Anouk M B Veldhuis, Henriëtte Brouwer-Middelesch, Nienke Paarlberg, Angela Deterink, Thomas Dijkstra, Lourens Heres, Debora Smits, Thijs Poll, Sabine Stoelinga, Inge Santman-Berends
{"title":"Evaluation of a data-driven tool to monitor youngstock rearing in dairy herds: Perception by its users and validation of improvement options.","authors":"Anouk M B Veldhuis, Henriëtte Brouwer-Middelesch, Nienke Paarlberg, Angela Deterink, Thomas Dijkstra, Lourens Heres, Debora Smits, Thijs Poll, Sabine Stoelinga, Inge Santman-Berends","doi":"10.1016/j.prevetmed.2025.106637","DOIUrl":null,"url":null,"abstract":"<p><p>Since 2018, dairy farmers in the Netherlands have access to a census data-driven tool to monitor calf rearing quality, called \"KalfOK\". Participants (N ≈ 12,000; 95 % of the population of dairy farms) receive a quarterly farm report with a score ranging between 0 and 100 points. The score is built on points graded for the value of 12 indicators for youngstock rearing quality (e.g. 'percentage of live births'). This study aimed to validate KalfOK's performance to distinguish farms with either reduced or excellent calf health, by the assessment of 205 farm visits by independent veterinarians. In a second part of the study, KalfOK was evaluated by means of a questionnaire amongst 324 randomly selected dairy farmers. They were surveyed on their experiences with KalfOK and suggestions for improvement. Feasible suggestions were included in a scenario analysis to quantify the impact of these proposed changes on the performance of KalfOK. Results showed that KalfOK's sensitivity to distinguish farms with very high calf rearing quality is 83.3 % (95 % CI: 36-100), with a corresponding specificity of 63.8 % (95 % CI: 55-72). The sensitivity to detect farms with supposedly low calf rearing quality was estimated to be 83.3 % (95 % CI: 36-100), with corresponding specificity of 75.6 % (95 % CI: 67-83). Surveyed farmers made a number of suggestions for improvement of KalfOK related to alternative calculation of health indicators, such as adapting the temporal unit used for calculating indicators from quarterly to annually, and clemency in the event of perinatal mortality of twin/triplet calves. Scenario analyses revealed that such alternatives, perceived by farmers as improvement options, are not always in their interest as they either lead to lower scores or they reduce KalfOK's performance in distinguishing high and low performing farms. Results also revealed that about 50 % of the dairy farmers do not actively use the tool in their calf rearing management. This means that in order to improve uptake of KalfOK by farmers, substantial communication efforts should be made to change farmer's perceptions of KalfOK by emphasizing the tool's possibilities, limitations and added value.</p>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"244 ","pages":"106637"},"PeriodicalIF":2.4000,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Preventive veterinary medicine","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1016/j.prevetmed.2025.106637","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/31 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"VETERINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Since 2018, dairy farmers in the Netherlands have access to a census data-driven tool to monitor calf rearing quality, called "KalfOK". Participants (N ≈ 12,000; 95 % of the population of dairy farms) receive a quarterly farm report with a score ranging between 0 and 100 points. The score is built on points graded for the value of 12 indicators for youngstock rearing quality (e.g. 'percentage of live births'). This study aimed to validate KalfOK's performance to distinguish farms with either reduced or excellent calf health, by the assessment of 205 farm visits by independent veterinarians. In a second part of the study, KalfOK was evaluated by means of a questionnaire amongst 324 randomly selected dairy farmers. They were surveyed on their experiences with KalfOK and suggestions for improvement. Feasible suggestions were included in a scenario analysis to quantify the impact of these proposed changes on the performance of KalfOK. Results showed that KalfOK's sensitivity to distinguish farms with very high calf rearing quality is 83.3 % (95 % CI: 36-100), with a corresponding specificity of 63.8 % (95 % CI: 55-72). The sensitivity to detect farms with supposedly low calf rearing quality was estimated to be 83.3 % (95 % CI: 36-100), with corresponding specificity of 75.6 % (95 % CI: 67-83). Surveyed farmers made a number of suggestions for improvement of KalfOK related to alternative calculation of health indicators, such as adapting the temporal unit used for calculating indicators from quarterly to annually, and clemency in the event of perinatal mortality of twin/triplet calves. Scenario analyses revealed that such alternatives, perceived by farmers as improvement options, are not always in their interest as they either lead to lower scores or they reduce KalfOK's performance in distinguishing high and low performing farms. Results also revealed that about 50 % of the dairy farmers do not actively use the tool in their calf rearing management. This means that in order to improve uptake of KalfOK by farmers, substantial communication efforts should be made to change farmer's perceptions of KalfOK by emphasizing the tool's possibilities, limitations and added value.
期刊介绍:
Preventive Veterinary Medicine is one of the leading international resources for scientific reports on animal health programs and preventive veterinary medicine. The journal follows the guidelines for standardizing and strengthening the reporting of biomedical research which are available from the CONSORT, MOOSE, PRISMA, REFLECT, STARD, and STROBE statements. The journal focuses on:
Epidemiology of health events relevant to domestic and wild animals;
Economic impacts of epidemic and endemic animal and zoonotic diseases;
Latest methods and approaches in veterinary epidemiology;
Disease and infection control or eradication measures;
The "One Health" concept and the relationships between veterinary medicine, human health, animal-production systems, and the environment;
Development of new techniques in surveillance systems and diagnosis;
Evaluation and control of diseases in animal populations.