Nursing Introduction & PICOT Question Assignment

1020  |  wileyonlinelibrary.com/journal/jnu J Nurs Sch. 2023;55:1020–1035.© 2023 Sigma Theta Tau International.

Received: 13 October 2022  | Revised: 30 January 2023  | Accepted: 10 February 2023

DOI: 10.1111/jnu.12882

H E A L T H P O L I C Y A N D S Y S T E M

The effect of nurse- led digital health interventions on blood pressure control for people with hypertension: A systematic review and meta- analysis

Misun Hwang MSN, RN  | Ae Kyung Chang PhD, RN

Kyung Hee University, College of Nursing Science, Seoul, Republic of Korea

Correspondence Ae Kyung Chang, Kyung Hee University, College of Nursing Science, Seoul 02447, Republic of Korea. Email: [email protected]

Abstract Purpose: Nurse- led digital health interventions (DHIs) for people with chronic disease are increasing. However, the effect of nurse- led DHIs on blood pressure control and hypertension self- management remains unclear. This study aimed to identify the char- acteristics of nurse- led DHIs for people with hypertension and compared the effect size of nurse- led DHIs with that of usual care to establish evidence for the develop- ment of effective nursing interventions using technologies. Design: Systematic review and meta- analysis. Methods: This systematic review and meta- analysis followed the Preferred Reporting Items for Systematic Reviews of Intervention (PRISMA) guidelines and registered the protocol in PROSPERO. Studies published from 2000 to August 5, 2021, were searched using the international databases: PubMed; Embase; Cochrane Central Register of Controlled Trials; Web of Science; CINAHL; Korean databases: RISS, KISS, KMBASE; and NDSL. Risk of bias 2.0 was used for evaluating the quality of stud- ies. The primary outcome was blood pressure control. The secondary outcomes were self- management, medication adherence, and diet adherence. Publication bias was assessed using the funnel plot and Egger's regression tests. Findings: The systematic review included 26 studies. A meta- analysis of 21 studies was conducted to calculate the effect size and identify heterogeneity among the in- cluded studies. In our meta- analysis, we observed that nurse- led DHIs reduced sys- tolic blood pressure by 6.49 mmHg (95% confidence interval [CI]: −8.52 to −4.46, I2 = 75.4%, p < 0.05) and diastolic blood pressure by 3.30 mmHg (95% CI: −4.58 to −2.01, I2 = 70.3%, p < 0.05) when compared with usual care. Concerning secondary outcomes, the effect size on self- management, medication adherence, and diet adher- ence was 0.98 (95% CI: 0.58 to 1.37, I2 = 63.2%, p < 0.05), 1.05 (95% CI: 0.41 to 1.69, I2 = 92.5%, p < 0.05), and 0.80 (95% CI: 0.17 to 1.42, I2 = 80.5%, p < 0.05), respectively. Conclusion: Nurse- led DHIs were more effective in reducing blood pressure and en- hancing self- management than usual care among people with hypertension. Therefore, as new technologies are being rapidly developed and applied in healthcare systems, further studies and policy support are needed to utilize the latest digital innovations with nursing interventions.

    |  1021NURSE-­LED­DHIS­FOR­HYPERTENSION

INTRODUC TION

Hypertension is a global public health problem affecting 31.1% of the world's population, and the number of people with hyperten- sion is predicted to increase by more than 1.5 billion by 2025 (Mills et al., 2016; Williams et al., 2018). Hypertension requires lifelong management, and failure to control blood pressure increases car- diovascular complications and the burden on national medical ex- penses. The previous report shows that a 10 mmHg reduction in systolic blood pressure and a 5 mmHg reduction in diastolic blood pressure reduced the risk of stroke and cardiovascular disease by 40% and 25%, respectively (Law et al., 2009). Therefore, effective interventions for hypertension management are needed to achieve optimal blood pressure control among this population.

Self- management, such as blood pressure monitoring, medica- tion, and diet adherence, is essential for maintaining optimal blood pressure in people with hypertension. However, the hypertension control rate is <50% in most countries (Weber et al., 2014), despite the existing self- management strategies and anti- hypertensive drugs. This poor adherence is mainly caused by a lack of patient engagement with disease management, insufficient education on lifestyle modifications owing to limited resources, and inadequate communication with healthcare providers (Himmelfarb et al., 2016; Milani & Lavie, 2015; Williams et al., 2018).

There is mounting evidence that a practical timely approach to managing hypertension is to ensure adequate patient edu- cation followed by patient- tailored interventions (Osterberg & Blaschke, 2005). However, most existing interventions for people with hypertension have utilized in- person visit strategies. Within this context, healthcare providers cannot provide adequate information and interventions that reflect the patient's needs and characteris- tics due to space constraints and limited treatment time for primary care management for hypertension. Therefore, there is an increasing need for innovative intervention approaches that enable the provi- sion of patient- centered care through real- time communication be- tween patients and healthcare providers, as well as enhanced access to healthcare services (Milani & Lavie, 2015).

Digital health interventions (DHIs) can be critical solutions as safe and cost- effective methods that improve health status. The World Health Organization (WHO) defines digital health as using

digital, mobile, and wireless technologies to achieve health ob- jectives, which is a broad concept that includes the general use of information and communication technologies (World Health Organization, 2016). Specifically, DHIs refer to using various tech- nologies as delivery channels of health intervention, including tele- phone, text message, mobile apps, social media, telemonitoring, or wearable devices. DHIs allow people to record and share immediate health status with healthcare providers in a more convenient mode. Additionally, healthcare providers can easily provide care and edu- cation to promote behavioral changes (Parati et al., 2019).

