Algosphere - Introduction to the Systematic Study of Suffering

ALGOSPHERE

An enterprise about suffering

INTRODUCTION TO ALGOSCIENCE

This Algosphere project consists in producing, on this website and eventually as a book, a document that presents the first elements of a new discipline which is tentatively called algoscience, or scientific algonomy. The term algonomy is explained elsewhere. Algoscience may be defined as a branch of systematic knowledge where cumulative verifiable information on the whole range of theoretical and practical matters pertaining specifically to suffering, is sought, or used, in conformity with recognized scientific methods. In other words, algoscience is the science of suffering, or the branch of science concerned with the knowledge and management of the phenomenon of suffering.

The following preliminary work is offered.

It seems that today, especially with the proliferation of researches related to brain imaging, it would be possible to elaborate a first scientific theory of suffering, and to publish that theory in the form of an article in a specialized journal. Preliminary moves are being made in that direction. For instance, see hereunder the letter to the editor which appeared in Pain Research and Management, the journal of the Canadian Pain Society.

METHODOLOGY IN ALGOSCIENCE

Methodology is necessary to algoscience in order to develop formally its conceptual basis and its methods. The word methodology here refers to the rationale and the philosophical assumptions that underlie a particular discipline, and that determine how methods (specific principles, practices, procedures) are deployed and interpreted. There can be no detailed guide on how to create a new science, but algoscientists could probably draw many lessons from studies on how modern knowledge is pursued, or on how new fields are being developed (e.g. pain research, scientific study of consciousness, sociology of happiness...). For now, the main ideas that are proposed in algoscience methodology can be summed up as follows.

The nature of algoscience is a matter for people to explore, to invent, and to agree upon. This discipline is originally conceived as a comprehensive, theoretical and practical, 'soft' science. It appears to be a very large discipline, given its specific object, the phenomenon of suffering, and given its field, the set of all things that may concern directly or indirectly that formal object. Every modern science, it should be noted, seems to be exceedingly large, or indefinitely expansible. At this time, embryonic algoscience can be handled by "general algoscientists", but eventually the discipline, like others, will probably have to be divided into a number of specialized parts.

Recognition from the scientific community will come to algoscience inasmuch as its "paradigm" helps to produce new theoretical and technical knowledge about suffering and its management. But prior to any demonstrative results, the following considerations may invite confidence in the new paradigm.

Algoscience considers suffering as the "specific object" of a "comprehensive" discipline. For the first time, suffering is dealt with as a whole and intrinsic concern. Until now, this concern has generally been subordinated to other preoccupations in politics, economy, society, religion, morals, philosophy, medicine, psychology, neurology, etc., and advances about suffering have mostly followed from our interest in health, knowledge, love, welfare, security, etc. In algoscience, there is a reversal of perspective : suffering is not only specifically and extensively considered, but it is also the chief concern to which other preoccupations are subordinated. Suffering, in its own specificity, is the matter of algoscience : it is not as such the matter of neuroscience, psychotherapy, social work, or medicine because such disciplines are primarily concerned with aspects of suffering that are specific not to suffering itself, but to neuron and brain, or mind and behavior, or social problems, or health and illness. Hopefully, a general science of suffering will make possible what others were unable to allow in the knowledge and management of suffering.
Algoscience considers suffering as a conceptually defined phenomenon. Events or things in the real world are particular and unique, and it is the role of science to turn them into conceptually defined phenomena or facts that are general and comparable to one another. As a conceptually defined phenomenon, suffering is a kind of abstraction comprising temporal, spatial, subjective or other types of attributes, but devoid of particularities such as a date, a place, a specific individual's presence or any other contingent condition of manifestation. This abstractive process makes scientific knowledge possible, because it makes it "verifiable". It may be reminded that there is no truth in science, but only theories that at all time can be proved or disproved. In the same line of thought, it may be noted that all matters that may concern suffering can be treated in algoscience, but only inasmuch as they are amenable to scientific verification : religious or philosophical viewpoints on suffering, for example, belong in some aspects to science, but in their specificity they belong to another sphere.
Algoscience considers suffering as an empirical concept, because it is a psychological process that can be observed through the behavior or the functioning of groups, individuals, bodies, brains, neurons… Suffering can be measured and modified, augmented or diminished, started or stopped. Objective correlations can be established, and empirical knowledge can be developed.
Algoscience considers suffering with a radical, typically scientific stance of objectivity. It does not value suffering negatively nor positively. Consequently, parts of algoscience that are evaluative (e.g. critical studies of theories), or prescriptive (e.g. developmental studies of antalgic factors), or even factual (e.g. inventorial collections), are scientific only inasmuch as "statements of existence of value" are used rather than "intrinsic value judgments". Criteria must be made explicit, in particular, when suffering is said to be good or bad, useful or useless, acceptable or unacceptable, avoidable or unavoidable, light or severe, etc. Authors of algoscientific documents should mandatorily identify formally what, how, and especially "whose" values or interests are taken as parameters in their work. Neutral objectivity in science has often been a heuristic device, and hopefully it will have the same serendipity with suffering. Besides, there is a place for ethics in algoscience. Algonomic science cannot and should not have an ethical position, but students of suffering should have one! In short, algoscience as a discipline has only one purpose : universal knowledge about suffering. By itself, it has no other goal, value, strategy, or program of action.

