Effectiveness of mHealth interventions for improving hypertension control in uncontrolled hypertensive patients: A meta‐analysis of randomized controlled trials

Abstract

The benefits of mHealth interventions in uncontrolled hypertension are unclear. To determine whether mHealth effectively improves the control rate of uncontrolled hypertension. PubMed, Web of Science, EMBASE, Scopus, and Cochrane Library were searched for randomized controlled trials (RCTs) from January 2007 to September 2022. The intervention group consisted of mHealth intervention, and the control group was usual care. Random‐effects meta‐analysis models were used to assess pooled mHealth intervention effects and CIs. The primary outcome was the blood pressure (BP) control rate of uncontrolled hypertension. The secondary outcome was the change of BP. Thirteen RCTs were included in this meta‐analysis, of which eight reported the successful BP control rate, 13 reported the change of systolic blood pressure (SBP), and 11 reported the change in diastolic blood pressure (DBP). The mean age of trial participants ranged from 47.7 to 66.9 years old, with a female composition ratio of 40.0%–66.1%. The duration of follow‐up ranged from 3 to 18 months. This study showed a more robust effect size for improving BP control rate by mHealth interventions than usual care (57.5% vs. 40.8% of successful control rate; odds ratio [OR], 2.19 [95% CI, 1.32—3.62]). Furthermore, mHealth significantly reduced SBP by 4.45 mm Hg and DBP by 2.47 mm Hg, and subgroup analysis did not observe the major source of heterogeneity. This meta‐analysis found that mHealth could significantly improve the uncontrolled hypertension control rate and might be a feasible, acceptable, and effective tool for uncontrolled hypertension management.

1. INTRODUCTION

Hypertension affects approximately one‐quarter of adults worldwide ¹ and causes 10 million deaths per year. ² Hypertension is one of the leading risk factors for cardiovascular disease and mortality worldwide. However, given that the accessibility of antihypertensive medications has improved dramatically, many patients with hypertension continue to have uncontrolled blood pressure. The blood pressure control rate is still as low as 5.7% in developing countries like China. ³ Failure to commence pharmacotherapy, to take medication as often as prescribed, and to adhere to treatment long‐time are recognized factors contributing to the phenomenon of uncontrolled hypertension. ⁴

In an Asian population‐based study, a 10 mm Hg increase in systolic blood pressure (SBP) is associated with a 53% and 31% increase in the risk of stroke and fatal myocardial infarction, respectively. ⁵ Furthermore, many randomized controlled trials (RCTs) have provided accumulating evidence for the cardiovascular benefit of intensive blood pressure control in recent decades. ⁶ , ⁷ Moreover, appreciable evidence demonstrates the benefit of self‐management and enhanced medication adherence in managing BP ontrol. ⁸ , ⁹

With the continuous advancement of telehealth technology, the mHealth‐supported approach to hypertension management shows excellent promise by enhancing self‐management consciousness, improving adherence to pharmacotherapy and modifying bad lifestyles. ¹⁰ , ¹¹ , ¹² Mobile health (mHealth) interventions, which can provide real‐time feedback and support to patients, have emerged as a promising strategy for improving hypertension control rates. Recently, quite a few RCTs have focused on the effectiveness of mHealth on hypertensive patients compared to usual conventional treatment. Some concluded that mHealth might potentially control hypertension, ¹³ , ¹⁴ others have drawn conflicting results. ¹⁵ However, the stability of the previous articles concentrating on uncontrolled hypertension patients was limited by the small sample size. The successful rate of uncontrolled blood pressure control is still poorly explored. In this meta‐analysis, we aimed to evaluate the efficacy of mHealth interventions in enhancing hypertension control rates in uncontrolled hypertensive patients from recent RCTs and further explore the impact of duration, and type of mHealth on the beneficiary population.

