Overall animal welfare assessment reviewed. Part 1: Is it possible?

Several authors have concluded that scientists should not attempt to perform overall animal welfare assessment (OWA). They argue that scientists have continued to fail to make progress in this area and that value judgements are inherently involved in OWA for which science cannot provide answers. We take a more positive attitude toward OWA and argue that scientists should avoid creating a self-fulfilling prophecy. OWA is necessary for making actual moral and political decisions. Science has already accumulated much relevant information about welfare and this information should be applied in decision making. The task of OW A is to assess welfare based on knowledge of the biological needs of animals. Weighting of welfare relevant factors constitutes a problem. However, when scientists cannot provide empirical data to solve weighting issues, this does not mean that rational answers cannot be found, e.g. in the form of procedural rules. OWA is conceived as a problem of multi-criteria decision making with fuzzy information. It focuses on the descriptive aspect of welfare, i.e. on what the welfare status of the animals really is without taking an ethical stance. The welfare status of animals depends on their biology and on the way animals assess their own welfare. It does not depend on how it happens to be perceived by us. Even though OWA necessarily remains a human activity, it is not arbitrary, nor does it allow of multiple \u27correct\u27 answers. OWA is a descriptive activity that can achieve more and more accuracy as science proceeds

Overall animal welfare reviewed. Part 2: Assessment tables and schemes

In the scientific literature several attempts have been made to systematically assess the overall welfare-status of animals in relation to housing and management. This paper reviews assessment tables and schemes that have been constructed to this end. These tables and schemes have a tabular format that allows an assessment of housing systems using a list of welfare-relevant attributes (properties of the housing system). Rather than identifying deficits, the focus of this review is on finding positive recommendations for the purpose of developing a method for overall welfare assessment (OWA) on a scientific basis. The main recommendation is to use the tabular format as representation formalism for OWA. The concept of linked tables provides the key to performing OWA on a scientific basis in an explicit and systematic way

Overall animal welfare reviewed. Part 3: Welfare assessment based on needs and supported by expert opinion

Welfare concerns what matters to animals from their point of view. What matters to animals is their state of need. Satisfaction and frustration of needs are associated with emotional states, the subjective experience of which directly determines the welfare status of an animal. Because emotional states are difficult to assess, overall welfare assessment (OWA) is best approached as an assessment of needs. For actual OW A a list of needs must be formulated. Different authors have formulated different lists. From these lists a concept need-list was constructed. For validation the needs-based approach for OWA was discussed in interviews with experts (n = 21) in the field of ethology and other welfare related sciences. These experts generally used mental terminology to define welfare, but when asked to classify their definition of welfare, many preferred a definition in terms of measurable parameters or a combination of both mental terms (feelings) and measurables. Most experts believed that welfare can be assessed objectively and that the problem of OWA is indeed best approached through an assessment of needs. Experts differ as to the exact composition of the list of needs. A list of needs is formulated which we intend to use for OWA in the case of sows

Overall welfare assessment of pregnant sow housing systems based on interviews with experts

In interviews with 11 pig experts the main housing systems for pregnant sows were identified as tethering (T), individual housing in stalls (IS), group housing with stalls (GS), trickle feeding or biofix (B), electronic sow feeding (ESF), and outdoor housing with huts (O). The family pen system (Fam) was added as a reference system. The experts were asked to give a welfare score for each housing system. The 2 individual housing systems (mean scores: T=1.8; IS=2.3) scored significantly lower than more intensive indoor group housing systems (GS=5.4; B=5.3; ESF=6.2), and these scored lower than the more extensive systems (O=8.0; Fam=9.1; ANOVA, PP=0.008). The most important aspects for welfare assessment were space, substrate, feeding-related agonism and social parameters such as group size and group stability. Three different models were constructed to calculate welfare scores from the arguments given by the experts. When represented graphically the results seem comparable to the expert scores, although 2 of the 3 models differed significantly from the expert scores using analysis of variance. These results indicate that pig experts are able to perform overall welfare assessment in a rational way that allows modelling and that there is a consensus underlying welfare assessment. These outcomes provide support for the further development of a decision support system to assess farm animal welfare on a scientific basis

Age, physical activity motivation and perceived stress in minority girls

Background: Physical activity in childhood and adolescence helps support physical and emotional health. Purpose: The study aimed to investigate if age was related to motivation for physical activity in minority girls, and whether the relationship may be potentially mediated by psychological or physiological stress. Methods: This cross-sectional observational study recruited Latino and African American girls ages 8 – 12 years (n = 79) in Tanner stage 1 or 2 via purposive sampling. Intrinsic motivation and perceived stress were measured by self-report survey; morning salivary cortisol samples were taken to calculate cortisol awakening response to estimate biological stress reactivity. Results: Increased age was related to higher intrinsic motivation to engage in physical activity. Lower perceived stress and lower awakening cortisol response were associated with higher intrinsic motivation. Bootstrapped mediation results indicated perceived stress may be a pathway through which age impacts intrinsic motivation for physical activity. Conclusion: While motivation to engage in physical activity may increase with age, perceived stress may dampen this motivation, resulting in decreased physical activity. Interventions to help increase pre-adolescent girls’ engagement in active behaviors may benefit from reducing children’s perceptions of stress