DEFINITION OF SUFFERING

Wikipedia's definition of suffering is probably as good as any other. "Suffering, or pain in the broad sense, is an individual's basic affective experience of unpleasantness and aversion associated with harm or threat of harm." (as of 2010-08-29)

In the same Wikipedia article there is the following section entitled 'Terminology':

The word suffering is sometimes used in the narrow sense of physical pain, but more often it refers to mental or emotional pain, or more often yet to pain in the broad sense, i.e. to any unpleasant feeling, emotion or sensation. The word pain usually refers to physical pain, but it is also a common synonym of suffering. The words pain and suffering are often used both together in different ways. For instance, they may be used as interchangeable synonyms. Or they may be used in 'contradistinction' to one another, as in "pain is inevitable, suffering is optional", or "pain is physical, suffering is mental". Or they may be used to define each other, as in "pain is physical suffering", or "suffering is severe physical or mental pain".

Qualifiers, such as mental, emotional, psychological, and spiritual, are often used for referring to certain types of pain or suffering. In particular, mental pain (or suffering) may be used in relationship with physical pain (or suffering) for distinguishing between two wide categories of pain or suffering. A first caveat concerning such a distinction is that it uses physical pain in a sense that normally includes not only the 'typical sensory experience of physical pain' but also other unpleasant bodily experiences such as itching or nausea. A second caveat is that the terms physical or mental should not be taken too literally: physical pain or suffering, as a matter of fact, happens through conscious minds and involves emotional aspects, while mental pain or suffering happens through physical brains and, being an emotion, involves important physiological aspects.

Unpleasantness is another synonym of suffering or pain in the broad sense. More technically, the term is used in physical pain science for referring to the basic affective dimension of pain (its suffering aspect per se), usually in contrast with the sensory dimension, as for instance in this sentence from Professor Donald Price: “Pain-unpleasantness is often, though not always, closely linked to both the intensity and unique qualities of the painful sensation.”^[4] Words that are roughly synonymic with suffering, in addition to pain and unpleasantness, include distress, sorrow, unhappiness, misery, affliction, woe, ill, discomfort, displeasure, disagreeableness.

A page in preparation concerning the usage and study of terms and expressions used in algoscience can be seen here: Terminology in Algoscience.

QUANTITATIVE STUDIES

Measurement and estimation are of prime importance for most rational activities dealing with suffering, and quantitative studies concerning suffering should be developed as an independent subdiscipline, which could be called algometry. A few preparatory notes for algometry are given here.

