riboli sasco communication protocol

8/15/2019 Riboli Sasco Communication Protocol

1/50

Effectiveness ofcommunication strategiesembedded in socialmarketing programmes onhealth behaviours andrelated health and welfare

outcomes in Low and MiddleIncome Countries (LMICs)

Eva Riboli-Sasco, Jacqueline Leslie, Lambert Felix, RoyHead, Josip Car, Laura H. Gunn

PROTOCOL

Publication date: 02 March, 2015


2/50

2 The Campbell Collaboration | www.campbellcollaboration.org

Table of contents

TABLE OF CONTENTS 3

1 BACKGROUND 3

1.1 Description of the problem 3

1.2 Description of the intervention 5

1.3

How the intervention might work 6

1.4 Why it is important to do this review 11

2 OBJECTIVE OF THE REVIEW 14

3 METHODS 16

3.1 Criteria for including studies in the review [PICOS] 16

3.2 Search methods for identification of studies 21

3.3 Data collection and analysis 26

3.4 Data synthesis 31

4 TIMELINE 35

5 ACKNOWLEDGEMENTS 36

6 REFERENCES 37

7 APPENDIX 46

8 CONTRIBUTION OF AUTHORS 52

9 DECLARATIONS OF INTEREST 53

10 SOURCES OF SUPPORT 54

10.1 Internal sources 54

10.2 External sources 54


3/50


1

Background

1.1 DESCRIPTION OF THE PROBLEM

Human behaviour plays a significant role in the leading causes of disease, disability,

and death (Marteau, Hollands, & Fletcher, 2012). In developed countries, health

programmes use behaviour change communication to provide tailored messages and

a supportive environment that persuades individuals and encourages communities to

make better health changes (Glanz & Bishop, 2010; Gordon et al. 2006). For example,

many studies have examined behaviours like smoking cessation, dieting and exercise,

since these are important contributors to urgent health issues in developed countries

(Glanz & Bishop, 2010; Gordon et al., 2006; Hastings et al. 2006). However, in the

developing world it is becoming increasingly critical to address health issues and to

find new methods of promoting behaviours that might prevent illness. Based on this

reality, health communication campaigns have been developed to inform and

promote the adoption of preventive practices, health products and services and to

fight harmful cultural beliefs and behaviours, among groups and individuals (Snyder,

Linkov, & Laporte, 2007).

Health related communication strategies have changed significantly in the last 15

years from top down public service announcements to a wider approach which draws

on behaviour models and methods used in marketing and adapted for the purposes of

"social marketing" (Figueroa et al., 2008; Lefebvre & Flora, 1988).

Social marketing uses a consumer-focused approach based on behaviour, not

awareness or attitude, change and/or maintenance to maximise sale and use of the

product (for example, insecticide treated nets) or service (for example, peercounsellors) by segmented target groups, and uses a marketing mix or ‘‘4 Ps’’

(product, price, place, promotion) (Perez-Escamilla, 2012) to provide products

differentiated by brand, relevance, and positioning. The 4 ‘Ps’ are mostly used with

tangible products, however for non-tangible products or services (for example, hand

washing, exclusive breast feeding, regular exercise), a more appropriate marketing

mix to use would include the “4 Cs” (consumer need/want/desire, cost, convenience,

and communication) of Integrated Marketing Communication for Behavioural

Impact (IMC/COMBI) (Hosein, Parks, & Schiavo, 2009). The UK National Social

Marketing Centre (NSMC) has identified eight benchmark criteria defining key

characteristics of social marketing programmes (see Section 3.1.3 for these criteria)

(National Social Marketing Centre, 2010).


4/50


However the evidence on the effectiveness of social marketing and/or behaviour

change communication strategies in the health and public health context is not always

well synthesised, and often scattered across a number of subsectors in water and

sanitation, family planning, mother and child health, malaria, and epidemic diseases

such as HIV, polio, and avian influenza (Hornik, 2002; Bertrand et al., 2006). The

effectiveness of the communication strategies reported can also be confounded by

issues related to health product or service characteristics such as price, access, and

ease of use.

Early use of health communication relied on top-down one-way messages (Thackeray

& Neiger, 2009). They did not take account of motivational factors and constraints,

and as a result, these campaigns had limited impact (Pfeiffer, 2004). However,

communication approaches continuously evolve. Behaviour change communication

(BCC) is a more recent approach, which makes strategic use of communication to

promote positive health outcomes. It is based on proven theories and models of

behaviour change (and maintenance) and market segmentation. Segmentation is a

group-level, or community/population, marketing approach, whereas behaviour

change focuses primarily on individual actions. Both models of behaviour change and

market segmentation are often used for community mobilisation, health and

environmental education, and various public outreach programmes (Maibach et al.,

2007; Grier and Bryant, 2005). However in some cases, the effectiveness of BCC can

be constrained by other factors relating to product or service characteristics,

availability, and cost (Price, 2001). In India, the National Family Planning

programme uses BCC, however in selected areas, social marketing approaches were

added in order to improve access to products and services (Gurgaon, 2012).

Strategic communication is an important component of social marketing programmes

(UNICEF, 2005). The purpose of any social marketing campaign is to change people’s

behaviour (Andreasen, 1995), or maintain positive behaviour adoption (Hosein, et al.,

2009). Social marketing is distinguished from other health and education campaigns

by its adoption of commercial marketing principles, consumer orientated focus, and

its use of integrated market analysis, segmentation, and marketing strategies (Noble

& Camit, 2005). These are endorsed by the UK National Social Marketing Centre

(NSMC) who recognises these as benchmarks of what is needed for a successful socialmarketing programme (NSMC, 2010).

This review will assess the evidence on “what works” and the impact of BCC strategies

in a social marketing environment on health behaviour and other health and welfare

outcomes among individuals and their carers and communities. The review will draw

on a wide range of public health programmes implemented in low- and middle-

income countries (LMICs).


5/50


1.2 DESCRIPTION OF THE INTERVENTION

Health communication is concerned with “informing, influencing and motivating

individual, institutional [including community] and public audiences about

important health issues” (needs citation with page number) and engaging people

through three principal approaches: individual messaging, social networks, and thepopulation or a community (Maibach, Abroms, & Marosits, 2007).

A communication strategy has been defined by the Food and Agriculture Organization

of the United Nations as “a systematic, well-planned series of actions, combining

different methods, techniques and tools, to achieve an intended change or objective

utilising the available resources within a specific time frame” (Mefalopulos &

Kamlongera, 2004, p. xx).

Various communication strategies may be used within a campaign to change the

behaviour of the target population (Snyder, 2007). Whether acting as an individual

component or multi-component programme(s), single- or multimedia can be used

at various levels, including locally, regionally, and nationally (Noar et al., 2009).

Communication strategies can involve a range of complimentary components

delivered by various channels and in different interventional forms, including public

advocacy and public relations; awareness; mobilisation; education; and advertising,

promotion, and incentivisation.

Interventions can use a range of delivery channels including: mass media (for

example, television, radio, newspapers, leaflets, and posters); educationalentertainment (that is “edutainment”; for example, songs and dances, road shows,

dramas); interpersonal communication/counselling (for example, home visits,

discussion groups and point-of-service); and digital or electronic communications

(including individual mobile phone messaging and electronic social networks).

Although “traditional” mass media such as television and radio remain common, so-

called “new media” are increasingly being used in public communication campaigns

(Parker and Thorson, 2009), including health behaviour change interventions (Edgar,

Noar and Freimuth, 2008). This new field is referred to as eHealth. New media

includes emerging digital technologies and platforms (for example, video games,

virtual worlds, software, mobile devices), online communication (for example,

Internet, blogs, chat rooms, wikis, e-mail, online newsletters) and electronic and

multimedia publishing—multimedia CD-ROMs and hypertext (Shapiro et al., 2007) .

Their increasing success in health communication can be explained by the several

additional features brought by such technologies, including:

- the use of multimedia applications, combining text, audio, video, graphics,

and animation;

-

the possibility of an interactive process, as opposed to the passivity of watching

TV or listening to the radio;


6/50


- the tailoring of information which pushes further the broader targeting of

traditional campaigns by individualizing the message conveyed; and

- the use of hypertext which allows linkage of information with other related

content (Pavlik, 2001).

An important factor in this development has been the widespread usage of the

Internet, on which health promoters are increasingly capitalizing (Webb et al., 2010).