2. METHODS

The authors declare that all data in the article and supplement are available. This meta‐analysis was conducted according to the Cochrane Handbook for Systematic Reviews of Interventions. The results were presented in accordance with the Preferred Reporting Item statement for the systematic review and meta‐analysis. The study protocol has been registered with the PROSPERO (CRD42022364738).

3. SEARCH STRATEGY AND STUDY SELECTION

Two researchers (L.‐Z. and Y.W.‐L.) independently searched the following electronic databases, including PubMed, Web of Science, EMBASE, Scopus, and Cochrane Library, for studies published between January 2007 and September 2022. The search formula was: (“uncontrolled” OR “poorly controlled” OR “resistant”) AND (“hypertension” OR “high blood pressure” OR “hypertensive”) AND (“telehealth” OR “mHealth” OR “eHealth” OR “telemedicine” OR “telemonitor” OR “web‐based intervention” OR “E‐counselling”). Relevant studies cited in the references were manually searched and assessed for eligibility.

Two researchers (L.‐Z. and Y.W.‐L.) independently assessed the titles and abstracts of all acquired articles to determine whether they met the inclusion criteria. In case of inconsistency among reviewers, a third reviewer will act as a referee to judge. We searched all surveys on the effect of mHealth interventions on uncontrolled hypertension control rates. Also, we manually defined whether the investigation was the effect of mHealth interventions on controlling poor BP. Studies were included in this meta‐analysis only if they met the following criteria: (1) randomized controlled trials targeting a population with uncontrolled hypertension, defined as a mean systolic blood pressure ≥140 mm Hg or a mean diastolic blood pressure ≥90 mm Hg at enrollment; (2) comparing the effect of electronic and communication technologies (e.g., computers, wearable devices, apps, smartphones, etc.) and usual care; and (3) the follow‐up time was not less than 12 weeks (3 months). The following would be excluded: (1) studies pertaining to gestational hypertension; (2) baseline or endpoint values were incomplete; and (3) case report and observational study.

4. DATA EXTRACTION AND QUALITY ASSESSMENT

Data extraction will be performed independently by two researchers (L.‐.Z and Y.W.‐L.). The following items will be obtained from each article: the first author, the year of publication, country, the percentage of women, age, the mHealth type, the proportions of successful blood pressure control, the definition of uncontrolled blood pressure, the type of devices, study design, the duration of the study, the duration of the intervention, the number of intervention, and control individuals. The Cochrane Risk of Bias Assessment Tool was used to assess the quality of selected RCTs.

4.1. Statistical analysis

Differences in blood pressure change between the intervention and control groups were transformed to weighted mean differences (WMD) for further pooling the effect size. Prespecified subgroup analysis regarding different approaches for mHealth was performed to investigate potential heterogeneity. The heterogeneity of study outcomes was assessed using I², and >75% was considered as considerable heterogeneity. If I² was >50%, a random‐effects model would be conducted to generate pooled estimates of the hypertension control rate and the changes in BP across the study, otherwise fixed‐effect model would be conducted. In addition, we conducted leave‐one‐out sensitivity analyses to assess the impact of each study on the overall. Funnel plots and egger tests were used to assess publication bias. All statistical analyses were performed using Stata 14.0 and RevMan v5.4, and p values < .05 were considered statistically significant.

5. RESULTS

5.1. Literature search

A total of 2787 relevant studies were included in the preliminary retrieved items; among them, 1404 were identified as unique. After reading the titles and abstracts, 1362 articles were excluded because they did not meet the inclusion criteria. Meanwhile, after reading the full text of the remaining 42 articles, 13 eligible RCTs ¹³ , ¹⁴ , ¹⁵ , ¹⁶ , ¹⁷ , ¹⁸ , ¹⁹ , ²⁰ , ²¹ , ²² , ²³ , ²⁴ , ²⁵ were finally enrolled in this meta‐analysis. By searching the reference list, no other articles met the inclusion criteria. The flow chart of study selection is shown in Figure 1.

