public target interventions to reduce the inappropriate
TRANSCRIPT
SYSTEMATIC REVIEW Open Access
Public target interventions to reduce theinappropriate use of medicines or medicalprocedures: a systematic reviewLeesa Lin* , Prima Alam, Elizabeth Fearon and James R. Hargreaves
Abstract
Background: An epidemic of health disorders can be triggered by a collective manifestation of inappropriatebehaviors, usually systematically fueled by non-medical factors at the individual and/or societal levels. This study aimedto (1) landscape and assess the evidence on interventions that reduce inappropriate demand of medical resources(medicines or procedures) by triggering behavioral change among healthcare consumers, (2) map out interventioncomponents that have been tried and tested, and (3) identify the “active ingredients” of behavior change interventionsthat were proven to be effective in containing epidemics of inappropriate use of medical resources.
Methods: For this systematic review, we searched MEDLINE, EMBASE, the Cochrane Library, and PsychINFO from thedatabases’ inceptions to May 2019, without language restrictions, for behavioral intervention studies. Interventions hadto be empirically evaluated with a control group that demonstrated whether the effects of the campaign extendedbeyond trends occurring in the absence of the intervention. Outcomes of interest were reductions in inappropriate ornon-essential use of medicines and/or medical procedures for clinical conditions that do not require them. Tworeviewers independently screened titles, abstracts, and full text for inclusion and extracted data on study characteristics(e.g., study design), intervention development, implementation strategies, and effect size. Data extraction sheets werebased on the checklist from the Cochrane Handbook for Systematic Reviews.
Results: Forty-three studies were included. The behavior change technique taxonomy v1 (BCTTv1), which contains 93behavioral change techniques (BCTs), was used to characterize components of the interventions reported in the includedstudies. Of the 93 BCTs, 15 (16%) were identified within the descriptions of the selected studies targeting healthcareconsumers. Interventions consisting of education messages, recommended behavior alternatives, and a supportingenvironment that incentivizes or encourages the adoption of a new behavior were more likely to be successful.
Conclusions: There is a continued tendency in research reporting that mainly stresses the effectiveness of interventionsrather than the process of identifying and developing key components and the parameters within which they operate.Reporting “negative results” is likely as critical as reporting “active ingredients” and positive findings for implementationscience. This review calls for a standardized approach to report intervention studies.
Trial registration: PROSPERO registration number CRD42019139537
© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate ifchanges were made. The images or other third party material in this article are included in the article's Creative Commonslicence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commonslicence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtainpermission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to thedata made available in this article, unless otherwise stated in a credit line to the data.
* Correspondence: [email protected]; [email protected] School of Hygiene & Tropical Medicine, London, UK
Lin et al. Implementation Science (2020) 15:90 https://doi.org/10.1186/s13012-020-01018-7
BackgroundEpidemics, which traditionally refer to a widespread oc-currence of an infectious disease in a community at aparticular time, have in recent years been used to de-scribe large-scale public health issues caused by a sharedpattern of human behaviors that impact public healthand well-being. An epidemic of health disorders can notonly be triggered by organisms that cause communicablediseases, such as bacteria, viruses, fungi, or parasites, butalso by a collective manifestation of inappropriate behav-iors, usually systematically fueled by non-clinical factorsat the individual and/or societal levels. When medicinesor medical procedures are used for conditions for whichthey should not be used, they are deemed as inappropri-ate use of medical interventions. For example, the WorldHealth Organization and governments have warnedabout the recent spike in the use of prescription drugs[1] and cesarean sections [2] globally, which has formedan epidemic that has caused avoidable damage to indi-vidual health and introduced excessive burdens onhealth systems [3, 4].There have been experiments with programs specific-
ally designed to address factors driving the epidemics ofinappropriate use of medical interventions. These coun-termeasures are often non-clinical behavioral changeinterventions targeting physicians and pharmacists as apoint-of-entry for interventions and are designed toimprove clinical practices and policies that restrict un-necessary dispensing [5, 6]. These programs usuallyemployed educational materials (e.g., guidelines, lectures,workshops) [7, 8], auditing and feedback on prescribingpractices [9–12], or computer-aided clinical decision
support systems [13]. A 2005 Cochrane review con-cluded that, for interventions occurring on multiplelevels to be effective, local barriers to change—includingthe role patients play in driving inappropriate demand—must be addressed [14]. Current interventions to addressthe pressure of inappropriate demands outside the clin-ical setting range from national mass media campaignsto local interventions targeted at smaller communities[15], aiming to influence the knowledge, attitudes, andpractices towards medical use of the general public whohave yet to become healthcare consumers: namely pa-tients and caretakers of patients [15–17]. However, re-cent reviews highlighted that critical knowledge gapsexist in the evidence for engaging healthcare consumersas active decision-makers for appropriate medical use (asopposed to passive receivers of education materials) [18,19]. Furthermore, the lack of evidence in the develop-ment of and evaluation of the impact of these interven-tions, especially in low- and middle-income countries(LMICs), complicates replication efforts [16, 17, 20].The Behavioral Change Wheel (BCW) [21] and the be-
havior change techniques taxonomy volume 1 (BCTTv1)[22], developed by Michie and colleagues, facilitate re-searchers in organizing the content and components ofbehavioral interventions into nine intervention func-tions: education, persuasion, incentivization, coercion,training, enablement, modeling, environmental restruc-turing, and restrictions and assists them in translatingspecific techniques that were employed in a given inter-vention into change behaviors. Scientists have supportedthe use of BCW and BCTTv1 as a reliable and validatedmethodology that offers a common language for describ-ing intervention components that can be used for thestandardization of intervention content analysis and thedevelopment of interventions [23–25].In this study, we aimed to (1) landscape and critically
assess the evidence on non-clinical programs that reduceinappropriate or unnecessary use of medical interven-tions (i.e., medicines or medical procedures) by trigger-ing behavioral change among healthcare consumers, (2)map out intervention components that have been triedand tested, and (3) identify the “active ingredients” of be-havior change intervention programs that were provento be effective in containing “epidemics of inappropriateuse of medical interventions.”
MethodsSearchesFor this systematic review, we searched MEDLINE,EMBASE, the Cochrane Library, and PsychINFO fromthe databases’ inceptions to May 2019, without languagerestrictions, for behavioral intervention studies. A searchstrategy was first developed for MEDLINE and adaptedto other databases. The full-search strategy is detailed in
Contributions to the literature
� This review identifies the types, components, and
combinations of interventions more likely to successfully
initiate and sustain public behavior change in the context of
complexity.
� It can inform practitioners’ decisions about designing,
implementing, and reporting interventions to reduce
inappropriate use/demand of medical interventions while
researchers and funders can use this review to determine
where research is needed.
� No community-based interventions were found in LMICs; in-
terventions were limited to primary care settings or policy re-
strictions on the supply side (e.g., ban on over-the-counter
purchases).
� There is a need for standardized reporting of intervention
development, adaptation, and implementation to maximize
generalisability and replicability.
Lin et al. Implementation Science (2020) 15:90 Page 2 of 35
Additional file 1. We searched for behavioral change in-terventions that aimed to reduce inappropriate or non-essential use of medical services or medicines that weredriven by non-clinical factors and targeted health careconsumers in the community, including primary caresettings. For the purpose of this study, health careconsumers included the public, patients, and caregivers(e.g., parents or guardians).
Study inclusion and exclusion criteriaInclusion and exclusion criteria used for all stages of thescreening process are stated in Additional file 2. Studieshad to be empirically tested by either randomized con-trolled trial (RCT), cluster-RCT (CRT), nonrandomizedcontrolled trial (NCT), or interrupted times series (ITS)where the intervention time was clearly defined, andthere were at least three data points both before andafter the intervention, or quasi-experiments with a con-trol group. To enable assessment of effectiveness in in-cluded interventions, this review excludes before/afterevaluations of public campaigns or interventions thatfailed to employ a control group and therefore cannotshow whether the effects of the campaign extended be-yond trends occurring in the absence of the intervention.Outcomes of interest were reductions in inappropriateor non-essential use of medicines and/or medical proce-dures for clinical conditions that do not require them.Four major types of behaviors were identified, namelyinappropriate antibiotic consumption (e.g., for viral in-fections or self-limiting conditions), elective cesareansection, demand for brand-name drugs that are availableas generics, and non-medical use of prescription drugs,defined as “use without a prescription or use for reasonsother than what the medication is intended for” [16, 26,27]. Studies that focused only on change of knowledgeor attitudes and did not report actual behavioral datawere excluded. Studies mainly targeting clinicians, otherhealthcare staff, hospitals, inpatients, emergency care, orpatients with mental health conditions were excluded.To create a distinction between interventions directed athealth care consumers rather than providers, studies thataimed to modify clinical practices (e.g., prescribing) wereexcluded. Also, to differentiate behavior change inter-ventions from therapies/treatments addressing mentalhealth conditions such as addiction or depression, weexcluded interventions for substance abuse, where in-appropriate use was an outcome of a clinical condition,not a cause.
Data extraction strategyAll titles retrieved from the searches were imported intoEndnote referencing software. Duplicates were removed.Titles and abstracts were independently screened for in-clusion by two reviewers (L.L and P.A.) and removed if
deemed irrelevant. Both authors independently screenedthe full text (n = 347) of the remaining studies to assesseligibility. Substantial agreement was found at all threestages (> 90%). Disagreements were resolved throughdiscussion among reviewers to achieve consensus; anyfurther discrepancies about study inclusion were re-solved through discussion with a third reviewer (E.F. orJ.H). We also manually searched the bibliographies of allthe included studies and reference lists of relevant sys-tematic reviews to identify additional citations.We extracted the data on study characteristics: the
country where the study was conducted, type of inappro-priate use, target population, study design (e.g., RCT,controlled pre- and post-study [CPP]), data collectionmethods (e.g., survey, interview, medical records), and,when focused on a population study, sampling method-ology (e.g., cluster, convenience), primary or main out-come measure, and conclusions reported. We furtherexamined reporting on intervention development/adap-tion, design, and implementation strategies. Additionally,we extracted underlying theoretical domains, effect size,and risk of bias by two independent review authors, whodetermined the domains within the Behavioral ChangeWheel (BCW) and identified the “active ingredients” ofthe interventions according to BCTTv1. Data extractionsheets were based on the checklist from the CochraneHandbook for Systematic Reviews [28]. The forms weremodified after piloting on a sample of studies. Whencoding, we adopted the coding assumptions reported byPresseau et al. [25] that BCTs worked through targetingthe behavior of health care consumers, or both the be-havior of health care consumers and providers. We alsoassumed policy interventions and national campaignswere driven by governments and therefore coded gov-ernments as implementers for respective interventions.After the data extraction phase, we identified criticalevidence gaps in evaluation data and processes of inter-vention development and implementation. We thereforeconducted another round of targeted, investigativesearches, involving citation and publication searches onfirst, last, and corresponding authors of selected inter-ventions, seeking formative, process, and impact evalu-ation data.
Study quality assessmentWe conducted and reported the review in line with thePreferred Reporting Items for Systematic Reviews andMeta-Analyses statement (PRISMA). Risk of bias wasassessed by two reviewers using the Effective PublicHealth Practice Project’s (EPHPP) Quality AssessmentTool for Quantitative Studies [29], which includes eightcomponents (21 items): selection bias, study design, con-founders, blinding, data collection methods, withdrawalsor dropouts, intervention, and integrity. A rating of
Lin et al. Implementation Science (2020) 15:90 Page 3 of 35
weak, moderate, or strong was given to each of the firstsix components, and these scores contributed to a globalrating for the study. Qualitative data was assessed by theCritical Appraisal Skills Programme (CASP) checklist.
Data synthesis on active ingredientsUsing BCW domains and BCT taxonomies, we ana-lyzed descriptions of all interventions and identifiedthe commonly targeted aspects by looking at the fre-quency with which BCW domain and BCT of the in-terventions were incorporated in the studies. We alsoexplored the nature and pattern of the use of theseactive ingredients across the different studies, and theassociated magnitude of effect size. We descriptivelyreported the active ingredients and primary outcomes’effect sizes at the study level, counting the number oftimes a BCW domain and a BCT had been identified
across studies and in different types of use behaviorsand presented a description of features of includedinterventions.
ResultsReview statisticsOur systematic search of the literature yielded 4045results through database searching and an additional238 were identified through bibliography searches.After de-duplication and title and abstract screening,347 references were assessed in full text. A flow dia-gram of the study selection process is shown in Fig.1. Forty-three studies (representing 43 interventions,see Additional file 3)—conducted between 1994 andMay 2019 and meeting inclusion criteria—were in-cluded in the systematic review. Twenty-five studiedinterventions focused on the reduction of antibiotic
Fig. 1 Flow diagram of systematic review search
Lin et al. Implementation Science (2020) 15:90 Page 4 of 35
use—eight on elective cesarean section, four on theconversion from brand name drugs to generic equiva-lents, and six on nonmedical use of prescriptiondrugs. Table 1 provides an overview of the includedintervention studies for full-text extraction includingintervention aims and components.