Nurses' role in managing hypertension has been emphasized continuously, which includes medication management, education, referral, follow- up, and care coordination (Himmelfarb et al., 2016; Zhu et al., 2018). Especially nurses can encourage people with hy- pertension to actively engage in disease management through indi- vidualized education and feedback, reducing hypertension- related complications and mortality (Himmelfarb et al., 2016). Considering the expanded role of nurses and the advantages of two- way commu- nication employing DHIs, nurses are qualified and suitable profes- sionals who can develop and apply DHIs to people with hypertension.

Several original research, literature reviews, and meta- analyses of interventions using technologies for people with hypertension continue to emerge (Li et al., 2020; Xu & Long, 2020). In line with this stream, studies on nurse- led DHIs for people with hypertension are increasing. DHIs enable nurses to provide multifaceted interven- tions. Nurses can educate patients, communicate with them, improve treatment adherence, and monitor disease management remotely through digital technologies, such as telephone calls, text mes- sages, and mobile applications (Kes & Polat, 2022; Ling et al., 2021). Nurse- led DHIs also empowered patients to manage their disease by allowing them to record, monitor, and self- tracking their blood pres- sure using mobile applications and telehealth devices (Abu- El- Noor et al., 2021; Wakefield et al., 2011; Zha et al., 2020). However, the effects of nurse- led DHIs on blood pressure control and hyperten- sion self- management remain unclear (Kes & Polat, 2022; Kim, 2019; Sheilini et al., 2019). Accordingly, this study aimed to identify the characteristics of nurse- led DHIs for people with hypertension and compared the effect size of nurse- led DHIs with that of usual care to establish evidence for developing effective nursing interventions using technologies.

Clinical relevance: This study could be used to identify that nurse- led interventions may take advantage of real- time communication by employing digital technologies for improving blood control and self- management behaviors such as medication adherence and diet adherence. Using nurse- led DHIs allows nurses to provide patient- centered interventions such as reflecting on patients' needs and shared decision- making with- out space constraints and limited treatment time.

K E Y W O R D S digital health intervention, hypertension, meta- analysis, nurse- led intervention, self- management, systematic review

1022  |    NURSE-­LED­DHIS­FOR­HYPERTENSION

METHODS

This systematic review and meta- analysis followed the Preferred Reporting Items for Systematic Reviews of Intervention (PRISMA) guidelines and Cochrane Handbook. This study protocol was regis- tered in PROSPERO (CRD42021264095).

Data sources and search strategies

Studies in Korean and English published from 2000 to August 2021 were searched through the international databases PubMed, EMBASE, Cochrane Central Register of Controlled Trials, Web of Science, and CINAHL and domestic databases RISS, KISS, KMBASE, and NDSL using the combination of Medical Subject Headings (MeSH) and Emtree terms. The search strategy was centered on Participants and Intervention of the Participants, Interventions, Comparisons, Outcomes and the Study design (PICOS) framework. Search terms were related to “HTN,” “digi- tal technology,” and “nurse.” Detailed search strategies are shown in Data S1. In addition, manual searching was conducted for references of relevant literature and included studies.

Inclusion criteria

The inclusion criteria according to the PICOS framework were as follows:

1. Participants [P]: Studies on adults aged >18 years who were diagnosed with hypertension,

2. Intervention [I]: Nurse- led DHIs are defined if nurses use digital technology as the intervention delivery channel (channels could include telephone calls, text messages, e-mail, mobile applica- tions, social media, or telehealth devices),

3. Comparison [C]: Usual care group that did not undergo interventions employing digital technologies as intervention delivery channels,

4. Outcome [O]: Primary outcome of blood pressure before and after the intervention and secondary outcome of quantitative results on self- management, medication adherence, and diet adherence,

5. Study design [S]: Randomized controlled trials (RCTs).

Exclusion criteria

The exclusion criteria were as follows: (1) Studies that delivered the DHIs by healthcare professionals other than nurses; (2) Gray litera- ture; (3) Studies in languages other than Korean and English; and (4) Effect size not calculated owing to insufficient results.

Data extraction

Two authors (M.S. and A.K.) independently excluded duplicate studies using EndNote 20 (Clarivate, Philadelphia, PA) and

studies were primarily selected based on the title and abstract. The full text of the selected studies was reviewed, and articles for the final analysis were selected using the inclusion and exclusion criteria. In case of any disagreement between the researchers regarding the selection of literature, a consensus was reached through reviews and discussions based on the inclusion and exclusion criteria. Eligible studies were coded according to the criteria.

Risk of bias assessments

Two researchers (M.S. and A.K.) independently evaluated the quality of each study according to the Risk of Bias 2.0 (RoB 2.0), a randomized controlled trial evaluation tool, and assessed the fol- lowing: (1) bias arising from the randomization process; (2) bias due to deviations from intended interventions; (3) bias due to missing outcome data; (4) bias in measurement of the outcome; and (5) bias in selection of the reported result. Using the response to questions for each bias, the risk of bias was evaluated as “high risk of bias,” “some concerns,” and “low risk of bias” according to the algorithm (Sterne et al., 2019). Any disagreement between the researchers was resolved through discussions.

