Digital versus traditional agricultural extension for promoting climate-adaptive grape farming in the West Bank of Palestine: A randomized controlled trial protocol.

Intervention description:
This randomized controlled trial evaluates two agricultural extension approaches for promoting climate-adaptive grape farming in the West Bank of Palestine, with a total duration of 40 months. A total of 795 rainfed grape farmers in Bethlehem and Hebron districts will be randomly assigned to either digital extension (treatment arm) or traditional extension services (control arm).

Treatment arm: digital extension intervention:
The treatment group receives a digital agricultural extension program designed to equip grape farmers with climate-adaptive and market-responsive farming techniques. This intervention is based on the "Improved Extension for Value-Added Agriculture" (EVAP) Extension Package, developed by the Palestinian Ministry of Agriculture in collaboration with the Japan International Cooperation Agency. EVAP is a localized adaptation of the Smallholder Horticulture Empowerment and Promotion (SHEP) approach, tailored to Palestine's agricultural context. The objective is to facilitate farmers' transition from subsistence-oriented practices to market-driven farming while building climate resilience.

Blended learning approach:
The intervention employs a blended learning model combining three components: (1) bi-monthly online training sessions (1-2 hours) following EVAP steps and aligned with the grape farming calendar; (2) continuous digital content sharing through instructional videos, photographs, and extension tips distributed by extension agents; and (3) real-time communication via WhatsApp groups enabling interactive discussions, problem-solving, peer knowledge exchange, and technical assistance.

Seven-step structured curriculum:
The curriculum includes seven steps to build farmer capacity and facilitate market linkage: (1) Extension program introduction and participant confirmation; (2) Awareness creation tour with demonstration videos and peer learning between early adopters and target farmers; (3) Market opportunity identification through stakeholder insights and virtual discussions; (4) Participatory planning for agricultural practice improvement addressing climate adaptation needs; (5) Farm record keeping training with standardized templates; (6) Tailored extension activities on climate-adaptive practices including water conservation, soil management, pest control, and varietal selection using farmer-to-farmer methodology; and (7) Profitability and program evaluation by farmers through profit analysis and feedback sessions.

Implementation scale and coverage:
The intervention will be delivered at the farmer level within each target village, with a minimum of ten participating grape farmers per village. Villages are randomly allocated to the treatment arm. This village-level clustering facilitates peer learning, collective problem-solving, and local support networks that sustain practice adoption beyond the intervention period.

Control arm: traditional extension services:
The control group receives standard Ministry of Agriculture extension services, representing existing practice in the region. This traditional approach, analogous to the Training and Visit system, includes periodic in-person farm visits, on-site technical guidance, printed material distribution, and reactive support based on farmer inquiries. This group serves as the baseline for comparing effectiveness, cost-efficiency, and scalability of digital versus traditional extension in a conflict-affected setting where mobility restrictions and resource constraints limit conventional extension reach.

2026-02-25

2028-02-25

1. Level and Quality of CABFPs Adoption:
A composite index measuring the depth, breadth, and quality of CABFP adoption among participating grape farmers. This index captures not only whether farmers adopt climate-adaptive practices, but also how well they implement them. The index will be constructed as a weighted score (ranging from 0 to 10) based on:
- Number of practices adopted
- Relative significance of each practice for climate adaptation
- Fidelity of implementation

2. Gross Margin from Grape Production (NIS/dunum):
The change in gross margin from grape production from baseline to endline, measured in New Israeli Shekels (NIS) per dunum.

The index incorporates five key climate-adaptive practices with differential weights reflecting their climate adaptation potential:
- Drought-resistant grape varieties (weight = 2)
- Soil moisture conservation techniques (weight = 2)
- Shade nets (weight = 1)
- Integrated pest management (weight = 1)
- Canopy management (weight = 2)
Data will be collected through farmer self-reports on adoption status and implementation methods, verified through direct field observations where logistically feasible.

Gross margin is calculated as:
Gross Margin = Total Revenue - Total Variable Costs
Where:
- Total Revenue includes all income from grape sales and grape-related products
- Total Variable Costs include direct production expenses: fertilizers, pesticides, water, hired labor, and other purchased inputs
- Unpaid family labor is excluded

This measure represents the return to the household's own labor, management, and fixed assets. Data will be collected through farmer recall supported by simplified record-keeping sheets provided to farmers during the intervention period.

Both outcomes will be measured during the post-harvest season at baseline and endline to ensure comparability and minimize seasonal confounding, allowing farmers to provide complete information about annual productivity and income.

The study will measure four secondary outcome variables at baseline (February–June 2025) and endline (February–April 2028):
1. Grape productivity index:
A composite index combining standardized measures of grape yield (kg/1,000 m²) and grape quality (0–4 scale) into a single productivity score, calculated as: Productivity Index = (0.6 × Standardized Yield) + (0.4 × Standardized Quality). The quality component is based on farmer ratings across five dimensions (size, color uniformity, firmness, sweetness, pest resistance), while the yield component uses a three-year baseline average of self-reported data, verified where possible, compared to endline measurements.