Study characteristicsAll included studies were published in English.Twenty-four in North America (excluding Mexico;USA: n = 21, Canada: n = 3), four in Latin America(Chile, Colombia, Venezuela, Brazil, and Mexico), fourin the Middle East (Iran), eight in Europe (France,UK, Italy, Spain, and Moldova), three in East Asiaand Pacific (Australia and Singapore), and none fromsub-Saharan Africa, South Asia, or the Caribbean.The imbalance between high-income countries (HICs)and low- and middle-income countries (LMICs) is ap-parent when characterizing types of inappropriate use.Multifaceted interventions are scarce and limited toHICs while interventions in LMICs were limited toprimary care settings or policy restrictions (on over-the-counter purchases) with zero community-basedprograms identified. No studies from LMICs focusedon demands for brand-name drugs or non-medicaluse of prescription drugs.
Study designThe included studies consisted of 18 RCTs and fiveNCTs, eight ITS, and 12 quasi-experimental studies.These studies varied in their quality, methodologicaldesign, and implementation. Twenty-four studies re-ported longitudinal data; the rest employed cross-sectional study designs. All were outcome evaluationstudies. In terms of data collection methods for evalu-ation, 23 studies employed surveys and 30 utilizedmedical record data—these were not mutually exclu-sive. Four studies reported cost data. One studyemployed interviews as part of the intervention pro-cedure, but not for evaluation purposes [51]. Noqualitative data were reported in the initial includedstudies; we therefore conducted a targeted, investiga-tive search on the selected interventions, but only lo-cated minimal formative data on some of the studies[30, 45–47, 50]. One UK-based project that aimed toimprove the decision-making around mode of deliveryamong pregnant women published comprehensive im-plementation research data from pilot results [48] andstudy protocol [47] to outcome and economic evalu-ation [45, 46, 49, 52, 53]. Table 2 presents a summaryof the key characteristics of each study measuring be-havioral outcomes and reported formative and rele-vant evaluation data of the included interventions.
Study quality assessmentStudy quality varied by domain assessed based on theprimary behavioral outcomes (Additional file 4). Therewere 11 studies of overall strong quality, 12 of overallmoderate quality, and 20 of overall low quality. In orderto provide an overview of the entire literature, no studieswere excluded based on their methodological quality.The majority of behavior outcomes were derived frommedical records, leaving minimal room for reportingerrors with the exception that some only relied on self-reported data for evaluation.
Active ingredients of the behavior change interventionsAll of the interventions utilized multiple behaviorchange techniques (BCTs) with a primary aim to im-prove health care consumers’ behavior. Table 3 presentsthe features of all the included interventions; the fre-quency distributions of BCTs employed are presented inFig. 2. Of all 93 BCTs in the taxonomy, 19 (19/93,22.9%) were used as active ingredients in the includedinterventions: four BCTs were used exclusively for inter-ventions targeting health care consumers (BCTs 3.3, 6.1,9.2, 12.2); another four were used exclusively for multifa-ceted interventions that also targeted providers (BCTs1.3, 2.2, 3.2, 14.2), with 11 BCTs used for both (BCTs3.1, 4.1, 4.2, 5.1, 5.2, 8.2, 9.1, 10.1, 10.2, 12.1, 12.5; seeTables 4 and 5 for details). When compared with theprinciples in the Behavioral Change Wheel, 39 interven-tions employed education as an active ingredientfollowed by enablement (n = 12), environmental restruc-turing (n = 8), and restriction (n = 4). Of the 43 includedstudies, 22 were interventions delivered only at the com-munity level, 12 in primary care settings, six in bothcommunity and primary care settings, and three inschools. Nineteen interventions were delivered on an in-dividual basis, which tended to be shorter in duration,ranging from one to multiple short sessions. The major-ity of studies focused on evaluation design and outcomesand only provided high-level descriptions of the inter-vention, with or without details on the development orimplementation processes. Twenty studies providedclear descriptions on the intervention adaption/develop-ment process, all on implementation strategies (e.g.,channels and timing of dissemination), and, to a certainlevel, 15 on intervention dose (intensity) [54–56] andnine on designs (e.g., color and format) [55–58]. Somestudies provided links to intervention designs, but mostof these links had expired. Only eight interventionsexplicitly reported having adopted a theory or model ofbehavioral change, which included social marketing [56,59, 60], social cognitive theory [55], precede/proceedmodel [61], social development model [39, 40], and thehealth belief model [62]. However, little was reported on
Lin et al. Implementation Science (2020) 15:90 Page 5 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting
Con
text
Interven
tionelem
ents
Firstauthor,
year
Target
illne
ss/
cond
ition
Cou
ntry
Lastmon
thof
data
collected
Setting
Target
drivers/factors
Nam
eSlog
anTarget
audien
ceHealth
care
providers
Health
care
consum
ers
BCT-
provider
BCT-
consum
erBehavioral
Chang
eWhe
el
Theory-
based
Inapprop
riate
useof
antib
iotics
Belong
ia,
2001
RTIs
USA
June
1998
Com
mun
ityandprim
ary
care
setting
Know
ledg
e(includ
ing
awaren
ess),
cultu
ral,and
doctor-patient
relatio
nship
–Non
eCom
mun
ityand
healthcare
providers
Physician
education
(paren
ted
ucation
pamph
lets,
parent
inform
ation
sheets,a
sampleletter,
“prescrip
tion
pad,”CDCfact
sheets
Public
education
materials:
prog
rams,
pamph
letsand
posters,
presen
tatio
nsand“Coldkits”
4.1
4.2
5.1
8.2
12.5
4.1
4.2
5.1
8.2
12.5
Education
–
Belong
ia,
2005
Not
specified
USA
Decem
ber
2003
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess)
Wisconsin
antib
iotic
resistance
netw
ork
“The
re’sno
excuse
for
overuse!”and
“Get
smart
abou
tantib
iotics!”
Com
mun
ityand
healthcare
providers
Physician
education
(mailings,
suscep
tibility
repo
rts,
practice
guidelines,
satellite
conferen
ces,
and
presen
tatio
ns)
Massmed
iacampaign
(television,
radio,
newspapers,
press
conferen
ce;
paid
ad);
Patient
education
materials
4.1
4.2
5.1
12.5
4.1
4.2
5.1
12.5
Education
–
Bernier,
2014
Not
specified
France
Decem
ber
2010
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess)
–“Antibiotics
areno
tautomatic!”
and
“antibiotics,
used
unne
cessarily,
lose
their
potency!”
Com
mun
ityGuide
lines,
seminars,
academ
icde
tailing
,letters
Pamph
letsand
posters,print
med
ia,radio,
television
,web
site
4.1
4.2
5.1
12.5
4.1
4.2
5.1
12.5
Education
–
Ceb
otaren
co,
2008
RTIs
Moldo
vaMarch
2004
Scho
olsetting
Know
ledg
e(includ
ing
awaren
ess)
peer
–Non
eCom
mun
ity-
stud
entsand
guardians
–Peer-
education,
parents’
meetin
gs,
booklet,
vign
ette
vide
o,ne
wsletter,
poster,and
poster
contest
–4.1
4.2
6.1
12.2
Education
Social
cogn
itive
theory
Finkelstein,
2001
RTIs
USA
Decem
ber,
1998
Com
mun
ity&prim
ary
care
setting
Know
ledg
e(includ
ing
awaren
ess),
doctor-patient
relatio
nship,
peer
leader
––
Com
mun
ityand
healthcare
providers
Guide
line
dissem
ination,
small-g
roup
education,
edu-
catio
nalm
ate-
rials,and
Educational
materialsfor
parentsby
mailand
inprim
arycare
practices,
2.2
3.2
4.1
4.2
5.1
8.2
4.1
4.2
5.1
8.2
9.1
Education
–
Lin et al. Implementation Science (2020) 15:90 Page 6 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Con
text
Interven
tionelem
ents
Firstauthor,
year
Target
illne
ss/
cond
ition
Cou
ntry
Lastmon
thof
data
collected
Setting
Target
drivers/factors
Nam
eSlog
anTarget
audien
ceHealth
care
providers
Health
care
consum
ers
BCT-
provider
BCT-
consum
erBehavioral
Chang
eWhe
el
Theory-
based
prescribing
feed
back.
pharmacies,
andchildcare
settings
9.1
Finkelstein,
2008
RTIs
USA
Aug
ust
2003
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
doctor-patient
relatio
nship
Redu
cing
antib
ioticsfor
childrenin
Massachusetts
(REA
CHMass)
Non
eCom
mun
ityand
healthcare
providers
Guide
line
dissem
ination,
small-g
roup
education,
edu-
catio
nalm
ate-
rials,“prescrip-
tionpad”,and
prescribing
feed
back.
Educational
materialsfor
parentsby
mailand
inprim
arycare
practices,
pharmacies,
andchildcare
settings
2.2
3.2
4.1
4.2
5.1
8.2
4.1
4.2
5.1
8.2
Education
Social
marketin
g
Form
oso,
2013
RTIs
Italy
March
2012
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
cultu
ral,and
doctor-patient
relatio
nship
Antibiotics,
solutio
nor
prob
lem
“Antibiotics,
solutio
nor
prob
lem?”
Com
mun
ityand
healthcare
providers
ane
wsletteron
localA
MR.
campaign
materials
(highlighting
how
tode
alwith
patients’
expe
ctations,
occurren
ceof
AMRandof
side
effects.)