FIGURE 1.

Flow chart of studies for selecting process from databases.

5.2. Study characteristics

The characteristics of the included studies are shown in Table 1. The sample size of the studies ranged from 65 to 2086. Four RCTs occurred in the United Kingdom, three in the United States, one in China, one in China and India, one in Russia, one in Switzerland, one in Nepal, and one in Argentina. Moreover, two studies were three‐arm RCTs, but only mHealth intervention and usual care groups were included in this meta‐analysis. Margolis and coworkers ¹⁴ conducted 12 months mHealth intervention and 6 months of postintervention follow‐up, and this study analyzed the overall 18 months of follow‐up. The sample size of interventional group was less than 100 in three studies, and more than 150 in the other 10. The age of enrolled patients ranged from 47.7 to 66.9 years old, and the proportion ratio of females was 40.0%—66.1%. Devices applied for mHealth in the intervention group include text message/e‐mail (n = 5), smartphone app (n = 4), website (n = 2), and electronic monitor (n = 2). Blood pressure was collected either by participant self‐report or automatically by the monitoring device. Blood pressure during follow‐up for inclusion in the study was determined by calculating multiple recorded values and taking their average.

TABLE 1.

Summary of articles reporting on mHealth intervention for uncontrolled hypertension.

ID	Study	Year	Country	Female, (%) mHealth/control	Age (years) mHealth/control	mHealth type	Devices	Definition of uncontrolled hypertension	N mHealth/control (follow‐up)	Study design	Follow‐up duration	Intervention duration
1	Bhandari	2022	Nepal	42.0/47.0	49.2/51.7	Mobile phone text messaging intervention	Text message	Prescribed for antihypertensive medication for at least 3 months	79/75	Randomized control trial	3 months	3 months
2	Green	2008	United States	45.9/54.7	59.5/58.6	Home BP monitoring, and secure patient Web services training (BPM‐Web),	Website	Mean BP (last two of three BP recordings, with the first measurement dropped) was 90−109 mm Hg diastolic or 140−199 mm Hg systolic at both screening visits	246/247	Randomized control trial	12 months	12 months
3	He	2017	Argentina	52.6/53.4	56.1/55.5	CHW‐led home‐based intervention, physician education, and a text‐messaging	Text message	Systolic ≥140 mm Hg and/or diastolic ≥90 mm Hg on at least 2 separate screening visits	743/689	Randomized control trial	18 months	18 months
4	Ionov	2020	Russia	41.0/39.0	47.0/49.0	A free simple website and a mobile application	Website and app	With a systolic BP (SBP) level 140 mm Hg (measured at least on two prestudy office visits), ambulatory mean 24‐h SBP 130 mm Hg or/and home SBP 135 mm Hg, and ongoing treatment with at least one antihypertensive drug in the last 3 months	160/80	Randomized control trial	3 months	3 months
5	Margolis	2013	United States	45.2/44.1	62.0/60.2	Home BP telemonitoring with pharmacist case management	Website	With an elevated BP (≥140/90 mm Hg) at the two most recent primary care encounters in the previous year	228/222	Randomized controlled trial	18 months	12 months
6	Mckinstry	2013	United Kingdom	41.0/40.0	60.5/60.8	Telemonitoring	E‐mail/Text message	With a diagnosis of hypertension whose last surgery blood pressure measurement was > 145 mm Hg systolic or > 85 mm Hg diastolic to attend for a screening assessment	182/177	Randomized control trial	6 months	6 months
7	McManus	2010	United Kingdom	53.0/53.0	66.6/66.2	Telemonitoring	Electronic monitor	Had a blood pressure at baseline of more than 140/90 mm Hg	234/246	Randomized control trial	12 months	12 months
8	McManus	2018	United Kingdom	47.0/47.0	67·0/66.8	Telemonitoring	Text message‐based telemonitoring service with web‐based data	Taking no more than three antihypertensive agents, but with clinic blood pressure not controlled below 140/90 mm Hg	389/393	Randomized control trial	12 months	12 months
9	McManus	2020	United Kingdom	47.5/45.0	65.2/66.7	Digital intervention	E‐mail	Mean baseline blood pressure reading (calculated from the second and third blood pressure readings) of more than 140/90 mm Hg	305/317	Randomized control trial	12 months	12 months
10	Morawski	2018	United States	57.4/62.9	51.7/52.4	Medisafe app, which includes reminder alerts, adherence reports, and optional peer support	Medication Adherence Improvement Support App for Engagement—Blood Pressure [MedISAFE‐BP]	With a systolic blood pressure of 140 mm Hg or greater receiving treatment with at least 1, but no more than 3, first‐line antihypertensive medications (thiazide,calcium channel blocker, β‐blocker, angiotensin‐converting enzyme inhibitor, or angiotensin receptor blocker)	209/202	Randomized control trial	3 months	3 months
11	Pan	2018	China	50.0/52.5	56.6/57.8	Home telemonitoring	App	Having persistent high blood pressure for systolic or diastolic indicators or both over the last 3 months	52/55	Randomized control trial	6 months	6 months
12	Santschi	2008	Switzerland	44.1/38.2	61.4/71.2	Electronic monitor	Electronic system	Uncontrolled treated hypertension (office systolic BP≥ 140 mm Hg and/or diastolic BP≥90 mm Hg) according to the mean of two consecutive visits, despite their usual prescribed antihypertensive therapy	32/33	Randomized control trial	12 months	12 months
13	Tian	2015	China and India	65.4/66.8	59.7/60.4	Two therapeutic lifestyle modifications (smoking cessation and salt reduction) and the appropriate prescription of two medications (blood pressure lowering agents and aspirin)	App on smartphones	Measured systolic blood pressure (SBP) ≥160 mm Hg	1095/991	Randomized control trial	12 months	12 months

