Iris Schöberl

Dyadic relationships and operational performance of male and female owners and their male dogs

In the paper we investigate how owner personality, attitude and gender influence dog behavior, dyadic practical functionality and the level of dog salivary cortisol. In three meetings, 12 female and 10 male owners of male dogs answered questionnaires including the Neo-FFI human personality inventory. Their dyadic behavior was video-taped in a number of test situations, and saliva samples were collected. Owners who scored highly in neuroticism (Neo-FFI dimension one) viewed their dogs as social supporters and spent much time with them. Their dogs had low baseline cortisol levels, but such dyads were less successful in the operational task. Owners who scored highly in extroversion (Neo-FFI dimension two) appreciated shared activities with their dogs which had relatively high baseline cortisol values. Dogs that had female owners were less sociable-active (dog personality axis 1) than dogs that had male owners. Therefore, it appears that owner gender and personality influences dyadic interaction style, dog behavior and dyadic practical functionality.

Algorithm-supported visual error correction (AVEC) of heart rate measurements in dogs, Canis lupus familiaris

Dog heart rate (HR) is characterized by a respiratory sinus arrhythmia, and therefore makes an automatic algorithm for error correction of HR measurements hard to apply. Here, we present a new method of error correction for HR data collected with the Polar system, including (1) visual inspection of the data, (2) a standardized way to decide with the aid of an algorithm whether or not a value is an outlier (i.e., “error”), and (3) the subsequent removal of this error from the data set. We applied our new error correction method to the HR data of 24 dogs and compared the uncorrected and corrected data, as well as the algorithm-supported visual error correction (AVEC) with the Polar error correction. The results showed that fewer values were identified as errors after AVEC than after the Polar error correction (p < .001). After AVEC, the HR standard deviation and variability (HRV; i.e., RMSSD, pNN50, and SDNN) were significantly greater than after correction by the Polar tool (all p < .001). Furthermore, the HR data strings with deleted values seemed to be closer to the original data than were those with inserted means. We concluded that our method of error correction is more suitable for dog HR and HR variability than is the customized Polar error correction, especially because AVEC decreases the likelihood of Type I errors, preserves the natural variability in HR, and does not lead to a time shift in the data.

Attachment security in companion dogs: adaptation of Ainsworth’s strange situation and classification procedures to dogs and their human caregivers

ABSTRACT This exploratory study describes the development of a classification system for dogs’ attachment security to caregivers that adheres closely to Ainsworth’s seminal methodology. Fifty-nine adult dogs and caregivers participated in a mildly threatening laboratory encounter with a stranger (TS) and the Strange Situation (SSP). Dog and attachment experts adapted Ainsworth’s classification system for the behavioral repertoire of the dog. Four potentially comparable patterns of attachment were identified. The proportions of secure and insecure classifications (61% and 39%) were similar to those found in human toddlers. Caregivers’ sensitivity to their dogs during the TS procedure significantly differentiated dogs with secure vs. insecure classifications Lower scores on the Active/excited personality scale on the Monash Canine Personality Questionnaire-Revised (MCPQ-R) also were related to secure classification. This system now makes it possible to compare directly the effects of human and dog attachment patterns on the health and emotional well-being of humans and dogs.