massmed
iaspaces
(television,
radio,
newspapers)
written
materials
(brochures,
posters,
newsletters)
4.1
4.2
5.1
5.2
12.5
4.1
4.2
5.1
5.2
12.5
Education/
persuasion
Social
marketin
g
Fuertes,
2010
Not
specified
Canada
Decem
ber
2008
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess)
Dobu
gsne
eddrug
s?Non
eCom
mun
ityand
healthcare
providers
Television
campaign
Television
campaign
4.1
4.2
5.1
5.2
8.2
4.1
4.2
5.1
5.2
8.2
Education
–
Gon
zales,
2004
RTIs
USA
February
2002
Com
mun
ity&prim
ary
care
setting
Know
ledg
e(includ
ing
awaren
ess)
and
doctor-patient
relatio
nship
Minim
izing
antib
iotic
tesistance
inColorado
BeSM
ART
abou
tantib
iotics
Com
mun
ityand
healthcare
providers
Antibiotic
prescribing
profilesand
practices
guidelines
Waitin
groom
materials,
exam
ination
room
posters;
mailing
campaign
packets:
househ
old-
andoffice-
basedpatient
education
materials
1.3
12.5
4.1
4.2
5.1
9.1
12.5
Education
–
Gon
zales,
2005
RTIs
USA
February
2002
Com
mun
ity&prim
ary
care
setting
Know
ledg
e(includ
ing
awaren
ess)
anddo
ctor-
patient
relatio
nship
Minim
izing
antib
iotic
resistance
inColorado
BeSM
ART
abou
tantib
iotics
Com
mun
ityand
healthcare
providers
antib
iotic
prescribing
profilesand
practices
guidelines
Waitin
groom
materials,
exam
ination
room
posters;
mailing
campaign
1.3
12.5
4.1
4.2
5.1
9.1
12.5
Education
–
Lin et al. Implementation Science (2020) 15:90 Page 7 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Con
text
Interven
tionelem
ents
Firstauthor,
year
Target
illne
ss/
cond
ition
Cou
ntry
Lastmon
thof
data
collected
Setting
Target
drivers/factors
Nam
eSlog
anTarget
audien
ceHealth
care
providers
Health
care
consum
ers
BCT-
provider
BCT-
consum
erBehavioral
Chang
eWhe
el
Theory-
based
packets:
househ
old-
andoffice-
basedpatient
education
materials
Gon
zales,
2008
Not
specified
USA
Decem
ber
2003
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess)
Minim
izing
antib
iotic
resistance
inColorado
“Get
amart:
useantib
iotics
wisely.”and
“Use
antibio´
ticos
solosiun
doctor
selo
receta”
Com
mun
ityand
healthcare
providers
Prim
arycare
physicians
Massmed
iacampaign,
educational
even
tsand
written
educational
materials
4.1
4.2
5.1
12.5
4.1
4.2
5.1
12.5
Education
Social
marketin
g
Hen
nessy,
2002
RTIs
USA
Decem
ber
2000
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess)
––
Com
mun
ityand
healthcare
providers
Worksho
psand
follow-upvisits
Printed
inform
ation
and
newsletters
4.1
4.2
4.1
4.2
5.1
Education
–
Kliemann,
2016
Not
specified
Brazil
Decem
ber
2012
Com
mun
itySocioe
cono
mic
determ
inants;
access
tono
n-prescriptio
nantib
iotics
––
Com
mun
ityand
healthcare
providers
Restrictio
non
saleof
antib
iotics
with
out
prescriptio
n
Restrictio
non
saleof
antib
iotics
with
out
prescriptio
n
12.1
12.1
Restrictio
n,en
vironm
ental
restructuring
–
Lambe
rt,
2007
RTIs
UK
February
2005
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess)
–Antibiotics–
tracking
downthe
trust
Com
mun
ityand
healthcare
providers
Profession
aled
ucationand
prescribing
supp
ort
Massmed
iawith
printed
materials
4.1
8.2
12.5
4.1
8.2
12.5
Education
–
Lee,2017
RTIs
Sing
apore
Not
specified
Prim
arycare
setting
Know
ledg
e(correcting
misconcep
tions)
––
Com
mun
ity-
patients
–Educational
pamph
letsand
verbal
coun
seling
–4.1
4.2
Education
–
Maino
us,
2009
Not
specified
USA
June
2008
Com
mun
ityKn
owledg
e(includ
ing
misconcep
tions);
cultu
ral
“SoloCon
Receta”
(onlywith
aprescriptio
n)
–Com
mun
ity–
Culturally
sensitive
commun
ityinterven
tion
with
multip
lemed
iasources
–4.1
5.1
Education
–
McN
ulty,
2010
RTIs
UK
Janu
ary
2009
Com
mun
ity&prim
ary
care
setting
Know
ledg
e(correcting
misconcep
tions)
––
Com
mun
ity-
patients
NICEgu
idance
ontheprim
ary
care
managem
ent
ofcommon
,acute,self-
limiting
RTIs
Threepo
sters
displayedin
magazines
and
newspapers
4.1
4.2
8.2
4.1
4.2
Education
–
Lin et al. Implementation Science (2020) 15:90 Page 8 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Con
text
Interven
tionelem
ents
Firstauthor,
year
Target
illne
ss/
cond
ition
Cou
ntry
Lastmon
thof
data
collected
Setting
Target
drivers/factors
Nam
eSlog
anTarget
audien
ceHealth
care
providers
Health
care
consum
ers
BCT-
provider
BCT-
consum
erBehavioral
Chang
eWhe
el
Theory-
based
Perz,2002
RTIs
USA
April1999
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess);
peer
–Antibiotics
andyour
child
Com
mun
ityand
healthcare
providers
Educatingpe
erleader
presen
tatio
ns
Public
educationvia
printed
material
4.1
4.2
4.1
4.2
8.2
Education
–
Sabu
ncu,
2009
RTIs
France
Decem
ber
2007
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess)
Keep
antib
iotics
working
“Les
antib
iotiq
ues
c’estpas
automatique
”(“A
ntibiotics
areno
tautomatic”)
Com
mun
ityGuide
lines,
seminars,
academ
icde
tailing
,letters
Pamph
letsand
posters,print
med
ia,radio,
television
,web
site
4.1
4.2
5.1
12.5
4.1
4.2
5.1
12.5
Education
–
Santa-Ana-
Tellez,2013
Not
specified
Braziland
Mexico
June
2012
Com
mun
ityAccessto
non-prescriptio
nantib
iotics
––
Com
mun
ityand
healthcare
providers
Restrictio
non
saleof
antib
iotics
with
out
prescriptio
nin
pharmacies,
and
introd
uctio
nof
fineon
owne
rsof
pharmacies
forno
n-compliance.
Restrictio
non
saleof
antib
iotics
with
out
prescriptio
n
12.1
14.2
(only
Mexico)
12.1
Restrictio
n,coercion
,en
vironm
ental
restructuring
–
Santa-Ana-
Tellez,2015
Not
specified
Braziland
Mexico
March
2012
Com
mun
ityAccessto
non-prescriptio
nantib
iotics
––
Com
mun
ityand
healthcare
providers
Restrictio
non
saleof
antib
iotics
with
out
prescriptio
nin
pharmacies,
and
introd
uctio
nof
fineon
owne
rsof
pharmacies
forno
n-compliance.
Restrictio
non
saleof
antib
iotics
with
out
prescriptio
n
12.1
14.2
(only
Mexico)
12.1
Restrictio
n,coercion
,en
vironm
ental
restructuring
–
Taylor,2005
RTIs
USA
April2002
Prim
arycare
setting
Know
ledg
e,do
ctor-patient
relatio
nship
–Pu
getSoun
dPediatric
Research
Network
Com
mun
ity-
parentsand
children
-Educational
pamph
letsand
avide
o
–4.1
9.1
Education
–
Trep
ka,2001
RTIs
USA
Aug
ust
1998
Com
mun
ity&prim
ary
care
setting
Know
ledg
e(includ
ing
awaren
ess),
cultu
ral,and
doctor-patient
relatio
nship
–Yo
urchild
and
antib
iotics
Com
mun
ityand
healthcare
providers
“Grand
roun
ds”
presen
tatio
ns,
small-g
roup
academ
icde
-tailing
,and
dis-
tributionof
writtenmate-
rials(clinical
practice
Public
education
materials:
prog
rams,
pamph
lets,
andpo
sters,
presen
tatio
nsand
newspapers
4.1
4.2
5.1
8.2
12.5
4.1
4.2
5.1
8.2
12.5
Education
–
Lin et al. Implementation Science (2020) 15:90 Page 9 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Con
text
Interven
tionelem
ents
Firstauthor,
year
Target
illne
ss/
cond
ition
Cou
ntry
Lastmon
thof
data
collected
Setting
Target
drivers/factors
Nam
eSlog
anTarget
audien
ceHealth
care
providers
Health
care
consum
ers
BCT-
provider
BCT-
consum
erBehavioral
Chang
eWhe
el
Theory-
based
guidelines,clin-
icalfact
sheets,
andsamples
ofpatient
educa-
tionmaterials.)
Wirtz,2013
Not
specified
Chile,
Colom
bia,
Vene
zuela,
Mexico
Septem
ber
2009
Com
mun
ityAccessto
non-prescriptio
nantib
iotics
––
Com
mun
ityand
healthcare
providers
Restrictio
non
saleof
antib
iotics
with
out
prescriptio
n
Restrictio
non
saleof
antib
iotics
with
out
prescriptio
n
12.1
12.1
Restrictio
n,coercion
,en
vironm
ental
restructuring
–
Wutzke,2007
RTIs
Australia
Aug
ust
2004
Com
mun
ity&prim
ary
care
setting
Know
ledg
e,do
ctor-patient
relatio
nship;
peer
TheNPS
common
colds
commun
itycampaign
“Com
mon
coldsne
edcommon
sense:they
don’tne
edantib
iotics.”
Com
mun
ityand
healthcare
providers
Prescriptio
npads,p
atient
inform
ation
leaflets,
prescribing
software.
newsletters,
prescribing
feed
back,
educational
visitin
g,clinical
auditwith
feed
back
and
case
stud
ies
(paper
and
peer
grou
pdiscussion
).
Massmed
iaactivity
using
billboards,
television
,radio,
and
magazines
and
smallg
rantsto
prom
otelocal
commun
ityed
ucation
2.2
3.1
4.1
4.2
8.2
12.5
4.1
4.2
8.2
12.5
Education/
persuasion
–
Dem
andof
brandnamedrug
s
Beshears,
2013
Not
specified
USA
Octob
er2014
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
peer
influen
ce
––
Com
mun
ity-
union
mem
bers
–Inform
ational
letterswith
orwith
outa
testim
onial
from
person
with
/with
out
shared
union
affiliatio
n
–8.2
9.1
10.1
10.2
Education,
persuasion
–
O'Malley,
2006
Not
specified
USA
Decem
ber
2003
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
incentives
––
Com
mun
ityand
healthcare
providers
Free
gene
ricdrug
samples,
physician
financial
incentives
Mem
ber
mailings,
advertising
campaigns
3.2
4.1
8.2
10.1
10.2
12.5
4.1
8.2
10.1
10.2
12.5
Education,
incentivization
–
Sedjo,
2009
Not
specified
USA
Decem
ber
2007
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
incentives
––
Com
mun
ity–
health
plan
enrollees
–Targeted
messaging
toraise
awaren
ess
–4.1
8.2
10.1
10.2
Education,
incentivization
–
Lin et al. Implementation Science (2020) 15:90 Page 10 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Con
text
Interven
tionelem
ents
Firstauthor,
year
Target
illne
ss/
cond
ition
Cou
ntry
Lastmon
thof
data
collected
Setting
Target
drivers/factors
Nam
eSlog
anTarget
audien
ceHealth
care
providers
Health
care
consum
ers
BCT-
provider
BCT-
consum
erBehavioral
Chang
eWhe
el
Theory-
based
regarding
lower-cost
gene
ricalter-
natives
(aph
onecalland
quarterly
letters)
Vallès,2003
Not
specified
Spain
February
2000
Prim
arycare
setting
Know
ledg
e(includ
ing
awaren
ess)
––
chronic
disorders
patientswho
attend
edge
neral
practices
–Verbal
inform
ation
andhand
out
materialson
advantages
and
disadvantage
sof
gene
riceq
uivalents
andbrand-
namedrug
s
–4.1
8.2
9.2
Education
–
Non
-med
icaluseof
prescriptio
ndrug
s
Hasak
2018
Pain
managem
ent
(sho
rt-term
USA
Septem
ber,
2017
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
enabling
––
––
Inform
ation
brochu
re,
web
site
4.1
4.2
5.1
5.2
12.1
Education;
enablemen
t–
Lawrence,
2019
Pain
managem
ent
(sho
rt-term
USA
Janu
ary
2019
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
enabling
––
––
Inform
ation
brochu
re,
vide
o,Deterra
bags
4.1
4.2
5.1
5.2
12.1
12.5
Education;
enablemen
t;en
vironm
ental
restructuring;
–
Maugh
an,
2016
Pain
managem
ent
(sho
rt-term
USA
Octob
er2015
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
enabling
––
––
Inform
ation
brochu
re,
stud
yho
tline
4.1
4.2
5.1
5.2
12.1
12.5
Education;
enablemen
t;en
vironm
ental
restructuring;
–
Rose,2016
Pain
managem
ent
(sho
rt-term
Canada
April2015
Com
mun
ityKn
owledg
e(includ
ing
awaren
ess),
enabling
––
––
Inform
ation
brochu
re4.1
4.2
5.1
5.2
12.1
Education;
enablemen
t–
Spoth,
2008
Not
specified
USA
Decem
ber
2002
Scho
olsetting
Enhance
protective
factors
Family
dynamics
Streng
then
ing
Families
Prog
ram
(ISFP)
andLife
Skills
Training
(LST)
–Com
mun
ity-
stud
ents
–Universal
preven
tive
interven
tions
implem
ented
durin
gmiddle
scho
ol(stren
gthe
ning
families
prog
ram
and
–3.1
12.2
Education;
enablemen
t;en
vironm
ental
restructuring;
Social
developm
ent
model
Lin et al. Implementation Science (2020) 15:90 Page 11 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Con
text
Interven
tionelem
ents
Firstauthor,
year
Target
illne
ss/
cond
ition
Cou
ntry
Lastmon
thof
data
collected
Setting
Target
drivers/factors
Nam
eSlog
anTarget
audien
ceHealth
care
providers
Health
care
consum
ers
BCT-
provider
BCT-
consum
erBehavioral
Chang
eWhe
el
Theory-
based
lifeskills
training
)
Spoth,
2013
Not
specified
USA
Decem
ber
2011
Scho
olsetting
Enhance
protective
factors
Family
dynamics
Streng
then
ing
Families
Prog
ram
(ISFP)
andLife
Skills
Training
(LST)
–Com
mun
ity-
stud
ents
–Universal
preven
tive
interven
tions
implem
ented
durin
gmiddle
scho
ol(stren
gthe
ning
families
prog
ram
and
lifeskills
training
)
–3.1
12.2
Education;
enablemen
t;en
vironm
ental
restructuring;
Social
developm
ent
model
Electivecesarean
section
Eden
,2014
Expe
rienced
previous
cesarean
birth
USA
May
2007
Com
mun
ity&prim
ary
care
settings
Know
ledg
e(includ
ing
awaren
ess),
enabling
––
Com
mun
ity-
preg
nant
wom
enwith
oneprevious
cesarean
birth
–Eviden
ce-base
inform
ation
brochu
reor
facilitated
decision
analysis
–4.1
5.1
9.2
Education;
enablemen
t–
Fraser,1997
Expe
rienced
previous
cesarean
birth
Canada
Novem
ber
1994
Prim
arycare
setting
Know
ledg
e(includ
ing
awaren
ess),
Pred
ispo
sing
,en
ablingand
reinforcing
factors
––
Com
mun
ity-
preg
nant
wom
enwith
oneprevious
cesarean
birth
–Educational
pamph
let,
pren
atal
education,
and
peer
supp
ort
prog
ram
–3.3
4.1
5.1
Education;
enablemen
tThe
PREC
EDE-
PROCEED
mod
el
Hassani,2016
Not
specified
Iran
NR
Prim
arycare
setting
Know
ledg
e(includ
ing
awaren
ess
––
Com
mun
ity-
prim
iparou
spreg
nant
wom
en
–Instructional
sessions
inthe
form
ofspeech,g
roup
discussion
s,qu
estio
nsand
answ
ers,and
presen
tatio
ns
4.1
Education
Health
belief
mod
el
Mon
tgom
ery,
2007
Expe
rienced
previous
cesarean
birth
UK
Aug
ust
2006
Prim
arycare
setting
Know
ledg
e(includ
ing
awaren
ess),
enabling
––
Com
mun
ity-
preg
nant
wom
enwith
oneprevious
cesarean
birth
–Inform
ation
prog
ram
and
facilitated
decision
analysis
–4.1
5.1
9.2
9.2
Education;
enablemen
t–
Navaee,2015
Fear
ofchildbirth
Iran
NR
Prim
arycare
setting
Know
ledg
e(includ
ing
awaren
ess),
emotions
––
Com
mun
ity-
prim
iparou
spreg
nant
wom
en
–Education
throug
hrole
play
abou
tadvantages
and
disadvantage
s
–4.1
4.2
6.1
9.2
Education;
mod
eling
–
Lin et al. Implementation Science (2020) 15:90 Page 12 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Con
text
Interven
tionelem
ents
Firstauthor,
year
Target
illne
ss/
cond
ition
Cou
ntry
Lastmon
thof
data
collected
Setting
Target
drivers/factors
Nam
eSlog
anTarget
audien
ceHealth
care
providers
Health
care
consum
ers
BCT-
provider
BCT-
consum
erBehavioral
Chang
eWhe
el
Theory-
based
Sharifirad,
2013
Prim
iparou
spreg
nant
wom
en
Iran
NR
Prim
arycare
setting
Know
ledg
e(includ
ing
awaren
ess),
family
dynamics
––
Com
mun
ity—
spou
sesof
prim
iparou
spreg
nant
wom
en
–Educational
sessionabou
tmechanism
ofnaturalvaginal
andcesarean
deliveriesas
wellastheir
advantages
and
disadvantage
s.
