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College students experience high levels of stress. Mindfulness meditation delivered via a mobile app may be an appealing, efficacious way to reduce stress in college students. We aimed to test the initial efficacy and sustained effects of an 8-week mindfulness meditation mobile app-Calm-compared to a wait-list control on stress, mindfulness, and self-compassion in college students with elevated stress. We also explored the intervention's effect on health behaviors (ie, sleep disturbance, alcohol consumption [binge drinking], physical activity, and healthy eating [fruit and vegetable consumption]) and the feasibility and acceptability of the app. This study was a randomized, wait-list, control trial with assessments at baseline, postintervention (8 weeks), and at follow-up (12 weeks). Participants were eligible if they were current full-time undergraduate students and (1) at least 18 years of age, (2) scored ≥14 points on the Perceived Stress Scale, (3) owned a smartphone, (4) were willing to download the Calm app, (5) were willing to be randomized, and (7) were able to read and understand English. Participants were asked to meditate using Calm at least 10 minutes per day. A P value ≤.05 was considered statistically significant. A total of 88 participants were included in the analysis. The mean age (SD) was 20.41 (2.31) years for the intervention group and 21.85 (6.3) years for the control group. There were significant differences in all outcomes (stress, mindfulness, and self-compassion) between the intervention and control groups after adjustment for covariates postintervention (all P<.04). These effects persisted at follow-up (all P<.03), except for the nonreacting subscale of mindfulness (P=.08). There was a significant interaction between group and time factors in perceived stress (P=.002), mindfulness (P<.001), and self-compassion (P<.001). Bonferroni posthoc tests showed significant within-group mean differences for perceived stress in the intervention group (P<.001), while there were no significant within-group mean differences in the control group (all P>.19). Similar results were found for mindfulness and self-compassion. Effect sizes ranged from moderate (0.59) to large (1.24) across all outcomes. A significant group×time interaction in models of sleep disturbance was found, but no significant effects were found for other health behaviors. The majority of students in the intervention group reported that Calm was helpful to reduce stress and stated they would use Calm in the future. The majority were satisfied using Calm and likely to recommend it to other college students. The intervention group participated in meditation for an average of 38 minutes/week during the intervention and 20 minutes/week during follow-up. Calm is an effective modality to deliver mindfulness meditation in order to reduce stress and improve mindfulness and self-compassion in stressed college students. Our findings provide important information that can be applied to the design of future studies or mental health resources in university programs. ClinicalTrials.gov NCT03891810; https://clinicaltrials.gov/ct2/show/NCT03891810.

Delivering self-management support to people with type 2 diabetes mellitus is essential to reduce the health system burden and to empower people with the skills, knowledge, and confidence needed to take an active role in managing their own health. This study aims to evaluate the adoption, use, and effectiveness of the My Diabetes Coach (MDC) program, an app-based interactive embodied conversational agent, Laura, designed to support diabetes self-management in the home setting over 12 months. This randomized controlled trial evaluated both the implementation and effectiveness of the MDC program. Adults with type 2 diabetes in Australia were recruited and randomized to the intervention arm (MDC) or the control arm (usual care). Program use was tracked over 12 months. Coprimary outcomes included changes in glycated hemoglobin (HbA ) and health-related quality of life (HRQoL). Data were assessed at baseline and at 6 and 12 months, and analyzed using linear mixed-effects regression models. A total of 187 adults with type 2 diabetes (mean 57 years, SD 10 years; 41.7% women) were recruited and randomly allocated to the intervention (n=93) and control (n=94) arms. MDC program users (92/93 participants) completed 1942 chats with Laura, averaging 243 min (SD 212) per person over 12 months. Compared with baseline, the mean estimated HbA decreased in both arms at 12 months (intervention: 0.33% and control: 0.20%), but the net differences between the two arms in change of HbA (-0.04%, 95% CI -0.45 to 0.36; P=.83) was not statistically significant. At 12 months, HRQoL utility scores improved in the intervention arm, compared with the control arm (between-arm difference: 0.04, 95% CI 0.00 to 0.07; P=.04). The MDC program was successfully adopted and used by individuals with type 2 diabetes and significantly improved the users' HRQoL. These findings suggest the potential for wider implementation of technology-enabled conversation-based programs for supporting diabetes self-management. Future studies should focus on strategies to maintain program usage and HbA improvement. Australia New Zealand Clinical Trials Registry (ACTRN) 12614001229662; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12614001229662.