Statistical analysis

The effect size was calculated using “meta” and “metafor” pack- ages of R (version 4.1.1, R Foundation for Statistical Computing). For continuous variables, the mean change difference was consid- ered. If the measurement units were the same, the mean differ- ence (MD) was calculated as the effect size. If the measurement units were not the same, Hedge's g [standardized mean difference] was calculated.

If the standard deviation (SD) of MD before and after the in- tervention was not reported, SD was calculated using the standard error, confidence interval, and pre– post correlation coefficient (Higgins et al., 2021). If the outcome variable was measured multi- ple times during the intervention period, the value measured imme- diately after the intervention was used to calculate the effect size. Additionally, if the direction of the results of measurement tools for self- management- related items was different, the average value was treated as a negative number to match the direction of the effect, and the effect size was calculated. The overall effect and 95% con- fidence interval were evaluated, and p- value<0.05 indicated statis- tical significance.

Higgins' I2 statistic was used for statistical testing for heteroge- neity of effect size. I2 indicates the ratio of actual variance to the variance of the total effect size. I2 of <25%, 50%, and > 75% indi- cated low, medium, and high levels of heterogeneity, respectively (Higgins & Thompson, 2002). In this study, when heterogeneity was confirmed, subgroup analysis was conducted.

Publication bias was evaluated using the symmetry of the funnel plot, and the Egger's regression test was conducted.

    |  1023NURSE-­LED­DHIS­FOR­HYPERTENSION

RESULTS

Study selection

A total of 1973 studies were included in the initial search, and 1103 duplicate studies were removed. The studies were screened using the title and abstract, and a further 756 studies were excluded. A total of 204 articles were initially selected. A full- text review was conducted to exclude 178 studies, and 26 articles were included in the systematic review (Data S2). A meta- analysis of 21 articles was conducted, and 5 studies that were not possible to be quantitatively synthesized were excluded. The process of study selection is shown in the PRISMA flow chart (Figure 1).

Characteristics of included studies

Table S1 shows the characteristics of the selected 26 studies on nurse- led DHIs. The studies were published between 2001 and 2021, and among the studies, 21 articles (80.77%) were published after 2010. Eleven studies were conducted in the United States, while five stud- ies were conducted in China. Two studies were conducted in Iran and the following countries each conducted one study: Turkey, Palestine, Brazil, India, Korea, Italia, Spain, and the United Kingdom. In seven studies, the number of participants in the intervention group was be- tween 50 and 100. In another seven studies, the number of partici- pants in the experimental group was between 100 and 200. The mean age group of the participants was 60s in 12 studies.

Description of interventions

The contents of nurse- led DHIs included information and education about the disease, reminders, communication details, and referrals to visit medical institutions in necessary cases for improving blood pressure control and self- management. Among nurse- led DHIs, 11 studies provided patient- tailored interventions such as personal- ized feedback or education (Artinian et al., 2001, 2007; Bosworth et al., 2009, 2011; Kes & Polat, 2022; Kim, 2019; Ling et al., 2021; Marquez Contreras et al., 2005; Mattei da Silva et al., 2020; Wakefield et al., 2011; Zha et al., 2020).

In 17 studies, a single type of digital technology was applied, and in nine studies, two or more digital technologies were used to pro- vide nursing intervention. The delivery channels of digital technol- ogies were as follows: telephone (22 studies); mobile applications (Abu- El- Noor et al., 2021), including WeChat (Ling et al., 2021), iHealth MyVitals (Zha et al., 2020), and WhatsApp (Mattei da Silva et al., 2020) (four studies); telehealth devices (Artinian et al., 2007; Bosworth et al., 2011; Ruppar, 2010; Wakefield et al., 2011) (four studies); text message (Kes & Polat, 2022; Kim, 2019; Maslakpak & Safaie, 2016) (three studies); e-mail (Bobrow et al., 2016; Cicolini et al., 2014; Wakefield et al., 2011) (three studies); and Telegram (Najafi Ghezeljeh et al., 2018) (one study).

The intervention period ranged from 1 month (Ling et al., 2021) to 24 months (Bosworth et al., 2009). The most common interven- tion period was 6 months in seven studies. The frequency of inter- vention differed according to the type of digital technologies and was reported in only 20 studies. Additional support for DHIs in- cluded face- to- face contact strategies such as in- person counseling, education, and home visit in 13 studies.

Blood pressure, which is the primary outcome, was reported in 23 studies. For secondary outcomes, medication adherence, self- management, and diet adherence were reported in 12, 6, and 6 stud- ies, respectively. All control groups underwent usual care.

Risk of bias assessments

Among the 26 studies, 7, 15, and 4 studies had a high risk of bias, some concerns, and low risk of bias, respectively. High risk of bias and some concerns were caused by a lack of description of the rand- omization concealment process, single- blinded application, and lack of specification of blinding methods. The detailed results of quality evaluation are as follows (Figures 2, 3).

Effects of nurse- led digital health intervention

Blood pressure control

Blood pressure before and after the intervention was reported in 19 studies (Artinian et al., 2001, 2007; Brennan et al., 2010; Chiu & Wong, 2010; Cicolini et al., 2014; Hebert et al., 2012; Kerry et al., 2013; Kes & Polat, 2022; Kim, 2019; Ling et al., 2021; Marquez Contreras et al., 2005; Mattei da Silva et al., 2020; Miao et al., 2020; Pezzin et al., 2011; Rudd et al., 2004; Sheilini et al., 2019; Zha et al., 2020; Zhu et al., 2014, 2018). One of the 19 studies reported only systolic blood pressure (Kerry et al., 2013).

