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Study Overview
Objective. To assess whether systolic blood pressure improved with expert-driven or user-driven e-counseling compared with control intervention in patients with hypertension over a 4-month period.
Design. Three–parallel group, double-blind randomized controlled trial.
Setting and participants. In Toronto, Canada, participants were recruited through the Heart and Stroke Foundation heart disease risk assessment website, as well as posters at University Health Network facilities. Participants diagnosed with stage 1 or 2 hypertension (systolic blood pressure [SBP] = 140–180 mm Hg, diastolic blood pressure [DBP] = 90–110 mm Hg) and between the ages of 35 and 74 years were eligible. Hypertension diagnoses were confirmed with the participant’s family doctor at baseline if they were not prescribed antihypertensive medication. All participants were required to have an unchanged prescription for antihypertensive medication 42 months before enrollment. Participants prescribed antihypertensive medication were also required to have SBP ≥ 130 mm Hg or DBP ≥ 85 mm Hg in order to prevent “floor effects.” Exclusion criteria included: diagnosis of kidney disease, major psychiatric illness (eg, psychosis), alcohol or drug dependence in the previous year, pregnancy, and sleep apnea.
Participants were randomly assigned to 1 of 3 intervention groups: control, expert-driven, and user-driven e-counseling. Randomization was conducted by a web-based program using randomly permuted blocks. The randomization code was known only to the research coordinator and not to the investigators or research assistants who administered the assessments.
Intervention. Briefly, user-driven e-counseling enabled the participants to set their own goals or to select the interventions used to reach their behavioral goal. The user-driven group received weekly e-mails that enabled participants to select their areas of lifestyle change using text and video web links embedded in the e-mail. Expert-driven e-counseling involved prescribed specific changes for lifestyle behavior, which were intended to facilitate adherence to behavior change. Participants in the expert-driven group received the same hypertension management recommendations for lifestyle change as the user-driven group; however, the weekly e-mails consisted of predetermined exercise and dietary goals. The control group received weekly e-mails provided by the Heart and Stroke Foundation e-Health program that contained a brief newsletter article regarding BP management through lifestyle changes. The control group was distinct from the intervention groups, as the e-mails were limited to general information on BP management. Blinding to group assignment was maintained during baseline and 4-month follow-up.
Main outcome measures. The primary outcome was SDP; secondary outcomes included DBP, pulse pressure (PP), total cholesterol, 10-year Framingham cardiovascular risk (10-year CVD risk), daily physical activity, and dietary habits. Anthropometric characteristics, medical history, medication information, resting BP, daily step count, dietary behavior, participants’ readiness for lifestyle behavior changes, and participants’ cardiovascular risk (calculated by the Framingham 10-year absolute risk) were collected during the baseline and 4-month follow-up assessment.
Baseline and 4-month follow-up assessments at the Peter Munk Cardiac Center, Toronto General Hospital, University Health Network were scheduled between 8 AM and 12 PM to minimize diurnal BP variability. All participants fasted for 12 hours prior to their assessment in order to obtain accurate samples of cholesterol. Participants were also instructed to avoid smoking for > 4 hours, caffeine for 12 hours, and strenuous exercise for 24 hours prior to their assessment.
BP was measured by a validated protocol for automated BP assessments with the BpTRU blood pressure recording device. Participants were seated for >5 minutes prior to activation of the BpTRU device. The BP cuff was applied to participants’ left arms by a trained research assistant. Following the initial BP measurement, the research assistant exited the room while the BpTRU device completed an automated series of 5 BP recordings with 1-minute intervals separating each of these recordings. The recorded BP at each assessment interval was the mean of these 5 BpTRU measurements. PP was determined by the difference between SBP and DBP readings.
Daily physical activity was defined as the mean 4-day steps (3 weekdays, 1 weekend day) recorded on a pedometer (XL-18CN Activity Monitor), which all participants were given to use as part of the study. Diet was measured as adherence to recommended guidelines for daily intake of fruits and vegetables, and evaluated by the validated NIH/National Cancer Institute Diet History Questionnaire. Readiness for exercise and dietary change were measured using a questionnaire from the authors’ previous trial and the stages of change were defined as the following: precontemplation (not ready to adhere to the target behavior in the next 6 months), contemplation (ready to adhere to the target behavior in the next 6 months), preparation (ready to adhere to the target behavior in the next 4 weeks), action (adherence to the behavior but for < 6 months), and maintenance (adherence to the behavior for ≥ 6 months).
