smartphone'/exp OR 'text messaging'/exp OR 'personal digital assistant'/exp OR 'mhealth'/exp OR 'telemedicine'/exp OR 'tablet computer'/exp OR 'educational technology'/exp OR 'Internet'/exp). The Cochrane Library: (mh "implementation science" OR mh "health planning" OR mh "health plan implementation" OR mh "regional health planning") AND (mh "Primary Health Care) AND (mh "mental health" OR mh "mentally ill persons" OR mh "mental disorders" OR mh "mental health services" OR mh "community mental health centers" OR mh "community mental health services" OR mh "mental health recovery") AND (mh technology OR mh "mobile applications OR mh electronics OR mh "electronic health records" OR mh "electronic data processing" OR mh "wireless technology" OR mh "Biomedical technology" OR mh "educational technology" OR mh "information technology" OR mh "cell phone" OR mh smartphone OR mh "text messaging" OR mh "computers, handheld" OR mh telemedicine OR mhealth OR emedicine OR telemedicine OR ipad OR palmtop OR video OR internet) PSYCHinfo: implementation OR model of care OR "Health Plan Implementation" OR "Implementation Science" OR "Regional Health Planning" OR "Social Planning" OR "Risk Evaluation and Mitigation" OR "Health Services" OR "United States Public Health Service" OR "Women's Health Services" OR "Student Health Services" OR "Child Health Services" OR "School Health Services" OR "United States Indian Health Service" OR "Preventive Health Services" OR "Adolescent Health Services" OR Personal Health Services" OR Rural Health Services" OR "Suburban Health Services" OR "Urban Health Services" OR "Delivery of Health Care" OR "Quality Indicators, Health Care" OR "Health Care Sector" OR "Health Care Surveys" OR "Delivery of Health Care, Integrated" OR "Health Care Reform" OR "Peer Review, Health Care" OR "Health Care Evaluation Mechanisms" OR "Health Care Quality, Access, and Evaluation" OR "Process Assessment" OR "Outcome Assessment" OR "Health Care Costs" OR "Health Care Rationing" OR "Quality of Health Care" OR "Quality Assurance, Health Care") AND ("Primary Health Care") AND (mental health OR mental diseases OR mental disorders OR "Mental Health" OR "Mental Health Services" OR "Mental Health Associations" OR "Community Mental Health Services" OR "Community Mental Health Centers" OR "Mental Health Recovery" OR "Health Plan Implementation") AND ("Mobile Applications" OR "Electronics" OR "Electronic Health Records" OR "Electronic Data Processing" OR "Technology" OR "Wireless Technology" OR "Remote Sensing Technology" OR "Biomedical Technology" OR "Educational Technology" OR "Technology, High-Cost" OR "Technology Assessment, Biomedical" OR "Information Technology" OR "Cell Phone" OR "Cell Phone Use" OR "Smartphone" OR "Text Messaging" OR "Computers, Handheld" OR e-mdicine OR e-medicine OR mhealth OR emedicine OR telemedicine OR ipad* OR "Personal Digital Assistant*" OR pda* OR pad OR palmtop* OR "videotape" OR "recording" OR "videotape recording" OR "video" OR "telecoaching" OR "teleconference" OR "educational technology" OR "internet". LILACS: (salud mental OR mental health) AND (prevención OR atención primaria) AND (tw:telemedicina OR e-medicine OR tecnologia OR technology) AND (tw:modelo)." "etiqueta" => "Appendix A" "titulo" => "Search strategy" "identificador" => "sec0165" ] ] ] ] "multimedia" => array:3 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 3564 "Ancho" => 3318 "Tamanyo" => 745943 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Models identified and technology use by implementation stage. a) Yu, 2018. GAD-7: generalised anxiety disorder-7. SMS: short message service. b) SMART, 2017. GAD-7: generalised anxiety disorder-7. PHQ-9: patient health questionnaire-9. EDSS: electronic decision support system. IVRS: interactive voice response system. ASHAs: accredited social health activist. c) The Allillanchu Project, 2018. SRQ: self-reporting questionnaire. d) Quanbeck, 2018. e) Sorkin, 2019. HSC: Hopkins System Checklist. HQT: Harvard Trauma Questionnaire." ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1697 "Ancho" => 1508 "Tamanyo" => 179038 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "PRISMA flow chart." ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Name of study — Year \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Type of study \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Implementation site \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Target population \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Participant care site \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Number of participants (n) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mental health conditions evaluated \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Phases included in the model \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Technological tools \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Primary outcomes \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Follow-up time \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SMART, 2017 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Before-and-after study with no control \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Andhra Pradesh, India \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adults over 18 years of age \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Two primary care centres, homes of participants (30 villages of registered tribes) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">238 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Depression and anxiety \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Screening, diagnosis, treatment and follow-up \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tablet, EDSS<a class="elsevierStyleCrossRef" href="#tblfn0005">*</a>, IVRS<a class="elsevierStyleCrossRef" href="#tblfn0010">**</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Change on clinical scale \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 months \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The Allillanchu Project, 2018 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mixed-methods study \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Lima, Peru \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adults over 18 years of age \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Five public general primary care centres \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">143 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Depression, anxiety, psychosis, seizure disorder, AUD<a class="elsevierStyleCrossRef" href="#tblfn0015">***</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Screening, intervention, follow-up \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tablet, digital platform, text messages \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Seeking of mental healthcare \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 weeks \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care, 2018 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Type 2 hybrid effectiveness/implementation study \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">United States \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adults over 18 years of age with a diagnosis of \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">A primary care centre for patients with psychoactive substance use disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">207 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Psychoactive substance use disorder, AUD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Diagnosis, treatment, follow-up \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mobile app, website \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Substance use, quality of life, use of medical services, model adoption, costs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 months \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Implementation of a Guided, Digital Cognitive Behavioral Program for Anxiety in Primary Care: Preliminary Findings of Engagement and Effectiveness, 2018 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Before-and-after study with no control \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">United States \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adults 20−65 years of age \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Four general primary care centres \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Anxiety \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Screening, diagnosis, treatment and follow-up \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Electronic medical record, mobile app, text messages \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Change on clinical scale, commitment to app use \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 months \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " colspan="11" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">[0,1–11]</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Novel Health Information Technology to Aid Provider Recognition and Treatment of Major Depressive Disorder and Posttraumatic Stress Disorder in Primary Care, 2019 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Randomised two-group (two-arm) trial \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">United States \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adults over 18 years of age Refugees from Cambodia in the United States \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Two community clinics with a federal primary care qualification \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">390 patients (272 in the intervention group and 118 in the control group) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Depression, post-traumatic stress disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Screening, diagnosis, treatment and follow-up \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tablet, electronic app with evidence-based information \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Change on clinical scale, concordance between positive screening and medical diagnosis, following of evidence-based recommendations \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 months \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2752922.png" ] ] ] "notaPie" => array:3 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "*" "nota" => "EDSS=electronic decision support system." ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "**" "nota" => "IVRS=interactive voice response system." ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "***" "nota" => "AUD=alcohol use disorder." ] ] ] "descripcion" => array:1 [ "en" => "Characteristics of the studies included." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:27 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Declaracion de Alma-Ata" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "Organización Paramericana de la Salud" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Libro" => array:3 [ "fecha" => "1978" "paginaInicial" => "1" "paginaFinal" => "3" ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Principios de Brasilia" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "Organización Paramericana de la Salud" 1 => "Organizacion Mundial de la Salud" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Libro" => array:3 [ "fecha" => "2005" "paginaInicial" => "1" "paginaFinal" => "4" ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0015" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Consenso de Panamá" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "Organización Paramericana de la Salud" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Libro" => array:2 [ "titulo" => "Consenso de Panamá" "fecha" => "2010" ] ] ] ] ] ] 3 => array:3 [ "identificador" => "bib0020" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "La reforma de los servicios de salud mental: 15 años después de la delcaración de Caracas. 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Technology-based mental healthcare models: A systematic review of the literature

Modelos de atención en salud mental basados en tecnologías: Revisión sistemática de la literatura

Juan Camilo Rosasa,

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rosas.juan@javeriana.edu.co

Corresponding author.

