Welfare Assessment – Welfare Footprint Project

Quantifying Positive Animal Welfare in Individuals and Populations

editar — Tue, 12 Mar 2024 19:08:00 +0000

Beyond Suffering: A Framework for Quantifying Positive Animal Welfare in Individuals and Populations

Wladimir J Alonso, Cynthia Schuck-Paim

Center for Welfare Metrics, Brazil

https://welfarefootprint.org/team-mission

Main Takeaways

The Welfare Footprint Project has so far focused predominantly on quantifying negative affective experiences in animals, given pain’s greater impact on welfare.
However, positive affective states also play a crucial role in an animal’s quality of life, affecting long-term welfare through aspects such as immunity and resilience.
An operational definition of pleasure is proposed.
Categories of pleasure intensity are defined based predominantly on the degree of engagement with positive experiences.
The Pleasure-Track notation system is proposed, allowing for the description of the temporal evolution of the intensity of positive affective states.
Cumulative Pleasure is measured as the total time spent in positive affective states of different intensities.
The framework avoids equating the intensity categories of pleasure and pain, and acknowledges the complexity of balancing positive and negative affective states.
A graphic proposal is made for the visualization of Welfare Footprints, where they are expressed by a double bar chart representing the time spent in negative and positive affective states of different intensities (Cumulative Pain and Cumulative Pleasure).
animal experiences pain

INTRODUCTION

To inform efforts for the prevention and alleviation of animal suffering, the Welfare Footprint Project has so far primarily focused on quantifying negative affective experiences [1], often referred to simply as ‘pain.’ This emphasis is based on the understanding that negative experiences generally have a greater impact on well-being than positive ones, often preventing the experience of positive states [2]. From an evolutionary standpoint, pain is expected to be more noticeable than pleasure, as pain signals immediate threats to survival and reproduction, whereas positive experiences tend to reinforce behaviors that are beneficial in the medium term, like social bonding, learning, optimal foraging and mating. Failing to experience pleasure is not as immediately consequential as not responding to pain. This tendency to focus more on negative than positive events, known as negativity bias, is in fact a well-documented phenomenon in humans [3].

Still, positive states also play a crucial role in shaping an individual’s quality of life, and determining the extent to which it is ‘good’ [4], or at least ‘worth living’ [5]. Positive states are not only momentarily pleasurable; they also have long-term effects that help individuals overcome adversity [6]. For example, experiences of positive affect have been shown to naturally relieve pain (through endogenous analgesia), boost resilience to stress, and improve immune function [7–9]. Accordingly, the assessment of positive affect and the identification of conditions promoting it have gained substantial traction in the animal welfare sciences in recent years [10–12].

The goal of this contribution is to expand the Welfare Footprint framework to include not only the measurement of negative experiences in animals, but also positive states, or ‘pleasure’. Since the reasoning behind this metric is similar to that for assessing pain — already discussed in prior works [1,13] (see a 8 min video or a presentation at the Effective Altruism conference) — we do not describe these principles again here. Instead, we introduce the definitions and tools equivalent to those used for the quantification of negative affective states, now adapted for positive affect: the operational definitions of ‘pleasure’ and its four different intensity levels, the ‘Pleasure-Track’ notation system, and the ‘Cumulative Pleasure’. Additionally, with the full spectrum of affective experiences considered, we also introduce a visualization proposal, termed ‘Cumulative Affect’, to represent the overall Welfare Footprint of any population in a context and time scope of interest.

Operational definition of pleasure

We propose an operational definition of pleasure directly derived from the operational definition of pain previously proposed [14], as follows:

“Pleasure is a conscious experience, evolved to elicit or reinforce behaviors beneficial to an organism’s survival and/or reproduction. It is affectively and cognitively processed as a positive and dynamic sensation that can vary in intensity, duration, texture, spatial specificity, and anatomical location. Pleasure is characterized as ‘physical’ when primarily triggered by stimuli that are directly rewarding or enjoyable, and as ‘psychological’ when triggered by cognitive processes, memories, and emotional states. Depending on its intensity and duration, pleasure can override other adaptive instincts and motivational drives, leading to states of dependency and self-damage.”

Categories of Pleasure Intensity

In the Welfare Footprint Framework, pain intensity categories are operationally defined based on the assumption that more unpleasant sensations should be more disruptive, engaging a greater share of attention. [15,16]. This is rooted in the evolutionary expectation that the greater the threat, the more intense the signal should be to ensure it is prioritized over other functions and behaviors [17,18]. A similar approach can be used to define categories of pleasure intensity, with intensity categories defined based on the degree of engagement with positive experiences. First, the degree of engagement in experiences is likely to correspond to the hedonic value of these experiences [6]. A greater motivation to play, interact socially and explore is likely driven by a more intense positive experience. Second, the degree of motivation to engage in positive experiences is also likely to match their broader adaptive value [19]. Just as pain intensity often signals threat severity, pleasure intensity may correlate with the evolutionary importance of the activity, such as resource holding, learning, parental care, and mating (though maladaptive exceptions can be present, such as addiction in humans and feather-plucking in birds).

Similarly with the case of pain, here we propose the use of emphatic and universally recognized terms, focusing on concepts that reflect the degree of engagement with the pleasurable state. The definitions of pain intensities were first presented in a paper aimed at the medical audience [13], but designed to maintain their universality for non-human animals. This same broad approach is used to define pleasure intensities:

Satisfaction: low-intensity positive states, where an individual shows subtle signs of comfort or satisfaction associated with a physical sensation or meeting a non-essential need. These might include comfortable bedding conditions, grooming or basking in the sun. Engagement is present but not overwhelming, allowing the individual to easily shift attention to other stimuli or activities as needed.
Joy: positive states involving greater engagement in rewarding activities. Individuals may display enhanced vigor in play, stronger social bonding, or more or active engagement in highly preferred activities, such as foraging. Behaviors indicative of joy suggest a greater focus on these positive experiences, although they do not exclusively dominate the individual’s attention. The individual’s behavior is noticeably directed towards maintaining or enhancing the positive experience. Physiological indicators may include heightened autonomic responses (e.g., heart rate).
Euphoria: experiences in this category are intense and the primary focus of attention. Everything else might seem secondary. Euphoria might be observed in immersive play, mating rituals, or the pursuit and enjoyment of highly favored resources, such as a successful hunt. In some situations, this intense state might lead to spontaneous expressions of pleasure, such as vocalizations.
Bliss: At the peak of positive experiences, bliss represents a profound level of pleasure that pervades the individual’s sensory and emotional experience. It’s a sensation that transcends the ordinary. When experiencing bliss, the sensation of pleasure is so overwhelming that it eclipses other immediate needs or environmental stimuli for the duration of the experience. The world outside fades away as the individual is consumed by this all-encompassing state. Examples could be orgasmic states, reuniting with socially significant partners that are long missing, or the encounter of extremely positive conditions after prolonged periods of stress and hardship. Blissful states are expected to be rare and of short duration. pain

Just as we recently included the category ‘no pain’ as an additional intensity level (zero pain), it is also convenient, whenever relevant, to include the category ‘no pleasure,’ which represents the hypothesis that no positive affective states are experienced over the period of interest.

Pleasure-Tracks

The Pleasure-Track is a notation system analogous to the Pain-Track [13], where hypotheses on the temporal evolution and intensity of positive affective states are described. To this end, each experience is atomized into a level of analysis that is justifiable through empirical evidence. This is done by decomposing each experience into meaningful time segments, where each time segment is characterized by an expected intensity. Next, hypotheses about the intensity and duration of the experience at each of these segments can be informed by empirical evidence.

To illustrate the concept of a Pleasure-Track, we consider the hypothetical intensity and duration of play bouts in young calves, as follows: (Phase I) the play session begins with calves engaging in light play or exploration. This includes behaviors such as gently nudging or sniffing play objects, or light social interactions with other calves. The engagement is present but not overwhelming, allowing the calves to remain aware of their surroundings and easily shift their focus to other stimuli. As the play behavior escalates (Phase II), calves enter a state characterized by more vigorous activities such as running, jumping, and robust social play like head-butting or chasing. The calves show a clear focus on these rewarding activities, with their behavior directed towards maintaining or enhancing the experience. Physiological indicators might include increased heart rate or more expressive body language, reflecting their engagement in the play. The peak of the play experience (Phase III) is where the activity becomes the primary focus of the calves’ attention, with calves fully immersed in play, displaying spontaneous expressions of pleasure such as vocalizations or exuberant body movements. After reaching the peak of excitement, the intensity of play begins to decrease. Calves may start to engage in less vigorous activities, such as slower running or gentle nudging, as they start to wind down from the high energy play. This stage (Phase IV) is characterized by a gradual reduction in the intensity of their actions and a shift towards more relaxed behaviors. When the play bout concludes (Phase V) calves often display behaviors indicative of relaxation. This may include lying down, social grooming, or simply resting in close proximity to their playmates. The Pleasure-Track below summarizes these hypothetical ethological observations for a group of calves. Average phase durations are also hypothetical, and in real scenarios are expected to vary with factors such as the species, age, space available, group size, climatic conditions, time of day, and hunger [20].

As with the Pain-Track, the Pleasure-Track is designed to capture situations in which there is uncertainty in the classification of the intensity of pleasure. Therefore, probabilities are used to represent how likely it is that each category of pleasure intensity is experienced. Uncertainty (or natural variation) regarding how long each phase of the experience lasts is captured in the range of values at the bottom row of each temporal segment. The Pleasure-Track illustrated above is hypothetical, but in real situations, each numerical input should be based on a thorough review of evidence from various sources. Because evidence will be often limited, criticism of the proposed values should be always encouraged.

