Farmer field schools: a systematic review

www.3ieimpact.org Hugh Waddington

Farmer field schools: a

systematic review

International Initiative for Impact Evaluation

Hugh Waddington


Co-authors

• Birte Snilstveit

• Jorge Hombrados

• Martina Vojtkova

• Daniel Phillips

• Howard White


Agriculture starting to come back on the agenda

Source: Cabral and Howell 2012, ODI


Agricultural extension

• But age old questions remain:

– how to raise farmer productivity?

– how to reach the poorest and marginalised (eg

women)?

• Ag extension has been part of tool box forever but got a

bad rap in last two decades – e.g. rise and fall of T&V

• Participatory extension like Farmer Field Schools are

what is new, the latest fad "that works"


• Originally associated with

FAO and Integrated Pest

Management (IPM)

• Originated in response to

the overuse of pesticides in

irrigated rice systems in

Asia

• Belief that farmers need

confidence to reduce

dependence on pesticides,

through „discovery learning‟

• Now applied in 90+

countries, range of crops

and curricula

FFS history lesson


• Group of 25 farmers, meeting once a week in a designated field during the growing season

• Exploratory: facilitator encourages farmers to ask questions, and to seek answers, rather than lecturing or giving recommendations.

• Experimentation: group manages two plots

• Participatory: emphasis on social learning with exercises to build group dynamics

• Field days and follow-up activities may be provided for diffusion of message to neighbours

A „best practice‟ FFS


Types of curricula


Farmer field school

stylised ToC... Input 1 Training

of trainers Input 2 Field

school

Adoption

(FFS

participants)

Capacity

building (FFS

participants)

Capacity

building (FFS

neighbours)

Adoption

(FFS

neighbours)

Measured impacts: Yield, input-output ratio,

income, empowerment,

environmental

outcomes, health


Input 1 Training

of trainers Input 2 Field

school

Adoption

(FFS

participants)

Capacity

building (FFS

participants)

Capacity

building

(neighbours)

Adoption

(neighbours)

- Facilitators

adequately trained

- Farmers and

facilitators attend

sufficient meetings

- FFS synchronised

with planting

season

- Curriculum

relevant to

problems facing

farmers

-Farmer attitudes

changed

(convinced

message

appropriate)

- Relative

advantage over old

techniques

- Field

days/follow-up

- High degree of

social cohesion

- Geographical

proximity to other

farmers

(observation) or

market

(communication)

Measured impacts: Yield, input-output ratio,

income, empowerment,

environmental

outcomes. health

- New technology

appropriate

- Market access

- Favorable prices

- Environmental factors

including weather, soil

fertility

…with assumptions


Polarised debate on FFS

• "Studies reported substantial and consistent reductions

in pesticide use attributable to the effect of training. In a

number of cases, there was also a convincing increase

in yield due to training.... Results demonstrated

remarkable, widespread and lasting developmental

impacts” (Van den Berg 2004, FAO)

• “The analysis, employing a modified „difference-in-

differences‟ model, indicates that the program did not

have significant impacts on the performance of

graduates and their neighbors” (Feder et al. 2004)

• But how good are they really - what does a systematic

look at the evidence say?


Theory-based systematic review

• Review registered with Campbell Collaboration

• Uses theory of change to examine program mechanisms and outcomes along causal chain

• 3-part data review: – Quantitative review of effects (impact evaluations)

– Qualitative review of barriers and facilitators

– Global portfolio review of projects

• Integrated synthesis based around causal chain


• Population is farm households in low and middle income

countries (data collected and analysed at household level)

• Intervention: programmes explicitly referred to as „farmer

field school‟

• Outcomes: effectiveness across the causal chain

– Knowledge (+ attitudes): what was learnt?

– Adoption: did farmers utilise new technologies (methods of planting,

approach to disease/pest control, other inputs)?

– Impact on yields, revenues, environment, health, empowerment etc.