, María Camila Gómez-Ayalaa, Arturo Marroquín Riveraa, Felipe Botero-Rodrígueza, Magda Cepedaa, Fernando Suárez-Obandoa,b,c, Sophie M. Bartelsd, Carlos Gómez-Restrepoa,c,e

a Departamento de Epidemiología Clínica y Bioestadística, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia

b Instituto de Genética Humana, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia

c Hospital Universitario San Ignacio, Bogotá, Colombia

d Center for Technology and Behavioral Health, Departamento de Psiquiatría, Geisel School of Medicine at Dartmouth College, United States

e Departamento de Psiquiatría y Salud Mental, Facultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia

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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Mental health is essential to well-being&#59; nevertheless&#44; low-income and medium-income countries not only lack trained staff&#44; management guidelines and infrastructure&#44;<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#8211;3</span></a> but also face barriers such as inequities in resource distribution&#46;<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4&#44;5</span></a> Hence&#44; international organisations such as the World Health Organization &#40;WHO&#41; and the Pan American Health Organization &#40;PAHO&#41; have made proposals such as the Mental Health Gap Action Programme &#40;mhGAP&#41;<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> in order to raise awareness of mental health&#46; Some countries have leveraged these strategies to launch national care plans specifically for mental health conditions&#46; One example in Latin America is Chile&#44; which has a national model for detection&#44; diagnosis and treatment of depression based on technology use&#46;<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">The use of technological tools for health is more than a growing trend around the world&#46; It has demonstrated its potential to improve the efficiency of the use of mental health resources&#46;<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8&#44;9</span></a> This is primarily due to its contributions to breaking down barriers to access to services&#44; increasing coverage&#44; making treatments more flexible&#44; decreasing perceived stigma and increasing user commitment&#44; among other things&#46; Technology may be involved at different points in care &#40;screening&#44; diagnosis&#44; treatment and follow-up&#41; in both primary care and specialised medicine settings&#46;<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10&#44;11</span></a> Some examples of such integration are currently under development in Colombia&#46;<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8&#44;10</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Although the use of technologies has proven quite effective in the management of mental health disorders&#44; these tend to be insufficient interventions when made in isolation from other elements of care&#46;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> Therefore&#44; the proposal of a &#34;care model&#34; incorporating components of technology&#44; mental health and primary care has gained traction as a strategy for addressing shortcomings in and barriers to managing these health conditions&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">The concept of a model refers to a systematic process that includes actions from the admission of the patient to the healthcare service-providing institution and also includes phases of screening&#44; diagnosis&#44; treatment&#44; follow-up and referral&#44; always in accordance with the needs of the community&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Taking all of this into account&#44; the main objective of this review was to describe and synthesise the existing evidence on implementing technology-based care models in addressing mental health disorders in the primary care context in order to specifically evaluate the clinical effectiveness of those models&#44; as well as other pertinent outcomes&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Inclusion criteria for studies</span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Types of study</span><p id="par0030" class="elsevierStylePara elsevierViewall">Randomised controlled trials &#40;RCTs&#41;&#44; before-and-after studies &#40;with or without a control group&#41;&#44; interrupted time series &#40;ITS&#41; studies and studies with any other type of prospective design that met the eligibility criteria were included&#46; The studies selected could measure outcomes by comparing institutions or examining a single institution before and after implementation&#46; Mixed-methods studies were included if they evaluated any of the outcomes identified&#46; Strictly qualitative studies were excluded&#46; No studies were excluded on the basis of language or year of publication&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Population</span><p id="par0035" class="elsevierStylePara elsevierViewall">Research units corresponded to health centres where technology-based models were implemented&#46; No other restrictions in relation to the sociodemographic characteristics of the population that received care at those centres were applied&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Interventions</span><p id="par0040" class="elsevierStylePara elsevierViewall">Implementation of models focused on the use of technological or digital tools such as smartphones&#44; tablets&#44; Internet use or apps on other devices&#44; developed in primary care contexts for screening&#44; diagnosis&#44; treatment or follow-up of mental health conditions&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">Studies that reported interventions implemented in contexts other than primary care&#44; such as psychiatric hospitals&#59; studies with the main objective of examining outcomes in healthcare professionals&#59; and studies that used technologies solely as a communication medium &#40;e&#46;g&#46; telephone calls&#41; were excluded&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Outcomes</span><p id="par0320" class="elsevierStylePara elsevierViewall"><ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">-</span><p id="par0050" class="elsevierStylePara elsevierViewall">Clinical effectiveness &#40;measurement of symptoms using validated instruments&#41;&#46;</p></li><li class="elsevierStyleListItem" id="lsti0010"><span class="elsevierStyleLabel">-</span><p id="par0055" class="elsevierStylePara elsevierViewall">Treatment adherence &#40;continuity in the use of technological tools provided by the model&#41;&#46;</p></li><li class="elsevierStyleListItem" id="lsti0015"><span class="elsevierStyleLabel">-</span><p id="par0060" class="elsevierStylePara elsevierViewall">Costs &#40;change in care before and after implementation or between intervention and control group&#41;&#46;</p></li><li class="elsevierStyleListItem" id="lsti0020"><span class="elsevierStyleLabel">-</span><p id="par0065" class="elsevierStylePara elsevierViewall">Reach of the model &#40;number of participants enrolled compared to total number of eligible individuals&#41; 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Where they disagreed&#44; they consulted a third-party researcher &#40;MC&#41;&#46; To screen and select the articles&#44; the Rayyan QCRI<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> web app was used to facilitate the process of classification of references and discussion&#46; Two authors&#44; AMR and JCR&#44; independently extracted the data from the studies selected using a data extraction form specifically for this review and resolved discrepancies by referring to the original text&#46;</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Data analysis</span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Evaluation of risk of bias</span><p id="par0080" class="elsevierStylePara elsevierViewall">Due to the differences in design among the studies included&#44; domains of the Cochrane tool to evaluate risk of bias &#40;RoB 2&#41; and the &#34;Risk Of Bias In Non-randomized Studies - of Interventions&#34; &#40;ROBINS-I&#41; tool to assess non-randomised studies were adapted&#46; The domains considered were&#58; bias due to confounding&#47;randomisation&#44; bias in selection&#44; bias in classification&#44; lost in follow-up&#44; bias in measurement and bias in selection of the reported result&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">For the heterogeneity analysis&#44; differences among the studies were sought and explained in narrative form&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Data synthesis</span><p id="par0090" class="elsevierStylePara elsevierViewall">The studies included varied greatly in terms of study design&#44; target population&#44; interventions and comparators used&#44; instruments of measurement&#44; and points for follow-up and evaluation of outcomes&#46; Taking this into account&#44; 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2</a> summarises the search results&#46; The most common reasons why studies were excluded in the screening process were that they did not meet the definition for a care model sought by the researchers or that they did not report outcomes of interest&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Evaluation of risk of bias</span><p id="par0105" class="elsevierStylePara