Nurse- led DHIs reduced systolic blood pressure by 6.49 mmHg (95% CI: −8.52 to −4.46, Z = −6.27, p < 0.05, I2 = 75.4%, Figure 4a) and diastolic blood pressure by 3.30 mmHg (95% CI: −4.58 to −2.01, Z = −5.01, p < 0.05, I2 = 70.3%, Figure 4b). The heterogeneity of each effect size of systolic blood pressure and diastolic blood pressure was high, and a subgroup analysis was conducted. Subgroup anal- ysis using meta- ANOVA showed that tailored intervention mode was a moderator leading to a statistically significant difference in the effect size of systolic blood pressure reduction (Table S1). The tailored intervention mode, including personalized feedback or ed- ucation, was employed in eight studies (Artinian et al., 2001, 2007; Kes & Polat, 2022; Kim, 2019; Ling et al., 2021; Marquez Contreras et al., 2005; Mattei da Silva et al., 2020; Zha et al., 2020). However, there was no statistically significant difference in the effect sizes of systolic blood pressure and diastolic blood pressure reduction according to age, diagnosis, number of digital technologies used in the intervention, type and duration of interventions, and additional support.

1024  |    NURSE-­LED­DHIS­FOR­HYPERTENSION

Secondary outcomes

Self- management A total of three studies reported self- management results that were measured using the Hill- Bone Compliance to High Blood Pressure Therapy Scale (Abu- El- Noor et al., 2021), Adherence to Treatment of Systemic Hypertension (Mattei da Silva et al., 2020), and the tool developed by Lee (1995). Nurse- led DHIs were shown to improve

self- management in people with hypertension (SMD = 0.98, 95% CI: 0.58 to 1.37, Z = 4.39, p < 0.05, I2 = 63.2%, Figure 5a).

Medication adherence A total of six studies reported medication adherence that was measured using the Medication Adherence Self- Efficacy Scale (Kes & Polat, 2022; Zha et al., 2020), Hill- Bone Compliance to High Blood Pressure Therapy Scale (Abu- El- Noor et al., 2021), and the Morisky

F I G U R E 1  PRISMA flow diagram regarding the process of study selection.

    |  1025NURSE-­LED­DHIS­FOR­HYPERTENSION

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- 8 0

(6 7.

7/ 68

.3 )

Fe m

al e:

4 6%

H TN

So ci

al m

ed ia

(T el

eg ra

m )

• Q

ue st

io n

ab ou

t p at

ie nt

's he

al th

st

at us

a nd

tr ea

tm en

t a dh

er en

ce .

• In

fo rm

at io

n an

d ad

vi ce

u si

ng

im ag

es a

nd v

id eo

s.

6  w

ee ks

(w ee

kl y)

Ed uc

at io

n

10 Zh

u et

a l.

(2 01

8) C

hi na

13 4

(6 7/

67 )

≥1 8

(6 9/

69 )

U nc

on tr

ol le

d H

TN

Te le

ph on

e •

M on

ito r h

ea lth

p ro

bl em

s, c

ur re

nt

co nd

iti on

, a nd

m od

ifi ca

tio ns

in

se lf-

m an

ag em

en t.

• Re

fe rr

al if

th e

pa rt

ic ip

an ts

m et

th

e re

fe rr

al c

rit er

ia .

3  m

on th

s (b

iw ee

kl y)

H om

e vi

si t

BP , s

el f-

ca re

b eh

av io

r (m

ed ic

at io

n, d

ie t,

lif es

ty le

, B P

m on

ito rin

g)

11 M

as la

kp ak

e t a

l. (2

01 6)

Ir

an 82

(4 1/

41 )

20 - 6

0 (5

3. 7/

50 .5

) U

nc on

tr ol

le d

H TN

Te xt

m es

sa ge

• Ed

uc at

e ab

ou t t

re at

m en

t ad

he re

nc e,

p hy

si ca

l a ct

iv iti

es ,

an d

BP m

on ito

rin g.

• C

om m

un ic

at e

w ith

p ar

tic ip

an ts

an

d an

sw er

q ue

st io

ns .

3  m

on th

s (6

ti m

es a

w ee

k) —

m

ed ic

at io

n/ di

et /

ap po

in tm

en t/

tr ea

tm en

t ad

he re

nc e

12 Zh

u et

a l.

(2 01

4) C

hi na

73 (3

6/ 37

) ≥3

5 (7

0. 4/

67 .8

) Fe

m al

e: 6

3. 1%

H TN

Te le

ph on

e •

M on

ito r h

ea lth

p ro

bl em

s an

d cu

rr en

t c on

di tio

n. •

C oo

rd in

at e

pa tie

nt s

to m

an ag

e th

ei r h

ea lth

p ro

bl em

s. •

O rg

an iz

e an

d fa

ci lit

at e

re so

ur ce

s to

m ee

t p at

ie nt

s’ ne

ed s

2  m

on th

s (b

iw ee

kl y

fo r u

nc on

tr ol

le d

H TN

, b im

on th

ly fo

r co

nt ro

lle d

H TN

)

H om

e vi

si t

BP , s

el f-

ca re

b eh

av io

r (m

ed ic

at io

n,

di et

, l ife

st yl

e,

BP m

on ito

rin g)

, se

lf- ef

fic ac

y

13 C

ic ol

in i e

t a l.