5.3. Meta‐analysis of mHealth effectiveness on uncontrolled HTN

Of the 13 trials, eight RCTs involved rates of uncontrolled blood pressure control, and Figure 2 showed the forest plot of successful blood pressure control, which indicated that a 119% improvement in BP control through mHealth intervention (odds ratio [OR], 2.19 [95% confidence interval (CI), 1.32—3.62]). The specified count of successful BP control was shown in Table 2 (57.5% vs. 40.8% of successful control rate for intervention group and control group, respectively). Figures 3 and 4 provided a forest plot of individual and pooled effects of mHealth on SBP and diastolic blood pressure (DBP) control. Combining the 13 RCTs that reported data on SBP reduction using a random‐effect model produced a weighted mean difference in SBP of −4.45 mm Hg (95% CI, −5.92 to −2.99). And 11 among them reported comparisons of DBP reduction, using a random‐effect model to produce a weighted mean difference in DBP of −2.47 mm Hg (95% CI, −3.68 to −1.27). However, there was significant heterogeneity found in the successful hypertension control rate (I² = 89%, p < .001) and the changes in BP [SBP (I² = 72%, p < .001) and DBP (I² = 77%, p < .001)].

FIGURE 2.

Forest plot of the effect of mHealth intervention on uncontrolled hypertension. The above figure is an overall analysis of the rate of successful blood pressure controlling. BP, blood pressure; CI, confidence interval.

TABLE 2.

The specified count of successful BP control in intervention and control group.