Cumulative Pleasure (individual level)

Like with estimates of cumulative time in negative states (‘Cumulative Pain’), it is also possible to estimate ‘Cumulative Pleasure’, namely the time spent in positive affective states of different intensities, as follows:

The assessment of Cumulative Pleasure for an individual over a certain period or even their lifetime, can be also established by determining the cumulative impact of all the positive events experienced. Similar to negative experiences, this is best represented as the sum of the time spent in positive states from all these events, whether they happen sequentially or simultaneously. This also includes events that happen repeatedly. For instance, if young calves play as described in the hypothetical scenario 1-8 times a day for 4 weeks, the Cumulative Pleasure for each calf would be a total of approximately 15-130 minutes of Euphoria, 1 to 7.3 hours of Joy, and 1.7 to 13.3 hours of Satisfaction. This is the of the estimates shown in the Pleasure-Track, daily frequency of playing bout and total number of days playing.

Of course, different positive experiences can interact with each other in various ways, both physically and psychologically. These effects, when potentially leading to changes in the outcomes, must be investigated on a case-by-case basis.

Cumulative Pleasure (population level)

Cumulative Pleasure can be also calculated at the population level. This requires accounting for differences in the exposure of population members to different positive experiences. This is achieved by weighting estimates by the prevalence of each experience, which enables determining the cumulative time in pleasure experienced by an average member of the population. For example, in the hypothetical scenario of play in calves, Cumulative Pleasure could be weighted by the proportion of the calf population playing in the period of interest. For instance, if 50-90% of the calves played over the period of two weeks, Cumulative Pleasure for the average population member over this period would be the product of this prevalence and Cumulative Pleasure for each individual over the two weeks (resulting in 15-130 minutes of Euphoria, 59-440 minutes of Joy and 100-800 minutes of satisfaction)

As with estimates of time spent in pain, we don’t combine the four categories of pleasure intensity into a single one. This is because, as thoroughly discussed for pain [21], there are no empirical references to establish a weighting system between the intensity categories, hence a single scale of pleasure.

A notation proposal for Welfare Footprints

By considering positive experiences, Welfare Footprints can be expressed as the time spent in negative and positive affective states of different intensities, i.e., Cumulative Pain and Cumulative Pleasure. To help visualize these effects, we propose to present Welfare Footprints as a double bar chart, as illustrated in the examples below. This graphical representation juxtaposes the time spent in negative affective states against the time spent in positive affective states, across various intensities. The figure illustrates two footprints, depicting the distribution of time spent by an individual (or population, if the prevalence of different pains and pleasures are factored in the analysis) at each intensity of pain and pleasure (note that the quality of life depicted in the first Welfare Footprint [A] is clearly better than in the second [B]):

The time units used in the chart for each intensity category (seconds, hours, days, and months) are flexible and can be adjusted. However, because of this flexibility, it is crucial to always specify the units in the chart.

Because positive and negative intensities are displayed side by side, it is important to reiterate that no equivalence is implied. For instance, whether 10 seconds on the most intense form of pleasure (‘Bliss’) can be considered a direct counterpart of 10 seconds under the most intense form of pain (‘Excruciating’) remains to be determined.

Further Thoughts

The welfare of sentient organisms is shaped by a complex interplay of positive and negative affective states [6,19,22]. While combining both positive and negative experiences would offer a fuller picture of their affective lives, there are many challenges to measure or compare these states ethically or quantitatively [5,23–27]. For example, Shriver [26] challenges the idea that pleasure and pain are just two ends of a continuum, pointing out that these states are driven by different cognitive processes, contribute differently to overall well-being, and have separate relationships with motivational systems. Considering these complexities, we do not attempt estimating how cumulative time in pain and pleasure might balance each other out. Instead, we focus on describing and measuring these affective states in a transparent and relatable way: by estimating time spent in states of pleasure and pain, at different levels of intensity.

We still maintain that negative states have a disproportionate impact on an individual’s life and welfare. Pain, especially when severe, can prevent the possibility of positive experiences. However, positive experiences and states are valuable, especially when more intense sources of pain have already been mitigated. Therefore, Welfare Footprints must not overlook this aspect. This text is aimed at incorporating positive experiences into the Welfare Footprint framework. Welfare Footprints that focus solely on pain are already valuable (especially for addressing the extreme situations many captive animals face), but a more comprehensive approach that includes positive experiences can provide a richer assessment. This complete version of a Welfare Footprint can thus better guide animal welfare policies, inform advocacy groups, and enhance public awareness about the ethical implications of animal use.

References

1. Alonso WJ, Schuck-Paim C. The Comparative Measurement of Animal Welfare: the Cumulative Pain Framework. In: Schuck-Paim C, Alonso WJ, editors. Quantifying Pain in Laying Hens. Independently published. https://tinyurl.com/bookhens; 2021.
2. Schuck-Paim C, Alonso WJ. How attention modulates the perceived intensity and duration of simultaneous affective experiences:Implications for refining Cumulative Pain estimates and for determining the potential for positive welfare. In: Welfare Footprint Project [Internet]. 16 Apr 2023 [cited 5 May 2023]. Available: https://welfarefootprint.org/2023/04/16/method-refinement-attention/
3. Norris CJ. The negativity bias, revisited: Evidence from neuroscience measures and an individual differences approach. Soc Neurosci. 2021;16: 68–82.
4. Rowe E, Mullan S. Advancing a “Good Life” for Farm Animals: Development of Resource Tier Frameworks for On-Farm Assessment of Positive Welfare for Beef Cattle, Broiler Chicken and Pigs. Animals. 2022;12: 565.
5. Yeates J. Better to have lived and lost – the concept of a life worth living. In: Butterworth A, editor. Animal Welfare in a Changing World. CAB International; 2018. pp. 162–170.
6. Leknes S, Tracey I. A common neurobiology for pain and pleasure. Nat Rev Neurosci. 2008;9: 314–320.
7. Yeates JW, Main DCJ. Assessment of positive welfare: a review. Vet J. 2008;175: 293–300.
8. Moskowitz JT, Saslow LR. Health and psychology: The importance of positive affect. In: Tugade MM, editor. Handbook of positive emotions (pp. New York, NY, US: The Guilford Press, xv; 2014. pp. 413–431.
9. Gentle MJ. Attentional Shifts Alter Pain Perception in the Chicken. Anim Welf. 2001;10: 187–194.
10. EU. Action project to provide the background for including positive welfare in farm animal welfare assessment. In: LIFT – COST ACTION [Internet]. Super Admin; 2022-2026 [cited 28 Feb 2024]. Available: https://liftanimalwelfare.eu/
11. Mellor DJ. Animal emotions, behaviour and the promotion of positive welfare states. N Z Vet J. 2012;60: 1–8.
12. Mellor DJ. Updating Animal Welfare Thinking: Moving beyond the “Five Freedoms” towards “A Life Worth Living.” Animals (Basel). 2016;6. doi:10.3390/ani6030021
13. Alonso WJ, Schuck-Paim C. Pain-Track: a time-series approach for the description and analysis of the burden of pain. BMC Res Notes. 2021;14: 229.
14. Alonso WJ, Schuck-Paim C. A Novel Proposal for the Definition of Pain. pre-print (OSF). 2023; 2.
15. Barclay RJ, Herbert WJ, Poole T. The disturbance index : a behavioural method of assessing the severity of common laboratory procedures on rodents. UFAW, Universities Federation for Animal Welfare; 1988.
16. Eccleston C, Crombez G. Pain demands attention: a cognitive-affective model of the interruptive function of pain. Psychol Bull. 1999;125: 356–366.
17. Merker B. Drawing the line on pain. Animal Sentience: An Interdisciplinary Journal on Animal Feeling. 2016;1: 23.
18. Mellor DJ, Beausoleil NJ, Littlewood KE, McLean AN, McGreevy PD, Jones B, et al. The 2020 Five Domains Model: Including Human-Animal Interactions in Assessments of Animal Welfare. Animals (Basel). 2020;10. doi:10.3390/ani10101870
19. Mellor DJ. Positive animal welfare states and encouraging environment-focused and animal-to-animal interactive behaviours. N Z Vet J. 2015;63: 9–16.
20. Whalin L, Weary DM, von Keyserlingk MAG. Understanding Behavioural Development of Calves in Natural Settings to Inform Calf Management. Animals (Basel). 2021;11. doi:10.3390/ani11082446
21. Schuck-Paim C, Alonso WJ, Hamilton C. Short agony or long ache: comparing sources of suffering that differ in duration and intensity. Effective Altruism Forum. 2024. Available: https://forum.effectivealtruism.org/editPost?postId=C2qiY9hwH3Xuirce3)
22. Berridge KC, Kringelbach ML. Neuroscience of affect: brain mechanisms of pleasure and displeasure. Curr Opin Neurobiol. 2013;23: 294–303.
23. Reimert I, Webb LE, van Marwijk MA, Bolhuis JE. Review: Towards an integrated concept of animal welfare. Animal. 2023;17 Suppl 4: 100838.
24. Poirier C, Bateson M, Gualtieri F, Armstrong EA, Laws GC, Boswell T, et al. Validation of hippocampal biomarkers of cumulative affective experience. Neurosci Biobehav Rev. 2019;101: 113–121.
25. Suffering and happiness: Morally symmetric or orthogonal? In: Center for Reducing Suffering [Internet]. 9 Sep 2020 [cited 29 Feb 2024]. Available: https://centerforreducingsuffering.org/research/suffering-and-happiness-morally-symmetric-or-orthogonal/
26. Shriver A. The Asymmetrical Contributions of Pleasure and Pain to Subjective Well-Being. RevPhilPsych. 2014;5: 135–153.
27. Tomasik B. Are Happiness and Suffering Symmetric? [cited 29 Feb 2024]. Available: https://reducing-suffering.org/happiness-suffering-symmetric/

Could Transparency Interntional be a model for improved animal welfare?

editar — Sat, 24 Feb 2024 23:03:03 +0000

Could Transparency International Be a Model to Improve Farm Animal Welfare?

