The last part of the book was disappointing, as the coverage was generally weak and chapter 13 even basically devolved into a self-help chapter; I dislike self-help books immensely. I gave the book 2 stars on goodreads, but ended up significantly closer to one star than three. The truth of the matter is that if the book had been covering a different topic in which I had only had a more fleeting interest, there’s no way I’d have read it to the end.
A few observations from the last part of the book below.
“In 2006 we set out to test the impact of loneliness on responses to inequitable treatment. Our strategy involved a game in which the researcher designates one player as “proposer” and the other as “decider” and gives the proposer ten dollars. The proposer must split the money with the decider—along whatever lines he can get the decider to accept. If the decider rejects the proposal, neither player gets any money. […] It will probably come as no surprise that most people are sensitive to whether or not another person is dealing with them fairly, and that they agree to accept more fair offers than unfair ones. They do this even when, as in our experiment, rejecting an offer leaves them with no reward but their pride and their sense of right and wrong. Lonely players generally followed this pattern, and lonely and non-lonely participants in our game accepted comparable numbers of fair offers. However, lonely players accepted more unfair offers than did nonlonely players. They went along more often when their partner treated them unfairly, even though both lonely and nonlonely players rated the offers as equally and profoundly unfair.
This willingness to endure exploitation even when we have a clear sense that the other person is treating us unfairly does not bode well for our chances of achieving satisfying social connections in the long run, and it can place lonely individuals at greater risk of being scammed, or at least disappointed. Over time, the bad experiences that follow can contribute to the lonely person’s impression that, when you come right down to it, betrayal or rejection is lurking around every corner—a perception that plays into fear, hostility, learned helplessness, and passive coping. […] With an impaired ability to discriminate, persevere, and self-regulate, the lonely, both as children and as adults, often engage in extremes. Sometimes, in an effort to belong, they allow themselves to be pushed around, as in our “proposer/decider” game, when a lonely adult feels resentment, but goes ahead and accepts unfair offers. […] At other times, fear might lead […] to almost paranoid levels of self-protection […] whether driven by loneliness or by other factors, it is usually maladaptive to allow yourself to be taken advantage of. […] the most adaptive strategy is to maintain both the ability to detect cheating or betrayal and the ability to carefully modulate one’s response. The dysregulation caused by loneliness consigns us to the extremes of either suffering passively (responding too little) or being “difficult” (responding too intensely).”
“Among bonobos, if a low-ranking female commits some offense against a dominant female’s child, or grabs a piece of food that an older female had her eye on, or fails to surrender ground when a matriarch moves in to groom a male, the higher-ranking female may refuse to share food with or to accept grooming from her subordinate. This kind of rebuke can throw the younger animal into a tantrum right in front of the cold and rejecting elder. The affront is so stressful that it makes the subordinate physically sick, often causing her to vomit at the feet of her nemesis. It appears that apes do not enjoy social rejection any more than humans do.”
“The solution to loneliness is not quantity but quality of relationships. Human connections have to be meaningful and satisfying for each of the people involved, and not according to some external measure. Moreover, relationships are necessarily mutual and require fairly similar levels of intimacy and intensity on both sides. Even casual chitchat […] needs to proceed at a pace that is comfortable for everyone. Coming on too strong, oblivious to the other person’s response, is the quickest way to push someone away. So part of selection is sensing which prospective relationships are promising, and which would be climbing the wrong tree. Loneliness makes us very attentive to social signals. The trick is to be sufficiently calm and “in the moment” to interpret those signals accurately.”
“The kinds of connections — pets, computers — we substitute for human contact are called “parasocial relationships.” You can form a parasocial relationship with television characters, with people you “meet” online, or with your Yorkshire terrier. Is this an effective way to fill the void when connection with other humans, face to face, is thwarted?
The Greeks […] used the term “anthropomorphism” […] to describe the projection of specifically human attributes onto nonhuman entities. Increasing the strength of anthropomorphic beliefs appears to be a useful tactic for coping with loneliness, divorce, widowhood, or merely being single.16 Pet owners project all sorts of human attributes onto their animal companions, and elderly people who have pets appear to be buffered somewhat from the negative impact of stressful life events. They visit their doctors less often than do their petless age-mates. Individuals diagnosed with AIDS are less likely to become depressed if they own a pet. […] whether it’s a god, a devil, an animal, a machine […], a landmark, or a piece of cast-off sports equipment, the anthropomorphized being becomes a social surrogate, and the same neural systems that are activated when we make judgments about other humans are activated when we assess these parasocial relationships.21 […] Our parasocial relationships follow certain patterns based on aspects of our human relationships. People with insecure, anxious attachment styles are more likely than those with secure attachment styles to form perceived social bonds with television characters. They are also more likely than those with secure attachment styles to report an intensification of religious belief over a given time period, including sudden religious conversions later in life. […] Many proponents of technology tell us that computer-mediated social encounters will fill the void left by the decline of community in the real world. […] Studies have shown that the richer the medium […] the more it fosters social cohesion. This may be why, for those who do choose to connect electronically, multiplayer sites […] are becoming popular meeting places. […] forming connections with pets or online friends or even God is a noble attempt by an obligatorily gregarious creature to satisfy a compelling need. But surrogates can never make up completely for the absence of the real thing.”
