BackgroundThere is a strong will and need to find alternative models of health care delivery driven by the ever-increasing burden of chronic diseases.ObjectiveThe purpose of this 1-year trial was to study whether a structured mobile phone-based health coaching program, which was supported by a remote monitoring system, could be used to improve the health-related quality of life (HRQL) and/or the clinical measures of type 2 diabetes and heart disease patients.MethodsA randomized controlled trial was conducted among type 2 diabetes patients and heart disease patients of the South Karelia Social and Health Care District. Patients were recruited by sending invitations to randomly selected patients using the electronic health records system. Health coaches called patients every 4 to 6 weeks and patients were encouraged to self-monitor their weight, blood pressure, blood glucose (diabetics), and steps (heart disease patients) once per week. The primary outcome was HRQL measured by the Short Form (36) Health Survey (SF-36) and glycosylated hemoglobin (HbA1c) among diabetic patients. The clinical measures assessed were blood pressure, weight, waist circumference, and lipid levels.ResultsA total of 267 heart patients and 250 diabetes patients started in the trial, of which 246 and 225 patients concluded the end-point assessments, respectively. Withdrawal from the study was associated with the patients’ unfamiliarity with mobile phones—of the 41 dropouts, 85% (11/13) of the heart disease patients and 88% (14/16) of the diabetes patients were familiar with mobile phones, whereas the corresponding percentages were 97.1% (231/238) and 98.6% (208/211), respectively, among the rest of the patients (P=.02 and P=.004). Withdrawal was also associated with heart disease patients’ comorbidities—40% (8/20) of the dropouts had at least one comorbidity, whereas the corresponding percentage was 18.9% (47/249) among the rest of the patients (P=.02). The intervention showed no statistically significant benefits over the current practice with regard to health-related quality of life—heart disease patients: beta=0.730 (P=.36) for the physical component score and beta=-0.608 (P=.62) for the mental component score; diabetes patients: beta=0.875 (P=.85) for the physical component score and beta=-0.770 (P=.52) for the mental component score. There was a significant difference in waist circumference in the type 2 diabetes group (beta=-1.711, P=.01). There were no differences in any other outcome variables.ConclusionsA health coaching program supported with telemonitoring did not improve heart disease patients' or diabetes patients' quality of life or their clinical condition. There were indications that the intervention had a differential effect on heart patients and diabetes patients. Diabetes patients may be more prone to benefit from this kind of intervention. This should not be neglected when developing new ways for self-management of chronic diseases.Trial RegistrationClinicalTrials.gov NCT01310491; http://clinicaltrials.gov/ct2/show/NCT013...

Background Stress management interventions combining technology with human involvement have the potential to improve the cost-effectiveness of solely human-delivered interventions, but few randomized controlled trials exist for assessing the cost-effectiveness of technology-assisted human interventions. Objective The aim of this study was to investigate whether a technology-assisted telephone intervention for stress management is feasible for increasing mental well-being or decreasing the time use of coaches (as an approximation of intervention cost) while maintaining participants’ adherence and satisfaction compared with traditional telephone coaching. Methods A 2-arm, pilot randomized controlled trial of 9 months for stress management (4-month intensive and 5-month maintenance phases) was conducted. Participants were recruited on the web through a regional occupational health care provider and randomized equally to a research (technology-assisted telephone intervention) and a control (traditional telephone intervention) group. The coaching methodology was based on habit formation, motivational interviewing, and the transtheoretical model. For the research group, technology supported both coaches and participants in identifying behavior change targets, setting the initial coaching plan, monitoring progress, and communication. The pilot outcome was intervention feasibility, measured primarily by self-assessed mental well-being (WorkOptimum index) and self-reported time use of coaches and secondarily by participants’ adherence and satisfaction. Results A total of 49 eligible participants were randomized to the research (n=24) and control (n=25) groups. Most participants were middle-aged (mean 46.26, SD 9.74 years) and