Cynthia Schuck-Paim, Wladimir J Alonso,

February 24, 2024
11:03 pm

In a recent article shared on the Effective Altruism Forum, we discuss a new way to help farm animals. Drawing inspiration from the work of Transparency International, we explore the potential of applying similar principles to improve farm animal welfare.

Key Points:

The Challenge of Transparency: Lack of transparency enables companies to circumvent reforms and prevents assessing the true effectiveness of animal welfare policies.
Promoting Accountability: Increased transparency would promote accountability, compliance with standards, and enhancement of welfare practices.
Proposed Initiatives: We propose the creation of a dedicated organization focused on enhancing transparency in animal welfare. An organization focused on transparency could develop reporting frameworks, auditing processes, traceability systems, sourcing policies requiring transparency, and welfare labeling schemes.
Engaging Consumers: Increased consumer awareness through transparent labeling, traceability, sourcing policies, and educational campaigns could help bridge the gap between preferences and realities.
Potential Areas of Work: Transparency initiatives could include public sharing of independent audit results, animal-based health monitoring, stockmanship qualifications, slaughter line inspections, and transparency rankings of companies.

Read the full article on the Effective Altruism Forum

Short agony or long ache? Comparing intensity and duration of pain

editar — Tue, 20 Feb 2024 21:48:30 +0000

Short agony or long ache: comparing sources of suffering that differ in duration and intensity

Cynthia Schuck-Paim; Wladimir J. Alonso; Cian Hamilton

Summary

The Welfare Footprint framework quantifies the cumulative load of affective experiences an individual, or population, experiences over a period of time. Although applicable to affective states of positive and negative valence, it is primarily focused on the latter. Here, evidence-based estimates of the time spent in pain of four intensities (Annoying, Hurtful, Disabling, and Excruciating) are used to quantify suffering in different scenarios, and thus help prioritize among welfare interventions. However, in some cases trade-offs may arise between brief intense suffering or longer lasting suffering of a milder intensity. Here we review the extent to which existing evidence could be used to establish a weighting system between pain intensity categories, hence a single scale of suffering.

Here are some key take-aways:

* The perceived unpleasantness of pain, as subjectively rated on pain intensity scales, escalates disproportionatelly with these ratings, suggesting that experiences of more severe unpleasantness feel disproportionately worse compared to their placement on a typical scale.

* Determining the exact form of the relationship, however, is still challenging, as insights from human pain studies are limited and difficult to apply to animals, and designing experiments to address this issue in animals is inherently challenging.

* Pain Intensity weights are likely dynamic and modulated by multiple factors, including interspecific differences in the perception of time. The very relationship between pain aversiveness and intensity ratings may change depending on the experience’s duration.

* Currently, the uncertainty associated with equivalence weights among pain intensity categories is orders of magnitude greater than the uncertainty related to other attributes of pain experiences, such as their prevalence or duration.

* Given these challenges, we currently favor a disaggregated approach. Disaggregated estimates can currently rank most welfare challenges and farm animal production scenarios in terms of suffering.

* In the case of more complex trade-offs between brief severe pain and longer-lasting milder pain we suggest two approaches. First, ensuring that all consequences of the welfare challenges are taken into account. For example, the effects of long-lasting chronic pain extend beyond the immediate experience, leading to long-term consequences (e.g., pain sensitization, immune suppression, behavioral deprivation, helplessness, depression) that may themselves trigger experiences of intense pain. The same may happen with experiences of brief intense pain endured early in life. Second, once all secondary effects are considered, we suggest examining which weights would steer different decision paths, and determining how justifiable those weights are. This approach allows for normative flexibility, enabling stakeholders to rely on their own values and perspectives when making decisions.

background

Pain, both physical and psychological, is an integral aspect of life for sentient organisms. Pain serves a vital biological purpose by signaling actual or potential harm or injury, prompting individuals to avoid or mitigate the cause of pain [1]. It varies in intensity (where intensity denotes the unpleasantness or aversiveness experienced by an individual, not intensity of physical stimuli), from a mild annoyance to an excruciating agony, and duration, from fleeting moments to persistent, long-lasting conditions. This diversity in the intensity and duration of pain also serves the adaptive purpose of guiding priorities [1,2]: while an acute, sharp pain demands immediate attention, a chronic, dull ache reminds individuals of a lingering issue that, though not urgent, can also have multiple and serious consequences if not attended to.

While the function of pain as a biological alarm system is clear, its implications on overall well-being are more complex. Does a short-lived yet intense agony compromise well-being more than a prolonged but more moderate discomfort? For instance, farmed animals endure brief yet harrowing experiences, such as surgical castration without anesthesia or some slaughter practices, which are intensely painful but relatively quick. Contrast this with the more moderate, but continuous discomfort of being in an overcrowded space over several months. Both situations detrimentally affect welfare, but understanding which causes more distress, or if they can even be directly compared, is needed to make informed choices that prioritize welfare effectively [3].

In their quest to maximize fitness, organisms often operate on heuristic principles, prioritizing immediate or more intense threats based on simple rules of thumb, rather than a comprehensive evaluation of all potential consequences over a longer time frame [4]. This might mean, for instance, giving priority to pain of higher intensity, everything else being equal. However, in the realms of human and animal welfare, the goal is often to establish a metric that considers overall welfare over longer time frames, enabling the prioritization of actions that minimize suffering without burden shifting.

Within the Welfare Footprint framework [5], the intensity (unpleasantness) of negative affective experiences (referred to as ‘pain’ for simplicity) is categorized into four levels (Annoying, Hurtful, Disabling, and Excruciating) and welfare loss, or ‘suffering’, is expressed as total time spent in each intensity category (‘Cumulative Pain’). In this way, the method adopts a pragmatic stance by expressing outcomes across pain intensities over time without conflating them into a single metric. By doing so, it acknowledges the challenges and inherent uncertainties involved in comparing different pains across their dimensions, at the same time offering actionable, evidence-based results that can be used for the pursuit of different priorities (e.g., those prioritizing the relief of the worst kinds of preventable suffering can focus only on estimates of time in Disabling and Excruciating pain). Still, considering that this research area holds scientific and practical value, our focus here is to contribute to discussion in this direction.

We start by approaching the prioritization dilemma that may arise in the presence of a trade-off between brief and intense suffering versus longer lasting suffering of a milder intensity. One way to investigate this question would be to explore, quantitatively, the aversiveness caused by different levels of pain intensity, and how these differences can be offset by varying durations. How long must an individual endure an annoying or hurtful discomfort for it to be equivalent to a few hours of disabling pain? Or more generally, how do intensity and duration relate? ? In other words, is it possible to convert categories of pain intensity from an ordinal to a ratio scale?

Experimentally ascertaining whether severity or duration has a greater impact on the welfare of animals presents many challenges [6,7]. Although many studies have assessed pain intensity in animals and non-verbal human subjects (typically through the use of observational pain scales that score behaviors such as muscle tension, posture, head position and facial expressions), these studies are silent with respect to the trade-off between the intensity and duration of pain. During a workshop organized by Rethink Priorities [8], experts convened to discuss potential experimental strategies for evaluating this question [7]. Several barriers were identified, including the difficulties in ensuring external validity given the impossibility of replicating the severity and duration of animal experiences, the hidden nature of affective states [9], the fact that animal behavior and preferences will not necessarily align with their long-term welfare interests, and the lack of sensitive and specific biological markers of cumulative affect [7].

Given the complexities of studying pain in non-human animals and the common evolutionary role of pain in sentient beings, an attractive approach is to pivot towards human studies. Humans share fundamental neurological and physiological systems with other animals, and have the capacity for self-reporting, which greatly simplifies data-collection. Despite the potential for bias in self-reporting [10], understanding how humans navigate this trade-off, or at least the degree to which the most intense pains are perceived as more aversive compared to lesser ones [7], may provide a valuable starting point.

Therefore, we start by reviewing the extent to which empirical evidence in human studies could be potentially used in welfare prioritization when trade-offs between intensity and duration are present.

Potential Insights from Human Preferences

In the domain of human research, various efforts exist to quantify the relationship between states of well-being. This is especially pronounced in global health, where understanding the impact of different health conditions, as determined by their severity and duration, is crucial for defining resource allocation policies.

Accordingly, health metrics such as disability-adjusted life years (DALYs) integrate in a single cardinal scale the time spent in a health state with the severity of the state, or its ‘disability weight’, which varies from 0 (perfect health) to 1 (death) [11]. Inferences of disability weights can be conducted in different ways, from paired comparisons of preferences for hypothetical health conditions, to assessment of the time one would trade from perfect health to avoid a particular health state [12]. In all cases, however, estimates are derived from multiple dimensions of health states (e.g., mobility, level of functioning, anxiety and depression, pain, and self-care), many of which are not necessarily associated with affective experiences, but rather with cultural and social perceptions of the states evaluated that are not relevant to animals. Also, participants in these studies often judge health states they have not personally experienced, relying instead on their perception of what the experience might feel like, leading to multiple potential biases [10].