This will be a brief post, but I forgot to add this link in my recent random stuff/open thread post and it’s arguably important enough to deserve a post of its own, so instead of adding a link to the old post – with the inherent risk of some people who’d be interested missing it – I’ll add a link here.
Svidler has won the Russian Championship 7 (7!) times, he’s the current number 19 in the world of the active players and has been a top player for as long as I can remember, he’s very charismatic and an excellent communicator, and, most importantly, he’s recently started producing videos where he plays short time control games against people on chess24 while at the same time explaining his thoughts and ideas along the way. Blitz games with people giving live commentary isn’t a new thing, people like IM Sielecki has done this stuff for years, but long sessions like the one above with a player as strong as Svidler definitely is.
Each session (the link above is just to his latest session – he’s produced others before (I’m sure you can find them via google or the chess24 website, I’m unfortunately too lazy to look up the links myself)) lasts somewhere between an hour and a half and two hours. In terms of ‘chess as entertainment’, it does not get much better than this.
Here’s my first post about the book. I’d probably have liked the book better if I hadn’t read the Cognitive Psychology text before this one, as knowledge from that book has made me think a few times in specific contexts that ‘that’s a bit more complicated than you’re making it out to be’ – as I also mentioned in the first post, the book is a bit too popular science-y for my taste. I have been reading other books in the last few days – for example I started reading Darwin a couple of days ago – and so I haven’t really spent much time on this one since my first post; however I have read the first 10 chapters (out of 14) by now, and below I’ve added a few observations from the chapters in the middle.
“In 1958, in a now-legendary, perhaps infamous experiment, the psychologist Harry Harlow of the University of Wisconsin removed newborn rhesus monkeys from their mothers. He presented these newborns instead with two surrogates, one made of wire and one made of cloth […]. Either stand-in could be rigged with a milk bottle, but regardless of which “mother” provided food, infant monkeys spent most of their time clinging to the one made of cloth, running to it immediately when startled or upset. They visited the wire mother only when that surrogate provided food, and then, only for as long as it took to feed.2
Harlow found that monkeys deprived of tactile comfort showed significant delays in their progress, both mentally and emotionally. Those deprived of tactile comfort and also raised in isolation from other monkeys developed additional behavioral aberrations, often severe, from which they never recovered. Even after they had rejoined the troop, these deprived monkeys would sit alone and rock back and forth. They were overly aggressive with their playmates, and later in life they remained unable to form normal attachments. They were, in fact, socially inept — a deficiency that extended down into the most basic biological behaviors. If a socially deprived female was approached by a normal male during the time when hormones made her sexually receptive, she would squat on the floor rather than present her hindquarters. When a previously isolated male approached a receptive female, he would clasp her head instead of her hindquarters, then engage in pelvic thrusts. […] Females raised in isolation became either incompetent or abusive mothers. Even monkeys raised in cages where they could see, smell, and hear — but not touch — other monkeys developed what the neuroscientist Mary Carlson has called an “autistic-like syndrome,” with excessive grooming, self-clasping, social withdrawal, and rocking. As Carlson told a reporter, “You were not really a monkey unless you were raised in an interactive monkey environment.””
In the authors’ coverage of oxytocin’s various roles in human- and animal social interaction they’re laying it on a bit thick in my opinion, and the less than skeptical coverage there leads me to also be somewhat skeptical of their coverage of the topic of mirror neurons, also on account of stuff like this. However I decided to add a little of the coverage of this topic anyway:
“In the 1980s the neurophysiologist Giacomo Rizzolatti began experimenting with macaque monkeys, running electrodes directly into their brains and giving them various objects to handle. The wiring was so precise that it allowed Rizzolatti and his colleagues to identify the specific monkey neurons that were activated at any moment.
When the monkeys carried out an action, such as reaching for a peanut, an area in the premotor cortex called F5 would fire […]. But then the scientists noticed something quite unexpected. When one of the researchers picked up a peanut to hand it to the monkey, those same motor neurons in the monkey’s brain fired. It was as if the animal itself had picked up the peanut. Likewise, the same neurons that fired when the monkey put a peanut in its mouth would fire when the monkey watched a researcher put a peanut in his mouth. […] Rizzolatti gave these structures the name “mirror neurons.” They fire even when the critical point of the action—the person’s hand grasping the peanut, for instance — is hidden from view behind some object, provided that the monkey knows there is a peanut back there. Even simply hearing the action — a peanut shell being cracked — can trigger the response. In all these instances, it is the goal rather than the observed action itself that is being mirrored in the monkey’s neural response. […] Rizzolatti and his colleagues confirmed the role of goals […] by performing brain scans while people watched humans, monkeys, and dogs opening and closing their jaws as if biting. Then they repeated the scans while the study subjects watched humans speak, monkeys smack their lips, and dogs bark.9 When the participants watched any of the three species carrying out the biting motion, the same areas of their brains were activated that activate when humans themselves bite. That is, observing actions that could reasonably be performed by humans, even when the performers were monkeys or dogs, activated the appropriate portion of the mirror neuron system in the human brain. […] the mirror neuron system isn’t simply “monkey see, monkey do,” or even “human see, human do.” It functions to give the observing individual knowledge of the observed action from a “personal” perspective. This “personal” understanding of others’ actions, it appears, promotes our understanding of and resonance with others.”