–3.1
4.1
5.1
9.2
Education;
enablemen
t–
Shorten,2005
Expe
rienced
previous
cesarean
birth
Australia
May
2003
Prim
arycare
setting
Know
ledg
e(includ
ing
awaren
ess),
enabling
––
Com
mun
ity—
preg
nant
wom
enwith
oneprevious
cesarean
birth
–Inform
ation
materialsand
facilitated
decision
analysis
–4.1
5.1
9.2
Education;
enablemen
t–
Valiani,2014
Prim
iparou
spreg
nant
wom
en
Iran
NR
Prim
arycare
setting
Know
ledg
e(includ
ing
awaren
ess)
––
Com
mun
ity—
prim
iparou
spreg
nant
wom
en
–Childbirth
worksho
ps–
4.1
4.2
5.1
6.1
9.2
Education;
enablemen
t–
Implem
entatio
n
Firstauthor,
year
Interven
tion
adaptio
n/de
velopm
ent
Implem
entatio
nstrategy
Implem
enter(s)
Unitof
interven
tion
Dose/
intensity
Design
Costs
Duration
Datasources
Form
ativeor
process
evaluatio
nstud
ies
Note:NRno
trepo
rted
,RTIsrespira
tory
tractinfections,G
Pge
neralp
ractition
er,C
Selectiv
eaesarean
section
Lin et al. Implementation Science (2020) 15:90 Page 13 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Implem
entatio
n
Firstauthor,
year
Interven
tion
adaptio
n/de
velopm
ent
Implem
entatio
nstrategy
Implem
enter(s)
Unitof
interven
tion
Dose/
intensity
Design
Costs
Duration
Datasources
Form
ativeor
process
evaluatio
nstud
ies
Inapprop
riate
useof
antib
iotics
Belong
ia,
2001
Yes
Yes
Yes
Com
mun
ityPartially
repo
rted
NR
NR
4mon
ths
Med
icalrecords+self-
repo
rts,labtesting
Belong
ia,
2005
Yes
Yes
Yes
Com
mun
ityYes
Access
expired
NR
5years
Med
icalrecords
–
Bernier,
2014
NR
NR
Yes
Com
mun
ityNR
NR
NR
6mon
ths(ong
oing
)Med
icalrecords
–
Ceb
otaren
co,
2008
Yes
Yes
Yes
Com
mun
ityYes
Yes
NR
1year
Self-repo
rts
–
Finkelstein,
2001
Yes
Yes
Yes
Com
mun
ityNR
NR
NR
1year
Med
icalrecords
[30]
Finkelstein,
2008
Yes
Yes
Yes
Com
mun
ityPartially
repo
rted
NR
NR
3winters(Oct-M
arch)
Med
icalrecords
[30]
Form
oso,
2013
Yes
Yes
Yes
Com
mun
ityPartially
repo
rted
Access
expired
$60,800
4mon
ths
Med
icalrecords+self-
repo
rts
–
Fuertes,
2010
NR
Yes
Yes
Com
mun
ityNR
NR
NR
5mon
ths
Med
icalrecords
–
Gon
zales,
2004
Yes
Yes
Yes
Com
mun
ityAccess
expired
Access
expired
NR
1year
Med
icalrecords
[31]
Gon
zales,
2005
Yes
Yes
Yes
Com
mun
ityAccess
expired
Access
expired
$63,745
1year
Med
icalrecords
(see
Gon
zales,2004)
Gon
zales,
2008
Yes
Yes
Yes
Com
mun
ityYes
Yes
$196,710
4mon
ths
Med
icalrecords+self-
repo
rts
–
Hen
nessy,
2002
Yes
Yes
Yes
Com
mun
ityAccess
expired
Access
expired
NR
6mon
ths
Med
icalrecords+lab
testing+self-repo
rts
–
Kliemann,
2016
NA
Yes
Yes
Com
mun
ityNA
NA
NA
Ong
oing
Med
icalrecords
–
Lambe
rt,
2007
NR
Yes
Yes
Com
mun
ityNA
Partially
repo
rted
£25,000
2winters
Med
icalrecords+self-
repo
rts
–
Lee,2017
NR
NR
Yes
Individu
alNR
NR
NR
2weeks
Med
icalrecords
–
Maino
us,
2009
NR
Yes
Yes
Com
mun
ityPartially
repo
rted
NR
NR
9mon
ths
Med
icalrecords+self-
repo
rts
–
McN
ulty,
2010
NR
NR
Yes
Individu
alNR
Yes
NR
2mon
ths
Self-repo
rts
[32]
Perz,2002
Yes
Yes
Yes
Com
mun
ityPartially
repo
rted
Partially
repo
rted
NR
1year
Med
icalrecords
–
Sabu
ncu,
2009
NR
NR
Yes
Com
mun
ityNR
NR
NR
5years
Med
icalrecords
(see
Bernier,2014)
Lin et al. Implementation Science (2020) 15:90 Page 14 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Implem
entatio
n
Firstauthor,
year
Interven
tion
adaptio
n/de
velopm
ent
Implem
entatio
nstrategy
Implem
enter(s)
Unitof
interven
tion
Dose/
intensity
Design
Costs
Duration
Datasources
Form
ativeor
process
evaluatio
nstud
ies
Santa-Ana-
Tellez,2013
NA
Yes
Yes
Com
mun
ityNA
NA
NA
Ong
oing
Med
icalrecords
[33–36]
Santa-Ana-
Tellez,2015
NA
Yes
Yes
Com
mun
ityNA
NA
NA
Ong
oing
Med
icalrecords
(see
Santa-Ana-Tellez,
2013)
Taylor,2005
Yes
Yes
Yes
Com
mun
ityNR
NR
NR
1year
Med
icalrecords
–
Trep
ka,2001
Yes
Yes
Yes
Com
mun
ityPartially
repo
rted
NR
NR
4mon
ths
Self-repo
rts
–
Wirtz,2013
NA
Yes
Yes
Com
mun
ityNA
NA
NA
Ong
oing
Med
icalrecords
[33–36]
Wutzke,2007
Yes
Yes
Yes
Com
mun
ityPartially
repo
rted
Yes
NR
6years
Med
icalrecords+self-
repo
rts
–
Dem
andof
brandnamedrug
s
Beshears,
2013
NR
Yes
Yes
Individu
alPartially
repo
rted
NR
NR
1letter
Med
icalrecords
–
O'Malley,
2006
NR
Yes
Yes
Com
mun
ityNR
NR
NR
4years
Med
icalrecords
–
Sedjo,
2009
NR
Yes
Yes
Individu
alNR
NR
NR
1callandqu
arterly
mails
Med
icalrecords
–
Vallès,2003
NR
Yes
Yes
Individu
alNR
NR
NR
1session
Med
icalrecords
–
Non
-med
icaluseof
prescriptio
ndrug
s
Hasak
2018
Yes
Yes
Yes
Individu
alYes
Yes
NR
2tim
esSelf-repo
rts
[37]
Lawrence,
2019
Yes
Yes
Yes
Individu
alYes
Yes
Partially
repo
rted
($5–7pe
rbag)
1tim
eMed
icalrecords,self-
repo
rts
[38]
Maugh
an,
2016
NR
Yes
Yes
Individu
alYes
NR
NR
1tim
eSelf-repo
rts
Rose,2016
Yes
Yes
Yes
Individu
alYes
Yes
NR
1tim
eSelf-repo
rts
Spoth,
2008
NR
Yes
Yes
Individu
alNR
NR
NR
62-hsessions
+1family
follow-up+bo
osters
(coh
ort)
Self-repo
rts
[39–44]
Spoth,
2013
NR
Yes
Yes
Individu
alNR
NR
NR
62-hsessions
+1family
follow-up+bo
osters(co-
hortstud
y1:1993–2008;stud
y2:1998–2011)
Self-repo
rts
(see
Spoth,20080)
Electivecesarean
section
Eden
,2014
Yes
Yes
Yes
Individu
alNR
NR
NR
1session
Med
icalrecords+self-
repo
rts
–
Fraser,1997
NR
Yes
Yes
Individu
alNR
NR
NR
2sessions
Med
icalrecords+self-
repo
rts
–
Hassani,2016
NR
Yes
Yes
Individu
alNR
NR
NR
6sessions–50–60
min/session
Self-repo
rts
–
Mon
tgom
ery,
2007
Yes
Yes
Yes
Individu
alNR
NR
NR
10weeks
Med
icalrecords+self-
repo
rts
[45–49]
Navaee,2015
NR
Yes
Yes
Individu
alNR
NR
NR
1session–
90min
Self-repo
rts
–
Lin et al. Implementation Science (2020) 15:90 Page 15 of 35
Table
1Anoverview
oftheinclud
edstud
ies:interven
tionaims,compo
nents,andrepo
rting(Con
tinued)
Implem
entatio
n
Firstauthor,
year
Interven
tion
adaptio
n/de
velopm
ent
Implem
entatio
nstrategy
Implem
enter(s)
Unitof
interven
tion
Dose/
intensity
Design
Costs
Duration
Datasources
Form
ativeor
process
evaluatio
nstud
ies
Sharifirad,
2013
NR
Yes
Yes
Individu
alNR
NR
NR
1session–90min
Self-repo
rts
–
Shorten,2005
Yes
Yes
Yes
Individu
alNR
NR
NR
1session
Med
icalrecords+self-
repo
rts
[50]
Valiani,2014
NR
Yes
Yes
Individu
alNR
NR
NR
3–4h/week
Med
icalrecords
–
Lin et al. Implementation Science (2020) 15:90 Page 16 of 35
Table
2Summaryof
finding
sof
includ
edstud
iesmeasurin
gchange
sbe
havioralou
tcom
es
Firstauthor,year
Stud
yde
sign
Stud
ypo
pulatio
nStud
ysamplesize
Prim
aryou
tcom
e(s)
Belong
ia,2001
NCT
Long
itudinal
Physicians
andpu
blic
111facilities,664children
Pediatric
antib
iotic
prescribingin
child
care
facilities
Belong
ia,2005
CPP
Long
itudinal
Parentsandprim
arycare
clinicians
4115
prim
arycare
physicians
Chang
ein
annu
alantim
icrobial
prescribingrate
Bernier,2014
ITS
Long
itudinal
Fren
chcitizen
scoveredby
NHI
Not
repo
rted
Chang
ein
antim
icrobialprescribingrate
Ceb
otaren
co,2008
CPP
Cross-sectio
nalStud
entsandparents
~6302
peop
leNoantib
iotic
useforcold
andflu
Finkelstein,2001
RCT
Long
itudinal
Physicians
andparents
8815
children
Antibioticsdispen
sedpe
rpe
rson
-yearof
observationam
ongchildren
Finkelstein,2008
RCT
Long
itudinal
Physicians
andparents
223,135pe
rson
/years
Antibioticsdispen
sedpe
rpe
rson
-yearof
observationam
ongchildren
Form
oso,2013
NCT
Long
itudinal
Mod
enaandParm
a,Em
ilia-Ro
magna
region
1,150,000reside
nts
Antibiotic
prescriptio
nrate
Fuertes,2010
ITS
Long
itudinal
Popu
latio
nin
British
Colum
bia,Canada
Not
repo
rted
Antibiotic
utilizatio
nrate
Gon
zales,2004
NCT
Long
itudinal
Med
icareen
rollees
with
acuterespiratory
tract
infections
(ARIs)
4270
patient
visits
Decreased
antib
iotic
prescriptio
nrates
Gon
zales,2005
NCT
Long
itudinal
Childrenwith
pharyngitis
andadultswith
acute
bron
chitis
Baseline:10128patients
Stud
y:9586
patients
Decreased
antib
iotic
prescriptio
nrates
Gon
zales,2008
NCT
Long
itudinal
Mothe
rsof
youn
gchildrenandprim
arycare
physicians
922ho
useh
olds,1.38+
million
antib
iotic
prescriptio
nsNet
change
inantib
iotic
dispen
sed
per1000
person
s
Hen
nessy,2002
NCT
Long
itudinal
Med
icalprovidersandcommun
ity10,809
Antibiotic
utilizatio
n
Kliemann,2016
ITS
Long
itudinal
Reside
ntsof
SaoPaulo
41,262,199
Antibiotic
utilizatio
n
Lambe
rt,2007
CPP
Long
itudinal
Com
mun
ities
inNorth
Eastof
England
Not
repo
rted
Perpe
rson
,per
clinicvisit
Lee,2017
RCT
Cross-sectio
nalAdu
ltpatients
914patients
Antibiotic
prescriptio
ns
Maino
us,2009
QE(con
trolled
post-test)
Cross-sectio
nalLatin
oadults
500adults
Use
ofno
n-prescriptio
nantib
iotics
McN
ulty,2010
CPP
Cross-sectio
nalAdu
lt≥15
Pre=
(1999);p
ost(1830)
Antibiotic
usewith
outprofession
aladvice
Perz,2002
CPP
Long
itudinal
Children<15