One potentially promising strategy would thus involve conducting extensive surveys where participants from diverse backgrounds, who experienced the events evaluated, make comparisons between painful (affective) experiences of varying intensities and durations. This was the approach adopted by the Qualia Research Institute in a study that asked participants to quantitatively compare their most extreme negative experiences relative to each other [13,14] . Most participants rated their most intense painful experience as at least three times more intense than the second most intense [14]. The results resembled what one would expect if the subjective experience of pain were scaled in a logarithmic manner, with large differences between intensities. Still, biases that cause people to recollect experiences (especially extreme ones) very differently from how they were perceived at the time were not addressed. These effects can be so large that they may wash out the real effects of the nature of experience [10,15]. A famous example of such a bias is the Peak-End rule [16], namely the consistent observation that the peak of an experience and how it ends play important roles in determining how the experience is remembered. For example, if a painful procedure is prolonged by adding a period of less intense pain, it is retrospectively evaluated as less painful, even though it entailed more overall pain [17,18].

Given these constraints, in the next section we focus on studies that directly assess pain severity perceptions from participants currently experiencing or having recently undergone specific painful conditions.

Direct Evaluation of Pain Severity: Insights from Firsthand Experiences

Upon reviewing the literature, we found that studies directly assessing pain severity perceptions from participants currently experiencing or having recently undergone specific painful conditions are surprisingly scarce. In an assessment of low back pain [19], patients were asked the number of years in each state they would exchange for resolution of their symptoms. All patients were willing to trade a disproportionately larger number of years to avoid a more severe pain state. Specifically, the perceived aversiveness of back pain increased non-linearly with severity (ratio severe to mild pain = 12:1). Another study used a similar methodology with chronic pain patients [20], estimating the disutility of mild, moderate and severe chronic pain as, respectively, 0.04, 0.14, and 0.26 in a paper test, and as 0.16, 0.26, and 0.27 when interviewed face to face.

The observation that disproportionately longer durations are required to compensate for increases in pain intensity once more suggests that the aversiveness of pain increases super-linearly with intensity (i.e., high-intensity pain is disproportionately more unbearable than moderate pain). However, in all cases the aversiveness of the chronic conditions evaluated may have been to some extent confounded with simultaneously occurring disabilities and socio-cultural ramifications of pain, unlikely to be present in non-human species. We therefore searched for studies evaluating instances of acute pain. Two studies were found. One examined pain intensity experienced by women during labor or recently after delivery [21]. The authors report a preference for moderate pain (level 5 out of 10) for two hours over extreme pain (10/10) for 1 hour. Additionally, a prolonged but mild pain episode (18 hours at 1/10 intensity) was favored over an intense but shorter bout of pain (2 hours at 9/10). Although the methodology does not enable establishing the numerical equivalence among pain ratings, an intensity scored as level 10 was perceived as being more than twice as bad as one scored level 5, as was a score 9 perceived as worse than 9 times as bad as a score of 1.

The second study investigated postoperative pain and cancer pain [22]. Here, the relationship among seven categories of pain (2: just noticeable, 3: weak, 4: mild, 5: moderate, 6: strong, 7: severe, 8: excruciating) was best described by a power function of the form y=0.99*x^2.99 for patients with postoperative pain and a power function of the form y=1.1*x^2.14 for patients with chronic cancer pain, where x corresponds to the pain category (1 to 8) and y the perception of intensity/distress. This translates into a perception of intensity for the seven categories of respectively 1, 8, 25, 62, 122, 210, 333 and 496 (postoperative pain) and 1, 5, 12, 21, 34, 51, 71 and 94 (cancer pain).

We find that the latter studies are possibly the most informative on the potential temporal equivalence among pain intensity levels. In addition to being exclusively focused on pain, they were the only studies assessing painful conditions by patients experiencing the pain. We find it unlikely that the most intense pain experienced is of an Excruciating nature as defined in the Welfare Footprint framework, since this category is by definition associated with extreme and unbearable pain, not tolerated even if for a few seconds (a definition which does not coincide with the description of the patients in the studies above). But if the most intense pain, as evaluated in these studies, corresponded to the ‘Disabling’ category, the equivalence between Annoying and Disabling pain would be best represented by a ratio of approximately 1 to 94-496.

Empirical Evidence and Theoretical Challenges

The observation that pain’s aversiveness escalates super-linearly with intensity coincides with findings from experiments in psychophysics, a discipline that investigates the relationship between the physical intensity of stimuli and their subjective perception [23]. Research in this area indicates that as sensations, including pain, increase in intensity, their perceived aversiveness grows exponentially [24]. For instance, as the intensity of an electric shock rises, perception of the pain grows at an accelerating rate, so the hardest shock can feel over 3,000 times worse than the mildest [25]. Likewise, in humans exposed to contact temperatures between 43°C and 51°C, the worst pain was judged to be 4,000 to 25,000 times more intense than the mildest pain [26] [27]. The non-linear nature of pain perception is further illustrated by Gómez-Emilsson [13] through examples such as the Scoville scale (a scale that measures the spicy heat of chili peppers in heat units) and the KIP scale to rate cluster headaches, both assumed to be logarithmic in nature.

These findings are also aligned with evolutionary reasoning. Intense pain demands immediate cognitive prioritization, putting other functions on hold to ensure that, in the presence of potentially fatal threats, an organism’s primary objective is the mitigation of the pain source. By making the experience of intense pain overwhelmingly aversive, organisms are compelled to take swift action, increasing the odds of survival. Additionally, the threat to an organism’s survival is likely to increase exponentially with the severity of the harm. For example, while minor injuries are typically manageable and heal, critical thresholds can be crossed with harms of greater severity, overwhelming the body’s compensatory capacities. Severe injuries can lead to blood loss, organ failure, or infections, each exponentially increasing the risk of mortality. Moreover, the energy required for recovery from severe injuries can rapidly deplete the body’s reserves, reducing the ability to withstand additional threats and creating a cycle of increased susceptibility to further harm. Inflammatory and immune responses can also become detrimental with more severe harms, as excessive inflammation can damage healthy tissues and lead to a feedback loop that accelerates the impoverishment of welfare. These responses are also consistent with the observation that higher pain intensities have a disproportionately larger impact on human functioning than lower pain intensities [28,29].

Nonetheless, defining this relationship’s precise nature, remains fraught with uncertainty. In addition to empirical evidence being surprisingly scarce, intensity weights are likely dynamic and modulated by multiple contextual factors. For example, whether pain is delivered in short bursts or continuously seems to play a pivotal role in determining its relative unpleasantness [30]. In general, the perceived aversiveness of pain will be modulated by a myriad of factors that include its type, anatomical distribution, attentional states, anticipation, past experience and fear [29,31–33].

Other layers of complexity are also present. For example, pain itself might distort an individual’s perception of time [34]. Does enduring a certain level of pain for a shorter duration feel longer than a lesser pain endured for the same period? Similarly, relative weightings between categories of pain could vary among species. The ratio of how much worse ‘Excruciating’ pain is compared to ‘Annoying’ pain may differ for an insect, a fish, a cow, or a human [35,36], particularly in the presence of species-specific differences in the subjective perception of time [34,37,38]. In fact, the very relationship between the aversiveness of pain and its intensity may itself change depending on the duration of the experience. With no data to understand how this happens, the extent to which extrapolating from short to long intervals is valid is unclear, speaking against the use of fixed equivalence levels among pain intensity levels.

The non-linear nature of the relationship between pain intensity, as measured on orginal scales, and its corresponding aversiveness also means that even small errors in estimates of more intense pain have disproportionately larger effects in aggregated estimates of time suffering. To see this, consider the example in Table 1. Disabling pain is used as a reference, hence hypothetical equivalence factors represent the time needed in the other intensity categories that would make them as unpleasant as Disabling pain. As shown, there is a striking disparity in the contributions of different pain intensity categories to the final aggregated estimate. If Excruciating pain is assumed to be 10 to 1,000 more aversive than Disabling pain, estimates of time in Excruciating pain would account for over 90% of the aggregated estimate. Naturally, any imprecision in the estimated time in Excruciating pain would have a major impact on the aggregated results.

Table 1. Hypothetical weighting schemes: time units in each pain intensity category needed to make the experience as unpleasant as one time unit of disabling pain.

Category	Estimated time in pain at each intensity	Hypothetical Equivalence with Disabling pain	Time in Disabling- equivalent pain	Contribution of time in each intensity to aggregate estimate (%)
Annoying	10 minutes	1/(100 to 1,000)	0.6 to 6 sec	0.001 to 0.0094%
Hurtful	10 minutes	1/(5 to 100)	6 sec to 2 min	0.020 to 0.094%
Disabling	10 minutes	1	10 minutes	0.10 to 9.42%
Excruciating	10 minutes	10 to 1,000	1.6 to 166.6 h	90.45 to 99.88%

Aggregate Estimate: time in Disabling-Equivalent Pain			1.8 to 167 h

These observations could also lead to the conclusion that efforts on preventing cases of intense suffering should possibly dominate most utilitarian calculations [13]. However, while the nature of reactions to intense pain is shaped to be overwhelming and disproportionate, prolonged suffering of more moderate intensities is not necessarily less detrimental to overall welfare. In fact, enduring moderate pain over an extended period will typically affect an individual’s health and quality of life in a manner that exceeds what might be expected based on duration alone. For example, chronic pain can alter pain pathways and make other pain experiences more intense, both by exacerbating the pain experience and reducing the threshold for future pain [39]. Likewise, chronic pain is associated with alterations in neurochemical and hormonal levels, reducing the ability to cope with stress and making individuals more vulnerable to disease [40]. Long-lasting pain can also lead to anxiety, depression, and helplessness, and prevent, partially or completely, positive affective experiences. Finally, experienced durations of moderate pain are often many orders of magnitude longer that those associated with intense pain.

