Self-monitoring and self-management: new interventions to improve blood pressure control

Psychometric Testing of the Korean Version of the Self-Care of Coronary Heart Disease Inventory Version 3

PURPOSE

This methodological study evaluated the psychometric properties of the Self-Care of Coronary Heart Disease Inventory version 3 (SC-CHDI v3) in a Korean context.

METHODS

The SC-CHDI v3 was translated into Korean following a rigorous translation process. Participants were 452 patients who had experienced coronary heart disease (CHD), all recruited from a tertiary hospital in Korea. Exploratory and confirmatory factor analyses were performed to test construct validity. Concurrent validity was examined by correlating scores from the Korean version of the SC-CHDI v3 with those from the Cardiac Self-Efficacy Scale. Internal consistency was analyzed using Cronbach's alpha and McDonald's omega.

RESULTS

The Korean version of the SC-CHDI v3 consists of 21 items, excluding two from the original instrument. The self-care maintenance subscale identified a two-factor structure: "treatment adherence" and "health-promoting behaviors." The goodness-of-fit indices were satisfied: χ2 = 18.19, p = .110, comparative fit index (CFI) = .97, Tucker-Lewis Index (TLI) = .95, and standardized root mean square residual (SRMR) = .04. The self-care monitoring subscale consisted of a one-dimensional structure ("monitoring behaviors") and the goodness-of-fit indices were satisfied: χ2 = 19.19, p = .059, CFI = .99, TLI = .99, and SRMR = .04. The self-care management subscales had a two-factor structure of "consulting behaviors" and "problem-solving behaviors." The goodness-of-fit indices were satisfied: χ2 = 16.44, p = .037, CFI = .99, TLI = .98, and SRMR = .03. Scores from the Cardiac Self-Efficacy Scale showed a positive correlation with the Korean version of SC-CHDI v3 subscales. Reliability estimates were ≥ .80 for all subscales except for the self-care maintenance subscale.

CONCLUSIONS

The Korean version of the SC-CHDI v3 consists of 21 items in 3 subscales and is a valid and reliable instrument. Therefore, healthcare providers can effectively utilize it to assess the self-care levels of patients with CHD.

Factors influencing the continuation of home blood pressure measurement in community-dwelling older adults: the NOSE study

OBJECTIVE

This study aimed to identify the factors influencing home blood pressure measurement (HBPM) continuation in community-dwelling older adults.

METHODS

A longitudinal analysis used the NOSE study intervention group datasets. The participants were encouraged HBPM with self-monitoring devices provided to them twice in the morning and twice in the evening. Every 7-day interval from the HBPM start date was defined as 1 week, and the number of HBPMs per week was counted. The first week in which the number of HBPMs was zero was defined as the week in which HBPM was discontinued. Participants who did not experienced discontinuation until the end of the observation period were considered complete survivors in the survival time analysis.

RESULTS

Data from 437 participants were included in the analysis. Of these, 120 (27.5%) discontinued HBPM. In univariate analysis, factors significantly associated with HBPM discontinuation included exercise habits [hazard ratio per one unit 0.47; 95% confidence interval (CI) 0.31-0.69], social participation (hazard ratio 0.65; 95% CI 0.42-0.99), MoCA-J score (hazard ratio 0.94; 95% CI 0.90-0.98), and frailty (hazard ratio 5.20; 95% CI 2.87-9.43). In multivariate analysis, factors significantly associated with HBPM discontinuation included sex (hazard ratio 0.55; 95% CI 0.32-0.95; ref. = female individuals), smoking history (hazard ratio 1.69; 95% CI 1.02-2.80), exercise habits (hazard ratio 0.51; 95% CI 0.30-0.85), MoCA-J score (hazard ratio 0.93; 95% CI 0.88-0.98), and frailty (hazard ratio 3.31; 95% CI 1.50-7.29).

CONCLUSION

Among community-dwelling older adults, female sex, smoking history, lack of exercise, cognitive decline, and frailty were identified as factors influencing HBPM discontinuation.

Effect of a Lifestyle-Focused Web-Based Application on Risk Factor Management in Patients Who Have Had a Myocardial Infarction: Randomized Controlled Trial

BACKGROUND

Cardiac rehabilitation is central in reducing mortality and morbidity after myocardial infarction. However, the fulfillment of guideline-recommended cardiac rehabilitation targets is unsatisfactory. eHealth offers new possibilities to improve clinical care.