• Study designs:

– Effects: experimental, quasi-experimental with controlled comparison

(no treatment, pipeline, other intervention)

– Barriers/facilitators: qualitative with reporting on data collection

(CASP)

Review inclusion criteria (PICOS)


• Comprehensive search for published and

unpublished literature:

– General: SSCI, IBSS, EconLit,

– Subject specific: AgEcon, CAB Abstracts, Agricola,

US National Agricultural Library

– „Unpublished‟: JOLIS, BLDS, IDEAS, Google, Google

Scholar, Theses and Dissertations

• Hand search (journals, organisation websites)

• Literature snowballing (citation tracking)

• Contact key researchers and organisations

Search methods


1,112 abstracts

screened

751 excluded

312 full text sought

49 no access

183 Extension impact papers: 134 FFS

49 non-FFS

257 excluded

1453 abstracts

screened

27,866 titles screened

369 full text obtained

126 no access

186 excluded: 128 on relevance 58 on design (no

comparison)

134 FFS impact papers

80 individual FFS studies

25 qualitative

papers

Causal Chain

Analysis Effectiveness

20 individual

FFS studies

30 IE and sister

papers

11 individual

FFS studies

Qualitative

Synthesis BB+ Synthesis


• 93 FFS interventions: East Asia, South Asia, Latin America, Middle East, sub-Saharan Africa

– Cotton, rice, other cash crops, and food crops

– IPM, IPPM, IPNM, ICM, IWM

– Some with co-interventions (input support, marketing support)

• Design: No RCTs; quasi-experiments of varying quality (PSM, diff-in-diff, instrumental variables, Heckman, group means comparison)

• All effects measured relative to non-FFS farmers comparison; study arms include FFS-participants and ‘neighbouring’ farmers to measure spillovers (farmer-to-farmer diffusion)

• Small samples (approx. 200 farmers, often only a handful of villages) and short follow-up periods (most studies less than 2 years)

Characteristics of included impact evaluations


Internal validity assessment


Synthesis of outcomes across

the causal chain:

Knowledge adoption diffusion

agriculture yields net income (profits)

Environment

Health outcomes

Empowerment


Effect sizes

• Intermediate and endpoint outcomes

synthesised

• Standardised mean differences for outcomes

without „natural‟ scale unit and zero points

(knowledge and adoption indexes)

• Response ratios for outcomes based on ratio

scale (pesticide use, yields, income,

environment) and probabilities (health,

empowerment)


Positive

impacts on

knowledge

among

participants

NOTE: Weights are from random effects analysis

.

.

FFS participants

Huan et al., 1999 (Vietnam)

Endalew, 2009 (Ethiopia)

Price et al., 2001 (Philippines)

Rao et al., 2012 (India)

Reddy & Suryamani, 2005 (India)

Kelemework, 2005 (Ethiopia)

Mutandwa & Mpangwa, 2004 (Zimbabwe)

Dinpanah et al., 2010 (Iran)

Khan et al., 2007 (Pakistan)

Bunyatta et al., 2006 (Kenya)

Erbaugh, 2010 (Uganda)

Rebaudo & Dangles, 2011 (Ecuador)

Subtotal (I-squared = 93.3%, p = 0.000)

FFS neighbours


Reddy & Suryamani, 2005 (India)

Ricker-Gilbert et al, 2008 (Bangladesh)

Rebaudo & Dangles, 2011 (Ecuador)


ID

Study

0.02 (-0.06, 0.10)

0.27 (-0.06, 0.60)

0.42 (-0.17, 1.01)

0.43 (-0.02, 0.87)

0.45 (-0.04, 0.94)

0.54 (-0.22, 1.29)

0.59 (0.25, 0.92)

0.67 (0.41, 0.92)

0.79 (0.29, 1.29)

1.03 (0.65, 1.41)

1.14 (0.93, 1.34)

1.79 (1.17, 2.41)

0.66 (0.33, 1.00)

-0.13 (-0.68, 0.42)

0.05 (-0.45, 0.56)

0.17 (-0.25, 0.59)

0.38 (-0.15, 0.91)

0.13 (-0.12, 0.37)

ES (95% CI)

0.02 (-0.06, 0.10)

0.27 (-0.06, 0.60)

0.42 (-0.17, 1.01)

0.43 (-0.02, 0.87)

0.45 (-0.04, 0.94)

0.54 (-0.22, 1.29)

0.59 (0.25, 0.92)

0.67 (0.41, 0.92)

0.79 (0.29, 1.29)

1.03 (0.65, 1.41)

1.14 (0.93, 1.34)

1.79 (1.17, 2.41)

0.66 (0.33, 1.00)

-0.13 (-0.68, 0.42)

0.05 (-0.45, 0.56)

0.17 (-0.25, 0.59)

0.38 (-0.15, 0.91)

0.13 (-0.12, 0.37)

ES (95% CI)

Favours intervention

0-.5 0 .5 1 3


Reduced

pesticide

demand

among

participants

not

neighbours


.