female (47/49, 96%). Mental well-being improved significantly in both groups (WorkOptimum from “at risk” to “good” Â>0.85; P<.001), and no between-group differences were observed in the end (Â=0.56, 95% CI 0.37-0.74; P=.56). The total time use of coaches did not differ significantly between the groups (366.0 vs 343.0 minutes, Â=0.60, 95% CI 0.33-0.85; P=.48). Regarding adherence, the dropout rate was 13% (3/24) and 24% (6/25), and the mean adherence rate to coaching calls was 92% and 86% for the research and control groups, respectively; the frequency of performing coaching tasks was similar for both groups after both phases; and the diligence in performing the tasks during the intensive phase was better for the research group (5.0 vs 4.0, Â=0.58, 95% CI 0.51-0.65; P=.03), but no difference was observed during the maintenance phase. Satisfaction was higher in the research group during the intensive phase (5.0 vs 4.0, Â=0.66, 95% CI 0.58-0.73; P<.001) but not during the maintenance phase. Conclusions The technology-assisted telephone intervention is feasible with some modifications, as it had similar preliminary effectiveness as the traditional telephone intervention, and the participants had better satisfaction with and similar or better adherence to the intervention, but it did not reduce the time use of coaches. The technology should be improved to provide more digested information for action planning and templates for messaging. Trial Registration ClinicalTrials.gov NCT02445950; https://www.clinicaltrials.gov/ct2/show/study/NCT02445950

BACKGROUND Health interventions combining technology with human involvement have the potential to improve the cost-effectiveness of solely human-delivered interventions. However, the optimal combination of human and technology involvement is unclear. OBJECTIVE The aim of the study was to compare the intervention effectiveness and time use of coaches (as an approximation of intervention cost) between a technology-assisted telephone intervention and a traditional telephone intervention for stress management. METHODS A two-arm, randomized controlled trial of nine months (four months intensive and five months maintenance) for stress management was conducted. Participants were recruited online through a regional occupational health care provider in Finland, and randomized equally to a research (technology-assisted telephone intervention) and a control (telephone intervention) group. For both groups, coaching was provided by three occupational health coaches. The coaching methodology was based on habit formation, motivational interviewing and the transtheoretical model. For the research group, technology (web-based tools and wearables) was supporting both the coaches and participants in identifying behaviour change needs (goal setting), setting the initial coaching plan by recommending personalized coaching tasks, progress monitoring, and communication. Technology had greater role in the intensive phase. During the maintenance, technology was mostly used to replace coaching calls. Primary outcomes were participants’ self-assessed mental well-being (WorkOptimum index) and the self-reported time use of coaches. Secondary outcomes included adherence and self-assessed satisfaction with coaching. RESULTS Altogether, 49 eligible participants were randomized to the research (N=24) and control (N=25) groups. Most of the participants were middle-aged (mean 46.26 years, SD 9.74) and females (95.92%, 47/49). Mental well-being improved significantly in both groups (WorkOptimum from ‘at risk’ to ‘good’ P <.001), but no between-group differences were observed in the end (-0.47 vs -0.44, P=.56). The total time use of coaches did not differ significantly between the groups (366.0 min vs. 343.0 min, P=.48). Regarding adherence, the dropout rate was 12.50% (3/24) for the research and 24.00% (6/25) for the control group; the mean adherence rate to coaching calls was 91.67% and 85.50% for the two groups, respectively; the frequency of performing the coaching tasks was similar for both groups after both phases; and the diligence in performing coaching tasks during the intensive phase was better for the research group (5.0 vs. 4.0, P=.03), but no difference was observed for the maintenance phase. Satisfaction was significantly higher in the research group during the intensive phase (5.0 vs 4.0, P<.001), but not during the maintenance phase. CONCLUSIONS Technology-assisted telephone intervention seems to be as effective as the traditional telephone intervention but does not necessarily reduce time use of coaches with the realized human-technology involvement combination. Offering digital tools to complement telephone coaching seems to increase satisfaction with coaching. CLINICALTRIAL ClinicalTrials.gov NCT02445950