For the primary outcome (SBP), the difference among groups was evaluated using univariate linear regression. Post-hoc comparisons with Bonferroni adjustment, among the three treatment groups were performed only if the overall F-test was significant. Secondary outcomes (DBP, PP, total cholesterol, 10-year CVD risk, daily steps, and daily fruit and vegetable consumption) followed a similar statistical approach as the primary outcome analysis. Statistical significance was defined by a two-tailed test with a P value < 0.05.
Main results. Of those screened (n = 847), 128 participants were randomized into the study. Between the 3 groups (control with n = 43, user-driven with n = 42, expert-driven with n = 43), there were no statistically significant differences in age, sex, household income, education, ethnicity, body mass index, and medications (antihypertensive and lipid-lowering) at baseline. The average age was 56.9 ± 0.8 years, 48% were female, 66% had a household income of > $60,000, 79% had a college/university or graduate school education, 73% identified as white, and over 85% were taking ≥ 1 antihypertensive medications. Baseline SBP, DBP, PP, cholesterol, 10-year CVD risk, daily steps, daily vegetable intake, smoking status, readiness for exercise behavior change and readiness for dietary behavior change were also similar across the 3 groups. All participants were highly motivated at baseline for adopting a healthy lifestyle. The percentage of participants that were already in preparation, action, or maintenance of readiness for exercise and diet were 96% and 92%, respectively. Only 4% and 8% of participants were in either precontemplation or contemplation stage of readiness at baseline for exercise and diet, respectively.
The expert-driven group showed a greater SBP decrease than controls at follow-up (mean difference between expert-driven versus control: −7.5 mm Hg, 95% CI −12.5 to −2.6, P = 0.001). SBP reduction did not significantly differ between user- and expert-driven (P > 0.05). DBP reduction and improvement in daily vegetable intake was not significantly different across groups. However, the expert-driven group demonstrated a significant reduction compared with controls in PP (−4.6 mm Hg, 95% CI −8.3 to −0.9, P = 0.008), cholesterol (−0.48 mmol/L, 95% CI −0.84 to −0.14, P < 0.001), and 10-year CVD risk (−3.3%, 95% C −5.0 to −1.5, P = 0.005). The expert-driven group showed a significantly greater improvement than both controls and the user-driven group in daily steps (expert versus control: 2460 steps/day, 95% CI 1137–3783, P < 0.001; expert versus user: 1844 steps/day, 95% CI 512–3176, P = 0.003) and servings of fruit consumption (expert versus control: 1.5 servings/day, 95% CI 0.2–2.7, P = 0.01; expert versus user: 1.8 servings/day, 95% CI 0.8–3.2, P = 0.001).
Conclusion. Expert-driven e-counseling was more effective than control in reducing SBP, PP, cholesterol, and 10-year CVD risk at the 4-month follow-up. In addition, expert-driven e-counseling was more effective that user-driven counseling in improving daily steps and fruit intake. It may be advisable to incorporate an expert-driven e-counseling protocol in order to accommodate participants with greater motivation to change their lifestyle behaviors and improve BP.
Commentary
In a 2014 article, the authors summarized the efficacy of lifestyle counseling interventions in face-to-face, telehealth, and e-counseling settings, especially noting e-counseling as an emerging preventive strategy for hypertension [10]. E-counseling, a form of telehealth, presents information dynamically though combined video, text, image, and audio media, and incorporates two-way communication through phone, internet, and videoconferencing (ie, between patient and provider). This approach has the potential to increase adherence to counseling and self-care approaches by providing improved and convenient access to information, incorporating engaging components, expanding accessibility and comprehension of information among individuals with varying levels of health literacy, enabling increased and more frequent interactivity with health care professionals, and increasing engagement. Importantly, effective counseling approaches, whether through conventional or e-counseling approaches, should include certain core components, including goal-setting, self-monitoring of symptoms of behaviors, personalized training (based on patient setting or resources), performance-based feedback and reinforcement of health-promoting behaviors, and procedures to enhance self-efficacy [10].