.

FFS neighboursPananurak, 2010 (India)Khan et al., 2007 (Pakistan)Yamazaki & Resosudarmo, 2007 (Indonesia)Wu Lifeng, 2010 (China)Pananurak, 2010 (Pakistan)Labarta, 2005 (Nicaragua)Pananurak, 2010 (China)Praneetvatakul & Waibel, 2006 (Thailand)Khan et al., 2007 (Pakistan)Feder et al, 2004 (Indonesia)Subtotal (I-squared = 84.6%, p = 0.000)

FFS participantsYamazaki & Resosudarmo, 2007 (Indonesia)Birthal et al., 2000 (India)Yang et al., 2005 (China)Yorobe & Rejesus, 2011 (Philippines)Yang et al., 2005 (China)Khan et al., 2007 (Pakistan)Khalid, n.d. (Sudan)Rejesus et al, 2010 (Vietnam)Pananurak, 2010 (India)Mutandwa & Mpangwa, 2004 (Zimbabwe)Pananurak, 2010 (Pakistan)Amera, 2008 (Kenya)Pananurak, 2010 (China)Mancini et al., 2008 (India)Wu Lifeng, 2010 (China)Huan et al., 1999 (Vietnam)Van den Berg et al., 2002 (Sri Lanka)Praneetvatakul & Waibel, 2006 (Thailand)Murphy et al., 2002 Vietnam)Cole et al., 2007 (Ecuador)Ali & Sharif, 2011 (Pakistan)Khan et al., 2007 (Pakistan)Labarta, 2005 (Nicaragua)Feder et al, 2004 (Indonesia)Cavatassi et al., 2011 (Ecuador)Friis-Hansen et al., 2004 (Uganda)Subtotal (I-squared = 93.2%, p = 0.000)

IDStudy

0.54 (0.25, 1.15)0.61 (0.51, 0.74)0.67 (0.12, 3.88)0.68 (0.62, 0.76)0.78 (0.40, 1.49)0.99 (0.42, 2.33)1.11 (0.69, 1.79)1.15 (0.92, 1.43)1.20 (0.40, 3.53)1.30 (1.09, 1.55)0.88 (0.68, 1.14)

0.20 (0.01, 3.23)0.21 (0.17, 0.26)0.32 (0.21, 0.48)0.37 (0.18, 0.78)0.41 (0.36, 0.46)0.46 (0.39, 0.54)0.48 (0.31, 0.75)0.52 (0.24, 1.12)0.52 (0.30, 0.92)0.57 (0.36, 0.89)0.59 (0.41, 0.87)0.61 (0.52, 0.71)0.65 (0.50, 0.84)0.67 (0.46, 0.97)0.71 (0.64, 0.80)0.72 (0.62, 0.84)0.82 (0.74, 0.90)0.82 (0.68, 0.98)0.83 (0.75, 0.93)0.88 (0.68, 1.13)0.90 (0.75, 1.09)0.91 (0.28, 2.94)0.95 (0.39, 2.34)1.30 (1.08, 1.57)1.34 (0.99, 1.80)1.42 (1.09, 1.86)0.66 (0.56, 0.78)

ES (95% CI)

0.54 (0.25, 1.15)0.61 (0.51, 0.74)0.67 (0.12, 3.88)0.68 (0.62, 0.76)0.78 (0.40, 1.49)0.99 (0.42, 2.33)1.11 (0.69, 1.79)1.15 (0.92, 1.43)1.20 (0.40, 3.53)1.30 (1.09, 1.55)0.88 (0.68, 1.14)