464200
person
-years
Antibiotic
prescriptio
nrates
Sabu
ncu,2009
ITS
Long
itudinal
Fren
chcitizen
scoveredby
NHI
Not
repo
rted
Chang
ein
winterantib
iotic
prescribingrate
(Oct
toMar)
Santa-Ana-Tellez,2013
ITS
Long
itudinal
Popu
latio
nsin
MexicoandBrazil
Not
repo
rted
OTC
antib
ioticsconsum
ption
Santa-Ana-Tellez,2015
ITS
Long
itudinal
Popu
latio
nsin
MexicoandBrazil
Not
repo
rted
Season
alvariatio
nin
totalP
enicillin
use
Taylor,2005
RCT
Cross-sectio
nalParent/child
dyads
499children
Totaln
o.of
prescriptio
nsforantib
iotics
Trep
ka,2001
CPP
Cross-sectio
nalPh
ysicians
andpu
blic
365children
Expe
cted
anantib
iotic
fortheirchild
anddid
notreceiveon
eandbrou
ghttheirchild
toanothe
rph
ysicianbe
causethey
didno
treceive
anantib
iotic
Lin et al. Implementation Science (2020) 15:90 Page 17 of 35
Table
2Summaryof
finding
sof
includ
edstud
iesmeasurin
gchange
sbe
havioralou
tcom
es(Con
tinued)
Firstauthor,year
Stud
yde
sign
Stud
ypo
pulatio
nStud
ysamplesize
Prim
aryou
tcom
e(s)
Wirtz,2013
ITS
Long
itudinal
Chile,C
olom
bia,Vene
zuela,Brazil
Not
repo
rted
OTC
antib
ioticsconsum
ption
Wutzke,2007
ITS
Long
itudinal
Australiancommun
ityNot
repo
rted
Chang
ein
useof
antib
iotics
Beshears,2013
RCT
Cross-sectio
nalun
ionmem
bers
5498
adults
Con
versionrate
tolower-costalternatives
O'Malley,2006
QE
(matched
controlled)
Long
itudinal
Adu
ltpatients
9790064claims
Gen
ericdispen
sing
rate
Sedjo,2009
QE
Long
itudinal
Con
sumer-directed
health
care
enrolees
4026
peop
leCon
versionrate
tolower-costalternatives
Vallès,2003
RCT
Long
itudinal
Patientstaking
med
ications
forchronicdisorders
4620
patients
Evolutionof
thepe
rcen
tage
ofge
neric
prescribing
Hasak
2018
QE
Cross-sectio
nalPo
stop
erativepatients
258patients
Self-repo
rted
prop
erop
ioid
disposal
Lawrence,2019
RCT
Cross-sectio
nalParentsof
postop
erativepatients
202caregivers
Self-repo
rted
prop
erop
ioid
disposal
Maugh
an,2016
RCT
Cross-sectio
nalPo
stop
erativepatients
79patients
Self-repo
rted
prop
erop
ioid
disposal
Rose,2016
QE
Cross-sectio
nalPo
stop
erativepatients
87patients
Self-repo
rted
prop
erop
ioid
disposal
Spoth,2008
RCT
Long
itudinal
Late
adolescentsandyoun
gadults
2651
(study
2on
prescriptio
ndrug
s)
Self-repo
rted
lifetim
eprescriptio
ndrug
misuseoverall
Spoth,2013
RCT
Long
itudinal
Late
adolescentsandyoun
gadults
Stud
y1:667stud
ents;
Stud
y2:2127
stud
ents
Self-repo
rted
lifetim
eprescriptio
ndrug
misuseoverall
Eden
,2014
RCT
Cross-sectio
nalPreg
nant
wom
enwith
previous
cesarean
131wom
enMoD
(vaginal)
Fraser,1997
RCT
Cross-sectio
nalPreg
nant
wom
enwith
previous
cesarean
section
1275
wom
enMoD
(vaginal)
Hassani,2016
QE
Cross-sectio
nalPrim
iparou
swom
en60
wom
enMoD
(vaginal)
Mon
tgom
ery,2007
RCT
Cross-sectio
nalPreg
nant
wom
enwith
previous
cesarean
section
742wom
enMoD
(vaginal)
Navaee,2015
RCT
Cross-sectio
nalPrim
iparou
swom
en67
wom
enMoD
(vaginal)
Sharifirad,
2013
RCT
Cross-sectio
nalPreg
nant
wom
enandpartne
rs88
wom
enandpartne
rsMoD
(vaginal)
Shorten,2005
RCT
Cross-sectio
nalPreg
nant
wom
enwith
previous
cesarean
section
227wom
enMoD
(vaginal)
Valiani,2014
RCT
Cross-sectio
nalPreg
nant
wom
enandpartne
rs180wom
enandpartne
rsMoD
(vaginal)
Firstauthor,year
Chang
ein
interven
tiongrou
pChang
ein
controlg
roup
Effect
size
(95%
CI)
Pvalue
Effectivein
changing
public
behaviors
Qualityappraisal
Notes:C
Selectiv
ecesarean
section,
CPPcontrolledpre-
andpo
st-study
,NAno
tap
plicab
le,N
Rno
trepo
rted
,PDMOprescriptio
ndrug
misuseov
erall,NCT
nonran
domized
controlledtrial,OTC
over-the
-cou
nter
purcha
ses,MoD
mod
eof
delivery,RC
Trand
omized
controlledtrial,VD
norm
alvagina
ldelivery
Lin et al. Implementation Science (2020) 15:90 Page 18 of 35
Table
2Summaryof
finding
sof
includ
edstud
iesmeasurin
gchange
sbe
havioralou
tcom
es(Con
tinued)
Firstauthor,year
Chang
ein
interven
tiongrou
pChang
ein
controlg
roup
Effect
size
(95%
CI)
Pvalue
Effectivein
changing
public
behaviors
Qualityappraisal
Belong
ia,2001
Baseline:57.6%;
post-in
terven
tion:59.5%
ofinitialvisits
Baseline:60.1%;p
ost-interven
tion
61.5%
ofinitialvisits
NR
Baseline:P=0.56;
post-in
terven
tion:
P=0.66
No
Weak
Belong
ia,2005
−20.4%
−19.8%
−0.6%
NR
No
Mod
erate
Bernier,2014
NA
NA
−30%
(−36.3to
−23.8%)
P<0.001
Mixed
Strong
Ceb
otaren
co,2008
Stud
ents:a
33.7%
net
increase
inno
antib
iotic
use;Adu
lts:
a38.0%
netincrease
inno
use
Stud
ents−0.4%
;adu
lts+0.1%
Stud
ents3.694
(CI2.516
to5.423);
adults5.541
(CI4.559
to6.733)
P<0.0001
Yes
Weak
Finkelstein,2001
3to
<36
mon
ths
(−18.6%),
36to
<72
(−15.0%)
3to
<36
mon
ths(−
11.5%),
36to
<72
(−9.8%
)3to
<36
mon
nths
(−16%),
36to
<72
(−12%)
3to
<36
mon
ths
(P<0.001),
36to
<72
(P<0.001)
Yes
Strong
Finkelstein,2008
3to
<24
mon
ths
(−20.7%),
24to
<48
(−10.3),
48to
<72
(−2.5)
3to
<24
mon
ths(−
21.2),
24to
<48
(−14.5),
48to
<72
(−9.3)
3to
<24
mon
ths
(−0.5),
24to
<48
(−4.2),
48to
<72
(−6.7)
3to
<24
mon
ths
(P=0.69),
24to
<48
(P<0.01),
48to
<72
(P<0.0001)
Mixed
Strong
Form
oso,2013
−11.9
−7.4
−4.3%
(−7.1to
−1.5%
)P=0.008
Yes
Strong
Fuertes,2010
−5.8%
NA
NR
NR
No
Strong
Gon
zales,2004
−5%
−2%
NR
P=0.79
No
Mod
erate
Gon
zales,2005
Children:−4%
Adu
lts:−
24%
Children:−2%
atlocal
control;1%
atdistantcontrol;
Adu
lts:−
10%
atlocalcon
trol;
−6%
atdistantcontrol
NR
Children:P=0.18,
P=0.48
comparedwith
distantandlocalcon
trol;
Adu
lts:P
<0.002and
P=0.006,fordistantand
localcon
trol
Mixed
Mod
erate
Gon
zales,2008
––
−3.8%
inretail
pharmacyantib
iotic
dispen
sesand−8.8%
inmanaged
care
organizatio
n(M
CO)-
associated
dispen
ses
P=0.30
forpu
blic,
P=0.03
forMOCmem
bers
Mixed
Strong
Hen
nessy,2002
−31%
(P≤0.01)
−10%
(P≥0.05)
−21%
NR
Mixed
Mod
erate
Kliemann,2016
−1.616DID
NA
NR
P=0.002
Yes
Mod
erate
Lambe
rt,2007
Initial:−
31%
Expand
ed:−
35%
NA
NR
P<0.01
Mixed
Weak
Lin et al. Implementation Science (2020) 15:90 Page 19 of 35
Table
2Summaryof
finding
sof
includ
edstud
iesmeasurin
gchange
sbe
havioralou
tcom
es(Con
tinued)
Firstauthor,year
Chang
ein
interven
tiongrou
pChang
ein
controlg
roup
Effect
size
(95%
CI)
Pvalue
Effectivein
changing
public
behaviors
Qualityappraisal
Lee,2017
20.6%
17.7%
1.20
(0.83–1.73)
P=0.313
No
Weak
Maino
us,2009
1.3%
3.2%
NR
P=0.90
No
Weak
McN
ulty,2010
−0.5%
0%NR
NR
No
Weak
Perz,2002
Year
3:19%
Year
1:8%
11%
(8–14%
)P<0.001
Yes
Mod
erate
Sabu
ncu,2009
NA
NA
−26.5%
(−33.5to
−19.6%)
<0.0001
Yes
Strong
Santa-Ana-Tellez,2013
Brazil=−1.35;
Mexico=−1.17
NA
NR
BrazilP<0.01;
MexicoP<0.001
Mixed
Strong
Santa-Ana-Tellez,2015
Brazil=0.077;
Mexico=−0.359
NA
Brazil=0.077
(-1.142
to1.297);
Mexico=-0.359
(-0.613
to-0.105)
BrazilP>0.05;
MexicoP<0.01
Mixed
Strong
Taylor,2005
2.2±2.6
2.5±2.9
NR
P=0.23
No
Weak
Trep
ka,2001
Expe
cted
anantib
iotic
fortheir
child
anddidno
treceiveon
e:−5.1%
brou
ghttheirchild
toanothe
rph
ysician
becausethey
did
notreceivean
antib
iotic:−
2.9%
Expe
cted
anantib
iotic
fortheir
child
anddidno
treceiveon
e:3.2%
brou
ghttheirchild
toanothe
rph
ysicianbe
causethey
didno
treceivean
antib
iotic:1.6%
Expe
cted
anantib
iotic
fortheirchild
anddid
notreceiveon
e:−8.4%
(−13.9to
−2.8);
brou
ghttheirchild
toanothe
rph
ysician
becausethey
didno
treceivean
antib
iotic:
−4.5%
(−8.0to
–0.9),
they
didno
treceivean
antib
iotic:1.6%
Expe
cted
anantib
iotic
fortheirchild
anddid
notreceiveon
e:P=0.003brou
ghttheir
child
toanothe
rph
ysician
becausethey
didno
treceivean
antib
iotic:
P=0.02
Yes
Weak
Wirtz,2013
Colom
bia:−2.4D
ID;
Chile:−
3.8DID;
Vene
zuela:+5.39DID
andMexico:
−2.4D
ID
NA
Colom
bia:−1.00;
Chile:−
5.56;
Vene
zuela:op
posite
impact;M
exico:no
difference
Colom
bia:P=0.001;
Chile:P
<0.05
Mixed
Mod
erate
Wutzke,2007
−3.40%
NA
1.3–5.5
<0.05
Yes
Mod
erate
Beshears,2013
Unaffiliatedtestim
onial
grou
p11.3%;A
ffiliated
testim
onialg
roup
11.7%
12.20%
NR
NR(insign
ificant)
No
Mod
erate
O'Malley,2006
Mailing:
−4.94;
Advertising:
−0.13;
Gen
ericsampling:
−0.02;
physicianincentive:−0.33
Dou
blingco-paymen
tforbrand-name
drug
s:8.60
NR
P>0.05
No
Mod
erate
Sedjo,2009
0.30%
9.30%
29.82(4.41–201.93)
P<0.05
Yes
Mod
erate
Vallès,2003
5.10%
(1999–2000)
1.90%
(1999–2000)
NR
P<0.001
Yes
Strong
Hasak
2018
28(22)
14(11)
NR
P=0.02
Yes
Weak
Lin et al. Implementation Science (2020) 15:90 Page 20 of 35
Table
2Summaryof
finding
sof
includ
edstud
iesmeasurin
gchange
sbe
havioralou
tcom
es(Con
tinued)
Firstauthor,year
Chang
ein
interven
tiongrou
pChang
ein
controlg
roup
Effect
size
(95%
CI)
Pvalue
Effectivein
changing
public
behaviors
Qualityappraisal
Lawrence,2019
66(71.7)
50(56.2)
15.5(1.7to
29.3)
P=0.03.
