Smartphone-based safety planning and self-monitoring for suicidal patients: Rationale and study protocol of the CASPAR (Continuous Assessment for Suicide Prevention And Research) study

Background: It remains difficult to predict and prevent suicidal behaviour, despite growing understanding of the aetiology of suicidality. Clinical guidelines recommend that health care professionals develop a safety plan in collaboration with their high-risk patients, to lower the imminent risk of suicidal behaviour. Mobile health applications provide new opportunities for safety planning, and enable daily self-monitoring of suicide-related symptoms that may enhance safety planning. This paper presents the rationale and protocol of the Continuous Assessment for Suicide Prevention And Research (CASPAR) study. The aim of the study is two-fold: to evaluate the feasibility of mobile safety planning and daily mobile self-monitoring in routine care treatment for suicidal patients, and to conduct fundamental research on suicidal processes. Methods: The study is an adaptive single cohort design among 80 adult outpatients or day-care patients, with the main diagnosis of major depressive disorder or dysthymia, who have an increased risk for suicidal behaviours. There are three measurement points, at baseline, at 1 and 3 months after baseline. Patients are instructed to use their mobile safety plan when necessary and monitor their suicidal symptoms daily. Both these apps will be used in treatment with their clinician. Conclusion: The results from this study will provide insight into the feasibility of mobile safety planning and self-monitoring in treatment of suicidal patients. Furthermore, knowledge of the suicidal process will be enhanced, especially regarding the transition from suicidal ideation to behaviour

Application of Smartphone Technology in the Management and Treatment of Mental Illnesses

Abstract: Background: Mental illness continues to be a significant Public Health problem and the innovative use of technology to improve the treatment of mental illnesses holds great public health relevance. Over the past decade telecommunications technology has been used to increase access to and improve the quality of mental health care. There is current evidence that the use of landline and cellular telephones, computer-assisted therapy, and videoconferencing can be effective in improving treatment outcomes. Smartphones, as the newest development in communications technology, offer a new opportunity to improve mental health care through their versatile nature to perform a variety of functions. Methods: A critical literature review was performed to examine the potential of smartphones to increase access to mental health care, reduce barriers to care, and improve patient treatment outcomes. The review was performed by searching several electronic databases using a combination of keywords related to smartphones and mental health interventions using mobile devices. Literature concerning the use of cell phones, handheld computers, and smartphones to improve access to mental health care and improve treatment outcomes was identified.Results: The majority of studies identified were feasibility and pilot studies on patients with a variety of diagnosed mental illnesses using cell phones and PDAs. Authors report that most study participants, with some exceptions, were capable of using a mobile device and found them acceptable to use. Few studies extensively measured treatment outcomes and instead reported preliminary results and presented case illustrations. Studies which used smartphones successfully used them collect data on patients and deliver multimedia interventions. Discussion: The current literature offers encouraging evidence for the use of smartphones to improve mental health care but also reflects the lack of research conducted using smartphones. Studies which examine care provider use of smartphones to improve care is encouraging but has limited generalizability to mental health care. The feasibility of patient use of smartphones is also encouraging, but questions remain about feasibility in some sub-populations, particularly schizophrenia patients. Pilot testing of mobile devices and applications can greatly increase the feasibility of using smartphones in mental health care. Patients who are unfamiliar with smartphones will likely need initial training and support in their use. Conclusion: The literature identified several ways in which smartphones can increase access to care, reduce barriers, and improve treatment outcomes. Study results were encouraging but scientifically weak. Future studies are needed replicating results of studies using cell phones and PDAs on smartphones. Larger and higher quality studies are needed to examine the feasibility, efficacy, and cost-effectiveness of smartphones to deliver multiple component interventions that improve access to mental health care and improve treatment outcomes

Increasing physical activity in older adults using STARFISH, an interactive smartphone application (app); a pilot study

Background:Increasing physical activity in older adults has preventative and therapeutic health benefits. We have developed STARFISH, a smartphone application, to increase physical activity. This paper describes the features of STARFISH, presents the views of older users on the acceptability and usability of the app and reports the results of a six week pilot study of the STARFISH app in older adults. Methods:The operationalisation of the behaviour change techniques (BCTs) within the STARFISH app was mapped against the BCT Taxonomy of Michie et al. Sixteen healthy older adults (eight women and eight men; age 71.1 ± 5.2 years) used the app, in groups of four, for six weeks. Focus groups explored the user experience and objective measure of steps per day recorded. Results:Participants were very positive about using the STARFISH app, in particular the embedded BCTs of self-monitoring, feedback and social support (in the form of group rewards). Objective step data, available for eight participants, showed that step counts increased by an average of 14% (p = 0.077, d = 0.56). Conclusion:The STARFISH app was acceptable and straightforward to use for older adults. STARFISH has potential to increase physical activity in older adults; however, a fully powered randomised controlled trial is required

Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol

The screening of digital footprint for clinical purposes relies on the capacity of wearable technologies to collect data and extract relevant information’s for patient management. Artificial intelligence (AI) techniques allow processing of real-time observational information and continuously learning from data to build understanding. We designed a system able to get clinical sense from digital footprints based on the smartphone’s native sensors and advanced machine learning and signal processing techniques in order to identify suicide risk. Method/design: The Smartcrisis study is a cross-national comparative study. The study goal is to determine the relationship between suicide risk and changes in sleep quality and disturbed appetite. Outpatients from the Hospital Fundación Jiménez Díaz Psychiatry Department (Madrid, Spain) and the University Hospital of Nimes (France) will be proposed to participate to the study. Two smartphone applications and a wearable armband will be used to capture the data. In the intervention group, a smartphone application (MEmind) will allow for the ecological momentary assessment (EMA) data capture related with sleep, appetite and suicide ideations. Discussion: Some concerns regarding data security might be raised. Our system complies with the highest level of security regarding patients’ data. Several important ethical considerations related to EMA method must also be considered. EMA methods entails a non-negligible time commitment on behalf of the participants. EMA rely on daily, or sometimes more frequent, Smartphone notifications. Furthermore, recording participants’ daily experiences in a continuous manner is an integral part of EMA. This approach may be significantly more than asking a participant to complete a retrospective questionnaire but also more accurate in terms of symptoms monitoring. Overall, we believe that Smartcrises could participate to a paradigm shift from the traditional identification of risks factors to personalized prevention strategies tailored to characteristics for each patientThis study was partly funded by Fundación Jiménez Díaz Hospital, Instituto de Salud Carlos III (PI16/01852), Delegación del Gobierno para el Plan Nacional de Drogas (20151073), American Foundation for Suicide Prevention (AFSP) (LSRG-1-005-16), the Madrid Regional Government (B2017/BMD-3740 AGES-CM 2CM; Y2018/TCS-4705 PRACTICO-CM) and Structural Funds of the European Union. MINECO/FEDER (‘ADVENTURE’, id. TEC2015–69868-C2–1-R) and MCIU Explora Grant ‘aMBITION’ (id. TEC2017–92552-EXP), the French Embassy in Madrid, Spain, The foundation de l’avenir, and the Fondation de France. The work of D. Ramírez and A. Artés-Rodríguez has been partly supported by Ministerio de Economía of Spain under projects: OTOSIS (TEC2013–41718-R), AID (TEC2014–62194-EXP) and the COMONSENS Network (TEC2015–69648-REDC), by the Ministerio de Economía of Spain jointly with the European Commission (ERDF) under projects ADVENTURE (TEC2015– 69868-C2–1-R) and CAIMAN (TEC2017–86921-C2–2-R), and by the Comunidad de Madrid under project CASI-CAM-CM (S2013/ICE-2845). The work of P. Moreno-Muñoz has been supported by FPI grant BES-2016-07762

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

Examining adherence to activity monitoring devices to improve physical activity in adults with cardiovascular disease: A systematic review

Background Activity monitoring devices are currently being used to facilitate and monitor physical activity. No prior review has examined adherence to the use of activity monitoring devices amongst adults with cardiovascular disease. Methods Literature from June 2012 to October 2017 was evaluated to examine the extent of adherence to any activity monitoring device used to collect objective physical activity data. Randomized control trials comparing usual care against the use of an activity monitoring device, in a community intervention for adults from any cardiovascular diagnostic group, were included. A systematic search of databases and clinical trials registers was conducted using Joanna Briggs Institute methodology. Results Of 10 eligible studies, two studies reported pedometer use and eight accelerometer use. Six studies addressed the primary outcome. Mean adherence was 59.1% (range 39.6% to 85.7%) at last follow-up. Studies lacked equal representation by gender (28.6% female) and age (range 42 to 82 years). Conclusion This review indicates that current research on activity monitoring devices may be overstated due to the variability in adherence. Results showed that physical activity tracking in women and in young adults have been understudied

Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour : a systematic review

Background: Health and fitness applications (apps) have gained popularity in interventions to improve diet, physical activity and sedentary behaviours but their efficacy is unclear. This systematic review examined the efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour in children and adults. Methods: Systematic literature searches were conducted in five databases to identify papers published between 2006 and 2016. Studies were included if they used a smartphone app in an intervention to improve diet, physical activity and/or sedentary behaviour for prevention. Interventions could be stand-alone interventions using an app only, or multi-component interventions including an app as one of several intervention components. Outcomes measured were changes in the health behaviours and related health outcomes (i.e., fitness, body weight, blood pressure, glucose, cholesterol, quality of life). Study inclusion and methodological quality were independently assessed by two reviewers. Results: Twenty-seven studies were included, most were randomised controlled trials (n = 19; 70%). Twenty-three studies targeted adults (17 showed significant health improvements) and four studies targeted children (two demonstrated significant health improvements). Twenty-one studies targeted physical activity (14 showed significant health improvements), 13 studies targeted diet (seven showed significant health improvements) and five studies targeted sedentary behaviour (two showed significant health improvements). More studies (n = 12; 63%) of those reporting significant effects detected between-group improvements in the health behaviour or related health outcomes, whilst fewer studies (n = 8; 42%) reported significant within-group improvements. A larger proportion of multi-component interventions (8 out of 13; 62%) showed significant between-group improvements compared to stand-alone app interventions (5 out of 14; 36%). Eleven studies reported app usage statistics, and three of them demonstrated that higher app usage was associated with improved health outcomes. Conclusions: This review provided modest evidence that app-based interventions to improve diet, physical activity and sedentary behaviours can be effective. Multi-component interventions appear to be more effective than standalone app interventions, however, this remains to be confirmed in controlled trials. Future research is needed on the optimal number and combination of app features, behaviour change techniques, and level of participant contact needed to maximise user engagement and intervention efficacy

Evaluating the impact of physical activity apps and wearables: interdisciplinary review

Background: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work. Objectives: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. Method: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. Results: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). Conclusions: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines

Effectiveness and Feasibility of In-office versus Smartphone Text-delivered Nutrition Education in the College Setting: A Mixed-methods Pilot Study

Often, being away from home for the first time, coupled with limited knowledge regarding healthy eating behaviors, leads to poor food choices and an increased risk of obesity among college-aged young adults. These college students are prone to high-calorie diets and limited physical activity, putting them at risk for obesity, a physiologically, psychologically, and financially costly epidemic in the United States. College students use their cellular phones over eight and a half hours a day and cell phones are their primary means of information consumption outside of the classroom, suggesting that the phones would be a useful tool to provide nutrition education to this at-risk population. This mixed-methods randomized-controlled trial took place over eight weeks, between 9/15/15 and 12/2/15. The primary aims of this study were to assess the effectiveness and feasibility between an educational nutrition intervention delivered via smartphone texts and a traditional in-office setting for 18-22-year-old, overweight college students at the Sonoma State University Student Health Center. Using simple randomization, participants were assigned to one of two groups: text, or in-office. Participants in the in-office group received one-on-one nutrition counseling framed within the social cognitive theory by a registered nurse at the study onset, week two, and week four. Participants in the text group received the same information, broken up into weekly text messages with links to websites, YouTube, and explanations of content. Participant characteristics, including weight, height, and health behaviors (hours of sleep a night, number of fruits and vegetables per day), were assessed at the study onset (T1) and again at week two (T2), week four (T3), and week eight (T4). All participants were invited to take part in an in-depth, qualitative, face-to-face interview at the end of the study (T4). Nine participants completed both the trial and interviews. Two-thirds (66.7%, n=6) were in the text group, 66.7% (n=6) were female, 33.3% (n=3) were minorities, 66.7% lived on- campus, and 44.4% (n=4) took part in the university’s on-campus meal plan. No statistically significant differences were noted in participant characteristics, or health behaviors between the two groups throughout the study. Although no statistical significance was noted between the two groups with regard to weight change, the text group’s mean weight decreased from 188.25(sd=25.03) pounds to 184.58(sd=24.67) pounds while the in-office group’s mean weight increased from 254.00(sd=90.15) to 257.00(sd=94.14) pounds. Weight loss in the text group should be further evaluated as it may hold clinical significance for effectiveness of the intervention. Through qualitative interviews exploring participants’ experiences, four major themes emerged. All participants in the text group (n=6) stated that they felt there was a need for their method of education, they felt their method was effective, they would recommend their method, and their health behaviors changed positively. For the in-office group, all participants (n=3) said there was a need for their method of education, 67% (n=2) said it was effective, all would recommend it, and 67% stated that they changed their behaviors. Both the quantitative and qualitative findings of this study hold clinical significance as to the effectiveness and feasibility of text messages as a means of providing nutrition education in the college setting. Future research with larger sample sizes and a longer-term study are recommended for more statistical power and to determine the long-term benefits of these methods of nutrition education