Examples of interventions include the setting up of an Internet-Based Peer

Community dedicated to health information in Dakar, Senegal (Massey et al., 2009),

Despite several successful experiences, in the general context of LMICs, the individual

access to most new media, and particularly the Internet, often remains limited by

several socioeconomic, political and geographical barriers (Edejer, 2000). While the

World Bank estimated that 75.3% of the population in high-income countries had

access to the Internet in 2012, the figures dropped to 29.8% in middle-income

countries and 6.9% in low-income countries (World Bank, 2013a). As a result, thisusage limitation highly restricts the potential reach and impact of digital health

communication campaigns utilising the Internet in LMICs.

Whereas television, computers and landline phones tend to remain scarce in LMICs,

mobile phones constitute a noticeable exception. With 41.5 mobile subscriptions for

100 habitants in low-income countries and more than 80% in middle-income

countries (World Bank, 2013a), this technology is becoming ubiquitous, including in

the most deprived settings. Mobile phones, therefore, hold promising opportunities

for delivering health related messages to a wide audience, in the form of text messages

(Cole-Lewis and Kershaw, 2010) or apps (Cohn et al., 2011; Cowan et al., 2013).

However, the effectiveness of such interventions is still debated, dependent on a

multitude of internal and external factors, thus calling for high quality evidence-based

evaluations (Noar and Harrington, 2012; Sood et al., 2014). This is even more true for

LMICs where specific and often stronger social, economic and cultural constraints

might arise, compromising the success of these eHealth interventions (Kaplan, 2006).

Sood et al. (2014) conducted a review of health communication campaigns in

developing countries; however a major difference between their review and ours is

that our review will specifically address communication strategies embedded in social

marketing programmes.

1.3 HOW THE INTERVENTION MIGHT WORK

Figure 1 (below) presents an example of a logic model we created which shows the

connections between the possible variables identified in various theoretical models as

determinants of behaviour change and/or maintenance and potential health and

welfare outcomes, whether short term or intermediate-to-long term (Knowlton and

Phillips, 2009; Patton, 2008).


7/50


Figure 1. Example of a logic model of possible variables considered in communication interventions and the inputs and

channels used to affect short and intermediate-to-long term outcomes within a framework of social marketing health

programmes

Model

Socialmarketingframework

Behaviourmodels

McGuire'scommunication

stages

Audience

Individuals

Social & othernetworks

Communities

or

populations

Input

Public advocacy& publicrelations

Awareness

Mobilisation

Information &education

Promotion,advertising, &incentivisation

Channel

Mass media

Educationalentertainment

Digital orelectronic

communications

Interpersonal

Short Term

Outcomes

Communication& channel

contact rates

Cognitiveoutcomes

Behaviourchange

Changes indemand forservice orproduct

Intermediate-to-Long

TermOutcomes

Health outcomes

Welfareoutcomes

Social outcomes

Behaviour changeand/or

maintenance


8/50


Figure 1 portrays the theoretical models from a number of areas including behaviour

change and/or maintenance, communication theory, and social marketing.

Commonly used behaviour change (including maintenance) models include (though

are not limited to): Health Belief Model (Janz & Becker, 1984), Theory of Planned

Behaviour (Ajzen, 1991), and the Transtheoretical Model-Stages of Change

(Prochaska & Velicer, 1997). These three models are associated with behaviour change

at the individual level, whereas theories of mobilization and diffusion (for example,

Community Mobilisation Theory (Rothman & Tropman, 1987) and Diffusions of

Innovation Theory (Rogers, 2010)) are associated with the community level. The

social marketing framework considers both individual and community levels.

These models assume that any health or illness outcome is the consequence of the

complex interaction between social, economic, psychological and biomedical factors

(Edelman, 2000; Kelly et al., 2009). Essential components of these models and

theories are the set of mediators and other variables on which they rely. A mediator

is an intervening variable necessary to complete a cause-effect link between an

intervention programme and the targeted health behaviour. Common mediators

include, but are not restricted to: self-efficacy; attitudes towards the behaviour; fear;

perceived barriers and benefits; subjective norms; knowledge; and so forth (World

Bank, 2013b).

Furthermore, McGuire (McGuire, 1984) identifies five communication components

for successful communication. These include: credibility of the message source;

message design; delivery channel; intended audience; and intended behaviour (see

also (Clarke, 1999)).

We are interested to identify communication interventions, targeted at individuals,

groups (including social and other networks), or communities/populations, which

involve strategies (that is, inputs) with single or multiple media delivery channels.

For example, the health objective may be to reduce infant mortality (e.g., an

intermediate to long term health outcome), where messages are directed at mothers

and are delivered using different communication strategies in different programmes.

One strategy may involve interpersonal messaging only; another may involve

interpersonal messaging and a poster campaign; a third may include the same

elements plus advocacy through key networks. Such communication strategies have

been studied, particularly in relation to reviewing alternative strategies to improve the

performance of health workers (Rowe, 2011, 2013).1

1.4 WHY IT IS IMPORTANT TO DO THIS REVIEW

There is a lack of clear synthesised evidence on the effectiveness of communication

strategies of social marketing health programmes. It is unclear which communication

strategies are most effective as assessed by changes in health and welfare outcomes,

1http://obssr.od.nih.gov/scientific_areas/translation/dissemination_and_implementation/DI2011/res

ources/4B%20Rowe%20Reviews%20of%20Emerging%20Issues%20[Compatibility%20Mode].pdf

http://obssr.od.nih.gov/scientific_areas/translation/dissemination_and_implementation/DI2011/resources/4B%20Rowe%20Reviews%20of%20Emerging%20Issues%20%5bCompatibility%20Mode%5d.pdfhttp://obssr.od.nih.gov/scientific_areas/translation/dissemination_and_implementation/DI2011/resources/4B%20Rowe%20Reviews%20of%20Emerging%20Issues%20%5bCompatibility%20Mode%5d.pdfhttp://obssr.od.nih.gov/scientific_areas/translation/dissemination_and_implementation/DI2011/resources/4B%20Rowe%20Reviews%20of%20Emerging%20Issues%20%5bCompatibility%20Mode%5d.pdfhttp://obssr.od.nih.gov/scientific_areas/translation/dissemination_and_implementation/DI2011/resources/4B%20Rowe%20Reviews%20of%20Emerging%20Issues%20%5bCompatibility%20Mode%5d.pdfhttp://obssr.od.nih.gov/scientific_areas/translation/dissemination_and_implementation/DI2011/resources/4B%20Rowe%20Reviews%20of%20Emerging%20Issues%20%5bCompatibility%20Mode%5d.pdfhttp://obssr.od.nih.gov/scientific_areas/translation/dissemination_and_implementation/DI2011/resources/4B%20Rowe%20Reviews%20of%20Emerging%20Issues%20%5bCompatibility%20Mode%5d.pdf


9/50


as well as behaviour change and/or maintenance. There is a need to provide evidence

on what facilitates effective and persuasive messaging in different communication

interventions, which often brings together a mix of strategies (such as public advocacy

and public relations; awareness; mobilisation; information and education; and

advertising, promotion, and incentivisation) across a range of public health

programmes in LMICs (Noar et al., 2009).

Previous reviews to date conducted specifically on behaviour change communication

(BCC) interventions, and their outcomes, have several limitations. First, they have

focused on very specific topics such as: condom use (Sweat et al., 2012); HIV/AIDS

(Noar et al., 2009); uptake of HIV/STI testing in men who have sex with men (Wei et

al., 2011); alcohol (Moreira, Smith, & Foxcroft, 2009); hand hygiene (Mah et al.,

2008); bicycle helmet use (Spinks et al., 2005; Royal et al., 2007); and preventive

cardiology, sexual health, and substance use (Jepson et al., 2010). Second, previous

reviews have examined a single, specific type of communication channel, particularly

mass media (Bala, Strzeszynski, & Cahill, 2008; Bertrand et al., 2006; Grilli, Ramsay,

& Minozzi, 2002; Leavy et al., 2011; Lecouturier et al., 2010; Marcus et al., 1998; Noar

et al., 2009) and campaigns (Evans et al., 2008; Snyder, 2007). Third, some prior

reviews have restricted their search to the highest quality study designs such as

randomised controlled trials (RCTs) and cluster randomised controlled trials

(Moreira et al., 2009). Fourth, although many of these reviews did not exclude LMICs,

they nonetheless did not focus on LMICs. Fifth, previous reviews have neither

explored the theoretical basis nor the mechanism of action of the interventions,

whereas this review seeks to understand mechanisms of action by exploring potential

mediators of behaviour such as knowledge, intention, self-efficacy and attitudes.Finally, there are a couple of protocols registered with the Cochrane Public Health

Group that may overlap, to some degree, with this review but these reviews are

focussed on specific topics such as oral health in children (de Silva-Sanigorski et al.,

2012) and dietary behaviour in children and adolescents (Ganann et al., 2010).