In light of the complex interplay and cumulative impacts of chronic and acute experiences on overall well-being, comprehensive assessments of welfare that encompasses the effects derived from these experiences is essential for making informed decisions between interventions aimed at alleviating short-term intense suffering versus long-term moderate suffering. For example, in deciding between investing into banning experiences such as bodily mutilations or some slaughter methods versus longer-term issues such as high stocking density or confinement, an investigation of all the consequences of these practices would be required.

Potential practical approaches

Effective resource allocation and prioritization among sources of suffering requires finding ways to quantify their burden in a comparative way. In the Welfare Footprint framework, the cumulative load of negative affective experiences endured by animals are quantified using a biologically meaningful metric: time spent in pain of four intensities. This granulated view of suffering is clear and intuitive and can be traced back to evidence, aiding resource allocation and decision-making processes targeting different priorities. Currently, disaggregated estimates can also rank most welfare challenges and farm animal production scenarios in terms of suffering

Yet, challenges arise when this (or other metrics) are asked to balance the intensity and duration of suffering. Foremost among these is the uncertainty associated with equivalence factors, which are needed for converting time spent in different intensity levels to a common metric. So far, these factors are not empirically substantiated, and carry high levels of uncertainty.

Additionally, with aggregate estimates of time suffering, references to the actual experiences of animals are lost. While estimates of 10 minutes in Excruciating or Disabling pain are readily understandable by any audience, aggregate estimates of time in pain do not have an intuitive meaning. For example, it is not clear if a long time in Disabling-equivalent pain is dominated by experiences of chronic or acute suffering, or some combination thereof. Likewise, there is also an ethical puzzle regarding the validity of balancing different levels of suffering [41]. For example, aggregate estimates of time in pain in a population with individuals enduring intense pain could be similar to that of a population where no individual suffers intense pain, but a larger fraction of individuals experience milder pain for a sufficiently long time. The extent to which extreme suffering concentrated in fewer individuals can be compensated by milder suffering in a large number of individuals is unclear.

In short, the seemingly straightforward concept of a weighting system between pain intensities is still riddled with limitations. Until equivalences in the dimensions of pain are better understood, we favor a disaggregated approach. In its current form the Welfare Footprint framework can rank most events, scenarios and systems. Where difficult trade-offs are present, the framework can be extended further by examining which weights would steer different decision-making paths, and then determine whether such a weight is scientifically justifiable.

We illustrate this possibility by considering estimates of Cumulative Pain, at each intensity, for some of the most common welfare challenges commercial chickens experience over their lives, including slaughter (Table 2).

Table 2. Measures of Cumulative Pain in chickens (estimated seconds in pain, at each intensity). Estimates correspond to the midpoint of uncertainty intervals [42,43], and do not consider the welfare impacts of the secondary effects of the harms described. ‘Average flock member’: estimated time in pain weighted by the prevalence of the problem (considers that not all individuals experience the problem, and/or experience different degrees of severity). ‘Worst possible case’: individual enduring the worst possible outcome.

Seconds in Pain	Hurtful (1)	Disabling (2)	Excruciating (3)
(A) Effective electrical waterbath stunning in broilers (average flock member)	62	70	1
(B) Electrical waterbath set to low carcass damage (average flock member)	68	156	70
(C) Electrical waterbath stunning (any form) (worst possible case: conscious until scalding)	154	367	116
(D) Lameness in fast-growing broilers (average flock member)	805,464	193,068	0
(E) Lameness in fast-growing broilers (worst possible case: gait score 5 at slaughter)	1,384,200	1,591,920	0
(F) Chronic hunger in fast-growing broiler breeders (all individuals assumed to undergo same experience)	15,014,160	7,056,000	0
(G) Behavioral Deprivation in caged hens (all individuals assumed to undergo same experience)	10,930,500	1,165,500	0
(H) Depopulation and Transport in cage-free hens (average flock member)	41,184	90,180	2
(I) Keel bone fractures in cage-free hens (average flock member)	5,201,352	371,952	0

(1) pain that disrupts the ability of individuals to function optimally; (2) continuously distressing pain that takes priority over most behaviors (drastic reduction of activity and inattention to other stimuli); (3) extreme level of pain that would not normally be tolerated even if only for a few seconds.

The table shows that for an intervention that reduces extreme forms of suffering during slaughter (chiefly Excruciating pain) to be favored over one that averts less-intense suffering (including problems such as lameness in fast-growing broilers, chronic hunger in breeders or behavioral deprivation in caged hens), Excruciating pain would need to be perceived as being many orders of magnitude worse than Disabling or Hurtful pain. For instance, the average broiler stunned with electrical parameters set to reduce carcass damage (i.e., less effective at causing loss of consciousness, row ‘B’ in Table 2) endures about 70 seconds of Excruciating pain, while lameness causes, on average, 1,384,200 and 1,591,920 seconds of Hurtful and Disabling pain, respectively (‘D’). To justify prioritizing improvements in electrical stunning parameters over enhancements in lameness based solely on the reduction of suffering, the aversiveness of Excruciating pain would need to be perceived as approximately 3,000 times more severe than Disabling pain, or over 14,000 times more severe when considering the Disabling and Hurtful pain together. When comparing the most severe outcomes—birds that are scalded alive during slaughter (‘C’) against those suffering from the most severe form of lameness, with a gait score of 5 at the time of slaughter (‘E’)—the perceived aversiveness of Excruciating pain would need to be about 13,000 times greater than that of Disabling pain to justify a focus on stunning reforms over lameness improvements. Similarly, for interventions aimed at enhancing stunning parameters (‘B’) to be deemed more beneficial to welfare than those targeting the mitigation of chronic hunger in fast-growing female broiler breeders (‘F’), the aversiveness of Excruciating pain would need to be considered over 300,000 times worse than that of Disabling or Hurtful pain.

In determining the plausibility that Excruciating pain is several orders of magnitude more averse than pain intensities that are still very distressing (such as Disabling pain), it is also necessary to consider that estimates of the welfare impacts of the farm-level harms described, such as lameness, behavioral deprivation and chronic hunger, do not include their secondary effects. For example, in the case of chronic hunger, secondary effects emerging from feed restriction include aggression, higher incidence of feather pecking, skin lesions, foot pad lesions, disrupted resting, impaired immunity and long-term consequences for the welfare of offspring (meat chickens) through epigenetic effects [43]. In the case of lameness, by-products include a greater risk of infection, dehydration, contact dermatitis, the frustration to perform highly motivated behaviors and sleep disruption [43]. Should these effects be considered, they would require an even higher aversiveness ratio for Excruciating pain compared to Disabling and Hurtful pain.

While these observations align with the view that interventions targeting prolonged suffering may warrant prioritization absent evidence that the welfare impact of intense brief pains exceed more moderate pains by orders of magnitude [7], we suggest that in case of difficult trade-offs decisions should be determined on a case-by-case basis, considering species-specific pain responses, context of decision, and full range of welfare effects associated with the intervention. For instance, while the secondary effects of intense suffering at slaughter does not have lasting secondary effects due to the immediacy of death, intense brief suffering at early life (e.g., bodily mutilations) are likely to have multiple and profound welfare consequences, such as heightened pain sensitivity and reduced stress resilience.

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A Novel Proposal for the Definition of Pain

editar — Tue, 25 Jul 2023 09:50:00 +0000

A Novel Proposal for the Definition of Pain

Wladimir J Alonso, Cynthia Schuck-Paim

Defining pain has long been a subject of debate. Recently, a new and substantially modified definition was published by the International Association for the Study of Pain (IASP) (Raja et al., 2020). In this more recent version, pain is defined as “An unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage.” This definition is expanded by the addition of six key notes:

Pain is always a personal experience that is influenced to varying degrees by biological, psychological, and social factors.
Pain and nociception are different phenomena. Pain cannot be inferred solely from activity in sensory neurons.
Through their life experiences, individuals learn the concept of pain.
A person’s report of an experience as pain should be respected.
Although pain usually serves an adaptive role, it may have adverse effects on function and social and psychological well-being.
Verbal description is only one of several behaviors to express pain; inability to communicate does not negate the possibility that a human or a nonhuman animal experiences pain

We argue that the IASP’s definition of pain fails to fully encompass its evolutionary, cognitive, and affective dimensions. It overlooks key aspects of this sensory phenomenon, such as its inherent consciousness, its independence from learning, and its evolutionary role extending beyond mere avoidance of tissue damage – when what should be considered is fitness damage. The definition is also overly human-centric. For example, the note that a person’s report of an experience as pain should be respected ignores the weak association between pain indicators and self-reports (Labus, Keefe and Jensen, 2003). Assuming greater validity of self-reports relative to objective indicators of pain is also detrimental to the advancement of pain assessment in non-verbal subjects.