0.20 (0.01, 3.23)0.21 (0.17, 0.26)0.32 (0.21, 0.48)0.37 (0.18, 0.78)0.41 (0.36, 0.46)0.46 (0.39, 0.54)0.48 (0.31, 0.75)0.52 (0.24, 1.12)0.52 (0.30, 0.92)0.57 (0.36, 0.89)0.59 (0.41, 0.87)0.61 (0.52, 0.71)0.65 (0.50, 0.84)0.67 (0.46, 0.97)0.71 (0.64, 0.80)0.72 (0.62, 0.84)0.82 (0.74, 0.90)0.82 (0.68, 0.98)0.83 (0.75, 0.93)0.88 (0.68, 1.13)0.90 (0.75, 1.09)0.91 (0.28, 2.94)0.95 (0.39, 2.34)1.30 (1.08, 1.57)1.34 (0.99, 1.80)1.42 (1.09, 1.86)0.66 (0.56, 0.78)

ES (95% CI)


1.1 .25 .5 1 2


Positive

impacts on

other

adoption

measures

among

beneficiaries


Overall (I-squared = 94.2%, p = 0.000)

Kelemework, 2005 (Ethiopia)


Mauceri et al., 2007 (Ecuador)

Rao et al., 2012 (India)

Ricker-Gilbert et al, 2008 (Bangladesh)

Bunyatta et al., 2006 (Kenya)

Endalew, 2009 (Ethiopia)

ID

Zuger 2004 (Peru)

Study

0.73 (0.14, 1.32)

0.70 (-0.28, 1.67)

1.46 (1.18, 1.73)

1.41 (0.96, 1.86)

0.11 (-0.33, 0.55)

0.92 (0.29, 1.55)

1.45 (1.04, 1.85)

0.24 (-0.09, 0.58)

ES (95% CI)

-0.41 (-0.71, -0.11)

0.73 (0.14, 1.32)

0.70 (-0.28, 1.67)

1.46 (1.18, 1.73)

1.41 (0.96, 1.86)

0.11 (-0.33, 0.55)

0.92 (0.29, 1.55)

1.45 (1.04, 1.85)

0.24 (-0.09, 0.58)

ES (95% CI)

-0.41 (-0.71, -0.11)


0-.5 0 .5 1 2 3


Increased

yields among

FFS-

beneficiaries

not

neighbours


.

.

FFS neighbours

Pananurak, 2010 (India)


Feder et al, 2004 (Indonesia)

Labarta, 2005 (Nicaragua)

Pananurak, 2010 (China)

Wu Lifeng, 2010 (China)

Pananurak, 2010 (Pakistan)

Yamazaki & Resosudarmo, 2007 (Indonesia)


FFS participants


Van Rijn, 2010 (Peru)

Naik et al., 2008 (India)



Rejesus et al, 2010 (Vietnam)


Wu Lifeng, 2010 (China)

Ali & Sharif, 2011 (Pakistan)


Gockowski et al., 2010 (Ghana)

Yang et al., 2005 (China)

Hiller et al., 2009 (Kenya)


Cavatassi et al., 2011 (Ecuador)

Davis et al, 2012 (Tanzania)

Birthal et al., 2000 (India)



Wandji et al., 2007 (Cameroon)

Mutandwa & Mpangwa, 2004 (Zimbabwe)

Palis, 1998 (Philippines)

Zuger 2004 (Peru)

Carlberg et al., 2012 (Ghana)

Yamazaki & Resosudarmo, 2007 (Indonesia)

Van den Berg et al., 2002 (Sri Lanka)

Davis et al, 2012 (Kenya)

Pande et al., 2009 (Nepal)


Orozco Cirilo et al., 2008 b) (Mexico)

Todo & Takahashi, 2011 (Ethiopia)


ID

Study

0.79 (0.63, 1.00)

0.97 (0.74, 1.26)

0.99 (0.97, 1.01)

1.00 (0.99, 1.01)

1.02 (0.98, 1.07)

1.03 (0.99, 1.08)

1.03 (0.86, 1.25)

1.43 (1.05, 1.96)

1.01 (0.98, 1.03)

0.80 (0.61, 1.05)

0.86 (0.63, 1.18)

0.89 (0.83, 0.96)

0.95 (0.92, 0.98)

0.97 (0.92, 1.02)

0.97 (0.72, 1.31)

0.98 (0.96, 1.01)

1.08 (1.03, 1.14)

1.09 (1.03, 1.15)

1.09 (1.04, 1.14)

1.14 (1.03, 1.25)

1.15 (0.94, 1.41)

1.17 (0.53, 2.56)

1.17 (0.97, 1.42)

1.22 (0.97, 1.53)