elsevierViewall">Several of the studies included had components in addition to implementation outcomes&#59; hence&#44; in accordance with our objectives&#44; only the evaluation of treatment effectiveness and adherence were taken into account in evaluating bias&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Among the five studies included&#44; the sole RCT<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> showed various biases due to confounding &#40;participant screening and randomisation&#41;&#44; with intervention blinding and bias in measurement of outcomes&#46; In addition&#44; baseline differences were detected among patient groups&#44; including variations in level of education&#44; age and prevalence of depression and post-traumatic stress disorder &#40;PTSD&#41;&#46; Taking this into account and adding it to the possible influence of each provider on the outcomes of interest&#44; the study was considered to carry a high risk of bias&#46; The four remaining articles corresponded to non-randomised studies seen to be compromised in their entirety by biases due to confounding and&#44; to a lesser extent&#44; bias in measurement of outcomes&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Data extraction</span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">General characteristics of the studies</span><p id="par0115" class="elsevierStylePara elsevierViewall">The five articles selected were published between 2017 and 2019&#46; All of them enrolled elderly individuals only&#59; four screened the general population who visited the health centre<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">15&#8211;18</span></a> and one screened patients with a history of psychoactive substance use&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a></p><p id="par0120" class="elsevierStylePara elsevierViewall">The studies included screened different aspects of mental health&#44; except the Allillanchu study&#44;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> which also evaluated seizure disorder&#46; The most commonly examined diseases were anxiety and depression&#59; these figured in four of the studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">15&#8211;18</span></a> Other matters evaluated were psychoactive substance use and alcohol use&#44;<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">15&#44;19</span></a> quality of life&#44;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> PTSD&#44;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> risk of suicide<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> and related problems such as stigma&#44; which influences the implementation of&#44; adherence to and impact of interventions&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> Among the symptom evaluation tools used&#44; the most common were the PHQ-9 scale<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> and the GAD-7 scale<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;18</span></a> &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0155">Stages of the model and technologies used</span><span id="sec0090" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0160">Screening</span><p id="par0125" class="elsevierStylePara elsevierViewall">Of the five studies included&#44; four conducted screening through electronic tablets&#46;<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">15&#8211;18</span></a> Two of these specified that they used special apps to administer the questionnaires&#59;<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">15&#44;18</span></a> the other two did not&#46;<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;17</span></a> Regarding context&#44; three of the studies conducted screening in a clinical&#47;urban environment<a class="elsevierStyleCrossRefs" href="#bib0085"><span class="elsevierStyleSup">17&#8211;19</span></a> and the fourth conducted screening directly in the homes of potential participants and in a rural setting&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a></p><p id="par0130" class="elsevierStylePara elsevierViewall">In the Sorkin et al&#46; study&#44;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> the intervention had three main components&#58; 1&#41; an online tutorial for mental health management focused on trauma&#59; 2&#41; tablet-enhanced screening of all patients prior to medical consultation&#59; and 3&#41; provision of algorithms and guidelines to medical staff through mobile platforms&#46; In the experimental group&#44; healthcare providers were given the score for all patients who completed electronic screening&#59; in the control group&#44; physicians only received scores for cases at high risk of self-aggressiveness or hetero-aggressiveness&#46; The proportion of diagnoses made by medical staff was significantly higher in the experimental group than in the control group&#44; both for depression &#40;OR&#58; 6&#46;5&#59; 95&#37; confidence interval &#91;CI&#93;&#58; 1&#46;48&#8211;28&#44;79&#41; and for PTSD &#40;OR&#58; 23&#46;3&#59; 95&#37; CI&#58; 2&#46;99&#8211;151&#46;62&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> The three remaining studies corresponded to uncontrolled research lacking comparative measurements in this stage&#46;</p><p id="par0135" class="elsevierStylePara elsevierViewall">The Strengthening Mental Health and Research Training in Africa &#40;SMART&#41; project&#44;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> implemented in India&#44; developed a task distribution system in which accredited social health activists &#40;ASHAs&#41; conducted screening for depression and anxiety in the target population and advised patients with positive results to get counselling with physicians in health camps&#46;</p></span><span id="sec0095" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0165">Diagnosis</span><p id="par0140" class="elsevierStylePara elsevierViewall">Two studies implemented a diagnosis stage in previously screened patients&#46; Both carried out that stage using clinical practice algorithms and guidelines for patient diagnosis&#44; which were available in mobile apps installed on tablets&#46;<a class="elsevierStyleCrossRefs" href="#bib0085"><span class="elsevierStyleSup">17&#44;18</span></a> With regard to Sorkin et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> clinical decision-making was based on an 11-point algorithm designed to diagnose major depression and PTSD&#46; At the end of the intervention&#44; the proportion of patients who received a diagnosis of either of the two diseases in the intervention group was compared to the same proportion in the control group&#46; The participants in the intervention group were 2&#46;6 times more likely to have a diagnosis consistent with their screening compared to the control group&#46;</p></span><span id="sec0100" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0170">Treatment</span><p id="par0145" class="elsevierStylePara elsevierViewall">All five studies included a stage related to patient treatment linked to a technological&#47;digital strategy&#46; Two used mobile apps with modules and strategies as treatment aids<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;19</span></a>&#59; another two used management algorithms through digital platforms<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#44;18</span></a> and one designed an automated system to deliver motivational text messages &#40;SMS&#41; to incentivise consultation with mental health specialists&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a></p><p id="par0150" class="elsevierStylePara elsevierViewall">Regarding the two studies that used apps in the treatment stage&#44;<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;19</span></a> the study by Quanbeck et al&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> evaluated how mobile health technologies facilitated integration of treatment for addiction into primary care&#46; The Seva app offered patients interactive modules for learning how to solve problems and self-regulate&#44; tools for coping with high-risk situations&#44; and cognitive behavioural therapy strategies&#44; among other things&#46; The Lantern intervention consisted of a mobile app that provided the patient with a cognitive behavioural programme based on protocols for people with generalised anxiety disorder &#40;GAD&#41;&#46; Both studies collected data on app use&#44; including logins and use of modules&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">With regard to the two studies that used management algorithms on digital devices&#44; both were developed based on evidence-based and culturally validated scales and guidelines for management&#46; In the SMART study&#44;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> patients diagnosed with mental illness received psychotherapy from healthcare professionals affiliated with the study or were referred to hospitals able to provide more complex care&#46; Regarding the Sorkin et al&#46; study&#44;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> patients were managed using the digital algorithms designed in the intervention group or were managed as usual in the control group&#46; Participation by physicians could encompass aspects such as pharmacotherapy&#44; active surveillance with psychosocial support and referral to a mental health specialist&#46; Whereas in the SMART study