Yes
Mod
erate
Maugh
an,2016
52%
(16/31)
30%
(8/27)
NR
P=0.11.
No
Weak
Rose,2016
12(27%
)2(5%)
22%
(5to
38)
P=0.005
Yes
Weak
Spoth,2008
11th
graders:3.9%
;12th
graders:7.7%
11th
graders:7.7%
;12th
graders:10.5%
NR
11th
graders:
P<0.01;
12th
graders:
P<0.1
Yes
Weak
Spoth,2013
Stud
y1-
5.4;
Stud
y2-
2.5
inage21,4.4
inage22,
6.3in
age25.
Stud
y1-
15.5;
Stud
y2-
6.5in
age21,8.9
inage22,9.4in
age25.
Stud
y1:65%;
Stud
y2:62%
inage21,51%
inage22,33%
inage25.
Stud
y1-P<0.01;
Stud
y2-
age21,
P=0.015,age22,
P=0.019,age25,
P=0.064
Yes
Weak
Eden
,2014
41%
37%
NR
P=0.724
No
Weak
Fraser,1997
53%
49%
1.1(1.0to
1.2)
P>0.05
No
Weak
Hassani,2016
30%
10%
NR
NR
Yes
Weak
Mon
tgom
ery,2007
Decisionanalysis
grou
p:37%;Info:29%
Usualcare:30%
Info
v.usualcare:
0.93
(0.61,1.41)
Decisionv.usual
care:1.42(0.94,2.14)
P>0.9
P=0.22
No
Strong
Navaee,2015
62.9%
43.8%
NR
P=0.117
No
Weak
Sharifirad,
2013
71.5%
50.0%
NR
P<0.05
Yes
Weak
Shorten,2005
VD:49.2%
CS:50.8%
NR
NR
No
Weak
Valiani,2014
Mothe
rsalon
einterven
tion=60%;
Cou
ples
=56.7%
26.7%
NR
P=0.017
Yes
Weak
Lin et al. Implementation Science (2020) 15:90 Page 21 of 35
Table
3Features
ofinclud
edinterven
tions
Firstauthor,year
Gov’t
supp
ort
Policy
Profession
altarget
Lettersto
doctors
Educationalm
eetin
gs(acade
micde
tailing
)Writtenmaterials
Clinicalpracticegu
idelines
Prescribingfeed
back
Physicianfinancialincentives
Belong
ia,2001
Yes
XX
XX
Belong
ia,2005
Yes
XX
XX
Bernier,2014
Yes
XX
XX
Ceb
otaren
co,2008
No
Finkelstein,
2001
Yes
XX
XX
Finkelstein,
2008
Yes
XX
XX
Form
oso,
2013
Yes
X
Fuertes,2010
Yes
Gon
zales,2004
Yes
XX
Gon
zales,2005
Yes
XX
Gon
zales,2008
Yes
X
Hen
nessy,2002
Yes
X
Kliemann,
2016
Yes
X
Lambe
rt,2007
Yes
Lee,2017
No
Maino
us,2009
No
McN
uty,2010
Yes
XX
X
Perz,2002
Yes
XX
X
Sabu
ncu,2009
Yes
XX
XX
Santa-Ana-Tellez,2013
Yes
X
Santa-Ana-Tellez,2015
Yes
X
Taylor,2005
Yes
Trep
ka,2001
Yes
XX
XX
Wirtz,2013
Yes
X
Wutzke,2007
Yes
XX
XX
Beshears,2013
Yes
O’Malley,2006
No
XX
Sedjo,
2009
No
X
Vallès,2003
No
Hasak,2018
No
Lawrence,2019
No
Maugh
an,2016
No
Rose,2016
No
Spoth,
2008
No
Lin et al. Implementation Science (2020) 15:90 Page 22 of 35
Table
3Features
ofinclud
edinterven
tions
(Con
tinued)
Firstauthor,year
Gov’t
supp
ort
Policy
Profession
altarget
Lettersto
doctors
Educationalm
eetin
gs(acade
micde
tailing
)Writtenmaterials
Clinicalpracticegu
idelines
Prescribingfeed
back
Physicianfinancialincentives
Spoth,
2013
No
Eden
,2014
No
Fraser,1997
Yes
Hassani,2016
No
Mon
tgom
ery,2007
No
Navaee,2015
No
Sharifirad,
2013
No
Shorten,
2005
No
Valiani,2014
No
Firstauthor,year
Publictarget
Multilingu
al
TVVide
oNew
sletters/
mails
Poster
Radio
Press
conferen
ces
New
spapersor
advertisem
ents
(includ
ingbill
boards,b
ussign
s)
Web
sites
Inform
ationalw
ritten
materials(includ
ing
pamph
lets/brochures)
Education
meetin
gsMascots
Scho
olprog
ram
(includ
ingpe
er-
education)
Family
and
frien
ds
Decision-
aid/
enabling
tools
Other
mass
med
iacampaign
activities
NRno
trepo
rted
Lin et al. Implementation Science (2020) 15:90 Page 23 of 35
Table
3Features
ofinclud
edinterven
tions
(Con
tinued)
Firstauthor,year
Publictarget
Multilingu
al
TVVide
oNew
sletters/
mails
Poster
Radio
Press
conferen
ces
New
spapersor
advertisem
ents
(includ
ingbill
boards,b
ussign
s)
Web
sites
Inform
ationalw
ritten
materials(includ
ing
pamph
lets/brochures)
Education
meetin
gsMascots
Scho
olprog
ram
(includ
ingpe
er-
education)
Family
and
frien
ds
Decision-
aid/
enabling
tools
Other
mass
med
iacampaign
activities
Belong
ia,2001
XX
XNR
Belong
ia,2005
XX
XX
XX
XX
XX
XYes
Bernier,2014
XX
XX
XX
XX
XX
NR
Ceb
otaren
co,2008
XX
XX
XX
XX
NR
Finkelstein,
2001
XX
XNR
Finkelstein,
2008
XX
XX
XX
XNR
Form
oso,
2013
XX
XX
XX
NR
Fuertes,2010
XX
NR
Gon
zales,2004
XX
XX
XYes
Gon
zales,2005
XX
XX
XYes
Gon
zales,2008
XX
XX
XX
Yes
Hen
nessy,2002
XX
XX
NR
Kliemann,
2016
NA
Lambe
rt,2007
XX
XX
XX
XNR
Lee,2017
XX
Yes
Maino
us,2009
XX
XYes
McN
uty,2010
XX
XNR
Perz,2002
XX
XX
XX
XNR
Sabu
ncu,
2009
XX
XX
XX
XX
XX
NR
Santa-Ana-Tellez,2013
NA
Santa-Ana-Tellez,2015
NA
Taylor,2005
XX
NR
Trep
ka,2001
XX
XX
NR
Wirtz,2013
NA
Wutzke,2007
XX
XX
XX
XX
XNR
Beshears,2013
XNR
O’Malley,2006
XX
XX
XX
NR
Sedjo,
2009
XX
NR
Vallès,2003
XX
NR
Hasak,2018
XX
NR
Lawrence,2019
XX
XNR
Maugh
an,2016
XX
NR
Lin et al. Implementation Science (2020) 15:90 Page 24 of 35
Table
3Features
ofinclud
edinterven
tions
(Con
tinued)
Firstauthor,year
Publictarget
Multilingu
al
TVVide
oNew
sletters/
mails
Poster
Radio
Press
conferen
ces
New
spapersor
advertisem
ents
(includ
ingbill
boards,b
ussign
s)
Web
sites
Inform
ationalw
ritten
materials(includ
ing
pamph
lets/brochures)
Education
meetin
gsMascots
Scho
olprog
ram
(includ
ingpe
er-
education)
Family
and
frien
ds
Decision-
aid/
enabling
tools
Other
mass
med
iacampaign
activities
Rose,2016
XNR
Spoth,
2008
XX
XNR
Spoth,
2013
XX
XNR
Eden
,2014
XX
Yes
Fraser,1997
XX
XYes
Hassani,2016
XNR
Mon
tgom
ery,2007
XX
NR
Navaee,2015
XX
XNR
Sharifirad,
2013
XX
XNR
Shorten,
2005
XX
NR
Valiani,2014
XX
XNR
Lin et al. Implementation Science (2020) 15:90 Page 25 of 35
how these underlying theories were used in the develop-ment and evaluation of the interventions.
Interventions targeting health care consumersTable 4 reports the individual BCTs identified within thedescriptions as active ingredients of the selected inter-ventions targeting health care consumers. Of the 93BCTs, the most frequently used active ingredients in theselected interventions targeting health care consumerswere BCTs: 4.1-Instruction on how to perform the behav-ior (n = 34), 4.2 Information about antecedents (n = 22),5.1 Information about health consequences (n = 22),followed by 12.5 Adding objects to the environment (n =12), 8.2 Behavior substitution (n=11), and 12.1 Restruc-turing the physical environment (n = 8). Most studiesemployed education interventions aiming to improvepublic knowledge (including awareness or correctingmisconceptions). Mass media campaigns were widelyused to reduce antibiotic misuse [54–56, 60, 63–68] anddemand for brand-name drugs [69], all in HIC. The ef-fectiveness of such behavioral change interventions wasmixed. Decision aids to assist pregnant women makingdecisions about mode of delivery were tested in threedifferent trials in Australia, UK, and USA; all reported tobe ineffective [52, 70, 71]. Taylor et al. [72], Lee et al.[73], and Vallès et al. [51] trialed patient-based educa-tion interventions in primary care settings to reduceantibiotic use or to substitute generic for brand-namedrugs; only Vallès et al.’s [51] intervention found a posi-tive impact on behavior change. Mainous et al. andMcNulty et al. assessed community-wide education in-terventions in the USA and UK on their effectiveness inimproving public antibiotic use and found the provisionof educational messages itself was insufficient to over-come the influence of past attitudes and behaviors [57,66]. Formal and informal social support networks can beleveraged to influence individuals’ behaviors through im-proving doctor-patient communication [58–60, 64, 72,74] or by actively engaging family members in theprocess [39, 40, 75]. Four interventions aimed to encour-age disposal of leftover opioids among postoperative pa-tients by employing a combination BCWs of education,enablement, and environment restructuring (BCTs: 4.1,4.2, 5.1, 5.2, 8.2, 12.1, 12.5), which reported positive im-pact [76–79]. Two longitudinal RCTs on school-baseduniversal preventive interventions in the USA that aimedto strengthen families and build life skills were intro-duced to middle schoolers [39, 40] and reported a lastingimpact on preventing non-medical use of prescriptiondrugs into adulthood. Structural environmental condi-tions regarding access to healthcare services and medi-cines, and promotive and restrictive policies—or the lackthereof—can be pathways to shaping individual behav-iors. Two trend analyses assessing the effectiveness of
French public education campaigns [63, 68] reported asignificant reduction in antibiotic consumption rates;however, trials on community-wide public campaignswith academic detailing for practitioners did not demon-strate comparable levels of improvement in public anti-biotic use. Belongia et al. and Fiskelstein et al. foundlittle or no evidence—attributable to multi-year interven-tions in Wisconsin and Massachusetts—on reductions inantibiotic prescribing in the intervention areas, despiteimproved public knowledge [54, 59, 74]. Gonzales et al.found that the state-wide “Get Smart Colorado” cam-paign did not improve prescription rates, but might beassociated with a reduction in antibiotic use in the com-munity through decreases in office visit rates amongchildren [56, 64]. Four studies evaluated the effectivenessof the restrictions on OCT purchases on antibiotic con-sumption in five Latin American countries with mixedresults [33–35, 80].