Previous studies on telemedicine interventions have shown that older diabetic patients experience difficulty in using computers, which is a barrier to remote communication between medical teams and older diabetic patients. However, older people in China tend to find it easy to use mobile phones and personal messaging apps that have a user-friendly interface. Therefore, we designed a mobile health (mHealth) system for older people with diabetes that is based on mobile phones, has a streamlined operation interface, and incorporates maximum automation. The goal of the research was to investigate the use of mobile phone-based telemedicine apps for management of older Chinese patients with type 2 diabetes mellitus (T2DM). Variables of interest included efficacy and safety. A total of 91 older (aged over 65 years) patients with T2DM who presented to our department were randomly assigned to one of two groups. Patients in the intervention group (n=44) were provided glucometers capable of data transmission and received advice pertaining to medication, diet, and exercise via the mHealth telemedicine system. Patients assigned to the control group (n=47) received routine outpatient care with no additional intervention. Patients in both groups were followed up at regular 3-month intervals. After 3 months, patients in the intervention group showed significant (P<.05) improvement in postprandial plasma glucose level. After 6 months, patients in the intervention group exhibited a decreasing trend in postprandial plasma glucose and glycated hemoglobin levels compared with the baseline and those in the control group (P<.05). Mobile phone-based telemedicine apps help improve glycemic control in older Chinese patients with T2DM. China Clinical Trial Registration Center ChiCTR 1800015214; http://www.chictr.org.cn/showprojen.aspx?proj=25949 (Archived by WebCite at http://www.webcitation.org/73wKj1GMq).

Self-monitoring of dietary intake is a valuable component of behavioral weight loss treatment; however, it declines quickly, thereby resulting in suboptimal treatment outcomes. This study aimed to examine a novel behavioral weight loss intervention that aims to attenuate the decline in dietary self-monitoring engagement. GoalTracker was an automated randomized controlled trial. Participants were adults with overweight or obesity (n=105; aged 21-65 years; body mass index, BMI, 25-45 kg/m ) and were randomized to a 12-week stand-alone weight loss intervention using the MyFitnessPal smartphone app for daily self-monitoring of either (1) both weight and diet, with weekly lessons, action plans, and feedback (Simultaneous); (2) weight through week 4, then added diet, with the same behavioral components (Sequential); or (3) only diet (App-Only). All groups received a goal to lose 5% of initial weight by 12 weeks, a tailored calorie goal, and automated in-app reminders. Participants were recruited via online and offline methods. Weight was collected in-person at baseline, 1 month, and 3 months using calibrated scales and via self-report at 6 months. We retrieved objective self-monitoring engagement data from MyFitnessPal using an application programming interface. Engagement was defined as the number of days per week in which tracking occurred, with diet entries counted if ≥800 kcal per day. Other assessment data were collected in-person via online self-report questionnaires. At baseline, participants (84/100 female) had a mean age (SD) of 42.7 (11.7) years and a BMI of 31.9 (SD 4.5) kg/m . One-third (33/100) were from racial or ethnic minority groups. During the trial, 5 participants became ineligible. Of the remaining 100 participants, 84% (84/100) and 76% (76/100) completed the 1-month and 3-month visits, respectively. In intent-to-treat analyses, there was no difference in weight change at 3 months between the Sequential arm (mean -2.7 kg, 95% CI -3.9 to -1.5) and either the App-Only arm (-2.4 kg, -3.7 to -1.2; P=.78) or the Simultaneous arm (-2.8 kg, -4.0 to -1.5; P=.72). The median number of days of self-monitoring diet per week was 1.9 (interquartile range [IQR] 0.3-5.5) in Sequential (once began), 5.3 (IQR 1.8-6.7) in Simultaneous, and 2.9 (IQR 1.2-5.2) in App-Only. Weight was tracked 4.8 (IQR 1.9-6.3) days per week in Sequential and 5.1 (IQR 1.8-6.3) days per week in Simultaneous. Engagement in neither diet nor weight tracking differed between arms. Regardless of the order in which diet is tracked, using tailored goals and a commercial mobile app can produce clinically significant weight loss. Stand-alone digital health treatments may be a viable option for those looking for a lower intensity approach. ClinicalTrials.gov NCT03254953; https://clinicaltrials.gov/ct2/show/NCT03254953 (Archived by WebCite at http://www.webcitation.org/72PyQrFjn).

