Feedback loops in agricultural communication systems: Mechanisms for ensuring two-way information flow

Introduction

What happens to the advice that extension agents deliver once it leaves their hands? In most agricultural communication systems, information travels in a single direction from expert to farmer with little structured effort to capture whether that advice was understood or found useful [1] . This one-way model persists even though communication theory has long stressed that effective exchange requires active feedback from receivers [2] . In Hungary, the post-EU accession period brought new expectations for extension services, including demands for accountability and participatory approaches [3] . Yet field reports suggest that feedback collection from farmers is inconsistent and rarely formalized [4] . Communication scholars argue that feedback serves three purposes in agricultural contexts: confirming message reception, signaling misunderstandings, and providing local knowledge to improve future recommendations [5,6] . Several barriers weaken feedback transmission. Extension agents carry heavy caseloads that leave limited time for follow-up [7] . Farmers may feel reluctant to challenge expert advice [8] . And many organizations lack formal protocols for collecting and analyzing feedback [9] . Mobile surveys and interactive voice response systems have shown mixed results in Africa and South Asia [10] , but adoption of such tools in European extension programs has been slower [11] . This research addressed this gap by examining feedback loops in three agricultural districts of eastern Hungary, asking: a) Which feedback channels do farmers prefer b) What barriers weaken feedback loops and c) Does feedback completeness affect adoption of extension recommendations?

Theoretical framework

This research draws on Schramm's interactive communication model [6] , which treats both sender and receiver as active participants. Unlike linear models, Schramm's framework treats feedback as the mechanism through which mutual understanding is built. A second anchor comes from Rogers' diffusion of innovations theory [12] , specifically the concept of re-invention, which holds that adopters modify innovations based on local conditions. Feedback loops are the channels through which these modifications reach extension systems. The combination of these frameworks guided instrument design, variable selection, and interpretation of qualitative data. Qualitative data were coded using NVivo 12 following thematic analysis [13] , with 87.3% inter-coder agreement.

Material and Methods

Material

Instrument development and validation

The Feedback Loop Completeness Index (FLCI) was built on five indicators: a) Farmer provided verbal feedback after an extension visit, b) Farmer used a formal channel to send questions, c) Farmer received a response within 30 days, d) Farmer observed changes in subsequent advice, and e) Farmer rated the feedback process as satisfactory. Each item scored 0 or 1 (composite range: 0-5). Content validity was confirmed by four specialists. The FLCI showed acceptable internal consistency (Cronbach's α = 0.76) and test-retest reliability (r = 0.81, p<0.001).

Results

Discussion

The finding that face-to-face feedback channels outperformed digital alternatives echoes earlier work in East African extension contexts [10] and confirms that personal trust remains central to agricultural communication. Technology should supplement rather than replace human interaction in feedback systems. The strong association between feedback loop completeness and adoption aligns with Schramm's interactive model [6] and supports Rogers' observation that adopters who communicate experiences back to change agents sustain new practices more readily [12] . That the FLCI explained a larger share of variance than education or farm size www.extensionjournal.com underscores the independent contribution of communication quality to adoption outcomes. The barriers identified time pressure, low digital literacy, and missing protocols are not unique to Hungary. Research from the Netherlands [3] and sub-Saharan Africa [7] has reported similar constraints. What differs here is Hungary's fragmented extension governance, with responsibilities split between public agencies, university programs, and private consultants [4] , making it harder to standardize feedback practices. One practical takeaway is the value of scheduled feedback windows agents who set specific follow-up times reported higher completion rates in qualitative interviews.

Limitations

This research was limited to three districts in one Hungarian county, which may restrict generalizability. Self-reported feedback behaviors could be affected by social desirability.

Acknowledgement

Acknowledgements Funding sourcesThis research received support from the Hungarian Ministry of Agriculture through its rural extension development fund.

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