“In a study of how people monitor social cues, when researchers gave participants facts related to interpersonal or collective social ties presented in a diary format, those who were lonely remembered a greater proportion of this information than did those who were not lonely. Feeling lonely increases a person’s attentiveness to social cues just as being hungry increases a person’s attentiveness to food cues.28 […] They [later] presented images of twenty-four male and female faces depicting four emotions — anger, fear, happiness, and sadness — in two modes, high intensity and low intensity. The faces appeared individually for only one second, during which participants had to judge the emotional timbre. The higher the participants’ level of loneliness, the less accurate their interpretation of the facial expressions.”
“As we try to determine the meaning of events around us, we humans are not particularly good at knowing the causes of our own feelings or behavior. We overestimate our own strengths and underestimate our faults. We overestimate the importance of our contribution to group activities, the pervasiveness of our beliefs within the wider population, and the likelihood that an event we desire will occur.3 A At the same time we underestimate the contribution of others, as well as the likelihood that risks in the world apply to us. Events that unfold unexpectedly are not reasoned about as much as they are rationalized, and the act of remembering itself […] is far more of a biased reconstruction than an accurate recollection of events. […] Amid all the standard distortions we engage in, […] loneliness also sets us apart by making us more fragile, negative, and self-critical. […] One of the distinguishing characteristics of people who have become chronically lonely is the perception that they are doomed to social failure, with little if any control over external circumstances. Awash in pessimism, and feeling the need to protect themselves at every turn, they tend to withdraw, or to rely on the passive forms of coping under stress […] The social strategy that loneliness induces — high in social avoidance, low in social approach — also predicts future loneliness. The cynical worldview induced by loneliness, which consists of alienation and little faith in others, in turn, has been shown to contribute to actual social rejection. This is how feeling lonely creates self-fulfilling prophesies. If you maintain a subjective sense of rejection long enough, over time you are far more likely to confront the actual social rejection that you dread.8 […] In an effort to protect themselves against disappointment and the pain of rejection, the lonely can come up with endless numbers of reasons why a particular effort to reach out will be pointless, or why a particular relationship will never work. This may help explain why, when we’re feeling lonely, we undermine ourselves by assuming that we lack social skills that in fact, we do have available.”
“Because the emotional system that governs human self-preservation was built for a primitive environment and simple, direct dangers, it can be extremely naïve. It is impressionable and prefers shallow, social, and anecdotal information to abstract data. […] A sense of isolation can make [humans] feel unsafe. When we feel unsafe, we do the same thing a hunter-gatherer on the plains of Africa would do — we scan the horizon for threats. And just like a hunter-gatherer hearing an ominous sound in the brush, the lonely person too often assumes the worst, tightens up, and goes into the psychological equivalent of a protective crouch.”
“One might expect that a lonely person, hungry to fulfill unmet social needs, would be very accepting of a new acquaintance, just as a famished person might take pleasure in food that was not perfectly prepared or her favorite item on the menu. However, when people feel lonely they are actually far less accepting of potential new friends than when they feel socially contented.17 Studies show that lonely undergraduates hold more negative perceptions of their roommates than do their nonlonely peers.”
This is not a very ‘meaty’ post, but it’s been a long time since I had one of these and I figured it was time for another one. As always links and comments are welcome.
i. The unbearable accuracy of stereotypes. I made a mental note of reading this paper later a long time ago, but I’ve been busy with other things. Today I skimmed it and decided that it looks interesting enough to give it a detailed read later. Some remarks from the summary towards the end of the paper:
“The scientific evidence provides more evidence of accuracy than of inaccuracy in social stereotypes. The most appropriate generalization based on the evidence is that people’s beliefs about groups are usually moderately to highly accurate, and are occasionally highly inaccurate. […] This pattern of empirical support for moderate to high stereotype accuracy is not unique to any particular target or perceiver group. Accuracy has been found with racial and ethnic groups, gender, occupations, and college groups. […] The pattern of moderate to high stereotype accuracy is not unique to any particular research team or methodology. […] This pattern of moderate to high stereotype accuracy is not unique to the substance of the stereotype belief. It occurs for stereotypes regarding personality traits, demographic characteristics, achievement, attitudes, and behavior. […] The strong form of the exaggeration hypothesis – either defining stereotypes as exaggerations or as claiming that stereotypes usually lead to exaggeration – is not supported by data. Exaggeration does sometimes occur, but it does not appear to occur much more frequently than does accuracy or underestimation, and may even occur less frequently.”
ii. I’ve spent approximately 150 hours on vocabulary.com altogether at this point (having ‘mastered’ ~10.200 words in the process). A few words I’ve recently encountered on the site: Nescience (note to self: if someone calls you ‘nescient’ during a conversation, in many contexts that’ll be an insult, not a compliment) (Related note to self: I should find myself some smarter enemies, who use words like ‘nescient’…), eristic, carrel, oleaginous, decal, gable, epigone, armoire, chalet, cashmere, arrogate, ovine.
iv. A while back I posted a few comments on SSC and I figured I might as well link to them here (at least it’ll make it easier for me to find them later on). Here is where I posted a few comments on a recent study dealing with Ramadan-related IQ effects, a topic which I’ve covered here on the blog before, and here I discuss some of the benefits of not having low self-esteem.