Jeremy Bentham (1748-1832) has prompted much thoughts, in ethical philosophy and in political economy, with his calculus of pleasures and pains. Bentham mentions seven circumstances that affect the value of an actual or potential pleasure or pain : 1- its intensity; 2- its duration; 3- its certainty or uncertainty (how sure are we of its existence?) ; 4- its propinquity (proximity) or remoteness (is it present or more or less future?); 5- its fecundity (how much sensations of the same kind does it necessarily bring about?); 6- its purity (how much sensations of the opposite kind does it necessarily bring about?); 7- its extent (how many people are affected by it?). Modern utilitarians, in their computations, sometimes use hedons and dolors as units for, respectively, pleasures and pains.
The International Society for Panetics has inquired into quantification of matters related to the infliction of suffering (see Quantification Research about Suffering at the ISP). The Society's founder, Ralph Siu, has proposed a unit, the dukkha, for measuring suffering as a product of three factors : intensity, duration and number of persons affected.
Pain questionnaires of various kinds (some are quite long) are being developed in medicine for appraising pain in patients. The most usual and simple device is the 5 or 10-steps scale, which serves to communicate the intensity degree of a pain. That scale can be numerical, verbal, or visual-analog. Pain may be a purely subjective phenomenon, but its treatment has to be objective; therefore, pain intensity is measured according to "what the patient says", and thus the objective behavioral data collected from what the patient expresses become the basis of an objective pain measurement. Research shows that this method is more reliable than any other for assessing pain in patients. An important book in this area is "Handbook of Pain assessment", by Melzack and Turk.
In the field of psychophysiological measurement, various equipments (e.g. stimulus gauges, reflex gauges, nerve impulse recorders, electroencephalograms, computerized tomography scanners, magnetic resonance imaging scanners) are used to probe the measurable organic basis of physical pain or psychological suffering. That field has a long history that should be recapitulated as a part of algometrics. Some important concepts are the dol (a unit of pain), the JND (just noticeable difference), the Weber-Fechner law (the amount of a perception is proportional to the natural logarithm of the stimulus)… Generally, measurable aspects that are most significant to algometry are intensity, acuteness, dullness, aversion, duration, length, frequency, recurrence… It may be noted that as a psychophysiological phenomenon, suffering can be regarded under various aspects relating to neurology, endocrinology, affectivity, cognition, volition… Each aspects may require a special algometric treatment. As to physical pain, several imaging techniques, in addition to lab tests (blood, urine, spinal fluid, biopsy, etc.), are used for investigating and assessing its causes: CAT scan, MRI, x-ray, ultrasound, thermography, myelography, electromyography, etc. Richard Ryder, on page 64 of his book Painism - A Moral Modernity, mentions the following means for measuring pain in animals: behavior (such as screams, approach or avoidance preferences), autonomic responses (such as heart rate, respiration, galvanic skin response), level of hormones (such as adrenaline, noradrenaline, cortisol), level of pain-associated neurotransmitters, level of endogenous opiates, and with a view to rating their painful experiences for us, Ryder adds that animals can be trained to do something (e.g. pressing a lever) to avoid unpleasant situation or they can be given access to self-medication with analgesics. See also the article Dolorimeter in Wikipedia.
In the field of clinical psychology, a number of tests might be used for assessing psychological suffering. The category Clinical psychology tests at Wikipedia includes for instance Beck Hopelessness Scale, Hamilton Rating Scale for Depression, Zung Self-Rating Anxiety Scale... ), etc.

Evaluations of suffering are done by the courts in assessing damages. See for instance How do insurance companies and juries assign values to pain and suffering?.

Suffering in groups of individuals is sometimes tentatively quantified by using social indicators (like the Poverty Index), statistics on problems related to suffering (such as illnesses, deaths, crimes, human rights violations...), questions addressed to a sample of a population in a survey poll (like surveys about happiness), indexes made up with various data (see the idea of The International Human Suffering Index), etc.

A lot of micro and small sufferings are endured by everybody each day. Medium sufferings can be quite frequent as well. Even intense but unexcessive sufferings are not rare, as shown for instance in sports. Dealing with those 'unexcessive' kinds of pervasive sufferings in the same framework as sufferings that are 'excessive' may well turn out to be practically unfeasible, strategically counterproductive, and morally unacceptable. Distinguishing between excessive and unexcessive suffering is of course a matter of qualitative appreciation or value judgment, but it is clearly also a matter of applied algometry.

Eventually, in order to have a clear view of suffering in the world, an algometric epidemiology should be developed. One of the uses of this specialty could be to provide a periodical inventory of countable cases of excessive suffering that can be identified at various scales (global, national, local...) and in various areas (health care, social services, economic security, legal system, etc.).

There are still other aspects of suffering that need to be measured : its consequences, causes, remedies, contextual factors, costs, benefits, foreseeability, measurability, diminishability, augmentability, and other economical, social, ethical, political, strategical, or technical aspects that can be relevant to its study or its management.

From A talk with Daniel Gilbert : "What does it take to study something scientifically? One word: Measurement. If you can measure something, you can study it scientifically. Can we measure a person's subjective emotional experience? You bet. People can tell you with both words and actions what they are experiencing (...) and these reports are the essential data on which the science of experience is built. (...) optometry is another one of those sciences that is built entirely on people's reports of subjective experience. The one and only way for an optometrist to know what your visual experience is like is to ask you, 'Does it look clearer like this or (click click) like this?' On the basis of your answers, the optometrist is able to create a lens that corrects your vision quite precisely. Indeed, without your report of your subjective visual experience, optometry would be impossible. No 'objective test' — no eye test, no blood test, and no brain test — can provide this information."

Another argument against measuring suffering, besides the subjective aspect of the phenomenon or its first-person only accessibility, is that no two sufferings are alike, or that at least there are categorically distinct kinds of suffering which share no commensurable aspects. Against that argument, algoscience postulates that suffering, defined as a specific psychoneural phenomenon, is a real concrete thing which exists in space and time, in a given number of nervous systems: as such, it can be modified, augmented or diminished, started or stopped.