	MHealth intervention			Usual care
	BP control	Non‐BP control	Successful rate of BP control	BP control	Non‐BP control	Successful rate of BP control
Santschi 2007	9	23	9/32 (28.1%)	4	29	4/33 (12.1%)
Pan 2018	33	19	33/52 (63.5%)	23	32	23/55 (41.8%)
Morawski 2018	67	142	67/209 (32.1%)	69	133	69/202 (34.2%)
Margolis 2013	96	92	96/188 (51.1%)	42	140	42/182 (23.1%)
Ionov 2020	110	50	110/160 (68.8%)	20	60	20/80 (25.0%)
He 2017	517	192	517/709 (72.9%)	338	310	338/648 (52.2%)
Green 2008	76	170	76/246 (30.9%)	89	158	89/247 (36.0%)
Bhandari 2022	55	24	55/79 (70%)	36	39	36/75 (48%)
Total	963	712	963/1675 (57.5%)	621	901	621/1522 (40.8%)

Abbreviation: BP, blood pressure.

FIGURE 3.

Forest plot of the effect of mHealth intervention on uncontrolled hypertension in SBP. The above figure is an overall analysis of the change in SBP level. For each study, the estimated mean change and 95% CI of SBP levels are graphed with a diamond and a horizontal line, respectively. CI, confidence interval; SBP, systolic blood pressure; SMD, standard mean difference.

FIGURE 4.

Forest plot of the effect of mHealth intervention on uncontrolled hypertension in DBP. The above figure is an overall analysis of the change in DBP level. For each study, the estimated mean change and 95% CI of DBP levels are graphed with a diamond and a horizontal line, respectively. CI, confidence interval; DBP, diastolic blood pressure; SMD, standard mean difference.

5.4. Prespecified subgroup analysis

To obtain a stable conclusions, the subgroup analysis was as follows. Subgroup analysis revealed that the effect size of mHealth on BP control might not be associated with the duration of interventions (as shown in Table 3 and Table 4). The pooled MD of mHealth was not statistically significant between different intervention durations (as shown in Figures S1A and S2A). Moreover, the type of intervention device and pharmacist/clinician participation were not associated with the effect size for both SBP or DBP (as shown in Figures S1 and S2).

TABLE 3.

Subgroup analysis of the effect of mHealth intervention on SBP reduction.

Variables	Number of comparisons	WMD (95% CI)	p	p for interaction
Intervention duration
3 months	4	−6.75 (−12.64 to −0.86)	.020	.15
6 months	7	−4.74 (−6.53 to −2.95)	<.001
12 months	8	−4.16 (−5.72 to −2.60)	<.001
18 months	2	−6.60 (−8.15 to −5.05)	<.001
Type of intervention device
Text message/e‐mail	5	−4.66 (−7.16 to −2.15)	<.001	.84
Smartphone app	4	−5.22 (−8.24 to −2.20)	<.001
Website	2	−4.38 (−7.94 to −0.83)	.020
Electronic monitor	2	−3.04 (−6.77 to −0.70)	.110
Pharmacist/clinician guided medication
Yes	10	−4.91 (−6.59 to −3.22)	<.001	.16
No	3	−2.58 (−5.32 to −0.15)	.060

Abbreviations: CI, confidence interval; SBP, systolic blood pressure; WMD, weighted mean difference.

TABLE 4.

Subgroup analysis of the effect of mHealth intervention on DBP reduction.

Variables	Number of comparisons	WMD (95% CI)	p	p for interaction
Intervention duration
3 months	3	−4.66 (−6.61 to −2.71)	<.001	.05
6 months	7	−2.36 (−3.53 to −1.20)	<.001
12 months	7	−2.07 (−3.39 to −0.75)	.002
18 months	2	−4.61 (−6.74 to −2.47)	<.001
Type of intervention device
Text messages/e‐mail	4	−4.04 (−5.66 to −2.43)	<.001	.08
Smartphone app	3	−2.10 (−4.65 to 0.45)	.11
Website	2	−1.30 (−2.86 to 0.27)	.10
Electronic monitor	2	−1.56 (−3.27 to 0.14)	.07
Pharmacist/clinician guided medication
Yes	9	−2.59 (−3.99 to −1.18)	<.001	.74
No	2	−2.02 (−5.01 to 0.97)	.11

Abbreviations: CI, confidence interval; DBP, diastolic blood pressure; WMD, weighted mean difference.