On a completely unrelated note, today I left a comment in a reddit thread about ‘Books That Challenged You / Made You See the World Differently’ which may also be of interest to readers of this blog. I realized while writing the comment that this question is probably getting more and more difficult for me to answer as time goes by. It really all depends upon what part of the world you want to see in a different light; which aspects you’re most interested in. For people wondering about where the books about mathematics and statistics were in that comment (I do like to think these fields play some role in terms of ‘how I see the world‘), I wasn’t really sure which book to include on such topics, if any; I can’t think of any single math or stats textbook that’s dramatically changed the way I thought about the world – to the extent that my knowledge about these topics has changed how I think about the world, it’s been a long drawn-out process.
People who care the least bit about such things probably already know that a really strong tournament is currently being played in St. Louis, the so-called Sinquefield Cup, so I’m not going to talk about that here (for resources and relevant links, go here).
I talked about the strong rating pools on ICC not too long ago, but one thing I did not mention when discussing this topic back then was that yes, I also occasionally win against some of those grandmasters the rating pool throws at me – at least I’ve won a few times against GMs by now in bullet. I’m aware that for many ‘serious chess players’ bullet ‘doesn’t really count’ because the time dimension is much more important than it is in other chess settings, but to people who think skill doesn’t matter much in bullet I’d say they should have a match with Hikaru Nakamura and see how well they do against him (if you’re interested in how that might turn out, see e.g. this video – and keep in mind that at the beginning of the video Nakamura had already won 8 games in a row, out of 8, against his opponent in the first games, who incidentally is not exactly a beginner). The skill-sets required do not overlap perfectly between bullet and classical time control games, but when I started playing bullet online I quickly realized that good players really require very little time to completely outplay people who just play random moves (fast). Below I have posted a screencap I took while kibitzing a game of one of my former opponents, an anonymous GM from Germany, against whom I currently have a 2.5/6 score, with two wins, one draw, and three losses (see the ‘My score vs CPE’ box).
I like to think of a score like this as at least some kind of accomplishment, though admittedly perhaps not a very big one.
Also in chess-related news, I’m currently reading Jesús de la Villa’s 100 Endgames book, which Christof Sielecki has said some very nice things about. A lot of the stuff I’ve encountered so far is stuff I’ve seen before, positions I’ve already encountered and worked on, endgame principles I’m familiar with, etc., but not all of it is known stuff and I really like the structure of the book. There are a lot of pages left, and as it is I’m planning to read this book from cover to cover, which is something I usually do not do when I read chess books (few people do, judging from various comments I’ve seen people make in all kinds of different contexts).
Lastly, a lecture:
Like in the first post I cannot promise I have not already covered the topics I’m about to cover in this post before on the blog. In this post I’ll include and discuss material from two chapters of the book: the chapters on how to measure, value, and analyze health outcomes, and the chapter on how to define, measure, and value costs. In the last part of the post I’ll also talk a little bit about some research related to the coverage which I’ve recently looked at in a different context.
In terms of how to measure health outcomes the first thing to note is that there are lots and lots of different measures (‘thousands’) that are used to measure aspects of health. The symptoms causing problems for an elderly man with an enlarged prostate are not the same symptoms as the ones which are bothering a young child with asthma, and so it can be very difficult to ‘standardize’ across measures (more on this below).
A general distinction in this area is that between non-preference-based measures and preference-based measures. Many researchers working with health data are mostly interested in measuring symptoms, and metrics which do (‘only’) this would be examples of non-preference-based measures. Non-preference based measures can again be subdivided into disease- and symptom-specific measures, and non-disease-specific/generic measures; an example of the latter would be the SF-36, ‘the most widely used and best-known example of a generic or non-disease-specific measure of general health’.
Economists will often want to put a value on symptoms or quality-of-life states, and in order to do this you need to work with preference-based measures – there are a lot of limitations one confronts when dealing with non-preference-based measures. Non-preference based measures tend for example to be very different in design and purpose (because asthma is not the same thing as, say, bulimia), which means that there is often a lack of comparability across measures. It is also difficult to know how to properly trade off various dimensions included when using such metrics (for example pain relief can be the result of a drug which also increases nausea, and it’s not perfectly clear when you use such measures whether such a change is to be considered desirable or not); similar problems occur when taking the time dimension into account, where problems with aggregation over time and how to deal with this pop up. Various problems related to weighting are recurring problems; for example a question can be asked when using such measures which symptoms/dimensions included are more important? Are they all equally important? This goes for both the weighting of various different domains included in the metric, and for how to weigh individual questions within a given domain. Many non-preference-based measures contain an implicit equal-interval assumption, so that a move from (e.g.) level one to level two on the metric (e.g. from ‘no pain at all’ to ‘a little’) is considered the same as a move from (e.g.) level three to level four (e.g. ‘quite a bit’ to ‘very much’), and it’s not actually clear that the people who supply the information that goes into these metrics would consider such an approach to be a correct reflection of how they perceive these things. Conceptually related to the aggregation problem mentioned above is the problem that people may have different attitudes toward short-term and long-term health effects/outcomes, but non-preference-based measures usually give equal weight to a health state regardless of the timing of the health state. The issue of some patients dying is not addressed at all when using these measures, as they do not contain information about mortality; which may be an important variable. For all these reasons the authors argue in the text that:
“In summary, non-preference-based health status measures, whether disease specific or generic, are not suitable as outcome measures in economic evaluation. Instead, economists require a measure that combines quality and quantity of life, and that also incorporates the valuations that individuals place on particular states of health.