the treatment provided was not evaluated in detail in relation to the management algorithms&#44; in the Sorkin study these were primary outcomes that were evaluated by means of review of medical records after the care model had been implemented for 12 weeks&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">Finally&#44; the Allillanchu study<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> did not include a direct treatment&#44; but did implement a text message system with the aim of increasing specialised medical consultations among patients identified in primary care&#46;</p></span><span id="sec0105" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0175">Follow-up</span><p id="par0165" class="elsevierStylePara elsevierViewall">The five studies included reported data on patient follow-up during the implementation of the models&#46; Concerning the strategies used&#44; one study conducted interviews with participants to enquire about specialised medical consultations&#44;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> one study optimised the follow-up stage using digital algorithms and automated voice messages&#44;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> another followed up patients by means of messages through a mobile app&#44;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> another study performed follow-up after 12 weeks of intervention using validated scales&#44;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> and one of the studies granted medical staff access to clinical reports on app use with patient-generated data regarding their substance use and general well-being&#46; All follow-up processes were extremely heterogeneous in terms of both methods and objectives of follow-up&#44; which ranged from optimising management continuity to serving as a medium for collecting information&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">In the SMART study&#44; treatment data were shared among medical providers and ASHAs&#46; ASHAs could use algorithms to better plan follow-up and prioritise patients who required timelier visits to ensure treatment adherence&#46; In parallel&#44; physicians&#44; ASHAs and patients received automated voice messages to facilitate follow-up and treatment continuity&#46;</p></span></span><span id="sec0110" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0180">Effect of interventions</span><span id="sec0115" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0185">Symptom severity</span><p id="par0175" class="elsevierStylePara elsevierViewall">All studies demonstrated effectiveness on the part of the interventions evaluated&#46; Regarding depression&#44; the SMART study<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> showed a nine-point reduction in the median in its population&#44; while Sorkin et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> who compared two groups&#44; found a decrease in the score in both&#46; The Allillanchu project&#44;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> for its part&#44; pointed to a benefit of this intervention through a qualitative evaluation&#46; Among interventions for the management of anxiety&#44; there was also a nine-point reduction on the GAD-7 scale subsequent to the intervention&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> This trend was also represented in the study by Yu et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> with a 4&#46;1-point decrease in the average score &#40;&#174;&#61; &#8211;2&#46;06&#59; SD<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;77&#41;&#46;</p><p id="par0180" class="elsevierStylePara elsevierViewall">The impact on behaviour of the Seva strategy<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> was demonstrated in the increase in abstinence from alcohol among those who used the app on more days &#40;p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;02&#41;&#44; while those who advanced more in the app also showed a higher rate of abstinence from alcohol and psychoactive substances &#40;p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;01&#41;&#44; and furthermore exhibited fewer risky behaviours for spreading human immunodeficiency virus &#40;HIV&#41; &#40;p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;02&#41;&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">In addition&#44; positive outcomes were found with regard to seeking professional mental healthcare and stigma&#44; measured using two instruments &#40;the Knowledge&#44; Attitude and Behaviour about mental health instrument and the Barriers to Access to Care Evaluation &#8212; treatment stigma subscale&#41;&#46; The SMART project<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> showed that knowledge&#44; attitudes and behaviours related to mental health improved towards acceptance of the topic subsequent to evaluation using these instruments&#46;</p></span><span id="sec0120" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0190">Treatment adherence</span><p id="par0190" class="elsevierStylePara elsevierViewall">Two studies reported data related to treatment adherence&#44;<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;19</span></a> although the definition of management adherence differed between the two&#46; The Yu et al&#46; study<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> evaluated this outcome taking into account the number of modules completed by each participant&#44; the number of times that each technique was practised and the number of days that each person logged on to the application&#46; A &#34;committed&#34; participant was defined as a participant who completed three or more techniques&#46; On average&#44; during the two months of implementation&#44; the subjects used the Lantern app for 18&#46;4 days &#40;SD<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>15&#46;8&#41;&#44; completed 11&#46;2 units &#40;SD<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>14&#46;3&#41; out of 40 and practised 16&#46;1 techniques &#40;SD<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>20&#46;3&#41; out of a total of 26&#46; Although there were significant differences in favour of &#34;committed&#34; patients&#44; longitudinal analyses indicated that the number of units or techniques completed and the days of app use were not related to significant differences in terms of changes in scores on the GAD-7 at the end of the two months&#46; Quanbeck et al&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> evaluated management adherence by means of continuity of use of the Seva mobile app&#46; At the start of implementation&#44; app use at the three sites ranged from 94&#37; &#40;90&#47;96&#41; to 99&#37; &#40;69&#47;70&#41;&#59; after 12 months of implementation&#44; app use adherence was found to be between 53&#37; &#40;41&#47;78&#41; and 60&#37; &#40;39&#47;65&#41; across the three sites&#46;</p><p id="par0195" class="elsevierStylePara elsevierViewall">While one of the studies evaluated adherence through commitment to app use&#44;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> the second assessed this outcome through continuity in the use of the tool at the end of the implementation period&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> Therein lay the first major difference that precluded joint analysis of results obtained&#46; Moreover&#44; although the decrease in the use of the mobile app in the study by Quanbeck et al&#46; could be compared to findings in similar studies&#44; the lack of a control group rendered suitable appreciation of the results impossible&#46;</p></span><span id="sec0125" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0195">Costs</span><p id="par0200" class="elsevierStylePara elsevierViewall">None of the studies included evaluation of variation in costs due to the implementation of the model&#59; however&#44; Quanbeck et al&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> reported data related to implementation costs&#46; In that study&#44; the costs reported were subdivided into the following categories&#58; operational costs&#44; costs of implementation&#44; costs per patient and total costs for each of the three primary care centres in the study&#46; Operating costs per patient were estimated at 1185 United States dollars &#40;USD&#41;&#44; total costs per clinic were on average 124&#44;000 USD among the three clinics and costs per patients were an average of 1400 USD&#46;</p></span><span id="sec0130" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0200">Reach and response rate</span><p id="par0205" class="elsevierStylePara elsevierViewall">All studies included collected data with respect to the reach or response rate of the intervention&#44; but only in the study by Quanbeck et al&#46; was this explicitly defined as an outcome of interest&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> In the study by Sorkin et al&#46;&#44; the patients seen by physicians trained in the digital algorithms were significantly more likely to start on a prescription &#40;44&#37; versus 14&#37;&#59; p<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41; or begin active surveillance with psychological support &#40;2&#46;6&#37; versus 0&#37;&#59; p<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;008&#41; compared to the patients in the control group&#46; In the Allillanchu study&#44;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> of