A review was undertaken in 2003 by PSI (Population Services International) of health

based social marketing research (Department for International Development, 2003).

The evidence base was defined through systematic review methodological procedures

of the published literature documenting the effectiveness of social marketing availableon PubMed as well as unpublished PSI papers. The review resulted in the

identification of 87 studies, which almost exclusively were related to HIV/AIDS,

maternal and child health (including malaria interventions), and family planning and

reproductive health. The review evaluated the effectiveness, efficiency and equity of

social marketing programmes presented in the papers. Effectiveness of social

marketing appeared clear based on strong evidence of a positive relationship between

social marketing interventions and changes in product and service use as well as non-

product related behaviours. The underlying process of such changes involves the areas

of opportunity, ability and motivation as key determinants of health behaviours. On

the other hand, recurrent observation of substitution as well as halo effects supported

the claim of efficiency of social marketing interventions. Only in terms of equity, the


10/50


evidence base is more mixed, due mainly to differences in the statistical choices of

study authors. More data is therefore required for it to be assessed properly.

Despite these encouraging results, the review also demonstrated the gaps in the

knowledge base about social marketing, and in particular in terms of:

Guidance on the design of interventions, projects, and programmes; Evidence of the rates of change at which targeted behaviour practices occur;

Effectiveness of different levels of intensity/frequency;

Effectiveness and efficiency of different marketing mixes as behaviour

changes within a population;

Long term effect on health behaviours; and

Role of the price as a potential barrier to continued use of products and

services.

The major investment made by the international community in the communicationcomponent of global public health and development programmes, along with an

increasing scientific literature, illustrate the importance accorded to this component

– and hope in its effectiveness (Obregon & Waisbord, 2012). However, more evidence

on its processes and best practices is needed.

This review will address the gaps identified in the earlier PSI study and Department

for International Development (DFID) review discussed above and will focus

specifically on evidence from studies that have used BCC strategies in an intervention

underpinned by social marketing principles.

There is an increasing demand from policy-makers and funders for rigorous evidence

for the impact of BCC projects on health behaviours and health outcomes and on

market efficiency (Dhaliwal & Tulloch, 2012). This is driven by several factors:

A significantly increased emphasis on evidence-based policy and funding

within the international development sector as a whole, and thus on the

importance of rigorous impact evaluation (UNICEF, 2005);

A linked increase in the importance placed by donors (such as DFID and

USAID, United States Agency for International Development) as well as

NGOs on cost-effectiveness and value for money in the context of increased

public scrutiny of funding for overseas aid and pressure on philanthropic

budgets (Fowler, 2013);

Scepticism in some quarters about the effectiveness of mass media behaviour

change campaigns, given the lack of robust evidence, exacerbated by an

impression that some BCC campaigns (for example, promoting condom use)

have not always been effective; and

Increased interest and funding in markets for the poor and underserved

(Heierli, 2009; Bloom et al., 2014).


11/50


This review will focus on those studies that have specifically used single and multi-

channel communication strategies in social marketing health programmes as defined

by at least five of the eight underlying NSMC criteria mentioned in Section 1.1 above.

The review will consider social marketing programmes from all LMIC health related

sectors.


12/50


2

Objective of the review

The overall objectives of the review are to assess the effectiveness of communication

strategies incorporated in social marketing, on behaviour changes and/or

maintenance, and health and welfare outcomes in LMICs.

Primary objectives

1) To assess the effectiveness of communication strategies and the impact of such

“messages’’ that are most used to underpin communication strategies through

theoretical models of behaviour change and/or maintenance and social marketing

strategies (that is, message impact); and

2) To assess the effectiveness of such communication strategies on health outcomes

(prevalence, morbidity and mortality).

Secondary objectives

The following secondary objectives will be addressed, when available among includedstudies, in a narrative review:

3) To assess the barriers, mediators and moderators which significantly influence the

impact of communication strategies on health behaviour change and/or

maintenance;

4) To review the convergence of tools/technologies and channels which have been

most used in communications for social marketing programmes. What evidence

and potentially on-going research is available to support what is the best

combination of tools and how and when should these be used (while keeping inmind that it may not always be evident for authors of studies involving complex

interventions to identify exactly which tool, or combination of tools, yields the

most favourable outcomes);

5) To review the principles and approaches used in communication design and

evaluation, particularly the methods or theories used for: effective messaging;

persuasiveness and information processing; credibility of programme and spokes

people; and message design; and

6)

To identify important evidence gaps in communication strategies.


13/50


14/50


to): statistical matching (for example, propensity score matching); and regression

adjustment (for example, difference-in-differences, estimation, and variable selection

models) (Waddington et al., 2012).

With the breadth of different study designs within the inclusion criteria, any meta-

analysis to evaluate the effect size(s) will be appropriately sub-grouped by study

design (in addition to other PICO components – participants, interventions,

comparisons, outcomes, including by health condition) in order to minimise biases

that could occur from combining studies of multiple types; further explanation of

analyses are presented in Sections 3.3 and 3.4.

3.1.2 Participants

Participants will include targeted populations or communities, including social

networks, and/or individuals in low- and middle-income countries (LMICs) of any

age, gender, education, socio-economic status, or health conditions, who are eitherthe direct recipient of the health treatment product or service, the carer, or those in

positions to administer or provide a treatment, product or service.

3.1.3 Interventions

Interventions would include all communication strategies in social marketing health

behaviour change and maintenance programmes (which could also include those

among the private sector) which agree with a modified version of at least five of the

eight NSMC criteria that use communication inputs and channels designed to

influence voluntary behaviour of target audiences (NSMC, 2010). The strategiescould relate to any product and/or service, or variation of these, promoted as part of

the health programme.

These criteria include:

1) Behaviour change and/or maintenance: the intervention seeks to change (or

maintain, in the case of positive behaviour adoption at baseline; for example,

exclusive breast feeding may be an initial behaviour adoption but then it is often not

always sustained for the recommended period) behaviour and has specific measurable

behavioural objectives;

2) Consumer research: formative research is conducted to identify consumer

characteristics and needs, including their view of the recommended behaviour and

what they see as constraining and facilitating factors in terms of implementing the

behaviour. Interventions are pre-tested with the target group;

3) Segmentation and targeting: different segmentation variables are used and a

strategy is tailored to the segments;

4) Marketing communication mix: the intervention must consist of communications

(for example, mass media, personal selling, advertising, community mobilisation, or


15/50


public relations) plus at least one ‘P’ (from product, price, place, or promotion) or ‘C’

(from consumer need/want/desire, cost, convenience, and communication);

5) Exchange: the intervention considers what will motivate people to engage

voluntarily with the intervention and offers them something beneficial in return,

whether that is intangible or tangible, and whether the benefits are of value to the

consumer (for example, insecticide treated bed nets are beneficial, but are these

benefits perceived by the consumer as of value to them?);

6) Competition: the intervention considers the appeal of competing behaviours

(including the current behaviour) and uses strategies to decrease competition;

7) Theory: the intervention uses behavioural theories to understand human behaviour

and to build programmes around this understanding; and

8) Customer orientation: the intervention attaches importance to understanding from

where the customers are starting, their knowledge, attitudes and beliefs, and the social

context in which they work.

The intervention setting should be a developing country defined as a country bearing

the World Bank designation of a low income, lower middle income, or upper middle

income economy (World Bank, 2012).

3.1.4 Comparisons

Any comparisons will be included, both inactive and active controls including

comparisons between different types of medium of communications.

Comparisons would include:

Baseline or adjusted baseline;

Communication strategies, which can be comprised of at least one different

type of communication method/channel;

Use of different communication channels and their attributes including

persuasiveness and information processing and message design and

interactivity; and

Different characteristics of social marketing policy as identified through the

four “P”s (including, for example, differentiation in pricing, place of

delivery and organisational provider, products and promotion), or the four

“C”s (including, for example, differences in consumer

needs/wants/desires, costs, conveniences to obtain the product or service,

and communications).

With the possible comparisons that could exist in evaluating effect sizes among

studies of the same study design, further sub-groups will be defined to meta-analyse


16/50


those studies with similar comparisons in order to minimise biases that could occur

from combining studies containing varying comparisons; further explanation of

analyses are presented in Sections 3.3 and 3.4.

3.1.5 Outcomes

Due to the nature of the interventions, only the primary outcome will form part of theeligibility criteria. As seen in Figure 1, outcomes can occur in the short term, as well

as in the more intermediate to long term. In some cases, outcomes can be both short

and intermediate-to-long term in nature.