IntelliCare is a modular platform that includes 12 simple apps targeting specific psychological strategies for common mental health problems. This study aimed to examine the effect of 2 methods of maintaining engagement with the IntelliCare platform, coaching, and receipt of weekly recommendations to try different apps on depression, anxiety, and app use. A total of 301 participants with depression or anxiety were randomized to 1 of 4 treatments lasting 8 weeks and were followed for 6 months posttreatment. The trial used a 2X2 factorial design (coached vs self-guided treatment and weekly app recommendations vs no recommendations) to compare engagement metrics. The median time to last use of any app during treatment was 56 days (interquartile range 54-57), with 253 participants (84.0%, 253/301) continuing to use the apps over a median of 92 days posttreatment. Receipt of weekly recommendations resulted in a significantly higher number of app use sessions during treatment (overall median=216; P=.04) but only marginal effects for time to last use (P=.06) and number of app downloads (P=.08). Coaching resulted in significantly more app downloads (P<.001), but there were no significant effects for time to last download or number of app sessions (P=.36) or time to last download (P=.08). Participants showed significant reductions in the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) across all treatment arms (P s<.001). Coached treatment led to larger GAD-7 reductions than those observed for self-guided treatment (P=.03), but the effects for the PHQ-9 did not reach significance (P=.06). Significant interaction was observed between receiving recommendations and time for the PHQ-9 (P=.04), but there were no significant effects for GAD-7 (P=.58). IntelliCare produced strong engagement with apps across all treatment arms. Coaching was associated with stronger anxiety outcomes, and receipt of recommendations enhanced depression outcomes. ClinicalTrials.gov NCT02801877; https://clinicaltrials.gov/ct2/show/NCT02801877.

The incidence of cancer pain increases in discharged patients because of discontinued standard treatments and reductions in medication adherence. Motivated by the need for better pain management in discharged patients, we developed a mobile phone app (Pain Guard) to provide continuous treatment information and feedback to discharged cancer patients suffering from pain. The aim was to design, construct, and test the Pain Guard app in patients managing cancer pain, evaluate the total remission rate of pain and the improvement in quality of life (QoL) to improve pain management for cancer pain patients, and assess patient acceptance of the app. This randomized controlled double-arm study involved 58 patients with cancer pain symptoms. Participants were randomly assigned to a group receiving care through the Pain Guard app (n=31) or to a control group (n=27) who received only traditional pharmaceutical care. In a pretest, participants were rated using a baseline cancer pain assessment and QoL evaluation. During treatment, the consumption levels of analgesic drugs were recorded every week. After a 4-week study period, another round of cancer pain assessment and QoL evaluation was conducted. The system's usability, feasibility, app compliance, and satisfaction were also assessed. Our primary outcome was remission rate of pain, and secondary outcomes were medication adherence, improvements in QoL, frequency of breakthrough cancer pain (BTcP), incidence of adverse reactions, and satisfaction of patients. All participants (N=58) successfully completed the study. There were no significant differences in baseline pain scores or baseline QoL scores between groups. At the end of the study, the rate of pain remission in the trial group was significantly higher than that in the control group (P<.001). The frequency of BTcP in the app group was considerably lower than that in the control group (P<.001). The rate of medication adherence in the trial group was considerably higher than that in the control group (P<.001). Improvements in global QoL scores in the trial group were also significantly higher than those in the control group (P<.001). The incidence of adverse reactions in the trial group (7/31) was lower than that in the control group (12/27), especially constipation, with significant differences (P=.01). The 31 participants in the trial group completed a satisfaction survey regarding Pain Guard: 23 (74%) indicated that they were satisfied with receiving pharmaceutical care by Pain Guard, 5 (16%) indicated that they were somewhat satisfied, 2 (6%) indicated neutral feelings, and 1 (3%) indicated that they were somewhat dissatisfied; no participants indicated that they were very dissatisfied. Pain Guard was effective for the management of pain in discharged patients with cancer pain, and its operability was effective and easily accepted by patients. Chinese Clinical Trials Registry ChiCTR1800016066; http://www.chictr.org.cn/showproj.aspx?proj=27153.