(2 01

4)

It al

y 19

8 (1

00 /9

8) ≥1

8 (5

9. 8/

58 .3

) H

TN

Em ai

l, Te

le ph

on e

• Re

m in

de r p

ro gr

am o

n tr

ea tm

en t

ad he

re nc

e an

d re

co m

m en

d he

al th

li fe

st yl

e vi

a em

ai l.

• Re

qu ire

p ar

tic ip

an ts

to re

ad

em ai

l v ia

te le

ph on

e.

6  m

on th

s (E

m ai

l: w

ee kl

y, T

el ep

ho ne

: N R)

—

BP , s

el f-

m an

ag em

en t

be ha

vi or

(m ed

ic at

io n,

di

et , l

ife st

yl e)

14 Ke

rr y

et a

l. (2

01 3)

U K

38 1

(1 87

/1 94

) ≥1

8 (7

1. 1/

72 .6

) H

TN w

ith s

tr ok

e of

TI

A h

is to

ry

Te le

ph on

e •

C he

ck B

P m

ea su

re m

en t

te ch

ni qu

e an

d re

vi ew

B P

re ad

in gs

. •

A dv

is e

to s

ee a

d oc

to r i

f n ee

de d.

12  m

on th

s (3

ti m

es , e

xc ep

t f or

un

co nt

ro lle

d H

TN )

—

SB P,

m ed

ic at

io n

ch an

ge

TA B

LE 1

(C on

tin ue

d)

    |  1027NURSE-­LED­DHIS­FOR­HYPERTENSION

N o

A ut

ho r (

Ye ar

) C ou

nt ry

Pa rt

ic ip

an ts

(I G

/C G

) M

ea n

ag e

(IG /C

G ) S

ex ,

D is

ea se

N ur

se - le

d di

gi ta

l h ea

lth in

te rv

en tio

ns A

dd iti

on al

su

pp or

t O

ut co

m e

Ty pe

Co nt

en ts

D ur

at io

n (F

re qu

en cy

)

15 H

eb er

t e t a

l. (2

01 2)

U

SA 16

8 (8

5/ 83

) ≥1

8 (6

0. 5/

60 .8

) Fe

m al

e: 7

0. 9%

U nc

on tr

ol le

d H

TN

Te le

ph on

e •

Re gu

la r f

ol lo

w - u

p fo

r r ei

nf or

ci ng

th

e ef

fe ct

o f c

ou ns

el lin

g re

ga rd

in g

BP m

on ito

rin g,

tr

ea tm

en t a

dh er

en ce

, a nd

lif

es ty

le m

od ifi

ca tio

n.

9  m

on th

s (N

R) C

ou ns

el lin

g BP

, m ed

ic at

io n

ad he

re nc

e

16 W

ak ef

ie ld

e t a

l. (2

01 1)

U

SA 20

0 (9

3/ 10

7) ≥1

8 (6

7. 8/

67 .9

) H

TN w

ith ty

pe 2

D M

Te le

he al

th

de vi

ce (V

ite rio

n- Ba

ye r

Pa na

so ni

c) ,

Te le

ph on

e,

Em ai

l

• Tr

an sm

it da

ta b

et w

ee n

pa tie

nt s

an d

st ud

y ce

nt er

v ia

te le

he al

th

de vi

ce .

• A

llo w

p ar

tic ip

an ts

to e

nt er

B P

da ta

a nd

re sp

on d

to q

ue st

io ns

. •

Fe ed

ba ck

d ep

en di

ng o

n th

e re

sp on

se s

of p

ar tic

ip an

ts .

• In

di vi

du al

iz ed

m es

sa ge

s an

d ad

vi ce

m es

sa ge

s

6  m

on th

s (T

el eh

ea lth

d ev

ic e:

w ee

kl y,

Te

le ph

on e:

N R,

E m

ai l:

N R)

—

BP

17 Bo

sw or

th e

t a l.

(2 01

1)

U SA

29 5

(1 48

/1 47

) ≥1

8 (6

3/ 64

) Fe

m al

e: 8

% H

TN

Te le

ph on

e, Te

le he

al th

de

vi ce

• Tr

an sm

it da

ta b

et w

ee n

pa tie

nt s

an d

st ud

y ce

nt er

v ia

te le

he al

th

de vi

ce .

• A

llo w

m on

ito rin

g vi

a a

te le

m ed

ic in

e de

vi ce

c on

ne ct

ed

to a

te le

ph on

e lin

e. •

Ta ilo

re d

in fo

rm at

io n

18  m

on th

s (N

R) —

BP

18 Pe

zz in

e t a

l. (2

01 1)

U SA

43 8

(2 21

/2 17

) 21

- 8 0

(6 4.

2/ 64

.3 )

Fe m

al e:

6 6%

U nc

on tr

ol le

d H

TN

Te le

ph on

e •

C ou

ns el

in g

• Re

vi ew

B P

da ta

a nd

co

m m

un ic

at e

fo r a

dj us

tin g

m ed

ic at

io n

if ne

ed ed

.

3  m

on th

s (b

iw ee

kl y)

—

BP

19 Ru

pp ar

(2 01

0) U

SA 15

(1 0/

5) ≥6

0 Fe

m al

e: 7

3% H

TN

Te le

he al

th

de vi

ce (M

EM S)

• In

di ca

te th

e nu

m be

r o f t

im es

th

e m

ed ic

at io

n bo

tt le

h as

b ee

n op

en ed

. •

A llo

w p

ar tic

ip an

ts to

d et

er m

in e

w he

th er

th ey

h ad

ta ke

n m

ed ic

at io

n.