Objectively Measured Physical Activity Is Negatively Associated with Plasma Adiponectin Levels in Minority Female Youth

Objective. To evaluate the relationship between adiponectin and physical activity (PA) in minority female youth. Methods. Plasma adiponectin was measured in 39 females (mean age 9.2 ± 0.9 years; 30 Latina, 9 African-American; 56% overweight). PA was assessed by accelerometry. Mean minutes per day spent in daily PA (DPA) (≥3 metabolic equivalents (METs)), moderate PA (MPA)(4–7 METs), vigorous PA (VPA)(≥7 METs), and moderate-to-vigorous PA (MVPA)(≥4 METs) were calculated. The association between adiponectin and PA, controlling for age, fat weight, lean weight, and insulin sensitivity (SI) was analyzed using linear regression. Results. Adiponectin correlated with fat weight (r = −0.43, P < .01) and SI (r = 0.52, P < .01). Minutes spent in DPA (β = −0.40, P = .02), MPA (β = −0.36, P = .04), or MVPA (β = −0.37, P = .03) were predictors of adiponectin in the adjusted model. Conclusions. Higher PA levels were related to lower adiponectin levels. Potential mechanisms include upregulation of adiponectin receptors or an increase in high-molecular weight adiponectin with increasing PA

Optimization of a Transdiagnostic Mobile Emotion Regulation Intervention for University Students:Protocol for a Microrandomized Trial

Background: Many university students experience mental health problems such as anxiety and depression. To support their mental health, a transdiagnostic mobile app intervention has been developed. The intervention provides short exercises rooted in various approaches (eg, positive psychology, mindfulness, self-compassion, and acceptance and commitment therapy) that aim to facilitate adaptive emotion regulation (ER) to help students cope with the various stressors they encounter during their time at university. Objective: The goals of this study are to investigate whether the intervention and its components function as intended and how participants engage with them. In addition, this study aims to monitor changes in distress symptoms and ER skills and identify relevant contextual factors that may moderate the intervention’s impact. Methods: A sequential explanatory mixed methods design combining a microrandomized trial and semistructured interviews will be used. During the microrandomized trial, students (N=200) will be prompted via the mobile app twice a day for 3 weeks to evaluate their emotional states and complete a randomly assigned intervention (ie, an exercise supporting ER) or a control intervention (ie, a health information snippet). A subsample of participants (21/200, 10.5%) will participate in interviews exploring their user experience with the app and the completed exercises. The primary outcomes will be changes in emotional states and engagement with the intervention (ie, objective and subjective engagement). Objective engagement will be evaluated through log data (eg, exercise completion time). Subjective engagement will be evaluated through exercise likability and helpfulness ratings as well as user experience interviews. The secondary outcomes will include the distal outcomes of the intervention (ie, ER skills and distress symptoms). Finally, the contextual moderators of intervention effectiveness will be explored (eg, the time of day and momentary emotional states). Results: The study commenced on February 9, 2023, and the data collection was concluded on June 13, 2023. Of the 172 eligible participants, 161 (93.6%) decided to participate. Of these 161 participants, 137 (85.1%) completed the first phase of the study. A subsample of participants (18/172, 10.5%) participated in the user experience interviews. Currently, the data processing and analyses are being conducted. Conclusions: This study will provide insight into the functioning of the intervention and identify areas for improvement. Furthermore, the findings will shed light on potential changes in the distal outcomes of the intervention (ie, ER skills and distress symptoms), which will be considered when designing a follow-up randomized controlled trial evaluating the full-scale effectiveness of this intervention. Finally, the results and data gathered will be used to design and train a recommendation algorithm that will be integrated into the app linking students to relevant content.</p

Go Figure? Body-Shape Motives are Associated with Decreased Physical Activity Participation Among Midlife Women

1 This study was designed to investigate the relationship between midlife women&apos;s physical activity motives and their participation in physical activity. Cross-sectional qualitative and quantitative data were collected from 59 midlife women, most of whom were well-educated European-Americans (mean age = 45.6 years). Body-shape physical activity motives (i.e., motives related to toning, shaping, and weight loss) were compared with all other types of physical activity motives combined. Participants with body-shape motives were significantly less physically active than those with non-body-shape motives (p &lt; .01). Negative affect toward physical activity was negatively associated with participation, but did not mediate the effect of physical activity motives on participation. Body Mass Index (BMI) was not related to physical activity motives or participation. Results suggest that body-shape motives might be associated with less physical activity participation than non-body-shape motives among midlife women