Primary

A change in behaviour, and/or sustained behaviour change over time, targeted by the

intervention, which could also include the adoption or sale of a service or product

(that is, change in, or maintenance/uptake of, demand of a service or product). This

may be objectively measured/observed or self-reported. In order to measure

sustainability, or maintenance, of a behaviour change (or an initial positive behaviour

adoption), the outcome would need to be measured for at least 6 months or longer

(Prochaska & Velicer, 1997).

Secondary

Any of the following health, welfare, and cognitive outcomes will be identified from

included studies, when available, and assessed narratively.

Health outcomes:

Prevalence and/or incidence;

Indicators of morbidity and/or severity of morbidity; and

Indicators of transmission, including change in transmission rate (for

example, change in infected vectors).

Welfare outcomes:

Economic

o Income (change in monetary income);

o Labour productivity (for example, change in working hours, ability

to work a “standard work day”, or to undertake more demanding

work e.g. heavier work or increased production, including

agricultural production for the same hours of work); and

o Voluntary leisure time;

Social


17/50


o Change in social relations (for example, measures of community

inclusion/exclusion, measures of stigma e.g. earnings,

employment, marriage status as compared with “health y people”);

and

Environmental

o Water and air quality.

There are also intermediaries that assist the assessment of progress toward achieving

a primary outcome of behaviour change, or a secondary health and welfare outcome.

Intermediaries will be considered only if the aforementioned primary outcome is

identified within a study. Intermediaries include the following:

Cognitive outcomes:

o Knowledge (for example, awareness of the disease, knowledge of

disease risk and realism of risk perception, and knowledge ofprivate and public benefits of the health intervention);

o Attitudes and intentions to change; and

o Self-efficacy (that is, a person’s belief in their capacity to carry out

a specific action).

Adverse outcomes may also be reported throughout the studies, which we will include

in this review.

Intermediate outcomes will be collected along the causal chain and may form part of

the contextual and background information of the study.

Based on the PICOS components defined above, an example of a study that meets the

eligibility criteria for inclusion is Pattanayak et al. (2009). The intervention reported

by the authors consisted in a community-led total sanitation approach aiming to

empower local inhabitants by not simply providing latrines but also fostering

discussions and reflexions to change knowledge, attitudes and practices. The

development of the campaign was informed by in-depth interviews and focus groups

with the targeted audience and key informants. Such formative research suggested

the importance of key notions such as privacy, dignity and safety benefits, thus going beyond a simply medical approach and encompassing social and cultural dimensions.

Social mobilization was fostered through a variety of intervention tools and channels,

including three community-based activities: a community walk, a participatory

mapping exercise, and group discussions. The planning and evaluation of the

intervention makes use of other key social marketing concepts including the

marketing mix approach: price, product, placement and promotion.

On the contrary, Khan et al. (2012) is an example of a study that does not meet

inclusion criteria. Although this study assesses a behaviour change communication,

it does not meet any of the following social marketing criteria: consumer research,

customer orientation, exchange, segmentation and targeting and therefore does not


18/50


reach the minimum five out of the eight criteria listed previously. Furthermore, the

communication is limited to a single booklet, which is not accessible to illiterate

women, thus reducing the reachable audience.

3.2 SEARCH METHODS FOR IDENTIFICATION OF STUDIES

3.2.1 Electronic searches

The search will be performed in the following electronic databases:

i. CENTRAL, The Cochrane Central Register of Controlled Trials (latest

issue);

ii. MEDLINE (Ovid SP) (1960 to date);

iii. EMBASE (Ovid SP) (1960 to date);

iv. PubMed;

v. PsycINFO (Ovid SP) (1960 to date);

vi. ERIC (Ovid) (1960 to date);

vii. CINAHL (Ovid) (1960 to date);

viii. Chinese Social Science Citation Index;

ix. Indian Citation Index;

x. Interred educational search engine;

xi. Global Health (Ovid) (1960 to date);

xii. WHOLIS (1960 to date);

xiii. LILACS (1960 to date);

xiv.

SCIRUS (1960 to date);

xv. Web of Science (1960 to date);

xvi. ASSIA (ProQuest) (1960 to date);

xvii. HMIC (Health Management Information Consortium)

xviii. WHO nutrition databases

(http://www.who.int/nutrition/databases/en/)

xix. Social Science Index

http://en.wikipedia.org/wiki/Chinese_Social_Science_Citation_Indexhttp://en.wikipedia.org/wiki/Indian_Citation_Indexhttp://en.wikipedia.org/wiki/Interred_educational_search_enginehttp://www.who.int/nutrition/databases/en/http://www.who.int/nutrition/databases/en/http://www.who.int/nutrition/databases/en/http://www.who.int/nutrition/databases/en/http://en.wikipedia.org/wiki/Interred_educational_search_enginehttp://en.wikipedia.org/wiki/Indian_Citation_Indexhttp://en.wikipedia.org/wiki/Chinese_Social_Science_Citation_Index


19/50


xx. OVID HealthStar

xxi. Open Grey

xxii. Sociofiles

xxiii.

HINARI

xxiv. Scopus

xxv. Social Care Online

3.2.2 Searching other resources

We will also search reference lists of included studies and related reviews.

In addition, we will search the grey literature using Google Scholar.

The following document repositories of organisations will also be searched,

throughout which we will use broad search terms such as ‘social marketing’ and

‘communication’:

i. Population Service International (http://www.psi.org);

ii. U.K. Department for International Development

(http://www.dfid.gov.uk);

iii.

U.S. Agency for International Development (http://www.usaid.gov);

iv. IDEAS/RePEc (http://ideas.repec.org);

v. 3ie impact evaluation (http://www.3ieimpact.org);

vi. JHPIEGO (http://www.jhpiego.org/en);

vii. Family Health International (FHI) (http://www.fhi.org/en/index.htm);

viii.

Population Council (http://www.popcouncil.org);

ix. The British Library for Development Studies;

(http://www.blds.ids.ac.uk);

x. Asian Development Bank (http://www.adb.org);

xi. Australian Aid Agency (http://www.ausaid.gov.au/Pages/home.aspx);

xii. Canadian International Development Agency

(http://www.acdi-cida.gc.ca/home);

http://www.psi.org/http://www.dfid.gov.uk/http://www.usaid.gov/http://www.3ieimpact.org/http://www.jhpiego.org/enhttp://www.fhi.org/en/index.htmhttp://www.popcouncil.org/http://www.blds.ids.ac.uk/http://www.blds.ids.ac.uk/http://www.popcouncil.org/http://www.fhi.org/en/index.htmhttp://www.jhpiego.org/enhttp://www.3ieimpact.org/http://www.usaid.gov/http://www.dfid.gov.uk/http://www.psi.org/


20/50


xiii. Swedish Development Agency (http://www.sida.se/English);

xiv. Danish Development Agency (http://um.dk/en/danida-en);

xv. Japan International Cooperation Agency (http://www.jica.go.jp/english);

xvi.

Japan Bank for International Cooperation (http://www.jbic.go.jp/en);

xvii. World Bank (Office of Evaluation and Development)

(http://go.worldbank.org/1F1W42VYV0);

xviii. Pan American Health Organization (http://www.paho.org);

xix. World Health Organization (http://www.who.int/en);

xx. United Nations (UNAIDS (http://www.unaids.org/en), UNICEF

(http://www.unicef.org), UNEP (http://www.unep.org), UNDP(http://www.undp.org), UN-HABITAT (http://www.unhabitat.org), and

UNRISD (http://www.unrisd.org));

xxi. Inter-American Development Bank (http://www.iadb.org);

xxii. African Development Bank (http://www.afdb.org);

xxiii. Red Cross (http://www.redcross.org);

xxiv. Christian Aid (http://www.christianaid.org.uk);

xxv. Oxfam (http://www.oxfam.org.uk);

xxvi. African Medical and Research Control (http://www.amref.org);

xxvii. Centers for Disease Control and Prevention (http://www.cdc.gov);

xxviii. Futures Group (http://futuresgroup.com);

xxix. Manoff Group (http://manoffgroup.com);

xxx. Centre of Excellence for Public Sector Marketing (CEPSM)

(http://cepsm.ca.home);

xxxi. Rescue Social Change Group (http://rescuescg.com);

xxxii. Strategic Social Marketing Ltd. (http://www.strategic-social-

marketing.vpweb.co.uk);

xxxiii. Social Marketing Services Inc. (http://www.socialmarketing

servive.com);


21/50


xxxiv. National Social Marketing Centre (NSMC) (http://www.thensmc.com);

and

xxxv. DKT International (http://www.dkinternational.org/about-dkt).