In a 1946 article On the theory of scales of measurement, psychophysicist Stanley Smith Stevens claimed that all measurement in science was conducted using four different types of scales that he called "nominal", "ordinal", "interval" and "ratio": those four levels of measurement should certainly be used in algometry. Also of interest, from the same psychophysicist, is Stevens' Power Law, a proposed relationship between the magnitude of a physical stimulus and its perceived intensity or strength, which is widely considered to supersede the Weber-Fechner law.

Finally, a thorough review of the literature about quantification and mathematization related to suffering should be a permanent feature of algometry.

COLLECTING AND CLASSIFYING

Collecting and classifying are usually among the first activities that are done within a new discipline. It is necessary to collect facts, ideas, documents, and to classify them methodically for convenient retrieval and handling. In algoscience, lists as exhaustive as possible should be set up concerning people or animals who suffer, kinds of suffering, causes of suffering, people and organizations who cause suffering, solutions or strategies relative to suffering, people and organizations who contribute to stop, diminish or prevent excessive suffering, documents having to do with suffering, and many other topics. See a page in preparation : Collecting and Classifying in Algoscience.

BIBLIOGRAPHY

It is important in algoscience to develop a bibliographic subspecialty dealing with documents that can be found on paper, or on the Internet, or on other media, and that are relevant to the knowledge and management of suffering. See a page in preparation : Bibliography in Algoscience.

FRENCH ABSTRACT — RÉSUMÉ EN FRANÇAIS

Introduction à l'algonomie scientifique
Ce projet d'Algosphère consiste à produire un document qui présente les premiers éléments d'une nouvelle discipline appelée provisoirement algoscience ou science algonomique. L'algoscience peut se définir comme une branche du savoir systématique où des connaissances vérifiables et cumulatives concernant toute la variété des matières théoriques et pratiques qui touchent spécifiquement à la souffrance, sont recherchées, et utilisées, en conformité avec des méthodes scientifiques reconnues. La méthodologie de la nouvelle discipline fait apparaître que l'étude algoscientifique de la souffrance relève d'un nouveau paradigme concernant cet objet, qui dès lors peut être considéré comme spécifique, premier, empirique, et digne d'un traitement aussi objectif et exhaustif que possible. Le terme souffrance désigne toute douleur, au sens large, et quelques notes sont offertes sur la terminologie en algoscience. Quelques notes préparatoires sont présentées concernant l'étude quantitative de la souffrance ou algométrie. La collection (des faits, des idées, des documents) et la classification en algoscience sont abordées en ce qui concerne les sortes de souffrance, les gens ou les animaux qui souffrent, les causes de souffrance, les gens et les organisations qui contribuent à produire la souffrance, les solutions ou les stratégies relatives à la souffrance, les gens et les organisations qui contribuent à arrêter, à diminuer ou à prévenir la souffrance excessive, et d'autres sujets. Enfin, une page en préparation est présentée sur la bibliographie en algoscience.

The following is taken from the journal of the Canadian Pain Society, Pain Research & Management, Volume 14, Number 2, March/April 2009. It is a letter to the editor, by Robert Daoust, page 173. The original text can be found on the Internet.

Letter to the Editor
Re: Craig KD. Knowledge translation and the science of pain. Pain Res Manage 2008;13:464.

Bonjour docteur Craig,
Your editorial about knowledge translation prompts me to send you this message.
I believe the problem of pain science knowledge translation has a political dimension that should be confronted head-on. It is a problem of resource distribution that could be compared, for example, to the one that prevails in nutrition science, in which solutions to hunger are well known but can only be implemented through politically adequate resource distribution.
What modern politics is still lacking, in my view, is an approach to suffering (algonomy; http://www.algosphere.org/indexen.htm) that could inform social-economic management. There is a need for a science of suffering (algoscience; http://www.algosphere.org/intro/index.html), and psychology as well as pain science should be more aware of that need. Your editorial uses the words suffer and suffering, it raises the question of how pain is conceptualized and it states that there is a great need for integrative, even speculative, reviews and theoretical analyses. I would like us to go further — to clarify the link between pain and suffering, to recognize that because pain is an unpleasant experience, it is therefore a kind of suffering, to perform not only reviews and analyses but also to create the new science of suffering that must be created.
If you ever hear of someone who might be interested, able, and available for that kind of creation work, please let me know!

Robert Daoust
Algosphere
Montreal, Quebec

Last modification : 2010/08/31

Email : info@algosphere.org