The outcome metric that is currently favoured as meeting these requirements and facilitating the widest possible comparison between alternative uses of health resources is the quality-adjusted life year“.
Non-preference-based tools may be useful, but you will usually need to go ‘further’ than those to be able to handle the problems economists will tend to care the most about. Some more observations from the chapter below:
“the most important challenge [when valuing health states] is to find a reliable way of quantifying the quality of life associated with any particular health state. There are two elements to this: describing the health state, which […] could be either a disease-specific description or a generic description intended to cover many different diseases, and placing a valuation on the health state. […] these weights or valuations are related to utility theory and are frequently referred to as utilities or utility values.
Obtaining utility values almost invariably involves some process by which individuals are given descriptions of a number of health states and then directly or indirectly express their preferences for these states. It is relatively simple to measure ordinal preferences by asking respondents to rank-order different health states. However, these give no information on strength of preference and a simple ranking suffers from the equal interval assumption […]; as a result they are not suitable for economic evaluation. Instead, analysts make use of cardinal preference measurement. Three main methods have been used to obtain cardinal measures of health state preferences: the rating scale, the time trade-off, and the standard gamble. […] The large differences typically observed between RS [rating scale] and TTO [time trade-off] or SG [standard gamble] valuations, and the fact that the TTO and SG methods are choice based and therefore have stronger foundations in decision theory, have led most standard texts and guidelines for technology appraisal to recommend choice-based valuation methods [The methods are briefly described here, where the ‘VAS’ corresponds to the rating scale method mentioned – the book covers the methods in much more detail, but I won’t go into those details here].”
“Controversies over health state valuation are not confined to the valuation method; there are also several strands of opinion concerning who should provide valuations. In principle, valuations could be provided by patients who have had first-hand experience of the health state in question, or by experts such as clinicians with relevant scientific or clinical expertise, or by members of the public. […] there is good evidence that the valuations made by population samples and patients frequently vary quite substantially [and] the direction of difference is not always consistent. […] current practice has moved towards the use of valuations obtained from the general public […], an approach endorsed by recent guidelines in the UK and USA explicitly recommend that population valuations are used”.
Given the very large number of studies which have been based on non-preference based instruments, it would be desirable for economists working in this field to somehow ‘translate’ the information contained in those studies so that this information can also be used for cost-effectiveness evaluations. As a result of this an increasing number of so-called ‘mapping studies’ have been conducted over the years, the desired goal of which is to translate the non-preference based measures into health state utilities, allowing outcomes and effects derived from the studies to be expressed in terms of QALYs. There’s more than one way to try to get from a non-preference based metric to a preference-based metric and the authors describe three approaches in some detail, though I’ll not discuss those approaches or details here. They make this concluding assessment of mapping studies in the text:
“Mapping studies are continuing to proliferate, and the literature on new mapping algorithms and methods, and comparisons between approaches, is expanding rapidly. In general, mapping methods seem to have reasonable ability to predict group mean utility scores and to differentiate between groups with or without known existing illness. However, they all seem to predict increasingly poorly as health states become more serious. […] all forms of mapping are ‘second best’, and the existence of a range of techniques should not be taken as an argument for relying on mapping instead of obtaining direct preference-based measurements in prospectively designed studies.”
I won’t talk too much about the chapter on how to define, measure and value costs, but I felt that a few observations from the chapter should be included in the coverage:
“When asking patients to complete resource/time questionnaires (or answer interview questions), a particularly important issue is deciding on the optimum recall period. Two types of recall error can be distinguished: simply forgetting an entire episode, or incorrectly recalling when it occurred. […] there is a trade-off between recall bias and complete sampling information. […] the longer the period of recall the greater is the likelihood of recall error, but the shorter the recall period the greater is the problem of missing information.”
“The range of patient-related costs included in economic valuations can vary considerably. Some studies include only the costs incurred by patients in travelling to a hospital or clinic for treatment; others may include a wider range of costs including over-the-counter purchases of medications or equipment. However, in some studies a much broader approach is taken, in which attempts are made to capture both the costs associated with treatments and the consequences of illness in terms of absence from or cessation of work.”