We will search the following theses and conference proceedings databases:

i. Index to Theses (http://www.theses.com); and

ii. Dissertation Abstracts

(http://library.dialog.com/bluesheets/html/bl0035.html).

We will search the following trial registers for on-going and recently completed trials:

i. WHO International Clinical Trials Registry Platform

(http://www.who.int/ictrp/en/);

ii. Current Controlled Trials (www.controlled-trials.com);

iii. Clinical Trials (www.clinicaltrials.gov);

iv. Trials Register of Promoting Health Interventions (TRoPHI)

(http://eppi.ioe.ac.uk/webdatabases/Intro.aspx?ID=5); and

v. Database of promoting health effectiveness reviews (DoPHER)

(http://eppi.ioe.ac.uk/webdatabases/Intro.aspx?ID=2).

We will also search the EPPI-Centre database of health promotion (Bibliomap)

(http://eppi.ioe.ac.uk/webdatabases/Intro.aspx?ID=7).

Given the focus of the review and the potential for studies to have been conducted and

reported in other countries and languages, studies will not be excluded based on

language of publication, and a translation will be performed when necessary.

3.2.3 Search terms

The following search terms will be used across marketing, communication, and

setting domains:

Marketing

1 exp Marketing

2 exp Social Marketing

3 marketing.ab.ti

4 (social adj3 market$).ab,ti.

http://www.dkinternational.org/about-dkthttp://www.dkinternational.org/about-dkthttp://www.dkinternational.org/about-dkthttp://eppi.ioe.ac.uk/webdatabases/Intro.aspx?ID=2http://eppi.ioe.ac.uk/webdatabases/Intro.aspx?ID=2http://www.dkinternational.org/about-dkt


22/50


5 behavio?r change.ab,ti.

6 consumer research.ab,ti.

7 audience segment$.ab,ti.

8 market$ mix.ab,ti.

9 customer orient$.ab,ti.

Communication

1 exp communication

2 exp advocacy

3 exp Consumer Advocacy/ or exp Patient Advocacy

4 exp information dissemination

5 information adj3 disseminat$.ab,ti.

6 exp health promotion

7 exp Education

8 exp advertising

9 adverti$.ab,ti.

10 exp mass media

11 mass media.ab.ti

12 exp multimedia

13 exp communications media

14 exp information technology

15 exp information

16 drama?.ab,ti.

17 "home visit*".ab,ti.

18 play$.ab,ti.

19 internet.ab,ti.


23/50


24/50


Setting

43 exp Developing Countries

44 low income countr$.ab,ti.

45 low middle income countr$.ab,ti.

46 developing countr$.ab,ti.

47 middle income countr$.ab,ti.

48 sub-saharan africa.ab,ti.

49 southeast asia.ab,ti.

50 latin america.ab,ti.

51 south america.ab,ti.

52 Exp Africa south of the Sahara

53 Exp Asia, Southeastern

54 Exp Latin America

55 exp South America

3.3 DATA COLLECTION AND ANALYSIS

We will follow a three-stage approach to data collection and analysis. Using the

aforementioned search strategy, Stage 1 will consist of identifying peer-reviewed and

grey literature from databases and other sources listed in the previous section. These

will be screened, first using titles and abstracts and then the full texts of potentially

eligible studies, to ensure that articles meet the study inclusion criteria. In the full text

screening, we will apply a restriction to include only those articles published after

1960, as although “social marketing” was coined in 1971 (Kotler & Zaltman, 1971) the

term and approach had already started being applied to health interventions by the

1960s, especially in developing countries (Manoff, 1985; Walsh et al., 1993). However,

we will not apply this restriction at the time of searching or initial screening of titles

and abstracts due to the possibility of incorrect indexing of an article, particularly the

date of publication.


25/50


In Stage 2, we will develop a matrix to facilitate the identification and categorisation

of relevant social marketing communication strategies. The columns in the matrix will

consist of common health conditions in LMICs that contribute to the global burden of

disease while the rows will consist of the different strategies of the alternative

communication strategies. These strategies relate to the inputs and channels outlined

in Figure 1.

In Stage 3, the definition and understanding of communication strategies will be

informed by the matrix and refined as necessary.

3.3.1 Selection of studies

We will merge search results across databases and other resources, using the

reference management software EndNote X5 (Thomson Reuters Corporation, 2010),

and remove duplicate records of the same report. Two authors (ERS and LF) will

independently examine titles and abstracts of records retrieved from the search. We will retrieve the full text of the potentially-relevant studies and assess their eligibility

against the inclusion criteria. Multiple reports of the same study will be reviewed in

order to determine if the study is eligible for inclusion, since oftentimes multiple

publications regarding a single study may not always provide the study design and

analysis information in each publication for that study. Authors will compare their

inclusion and exclusion decisions and discuss any differing results, with unresolved

disagreements about study eligibility evaluated by a third review author (LHG or JL),

who will serve as a mediator.

If any disagreements are not resolved, then we will place the article with those

'awaiting assessment' and will contact the author(s) for clarification. We will also

include any on-going trials if a study author(s) provides interim outcome data, or the

final data, ahead of publication of their report. We will describe all the potentially-

relevant excluded studies in the ‘Characteristics for Excluded Studies’ table along with

reasons for exclusion. We will use an adapted PRISMA (Preferred Reporting Items for

Systematic Reviews and Meta-Analyses) flow-chart to describe the study selection

process (Schünemann et al., 2011).

3.3.2

Data extraction and management

For studies meeting the inclusion criteria, we will extract the PICOS characteristics

(information on participants, interventions, comparisons, outcomes, and study

designs) and present them in a table. The Appendix (in Section 7) provides a draft

codebook of key constructs of interest for the data extraction. Two authors (ERS and

LF) will independently extract relevant PICOS characteristics of all the included

studies using a structured data collection/extraction form approved by the other team

members; any disagreements will be resolved by referencing the original article or

consulting, when necessary, with a third author (LHG). Any relevant missing

information on the study(s) will be sought from the original author(s) of the article, if

required. ERS will transfer the data from the extraction form to the Review Manager


26/50


software (The Cochrane Collaboration, 2012) while LF will confirm the accuracy of

the entered data. We will summarise extracted data in a ‘Characteristics of Included

Studies’ table.

3.3.3 Assessment of risk of bias in included studies

Two authors (ERS and LF) will perform independent assessments of the risks of biases within each study. For studies with a separate control group such as

randomised controlled trials, non-randomised controlled trials, and controlled

before-after studies, we will use the risk of bias criteria as suggested by the Cochrane

Collaboration’s Effective Practice and Organisation of Care (EPOC) review group

(Effective Practice and Organisation of Care Group, 2009). This judges the study

against nine criteria related to: sequence generation; allocation concealment; baseline

outcome measurements; baseline characteristics; incomplete outcome data; blinding

of outcome assessments; contamination; selective outcome reporting; and other

biases. For judging other biases, we will consider the following two criteria: use of valid and reliable outcome measurements; and funding sources. For each criterion,

the risk of bias will be judged as low, unclear, or high.

For studies that use an interrupted time series (ITS) design, we will assess the risk of

bias using the following domains as recommended by EPOC (Effective Practice and

Organisation of Care Group, 2009): 1) the intervention being independent of other

changes; 2) sufficient data points to enable statistical inference; 3) the intervention

being unlikely to affect data collection; 4) blinding of outcome assessors to

intervention allocation; 5) incomplete outcome data being adequately addressed; 6)

selective reporting of outcomes; and 7) other risk of bias related to validity and

reliability of outcome measures and funding sources.

We will seek guidance from the IDCG (International Development Coordinating

Group) secretariat to assess the risk of bias in studies that have used multiple

statistical analyses (IDCG, 2012).

In all cases, two authors (ERS and LF) will independently assess the risk of bias of

included studies, with any disagreements resolved by discussion, and with

consultation of a third review author (LHG) as a mediator. As necessary and wherepossible, we will contact study authors for additional information about the included

studies, or for clarification of the study methods. We will incorporate the results of

the risk of bias assessment into the review through a ‘Risk of Bias’ table, and a

systematic narrative description and commentary about each of the elements, leading

to an overall assessment of the risk of bias of included studies and a judgment about

the overall internal validity of the review’s results.

The correlation between these risks of bias measures and the effect sizes will be

examined. And a sensitivity analysis will be conducted using one or more risk of bias

scores as a moderator.


27/50


3.3.4 Assessment of statistical power of included studies

For any included study that is not eligible for a meta-analytic synthesis of estimating

pooled effects, we will obtain the statistical power of the study to detect pre-

established significant effect magnitudes from the published report (IDCG, 2012). If

this is not available, then we will calculate the power of the study (post-hoc) for the

point estimate of the effect based on the primary outcome. This will be based on the

assumption that the sample size is sufficient to detect an optimal difference in

behaviour change outcome with 90% power at the 0.05 significance level.