This study adds to the literature by demonstrating that the counseling communication strategies (expert- and user-driven) used to deliver e-counseling can significantly influence intervention outcomes related to hypertension management. Strengths of this study include the use of a double-blind randomized controlled study design powered to detect clinically meaningful SBP differences, the three– parallel group assignments (expert-driven, user-driven, control) that incorporated multiple evidence-based counseling approaches, the measurement of changes in multiple cardiovascular and behavioral outcomes (clinical and self-report measures), the inclusion of a theory-based measure of readiness for dietary and exercise behavior change, and the low attrition rate. However, there are key limitations, many acknowledged by the authors. The majority of the study participants were white, from higher income households, had completed higher education, and were already motivated for dietary and exercise behavior change, thus limiting the generalizability of findings. The study had a limited follow-up period (only 4 months) and the study design did not allow for the identification of the most impactful components of the intervention groups.
Applications for Clinical Practice
Expert-driven e-counseling may be an effective approach to managing hypertension, as this study showed that expert-driven e-counseling was more effective than control in reducing SBP, PP, cholesterol, and 10-year CVD risk at the 4-month follow-up, and expert-driven e-counseling was more effective that user-driven counseling in improving daily steps and fruit intake. However, providers should be mindful that this approach may be limited to patients with greater motivation to change their lifestyle behaviors to lower blood pressure.
1. Weber MA, Schiffrin EL, White WB, et al. Clinical practice guidelines for the management of hypertension in the community. J Clin Hypertens 2014;16:14–26.
2. American College of Cardiology. New ACC/AHA high blood pressure guidelines lower definition of hypertension; 2017.
3. Ruilope LM. Current challenges in the clinical management of hypertension. Nat Rev Cardiol 2012;9:267–75.
4. Borghi C, Cicero AFG. Hypertension: management perspectives. Expert Opin Pharmacother 2012;13:1999–2003.
5. Gupta R, Guptha S. Strategies for initial management of hypertension. Indian J Med Res 2010;132:531–42.
6. Pietrzak E, Cotea C, Pullman S. Primary and secondary prevention of cardiovascular disease. J Cardiopulm Rehabil Prev 2014;34:303–17.
7. Watson AJ, Singh K, Myint-U K, et al. Evaluating a web-based self-management program for employees with hypertension and prehypertension: A randomized clinical trial. Am Heart J 2012;164:625–31.
8. Thomas KL, Shah BR, Elliot-Bynum S, et al. Check it, change it: a community-based, multifaceted intervention to improve blood pressure control. Circ Cardiovasc Qual Outcomes 2014;7:828–34.
9. Hallberg I, Ranerup A, Kjellgren K. Supporting the self-management of hypertension: Patients’ experiences of using a mobile phone-based system. J Hum Hypertens 2016;30:141–6.
10. Nolan RP, Liu S, Payne AYM. E-counseling as an emerging preventive strategy for hypertension. Curr Opin Cardiol 2014;29:319–23.
11. Carter BL, Bosworth HB, Green BB. The hypertension team: the role of the pharmacist, nurse, and teamwork in hypertension therapy. J Clin Hypertens 2012;14:51–65.
Study Overview
Objective. To assess whether systolic blood pressure improved with expert-driven or user-driven e-counseling compared with control intervention in patients with hypertension over a 4-month period.
Design. Three–parallel group, double-blind randomized controlled trial.
Setting and participants. In Toronto, Canada, participants were recruited through the Heart and Stroke Foundation heart disease risk assessment website, as well as posters at University Health Network facilities. Participants diagnosed with stage 1 or 2 hypertension (systolic blood pressure [SBP] = 140–180 mm Hg, diastolic blood pressure [DBP] = 90–110 mm Hg) and between the ages of 35 and 74 years were eligible. Hypertension diagnoses were confirmed with the participant’s family doctor at baseline if they were not prescribed antihypertensive medication. All participants were required to have an unchanged prescription for antihypertensive medication 42 months before enrollment. Participants prescribed antihypertensive medication were also required to have SBP ≥ 130 mm Hg or DBP ≥ 85 mm Hg in order to prevent “floor effects.” Exclusion criteria included: diagnosis of kidney disease, major psychiatric illness (eg, psychosis), alcohol or drug dependence in the previous year, pregnancy, and sleep apnea.