5.5. Sensitivity analysis and publication bias

As shown in Figures S3, S5, and S7, the impact analysis results did not find significant changes in the rate of successful blood pressure controlling and overall results of SBP versus DBP by using the method of excluding relevant studies one by one. The funnel plot of blood pressure controlling, SBP change, and DBP change estimates was roughly symmetric (as shown in Figures S4, S6, and S8). Furthermore, no publication bias was observed in blood pressure controlling (the Egger test, p = .83), either SBP (the Egger test, p = .08) or DBP (the Egger test, p = .85).

5.6. Risk of bias

The Cochrane risk of bias assessment tool was used to evaluate the quality of RCT studies in this quantitative study. These RCTs were well‐designed in terms of random sequence generation. Only one study was considered to have a high risk of bias. Two studies did not mention adequate allocation concealment. Only three studies used and described blinding methods in terms of blinding of participants and personnel. The other studies were open‐label, which may have led to performance bias. Concerning blinding of outcome assessment, nine studies were considered to have an unclear risk of bias. Twelve randomized controlled trials had a low risk of bias for incomplete outcome data and selective outcomes reporting. Two studies had a high risk of bias in the “other bias” domain, and four had an unclear risk of bias in the “other bias” domain.

6. DISCUSSION

Through systematically reviewing from 13 randomized controlled trials, the present study further confirmed the additional benefit of mHealth technology for a 119% improvement in BP control compared to usual care. What's more, this meta‐analysis concluded that mHealth‐based intervention significantly reduced SBP by 4.45 mm Hg and DBP by 2.47 mm Hg. Our findings illustrated the potential of mHealth intervention for uncontrolled hypertension and advocated the clinical application of this novel e‐medical treatment.

In adults, uncontrolled hypertension could contribute to adverse clinical outcomes, and relevant statistics indicate a 20 mm Hg increase in SBP or a 10 mm Hg increase in DBP can increase mortality from stroke and other cardiovascular diseases by more than 2‐fold. ²⁶ In high‐income countries, population awareness against hypertension ranges from 58.2% to 67%; however, in low‐income and middle‐income countries, only 1/3 are aware of their hypertension status, and 8% of blood pressure is under control, ²⁷ a phenomenon that explains a large part of the uncontrolled hypertension. ²⁸ , ²⁹ Managing chronic diseases, such as hypertension, requires a joint and coordinated effort. Therefore, comprehensive patient‐provider communication can improve blood pressure control in patients with hypertension. ³⁰

mHealth can improve blood pressure control by enhancing patient awareness in self‐management and strengthening communication between healthcare providers and patients. ³¹ , ³² A previous meta‐analysis has reported the benefit of mHealth on blood pressure management in the general hypertensive population. Its subgroup analysis demonstrated that the effect size tended to be more prominent in those with baseline uncontrolled hypertension, ³³ but its sample limited the results. As more and more studies focus on patients with hypertensive patients and the rapid advancement of mHealth technology in recent years, it is essential to reassess the benefit of mHealth in improving the control rate of uncontrolled hypertension. To the best of our knowledge, this study is the most updated systematic and qualitative evaluation to analyze the effects of mHealth targeting the population with uncontrolled hypertension. This study demonstrated that mHealth interventions were associated with the successful hypertension control rate by decreasing BP. Despite the inspiring result of the present study, we still need to recognize the heterogeneity and the conflicting results of the enrolled publications.