Chronic kidney disease (CKD) is a global health burden. Self-management plays a key role in improving modifiable risk factors. The aim of this study was to evaluate the effectiveness of wearable devices, a health management platform, and social media at improving the self-management of CKD, with the goal of establishing a new self-management intervention model. In a 90-day prospective experimental study, a total of 60 people with CKD at stages 1-4 were enrolled in the intervention group (n=30) and control group (n=30). All participants were provided with wearable devices that collected exercise-related data. All participants maintained dietary diaries using a smartphone app. All dietary and exercise information was then uploaded to a health management platform. Suggestions about diet and exercise were provided to the intervention group only, and a social media group was created to inspire the participants in the intervention group. Participants' self-efficacy and self-management questionnaire scores, Kidney Disease Quality of Life scores, body composition, and laboratory examinations before and after the intervention were compared between the intervention and control groups. A total of 49 participants completed the study (25 in the intervention group and 24 in the control group); 74% of the participants were men and the mean age was 51.22 years. There were no differences in measured baseline characteristics between the groups except for educational background. After the intervention, the intervention group showed significantly higher scores for self-efficacy (mean 171.28, SD 22.92 vs mean 142.21, SD 26.36; P<.001) and self-management (mean 54.16, SD 6.71 vs mean 47.58, SD 6.42; P=.001). Kidney Disease Quality of Life scores were also higher in the intervention group (mean 293.16, SD 34.21 vs mean 276.37, SD 32.21; P=.02). The number of steps per day increased in the intervention group (9768.56 in week 1 and 11,389.12 in week 12). The estimated glomerular filtration rate (eGFR) of the intervention group was higher than that of the control group (mean 72.47, SD 24.28 vs mean 59.69, SD 22.25 mL/min/1.73m ; P=.03) and the decline in eGFR was significantly slower in the intervention group (-0.56 vs -4.58 mL/min/1.73m ). There were no differences in body composition between groups postintervention. The use of wearable devices, a health management platform, and social media support not only strengthened self-efficacy and self-management but also improved quality of life and a slower eGFR decline in people with CKD at stages 1-4. These results outline a new self-management model to promote healthy lifestyle behaviors for patients with CKD. ClinicalTrials.gov NCT04617431; https://www.clinicaltrials.gov/ct2/show/NCT04617431.

As the increasing prevalence of type 2 diabetes mellitus has put pressure on health systems to appropriately manage these patients, there have been a growing number of mobile apps designed to improve the self-management of diabetes. One such app, BlueStar, has been shown to significantly reduce hemoglobin A (HbA ) levels in small studies and is the first app in the United States to receive Food and Drug Administration approval as a mobile prescription therapy. However, the impact of the app across real-world population among different clinical sites and health systems remains unclear. The primary objective of this study was to conduct a pragmatic randomized controlled trial of the BlueStar mobile app to determine if app usage leads to improved HbA levels among diverse participants in real-life clinical contexts. We hypothesized that this mobile app would improve self-management and HbA levels compared with controls. The study consisted of a multicenter pragmatic randomized controlled trial. Overall, 110 participants randomized to the immediate treatment group (ITG) received the intervention for 6 months, and 113 participants randomized to the wait-list control (WLC) group received usual care for the first 3 months and then received the intervention for 3 months. The primary outcome was glucose control measured by HbA levels at 3 months. Secondary outcomes assessed intervention impact on patient self-management, experience of care, and self-reported health utilization using validated scales, including the Problem Areas in Diabetes, the Summary of Diabetes Self-Care Activities, and the EuroQol-5D. Intervention usage data were collected directly from the app. The results of an analysis of covariance controlling for baseline HbA levels did not show evidence of intervention impact on HbA levels at 3 months (mean difference [ITG-WLC] -0.42, 95% CI -1.05 to 0.21; P=.19). Similarly, there was no intervention effect on secondary outcomes measuring diabetes self-efficacy, quality of life, and health care utilization behaviors. An exploratory analysis of 57 ITG participants investigating the impact of app usage on HbA levels showed that each additional day of app use corresponded with a 0.016-point decrease in participants' 3-month HbA levels (95% CI -0.03 to -0.003). App usage varied significantly by site, as participants from 1 site logged in to the app a median of 36 days over 14 weeks (interquartile range [IQR] 10.5-124); those at another site used the app significantly less (median 9; IQR 6-51). The results showed no difference between intervention and control arms for the primary clinical outcome of glycemic control measured by HbA levels. Although there was low usage of the app among participants, results indicate contextual factors, particularly site, had a significant impact on overall usage. Future research into the patient and site-specific factors that increase app utilization are needed. Clinicaltrials.gov NCT02813343; https://clinicaltrials.gov/ct2/show/NCT02813343 (Archived by WebCite at https://clinicaltrials.gov/ct2/show/NCT02813343).