Participants were randomly assigned to 1 of 3 intervention groups: control, expert-driven, and user-driven e-counseling. Randomization was conducted by a web-based program using randomly permuted blocks. The randomization code was known only to the research coordinator and not to the investigators or research assistants who administered the assessments.
Intervention. Briefly, user-driven e-counseling enabled the participants to set their own goals or to select the interventions used to reach their behavioral goal. The user-driven group received weekly e-mails that enabled participants to select their areas of lifestyle change using text and video web links embedded in the e-mail. Expert-driven e-counseling involved prescribed specific changes for lifestyle behavior, which were intended to facilitate adherence to behavior change. Participants in the expert-driven group received the same hypertension management recommendations for lifestyle change as the user-driven group; however, the weekly e-mails consisted of predetermined exercise and dietary goals. The control group received weekly e-mails provided by the Heart and Stroke Foundation e-Health program that contained a brief newsletter article regarding BP management through lifestyle changes. The control group was distinct from the intervention groups, as the e-mails were limited to general information on BP management. Blinding to group assignment was maintained during baseline and 4-month follow-up.
Main outcome measures. The primary outcome was SDP; secondary outcomes included DBP, pulse pressure (PP), total cholesterol, 10-year Framingham cardiovascular risk (10-year CVD risk), daily physical activity, and dietary habits. Anthropometric characteristics, medical history, medication information, resting BP, daily step count, dietary behavior, participants’ readiness for lifestyle behavior changes, and participants’ cardiovascular risk (calculated by the Framingham 10-year absolute risk) were collected during the baseline and 4-month follow-up assessment.
Baseline and 4-month follow-up assessments at the Peter Munk Cardiac Center, Toronto General Hospital, University Health Network were scheduled between 8 AM and 12 PM to minimize diurnal BP variability. All participants fasted for 12 hours prior to their assessment in order to obtain accurate samples of cholesterol. Participants were also instructed to avoid smoking for > 4 hours, caffeine for 12 hours, and strenuous exercise for 24 hours prior to their assessment.
BP was measured by a validated protocol for automated BP assessments with the BpTRU blood pressure recording device. Participants were seated for >5 minutes prior to activation of the BpTRU device. The BP cuff was applied to participants’ left arms by a trained research assistant. Following the initial BP measurement, the research assistant exited the room while the BpTRU device completed an automated series of 5 BP recordings with 1-minute intervals separating each of these recordings. The recorded BP at each assessment interval was the mean of these 5 BpTRU measurements. PP was determined by the difference between SBP and DBP readings.
Daily physical activity was defined as the mean 4-day steps (3 weekdays, 1 weekend day) recorded on a pedometer (XL-18CN Activity Monitor), which all participants were given to use as part of the study. Diet was measured as adherence to recommended guidelines for daily intake of fruits and vegetables, and evaluated by the validated NIH/National Cancer Institute Diet History Questionnaire. Readiness for exercise and dietary change were measured using a questionnaire from the authors’ previous trial and the stages of change were defined as the following: precontemplation (not ready to adhere to the target behavior in the next 6 months), contemplation (ready to adhere to the target behavior in the next 6 months), preparation (ready to adhere to the target behavior in the next 4 weeks), action (adherence to the behavior but for < 6 months), and maintenance (adherence to the behavior for ≥ 6 months).
For the primary outcome (SBP), the difference among groups was evaluated using univariate linear regression. Post-hoc comparisons with Bonferroni adjustment, among the three treatment groups were performed only if the overall F-test was significant. Secondary outcomes (DBP, PP, total cholesterol, 10-year CVD risk, daily steps, and daily fruit and vegetable consumption) followed a similar statistical approach as the primary outcome analysis. Statistical significance was defined by a two-tailed test with a P value < 0.05.