We further argue that the definition should acknowledge the multidimensional and dynamic (temporally varying) nature of pain, and allow for both physical and psychological categorizations. While there is often a reluctance to extend the term ‘pain’ beyond the realm of tissue damage or sensations processed by pain receptors, it is important to recognize that the experience of pain originates in the brain and can emerge independently of these receptors. The sensation of pain, likely evolved originally to process information from these receptors, has been co-opted evolutionarily to signal other threats to the organism beyond physical tissue damage. Accordingly, evidence indicates the similar processing of emotional and physical pain in the brain (Kross et al., 2011), and the commonalities of their neural pathways (Sturgeon and Zautra, 2016), with psychological and physical pain engaging similar brain regions (Figure 1) and involving similar neurochemicals, such as opioids. Jaak Panksepp, the father of affective neuroscience, indeed used the term ‘psychological pain’ to describe emotional states associated with two primary systems, ‘PANIC/GRIEF’ and ‘FEAR’. This sub-classification of pain as “physical” and “psychological” recognizes these evolutionary and neuroanatomical commonalities.

Figure 1. Emotional and physical pain activate very similar brain regions (from: Kross, E. et al. 2011, Social rejection shares somatosensory representations with physical pain, PNAS, 108, 6270–6275). https://www.pnas.org/doi/10.1073/pnas.1102693108

In an effort to address these shortcomings, we propose the following alternative definition:

Pain is a conscious experience, evolved to elicit corrective behavior in response to actual or imminent damage to an organism’s survival and/or reproduction. Still, some manifestations, such as neuropathic pain, can be maladaptive. It is affectively and cognitively processed as an adverse and dynamic sensation that can vary in intensity, duration, texture, spatial specificity, and anatomical location. Pain is characterized as ‘physical’ when primarily triggered by pain receptors and as ‘psychological’ when triggered by memory and primary emotional systems. Depending on its intensity and duration, pain can override other adaptive instincts and motivational drives and lead to severe suffering.

The proposed definition addresses the following points:

Asserts that pain requires conscious awareness, agreeing with authors who argue that “feelings need to be felt.” While pain’s precursors are unconscious (e.g., sensory receptors eliciting reflexive retracting behaviors), pain itself necessitates consciousness for its existence.
Calls for consciousness (or sentience) but not learning, therefore disagreeing with the IASP’s third keynote. Pain is not a ‘concept’ requiring learning; rather, it is a feeling or affective state that can be fully experienced by young and inexperienced individuals. This does not deny that pain can be influenced or modulated by experience.
Describes pain’s evolutionary role as an adaptation to prevent not only tissue injury but also threats to an organism’s survival (e.g. the pain of suffocation) and reproduction (e.g. the pain of a parent facing the separation or death of a child). Like other biological features, pain can malfunction and present non-adaptive manifestations (e.g., chronic and neuropathic forms).
Acknowledges the multidimensional nature of pain (McDowell, 2006), outlining key attributes for describing pain (intensity, duration, texture, spatial specificity and anatomical location). The term “dynamic” encourages consideration of the variability of pain attributes over time (Alonso and Schuck-Paim, 2021).
Supports categorizing pain as physical or psychological (Alonso and Schuck-Paim, 2021) based on the primary origin of neuronal triggers (note that the term ‘pain receptors’ is used instead of the more technical ‘nociceptors’ for easier understanding by the broader public).
It is not human-centric, allowing for the recognition and comparison of pain and its evolutionary antecedents across species (Walters and Williams, 2019)
Acknowledges the profound impact pain can have on organisms experiencing it in its most extreme forms (Cervero, 2012).

REFERENCES

Alonso, W.J. and Schuck-Paim, C. (2021) ‘Pain-Track: a time-series approach for the description and analysis of the burden of pain’, BMC research notes, 14(1), p. 229.
Biro, D. Is there such a thing as psychological pain? And why it matters. Cult. Med. Psychiatry 34, 658–667 (2010).
Cervero, F. (2012) Understanding Pain: Exploring the Perception of Pain. MIT Press.
Kross, E., Berman, M. G., Mischel, W., Smith, E. E. & Wager, T. D. Social rejection shares somatosensory representations with physical pain. Proc. Natl. Acad. Sci. U. S. A. 108, 6270–6275 (2011).
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McDowell, I. (2006) Measuring Health: A Guide to Rating Scales and Questionnaires. 3 edition. Oxford University Press.
Raja, S.N. et al. (2020) ‘The revised International Association for the Study of Pain definition of pain: concepts, challenges, and compromises’, Pain, 161(9), pp. 1976–1982.
Sturgeon, J. A. & Zautra, A. J. Social pain and physical pain: shared paths to resilience. Pain Manag. 6, 63–74 (2016).
Walters, E.T. and Williams, A.C. de C. (2019) ‘Evolution of mechanisms and behaviour important for pain’, Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 374(1785), p. 20190275.

Introducing Pain-Compare: A Tool for Visualizing Welfare Loss Estimates in Animals

editar — Tue, 18 Jul 2023 17:06:07 +0000

Introducing Pain-Compare: A Tool for Visualizing Welfare Loss Estimates in Animals

July 18, 2023
5:06 pm

As a part of our ongoing efforts to quantify animal welfare and enable its incorporation into policy-making, economic and environmental analyses, we have recently launched the first of a series of visualization tools: Pain-Compare. This tool, inspired by the Global Burden of Disease Compare tool, invites users to compare the estimated time in pain an individual endures as a result of welfare challenges experienced. The tool shows multiple challenges experienced under different circumstances, production conditions and by different species.

Currently, Pain-Compare includes data for chickens, specifically laying hens and broilers. However, estimates for more challenges, production conditions and species will be included as they become available.

Pain-Compare deliberately does not incorporate estimates of the prevalence and number of individuals affected by each challenge. This allows different stakeholders to use the estimates to determine the burden of pain considering the prevalence and frequency of the problem in the specific scenarios of their interest.

All datasets are available for anyone interested in analyzing the data or utilizing it for decision-making. For more insights, visit welfarefootprint.org/compare.

Metrics vs. Indicators: Clarifying Essential Concepts in Animal Welfare Assessment

Wladimir Alonso — Wed, 31 May 2023 13:54:13 +0000

Welfare Metrics and Welfare Indicators: Clarifying Essential Concepts in Animal Welfare Assessment

Wladimir J. Alonso & Cynthia Schuck-Paim

It may initially appear that discussions around the concepts of welfare metrics and welfare indicators are abstract and perhaps without tangible benefits. Yet, the truth is, some degree of precision in terminology is required when it comes to assessments of animal welfare. Welfare metrics and welfare indicators are terms often used interchangeably, but they are not equivalent.

Welfare indicators are empirical measurements of specific traits or states that, based on evidence, are deemed to be correlated to a greater or lesser extent with an individual’s affective state. These indicators are a set of measures typically specific to a species and context of measurement. They can include neurological, physiological, behavioral, environmental, pharmacological, immune and anatomical factors. Welfare indicators are typically characterized as resource-based, such as environmental factors like food and water availability, temperature, and space available, and animal-based, which include, among others, spontaneously occurring behaviors specific to pain, changes in activity, social interaction patterns, attention and cognitive performance, vocalizations, facial expressions, neuroendocrine hormones, and autonomic responses. Indicators typically offer only a partial picture of welfare.

In general, the closer a trait is to the biological processes leading to the emergence of an affective experience, the greater the validity of this trait as an indicator of welfare. For instance, if an animal is in a housing system where the number of drinkers is clearly insufficient, one could reasonably suspect that this animal will experience thirst at some point. While useful, this is an indirect (“resource-based”) measure of welfare that does not reliably correlate with affective experiences, the ultimate target of assessment. Animal-based indicators are therefore more reliable welfare indicators, as they are typically the direct outcome of the processes that lead to the emergence of affective experiences (Figure 1). For example, the responses to a number of biological offenses, as measured by anatomical, neurophysiological and immunological parameters (e.g., inflammation, immune responses, hormone levels, oxidative stress, gene expression) can often indicate the level of disturbance endured by an organism, though the degree to which these markers is associated with affect is not always clearly established. Indicators of neural activity, in turn (“sensory data and appraisal”, Figure 1), can be a more accurate and specific representation of the affective experience of interest (e.g., neural signatures of pain or pleasure would be powerful indicators once the technology becomes available, as they would directly reflect the origin of these affective states). Finally, the Responses triggered by specific “affects” (vocalizations, posture, preferences, expressions, changes in activity levels) are particularly valuable for being the direct outcome of the affective experiences endured.

Figure 1. Process leading to affective experiences, the phenomena of interest in assessments of animal welfare. Diamants in green represent the main elements considered by the Five Domains Model (figure modified from Alonso WJ, Schuck-Paim C. 2021 The Comparative Measurement of Animal Welfare: the Cumulative Pain Framework. In: Schuck-Paim C, Alonso WJ, editors. Quantifying Pain in Laying Hens).

Welfare metrics, in turn, are quantitative constructs used to evaluate and compare animal welfare across different situations or over time. They are informed by welfare indicators and are often combined to create composite scores or indices that provide a more comprehensive assessment of animal welfare. Unlike welfare indicators, welfare metrics should be as universal and comparable as possible and should be ideally easily interpretable by wide audience and across disciplines.

Welfare metrics can be used to assess animal welfare in the field, inform decisions, or track progress. Examples of welfare metrics include the Cumulative Pain, the welfare risk scores developed by the European Food Safety Authority (EFSA) and in semantic models such as COWEL and SOWEL. Metrics used in assessments of animal welfare at the farm level include the scoring system of the Welfare Quality Protocol, AWIN Protocol and Animal Needs Index.

The distinctions between welfare metrics and welfare indicators are summarized in the table below.

Table 1. Conceptual differences between welfare metrics and welfare indicators.