3.3.5 Measures of treatment effect

We will compare characteristics of included studies to assess the feasibility of

conducting a meta-analysis. Only those studies that are deemed homogeneous based

on similar PICOS elements, including cultural and population-specific characteristics

(that is, it may be unrealistic to conclude that the effectiveness of the sameintervention strategy/mix of strategies is equivalent among varying cultures), will be

meta-analysed. For dichotomous outcomes of included studies, we will report risk

ratios and corresponding 95% confidence intervals. For continuous data among

studies that assess the same outcome measure, we will estimate mean differences (for

studies using the same scale) and standardised mean differences (for differences in

scale) between groups, along with their corresponding 95% confidence intervals.

Since included studies are likely to come from heterogeneous epidemiological and

socioeconomic settings, and true effect sizes are expected to vary, a random effects

meta-analysis will be employed, if feasible to combine similar studies by subgroups.

For controlled before and after studies, we will report the relative percentage change

post intervention and standardised mean differences, along with their associated 95%

confidence intervals.

Where follow-up data were collected at different time periods, we will report results

taken from the furthest points in time relative to the intervention (Deeks et al., 2011).

For interrupted time series studies, we will report the following estimates, and their

95% confidence intervals, from regression analyses which adjust for autocorrelation:

(i) change in level of the outcome at the first point after the introduction of the

intervention (immediate effect of the intervention); and (ii) post-intervention slope

minus the pre-intervention slope (long term effect of the intervention) (Brennan et

al., 2009).

3.3.6 Unit of analysis issues

If a study has multiple intervention arms, but only one that would fulfil our inclusion

criteria, then we would compare this arm with the least active or inactive arm. We

will, however, list all other arm(s) that were not used for comparison in the report.

Where a study has more than one active intervention arm, data from the appropriate

arms for each of the main comparisons will be extracted. If more than one treatment


28/50


arm is relevant for a single comparison, then data from all appropriate arms will be

included in that comparison.

In studies where the effects of clustering have not been taken into account (for

example, by using multilevel modelling), we will correct for this unit of analysis error

by adjusting the studies’ corresponding standard errors and confidence intervals, by

a factor including the intra-class correlation coefficient (ICC), if provided in papers,

or using a published estimate of the ICC for different interventions and outcomes

(Ukoumunne et al., 1999) as suggested by (Higgins et al., 2011).

3.3.7 Dealing with missing data and incomplete data

For any missing data within included studies, we will contact the study authors in an

effort to obtain this missing information (for example, number of participants in each

group, outcomes, and summary statistics). If the standard deviations (SDs) of

continuous outcome data are missing, then we will attempt to calculate them usingother reported statistics, such as 95% confidence intervals, standard errors, or p-

values. If these are unavailable, then we will contact the author(s) in an effort to obtain

them. We will use an intention-to-treat (ITT) analysis (Higgins et al., 2011).

3.4 DATA SYNTHESIS

3.4.1 Quantitative Synthesis

The studies’ characteristics based on the PICOS components will be compared to

determine whether studies can be combined with a meta-analysis based on relatively

little or moderate clinical heterogeneity, as determined by experts with knowledge of

communication strategies embedded within social marketing programmes. First,

studies will be grouped according to health condition and primary outcome(s) within

that condition. Next, studies will be assessed on the criteria of intervention(s),

comparison(s), and participants within a given health condition to determine whether

(or which) studies can be combined based on relatively low or moderate clinical

heterogeneity of these criteria (e.g., see Section 3.4.1.2 for some of the intervention

components that will be assessed). Experts with knowledge of communication

strategies embedded within social marketing programmes (for example, one of our

co-authors at Development Media International, some of the Key Influencers as

identified in our Policy Influence Plan) will be contacted to review these criteria to

assess the level of clinical heterogeneity, hence advising whether to combine

potentially similar studies in a meta-analysis. Grouped studies will then be assessed

by study design and only those with the same study design will be combined into a

meta-analysis. Thus, only those studies that are deemed by the experts as

homogeneous based on similar PICOS elements, including cultural and population-

specific characteristics (that is, it may be unrealistic to conclude that the effectiveness

of the same intervention strategy/mix of strategies is equivalent among varying


29/50


cultures), will be meta-analysed. Where appropriate, effects will be synthesized for

short, intermediate, and long term outcomes along the causal chain (IDCG, 2012).

If suitable numerical data are not available and/or if a meta-analysis is not

appropriate, as in cases where the included studies are too clinically heterogeneous to

combine, we will perform a narrative synthesis. We will refer to the narrative

synthesis framework to guide this process (Rodgers et al., 2009). In particular, we will

use the following steps:

Develop a preliminary synthesis by grouping the included studies by the type

of health condition;

Describe Participants, Interventions, Comparisons, and Outcomes (PICO

elements) along with the reported findings for each of the included studies;

Explore the relationships between characteristics of individual studies and

their reported findings, as well as those between the findings of different

studies;

Describe the moderators as well as the mediators that would have an impact

on the intervention effects. Depending on the availability of data from

included studies, we will also explore and report the impact of the

interventions on specific population groups such as those belonging to low

socioeconomic status, children, women, or older people; and

Use the summary of the risk of bias of an outcome across studies to judge therobustness of the evidence.

We will perform the statistical analysis using RevMan version 5.2 (The Cochrane

Collaboration, 2012). We will adhere to the statistical guidelines in (Higgins et al.,

2011).

We will use the GRADE system to assess the quality of the overall evidence. We will

construct a ‘Summary of Findings’ table that will include the magnitude of the effect

of the interventions, and a summary of available data for primary and secondary

outcomes (Schünemann et al., 2011).

3.4.1.1 Assessment of heterogeneity

When a meta-analysis is possible, we will assess statistical heterogeneity through

visual inspection of forest plots, by assessing the overlap of 95% confidence intervals

for estimated intervention effects across studies (i.e., with poor overlap indicative of

statistical heterogeneity), and through assessment of heterogeneity statistics, such as

I2 and the Chi-square significance test for heterogeneity. Since the Chi-square test

may have lower statistical power for a smaller number of combined studies or with

studies of small sample sizes, a 0.1 significance level will be used rather than the

standard 0.05 level, with significant results indicative of statistical heterogeneity


30/50


(Deeks et al., 2011). As we will be using a random effects meta-analytic model, we will

also report the between study variability, tau-squared (τ 2).

3.4.1.2 Investigation of Heterogeneity

We will investigate whether findings differ according to key intervention components

or potential contextual mediators as listed below (Baron & Kenny, 1986; Bauman etal., 2002):

Theoretical models used;

Mono or multi intervention and intervention combinations;

Duration of intervention, its frequency and intensity;

Channel(s) of delivery (fore example, media, face-to-face, electronic, and so

forth);

Level of interaction allowed by intervention;

Audience health status; Product or service type;

Level and attributes of segmentation;

Country income level (that is, ‘lower middle income countries’, ‘higher middle

income countries’ and ‘low income countries’); and

Source of funding and/or implementation (that is, industry, aid, national).

In addition, we will collect information on sub-groups of interest, including

vulnerable groups, according to PROGRESS-plus (place of residence, race/ethnicity,

occupation, gender, religion, education, socioeconomic status, social capital, age,

disability, and sexual orientation) categories (Kavanagh et al., 2009).

If sufficient studies are available for a given outcome and potentially important

moderators are identified in the review through a sub-group meta-analysis, then we

will perform meta-regression to estimate the independent effects of these covariates

on effect (IDCG, 2012). This would be performed in the statistical software package R

(R Core Team, 2013).

3.4.1.3 Sensitivity Analysis

We will perform sensitivity analyses (using the criteria discussed in the ‘Assessment

of Risk of Bias in Included Studies’ section, and as recommended by Effective Practice

and Organisation of Care Group, (2009)) including:

Exclusion of studies with a high risk of attrition bias, that is, incomplete

outcome data; and

Exclusion of potentially influential outliers (that is, large studies with

excessively large or small effect sizes that may heavily influence the mean

effect size).


31/50


At the end we will apply 3ie’s quality appraisal of systematic reviews checklist2 to

check for the completeness of all the review methods and to improve clarity in the

final report.

