A mapping review of worldwide current and previous cohort research programmes in cats and dogs

Cohort research programmes follow individuals over time to enable study of effects from various factors on health or other outcomes. To date, the global distribution of formal cohort programmes in cats and dogs has not been mapped, and a comprehensive synthesis of their methodological characteristics is lacking. That limits methods improvement and wider adoption of cohort programmes in veterinary medicine. A mapping review methodology aligned with the JBI Manual for Evidence Synthesis was used to summarise existing cohort research programmes on cats and dogs worldwide. Electronic databases were searched (Embase, MEDLINE, Scopus, Web of Science) to identify eligible cohort papers, followed by a two-step selection process (title and abstract screening, full text screening) for paper inclusion. Information extracted at the individual cohort programme level covered: 1. location and veterinary specialty; 2. study design; 3. study variables; 4. collected data; 5. recruitment and retention strategies. Database searches yielded 6,777 unique papers, of which 73 met the inclusion criteria. Twenty-two programmes were identified, predominantly in the UK (8/22, 36%) or US (6/22, 27%) with 55% (12/22) involving dogs. Most of the programmes (18/22, 82%) aimed at disease prevention. Out of 19 programmes for which full-text papers were available, and therefore more information could be extracted, animal demographics were the most commonly considered study variable (15/19, 79%). The biggest reporting gaps were identified in the study planning phase, design, and programme management. Consequently, limited information was retrievable from the programmes papers to create learning opportunities for other researchers planning future cohort programmes. Improved or new reporting practices are needed to enhance knowledge sharing and promote cohort programmes in veterinary medicine. The study protocol was preregistered on the 27th of December 2023 (https://osf.io/wkg53/).