Morawski and coworkers has reported that mHealth management had no significant benefit in systolic blood pressure control and only had improvement in self‐reported adherence. ¹⁵ The discrepancy between this result and the results of the present study may be due to the following reason. The most potent methods to improve BP involve a reorganization of clinical practice and empowerment of nonphysician practitioners to adjust antihypertensive therapy. Several trials have shown that isolated patient self‐monitoring without care providers' feedback has, if any, a negligible effect on improving BP levels. ²² , ³⁴ Our study also found that the presence of pharmacist/clinician‐guided medication tended to be positive in decreasing blood pressure (WMD = −4.91 mm Hg, 95%CI: −6.59 to −3.22 for SBP; WMD = −2.59 mm Hg, 95%CI: −3.99 to −1.18 for DBP), even though there was no statistically significant difference with or without pharmacist/clinician guided medication (p for interaction = .16 for SBP; p for interaction = .74 for DBP).

Studies in recent years have found some additional benefits of mHealth beyond blood pressure control, such as reducing obesity, encouraging regular physical activity, smoking cessation, dyslipidemia reduction, and treating diabetes mellitus. ³⁵ , ³⁶ These factors are highly associated with reduced long‐term cardiovascular events in patients with hypertension. Mobile health‐based hypertension interventions are widely supported by definitive evidence, yet the efficiency of blood pressure control is associated with different intervention characteristics. ³⁷ However, the subgroup analysis demonstrated that the mHealth intervention was positively influential on BP control, regardless of different duration. One possible explanation may be that the intervention might attenuate patients’ anxiety and increase patients’ adherence to hypertension control. Our study also found that different intervention devices could contribute to a drop in blood pressure (p for interaction = .84 for SBP; p for interaction = .08 for DBP). This also confirmed the effectiveness of mHealth intervention, as different approaches effectively lower blood pressure for uncontrolled hypertension patients.

Even though mHealth care is considered to positively impact uncontrolled hypertension in this study, there are some limitations to this paper. First, the definition of uncontrolled hypertension varies between RCT articles, but generally, they all have two or more blood pressure values greater than 140/90 mm Hg. Second, the population included in this meta‐analysis is from different countries (United States, United Kingdom, China, Russia, Switzerland, etc.) indicating that the results of this study may not apply to other ethnic groups. Thirdly, the patients in the RCT studies included often have multiple coexisting conditions. Generally, they take more than antihypertensive drugs, which may also contribute to the instability of the results. Moreover, this study should have included more articles, which may need more guidance on sufficient factors affecting hypertension. Lastly, we conducted sensitivity and subgroup analyses to ascertain the source of heterogeneity; however, the natural source was not found.

7. CONCLUSIONS

The population included in this meta‐analysis revealed that mHealth could improve hypertension control rate by decreasing sub‐standard blood pressure, which suggested that mHealth as a complementary treatment may be a new and effective tool for uncontrolled hypertension. This study provided a more comprehensive management plan for patients with poorly controlled hypertension.

CONFLICT OF INTEREST STATEMENT

Changsheng Ma has received honoraria from Bristol‐Myers Squibb (BMS), Pfizer, Johnson & Johnson, Boehringer‐Ingelheim (BI), and Bayer for giving lectures. Jianzeng Dong has received honoraria from Johnson & Johnson for giving lectures. The remaining authors have no disclosures to report.

Supporting information

Figure S1. Forest plot of the effect of mHealth intervention on SBP reduction according to the subgroup analysis.

Figure S2. Forest plot of the effect of mHealth intervention on DBP reduction according to the subgroup analysis.

Figure S3. Sensitive analysis of blood pressure controlling.

Figure S4. Funnel plot of blood pressure controlling.

Figure S5. Sensitive analysis of systolic blood pressure.

Figure S6. Funnel plot of the systolic blood pressure.

Figure S7. Sensitive analysis of diastolic blood pressure.

Figure S8. Funnel plot of the diastolic blood pressures.

Zhou L, He L, Kong Y, Lai Y, Dong J, Ma C. Effectiveness of mHealth interventions for improving hypertension control in uncontrolled hypertensive patients: A meta‐analysis of randomized controlled trials. J Clin Hypertens. 2023;25:591–600. 10.1111/jch.14690

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available within the article.