3.4.1.4 Assessment of Publication Bias

We will evaluate funnel plots for asymmetry (provided there are at least ten includedstudies in the meta-analysis). Funnel plots will be used as a means of investigating

small study effects that may have occurred due to the potential existence of reporting

biases (for example, small study bias). Tests of funnel plot asymmetry may also be

used to examine whether the association between estimated intervention effects and

a measure of study size is greater than might be expected to occur by chance, and to

add further consideration to the visual inspection of the funnel plot (Sterne et al.,

2011). We will also consider other reasons for possible funnel plot asymmetry such as

true heterogeneity or the methodological quality of included studies.

3.4.2 External Validity

In order to explore external validity of the review, we will present results in terms of

relative and/or absolute effects and discuss the implications of differences in absolute

or relative effects for different contexts such as related to moderators and PROGRESS

plus categories as listed under the Assessment of Heterogeneity section. In addition,

we will use the GRADE system to assess the quality of the evidence, the magnitude of

effect of the interventions, and the available information on the primary and

secondary outcomes. Results will be presented in a ‘Summary of Findings’ table

(Schünemann et al., 2011).

2http://www.3ieimpact.org/media/filer/2012/05/07/quality_appraisal_checklist_srdatabas

e.pdf

http://www.3ieimpact.org/media/filer/2012/05/07/quality_appraisal_checklist_srdatabase.pdfhttp://www.3ieimpact.org/media/filer/2012/05/07/quality_appraisal_checklist_srdatabase.pdfhttp://www.3ieimpact.org/media/filer/2012/05/07/quality_appraisal_checklist_srdatabase.pdfhttp://www.3ieimpact.org/media/filer/2012/05/07/quality_appraisal_checklist_srdatabase.pdfhttp://www.3ieimpact.org/media/filer/2012/05/07/quality_appraisal_checklist_srdatabase.pdfhttp://www.3ieimpact.org/media/filer/2012/05/07/quality_appraisal_checklist_srdatabase.pdf


32/50


4

Timeline

Date Event

1 March 2013 Preliminary Protocol submitted to Campbell Collaboration

14 April 2013 Comments received from Campbell Collaboration

21 May 2013 Final Protocol submitted to Campbell Collaboration

15 October 2013 Submission of draft report to Campbell Collaboration

15 November 2013 Comments received from Campbell Collaboration

31 December 2013 Submission of final paper to Campbell Collaboration


33/50


5

Acknowledgements

We would like to acknowledge support and assistance from:

International Initiative for Impact Evaluation (3ie) who are funding this

review;

Tim Reeves, Medical Research Support Librarian at Imperial College

London, for his advice on devising the search strategies;

The review Advisory Group members for their feedback on a draft of this

document; and

Campbell peer review groups.


34/50


6

References

Andreasen, A. R. (1995). Marketing Social Change: Changing Behavior to Promote

Health, Social Development, and the Environment . San Francisco, CA:

Jossey-Bass.

Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and

human decision processes, 50(2), 179-211.

Bala, M., Strzeszynski, L., & Cahill, K. (2008). Mass media interventions for

smoking cessation in adults. Cochrane Database of Systematic Reviews.

Baron, R. M., & Kenny, D. A. (1986). The Moderator-Mediator Variable Distinction

in Social Psychological Research: Conceptual, Strategic, and Statistical

Considerations Journal of Personality and Social Psychology, 51(6), 1173-

1182.

Bauman, A. E., Sallis, J. F., Dzewaltowski, D. A., & Owen, N. (2002). Toward a better

understanding of the influences on physical activity: The role of

determinants, correlates, causal variables, mediators, moderators, and

confounders. American Journal of Preventive Medicine, 23(2, Supplement

1), 5-14. doi: http://dx.doi.org/10.1016/S0749-3797(02)00469-5

Bertrand, J. T., O'Reilly, K., Denison, J., Anhang, R., & Sweat, M. (2006). Systematic

review of the effectiveness of mass communication programs to change

HIV/AIDS-related behaviors in developing countries. Health Educ Res,

21(4), 567-597. doi: 10.1093/her/cyl036

Bloom, G., Wilkinson, A., Standing, A., Lucas, H. (2014). Engaging With Health

Markets in Low and Middle-Income Countries. IDS Working Paper 443.

Brennan, S., McKenzie, J., Whitty, P., Buchan, H., & Green, S. (2009). Continuous

quality improvement: effects on professional practice and healthcare

outcomes. Cochrane Database of Systematic Reviews, (4). Retrieved from

http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD003319.pub2/abst

ract doi:10.1002/14651858.CD003319.pub2

Campbell, C. (2001). Health Education Behavior Models And Theories-- A Review

Of The Literature - Part I Retrieved from

http://msucares.com/health/health/appa1.htm

Clarke, A. (1999). Changing attitudes through persuasive communication. Nursing

Standard, 13(30), 45-47.

Cohn, A. M., Hunter-Reel, D., Hagman, B. T., & Mitchell, J. (2011). Promoting

Behavior Change from Alcohol Use Through Mobile Technology: The Future

of Ecological Momentary Assessment. Alcoholism: Clinical and


35/50


Experimental Research, 35(12), 2209–2215. doi:10.1111/j.1530-

0277.2011.01571.x

Cole-Lewis, H., & Kershaw, T. (2010). Text Messaging as a Tool for Behavior Change

in Disease Prevention and Management. Epidemiologic Reviews , 32 (1 ),

56–69.

Cowan, L. T., Van Wagenen, S. A., Brown, B. A., Hedin, R. J., Seino-Stephan, Y.,

Hall, P. C., & West, J. H. (2013). Apps of Steel: Are Exercise Apps Providing

Consumers With Realistic Expectations?: A Content Analysis of Exercise

Apps for Presence of Behavior Change Theory . Health Education &

Behavior, 40 (2 ), 133–139.

de Silva-Sanigorski, A., Prosser, L., Hegde, S., Gussy, M. G., Calache, H., Boak, R.,.

Suyan, B. (2012). Community-based, population level interventions for

promoting child oral health. Cochrane Database of Systematic Reviews

(Issue 5. Art. No.: CD009837. DOI: 10.1002/14651858.CD009837).

Deeks, J. J., Higgins, J. P. T., Altman, D. G. (2011). Chapter 9: Analysing data and

undertaking meta-analyses. In G. S. Higgins JPT (Ed.), Cochrane Handbook

for Systematic Reviews of Interventions (Version 5.1.0). The Cochrane

Collaboration.

Department for International Development. (2003). Review of DFID Approach to

Social Marketing Annex 5: Effectiveness, efficiency and equity of social

marketing. London: DFID Health Systems Resource Centre/PSI Research

Division.

Dhaliwal, I., & Tulloch, C. (2012). From research to policy: using evidence from

impact evaluations to inform development policy. Journal of Development

Effectiveness, 4(4), 515-536.

Edejer, T. T. T. (2000). Disseminating health information in developing countries:

the role of the internet. Bmj , 321(7264), 797-800.

Edelman, J. R. (2000). Psychosocial Aspects of the Health Care Process. Essex:

Pearson Education Limited.

Edgar, T. M., Noar, S. M., & Freimuth, V. S. (Eds.) (2008). Communication

perspectives on HIV/AIDS for the 21st Century. New York: Lawrence

Erlbaum.

Effective Practice and Organisation of Care Group. (2009). Suggested risk of bias

criteria for EPOC reviews. Retrieved from

http://epoc.cochrane.org/sites/epoc.cochrane.org/files/uploads/Suggested

%20risk%20of%20bias%20criteria%20for%20EPOC%20reviews.pdf

Evans, W. D., Blitstein, J., Hersey, J. C., Renaud, J., & Yaroch, A. L. (2008).

Systematic review of public health branding. Journal of Health

Communication, 13(8), 721-741. doi: 10.1080/10810730802487364

Figueroa, J. P., Duncan, J., Byfield, L., Harvey, K., Gebre, Y., Hylton-Kong, T., &

Brathwaite, A. R. (2008). A comprehensive response to the HIV/AIDS

epidemic in Jamaica: a review of the past 20 years. West Indian Medical

Journal , 57 (6), 562-576.


36/50


Fowler, A. (2013). Striking a balance: A guide to enhancing the Effectiveness of

Non-Governmental Organisations in International Development.

Routeldge.

Ganann, R., Fitzpatrick-Lewis, D., Ciliska, D., Dobbins, M., Krishnaratne, S., Beyers,

J., Clay, F. (2010). Community-based interventions for enhancing access to

or consumption of fruit and vegetables (or both) among five to 18-year olds

(Protocol). Cochrane Database of Systematic Reviews (Issue 8. Art. No.:

CD008644. DOI: 10.1002/14651858.CD008644).

Glanz, K., & Bishop, D. B. (2010). The role of behavioral science theory in

development and implementation of public health interventions. Annual

review of public health, 31, 399-418.