Mental health disorders are the most prevalent health issues among postsecondary students, yet few solutions to this emerging crisis exist. While mobile health technologies are touted as promising solutions for the unmet mental health needs of these students, the efficacy of these tools remains unclear. In response to these gaps, this study evaluates Thought Spot, a mobile and web app created through participatory design research. The goal of the research is to examine the impact of Thought Spot on mental health and wellness help-seeking intentions, behaviors, attitudes, self-stigma, and self-efficacy among postsecondary students in Canada. A 2-armed randomized controlled trial involving students from three postsecondary institutions was conducted. Students were eligible if they were aged 17 to 29 years, enrolled in full-time or part-time studies, functionally competent in English, and had access to a compatible digital device. The usual care group received a mental health services information pamphlet. The intervention group received the Thought Spot app on their digital device. Thought Spot is a standalone app that allows users to add, review, and search crowdsourced information about nearby mental health and wellness services. Users can also track their mood on the app. Outcomes were self-assessed through questionnaires collected at baseline and 3 and 6 months. The primary outcome was change in formal help-seeking intentions from baseline to 6 months, measured by the General Help-Seeking Questionnaire. A mixed-effects model was used to compare the impact of usual care and intervention on the primary outcome (formal help-seeking intentions). Secondary outcomes included changes in informal help-seeking intentions and help-seeking behaviors, help-seeking attitudes, self-stigma, and self-efficacy. A total of 481 students were randomized into two groups: 240 to usual care, and 241 to the intervention group. There were no significant differences in help-seeking intentions between the usual care and intervention groups over 6 months (F =0.85; P=.43, f=0.04). Both groups demonstrated similar increases in formal help-seeking intentions at 3 and 6 months (F =23.52; P<.001, f=0.21). Compared with males, females sought more help from formal resources (OR 1.86; 95% CI 1.22 to 2.83, P=.001). Females were less likely to seek help from informal sources than males (OR 0.80; 95% CI 0.22 to 0.73, P<.001). Prompting postsecondary students about mental health and help-seeking appears to increase help-seeking intentions. mHealth interventions may be as effective as information pamphlets in increasing formal help-seeking but may confer a small advantage in driving help-seeking from informal sources. Although there is enthusiasm, developers and health policy experts should exercise caution and thoroughly evaluate these types of digital tools. Future studies should explore the cost-effectiveness of digital interventions and develop strategies for improving their efficacy. ClinicalTrials.gov NCT03412461; https://clinicaltrials.gov/ct2/show/NCT03412461. RR2-10.2196/resprot.6446.

Despite substantial improvements in technology and the increased demand for technology-enabled behavioral health tools among consumers, little progress has been made in easing the burden of mental illness. This may be because of the inherent challenges of conducting traditional clinical trials in a rapidly evolving technology landscape. This study sought to validate the effectiveness of Pacifica, a popular commercially available app for the self-management of mild-to-moderate stress, anxiety, and depression. A total of 500 adults with mild-to-moderate anxiety or depression were recruited from in-app onboarding to participate in a randomized waitlist controlled trial of Pacifica. We conducted an all-virtual study, recruiting, screening, and randomizing participants through a Web-based participant portal. Study participants used the app for 1 month, with no level of use required, closely mimicking real-world app usage. Participants in the waitlist group were given access to the app after 1 month. Measurements included self-reported symptoms of stress, anxiety, depression, and self-efficacy. We performed an intent-to-treat analysis to examine the interactive effects of time and condition. We found significant interactions between time and group. Participants in the active condition demonstrated significantly greater decreases in depression, anxiety, and stress and increases in self-efficacy. Although we did not find a relationship between overall engagement with the app and symptom improvement, participants who completed relatively more thought record exercises sustained improvements in their symptoms through the 2-month follow-up to a greater degree than those who completed fewer. In addition, we found that participants who reported concomitantly taking psychiatric medications during the trial benefitted less from the app, as measured by the symptoms of anxiety and stress. This study provides evidence that Pacifica, a popular commercially available self-help app, is effective in reducing self-reported symptoms of depression, anxiety, and stress, particularly among individuals who utilize thought records and are not taking psychiatric medication. ClinicalTrials.gov NCT03333707; https://clinicaltrials.gov/ct2/show/NCT03333707 (Archived by WebCite at http://www.webcitation.org/78YE07ADB).