the 159 subjects eligible due to positive screening&#44; 127 attended the follow-up interview and 92 of them reported having sought help from a specialised professional after being advised to do so by their primary care physician&#46; In the SMART study&#44;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> of the 238 individuals identified as positive in the screening conducted by ASHAs&#44; just 30 &#40;13&#37;&#41; visited a physician&#44; 19 at health camps and 11 at primary care centres&#46; Following implementation of the model&#44; the use of mental health services was seen to increase from 0&#46;8&#37; at the start of the intervention to 12&#46;6&#37; at the end thereof&#46;</p><p id="par0210" class="elsevierStylePara elsevierViewall">Regarding the Quanbeck et al&#46; study&#44; out of 3&#44;226 patients eligible to use the Seva app&#44; 238 were enrolled in the study&#44; thus achieving a reach of 8&#46;31&#37; of people with substance use at the three sites of implementation of the study&#46; In this case&#44; the number of patients enrolled was correlated with the total number of mobile phones available at each care site&#59; this was mentioned as a limitation on achieving a greater reach&#46;</p><p id="par0215" class="elsevierStylePara elsevierViewall">The response rate achieved by the different studies varied greatly&#59; this variation might have been due to multiple factors&#46; One of them was related to the differences between the implementation sites&#58; models applied in urban areas&#44; as in the Allillanchu study in Lima&#44; Peru&#44; had a higher response rate compared to studies conducted in remote rural areas with limited opportunities for access to healthcare on the part of the target population&#44; as in the SMART project&#44; implemented in Andhra Pradesh&#44; India&#46; The differences in the mental health conditions addressed at each site may also have influenced the scope of the intervention&#59; patients with conditions associated with greater social stigma were less likely to enrol in the proposed care model&#46;</p></span></span></span><span id="sec0135" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0205">Discussion</span><p id="par0220" class="elsevierStylePara elsevierViewall">To our knowledge&#44; this review is the first to systematically evaluate existing evidence on technology-based care models for addressing mental health&#46; At present&#44; there are studies evaluating similar interventions&#44; but these studies have only evaluated one point in the patient&#39;s primary care<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> or adherence to a certain technology<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a>&#59; they have not assessed the structured implementation of an optimised model with digital technologies as a whole from patient identification to patient treatment and follow-up over time&#46; Although RCTs that evaluated technological interventions for mental health disorders were identified&#44;<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">20&#8211;22</span></a> they were excluded from the review as they did not take into account the different stages of patient care&#46; Of the five studies included&#44; just one was an RCT&#59; the other four lacked a control or randomisation process&#46; As a result&#44; the quality of the evidence was seriously compromised by a high risk of bias&#44; and this was compounded by small sample sizes and short follow-up periods&#46; The RCT included&#44; for its part&#44; was classified as having a high risk of bias due to compromise in its processes of participant screening&#44; blinding and analysis of outcomes&#46;</p><p id="par0225" class="elsevierStylePara elsevierViewall">The studies selected enabled identification of screening of medical disorders&#44; with apps on tablets being the most prevalent technology-enhanced process across the care models&#44; followed by patient treatment through mobile apps&#46; This was consistent with a recent systematic review that identified apps as the most commonly used digital technologies in the treatment of patients with severe mental illness&#46;<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a></p><p id="par0230" class="elsevierStylePara elsevierViewall">Moreover&#44; these studies showed an improvement in endpoints&#59; it was unclear&#44; however&#44; whether this was due solely to the implementation of a new model&#44; or to the implementation of the model added to the use of technological tools&#46; Psychotherapy and rehabilitation approaches start from the assumption that the individual is willing and able to dedicate time to this treatment&#44; allocate around one hour per session and engage in a longer-lasting type of treatment than other types of clinical intervention&#46; The use of technologies to facilitate application and adaptation of interventions has arisen as a result&#44; since it does not depend on office hours or hospital settings&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a> On the other hand&#44; it does involve more active participation on the part of the patient&#59; it also entails subsequent legal and professional responsibility in services and treatments provided or indicated through these platforms&#44; which might alter the communication between the two players&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a></p><p id="par0235" class="elsevierStylePara elsevierViewall">With this in mind&#44; this review did not find sufficient evidence to support the use of a technology-based mental healthcare model over other existing models&#46;</p><span id="sec0140" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0210">Strengths and limitations</span><p id="par0240" class="elsevierStylePara elsevierViewall">One of the greatest strengths of this review was the spectrum of models sought&#58; no mental health disorder&#44; time of care or technology used was excluded&#46; The search was also not limited by year&#44; location&#44; or language&#44; which ensured that it would encompass a larger quantity of pertinent articles&#46; In focusing on studies that assessed interventions linked to the development of a care model&#44; we arrived at a better evaluation of the use of technologies as tools intended to optimise care processes for patients with mental disorders and the effectiveness of interventions in a care context closer to reality&#46;</p><p id="par0245" class="elsevierStylePara elsevierViewall">However&#44; this review did have some limitations&#44; which could not be separated from its greatest strengths&#46; Given that we did not limit our searches according to the above-mentioned criteria&#44; we found a great deal of heterogeneity among studies&#46; This made it impossible to conduct a quantitative synthesis of the results for disorders across studies such as depression and anxiety&#46; Although individual findings with respect to these interventions were favourable across all studies&#44; their low methodological quality undermined confidence in the results obtained&#46; First and foremost&#44; the absence of randomisation and a control group due to confounding factors&#44; added to other previously mentioned factors&#44; seriously affected the quality of the evidence&#46;</p><p id="par0250" class="elsevierStylePara elsevierViewall">In addition&#44; the small number of eligible studies restricted the robustness of the conclusions of this study&#46; This limitation can be attributed in part to the process of determining the definition of a &#34;care model&#34;&#46; Given that the existing literature on this topic is scant&#44; the review team adapted a set of characteristics considered essential when determining whether the studies retrieved featured mental healthcare models&#46; This contributed in large part to the limited number of eligible studies identified and the lack of homogeneity among those studies&#46;</p><p id="par0255" class="elsevierStylePara elsevierViewall">Moreover&#44; there was likely some publication bias&#44; bearing in mind that the search was primarily focused on the most important electronic databases and did not delve into grey literature&#46; Added to this was the fact that the low number of studies included did not allow for an analysis using funnel diagrams or statistical methods to evaluation publication bias&#46;</p></span><span id="sec0145" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0215">Implications for practice and future research</span><p id="par0260" class="elsevierStylePara elsevierViewall">For implementation research on healthcare models to result in learning processes on a national or global level&#44; studies of good methodological quality that evaluate both the implementation of models and the effectiveness of the interventions derived from them must be conducted&#46; Regarding evaluation of effectiveness&#44; the way in which confounding factors are controlled for must always be assessed&#44; either through randomisation processes or through analysis of baseline characteristics in groups and possible factors that could end up influencing outcomes&#46; The conduct of hybrid implementation&#47;effectiveness studies could help to address this divide&#44; in particular hybrid type 2 studies since they are focused on simultaneous evaluation of clinical interventions and implementation outcomes&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> In