An important note here which I thought I should add is that whereas many people unfamiliar with this field may translate ‘medical costs of illness’ with ‘the money that is paid to the doctor(s)’, direct medical costs will in many cases drastically underestimate the ‘true costs’ of disease. To give an example, Ferber et al. (2006) when looking at the costs of diabetes included two indirect cost components in their analysis – inability to work, and early retirement – and concluded that these two cost components made up approximately half of the total costs of diabetes. I think there are reasons to be skeptical of the specific estimate on account of the way it is made (for example if diabetics are less productive/earn less than the population in general, which seems likely if the disease is severe enough to cause many people to withdraw prematurely from the labour market, the cost estimate may be argued to be an overestimate), but on the other hand there are multiple other potentially important indirect cost components they do not include in the calculation, such as e.g. disease-related lower productivity while at work (for details on this, see e.g. this paper – that cost component may also be substantial in some contexts) and things like spousal employment spill-over effects (it is known from related research – for an example, see this PhD dissertation – that disease may impact on the retirement decisions of the spouse of the individual who is sick, not just the individual itself, but effects here are likely to be highly context-dependent and to vary across countries). Another potentially important variable in an indirect cost context is informal care provision. Here’s what they authors say about that one:
“Informal care is often provided by family members, friends, and volunteers. Devoting time and resources to collecting this information may not be worthwhile for interventions where informal care costs are likely to form a very small part of the total costs. However, in other studies non-health-service costs could represent a substantial part of the total costs. For instance, dementia is a disease where the burden of care is likely to fall upon other care agencies and family members rather than entirely on the health and social care services, in which case considering such costs would be important.
To date [however], most economic evaluations have not considered informal care costs.”
I’m currently reading this book by John Cacioppo and William Patrick. It’s a bit too soft/popular science-y for my taste, but the material is interesting.
Below some observations from the book’s part one:
“Serving as a prompt to restore social bonds, loneliness increases the sensitivity of our receptors for social signals. At the same time, because of the deeply rooted fear it represents, loneliness disrupts the way those signals are processed, diminishing the accuracy of the message that actually gets through. When we are persistently lonely, this dual influence — higher sensitivity, less accuracy — can leave us misconstruing social signals that others do not even detect, or if they detect, interpret quite differently.
Reading and interpreting social cues is for any of us, at any time, a demanding and cognitively complex activity, which is why our minds embrace any shortcut that simplifies the job. […] We [all] invariably take cognitive shortcuts, but when we are lonely, the social expectations and snap judgments we create are generally pessimistic. We then use them to construct a bulwark against the negative evaluations and ultimate rejection that the fearful nature of loneliness encourages us to anticipate.”
“When we feel socially connected […] we tend to attribute success to our own actions and failure to bad luck. When we feel socially isolated and depressed, we tend to reverse this useful illusion and turn even small errors into catastrophes—at least in our own minds. Meanwhile, we use the same everyday cognitive shortcuts to try to barricade ourselves against criticism and responsibility for our screw-ups. The net result is that, over time, if we get stuck in loneliness, this complex pattern of behavior can contribute to our isolation from other people. […] What makes loneliness especially insidious is that it contains this Catch-22: Real relief from loneliness requires the cooperation of at least one other person, and yet the more chronic our loneliness becomes, the less equipped we may be to entice such cooperation. Other negative states, such as hunger and pain, that motivate us to make changes to modify unpleasant or aversive conditions can be dealt with by simple, individual action. When you feel hungry, you eat. […] But when the unpleasant state is loneliness, the best way to get relief is to form a connection with someone else. Each of the individuals involved must be willing to connect, must be free to do so, and must agree to more or less the same timetable. Frustration with the difficulty imposed by these terms can trigger hostility, depression, despair, impaired skills in social perception, as well as a sense of diminished personal control. This is when failures of self-regulation, combined with the desire to mask pain with whatever pleasure is readily available, can lead to unwise sexual encounters, too much to drink, or a sticky spoon in the bottom of an empty quart of ice cream. Once this negative feedback loop starts rumbling through our lives, others may start to view us less favorably because of our self-protective, sometimes distant, sometimes caustic behavior. This, in turn, merely reinforces our pessimistic social expectations. Now others really are beginning to treat us badly, which seems like adding insult to injury, which spins the cycle of defensive behavior and negative social results even further downhill.”
“In 2002 our team at the University of Chicago began collecting longitudinal data on a representative sample of middle-aged and older citizens in the greater Chicago metropolitan area. We subjected these volunteers to numerous physiological and psychological measurements, including the UCLA Loneliness Scale. […] When we analyzed the diets of these older adults, what they ate week after week, month after month in real life [we found that] older adults who felt lonely in their daily lives had a substantially higher intake of fatty foods. […] we found that the calories of fat they consumed increased by 2.56 percent for each standard deviation increase in loneliness as measured by the UCLA Loneliness Scale.12“
I must admit I found this finding in particular quite interesting, and surprising:
“In another study, researchers asked participants either to describe a personal problem to an assigned partner, or to adopt the role of listener while the partner described his or her problem.17 Lonely individuals, when specifically requested to take the helping role, were just as socially skilled as the others. They were active listeners, they offered assistance to their partners, and they stayed with the conversation longer than those who were describing their troubles. So we retain the ability to be socially adept when we feel lonely. […] [However] [d]espite their display of skill in the experiment, the lonely participants consistently rated themselves as being less socially adept than other people.”
“factor analysis tells us that loneliness and depression are, in fact, two distinct dimensions of experience.10 […] Loneliness reflects how you feel about your relationships. Depression reflects how you feel, period. Although both are aversive, uncomfortable states, loneliness and depression are in many ways opposites. Loneliness, like hunger, is a warning to do something to alter an uncomfortable and possibly dangerous condition. Depression makes us apathetic. Whereas loneliness urges us to move forward, depression holds us back. But where depression and loneliness converge is in a diminished sense of personal control, which leads to passive coping. This induced passivity is one of the reasons that, despite the pain and urgency that loneliness imposes, it does not always lead to effective action. Loss of executive control leads to lack of persistence, and frustration leads to what the psychologist Martin Seligman has termed “learned helplessness.””