Interventions also targeting health care providersTable 5 reports the individual BCTs identified within thedescriptions as active ingredients of the selected inter-ventions targeting health care providers. The mostfrequently used BCTs targeting health care providerswere similar with those targeting consumers, with smalldifferences in the ranking: BCTs: 4.1 Instruction on howto perform the behavior (n = 15), 4.2 Information aboutantecedents (n = 13), 12.5 Adding objects to the environ-ment (n = 10), followed by 5.1 Information about healthconsequences (n = 9), 8.2 Behavior substitution (n = 9),and 12.1 Restructuring the physical environment (n = 4).We noticed that, except for programs aiming to containinappropriate use of antibiotics, other interventions hadlimited engagement between consumers and providers.
DiscussionSummary of findingsUsing the Behavioral Change Wheel (BCW) domains toidentify the theoretical concepts underlying interven-tions and the behavior change technique taxonomy v1(BCTTv1) to identify the active ingredients of interven-tions, we found that the domain of education was themost commonly targeted by a majority of interventionswith primary focus on the provision of information onBCTs 4.1 how to perform the behavior and 4.2 about an-tecedents and 5.1 the associated health consequences. Aplethora of evidence supports the view that human be-haviors should be understood in their social ecologicalcontext, as products of intertwined influences at the per-sonal, communal, societal, and structural levels [81–83].Studies show that improving knowledge and awarenessdoes not equate with appropriate behavior change, aslack of information is often not the only barrier to chan-ging behavior [64, 66, 84–86]. The effects of education
Lin et al. Implementation Science (2020) 15:90 Page 26 of 35
interventions have been mixed—most likely due to het-erogeneity in context, population served, and interven-tion design and measures. Cabral et al. examined howcommunication affects prescription decisions for acuteillnesses and demonstrated a clear miscommunicationwith cross-purposes between health care consumers andproviders, as patients and/or caregivers focused on their
concerns and information needs, which clinicians inter-preted as an expectation for antibiotics [87]. This reviewsupports the use of multifaceted (complex) interventionsthat incorporate BCTs related to provision of informa-tion (BCTs 4.1, 4.2, or 5.1) and, as an alternative to anti-biotics, prescription pads with clear explanations onsymptoms, and appropriate treatment options (BCT 8.2),
Fig. 2 Frequency distribution of behavior change techniques (BCTs) coded for 43 interventions
Lin et al. Implementation Science (2020) 15:90 Page 27 of 35
as education alone is not sufficient to be effective. Inter-ventions consisting of health education messages (e.g.,BCTs 4.1, 4.2, 5.1), recommended behavior alternatives(BCT 8.2), and a supporting environment that incentiv-izes or encourages the adoption of a new behavior (e.g.,BCTs 10.1, 10.2, 12.1, 12.5) are more likely to besuccessful. Other types of utilized behavior change tech-niques often aimed to encourage alternative behaviorsand improve the physical environments via regulationsor mass media.The continuing tendency in research reporting has
been to stress the effectiveness of interventions ratherthan the process of identifying and developing key com-ponents and the parameters within which they operate.
There is a lack of detail on how the intervention compo-nents were selected, designed, and the process of imple-menting them, with limited descriptions provided on the“contexts” and “mechanisms” that determine the effect-iveness of interventions. Few studies provided sufficientdetails on intervention development, dose/intensity, anddesign; some provided links to project materials that hadexpired [54–56, 60]. The majority of the selected inter-ventions did not describe the pilot or process data forimplementation, nor did they discuss the disseminationof findings and pathways to impact. Even after identify-ing active ingredients of interventions using BCTTv1,without a complete “recipe,” one cannot recreate suc-cesses in other contexts. Just like there are agreed-upon
Table 4 Behavior change techniques and number of interventions targeting health care consumers and included specific behaviorchange techniques, behavior change techniques taxonomy volume 1 (BCTTv1) hierarchical clusters, and intervention contentexamples
BCT BCTTv1hierarchicalclusters
Examples extracted from descriptions of the interventions Frequency
3.1 Social support(unspecified)
3. Social support Educational programs for husbands of pregnant women that aimed to provide socialsupport of husbands, which consequently reduces the rate of elective cesarean section.
3
3.3 Social support(emotional)
3. Social support A resource person will provide peer influence during decision making process about modeof delivery
1
4.1 Instruction on how toperform the behavior
4. Shapingknowledge
Information about when antibiotics are and are not needed (e.g., rarely for bronchitis, notfor colds).
34
4.2 Information aboutAntecedents
4. Shapingknowledge
Information about bacterial and viral infections 22
5.1 Information abouthealth consequences
5. Naturalconsequences
Information about bacterial resistance or side effects of antibiotic use 22
5.2 Salience ofconsequences
5. Naturalconsequences
Emphasis on the consequences inappropriate use of antibiotics (e.g., antimicrobialresistance or side effects of antibiotic use)
6
6.1 Demonstration of thebehavior
6. Comparison ofbehavior
Role play education to reduce the fear of childbirth 3
8.2 Behavior substitution 8. Repetition andsubstitution
Alternative remedies instead of antibiotics for colds 11
9.1 Credible source 9. Comparison ofoutcomes
Endorsement by CDC was designed to increase the credibility of key messages. 4
9.2 Pros and cons 9. Comparison ofoutcomes
Information about the differences between generic and brand-name drugs in terms of ad-vantages (high-quality bioequivalent formulations, health professionals’ preferences, avoid-ance of confusions) and disadvantages (popularity, fidelity to branded products)
8
10.1 Material incentive(behavior)
10. Reward andthreat
Switching to a lower-cost generic medication is cost-saving 3
10.2 Material reward(behavior)
10. Reward andthreat
Associated cost savings to the recipient from switching to each of these alternatives 3
12.1 Restructuring thephysical environment
12. Antecedents Restriction on sale of antibiotics without prescription 8
12.2 Restructuring thesocial environment
12. Antecedents Interventions focused on empirically supported family risk and protective factors, such asparental nurturing, child management skills, improved parent–adolescent communicationskills and adolescent prosocial skill development (e.g., managing conflict and stress,handling peer pressure, developing positive friendships)
3
12.5 Adding objects to theenvironment
12. Antecedents Mass media strategies were undertaken including advertising using billboards, television,radio, and magazines.
12
15 8 143
Lin et al. Implementation Science (2020) 15:90 Page 28 of 35
elements that constitute a rigorous and comprehensivereporting of evaluation studies, publications on behav-ioral change interventions should systematically cover astandardized list of intervention elements from the de-velopment, adaption and refinement, feasibility andpilot-testing, implementation, evaluation, and reportingof BCTs. The CONSORT-SPI team [88] has developedguidance and checklists for the reporting of BCT trials;however, the required details on the reporting are stillprimarily focused on evaluation study designs (e.g.,process of randomization) rather than BCT development
and implementation. From implementation researchperspective and following the Medical Research Council(MRC) guidance on developing and evaluating complexinterventions, reporting of BCT development and imple-mentation should include descriptions on the context,target behavior determinants, theories and rationale(theory of change), intervention design features, adap-tion/development process, implementation strategy (e.g.,implementor, dose/intensity), modifications made be-tween the feasibility and effective assessment phases, andevaluation outcomes. The lack of detailed reporting
Table 5 Behavior change techniques and number of interventions targeting health care providers that included specific behaviorchange techniques, behavior change techniques taxonomy volume 1 (BCTTv1) hierarchical clusters, and intervention contentexamples
BCT BCTTv1hierarchicalclusters
Examples extracted from descriptions of the interventions Frequency
1.3 Goal setting (outcome) 1. Goals andplanning
Provision of individual prescribing profiles depicting: (1) the proportion of adult bronchitispatients receiving antibiotic treatment (target 10 percent or less); (2) the proportion of theseantibiotics belonging to a first-line group (erythromycin, doxycycline, tetracycline) (target70% or more); and (3) the proportion of these antibiotics that are ineffective against provenbacterial causes of uncomplicated acute bronchitis (target 0%).
1
2.2 Feedback on behavior 2. Feedback andmonitoring
Prescribing feedback, clinical audit with feedback 3
3.1 Social support(unspecified)
3. Social support Interventions that inform best practice prescribing and that support health professionalsmanage patient expectations
1
3.2 Social support(practical)
3. Social support This intervention will (1) provide a range of patient education materials to physician officeswithout charge, (2) provide ongoing information about antibiotic-use rates and resistancein the community, (3) provide feedback about prescribing by practice, and (4) serve as ageneral resource on issues of antibiotic prescribing and resistance
3
4.1 Instruction on how toperform the behavior
4. Shapingknowledge
Academic detailing to promote appropriate antibiotic use; practice guidelines whichincluded with the patient profiles for adults with bronchitis and children with pharyngitiswere compatible with those produced by the Centers for Disease Control and Prevention(CDC)
15
4.2 Information aboutAntecedents
4. Shapingknowledge
Clinical practice guidelines for common respiratory illnesses 13
5.1 Information abouthealth consequences
5. Naturalconsequences
A reference card providing easy-to-read facts about symptoms and treatments for ARIs 9
5.2 Salience ofconsequences
5. Naturalconsequences
Emphasis on AMR 2
8.2 Behavior substitution 8. Repetition andsubstitution
Prescription pads with explanations on symptoms and appropriate treatment options (tobe given to patients instead of antibiotic prescriptions)
9
9.1 Credible source 9. Comparison ofoutcomes
Endorsement by CDC was designed to increase the credibility of key messages. 1
10.1 Material incentive(behavior)
10. Reward andthreat
An intervention intends to reward physicians for reducing pharmacy costs for their patients,one component of which was to increase their prescribing of generic drugs
1
10.2 Material reward(behavior)
10. Reward andthreat
Reward given to physicians for reducing pharmacy costs for their patients, one componentof which was to increase their prescribing of generic drugs
1
12.1 Restructuring thephysical environment
12. Antecedents Waiting room materials (CDC posters and patient reference cards) 4
12.5 Adding objects to theenvironment
12. Antecedents Mass media strategies were undertaken including advertising using billboards, television,radio and magazines.
10
14.2 Punishment 14. Scheduledconsequences
Regulations that require prescriptions for antibiotics to be retained and registered inpharmacies and imposes fines to the owners of the pharmacies for non-compliance.
2
15 10 75
Lin et al. Implementation Science (2020) 15:90 Page 29 of 35
among included intervention studies on evidence-baseddevelopment and implementation processes underminesthe generalizability of study findings, makes cross-intervention comparisons difficult, and complicatesfuture adaption and replication efforts.This systematic literature review is the first on the
effectiveness of public-targeted behavioral change inter-ventions to reduce inappropriate use of medical inter-ventions. It identified a serious lack of formative data,which means that interventions to change public use ofmedical interventions are often designed on the basis of“best guesses” of what needs to change, without anevidence base or explicit rationale for the selection of aspecific intervention strategy. There is an urgent need toadopt a multidisciplinary, systematic approach to devel-oping evidence-based behavioral change interventions toreduce inappropriate medical use and to develop an op-erational mechanism for knowledge translation andscale-up within and across different countries. We foundlimited evidence [39, 63] on evaluating the impact ofprevious or ongoing education interventions on inappro-priate use in terms of long-term impact, scalability, andreplicability. The root causes of why certain interven-tions were unsuccessful are not systematically exploredor reported, yet reporting “negative results” is likely ascritical as reporting “active ingredients” and positivefindings for the development and sustainability of imple-mentation science.