Gordon, R., McDermott, L., Stead, M., & Angus, K. (2006). The effectiveness of

social marketing interventions for health improvement: what's the

evidence?. Public health, 120(12), 1133-1139.

Grier, S., Bryant, C. A. (2005). Social marketing in public health. Annual Review of

Public Health. 26, 319–39

Grilli, R., Ramsay, C., & Minozzi, S. (2002). Mass media interventions: effects on

health services utilisation. Cochrane Database of Systematic Reviews (1),

CD000389. doi: 10.1002/14651858.cd000389

Gurgaon, H. F. G. (2012). Behavior Change Communication Activities and

Achievements – Lessons Learned, Best Practices and Promising Approaches:

IFPS Technical Assistance Project (ITAP). 2012. USAID.

Hastings, G., McDermott, L., Angus, K., Stead, M., & Thomson, S. (2006). The

extent, nature and effects of food promotion to children: a review of the

evidence. Geneva: World Health Organisation.

Heierli, U. (2009). Market approaches that work for development. How the private

sector can contribute to poverty reduction. Swiss Agency for Development

and Cooperation – SDC.

Higgins, J., Deeks, J., & Altman, D. (2011). Chapter 16: Special topics in statistics. In

G. S. Higgins JPT (Ed.), Cochrane Handbook for Systematic Reviews of

Interventions (Version 5.1.0). The Cochrane Collaboration.

Hornik, R. (Ed.). (2002). Public health communication: Evidence for behavior

change. Routledge.

Hosein, E., Parks, W., & Schiavo, R. (2009). Communication-for-Behavioral-Impact:

An Integrated Model for Health and Social Change. In R. J. C. DiClemente,

R.A. and Kegler, M.C. (Ed.), Emerging Theories in Health Promotion

Practice and Research: Strategies for Improving Public Health (Second ed.,

pp. 535-550). San Francisco: John Wiley & Sons.

IDCG. (2012). Campbell International Development Coordinating Group: Protocol

and Review Guidelines: The Campbell Collaboration.

Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to

practice. Journal of Econometrics, 142(2), 615-635. Janz, N. K., & Becker, M.

H. (1984). The health belief model: A decade later. Health Education &

Behavior, 11(1), 1-47.


37/50


Janz, N. K., & Becker, M. H. (1984). The health belief model: A decade later. Health

Education & Behavior, 11(1), 1-47.

Jepson, R., Harris, F., Platt, S., & Tannahill, C. (2010). The effectiveness of

interventions to change six health behaviours: a review of reviews. BMC

Public Health, 10(1), 538.

Kaplan, W. A. (2006). Can the ubiquitous power of mobile phones be used to

improve health outcomes in developing countries. Global Health, 2(9), 399-

404.

Kavanagh, J., Oliver, S., Lorenc, T., Caird, J., Tucker, H., Harden, A., & Oakley, A.

(2009). School-based cognitive-behavioural interventions: A systematic

review of effects and inequalities. Health Sociology Review, 18(1), 61-78.

Kelly, M., Stewart, E., Morgan, A., Killoran, A., Fischer, A., & Threlfall, A. e. a.

(2009). A conceptual framework for public health: NICE's emerging

approach. Public Health, 123(1), 14-20.

Khan, M. H., et al., 2012, Effect of behaviour change communication on

breastfeeding practices in periurban area of Aligarh, Indian Journal of

Community Health, Vol 24, no 2.

Kotler, P., & Zaltman, G. (1971). Social marketing: an approach to planned social

change. The Journal of Marketing, 35, 3-12.

Knowlton LW, Phillips CC. (2009). The Logic Model Guidebook: Better Strategies

for Great Results. London, UK: SAGE Publications Ltd.

Leavy, J. E., Bull, F. C., Rosenberg, M., & Bauman, A. (2011). Physical activity mass

media campaigns and their evaluation: a systematic review of the literature

2003-2010. Health Education Research, 26(6), 1060-1085. doi:

10.1093/her/cyr069

Lecouturier, J., Rodgers, H., Murtagh, M. J., White, M., Ford, G. A., & Thomson, R.

G. (2010). Systematic review of mass media interventions designed to

improve public recognition of stroke symptoms, emergency response and

early treatment. BMC Public Health, 10, 784. doi: 10.1186/1471-2458-10-784

Lefebvre, R. C., & Flora, J. A. (1988). Social marketing and public health

intervention. Health Education & Behavior, 15 (3), 299-315.

Mah, M. W., Tam, Y. C., & Deshpande, S. (2008). Social marketing analysis of 2

years of hand hygiene promotion. infection control and hospital

epidemiology,29(3), 262-270.

Maibach, E., Abroms, L., & Marosits, M. (2007). Communication and marketing as

tools to cultivate the public's health: a proposed "people and places"

framework. BMC Public Health, 7 (1), 88.

Manoff, R. K. (1985). Social marketing: new imperative for public health. New

York. Praeger.

Marcus, B. H., Owen, N., Forsyth, L. H., Cavill, N. A., & Fridinger, F. (1998).

Physical activity interventions using mass media, print media, and

information technology. American Journal of Preventive Medecine, 15 (4),

362-378.


38/50


39/50


Pfeiffer, J. (2004). Condom social marketing, Pentecostalism, and structural

adjustment in Mozambique: a clash of AIDS prevention messages. Medical

Anthropology Quarterly, 18(1), 77-103.

Price, N. (2001). The performance of social marketing in reaching the poor and

vulnerable in AIDS control programmes. Health Policy and Planning, 16(3),

231-239.

Prochaska, J. O., & Velicer, W. F. (1997). The Transtheoretical Model of Health

Behavior Change. American Journal of Health Promotion, 12(1), 38-48. doi:

10.4278/0890-1171-12.1.38

R Core Team. (2013). R: A Language and Environment for Statistical Computing.

Vienna, Austria. Retrieved from http://www.R-project.org

Rogers, E. M. (2010). Diffusion of innovations. (4th edition) Simon and Schuster.

Rodgers, M., Sowden, A., Petticrew, M., Arai, L., Roberts, H., Britten, N., & Popay, J.

(2009). Testing methodological guidance on the conduct of narrative

synthesis in systematic reviews: Effectiveness of interventions to promote

smoke alarm ownership and function. Evaluation., 15(1):(Article), 49-73.

Rothman, J., and Tropman, J.E. (1987). Models of community organization and

macro practice: their mixing and phasing. In F.M. Cox et al. (Eds). Strategies

of Community Organization (4th Edition). Itasca, Illinois: Peacock.

Rowe, A. (2011). Presentation on the literature review of interventions to improve

health care performance. Early results of a systematic review to improve

health workers performance in low- and middle- income countries. Paper

presented at the 4th Annual NIH Conference on the Science of

Dissemination & Implementation: Policy & Practice, Bethesda, MD.

http://obssr.od.nih.gov/scientific_areas/translation/dissemination_and_im

plementation/DI2011/resources/4B%20Rowe%20Reviews%20of%20Emerg

ing%20Issues%20[Compatibility%20Mode].pdf (accessed 11/07/2014)

Rowe, A. (2013). Strategies to improve health worker performance in low income

settings - a systematic review. Paper presented at the IDEAS Seminar,

LSHTM, London, UK.

Royal, S., Kendrick, D., & Coleman, T. (2007). Promoting bicycle helmet wearing by

children using non-legislative interventions: systematic review and meta-

analysis. Injury prevention, 13(3), 162-167.

Ryan, R., Hill, S., Prictor, M., McKenzie, J., & Cochrane Consumers and

Communication Review Group. (2011). Study Quality Guide.

http://www.latrobe.edu.au/chcp/cochrane/resources.html (accessed

11/07/2014)

Schünemann, H. J., Oxman, A. D., Higgins, J. P. T., Vist, G. E., Glasziou, P., &

Guyatt, G. H. (2011). Chapter 11: Presenting results and ‘Summary of

findings' tables. In G. S. Higgins, J. P. T. (Ed.). Cochrane Handbook for

Systematic Reviews of Interventions (Version 5.1.0). The Cochrane

Collaboration.

Shapiro, J. R., Reba-Harrelson, L., Dymek-Valentine, M., Woolson, S. L., Hamer, R.

M., & Bulik, C. M. (2007). Feasibility and acceptability of CD-ROM-based


40/50


cognitive-behavioural treatment for binge-eating disorder. European Eating

Disorders Review, 15(3), 175–184. doi:10.1002/erv.787

Snyder, G., Linkov, F., & Laporte, R. (2007). Global Health Communications, Social

Marketing and Emerging Communication Technologies. In Markle, W. H.,

Fishe

riboli sasco communication protocol

Documents