1.23 (1.00, 1.51)

1.24 (1.13, 1.36)

1.24 (1.01, 1.54)

1.32 (1.22, 1.42)

1.32 (1.07, 1.63)

1.36 (1.06, 1.73)

1.36 (0.97, 1.92)

1.44 (1.09, 1.92)

1.58 (1.19, 2.10)

1.67 (1.23, 2.26)

1.68 (1.30, 2.18)

1.81 (1.15, 2.84)

2.11 (1.25, 3.56)

2.52 (2.05, 3.11)

2.62 (2.23, 3.08)

2.71 (1.11, 6.60)

1.23 (1.16, 1.32)

ES (95% CI)

0.79 (0.63, 1.00)

0.97 (0.74, 1.26)

0.99 (0.97, 1.01)

1.00 (0.99, 1.01)

1.02 (0.98, 1.07)

1.03 (0.99, 1.08)

1.03 (0.86, 1.25)

1.43 (1.05, 1.96)

1.01 (0.98, 1.03)

0.80 (0.61, 1.05)

0.86 (0.63, 1.18)

0.89 (0.83, 0.96)

0.95 (0.92, 0.98)

0.97 (0.92, 1.02)

0.97 (0.72, 1.31)

0.98 (0.96, 1.01)

1.08 (1.03, 1.14)

1.09 (1.03, 1.15)

1.09 (1.04, 1.14)

1.14 (1.03, 1.25)

1.15 (0.94, 1.41)

1.17 (0.53, 2.56)

1.17 (0.97, 1.42)

1.22 (0.97, 1.53)

1.23 (1.00, 1.51)

1.24 (1.13, 1.36)

1.24 (1.01, 1.54)

1.32 (1.22, 1.42)

1.32 (1.07, 1.63)

1.36 (1.06, 1.73)

1.36 (0.97, 1.92)

1.44 (1.09, 1.92)

1.58 (1.19, 2.10)

1.67 (1.23, 2.26)

1.68 (1.30, 2.18)

1.81 (1.15, 2.84)

2.11 (1.25, 3.56)

2.52 (2.05, 3.11)

2.62 (2.23, 3.08)

2.71 (1.11, 6.60)

1.23 (1.16, 1.32)

ES (95% CI)


1.5 1 2 3


Increased

revenues

among

participants

of FFS and

FFS+


.

.

.

FFS neighbours







FFS participants



Waarts et al., 2012 (Kenya)



Naik et al., 2008 (India)

Van de Fliert 2000 (Indonesia)





FFS+ participants






ID

Study

0.93 (0.66, 1.32)

1.07 (1.00, 1.14)

1.13 (1.01, 1.26)

1.39 (0.66, 2.92)

1.51 (0.51, 4.45)

1.08 (1.03, 1.15)

0.28 (0.02, 3.48)

1.06 (0.68, 1.66)

1.14 (0.92, 1.41)

1.17 (1.08, 1.27)

1.23 (1.09, 1.40)

1.25 (1.09, 1.42)

1.31 (1.11, 1.55)

1.41 (1.19, 1.67)

1.53 (1.10, 2.15)

3.40 (1.94, 5.97)

1.28 (1.17, 1.41)

1.43 (1.19, 1.72)

2.00 (1.02, 3.94)

3.34 (1.56, 7.15)

4.61 (3.83, 5.56)

2.57 (1.18, 5.58)

ES (95% CI)

0.93 (0.66, 1.32)

1.07 (1.00, 1.14)

1.13 (1.01, 1.26)

1.39 (0.66, 2.92)

1.51 (0.51, 4.45)

1.08 (1.03, 1.15)

0.28 (0.02, 3.48)

1.06 (0.68, 1.66)

1.14 (0.92, 1.41)

1.17 (1.08, 1.27)

1.23 (1.09, 1.40)

1.25 (1.09, 1.42)

1.31 (1.11, 1.55)

1.41 (1.19, 1.67)

1.53 (1.10, 2.15)

3.40 (1.94, 5.97)

1.28 (1.17, 1.41)

1.43 (1.19, 1.72)

2.00 (1.02, 3.94)

3.34 (1.56, 7.15)

4.61 (3.83, 5.56)

2.57 (1.18, 5.58)

ES (95% CI)


1 .5 1 2 3


Limited knowledge spillovers among neighbours

explains lack of adoption and impact

Num complex practices known

Num intermediate practices known

Num simple practices known

ID

Study

-0.09 (-0.49, 0.32)

0.11 (-0.31, 0.53)

0.49 (0.11, 0.88)

ES (95% CI)

-0.09 (-0.49, 0.32)

0.11 (-0.31, 0.53)

0.49 (0.11, 0.88)

ES (95% CI)

Favours intervention 0-.5 0 .5 1 2


Reduced environmental risk factors


.