OBJECTIVE

This study aims to assess the effect of a web-based application designed to support adherence to lifestyle advice and self-control of risk factors (intervention) in addition to center-based cardiac rehabilitation, compared with cardiac rehabilitation only (usual care).

METHODS

All 150 patients participated in cardiac rehabilitation. Patients randomized to the intervention group (n=101) received access to the application for 25 weeks where information about lifestyle (eg, diet and physical activity), risk factors (eg, weight and blood pressure [BP]), and symptoms could be registered. The software provided feedback and lifestyle advice. The primary outcome was a change in submaximal exercise capacity (Watts [W]) between follow-up visits. Secondary outcomes included changes in modifiable risk factors between baseline and follow-up visits and uptake and adherence to the application. Regression analysis was used, adjusting for relevant baseline variables.

RESULTS

There was a nonsignificant trend toward a larger change in exercise capacity in the intervention group (n=66) compared with the usual care group (n=40; +14.4, SD 19.0 W, vs +10.3, SD 16.1 W; P=.22). Patients in the intervention group achieved significantly larger BP reduction compared with usual care patients at 2 weeks (systolic -27.7 vs -16.4 mm Hg; P=.006) and at 6 to 10 weeks (systolic -25.3 vs -16.4 mm Hg; P=.02, and diastolic -13.4 vs -9.1 mm Hg; P=.05). A healthy diet index score improved significantly more between baseline and the 2-week follow-up in the intervention group (+2.3 vs +1.4 points; P=.05), mostly owing to an increase in the consumption of fish and fruit. At 6 to 10 weeks, 64% (14/22) versus 46% (5/11) of smokers in the intervention versus usual care groups had quit smoking, and at 12 to 14 months, the respective percentages were 55% (12/22) versus 36% (4/11). However, the number of smokers in the study was low (33/149, 21.9%), and the differences were nonsignificant. Attendance in cardiac rehabilitation was high, with 96% (96/100) of patients in the intervention group and 98% (48/49) of patients receiving usual care only attending 12- to 14-month follow-up. Uptake (logging data in the application at least once) was 86.1% (87/101). Adherence (logging data at least twice weekly) was 91% (79/87) in week 1 and 56% (49/87) in week 25.

CONCLUSIONS

Complementing cardiac rehabilitation with a web-based application improved BP and dietary habits during the first months after myocardial infarction. A nonsignificant tendency toward better exercise capacity and higher smoking cessation rates was observed. Although the study group was small, these positive trends support further development of eHealth in cardiac rehabilitation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03260582; https://clinicaltrials.gov/ct2/show/NCT03260582.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s13063-018-3118-1.

Improving Blood Pressure Control Using Smart Technology

BACKGROUND

The authors sought to determine if wireless oscillometric home blood pressure monitoring (HBPM) that integrates with smartphone technology improves blood pressure (BP) control among patients with new or existing uncontrolled hypertension (HTN).

METHODS

A prospective observational cohort study monitored BP control before and after an educational intervention and introduction to HBPM. Patients in the intervention group were instructed to track their BP using a smartphone device three to seven times per week. Cases were matched to controls at a 1:3 allocation ratio on several clinical characteristics over the same period and received usual care. The proportion of patients with controlled BP was compared between groups at pre- and postintervention, ∼9 months later. Results and Materials: The total study population included 484 patients with mean age 60 years (range 23-102 years), 47.7% female, and 84.6% Caucasian. Mean preintervention BP was 137.8 mm Hg systolic and 81.4 mm Hg diastolic. Mean BP control rates improved for patients who received HBPM from 42% to 67% compared with matched control patients who improved from 59% to 67% (p < 0.01).

CONCLUSION

HBPM with smartphone technology has the potential to improve HTN management among patients with uncontrolled or newly diagnosed HTN. Technology needs to be easy to use and operate and would work best when integrated into local electronic health record systems. In systems without this capability, medical assistants or other personnel may be trained to facilitate the process. Nurse navigator involvement was instrumental in bridging communication between the patients and provider.