2  m

on th

s (N

R) H

om e

vi si

t, Ed

uc at

io n

BP , m

ed ic

at io

n ad

he re

nc e

20 C

hi u

et a

l. (2

01 0)

C hi

na 63

(3 1/

32 )

≥1 8

(5 3.

3/ 54

.4 )

Fe m

al e:

6 6.

7% H

TN

Te le

ph on

e •

A ss

es s

he al

th c

on di

tio n,

B P,

a nd

ad

he re

nc e

to li

fe st

yl e.

• In

fo rm

at io

n an

d ad

vi ce

. •

Re in

fo rc

e se

lf- m

an ag

em en

t. •

A ss

es s

th e

ne ed

fo r r

ef er

ra l.

2  m

on th

s (e

ve ry

2 – 3

 w ee

ks )

C on

su lta

tio n

BP , s

el f-

ca re

a dh

er en

ce

21 Br

en na

n et

a l.

(2 01

0)

U SA

63 8

(3 20

/3 18

) ≥1

9 (5

5. 3/

56 .1

) H

TN

Te le

ph on

e,

Em ai

l •

In fo

rm at

io n

ab ou

t t he

d is

ea se

. •

Su pp

or t l

ife st

yl es

c ha

ng e

an d

tr ea

tm en

t a dh

er en

ce .

• Ed

uc at

io na

l m at

er ia

l v ia

e m

ai l.

6  m

on th

s (T

el ep

ho ne

: m on

th ly

, E m

ai l:

on ce

)

BP

TA B

LE 1

(C on

tin ue

d)

1028  |    NURSE-­LED­DHIS­FOR­HYPERTENSION

N o

A ut

ho r (

Ye ar

) C ou

nt ry

Pa rt

ic ip

an ts

(I G

/C G

) M

ea n

ag e

(IG /C

G ) S

ex ,

D is

ea se

N ur

se - le

d di

gi ta

l h ea

lth in

te rv

en tio

ns A

dd iti

on al

su

pp or

t O

ut co

m e

Ty pe

Co nt

en ts

D ur

at io

n (F

re qu

en cy

)

22 Bo

sw or

th e

t a l.

(2 00

9) U

SA 31

8 (1

59 /1

59 )

≥1 8

(6 1/

62 )

Fe m

al e:

6 6%

H TN

Te le

ph on

e •

Ta ilo

re d

be ha

vi or

al in

te rv

en tio

n fo

cu se

d on

im pr

ov in

g lif

es ty

le

m od

ifi ca

tio n.

24  m

on th

s (b

im on

th ly

) —

BP

, t re

at m

en t a

dh er

en ce

23 A

rt in

ia n

et a

l. (2

00 7)

U

SA 38

7 (1

94 /1

93 )

≥1 8

(5 9.

1/ 60

.2 )

H TN

Te le

m on

ito rin

g de

vi ce

, Te

le ph

on e

• C

ol le

ct d

at a

ab ou

t B P

m ea

su re

m en

t u si

ng a

B P

m on

ito r

co nn

ec te

d to

th e

te le

ph on

e. •

Fe ed

ba ck

a bo

ut ta

rg et

g oa

ls .

• C

ou ns

el in

g ab

ou t l

ife st

yl e

m od

ifi ca

tio n

an d

m ed

ic at

io n

ad he

re nc

e.

12  m

on th

s (T

el ep

ho ne

: w ee

kl y

un til

3 

m on

th s,

m on

th ly

be

tw ee

n 4

an d

6, a

nd o

nc e

at 8

 m on

th s)

—

BP

24 M

ar qu

ez C

on tr

er as

et

a l.

(2 00

5) S

pa in

36 6

(1 84

/1 82

) 18

- 8 0

(5 9.

1/ 60

.2 )

U nc

on tr

ol le

d H

TN

Te le

ph on

e •

Re in

fo rc

e co

m pl

ia nc

e. •

In fo

rm th

e de

gr ee

o f c

om pl

ia nc

e to

p at

ie nt

s. •

En co

ur ag

e pa

tie nt

s to

c on

tin ue

or

c om

pl y

tr ea

tm en

t a dh

er en

ce .

6  m

on th

s (3

ti m

es )

—

BP

25 Ru

dd e

t a l.

(2 00

4) U

SA 15

0 (7

4/ 76

) ≥6

0 (6

1. 7/

61 .9

) H

TN

Te le

ph on

e •

C ou

ns el

in g

ab ou

t d is

ea se

a nd

tr

ea tm

en t a

dh er

en ce

• C

om m

un ic

at e

w ith

p ar

tic ip

an ts

ab

ou t h

ea lth

s ta

tu s.

• M

an ag

em en

t a lg

or ith

m b

as ed

on

p ar

tic ip

an ts

’ m ed

ic at

io n,

la

bo ra

to ry

v al

ue s,

a nd

B P

m ea

su re

m en

ts .

6  m

on th

s (4

ti m

es )

C ou

ns el

lin g

BP , m

ed ic

at io

n ad

he re

nc e

26 A

rt in

ia n

et a

l. (2

00 1)

U

SA 15

(6 /9

) ≥1

8( 59

/6 0)

Fe m

al e:

8 8.

