Background: Lameness diagnosis and treatment have important welfare and production consequences in dairy farming. Methods: A questionnaire examining factors affecting non‐steroidal anti‐inflammatory drug (NSAID) use and pain scores associated with 16 lameness scenarios was distributed among UK farmers, veterinarians, veterinary technicians and foot trimmers. Principal component analysis was used to allow investigation of patterns between different respondent demographics and lameness scenarios. Results: After correcting for multiple testing, no significant associations were found between pain perception component variables and any of the variables examined. For attitudes towards NSAID use, there was a significant association with job role, with veterinarians more likely to provide analgesia across all conditions than farmers ( p < 0.001). Both active digital dermatitis (DD) and trimming of a DD lesion were given high pain scores (median of 7 and 8 out of 10, respectively), but were less likely to be given NSAIDs than other conditions with lower pain scores. Limitations: This was a small, exploratory study, with potential for both confounding and limited power. Some of the variation seen between respondents may have been due to differential interpretation of the questions. Conclusions: While respondents broadly agreed on pain scores for each of the lameness scenarios, there was variability in NSAID use between job roles. Furthermore, NSAID use was less likely for some painful conditions, such as DD. This may lead to some cows being under‐analgesed, with consequent welfare implications.

Qualitative Behavioural Assessment (QBA) has been used at both the herd and individual levels as an indirect measure to assess changes in the emotional state in dairy cattle but has not been used in individual cattle to explore associations between emotional state and milk production over a lactation. The study assessed 114 individual cows over a 13-month period utilising QBA and milk production data on a single farm. QBA scores were analysed using Principal Component Analysis (PCA). A decrease in Principal Component 1 (PC1) was associated with an increase in scores for positive behavioural terms such as happy, relaxed, calm and content. An increase in Principal Component 2 (PC2) was associated with an increased score for terms such as active, playful and inquisitive. Analysis with mixed models showed that milk yield was significantly negatively associated with PC1 for first-lactation cows (estimate = −0.24, p = 0.016) whilst accounting for days in milk (DIM) and temporal dependence. Variations in daily milk yields, assessed using the log-transformed variance of deviations from individual lactation curves (LnVar), were significantly positively associated with PC1 (percentage change in variability = 3.63, p = 0.004). These results indicate that increased milk yield and reduced daily yield variation were associated with more positive behavioural QBA terms. Exploratory work using clustering of PCA scores from the first 30 DIM was associated with 100-day milk yield, with cows in the more positive clusters (cluster 2 for PC1 and cluster 2 for PC2) producing the greater yield volumes (PC1 cluster 2: estimate 529.4, p = 0.02; PC2 cluster 2: estimate 1158.5, p < 0.001). These findings suggest that cows with more positive emotion scores are associated with increased milk production and provides evidence for further exploration in this research area.