Relation to other studiesLike most stewardship programs, quaternary preven-tion—a relatively new category of medical preventionfirst raised in 1986 by Dr. Marc Jamoulle, a family phys-ician, to addressing concerns around the protection ofpeople and patients from being harmed by over-diagnosis or overtreatment—tends to focus mostly onhealth care providers while placing less attention onconsumers [5, 89–91]. The definition of quaternary pre-vention was later expanded by Brodersen et al. in 2014to include patients and medical interventions as an ac-tion taken to protect individuals (persons/patients) frommedical interventions that are likely to cause more harmthan good [92, 93]. The expanded definition recognizesthe contemporary reality in medicine in which peoplemay suffer harm from medical interventions throughouttheir entire lifetime—from conception to adulthood, intimes of good health, as well as when experiencing self-limited disease, chronic conditions, or terminal disease.Therefore, quaternary prevention should includepreventing all types of harm associated with medical in-terventions [92, 93]. From this perspective, quaternaryprevention is aligned with the aims of the behavioralchange interventions and techniques identified in our re-view and should be considered alongside the other four
classical levels of preventive activities, i.e., primordial(e.g., laws that restrict over-the-counter purchases ofantibiotics), primary (e.g., prescription drugs disposalprograms), and secondary and tertiary preventions (e.g.,interventions that reduce fear of childbirth or convertdemand of brand-name drugs to generic drugs).The use of medicine or medical procedures is a highly
complex set of behaviors involving multiple actions, in-cluding the self-diagnostic process, assessing benefit/risk,decision-making around healthcare seeking and treat-ment choice, and review of treatment—each performedat different time points across the care continuum [94,95]. It involves interactions with various stakeholders(i.e., family members and providers) and is often shapedmore by individual and contextual factors than by a clin-ical diagnosis [94, 95]. Therefore, developers and imple-menters of behavioral change interventions should beclear as to whose and which behaviors are being targetedfor change and how—namely, who needs to do what dif-ferently, how, to whom, where, when, and for how long.A set of precisely specified behaviors would allow foreasier measurement and therefore would offer a baselineand metric for evaluating the success of an intervention.In order to develop effective behavioral change inter-
ventions, we first need to explain why people behave incertain ways, yet a more in-depth look at people’s life-world is lacking from every reviewed article. As the dualprocessing theory (DPT) posits, human behavior isguided by two types of processing mechanisms: the im-plicit, intuitive system 1 and the explicit, rational system2 [96]. Behavioral economists elaborate that, due to lim-ited self-control, rationality and social preferences, actualdecisions are less rational and stable than traditionalnormative theory suggests [96]. They are usually madewith a range of biases resulting from the way peoplethink and feel, rather than with rationality or fullinformation. However, most of the included interven-tions—appealing to system 2 processing—attempted toinfluence behaviors via improved knowledge and atti-tudes; disappointingly, many trials indicated that this didnot automatically lead to preferred behaviors [54, 59, 72,74]. To complicate things further, Zinn argues that be-tween rationality and irrationality, there is a third, “in-between” dimension that includes trust, intuition, andemotion, which is an important aspect of decision-making when people deal with risk and uncertainty,especially in anticipation of the possible undesired out-comes of decisions [97]. This may explain why threeRCTs on decision aids (system 1) to address individualemotions (system 2) had no real impact on choice of va-ginal birth [52, 70]. On the other hand, in addition toeducation programs, financial incentives (changes in co-payment), free medicine, advertisements (print media),and health policies have been experimented with as
Lin et al. Implementation Science (2020) 15:90 Page 30 of 35
behavioral change interventions to influence healthcareconsumers’ choice of medicine—in particular, to pro-mote uptake of generic medicines—though they havedemonstrated inconsistent results [98, 99].The most promising measure was an intervention de-
livered face-to-face, where consumers were told thatthey had the option of switching back to brand-namedrugs anytime [51, 100, 101]; hence, an intervention thatleverages human behavioral mechanisms may be moreeffective and cost-effective in optimizing decisionmaking than repeated, expensive education campaigns.In response to the recent opioid epidemic across theglobe, promising prevention programs aimed not only toimprove the knowledge and awareness of the risk ofnonmedical use of prescription drugs among at risk indi-viduals, but also to empower healthcare consumers byproviding skills or tools that enable them to take actionprior to the occurrence of misuse and/or before thedevelopment of poor habits [39, 40, 76–79]. These inter-ventions further improved the socio-ecological sur-roundings of the target audience by involving familymembers and restructuring their social or physical envi-ronments [39, 40, 76–79].Our review showed only 19% of BCTs have been
utilized by included interventions (i.e., 81% of BCTsunexplored), with great variation between different typesof misuse—most were limited to education. Futurestudies should explore other BCTs. A wide range ofdisciplines engaging in social and behavioral sciences,such as psychology, sociology, anthropology, communi-cation, and marketing, can provide theories, models, andmethods for a more comprehensive and coherent ap-proach to understanding or even modifying contextual,organizational and interpersonal determinants of behav-ior. In terms of sustainability of the interventions them-selves, other than a few longitudinal studies [39, 40], wedo not know how long the reported effect of behavioralchange will sustain. Few studies incorporated economicevaluations, and therefore, it was not possible to deter-mine the returns on investment (ROI) for these includedinterventions. Future intervention studies should con-sider the aspects of RE-AIM (Reach EffectivenessAdoption Implementation Maintenance) framework orfollow the MRC Guidelines on Developing and Evaluat-ing Complex Interventions during the planning stage toenhance the impact of interventions and the reporting ofthem.Development of a behavioral change intervention has
to start with a realist, comprehensive understanding ofthe complex environment that shapes individual and col-lective behaviors. The etiology of inappropriate use ofmedical interventions should be studied and addressedwithin the context of its biological, psychosocial, behav-ioral, and environmental factors and the interactions
between them. In early 2000, Sallies et al. developed abehavioral epidemiology framework, which specified asystematic sequence of studies on health-related behav-iors leading to evidence-based interventions directed atpopulations in the following five phases: (1) establishlinks between behaviors and health, (2) develop mea-sures of the behavior, (3) identify influences on the be-havior, (4) evaluate interventions to change the behavior,and (5) translate research into practice [21, 83, 102]. In2011, Michie and colleagues mapped out various path-ways to influencing behavioral change and recom-mended that interventions seeking to change behaviorshould be designed on the basis of a thorough “behav-ioral diagnosis” of why behaviors are the way they areand what needs to change in order to bring about thedesired behavior [21]. Conducting such diagnosis shouldbe facilitated by the use of behavioral theory. Not untilrecent years did researchers systematically report effortsin the identification of the root causes of operationalbarriers and facilitators in designing, implementing, andevaluating interventions. For instance, in 2018 and 2019,Langdridge et al. have attempted to decipher the inter-vention elements and visual imagery used in public anti-microbial stewardship [23, 103].Consistent with the findings from recent reviews by
Cochrane and the Department of Health and Social Careand Public Health in England [5, 104, 105], our reviewfound that few interventions employed behavior changetheories or techniques. Behavioral determinants and so-cial influences are often not given sufficient consider-ation in the design and evaluations of interventions. Toinform the design of effective, context-specific behaviorchange interventions, one must first define the problemin both behavioral terms and in its current context andadopt a theory-driven, systematic approach to inter-vention design. This points to another critical know-ledge gap identified by this review in implementationscience, namely early studies that take place prior tothe implementation of behavioral change interventions.Following the Medical Research Council (MRC) guide-lines on developing and evaluating complex interven-tions [106], as presented in Table 1, we find there islittle reporting on the feasibility, pilot, or process datathat generates the needed contextual information andevidence base for acceptance, adaption, and uptake.Limited detail has been made available on the develop-ment of the included interventions regarding how keydecisions were made, including feasibility and com-pliance. Future research on pilot and/or feasibility studiesthat aim to strengthen large-scale behavioral changeintervention design can span the continuum of imple-mentation science research from idea generation tointervention development, implementation, evaluation,and scale-up.
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LimitationsThis systematic review is subject to important limita-tions as we worked with interventions that are complex,heterogeneous, non-standardised, and targeted differenttypes of inappropriate use of medical interventions andusers. The diversity in the design and outcome measuresof the included interventions prevents us from perform-ing a meta-analysis. We demonstrated great variability inthe effect size observed within each behavioral changeintervention considered. We cannot make a conclusionthat certain types of behavioral change interventionmight be more effective than any other type of designdue to the limitations of the literature relating to thelack of evidence-based development process and evalu-ation design. Behavioral data that were gathered via sur-vey instruments were by nature self-reported fromhealth care consumers who may have been reluctant toreport practices that could be considered inappropriateor may have been subject to recall bias. Often there weremore than one “active ingredient” identified for each in-cluded intervention, yet retrospective coding and thestudy design did not allow us to pinpoint which compo-nent was more effective. Further, some studies containedbundles of interventions while others contained similar,yet different interventions implemented in multiplecountries; therefore, the results of this review may havebeen clouded by unconsidered/unreported interventioncomponents in the studies included. The studies in thisreview were spread across a wide range of settings andpopulations, so general conclusions should be drawnwith caution. Publication bias may be a critical problemsince it implies that most interventions have a positiveeffect. We expect most interventions aimed at individ-uals to be much more complex in reality; however, thisreview was not able to capture how and why “active in-gredients” were selected, implemented, or functioned inthe respective socioeconomical, cultural, and healthcaresettings. Future work should focus on addressing thelimitations and uncertainties surrounding existing be-havioral change interventions.
ConclusionSystematically assessing the evidence across behavioralchange interventions allows for the identification of the“active ingredients” of effective interventions thatimprove healthcare consumers’ use of medical interven-tions, as well as the identification of those with ineffect-ive or uncertain outcomes. Although opportunities forbehavioral change interventions are becoming morecommonly recognized, multifaceted (complex) interven-tions are still new, scarce, limited to high-income coun-tries, and, as is evident from our findings, highlyheterogeneous. Public-targeted behavioral change inter-ventions in low- and middle-income countries (LMICs)
were exclusively limited to primary care settings. Inter-ventions that consist of health education messages,recommended behavior alternatives, and a supportingenvironment that incentivizes or encourages the adop-tion of a new behavior are more likely to be successful.Future research should also seek to unpack the distinc-tions between various audience segments, the influenceof the social ecological context, and the utility of the un-explored 81% of behavioral change techniques (BCTs). Itis critical to adhere to a rigorous framework that guidesthe development, implementation, evaluation, andreporting of evidence-based interventions, so that gener-ated evidence can be documented, disseminated,compared, and utilized for further research. The lack ofreporting on evidence-based development and imple-mentation processes makes cross-intervention compari-sons and replication difficult. Our review furtheridentified a need for standardized reporting of interven-tion development, adaptation, and implementation tomaximize generalisability and replicability.
Supplementary informationSupplementary information accompanies this paper at https://doi.org/10.1186/s13012-020-01018-7.
Additional file 1:. Search Strategy
Additional file 2:. Inclusion and Exclusion Criteria
Additional file 3:. List of included studies
Additional file 4:. Summary of quality assessment of included studies
AbbreviationsABR: Antibiotic resistance; AMR: Antimicrobial resistance; BCT: Behaviorchange technique; BCTT: Behavior change technique taxonomy;BCW: Behavioral Change Wheel; CPP: Controlled pre- and post-study;CRT: Cluster randomized control trial; CS: Elective cesarean section; DPT: Dualprocessing theory; EPHPP: Effective Public Health Practice Project’s QualityAssessment Tool for Quantitative Studies; HIC: High-income country;ITS: Interrupted time series; LMIC: Low- and middle-income country;MoD: Mode of delivery; MRC: Medical research council; NA: Not applicable;NR: Not reported; NCT: Nonrandomized controlled trial; OTC: Over-the-counter purchases; PDM: Prescription drug misuse; PRISMA : PreferredReporting Items for Systematic Reviews and Meta-Analyses; RCT: Randomizedcontrol trial; ROI: Returns on investment; VD: Normal vaginal delivery;WHO: World Health Organization
Authors’ contributionsLL conceived of the study. LL developed the search string for analysis andcontributed to piloting abstraction tools. LL and PA selected, reviewed, andcoded the studies. EF or JH served as the third reviewer. LL wrote the firstdraft and revisions of the manuscript, and all authors commented on it andthe subsequent drafts. The authors read and approved the final manuscript.
FundingNot applicable.
Availability of data and materialsNot applicable.
Ethics approval and consent to participateNot applicable.
Lin et al. Implementation Science (2020) 15:90 Page 32 of 35
Consent for publicationNot applicable.
Competing interestsThere are no conflicts of interest.
Received: 7 March 2020 Accepted: 6 July 2020
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