2. Extension service engagement index:
A composite measure quantifying the extent and quality of farmer interaction with agricultural extension services. This continuous variable (0–1) is calculated by averaging three equally weighted, normalized components: (a) Contact Frequency (interactions with traditional and digital channels); (b) Information Diversity (variety of sources consulted); and (c) Satisfaction (reported contentment with information quality, relevance, and timeliness).

3. Farmer capacity and self-efficacy:
This outcome measures the change in farmers' knowledge, skills, and confidence related to CABFP and climate resilience. Assessment will use a mixed-methods approach, drawing on proxy indicators within the survey (e.g., reported adoption of CABFP practices, participation in training, decision-making confidence) along with qualitative interviews with a subsample of farmers.

4. Cost-effectiveness:
This outcome evaluates the economic efficiency of the digital versus traditional extension modalities, measured using three key indicators: (a) Cost per farmer reached (total program cost / number of engaged farmers); (b) Cost per farmer adopting (total program cost / number of farmers adopting at least one CABFP); and (c) Cost-benefit ratio (total economic benefits from increased net income / total program costs).

(1). Grape Productivity Index:
The Grape Productivity Index is constructed to capture both quantity and quality dimensions of agricultural productivity. Construction involves four steps:
Step 1 - Yield Measurement: Grape yield is measured in kg/1,000 m² to standardize across farm sizes. Baseline yield is calculated as a three-year average of self-reported production data to reduce year-to-year variability. Self-reported data will be verified through field observations where feasible. Endline yield uses the same methodology.
Step 2 - Quality Measurement: Grape quality is assessed on a 0–4 scale based on farmer ratings across five dimensions: size (berry and cluster), color uniformity, firmness, sweetness, and pest resistance. Each dimension is rated 0–4, and the overall quality score is the average of the five dimensions.
Step 3 - Standardization: Both yield and quality measures are standardized (z-scores) to enable meaningful combination into a single index, ensuring neither component dominates due to differences in scale or variance.
Step 4 - Index Calculation: The final index is calculated as: Productivity Index = (0.6 × Standardized Yield) + (0.4 × Standardized Quality). The weights reflect the relative market importance of quantity versus quality in the Palestinian grape market, determined through consultation with market actors and agricultural experts.

(2). Extension service engagement index:

The Extension Service Engagement Index captures the multi-dimensional nature of farmer engagement with extension services, moving beyond simple contact counts to assess depth and quality of engagement. The index is constructed from three equally weighted components, each normalized to a 0–1 scale:

Component 1- Contact Frequency: Measures the number and frequency of farmer interactions with extension services across traditional and digital channels, including in-person visits, phone calls, WhatsApp group participation, and training attendance. Raw contact counts are normalized using min-max normalization.

Component 2- Information Diversity: Measures the variety of information sources consulted, including extension agents, fellow farmers, digital platforms, printed materials, radio/television programs, and input suppliers/market actors. The diversity score is calculated as the proportion of available sources accessed by the farmer.

Component 3 - Satisfaction: Measures farmer-reported satisfaction with extension services across three dimensions: information quality (accuracy, usefulness), information relevance (applicability to context), and information timeliness (availability when needed). Each dimension is rated on a Likert scale and averaged.
=> Final Index Calculation: Engagement Index = (Contact Frequency + Information Diversity + Satisfaction) / 3

(3). Framer capacity and self-efficacy:
This outcome is constructed using a mixed-methods approach combining quantitative proxy indicators and qualitative data:
Quantitative Components include: (1) Practice Adoption Breadth - number of different CABFPs attempted or adopted; (2) Training Participation- number of training sessions attended; (3) Decision-Making Confidence- Likert-scale ratings of confidence in decisions about variety selection, input application, climate response, and market opportunities; and (4) Self-Efficacy Scale- Likert-scale responses to statements about confidence in implementing climate-adaptive practices and overcoming climate challenges.
Qualitative Component: Semi-structured interviews with 30–50 farmers from treatment and control groups to explore perceived changes in knowledge and skills, confidence in applying practices, barriers to adoption, and learning preferences.
Integration: Quantitative components are standardized and combined into a composite Farmer Capacity Index using principal component analysis (PCA) or simple averaging of standardized scores. Qualitative findings triangulate and interpret quantitative results, providing contextual understanding of capacity development processes.

(4). Cost effectiveness:
Cost-effectiveness is assessed through three complementary metrics:
1. Cost per Farmer Reached = Total Program Cost / Number of Engaged Farmers
Total Program Cost includes personnel costs (extension agent salaries, facilitators), material costs (printed materials for control; digital platform development/maintenance for treatment), communication costs (WhatsApp data, website hosting), training costs (venue rental, refreshments), and administrative/overhead costs. Number of Engaged Farmers is defined as farmers with at least one meaningful interaction with extension services (threshold based on pilot data, e.g., attending one training or having three contacts with agents).

2. Cost per Farmer Adopting = Total Program Cost / Number of Farmers Adopting at Least One CABFP
This metric focuses on actual behavior change rather than just engagement. Number of Farmers Adopting is defined as farmers reporting adoption of at least one climate-adaptive practice by endline, verified through field observations where feasible.