Main results. Of those screened (n = 847), 128 participants were randomized into the study. Between the 3 groups (control with n = 43, user-driven with n = 42, expert-driven with n = 43), there were no statistically significant differences in age, sex, household income, education, ethnicity, body mass index, and medications (antihypertensive and lipid-lowering) at baseline. The average age was 56.9 ± 0.8 years, 48% were female, 66% had a household income of > $60,000, 79% had a college/university or graduate school education, 73% identified as white, and over 85% were taking ≥ 1 antihypertensive medications. Baseline SBP, DBP, PP, cholesterol, 10-year CVD risk, daily steps, daily vegetable intake, smoking status, readiness for exercise behavior change and readiness for dietary behavior change were also similar across the 3 groups. All participants were highly motivated at baseline for adopting a healthy lifestyle. The percentage of participants that were already in preparation, action, or maintenance of readiness for exercise and diet were 96% and 92%, respectively. Only 4% and 8% of participants were in either precontemplation or contemplation stage of readiness at baseline for exercise and diet, respectively.
The expert-driven group showed a greater SBP decrease than controls at follow-up (mean difference between expert-driven versus control: −7.5 mm Hg, 95% CI −12.5 to −2.6, P = 0.001). SBP reduction did not significantly differ between user- and expert-driven (P > 0.05). DBP reduction and improvement in daily vegetable intake was not significantly different across groups. However, the expert-driven group demonstrated a significant reduction compared with controls in PP (−4.6 mm Hg, 95% CI −8.3 to −0.9, P = 0.008), cholesterol (−0.48 mmol/L, 95% CI −0.84 to −0.14, P < 0.001), and 10-year CVD risk (−3.3%, 95% C −5.0 to −1.5, P = 0.005). The expert-driven group showed a significantly greater improvement than both controls and the user-driven group in daily steps (expert versus control: 2460 steps/day, 95% CI 1137–3783, P < 0.001; expert versus user: 1844 steps/day, 95% CI 512–3176, P = 0.003) and servings of fruit consumption (expert versus control: 1.5 servings/day, 95% CI 0.2–2.7, P = 0.01; expert versus user: 1.8 servings/day, 95% CI 0.8–3.2, P = 0.001).
Conclusion. Expert-driven e-counseling was more effective than control in reducing SBP, PP, cholesterol, and 10-year CVD risk at the 4-month follow-up. In addition, expert-driven e-counseling was more effective that user-driven counseling in improving daily steps and fruit intake. It may be advisable to incorporate an expert-driven e-counseling protocol in order to accommodate participants with greater motivation to change their lifestyle behaviors and improve BP.
Commentary
In a 2014 article, the authors summarized the efficacy of lifestyle counseling interventions in face-to-face, telehealth, and e-counseling settings, especially noting e-counseling as an emerging preventive strategy for hypertension [10]. E-counseling, a form of telehealth, presents information dynamically though combined video, text, image, and audio media, and incorporates two-way communication through phone, internet, and videoconferencing (ie, between patient and provider). This approach has the potential to increase adherence to counseling and self-care approaches by providing improved and convenient access to information, incorporating engaging components, expanding accessibility and comprehension of information among individuals with varying levels of health literacy, enabling increased and more frequent interactivity with health care professionals, and increasing engagement. Importantly, effective counseling approaches, whether through conventional or e-counseling approaches, should include certain core components, including goal-setting, self-monitoring of symptoms of behaviors, personalized training (based on patient setting or resources), performance-based feedback and reinforcement of health-promoting behaviors, and procedures to enhance self-efficacy [10].
This study adds to the literature by demonstrating that the counseling communication strategies (expert- and user-driven) used to deliver e-counseling can significantly influence intervention outcomes related to hypertension management. Strengths of this study include the use of a double-blind randomized controlled study design powered to detect clinically meaningful SBP differences, the three– parallel group assignments (expert-driven, user-driven, control) that incorporated multiple evidence-based counseling approaches, the measurement of changes in multiple cardiovascular and behavioral outcomes (clinical and self-report measures), the inclusion of a theory-based measure of readiness for dietary and exercise behavior change, and the low attrition rate. However, there are key limitations, many acknowledged by the authors. The majority of the study participants were white, from higher income households, had completed higher education, and were already motivated for dietary and exercise behavior change, thus limiting the generalizability of findings. The study had a limited follow-up period (only 4 months) and the study design did not allow for the identification of the most impactful components of the intervention groups.