	Welfare Indicators	Welfare Metrics
Measurement	Typically empirical measurements of specific traits or states	Constructs based on integration of information provided by welfare indicators
Standardization (units of measurement)	Each indicator is measured with different methods, in different units and time frames depending on the species	Ideally, consensus should be reached for adoption of a single welfare metric, facilitating integration of efforts and communication*
Applicability	Typically specific to a context and species	Ideally applicable across contexts and even species
Scope	Indicators can be correlated to different degrees with well-being, in time frames typically limited by the nature of the indicator	Integration of subjective experiences (affective states) over entire time horizon of interest
Interpretability	Welfare indicators often require in-depth knowledge of the species and nature of the indicator	Should be easily interpretable by a wide audience and across disciplines.
Examples	Behavior, neurophysiology, clinical signs, anatomy, immune function, preferences	Cumulative Time in Pain, Welfare Quality Scores, EFSA Scores, Semantic scores

*Standardization between species based on their capacity for welfare is still required

In summary, while welfare indicators provide specific empirical measurements of traits or states, welfare metrics are constructs based on the integration of information provided by these indicators. They are designed to be universally applicable and easily interpretable by a wide audience across disciplines, facilitating the assessment and comparison of animal welfare in various contexts and over time.

The role of attention on affective experiences and the concept of ‘Potential for Positive Welfare’

editar — Sun, 16 Apr 2023 20:53:50 +0000

How attention modulates the perceived intensity and duration of simultaneous affective experiences, and the potential for positive welfare

Implications for refining Cumulative Pain estimates and for determining the potential for positive welfare

Cynthia Schuck-Paim and Wladimir J Alonso

SUMMARY

Because organisms frequently experience welfare challenges that overlap in time, assumptions about how concurrent affective states permit, exclude, or modulate one another can critically affect estimates of the actual times experienced in the affective states examined.
When individuals are exposed to simultaneous pain sources that differ in their salience, the brain will prioritize processing of the more salient one, devoting a greater share of its limited attentional resources. Thus, high intensity pain is expected to diminish or eliminate attention concurrent sources of less intense pain.
With concurrent pain of similar intensity, the share of attention devoted to the painful experience is likely summated in a sub-additive way. The extent to which summation is sub-additive may, however, depend on pain intensity itself. Because pain of greater intensities demands a greater share of the organism’s attention, remaining attentional resources for the processing of additional pain would become progressively scarcer.
Currently, knowledge is lacking on the share of attention associated with different levels of pain intensity. Should this knowledge be available, it would enable refining estimates of the time an individual is attending to pain, (i.e. fully aware of the painful sensation) as opposed to the time an individual is exposed to an unpleasant experience;
Knowledge of the share of attention associated with different levels of pain intensity is also needed to determine the ‘potential for positive welfare’, namely the time available to enjoy positive affective experiences once the time attending to pain is properly discounted.

“Is a chameleon having two thoughts simultaneously as one eye focuses on a juicy grasshopper on the neighboring twig while the other eye searches the branches overhead for a better approach route? Can a seahorse ogle a potential mate with one eye while tracking the movements of a lurking predator with the other? My single-track brain can’t. If I read the newspaper while the radio plays ‘This American Life’, my mind can toggle back and forth between the two, but try as I might I cannot stream both stories at the same instant.”

Jonathan Balcombe (What a Fish Knows)

INTRODUCTION

The possibility of genuinely experiencing multiple stimuli, thoughts or affective states simultaneously is a contentious topic. While one view holds that it is possible to multitask and attend to multiple stimuli in a parallel manner, another holds that what one may feel as attention to multiple stimuli in fact involves switching among them very rapidly, in a serial manner [1]. The latter view is consistent with theories that compare conscious awareness to a spotlight in a dark room, where the spotlight represents the focus of one’s awareness, and the dark room encompasses all sensory inputs, perceptions, memories, and affective states immediately available. Like a moving flashlight, it illuminates one experience at a time [2,3].

This scientific debate holds significance for assessments of animal welfare, as assumptions about how concurrent affective states (positive or negative) permit, exclude, or modulate one another can critically affect estimates of the actual times experienced in the affective states examined. This is especially true if we consider that organisms may frequently experience welfare challenges that overlap in time. Here we explore the role of attention on affective experiences within the context of ‘Cumulative Pain’ assessments [4] (where pain is used as a shorthand for any negative affective experiences).

For instance, consider a hypothetical scenario where an individual is exposed, in one day, to two consecutive sources of Hurtful pain for five hours each. In this case, Cumulative time in pain would be represented by 10 hours. But if the two pain episodes unfolded simultaneously, would Cumulative Pain still be best represented by 10 hours? And during the five hours of simultaneous exposure to these two pain sources, would there be any time left for positive experiences? Would this change if the second source of pain was of a different intensity (e.g., Annoying)?

So far, estimates of Cumulative Pain have been based on the operational assumption that multiple concurrent challenges have the above mentioned additive effect on experience (namely that their effects when experienced simultaneously are best represented by the sum of their isolated effects). This solution works well for the purpose of distinguishing the impact of welfare challenges across scenarios or production systems [5,6]. However, to the extent that attention is selective, switching among simultaneously occurring experiences, estimates of cumulative time in pain can be refined to incorporate this phenomenon. Such a refinement should enable estimating the time individuals are aware of and focused on each negative experience (as opposed to simply being exposed to them). Additionally, it allows exploring the time that remains available for individuals to enjoy positive affective experiences, once the time actually preoccupied with ‘pain’ is properly discounted.

ATTENTION AS A LIMITED RESOURCE

The dynamic nature of attention plays a critical role in our affective experiences. Our affective states are not static, instead fluctuating as our attention shifts between various aspects of a situation, memory, or sensory input. This continuous shift in attention leads to the processing and prioritization of different emotions or emotional cues at different points in time.

The involuntary capture of attention by pain is a crucial aspect of its role as a warning signal of (real or perceived) danger. Pain demands attention, as it must change behavior to prevent survival and reproduction from being compromised [7–10]. In general, the greater the threat, the more intense the pain signal [11,12], engaging more of the individual’s attention [10,12–15].

Attention is, however, a limited resource, constrained by the brain’s architecture, its finite capacity for neural processing and limited supply of energy. Amidst the constant influx of vast amounts of sensory data, various mechanisms evolved to direct the brain’s attention to relevant information, while suppressing less relevant stimuli. For example, top-down mechanisms of attentional control are driven by an individual’s goals and expectations (e.g., if an individual is searching for red food, these mechanisms will enhance the processing of red stimuli while suppressing other colors) [16,17]. Allocation of attention is also determined by bottom-up saliency mechanisms that are triggered by the inherent features of stimuli, particularly their intensity, novelty, or contrast [18]. Sensory processing areas respond more robustly to more intense, contrasting and novel stimuli, and this enhanced activity increases the likelihood that these stimuli are attended to [19].

The perception of pain, both physical and psychological, is closely intertwined with these attentional processes. Pain’s ability to capture attention is also largely mediated by bottom-up saliency mechanisms triggered by the inherent features of the painful experience, such as their intensity or sudden onset. For example, in the case of physical pain, as intensity increases, nociceptors transmit more frequent and larger electrical signals along the pain-processing pathway, triggering the release of greater amounts of neurotransmitters like glutamate (a primary excitatory neurotransmitter) and neuromodulators like substance P (involved in pain transmission and sensitization of nociceptors). This, in turn, intensifies the activation of pain-processing neurons and amplifies pain signals within the neural network, capturing more attention to ensure that organisms respond adequately [20,21] .

Pain is also modulated by voluntary mechanisms such as attentional focus [22]. Consciously directing attention towards a painful stimulus can increase the perception of pain intensity, given the heightened awareness of the pain sensation and the amplification of emotional components of pain, such as anxiety or distress [23,24]. Conversely (and this is also of great relevance to strategies to improve animal welfare), reduced pain is observed if attention is directed away from the painful stimuli by more salient experiences (e.g., fear, stress, highly motivated tasks) [21]. By occupying the brain’s limited attentional resources with alternative tasks or stimuli, the processing of pain signals is inhibited, leading to a reduction in pain perception.

TIME IN CONCURRENT AFFECTIVE STATES OF DIFFERENT INTENSITY

A natural conclusion from the previous section is that when individuals are exposed to simultaneous pain sources that differ in their salience, the brain will prioritize processing of the more salient one (i.e., more intense, novel or threatening), devoting a greater share of its limited attentional resources.

Top-down mechanisms can also lead to inhibition of concurrent, less salient, pain. One such mechanism is known as conditioned pain modulation (CPM), or ‘diffuse noxious inhibitory control’ (a term used more often in animal research), sometimes described as ‘pain inhibits pain’ [25]. CPM occurs when response from a painful stimulus is inhibited by another, often spatially distant noxious stimulus. The process involves the activation of descending inhibitory pathways that can reduce the activity of pain-transmitting neurons in the spinal cord. One means whereby this modulation happens is through the release of endogenous opioids, which inhibit the release of neurotransmitters (e.g., substance P, glutamate) needed for pain transmission. Engagement in pleasant and highly motivated activities and movement may also trigger the release of endogenous opioids, as well as other neurochemicals like dopamine, serotonin, and oxytocin, which can too contribute to a reduced perception of pain. Additionally, a strong painful experience may also serve as an anchor or comparison point by which others are judged (hence reducing their intensity relative to when they are judged individually) [26]

If less intense pain is nearly overshadowed by more intense pain, then the experience of simultaneous pain cannot be represented by the sum of the experience of each pain stimulus when experienced alone. High intensity pain will likely eliminate less intense pain during those moments when attention is recruited to the former.

For the purposes of Cumulative Pain analysis, and until further knowledge is available, we therefore assume that when an individual experiences pain episodes of different intensities concurrently, only the most intense pain should be computed.