“For our cross-sectional analysis, we went back to the large population of Ohio State students that had supplied volunteers for our dichotic listening test. We refined our sample down to 135 participants, 44 of them high in loneliness, 46 average, and 45 low in loneliness, with each subset equally divided between men and women.16 […] this study population gave us a clear picture of the full psychological drama accompanying loneliness as it occurs in the day-to-day lives of a great many people observed during a specific period of time. The cluster of characteristics we found were the ones we had anticipated: depressed affect, shyness, low self-esteem, anxiety, hostility, pessimism, low agreeableness, neuroticism, introversion, and fear of negative evaluation. […] Analysis of the longitudinal data from our middle-aged and older adults showed that a person’s degree of loneliness in the first year of the study predicted changes in that person’s depressive symptoms during the next two years.21 The lonelier that people were at the beginning, the more depressive affect they experienced in the following years, even after we statistically controlled for their depressive feelings in the first year. We also found that a person’s level of depressive symptoms in the first year of the study predicted changes in that person’s loneliness during the next two years. Those who felt depressed withdrew from others and became lonelier over time.”
“In 1988 an article in Science reviewed [research on loneliness], and that meta-analysis indicated that social isolation is on a par with high blood pressure, obesity, lack of exercise, or smoking as a risk factor for illness and early death.4 For some time the most common explanation for this sizeable effect has been the “social control hypothesis.” This theory holds that, in the absence of a spouse or close friends who might provide material help or a more positive influence, individuals may have a greater tendency to gain weight, to drink too much, or to skip exercise. […] But epidemiological research done on the heels of the analysis published in Science determined that the health effect associated with isolation was statistically too large and too dramatic to be attributed entirely to differences in behavior.”
However behaviour does matter:
“we found that the health-related behaviors of lonely young people were no worse than those of socially embedded young people. In terms of alcohol consumption, their behavior was, in fact, more restrained and healthful. […] our study of older adults did [however] indicate that, by middle age, time had taken its toll, and the health habits of the lonely had indeed become worse than those of socially embedded people of similar age and circumstances.21 Although lonely young adults were no different from others in their exercise habits, measured either by frequency of activity or by total hours per week, the picture changed with our middle-aged and older population. Socially contented older adults were thirty-seven percent more likely than lonely older adults to have engaged in some type of vigorous physical activity in the previous two weeks. On average they exercised ten minutes more per day than their lonelier counterparts.”
“It may be that the decline in healthful behavior in the lonely can be partially explained by the impairment in executive function, and therefore in self-regulation, that we saw in individuals induced to feel socially rejected. Doing what is good for you, rather than what merely feels good in the moment, requires disciplined self-regulation. Going for a run might feel good when you’re finished, but for most of us, getting out the door in the first place requires an act of willpower. The executive control required for such discipline is compromised by loneliness, and loneliness also tends to lower self-esteem. If you perceive that others see you as worthless, you are more likely to engage in self-destructive behaviors and less likely to take good care of yourself.
Moreover, for lonely older adults, it appears that emotional distress about loneliness, combined with a decline in executive function, leads to attempts to manage mood by smoking, drinking, eating too much, or acting out sexually. Exercise would be a far better way to try to achieve a lift in mood, but disciplined exercise, again, requires executive control. Getting down to the gym or the yoga class three times a week also is much easier if you have friends you enjoy seeing there who reinforce your attempts to stay in shape.”
“Our surveys with the undergraduates at Ohio State showed that lonely and non-lonely young adults did not differ in their exposure to major life stressors, or in the number of major changes they had endured in the previous twelve months. […] However, among the older adults we studied, we found that those who were lonelier also reported larger numbers of objective stressors as being “current” in their lives. It appears that, over time, the “self-protective” behavior associated with loneliness leads to greater marital strife, more run-ins with neighbors, and more social problems overall. […] Even setting aside the larger number of objective stressors in their lives, the lonely express greater feelings of helplessness and threat. In our studies, the lonely, both young and old, perceived the hassles and stresses of everyday life to be more severe than did their non-lonely counterparts, even though the objective stressors they encountered were essentially the same. Compounding the problem, the lonely found the small social uplifts of everyday life to be less intense and less gratifying. […] when people feel lonely, they are far less likely to see any given stressor as an invigorating challenge. Instead of responding with realistic optimism and active engagement, they tend to respond with pessimism and avoidance. They are more likely to cope passively, which means enduring without attempting to change the situation.”
“We found loneliness to be associated with higher traces of the stress hormone epinephrine in the morning urine of older adults.30 Other studies have shown that the allostatic load of feeling lonely also affects the body’s immune and cardiovascular function. Years ago, a classic test with medical students showed that the stress of exams could have a dramatic dampening effect on the immune response, leaving the students more vulnerable to infections. Further studies showed that lonely students were far more adversely affected than those who felt socially contented.”