5% H

TN

Te le

ph on

e •

C ou

ns el

in g

ab ou

t l ife

st yl

e m

od ifi

ca tio

n •

Fe ed

ba ck

a bo

ut B

P in

re la

tio n

to p

ar tic

ip an

ts ’ t

ar ge

t g oa

l, m

ed ic

at io

n ad

he re

nc e,

a nd

lif

es ty

le m

od ifi

ca tio

n

3  m

on th

s (w

ee kl

y) H

om e

vi si

t BP

A bb

re vi

at io

ns : B

P, b

lo od

p re

ss ur

e; C

G , C

on tr

ol g

ro up

; H TN

, H yp

er te

ns io

n; IG

, I nt

er ve

nt io

n gr

ou p;

M EM

S, M

ed ic

at io

n Ev

en t M

on ito

rin g

Sy st

em ; N

R, N

ot re

po rt

ed ; S

BP , S

ys to

lic b

lo od

p re

ss ur

e; a

nd T

IA ,

Tr an

si en

t I sc

he m

ic A

tt ac

k.

TA B

LE 1

(C on

tin ue

d)

    |  1029NURSE-­LED­DHIS­FOR­HYPERTENSION

Medication Adherence Scale (Hebert et al., 2012; Kim, 2019; Sheilini et al., 2019). Nurse- led DHIs were shown to improve medication adherence in people with hypertension (SMD = 1.05, 95% CI: 0.41 to 1.69, Z = 3.23, p < 0.05, I2 = 92.5%, Figure 5b).

Diet adherence A total of two studies reported diet adherence that was measured using the Hill- Bone Compliance to High Blood Pressure Therapy Scale (Abu- El- Noor et al., 2021; Maslakpak & Safaie, 2016). Nurse- led DHIs were shown to improve diet adherence in people with hy- pertension (SMD = 0.80, 95% CI: 0.17 to 1.42, Z = 2.51, p < 0.05, I2 = 80.5%, Figure 5c).

Publication bias

To verify the validity of the results of studies on nurse- led DHIs for people with hypertension, publication bias for blood pressure was ana- lyzed using a funnel plot (Data S3). The Egger's regression test showed non- significant results with p = 0.67 for systolic blood pressure and p = 0.30 for diastolic blood pressure, suggesting no publication bias.

DISCUSSION

This systematic review and meta- analysis identified the effect of nurse- led digital health interventions (DHIs) on improving blood pres- sure control and self- management in people with hypertension. A total of 26 randomized controlled trials published after 2000 showed that studies on nurse- led DHIs for people with hypertension actively started in the 2000s, although most were published after 2010. Most studies were conducted in the United States, followed by Asia and Europe. This suggests that DHIs are adequate for providing nursing care for use in different populations and healthcare systems.

The components of nurse- led DHIs include interactive and ongo- ing communication between patients and healthcare providers using

technologies by education and motivation to improve blood pressure control and self- management. Our results found that nurses mainly used the telephone as a delivery channel for intervention, which was consistent with the findings of previous systematic reviews on inter- vention using digital technologies led by healthcare providers (Crilly & Kayyali, 2020; McLean et al., 2016). In our studies, 13 of 26 research (50%) used the telephone only, and nine studies (34.6%) used the telephone with other digital technologies, including mobile applica- tions, text messages, e-mail, telehealth devices, or social media. Given that nurse- led DHIs for patients with hypertension are mostly aimed at achieving optimal treatment adherence through counseling, tele- phone calls might have been often selected for real- time communica- tion between patients and nurses. However, our findings have shown that most nurse- led DHIs required functions sharing and transmitting health data between patients and nurses to provide education or feedback customized to patients' needs based on health- related data. Within this context, telephone- based interventions have limitations compared to other digital technologies to provide individualized care.

Various digital technologies other than telephone calls have begun to be used in nursing intervention for people with hyperten- sion since 2010. Nurse- led interventions utilizing mobile applications and telehealth devices allowed nurses to collect patient- reported health outcomes without limitation of time and space (Abu- El- Noor et al., 2021; Wakefield et al., 2011; Zha et al., 2020). One study used social media as a delivery channel to communicate effectively with patients, enabling nursing care using image and video material (Najafi Ghezeljeh et al., 2018). Considering new technologies are being rapidly developed and applied in healthcare systems, further studies using novel technologies such as wearable devices, video- conferencing, and artificial intelligence could be considered in de- veloping nursing interventions. In addition, allowing participants to choose their preferred technologies can be conducted to encour- age people with hypertension to interact with healthcare providers actively and promote treatment adherence with appropriate self- management. These strategies could improve patient engagement in disease management and blood pressure control.

F I G U R E 2  Graph of risk of bias.

1030  |    NURSE-­LED­DHIS­FOR­HYPERTENSION

In our meta- analysis, nurse- led DHIs reduced systolic blood pressure by 6.49 mmHg and diastolic blood pressure by 3.30 mmHg, compared with usual care. This was in line with previous meta- analysis findings

reporting that nurse- led interventions, including both in- person and remote strategies for hypertension patients, effectively reduced blood pressure (Stephen et al., 2022). It is worth mentioning that a reduction

F I G U R E 3  Summary of risk of bias.

    |  1031NURSE-­LED­DHIS­FOR­HYPERTENSION

in systolic blood pressure of ≥5 mmHg and diastolic blood pressure of ≥2 mmHg can reduce the risk of stroke by 7% and 11.5%, respectively (Reboldi et al., 2011; Stamler et al., 1989). Therefore, nurse- led DHIs may be a clinically effective strategy for people with hypertension.