.

FFS participants


Praneetvatakul & Waibel, 2006 (Thailand)




FFS neighbours




Praneetvatakul & Waibel, 2006 (Thailand)


ID

Study

0.52 (0.32, 0.85)

0.54 (0.39, 0.76)

0.55 (0.41, 0.75)

0.82 (0.55, 1.23)

0.59 (0.49, 0.71)

0.58 (0.24, 1.41)

0.64 (0.37, 1.10)

0.69 (0.43, 1.11)

1.04 (0.32, 3.40)

0.68 (0.49, 0.93)

ES (95% CI)

0.52 (0.32, 0.85)

0.54 (0.39, 0.76)

0.55 (0.41, 0.75)

0.82 (0.55, 1.23)

0.59 (0.49, 0.71)

0.58 (0.24, 1.41)

0.64 (0.37, 1.10)

0.69 (0.43, 1.11)

1.04 (0.32, 3.40)

0.68 (0.49, 0.93)

ES (95% CI)


1 .1 .2 .5 1 2


Farmers feel empowered, more confident



Friis-Hansen & Duveskog, 2012 (Uganda)

Friis-Hansen & Duveskog, 2012 (Tanzania)

Friis-Hansen & Duveskog, 2012 (Kenya)


Rusike et al., 2004 (Zimbabwe)

ID

Study

Favours intervention 1.2 .5 1 2 3


Sensitivity analysis


Publication bias in evidence on yields

95% L ES 95%

U #

MA 1.10 1.18 1.25 23

Filled MA 1.00 1.07 1.14 30

Egger’s test: P=0.002


Sensitivity

analysis:

Yields by

risk of bias

status

High risk of

bias studies

over-

estimate

impacts


.

.

Overall (I-squared = 93.0%, p = 0.000)



Gockowski et al., 2010 (Ghana)

Todo & Takahashi, 2011 (Ethiopia)


Yamazaki & Resosudarmo, 2007 (Indonesia)Pananurak, 2010 (Pakistan)




Wu Lifeng, 2010 (China)Ali & Sharif, 2011 (Pakistan)

Rejesus et al, 2010 (Vietnam)

ID


Carlberg et al., 2012 (Ghana)



High risk of biasNaik et al., 2008 (India)

Medium risk of bias

Davis et al, 2012 (Kenya)

Zuger 2004 (Peru)

Davis et al, 2012 (Tanzania)

Dinpanah et al., 2010 (Iran)Pande et al., 2009 (Nepal)







Orozco Cirilo et al., 2008 b) (Mexico)

Wandji et al., 2007 (Cameroon)Mutandwa & Mpangwa, 2004 (Zimbabwe)


Study

1.23 (1.16, 1.32)

1.24 (1.13, 1.36)

1.35 (1.19, 1.52)

1.14 (1.03, 1.25)

2.71 (1.11, 6.60)

0.95 (0.92, 0.98)

1.67 (1.23, 2.26)1.24 (1.01, 1.54)

1.22 (0.97, 1.53)

1.32 (1.22, 1.42)

1.68 (1.30, 2.18)

1.08 (1.03, 1.14)1.09 (1.03, 1.15)

0.97 (0.72, 1.31)

ES (95% CI)

0.80 (0.61, 1.05)

1.58 (1.19, 2.10)

1.09 (1.04, 1.14)

1.17 (0.53, 2.56)

0.89 (0.83, 0.96)

1.81 (1.15, 2.84)

1.44 (1.09, 1.92)

1.23 (1.00, 1.51)

2.52 (2.05, 3.11)2.11 (1.25, 3.56)

0.97 (0.92, 1.02)

0.98 (0.96, 1.01)

1.15 (0.94, 1.41)

1.17 (0.97, 1.42)

1.10 (1.03, 1.17)