Applications for Clinical Practice
Expert-driven e-counseling may be an effective approach to managing hypertension, as this study showed that expert-driven e-counseling was more effective than control in reducing SBP, PP, cholesterol, and 10-year CVD risk at the 4-month follow-up, and expert-driven e-counseling was more effective that user-driven counseling in improving daily steps and fruit intake. However, providers should be mindful that this approach may be limited to patients with greater motivation to change their lifestyle behaviors to lower blood pressure.
Study Overview
Objective. To assess whether systolic blood pressure improved with expert-driven or user-driven e-counseling compared with control intervention in patients with hypertension over a 4-month period.
Design. Three–parallel group, double-blind randomized controlled trial.
Setting and participants. In Toronto, Canada, participants were recruited through the Heart and Stroke Foundation heart disease risk assessment website, as well as posters at University Health Network facilities. Participants diagnosed with stage 1 or 2 hypertension (systolic blood pressure [SBP] = 140–180 mm Hg, diastolic blood pressure [DBP] = 90–110 mm Hg) and between the ages of 35 and 74 years were eligible. Hypertension diagnoses were confirmed with the participant’s family doctor at baseline if they were not prescribed antihypertensive medication. All participants were required to have an unchanged prescription for antihypertensive medication 42 months before enrollment. Participants prescribed antihypertensive medication were also required to have SBP ≥ 130 mm Hg or DBP ≥ 85 mm Hg in order to prevent “floor effects.” Exclusion criteria included: diagnosis of kidney disease, major psychiatric illness (eg, psychosis), alcohol or drug dependence in the previous year, pregnancy, and sleep apnea.
Participants were randomly assigned to 1 of 3 intervention groups: control, expert-driven, and user-driven e-counseling. Randomization was conducted by a web-based program using randomly permuted blocks. The randomization code was known only to the research coordinator and not to the investigators or research assistants who administered the assessments.
Intervention. Briefly, user-driven e-counseling enabled the participants to set their own goals or to select the interventions used to reach their behavioral goal. The user-driven group received weekly e-mails that enabled participants to select their areas of lifestyle change using text and video web links embedded in the e-mail. Expert-driven e-counseling involved prescribed specific changes for lifestyle behavior, which were intended to facilitate adherence to behavior change. Participants in the expert-driven group received the same hypertension management recommendations for lifestyle change as the user-driven group; however, the weekly e-mails consisted of predetermined exercise and dietary goals. The control group received weekly e-mails provided by the Heart and Stroke Foundation e-Health program that contained a brief newsletter article regarding BP management through lifestyle changes. The control group was distinct from the intervention groups, as the e-mails were limited to general information on BP management. Blinding to group assignment was maintained during baseline and 4-month follow-up.
Main outcome measures. The primary outcome was SDP; secondary outcomes included DBP, pulse pressure (PP), total cholesterol, 10-year Framingham cardiovascular risk (10-year CVD risk), daily physical activity, and dietary habits. Anthropometric characteristics, medical history, medication information, resting BP, daily step count, dietary behavior, participants’ readiness for lifestyle behavior changes, and participants’ cardiovascular risk (calculated by the Framingham 10-year absolute risk) were collected during the baseline and 4-month follow-up assessment.
Baseline and 4-month follow-up assessments at the Peter Munk Cardiac Center, Toronto General Hospital, University Health Network were scheduled between 8 AM and 12 PM to minimize diurnal BP variability. All participants fasted for 12 hours prior to their assessment in order to obtain accurate samples of cholesterol. Participants were also instructed to avoid smoking for > 4 hours, caffeine for 12 hours, and strenuous exercise for 24 hours prior to their assessment.
BP was measured by a validated protocol for automated BP assessments with the BpTRU blood pressure recording device. Participants were seated for >5 minutes prior to activation of the BpTRU device. The BP cuff was applied to participants’ left arms by a trained research assistant. Following the initial BP measurement, the research assistant exited the room while the BpTRU device completed an automated series of 5 BP recordings with 1-minute intervals separating each of these recordings. The recorded BP at each assessment interval was the mean of these 5 BpTRU measurements. PP was determined by the difference between SBP and DBP readings.
