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Application of robotics and automation in pasture-grazed agriculture is in an emergent phase. Technology developers face significant challenges due to aspects such as the complex and dynamic nature of biological systems, relative cost of technology versus farm labor costs, and specific market characteristics in agriculture. Overlaying this are socio-ethical issues around technology development, and aspects of responsible research and innovation. There are numerous examples of technology being developed but not adopted in pasture-grazed farming, despite the potential benefits to farmers and/or society, highlighting a disconnect in the innovation system. In this perspective paper, we propose a “responsibility by design” approach to robotics and automation innovation, using development of batch robotic milking in pasture-grazed dairy farming as a case study. The framework we develop is used to highlight the wider considerations that technology developers and policy makers need to consider when envisaging future innovation trajectories for robotics in smart farming. These considerations include the impact on work design, worker well-being and safety, changes to farming systems, and the influences of market and regulatory constraints.

BACKGROUND: Dissociative seizures are paroxysmal events resembling epilepsy or syncope with characteristic features that allow them to be distinguished from other medical conditions. We aimed to compare the effectiveness of cognitive behavioural therapy (CBT) plus standardised medical care with standardised medical care alone for the reduction of dissociative seizure frequency. METHODS: In this pragmatic, parallel-arm, multicentre randomised controlled trial, we initially recruited participants at 27 neurology or epilepsy services in England, Scotland, and Wales. Adults (≥18 years) who had dissociative seizures in the previous 8 weeks and no epileptic seizures in the previous 12 months were subsequently randomly assigned (1:1) from 17 liaison or neuropsychiatry services following psychiatric assessment, to receive standardised medical care or CBT plus standardised medical care, using a web-based system. Randomisation was stratified by neuropsychiatry or liaison psychiatry recruitment site. The trial manager, chief investigator, all treating clinicians, and patients were aware of treatment allocation, but outcome data collectors and trial statisticians were unaware of treatment allocation. Patients were followed up 6 months and 12 months after randomisation. The primary outcome was monthly dissociative seizure frequency (ie, frequency in the previous 4 weeks) assessed at 12 months. Secondary outcomes assessed at 12 months were: seizure severity (intensity) and bothersomeness; longest period of seizure freedom in the previous 6 months; complete seizure freedom in the previous 3 months; a greater than 50% reduction in seizure frequency relative to baseline; changes in dissociative seizures (rated by others); health-related quality of life; psychosocial functioning; psychiatric symptoms, psychological distress, and somatic symptom burden; and clinical impression of improvement and satisfaction. p values and statistical significance for outcomes were reported without correction for multiple comparisons as per our protocol. Primary and secondary outcomes were assessed in the intention-to-treat population with multiple imputation for missing observations. This trial is registered with the International Standard Randomised Controlled Trial registry, ISRCTN05681227, and ClinicalTrials.gov, NCT02325544. FINDINGS: Between Jan 16, 2015, and May 31, 2017, we randomly assigned 368 patients to receive CBT plus standardised medical care (n=186) or standardised medical care alone (n=182); of whom 313 had primary outcome data at 12 months (156 [84%] of 186 patients in the CBT plus standardised medical care group and 157 [86%] of 182 patients in the standardised medical care group). At 12 months, no significant difference in monthly dissociative seizure frequency was identified between the groups (median 4 seizures [IQR 0-20] in the CBT plus standardised medical care group vs 7 seizures [1-35] in the standardised medical care group; estimated incidence rate ratio [IRR] 0·78 [95% CI 0·56-1·09]; p=0·144). Dissociative seizures were rated as less bothersome in the CBT plus standardised medical care group than the standardised medical care group (estimated mean difference -0·53 [95% CI -0·97 to -0·08]; p=0·020). The CBT plus standardised medical care group had a longer period of dissociative seizure freedom in the previous 6 months (estimated IRR 1·64 [95% CI 1·22 to 2·20]; p=0·001), reported better health-related quality of life on the EuroQoL-5 Dimensions-5 Level Health Today visual analogue scale (estimated mean difference 6·16 [95% CI 1·48 to 10·84]; p=0·010), less impairment in psychosocial functioning on the Work and Social Adjustment Scale (estimated mean difference -4·12 [95% CI -6·35 to -1·89]; p