Subgroup analyses were conducted to explain the cause of het- erogeneity in the effect size of blood pressure. In contrast to the non- tailored intervention mode, the effect of systolic blood pres- sure reduction was higher with the tailored intervention mode,

F I G U R E 4  Forest plot showing the effect of nurse- led DHIs on blood pressure control: (a) systolic blood pressure and (b) diastolic blood pressure.

1032  |    NURSE-­LED­DHIS­FOR­HYPERTENSION

suggesting that the tailored factor could be a moderator that ex- plains the heterogeneity between studies. In our review, nurse- led DHIs, employing a tailored intervention mode, included personal- ized education and feedback as main characteristics. This result sup- ports the previous findings that a patient- tailored intervention, such as reflecting the preferences or perspectives of patients and shared decision- making, improved blood pressure more than usual care (Li et al., 2020; Manalili et al., 2021). Our results have shown that fewer than half of the nurse- led DHIs used a tailored intervention mode when comprising the contents. This indicates additional effort is needed to develop effective intervention strategies with multifac- eted perspectives. There is evidence that following well- established processes, such as intervention mapping, could be one of the strategies for systematically integrating tailored factors into DHIs (Athilingam et al., 2018). This suggests that selecting a systematic

approach in the early stage for developing nurse- led DHIs would be appropriate to provide effective tailored intervention for achieving optimal blood pressure levels in people with hypertension.

In the secondary outcomes of our meta- analysis, each outcome showed large effect sizes for self- management of hypertension, medication adherence, and diet adherence. These findings differ from those of Ma et al. (2019), who reported no effect on medica- tion adherence and a small effect on diet adherence in their review of eHealth interventions. This may be attributed to program com- positions. The previous review included eHealth studies primarily focusing on antihypertensive medication adherence; however, this nurse- led DHIs included studies on blood pressure control as well as self- management behavior, including medication adherence and diet adherence. Non- adherence to self- management is a crucial fac- tor affecting the failure of hypertension management. Although the

F I G U R E 5  Forest plot showing the effect of nurse- led DHIs on self- management: (a) self- management; (b) medication adherence; and (c) diet adherence.

    |  1033NURSE-­LED­DHIS­FOR­HYPERTENSION

importance of self- management is highlighted for people with hyper- tension, only a few studies have included self- management- related outcomes (Williams et al., 2018). Therefore, further studies would be necessary to identify the effects of nurse- led DHIs on overall health improvement in hypertensive patients by measuring various vari- ables related to self- management other than blood pressure.

Some limitations must be considered for interpreting the find- ings of this systematic review and meta- analysis. Firstly, the studies included in our systematic review were not of high quality. In partic- ular, the studies had a high risk for bias arising from the randomiza- tion process and bias in the selection of the reported result domains. The main cause of the risk of bias for randomization was the lack of specification about the concealment of the randomization process. Therefore, a detailed description of allocation concealment would be necessary to increase the validity of future studies. The absence of previous protocols and protocol adherence affects the risk of bias for selective reporting. Among the 26 studies included in this sys- tematic review, 11 studies reported the protocol employed; how- ever, seven studies showed differences in the research process and outcome reporting process. Therefore, registering the study pro- tocol before starting RCTs and complying with the protocol would be necessary. Secondly, owing to the nature of DHIs with a broad concept, there was high heterogeneity between the studies. In par- ticular, although secondary outcomes (self- management, medication adherence, and diet adherence) showed high heterogeneity, sub- group analysis could not be performed owing to the small number of studies that reported each variable. Therefore, efforts to derive more valid evidence through additional meta- analysis studies would be necessary in the future. Lastly, this meta- analysis used results measured immediately after the interventions. Thus, the long- term effects of nurse- led DHIs could not be evaluated.

CONCLUSION

This study systematically reviewed RCTs regarding nurse- led DHIs for blood pressure control and self- management of people with hy- pertension and estimated the effect size through a meta- analysis. This study provided basic data for evidence- based practice to con- tribute to the development of future nursing interventions using digital technologies. Herein, we observed that nurse- led DHIs re- duced systolic blood pressure and diastolic blood pressure more ef- fectively than usual care. The reduction in systolic blood pressure was more effective when patient- tailored interventions were pro- vided. Additionally, nurse- led DHIs had a high effect size on self- management, medication adherence, and diet adherence in people with hypertension. Therefore, as new technologies are rapidly de- veloped and applied to the healthcare system, further studies and policy support are needed to utilize the latest digital innovations with nursing interventions.

ACKNO WLE DG E MENTS None.

FUNDING INFORMATION Not applicable.

CONFLIC T OF INTERE S T S TATEMENT No conflict of interest has been declared by the authors.

CLINIC AL RE SOURCE S PROSPERO International Prospective Register of Systematic Reviews (Registration number: CRD42021264095).

ORCID Misun Hwang https://orcid.org/0000-0001-8102-3308 Ae Kyung Chang https://orcid.org/0000-0002-6679-7310

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SUPPORTING INFORMATION Additional supporting information can be found online in the Supporting Information section at the end of this article. Data S1. Search strategies Data S2. Included studies (*meta- analysis) Data S3. Publication bias Tables S1.

How to cite this article: Hwang, M. & Chang, A. K. (2023). The effect of nurse- led digital health interventions on blood pressure control for people with hypertension: A systematic review and meta- analysis. Journal of Nursing Scholarship, 55, 1020–1035. https://doi.org/10.1111/jnu.12882