3. Cost-Benefit Ratio = Total Economic Benefits / Total Program Costs
Total Economic Benefits is calculated as the aggregate increase in net income (gross margin) across all treatment farmers compared to control: Total Benefits = (Average Gross Margin Increase per Farmer in Treatment) × (Number of Treatment Farmers). A ratio greater than 1 indicates economic benefits exceed program costs, suggesting positive return on investment.
Data Collection: Program cost data will be collected through detailed financial tracking of all intervention-related expenditures, categorized by type (personnel, materials, communication) and extension modality (digital vs. traditional) to enable comparative analysis.

This study employs a two-arm, parallel-group, individual randomized controlled trial (RCT) design to evaluate the effectiveness of digital agricultural extension compared to traditional extension services for promoting climate-adaptive grape farming in the West Bank of Palestine.

(1). Study population and setting:
A total of 795 eligible rainfed grape farmers from the Bethlehem and Hebron governorates will be recruited for the trial. Eligible farmers are those who cultivate rainfed grapes as a primary agricultural activity, own or manage at least 1 dunum (1,000 m²) of grape vineyards, reside in the study area, and provide informed consent to participate.

(2). Randomization and allocation:
Participants will be randomly allocated on a 1:1 basis to either the intervention arm or the control arm, resulting in approximately 398 farmers per arm.

(3). Intervention arm: Digital extension service:
Farmers allocated to the intervention arm will receive digital agricultural extension services over a 40-month period. Extension agents serve as intermediaries to deliver information through digital platforms. Agents access implementation e-guidelines on one Google Sites-based website and share technical materials from another website with farmers through dedicated WhatsApp groups, where they also share instructional videos, facilitate peer-to-peer discussions, and provide real-time technical support. The digital extension program is structured around a seven-step curriculum based on the "Improved Extension for Value-Added Agriculture" (EVAP) Extension Package, focusing on CABFPs and market-oriented farming.

(4). Control arm: Traditional extension services:
Farmers allocated to the control arm will continue to receive the standard "business-as-usual" extension services provided by the Palestinian MOA. This traditional approach includes periodic in-person visits from extension agents, on-site technical guidance, distribution of printed materials, and reactive support based on farmer inquiries.

(5). Data collection and outcome measurement:
The trial's effectiveness will be determined by comparing key outcomes between the two arms. Data will be collected at baseline (pre-intervention, February–June 2025) and endline (post-intervention, February–April 2028), approximately 24 months apart. Both data collection rounds will be conducted during the post-harvest season to ensure comparability.

(5.1). Primary outcomes include: (1) Level and quality of CABFPs adoption, measured using a composite index (0–10 scale); and (2) Gross margin from grape production (NIS/dunum), calculated as total revenue minus total variable costs.

(5.2). Secondary outcomes include: (1) Grape productivity index, combining yield and quality measures; (2) Extension service engagement index, measuring farmer interaction with extension services; (3) Farmer capacity and self-efficacy, assessing knowledge, skills, and confidence; and (4) Cost-effectiveness, evaluating the economic efficiency of each extension modality.

(6). Statistical analysis:
The primary analysis will follow an intention-to-treat (ITT) principle, comparing outcomes between the intervention and control arms. Treatment effects will be estimated using appropriate regression models, adjusting for baseline values and relevant covariates. Statistical significance will be assessed at the 5% level (α = 0.05).

(7). Ethical considerations:
The study protocol has received ethical approval from the relevant institutional review board. All participants will provide written informed consent prior to enrollment. Participation is voluntary, and farmers may withdraw at any time without penalty.

Not available

Randomization will be done in office by computer. The allocation sequence will be generated using a computer-based randomization algorithm administered by an independent researcher with no involvement in fieldwork or data collection. Individual farmers within each of the 39 villages will be randomly allocated to either the intervention or control arm in a 1:1 ratio, stratified by village to account for local confounding factors.

Individual farmer. Randomization will be conducted at the individual farmer level within villages, stratified by village (39 villages total) (meaning villages are used as strata to ensure balance). Each eligible farmer within a village will be randomly allocated to either the intervention or control arm in a 1:1 ratio.

Yes

39 villages

795 farmers

398 farmers intervention arm (digital extension), 397 farmers control arm (traditional extension)
Note: The total is 795 farmers allocated 1:1, which gives approximately 398 per arm (with one arm having 397 to make the total exactly 795).

Primary Outcome—CABFP Adoption: The study is powered to detect a minimum detectable effect size (MDE) of 11 percentage points of absolute increase in the adoption of CABFPs, from a baseline adoption rate of 34.3% to 45.3% in the treatment group. This value corresponds to a Cohen's d of 0.32, representing a small-to-medium effect size. The sample size of 795 farmers (398 intervention, 397 control) provides 80% statistical power to detect this effect at a 5% significance level (two-sided test), accounting for 22% anticipated attrition over the 40-month intervention period. The MDE of an 11-percentage-point increase is grounded in existing literature on agricultural extension interventions, which have documented similar effect sizes ranging from 11% to 18.1% in comparable contexts.