addition&#44; as we did not find studies done in a context similar to Colombia&#44; we believe it is important to conduct feasibility studies adapted to the needs and capacities of the Colombian population and health system&#46;</p><p id="par0265" class="elsevierStylePara elsevierViewall">Among the studies identified&#44; those that evaluated the use of digital apps during the treatment phase did so by creating and testing their own apps&#46; However&#44; none of the studies developed these apps according to pre-established recommendations or consensuses&#46; Although scant literature exists to date&#44; a recent review set out multiple considerations in creating mental health apps in order to improve the functionality of these digital tools&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> Future research should focus on standardising app development according to evidence-based recommendations&#44; then validating these tools by means of experimental studies&#46; In addition&#44; longer follow-up times are desirable to evaluate patient adherence to such digital tools&#44; the use of which is essentially self-regulated&#46;</p></span></span><span id="sec0150" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0220">Conclusion</span><p id="par0270" class="elsevierStylePara elsevierViewall">This review provides clinicians and decision-makers with a synthesis of the evidence existing to date on technology-based care models for the broad spectrum of disorders in mental health&#46; Implementation of technological models that address the different stages of patient care&#44; as seen in the five studies included&#44; is a viable strategy that could optimise processes of screening&#44; diagnosis&#44; treatment and follow-up of patients with this type of disorder&#46; However&#44; the evidence existing to date and the quality thereof are insufficient for determining whether a technology-enhanced care model is superior to other similar models in addressing mental health&#46; Studies with good methodological quality that evaluate the implementation and effectiveness of these models must be conducted before the best technology-based mental healthcare model can be identified&#46;</p></span><span id="sec0155" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0225">Funding</span><p id="par0275" class="elsevierStylePara elsevierViewall">The research reported in this publication was funded by the <span class="elsevierStyleGrantSponsor" id="gs0005">National Institute of Mental Health</span> &#40;NIMH&#41; of the National Institutes of Health &#40;NIH&#41; of the United States with Grant Number <span class="elsevierStyleGrantNumber" refid="gs0005">1U19MH109988</span> &#40;multiple principal investigators&#58; Lisa A&#46; Marsch&#44; PhD&#44; and Carlos G&#243;mez-Restrepo&#44; MD&#44; PhD&#41;&#46; Juan Camilo Rosas and Arturo Marroqu&#237;n Rivera participated as Young Researchers&#44; funded by the <span class="elsevierStyleGrantSponsor" id="gs0010">J&#243;venes Investigadores e Innovadores</span> program by the Colombian Ministry of Science&#44; Technology and Innovation &#40;Contract 829&#44; 2018&#41;&#46;</p></span><span id="sec0160" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0230">Conflicts of interest</span><p id="par0280" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest&#46;</p></span></span>"
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        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">This systematic review summarises the existing evidence on the implementation of technology-based mental healthcare models in the primary care setting&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">A systematic search was conducted &#40;MEDLINE&#44; Embase&#44; CENTRAL&#41; in August 2019 and studies were selected according to predefined eligibility criteria&#46; The main outcomes were clinical effectiveness&#44; adherence to primary treatment and cost of implementation&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Selection criteria</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Studies with an experimental or quasi-experimental design that evaluated the implementation of technology-based mental healthcare models were included&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Five articles met the inclusion criteria&#46; The models included technological devices such as tablets&#44; cellphones and computers&#44; with programs and mobile apps that supported decision-making in the care pathway&#46; These decisions took place at different times&#44; from the universal screening phase to the follow-up of patients with specific conditions&#46; In general&#44; the studies showed a decrease in the reported symptoms&#46; However&#44; there was great heterogeneity in both the health conditions and the outcomes&#44; which hindered a quantitative synthesis&#46; The assessment of risk of bias showed low quality of evidence&#46;</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusion</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">There is not enough evidence to support the implementation of a technology-based mental healthcare model&#46; High quality studies that focus on implementation and effectiveness outcomes are needed to evaluate the impact of technology-based mental healthcare models in the primary care setting&#46;</p></span>"
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        "resumen" => "<span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Introducci&#243;n</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Esta revisi&#243;n sistem&#225;tica resume la evidencia existente sobre los modelos de implementaci&#243;n basados en tecnolog&#237;as para el abordaje de la salud mental en el contexto de la atenci&#243;n primaria&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">M&#233;todos</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Se realiz&#243; una b&#250;squeda sistem&#225;tica en las principales bases de datos electr&#243;nicas &#40;MEDLINE&#44; Embase&#44; CENTRAL&#41; en agosto del 2019 y se eligieron estudios seg&#250;n criterios de selecci&#243;n predefinidos&#46; Los desenlaces principales fueron efectividad cl&#237;nica&#44; adherencia al tratamiento y costos de implementaci&#243;n&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Criterios de selecci&#243;n</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Se incluyeron estudios con dise&#241;os experimentales o cuasiexperimentales que evaluaran la implementaci&#243;n de modelos basados en tecnolog&#237;as para el abordaje de la salud mental&#46;</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Resultados</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Cinco art&#237;culos cumplieron con los criterios de selecci&#243;n&#46; Los modelos inclu&#237;an dispositivos tecnol&#243;gicos como tabletas&#44; celulares y computadores con programas y aplicativos m&#243;viles que ayudaban con la toma de decisiones en la ruta de atenci&#243;n&#46; Estas ten&#237;an lugar en diferentes momentos&#44; desde el tamizaje a la poblaci&#243;n general&#44; hasta el seguimiento de los pacientes con alguna condici&#243;n espec&#237;fica&#46; De forma general&#44; en los estudios se evidencia una disminuci&#243;n de los s&#237;ntomas reportados&#44; sin embargo&#44; tanto las condiciones de salud como los desenlaces muestran gran heterogeneidad&#44; lo que impidi&#243; realizar una s&#237;ntesis cuantitativa&#46; La evaluaci&#243;n del riesgo de sesgo mostr&#243; baja calidad de la evidencia&#46;</p></span> <span id="abst0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Conclusi&#243;n</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">No hay suficiente evidencia para determinar la superioridad de un modelo de atenci&#243;n optimizado por tecnolog&#237;as para el abordaje de la salud mental&#46; Es necesario realizar estudios primarios con una adecuada calidad metodol&#243;gica que eval&#250;en desenlaces relevantes de implementaci&#243;n y efectividad&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0020">Please cite this article as&#58; Rosas JC&#44; G&#243;mez-Ayala MC&#44; Rivera AM&#44; Botero-Rodr&#237;guez F&#44; Cepeda M&#44; Su&#225;rez-Obando F&#44; et al&#46; Modelos de atenci&#243;n en salud mental basados en tecnolog&#237;as&#58; revisi&#243;n sistem&#225;tica de la literatura&#46; Rev Colomb Psiquiat&#46; 2021&#59;50&#58;30&#8211;41&#46;</p>"