Daily physical activity was defined as the mean 4-day steps (3 weekdays, 1 weekend day) recorded on a pedometer (XL-18CN Activity Monitor), which all participants were given to use as part of the study. Diet was measured as adherence to recommended guidelines for daily intake of fruits and vegetables, and evaluated by the validated NIH/National Cancer Institute Diet History Questionnaire. Readiness for exercise and dietary change were measured using a questionnaire from the authors’ previous trial and the stages of change were defined as the following: precontemplation (not ready to adhere to the target behavior in the next 6 months), contemplation (ready to adhere to the target behavior in the next 6 months), preparation (ready to adhere to the target behavior in the next 4 weeks), action (adherence to the behavior but for < 6 months), and maintenance (adherence to the behavior for ≥ 6 months).
For the primary outcome (SBP), the difference among groups was evaluated using univariate linear regression. Post-hoc comparisons with Bonferroni adjustment, among the three treatment groups were performed only if the overall F-test was significant. Secondary outcomes (DBP, PP, total cholesterol, 10-year CVD risk, daily steps, and daily fruit and vegetable consumption) followed a similar statistical approach as the primary outcome analysis. Statistical significance was defined by a two-tailed test with a P value < 0.05.
Main results. Of those screened (n = 847), 128 participants were randomized into the study. Between the 3 groups (control with n = 43, user-driven with n = 42, expert-driven with n = 43), there were no statistically significant differences in age, sex, household income, education, ethnicity, body mass index, and medications (antihypertensive and lipid-lowering) at baseline. The average age was 56.9 ± 0.8 years, 48% were female, 66% had a household income of > $60,000, 79% had a college/university or graduate school education, 73% identified as white, and over 85% were taking ≥ 1 antihypertensive medications. Baseline SBP, DBP, PP, cholesterol, 10-year CVD risk, daily steps, daily vegetable intake, smoking status, readiness for exercise behavior change and readiness for dietary behavior change were also similar across the 3 groups. All participants were highly motivated at baseline for adopting a healthy lifestyle. The percentage of participants that were already in preparation, action, or maintenance of readiness for exercise and diet were 96% and 92%, respectively. Only 4% and 8% of participants were in either precontemplation or contemplation stage of readiness at baseline for exercise and diet, respectively.
The expert-driven group showed a greater SBP decrease than controls at follow-up (mean difference between expert-driven versus control: −7.5 mm Hg, 95% CI −12.5 to −2.6, P = 0.001). SBP reduction did not significantly differ between user- and expert-driven (P > 0.05). DBP reduction and improvement in daily vegetable intake was not significantly different across groups. However, the expert-driven group demonstrated a significant reduction compared with controls in PP (−4.6 mm Hg, 95% CI −8.3 to −0.9, P = 0.008), cholesterol (−0.48 mmol/L, 95% CI −0.84 to −0.14, P < 0.001), and 10-year CVD risk (−3.3%, 95% C −5.0 to −1.5, P = 0.005). The expert-driven group showed a significantly greater improvement than both controls and the user-driven group in daily steps (expert versus control: 2460 steps/day, 95% CI 1137–3783, P < 0.001; expert versus user: 1844 steps/day, 95% CI 512–3176, P = 0.003) and servings of fruit consumption (expert versus control: 1.5 servings/day, 95% CI 0.2–2.7, P = 0.01; expert versus user: 1.8 servings/day, 95% CI 0.8–3.2, P = 0.001).
Conclusion. Expert-driven e-counseling was more effective than control in reducing SBP, PP, cholesterol, and 10-year CVD risk at the 4-month follow-up. In addition, expert-driven e-counseling was more effective that user-driven counseling in improving daily steps and fruit intake. It may be advisable to incorporate an expert-driven e-counseling protocol in order to accommodate participants with greater motivation to change their lifestyle behaviors and improve BP.