Objective\ud We aimed to characterize the demographics of adults with dissociative (nonepileptic) seizures, placing emphasis on distribution of age at onset, male:female ratio, levels of deprivation, and dissociative seizure semiology.\ud \ud Methods\ud We collected demographic and clinical data from 698 adults with dissociative seizures recruited to the screening phase of the CODES (Cognitive Behavioural Therapy vs Standardised Medical Care for Adults With Dissociative Non‐Epileptic Seizures) trial from 27 neurology/specialist epilepsy clinics in the UK. We described the cohort in terms of age, age at onset of dissociative seizures, duration of seizure disorder, level of socioeconomic deprivation, and other social and clinical demographic characteristics and their associations.\ud \ud Results\ud In what is, to date, the largest study of adults with dissociative seizures, the overall modal age at dissociative seizure onset was 19 years; median age at onset was 28 years. Although 74% of the sample was female, importantly the male:female ratio varied with age at onset, with 77% of female but only 59% of male participants developing dissociative seizures by the age of 40 years. The frequency of self‐reported previous epilepsy was 27%; nearly half of these epilepsy diagnoses were retrospectively considered erroneous by clinicians. Patients with predominantly hyperkinetic dissociative seizures had a shorter disorder duration prior to diagnosis in this study than patients with hypokinetic seizures (P < .001); dissociative seizure type was not associated with gender. Predominantly hyperkinetic seizures were most commonly seen in patients with symptom onset in their late teens. Thirty percent of the sample reported taking antiepileptic drugs; this was more common in men. More than 50% of the sample lived in areas characterized by the highest levels of deprivation, and more than two‐thirds were unemployed.\ud \ud Significance\ud Females with dissociative seizures were more common at all ages, whereas the proportion of males increased with age at onset. This disorder was associated with socioeconomic deprivation. Those with hypokinetic dissociative seizures may be at risk for delayed diagnosis and treatment.

Objective\ud \ud We aimed to characterize the demographics of adults with dissociative (nonepileptic) seizures, placing emphasis on distribution of age at onset, male:female ratio, levels of deprivation, and dissociative seizure semiology.\ud Methods\ud \ud We collected demographic and clinical data from 698 adults with dissociative seizures recruited to the screening phase of the CODES (Cognitive Behavioural Therapy vs Standardised Medical Care for Adults With Dissociative Non‐Epileptic Seizures) trial from 27 neurology/specialist epilepsy clinics in the UK. We described the cohort in terms of age, age at onset of dissociative seizures, duration of seizure disorder, level of socioeconomic deprivation, and other social and clinical demographic characteristics and their associations.\ud Results\ud \ud In what is, to date, the largest study of adults with dissociative seizures, the overall modal age at dissociative seizure onset was 19 years; median age at onset was 28 years. Although 74% of the sample was female, importantly the male:female ratio varied with age at onset, with 77% of female but only 59% of male participants developing dissociative seizures by the age of 40 years. The frequency of self‐reported previous epilepsy was 27%; nearly half of these epilepsy diagnoses were retrospectively considered erroneous by clinicians. Patients with predominantly hyperkinetic dissociative seizures had a shorter disorder duration prior to diagnosis in this study than patients with hypokinetic seizures (P < .001); dissociative seizure type was not associated with gender. Predominantly hyperkinetic seizures were most commonly seen in patients with symptom onset in their late teens. Thirty percent of the sample reported taking antiepileptic drugs; this was more common in men. More than 50% of the sample lived in areas characterized by the highest levels of deprivation, and more than two‐thirds were unemployed.\ud Significance\ud \ud Females with dissociative seizures were more common at all ages, whereas the proportion of males increased with age at onset. This disorder was associated with socioeconomic deprivation. Those with hypokinetic dissociative seizures may be at risk for delayed diagnosis and treatment.