1.36 (0.97, 1.92)

2.62 (2.23, 3.08)

1.32 (1.07, 1.63)1.36 (1.06, 1.73)

0.86 (0.63, 1.18)

1.23 (1.16, 1.32)

1.24 (1.13, 1.36)

1.35 (1.19, 1.52)

1.14 (1.03, 1.25)

2.71 (1.11, 6.60)

0.95 (0.92, 0.98)

1.67 (1.23, 2.26)1.24 (1.01, 1.54)

1.22 (0.97, 1.53)

1.32 (1.22, 1.42)

1.68 (1.30, 2.18)

1.08 (1.03, 1.14)1.09 (1.03, 1.15)

0.97 (0.72, 1.31)

ES (95% CI)

0.80 (0.61, 1.05)

1.58 (1.19, 2.10)

1.09 (1.04, 1.14)

1.17 (0.53, 2.56)

0.89 (0.83, 0.96)

1.81 (1.15, 2.84)

1.44 (1.09, 1.92)

1.23 (1.00, 1.51)

2.52 (2.05, 3.11)2.11 (1.25, 3.56)

0.97 (0.92, 1.02)

0.98 (0.96, 1.01)

1.15 (0.94, 1.41)

1.17 (0.97, 1.42)

1.10 (1.03, 1.17)

1.36 (0.97, 1.92)

2.62 (2.23, 3.08)

1.32 (1.07, 1.63)1.36 (1.06, 1.73)

0.86 (0.63, 1.18)


1.5 1 2 3


Moderator analysis: high risk of bias excluded

Crop Effect size 95% confidence interval Num. estimates

I-squared

Rice 1.14 0.85 1.54 3 82.3% (p=0.004)

Cotton 1.09 1.06 1.12 4 0.0% (p=0.675)

Staples/veg 1.37 1.10 1.70 4 43.6% (p=0.150)

Cash crops (tea, coffee, cocoa)

0.86 0.63 1.18 1 n/a

Region

East Asia & Pacific

1.07 0.99 1.17 4 88.0% (p=0.000)

Latin America & Caribbean

1.04 0.74 1.46 2 67.6% (p=0.079)

South Asia 1.12 1.01 1.24 2 29.3% (p=0.234)

Sub-Saharan Africa

1.58 1.06 2.36 3 58.5% (p=0.090)

Length of follow-up Up to 2 years

1.14 1.06 1.23 7 51.3% (p=0.055)

More than 2 years

1.06 0.95 1.17 5 83.4% (p=0.000)


Summary of quant findings

• FFS increase knowledge and improve adoption

of the FFS practices (e.g., reduction in pesticide-

use)

• Without negatively affecting the yields and

incomes, on average increasing one or both

• Suggestions of farmers feeling empowered

• Limited, if any, spillovers: Some simple

knowledge may diffuse to neighbours, but not

complex

• Neighbours do not adopt the practices

consistently


But what were the barriers and facilitators of

these effects on outcomes?

•Full story of qualitative

synthesis: Birte

Snilstveit‟s

presentation Friday

9.30am


In brief, qualitative evidence highlights key

process and implementation factors

• Targeting and participation (interest, group dynamics)

• Appropriateness of the curriculum for the farmers

• Delivery of the curriculum (participatory)

• Facilitators facilitation skills, perception by the

participants

• Language of instruction and the way the ideas are

introduced

• Policy context (eg subsidies and promotion of pesticides)


Revised theory of change


• Protocol development crucial – piloting of searches, data collection tool and critical appraisal technique

• Early development of theory of change (with underlying assumptions)

• Balance between comprehensive study and budget: keep interventions narrow, careful consideration of inclusion criteria for causal chain analysis

• Iteration between review components required to produce integrated rather than parallel synthesis

• Integrated synthesis is resource intensive, particularly for large bodies of evidence such as FFS

Lessons for design of SRs


Thank you

Review available shortly:

http://campbellcollaboration.org/lib

/project/203/

Please visit:

www.3ieimpact.org/systematicrevi

ews

http://campbellcollaboration.org/lib/project/203/

http://campbellcollaboration.org/lib/project/203/

http://www.3ieimpact.org/systematicreviews

http://www.3ieimpact.org/systematicreviews

Documents

Farmer field schools: a systematic review