Commentary
In a 2014 article, the authors summarized the efficacy of lifestyle counseling interventions in face-to-face, telehealth, and e-counseling settings, especially noting e-counseling as an emerging preventive strategy for hypertension [10]. E-counseling, a form of telehealth, presents information dynamically though combined video, text, image, and audio media, and incorporates two-way communication through phone, internet, and videoconferencing (ie, between patient and provider). This approach has the potential to increase adherence to counseling and self-care approaches by providing improved and convenient access to information, incorporating engaging components, expanding accessibility and comprehension of information among individuals with varying levels of health literacy, enabling increased and more frequent interactivity with health care professionals, and increasing engagement. Importantly, effective counseling approaches, whether through conventional or e-counseling approaches, should include certain core components, including goal-setting, self-monitoring of symptoms of behaviors, personalized training (based on patient setting or resources), performance-based feedback and reinforcement of health-promoting behaviors, and procedures to enhance self-efficacy [10].
This study adds to the literature by demonstrating that the counseling communication strategies (expert- and user-driven) used to deliver e-counseling can significantly influence intervention outcomes related to hypertension management. Strengths of this study include the use of a double-blind randomized controlled study design powered to detect clinically meaningful SBP differences, the three– parallel group assignments (expert-driven, user-driven, control) that incorporated multiple evidence-based counseling approaches, the measurement of changes in multiple cardiovascular and behavioral outcomes (clinical and self-report measures), the inclusion of a theory-based measure of readiness for dietary and exercise behavior change, and the low attrition rate. However, there are key limitations, many acknowledged by the authors. The majority of the study participants were white, from higher income households, had completed higher education, and were already motivated for dietary and exercise behavior change, thus limiting the generalizability of findings. The study had a limited follow-up period (only 4 months) and the study design did not allow for the identification of the most impactful components of the intervention groups.
Applications for Clinical Practice
Expert-driven e-counseling may be an effective approach to managing hypertension, as this study showed that expert-driven e-counseling was more effective than control in reducing SBP, PP, cholesterol, and 10-year CVD risk at the 4-month follow-up, and expert-driven e-counseling was more effective that user-driven counseling in improving daily steps and fruit intake. However, providers should be mindful that this approach may be limited to patients with greater motivation to change their lifestyle behaviors to lower blood pressure.
1. Weber MA, Schiffrin EL, White WB, et al. Clinical practice guidelines for the management of hypertension in the community. J Clin Hypertens 2014;16:14–26.
2. American College of Cardiology. New ACC/AHA high blood pressure guidelines lower definition of hypertension; 2017.
3. Ruilope LM. Current challenges in the clinical management of hypertension. Nat Rev Cardiol 2012;9:267–75.
4. Borghi C, Cicero AFG. Hypertension: management perspectives. Expert Opin Pharmacother 2012;13:1999–2003.
5. Gupta R, Guptha S. Strategies for initial management of hypertension. Indian J Med Res 2010;132:531–42.
6. Pietrzak E, Cotea C, Pullman S. Primary and secondary prevention of cardiovascular disease. J Cardiopulm Rehabil Prev 2014;34:303–17.
7. Watson AJ, Singh K, Myint-U K, et al. Evaluating a web-based self-management program for employees with hypertension and prehypertension: A randomized clinical trial. Am Heart J 2012;164:625–31.
8. Thomas KL, Shah BR, Elliot-Bynum S, et al. Check it, change it: a community-based, multifaceted intervention to improve blood pressure control. Circ Cardiovasc Qual Outcomes 2014;7:828–34.
9. Hallberg I, Ranerup A, Kjellgren K. Supporting the self-management of hypertension: Patients’ experiences of using a mobile phone-based system. J Hum Hypertens 2016;30:141–6.
10. Nolan RP, Liu S, Payne AYM. E-counseling as an emerging preventive strategy for hypertension. Curr Opin Cardiol 2014;29:319–23.
11. Carter BL, Bosworth HB, Green BB. The hypertension team: the role of the pharmacist, nurse, and teamwork in hypertension therapy. J Clin Hypertens 2012;14:51–65.
1. Weber MA, Schiffrin EL, White WB, et al. Clinical practice guidelines for the management of hypertension in the community. J Clin Hypertens 2014;16:14–26.
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