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&#91;Mesh&#93; OR &#34;Urban Health Services&#34; &#91;Mesh&#93; OR &#34;Delivery of Health Care&#34; &#91;Mesh&#93; OR &#34;Quality Indicators&#44; Health Care&#34; &#91;Mesh&#93; OR &#34;Health Care Sector&#34; &#91;Mesh&#93; OR &#34;Health Care Surveys&#34; &#91;Mesh&#93; OR &#34;Delivery of Health Care&#44; Integrated&#34; &#91;Mesh&#93; OR &#34;Health Care Reform&#34; &#91;Mesh&#93; OR &#34;Peer Review&#44; Health Care&#34; &#91;Mesh&#93; OR &#34;Health Care Evaluation Mechanisms&#34; &#91;Mesh&#93; OR &#34;Health Care Quality&#44; Access&#44; and Evaluation&#34; &#91;Mesh&#93; OR &#34;Process Assessment &#40;Health Care&#41;&#34; &#91;Mesh&#93; OR &#34;Outcome Assessment &#40;Health Care&#41;&#34; &#91;Mesh&#93; OR &#34;Health Care Costs&#34; &#91;Mesh&#93; OR &#34;Health Care Rationing&#34; &#91;Mesh&#93; OR &#34;Quality of Health Care&#34; &#91;Mesh&#93; OR &#34;Quality Assurance&#44; Health Care&#34; &#91;Mesh&#93; AND &#40;&#34;Primary Health Care&#34; &#91;Mesh&#93;&#41; AND &#40;mental health OR mental diseases OR mental disorders OR &#34;Mental Health&#34; &#91;Mesh&#93; OR &#34;Mental Health Services&#34; &#91;Mesh&#93; OR &#34;Mental Health Associations&#34; &#91;Mesh&#93; OR &#34;Community Mental Health Services&#34; &#91;Mesh&#93; OR &#34;Community Mental Health Centers&#34; &#91;Mesh&#93; OR &#34;Mental Health Recovery&#34; &#91;Mesh&#93; OR &#34;Health Plan Implementation&#34; &#91;Mesh&#93; AND &#40;Mobile Applications&#34; &#91;Mesh&#93; OR Electronics&#34; &#91;Mesh&#93; OR Electronic Health Records&#34; &#91;Mesh&#93; OR Electronic Data Processing&#34; &#91;Mesh&#93; OR Technology&#34; &#91;Mesh&#93; OR &#34;Wireless Technology&#34; &#91;Mesh&#93; OR &#34;Remote Sensing Technology&#34; &#91;Mesh&#93; OR &#34;Biomedical Technology&#34; &#91;Mesh&#93; OR &#34;Educational Technology&#34; &#91;Mesh&#93; OR &#34;Technology&#44; High-Cost&#34; &#91;Mesh&#93; OR &#34;Technology Assessment&#44; Biomedical&#34; &#91;Mesh&#93; OR &#34;Information Technology&#34; &#91;Mesh&#93; OR &#34;Cell Phone&#34; &#91;Mesh&#93; OR &#34;Cell Phone Use&#34; &#91;Mesh&#93; OR &#34;Smartphone&#34; &#91;Mesh&#93; OR &#34;Text Messaging&#34; &#91;Mesh&#93; OR &#34;Computers&#44; Handheld&#34; &#91;Mesh&#93; OR e-medicine OR mhealth OR emedicine OR telemedicine OR ipad&#42; OR &#34;Personal Digital Assistant&#42;&#34; OR pda&#42; OR palmtop&#42; OR &#34;videotape&#34; &#91;All Fields&#93; OR &#34;recording&#34; &#91;All Fields&#93; OR &#34;videotape recording&#34; &#91;All Fields&#93; OR &#34;video&#34;&#91;All Fields&#93; OR &#34;telecoaching&#34; &#91;All Fields&#93; OR &#34;teleconference&#34; &#91;All Fields&#93; OR &#34;educational technology&#34; &#91;All Fields&#93; OR &#34;internet&#34; &#91;MeSH Terms&#93;&#41;&#46;</p> <p id="par0295" class="elsevierStylePara elsevierViewall">Web of science&#58; &#40;&#34;implementation&#34; OR &#34;care model&#34; OR &#34;Health plan implementation&#34; OR &#34;implementation science&#34; OR &#34;regional health planning&#34; OR &#34;social planning&#34;&#41; AND &#40;&#34;mental health&#34; OR &#34;mental disease&#34; OR &#34;mental disorders therapy&#34; OR &#34;mental health service&#34; OR &#34;community mental health&#34; OR &#34;mental health recovery&#34;&#41; AND &#40;&#34;mobile application&#34; OR &#34;electronics&#34; OR &#34;electronic medical record&#34; OR &#34;information processing&#34; OR &#34;technology&#34; OR &#34;wireless communication&#34; OR &#34;medical technology&#34; OR &#34;educational technology&#34; OR &#34;biomedical technology assessment&#34; OR &#34;information technology device&#34; OR &#34;mobile phone&#34; OR &#34;wireless communication&#34; OR &#34;medical technology&#34; OR &#34;wireless technology&#34; OR &#34;cell phone&#34; OR &#34;smartphone&#34; OR &#34;text messaging&#34; OR &#34;handheld computers&#34; OR &#34;mhealth&#34; OR &#34;palmtop&#34; OR &#34;video&#34; OR &#34;telecoaching&#34; OR &#34;internet&#34;&#41;&#46;</p> <p id="par0300" class="elsevierStylePara elsevierViewall">EMBASE&#58; &#40;&#39;implementation science&#39;&#47;exp OR &#39;health care planning&#39;&#47;exp OR &#39;social aspect&#39;&#47;exp OR &#39;risk evaluation and mitigation strategy&#39;&#47;exp OR &#39;health service&#39;&#47;exp OR &#39;public health service&#39;&#47;exp OR &#39;preventive health service&#39;&#47;exp OR &#39;health care delivery&#39;&#47;exp&#41; AND &#40;&#39;primary health care&#39;&#47;exp&#41; AND &#40;&#39;mental health&#39;&#47;exp OR &#39;mental disease&#39;&#47;exp OR &#39;mental disorders therapy&#39;&#47;exp OR &#39;mental health service&#39;&#47;exp OR &#39;community mental health&#39;&#47;exp OR &#39;mental health recovery&#39;&#47;exp OR &#39;health care planning&#39;&#47;exp&#41; AND &#40;&#39;mobile application&#39;&#47;exp OR &#39;electronics&#39;&#47;exp OR &#39;electronic medical record&#39;&#47;exp OR &#39;information processing&#39;&#47;exp OR &#39;technology&#39;&#47;exp OR &#39;wireless communication&#39;&#47;exp OR &#39;medical technology&#39;&#47;exp OR &#39;educational technology&#39;&#47;exp OR &#39;biomedical technology assessment&#39;&#47;exp OR &#39;information technology device&#39;&#47;exp OR &#39;mobile phone&#39;&#47;exp OR &#39;smartphone&#39;&#47;exp OR &#39;text messaging&#39;&#47;exp OR &#39;personal digital assistant&#39;&#47;exp OR &#39;mhealth&#39;&#47;exp OR &#39;telemedicine&#39;&#47;exp OR &#39;tablet computer&#39;&#47;exp OR &#39;educational technology&#39;&#47;exp OR &#39;Internet&#39;&#47;exp&#41;&#46;</p> <p id="par0305" class="elsevierStylePara elsevierViewall">The Cochrane Library&#58; &#40;mh &#34;implementation science&#34; OR mh &#34;health planning&#34; OR mh &#34;health plan implementation&#34; OR mh &#34;regional health planning&#34;&#41; AND &#40;mh &#34;Primary Health Care&#41; AND &#40;mh &#34;mental health&#34; OR mh &#34;mentally ill persons&#34; OR mh &#34;mental disorders&#34; OR mh &#34;mental health services&#34; OR mh &#34;community mental health centers&#34; OR mh &#34;community mental health services&#34; OR mh &#34;mental health recovery&#34;&#41; AND &#40;mh technology OR mh &#34;mobile applications OR mh electronics OR mh &#34;electronic health records&#34; OR mh &#34;electronic data processing&#34; OR mh &#34;wireless technology&#34; OR mh &#34;Biomedical technology&#34; OR mh &#34;educational technology&#34; OR mh &#34;information technology&#34; OR mh &#34;cell phone&#34; OR mh smartphone OR mh &#34;text messaging&#34; OR mh &#34;computers&#44; handheld&#34; OR mh telemedicine OR mhealth OR emedicine OR telemedicine OR ipad OR palmtop OR video OR internet&#41;</p> <p id="par0310" class="elsevierStylePara elsevierViewall">PSYCHinfo&#58; implementation OR model of care OR &#34;Health Plan Implementation&#34; OR &#34;Implementation Science&#34; OR &#34;Regional Health Planning&#34; OR &#34;Social Planning&#34; OR &#34;Risk Evaluation and Mitigation&#34; OR &#34;Health Services&#34; OR &#34;United States Public Health Service&#34; OR &#34;Women&#39;s Health Services&#34; OR &#34;Student Health Services&#34; OR &#34;Child Health Services&#34; OR &#34;School Health Services&#34; OR &#34;United States Indian Health Service&#34; OR &#34;Preventive Health Services&#34; OR &#34;Adolescent Health Services&#34; OR Personal Health Services&#34; OR Rural Health Services&#34; OR &#34;Suburban Health Services&#34; OR &#34;Urban Health Services&#34; OR &#34;Delivery of Health Care&#34; OR &#34;Quality Indicators&#44; Health Care&#34; OR &#34;Health Care Sector&#34; OR &#34;Health Care Surveys&#34; OR &#34;Delivery of Health Care&#44; Integrated&#34; OR &#34;Health Care Reform&#34; OR &#34;Peer Review&#44; Health Care&#34; OR &#34;Health Care Evaluation Mechanisms&#34; OR &#34;Health Care Quality&#44; Access&#44; and Evaluation&#34; OR &#34;Process Assessment&#34; OR &#34;Outcome Assessment&#34; OR &#34;Health Care Costs&#34; OR &#34;Health Care Rationing&#34; OR &#34;Quality of Health Care&#34; OR &#34;Quality Assurance&#44; Health Care&#34;&#41; AND &#40;&#34;Primary Health Care&#34;&#41; AND &#40;mental health OR mental diseases OR mental disorders OR &#34;Mental Health&#34; OR &#34;Mental Health Services&#34; OR &#34;Mental Health Associations&#34; OR &#34;Community Mental Health Services&#34; OR &#34;Community Mental Health Centers&#34; OR &#34;Mental Health Recovery&#34; OR &#34;Health Plan Implementation&#34;&#41; AND &#40;&#34;Mobile Applications&#34; OR &#34;Electronics&#34; OR &#34;Electronic Health Records&#34; OR &#34;Electronic Data Processing&#34; OR &#34;Technology&#34; OR &#34;Wireless Technology&#34; OR &#34;Remote Sensing Technology&#34; OR &#34;Biomedical Technology&#34; OR &#34;Educational Technology&#34; OR &#34;Technology&#44; High-Cost&#34; OR &#34;Technology Assessment&#44; Biomedical&#34; OR &#34;Information Technology&#34; OR &#34;Cell Phone&#34; OR &#34;Cell Phone Use&#34; OR &#34;Smartphone&#34; OR &#34;Text Messaging&#34; OR &#34;Computers&#44; Handheld&#34; OR e-mdicine OR e-medicine OR mhealth OR emedicine OR telemedicine OR ipad&#42; OR &#34;Personal Digital Assistant&#42;&#34; OR pda&#42; OR pad OR palmtop&#42; OR &#34;videotape&#34; OR &#34;recording&#34; OR &#34;videotape recording&#34; OR &#34;video&#34; OR &#34;telecoaching&#34; OR &#34;teleconference&#34; OR &#34;educational technology&#34; OR &#34;internet&#34;&#46;</p> <p id="par0315" class="elsevierStylePara elsevierViewall">LILACS&#58; &#40;salud mental OR mental health&#41; AND &#40;prevenci&#243;n OR atenci&#243;n primaria&#41; AND &#40;tw&#58;telemedicina OR e-medicine OR tecnologia OR technology&#41; AND &#40;tw&#58;modelo&#41;&#46;</p>"
            "etiqueta" => "Appendix A"
            "titulo" => "Search strategy"
            "identificador" => "sec0165"
          ]
        ]
      ]
    ]
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      0 => array:8 [
        "identificador" => "fig0005"
        "etiqueta" => "Figure 1"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr1.jpeg"
            "Alto" => 3564
            "Ancho" => 3318
            "Tamanyo" => 745943
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        ]
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0005"
            "detalle" => "Figure "
            "rol" => "short"
          ]
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        "descripcion" => array:1 [