TIME IN NEGATIVE AFFECTIVE STATES OF SIMILAR INTENSITY

With concurrent pain of similar intensity a more nuanced strategy is required. In line with observations that increasing the area of exposure to noxious stimuli produces a disproportionately small (sub-additive) increase in the perceived intensity of pain [27], we consider the possibility that for pain of similar intensity, the share of attention devoted to the experience is summated in a sub-additive way. The extent to which summation is sub-additive is, however, unclear. As a starting point for further investigation and debate, we consider two scenarios:

Strategy A: conditional sub-additivity that depends on pain intensity

Because pain of greater intensities demands a greater share of the organism’s attention, remaining attentional resources for the processing of additional pain would become progressively scarcer. A tentative set of estimates for the degree of attention allocated to each intensity category is as follows: (1) Excruciating: 91-100%, (2) Disabling: 61-90%, (3) Hurtful: 26-60%, (4) Annoying: 1-25%. In Table 1, these estimates are used to suggest the extent to which sub-additivity is expected with simultaneous sources of similarly intense pain in each case.

For example, in the case of Excruciating pain, these thresholds would suggest that when a second source of Excruciating pain is experienced simultaneously, the maximum increase in the time attending to the new source of pain (in addition to that grabbed by an isolated source of Excruciating pain) would be 9%. Conversely, if two sources of Annoying pain are experienced simultaneously, there would be near complete additivity (70-99%).

One obvious limitation of this approach is our current lack of evidence on the share of attention associated with each level of pain intensity (i.e. the validity of estimates in Table 1). Another limitation is the fact the proportion of attention allocated to each intensity category cannot be equated to its degree of unpleasantness. Consider this scenario as an example: two individuals are enjoying a pleasant conversation in a park. Suddenly, one is bitten by a mosquito. The discomfort experienced is just Annoying, capturing approximately 10% of the individual’s attention. Now imagine that a dozen additional mosquitoes begin to bite this person, causing their attention to become almost entirely focused on attempting to shoo the insects away and scratching the bites. The conversation in the park is no longer feasible. In this scenario, nearly all attention was focused on this experience. Although the unpleasantness of the experience increased, it is not possible to say that the intensity of the overall pain increased proportionally to the attention it demanded as the number of mosquitoes grew, becoming Hurtful. Pain intensity and pain-related attention are related but separate aspects of the pain experience. Pain intensity refers to the magnitude of the unpleasant sensory and emotional experience. Pain-related attention, on the other hand, refers to the extent to which an individual’s cognitive resources are directed towards or distracted by the pain.

Strategy B: fixed sub-additivity

The second scenario adopts a simpler analytical approach, whereby each subsequent source of pain is assigned a progressively smaller increase in perceived intensity, with the second source contributing a 50% increase, the third source a 25% increase, and so on progressively. As before, in the Cumulative Pain framework such increases are translated into a greater share of time attending to pain of that intensity.

Again, these proposed values are only provisional and should be considered as a simplified starting point given our limited understanding of pain and attention mechanisms, and the many potentially confounding factors in this analysis. For example, attention to pain will be also influenced by the presence of additional stimuli competing for attention, differences in the discriminatory properties of the pain sources, and variability in pain thresholds and coping mechanisms. Thus, the proposed values are unlikely to be universally applicable.

CUMULATIVE PAIN ESTIMATES: TIME EXPOSED TO PAIN VS TIME ATTENDING TO PAIN

The Cumulative Pain framework estimates the time individuals typically spend with pain of each intensity category. Thus, one hour of Hurtful pain means that an individual was exposed to a source of Hurtful pain for one hour. In its current form, the framework represents two simultaneous sources of Hurtful pain, each lasting an hour, as two hours of Hurtful pain. This choice offers the benefit of simplicity, and eliminates the need for more complex assumptions about the type of additivity in the subjective perception of pain, for which knowledge is not yet available.

However, estimates computed in this manner often raise the question of how an individual can experience more hours of pain than there are hours in a day, or even a lifetime. For instance, consider a fictitious case: an animal spends her life with two ailments: (1) a mild “itch” (of an Annoying intensity) and (2) a mild thermal discomfort (of an Annoying nature too). She lives for 60 weeks, and pain is only felt when awake (16 hours/day, totaling 6,720 hours awake). In this case, she experiences 6,720 hours of Annoying pain due to the itch and 6,720 hours of Annoying pain due to thermal discomfort. The total of 13,440 hours of Annoying pain is longer than her life. This is a by-product of a technical choice in the approach, but one that may confuse the audience.

One potential solution to this issue involves incorporating the degree of attention allocated to each pain intensity category into Cumulative Pain calculations. In other words, instead of estimating the duration an individual is subjected to pain (i.e., the entire period during which an individual is exposed to an unpleasant experience), one would estimate the time spent attending to pain, namely the duration of those moments an individual actively focuses on or is aware of this sensation. This latter time estimate will be typically shorter, as individuals may not be continuously aware of their discomfort or may actively choose to focus on other aspects of their experience part of the time.

For instance, if we assume that an individual is aware of Annoying pain only 25% of the time, then each hour of Annoying pain exposure should be converted into a maximum of 15 minutes of actual time spent in Annoying pain. Consequently, two simultaneous sources of annoying pain lasting one hour would be translated into a maximum of 30 minutes of annoying pain (following strategy A in the previous section) or 22.5 minutes of annoying pain (strategy B).

By incorporating attention allocation into the framework, we can more accurately estimate the actual time spent aware of a negative affective state. This resolves the apparent contradiction of cumulative pain estimates exceeding a lifetime. However, the decision to incorporate this refinement depends on the reliability of estimates for the share of attention allocated to painful experiences of varying intensities. Adopting provisional values that may change in the future could harm the comparability of analytical results. Therefore, we greatly appreciate any feedback and input that can help inform our decision-making in this regard.

TIME AVAILABLE FOR POSITIVE WELFARE

Although, in our view, negative affective states (particularly more extreme forms) have a larger impact on well-being (e.g., improvements in positive states are frequently bounded and lost to hedonic adaptation, whereas adaptation to pain is unlikely; [28]), it is also important to consider how concurrent experiences of different valence may affect each other. In this regard, it is reasonable to assume that positive welfare is precluded, either partially or completely, in animals experiencing negative affective states, particularly the more intense ones. This assumption is in fact part of the defining criteria of the four intensity categories considered in the Cumulative Pain framework.

We propose that the amount of time individuals spend focusing on pain determines the time remaining for the experience of positive states. Thus, ‘potential for positive welfare’ can be defined as the estimated time available to enjoy positive affective experiences once the time spent in pain has been discounted. We purportedly use the term ‘potential’ since the absence of suffering both allows for a state of neutral welfare (something that by itself could be considered good) and for experiences of positive valence (e.g. enjoyment or pleasure), equated to good welfare by some authors [29].

Some practical limitations must be highlighted in this exercise. Again, as discussed, empirical evidence is still lacking on the extent to which pain of different intensities differentially demands attention. Importantly, estimating the potential for positive welfare requires considering all time in negative affective states. In other words, it is necessary to take into account every single challenge to which individuals are exposed. If only a subset of challenges is considered, the time available for neutral or positive welfare may be largely overestimated.

Additionally, the potential for positive welfare may be also overestimated if factors other than attention are not considered. For example, pain caused by traumatic injury or pathological processes may lead to immobility, restricted movement or impaired behavioral responsiveness to potentially pleasurable opportunities [30]. Similarly, sickness, weakness, nausea, dizziness and other debilitating affects may demotivate animals from engaging in physically active, gregarious and positive behaviors [30].

Finally, positive and negative affective states may interact in complex ways other than those considered. For instance, evidence indicates that in environments where animals can engage in motivated behaviors the perceived intensity of pain is reduced. In chickens, experiments conducted by Mike Gentle two decades ago [21,31] have shown that the higher the motivation to engage in a behavior (hence attention diverted to it), the higher the degree of endogenous analgesia mediated by opioids. The possibility to express positive behaviors may therefore inhibit pain that would otherwise be felt as Hurtful or Annoying (pain of higher intensity cannot, by definition, be eliminated with distraction).

CONCLUSION

Understanding the role of attention in the perception of concurrent negative affective states is crucial for refining estimates of cumulative time in pain and animal welfare assessments. Taking the temporal synchronicity of the various welfare challenges animals experience into account is also necessary to determine the potential for positive welfare — the time available for animals to experience positive affective states once the time spent in pain has been discounted.

As an immediate step to refine estimates of Cumulative Pain, we suggest that when individuals experience pain of different intensities simultaneously, the most intense pain is likely to capture most of the individual’s attention, overshadowing less intense pain.

When it comes to concurrent pain of similar intensity, the degree to which pain summation is sub-additive is an important aspect to consider. The analytical strategies presented here are meant only as a starting point for research and debate in this area. They depend critically on acquiring more knowledge about the share of attention demanded by pain of varying intensities. More evidence in this regard is also needed to determine, more rigorously, the actual time spent aware of and focused on pain, which in turn resolves the apparent contradiction of cumulative pain estimates surpassing a lifetime.

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acknowledgementS

The content of this discussion was inspired by various (very pertinent) questions about the method raised by Michael St. Jules.

Our ‘Pain-Track’ article at BMC Research Notes

editar — Wed, 21 Apr 2021 08:31:35 +0000

Publication at BMC Research Notes

We are glad to know that our research note on the Pain-Track approach has just been published at BMC Research Notes! The article is open-source, and freely available here, as well as below..

The short video below describes it.