Background: Precision dairy technologies are principally developed by private companies. Research has shown these companies can lack farm systems expertise to support on-farm use and adaptation, leading to uncertainty about how to best use technologies on-farm. Support structures are required to facilitate learning and reduce uncertainty for farmers, however this currently represents an area of market failure. Methods: A timeline analysis methodology was used to explore roles of public and private organisations in the development of precision dairy farming in New Zealand. This timeline method facilitates documentation and understanding of the important stages of an innovation processes. We used a meta-analysis and expert knowledge to identify and describe these important stages. These were then analysed using the seven-stage Hekkert framework for innovation systems functions. Results: There were several key events in the development of PD in New Zealand. These included the Greenfields Robotic Milking project, instigation of the livestock traceability scheme (NAIT), evolution of dairy technology start-ups, and the influence of multi-national dairy technology companies. Discussion: PD technologies are complex in nature and require a collaborative approach for successful innovation and adoption. Commercial organisations vary in their ability to support the technologies on farm. Historically, physical technologies (such as sensors) were the main focus, however in recent years there has been significant activity in development on online platforms for collating and analysing data for farm management decision support. Successful uptake of these products by farmers will require enhanced data integration and transfer to minimise ‘computer time’ for farmers and maximise useability. Conclusion: The PD innovation system in New Zealand remains relatively immature and requires greater industry-level leadership to improve performance across the various innovation system functions. In the rapidly evolving agri-tech sector, a focus is required on more open innovation structures and building farmer skills and knowledge about technology options.

There is large variability in pasture grown and harvested on New Zealand dairy farms. Some of these differences are due to fixed factors such as rainfall, soil type, and temperature, while other factors could be remedied, for example improving pasture management, soil fertility and drainage. Of the aspects that could be remedied, it is expected that a substantial proportion would not be profitable to fix with current costs, knowledge, or technologies available in the near future. Of the proportion where it may be possible to fix cost-effectively, it was estimated that the net gain (after costs) is approximately $200 million per year to the dairy industry.

Increased precision in grazing management decisions requires regular pasture measurement and effective use of the data for enhanced decision-making. Technology adoption theory can help to provide insights on the incentives and barriers to uptake and on-farm adaptation of precision farming tools. In this study, we used an inductive workshop process with experts in grazing management software design and marketing to explore software adoption by farmers. Important factors included alignment of data for monitoring key performance indicators, using data for benchmarking and reporting, enabling farm team communication. Discontinued use by farmers was seen to be influenced by; technology features being misaligned with farmer practice, users not having the skills required to interpret data, practice change inertia, and farmers lacking the time to invest in learning. Future research aimed at understanding those farmers who apply ‘best practice’ in respect to grazing management, either with or without the use of precision farming tools, would guide better product development.

Background: Precision dairy technologies are principally developed by private companies. Research has shown these companies can lack farm systems expertise to support on-farm use and adaptation, leading to uncertainty about how to best use technologies on-farm. Support structures are required to facilitate learning and reduce uncertainty for farmers, however this currently represents an area of market failure. Methods: A timeline analysis methodology was used to explore roles of public and private organisations in the development of precision dairy farming in New Zealand. This timeline method facilitates documentation and understanding of the important stages of an innovation processes. We used a meta-analysis and expert knowledge to identify and describe these important stages. These were then analysed using the seven-stage Hekkert framework for innovation systems functions. Results: There were several key events in the development of PD in New Zealand. These included the Greenfields Robotic Milking project, instigation of the livestock traceability scheme (NAIT), evolution of dairy technology start-ups, and the influence of multi-national dairy technology companies. Discussion: PD technologies are complex in nature and require a collaborative approach for successful innovation and adoption. Commercial organisations vary in their ability to support the technologies on farm. Historically, physical technologies (such as sensors) were the main focus, however in recent years there has been significant activity in development on online platforms for collating and analysing data for farm management decision support. Successful uptake of these products by farmers will require enhanced data integration and transfer to minimise ‘computer time’ for farmers and maximise useability. Conclusion: The PD innovation system in New Zealand remains relatively immature and requires greater industry-level leadership to improve performance across the various innovation system functions. In the rapidly evolving agri-tech sector, a focus is required on more open innovation structures and building farmer skills and knowledge about technology options.