          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Models identified and technology use by implementation stage&#46;</p> <p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">a&#41; Yu&#44; 2018&#46; GAD-7&#58; generalised anxiety disorder-7&#46; SMS&#58; short message service&#46;</p> <p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">b&#41; SMART&#44; 2017&#46; GAD-7&#58; generalised anxiety disorder-7&#46; PHQ-9&#58; patient health questionnaire-9&#46; EDSS&#58; electronic decision support system&#46; IVRS&#58; interactive voice response system&#46; ASHAs&#58; accredited social health activist&#46;</p> <p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">c&#41; The Allillanchu Project&#44; 2018&#46; SRQ&#58; self-reporting questionnaire&#46;</p> <p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">d&#41; Quanbeck&#44; 2018&#46;</p> <p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">e&#41; Sorkin&#44; 2019&#46; HSC&#58; Hopkins System Checklist&#46; HQT&#58; Harvard Trauma Questionnaire&#46;</p>"
        ]
      ]
      1 => array:8 [
        "identificador" => "fig0010"
        "etiqueta" => "Figure 2"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr2.jpeg"
            "Alto" => 1697
            "Ancho" => 1508
            "Tamanyo" => 179038
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        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0010"
            "detalle" => "Figure "
            "rol" => "short"
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">PRISMA flow chart&#46;</p>"
        ]
      ]
      2 => array:8 [
        "identificador" => "tbl0005"
        "etiqueta" => "Table 1"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0015"
            "detalle" => "Table "
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        "tabla" => array:2 [
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Name of study &#8212; Year&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Type of study&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Implementation site&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Target population&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Participant care site&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Number of participants &#40;n&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mental health conditions evaluated&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Phases included in the model&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Technological tools&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Primary outcomes&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Follow-up time&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">SMART&#44; 2017&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Before-and-after study with no control&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Andhra Pradesh&#44; India&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adults over 18 years of age&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Two primary care centres&#44; homes of participants &#40;30 villages of registered tribes&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">238&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Depression and anxiety&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Screening&#44; diagnosis&#44; treatment and follow-up&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Tablet&#44; EDSS<a class="elsevierStyleCrossRef" href="#tblfn0005">&#42;</a>&#44; IVRS<a class="elsevierStyleCrossRef" href="#tblfn0010">&#42;&#42;</a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Change on clinical scale&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 months&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">The Allillanchu Project&#44; 2018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Mixed-methods study&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Lima&#44; Peru&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adults over 18 years of age&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Five public general primary care centres&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">143&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Depression&#44; anxiety&#44; psychosis&#44; seizure disorder&#44; AUD<a class="elsevierStyleCrossRef" href="#tblfn0015">&#42;&#42;&#42;</a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Screening&#44; intervention&#44; follow-up&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Tablet&#44; digital platform&#44; text messages&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Seeking of mental healthcare&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 weeks&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care&#44; 2018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Type 2 hybrid effectiveness&#47;implementation study&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">United States&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adults over 18 years of age with a diagnosis of&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">A primary care centre for patients with psychoactive substance use disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">207&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Psychoactive substance use disorder&#44; AUD&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Diagnosis&#44; treatment&#44; follow-up&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Mobile app&#44; website&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Substance use&#44; quality of life&#44; use of medical services&#44; model adoption&#44; costs&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6 months&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Implementation of a Guided&#44; Digital Cognitive Behavioral Program for Anxiety in Primary Care&#58; Preliminary Findings of Engagement and Effectiveness&#44; 2018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Before-and-after study with no control&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">United States&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adults 20&#8722;65 years of age&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Four general primary care centres&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">63&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Anxiety&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Screening&#44; diagnosis&#44; treatment and follow-up&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Change on clinical scale&#44; commitment to app use&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " colspan="11" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#91;0&#44;1&#8211;11&#93;</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Novel Health Information Technology to Aid Provider Recognition and Treatment of Major Depressive Disorder and Posttraumatic Stress Disorder in Primary Care&#44; 2019&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Randomised two-group &#40;two-arm&#41; trial&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">United States&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Adults over 18 years of age Refugees from Cambodia in the United States&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Two community clinics with a federal primary care qualification&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">390 patients &#40;272 in the intervention group and 118 in the control group&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">Depression&#44; post-traumatic stress disorder&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Screening&#44; diagnosis&#44; treatment and follow-up&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Tablet&#44; electronic app with evidence-based information&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Change on clinical scale&#44; concordance between positive screening and medical diagnosis&#44; following of evidence-based recommendations&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12 months&nbsp;\t\t\t\t\t\t\n
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                0 => array:2 [
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                          "autores" => array:3 [
                            0 => "K&#46;-Y&#46; Huang"
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                      "Revista" => array:5 [
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                  "contribucion" => array:1 [
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                          "autores" => array:6 [
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              "referencia" => array:1 [
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                  "contribucion" => array:1 [
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                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "E&#46; Aharonovicha"
                            1 => "M&#46; Stohlb"
                            2 => "D&#46; Cannizzarob"
                            3 => "D&#46; Hasin"
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                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/j.jsat.2017.09.013"
                      "Revista" => array:6 [
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Article information

ISSN: 25303120
Original language: English

DOI:10.1016/j.rcpeng.2021.07.002

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