“One clearly demonstrable consequence of social alienation and isolation for physiological resilience and recovery occurs in the context of the quintessential restorative behavior — sleep. […] when we asked participants to wear a device called the “nightcap” to record changes in the depth and quality of their sleep, we found that total sleep time did not differ across the groups. However, lonely young adults reported taking longer to fall sleep and also feeling greater daytime fatigue.39 Our studies of older adults yielded similar findings, and longitudinal analyses confirmed that it was loneliness specifically that was associated with changes in daytime fatigue. Even though the lonely got the same quantity of sleep as the nonlonely, their quality of sleep was greatly diminished.40″
Yesterday’s SMBC was awesome, and I couldn’t help myself from including it here (click to view full size):
In a way the three words I chose to omit from the post title are rather important in order to know which kind of book this is – the full title of Gray et al.’s work is: Applied Methods of … – but as I won’t be talking much about the ‘applied’ part in my coverage here, focusing instead on broader principles etc. which will be easier for people without a background in economics to follow, I figured I might as well omit those words from the post titles. I should also admit that I personally did not spend much time on the exercises, as this did not seem necessary in view of what I was using the book for. Despite not having spent much time on the exercises myself, I incidentally did reward the authors for including occasionally quite detailed coverage of technical aspects in my rating of the book on goodreads; I feel confident from the coverage that if I need to apply some of the methods they talk about in the book later on, the book will do a good job of helping me get things right. All in all, the book’s coverage made it hard for me not to give it 5 stars – so that was what I did.
I own an actual physical copy of the book, which makes blogging it more difficult than usual; I prefer blogging e-books. The greater amount of work involved in covering physical books is also one reason why I have yet to talk about Eysenck & Keane’s Cognitive Psychology text here on the blog, despite having read more than 500 pages of that book (it’s not that the book is boring). My coverage of the contents of both this book and the Eysenck & Keane book will (assuming I ever get around to blogging the latter, that is) be less detailed than it could have been, but on the other hand it’ll likely be very focused on key points and observations from the coverage.
I have talked about cost-effectiveness before here on the blog, e.g. here, but in my coverage of the book below I have not tried to avoid making points or including observations which I’ve already made elsewhere on the blog; it’s too much work to keep track of such things. With those introductory remarks out of the way, let’s move on to some observations made in the book:
“In cost-effectiveness analysis we first calculate the costs and effects of an intervention and one or more alternatives, then calculate the differences in cost and differences in effect, and finally present these differences in the form of a ratio, i.e. the cost per unit of health outcome effect […]. Because the focus is on differences between two (or more) options or treatments, analysts typically refer to incremental costs, incremental effects, and the incremental cost-effectiveness ratio (ICER). Thus, if we have two options a and b, we calculate their respective costs and effects, then calculate the difference in costs and difference in effects, and then calculate the ICER as the difference in costs divided by the difference in effects […] cost-effectiveness analyses which measure outcomes in terms of QALYs are sometimes referred to as cost-utility studies […] but are sometimes simply considered as a subset of cost-effectiveness analysis.”
“Cost-effectiveness analysis places no monetary value on the health outcomes it is comparing. It does not measure or attempt to measure the underlying worth or value to society of gaining additional QALYs, for example, but simply indicates which options will permit more QALYs to be gained than others with the same resources, assuming that gaining QALYs is agreed to be a reasonable objective for the health care system. Therefore the cost-effectiveness approach will never provide a way of determining how much in total it is worth spending on health care and the pursuit of QALYs rather than on other social objectives such as education, defence, or private consumption. It does not permit us to say whether health care spending is too high or too low, but rather confines itself to the question of how any given level of spending can be arranged to maximize the health outcomes yielded.
In contrast, cost-benefit analysis (CBA) does attempt to place some monetary valuation on health outcomes as well as on health care resources. […] The reasons for the more widespread use of cost-effectiveness analysis compared with cost-benefit analysis in health care are discussed extensively elsewhere, […] but two main issues can be identified. Firstly, significant conceptual or practical problems have been encountered with the two principal methods of obtaining monetary valuations of life or quality of life: the human capital approach […] and the willingness to pay approach […] Second, within the health care sector there remains a widespread and intrinsic aversion to the concept of placing explicit monetary values on health or life. […] The cost-benefit approach should […], in principle, permit broad questions of allocative efficiency to be addressed. […] In contrast, cost-effectiveness analysis can address questions of productive or production efficiency, where a specified good or service is being produced at the lowest possible cost – in this context, health gain using the health care budget.”
“when working in the two-dimensional world of cost-effectiveness analysis, there are two uncertainties that will be encountered. Firstly, there will be uncertainty concerning the location of the intervention on the cost-effectiveness plane: how much more or less effective and how much more or less costly it is than current treatment. Second, there is uncertainty concerning how much the decision-maker is willing to pay for health gain […] these two uncertainties can be presented together in the form of the question ‘What is the probability that this intervention is cost-effective?’, a question which effectively divides our cost-effectiveness plane into just two policy spaces – below the maximum acceptable line, and above it”.
“Conventionally, cost-effectiveness ratios that have been calculated against a baseline or do-nothing option without reference to any alternatives are referred to as average cost-effectiveness ratios, while comparisons with the next best alternative are described as incremental cost-effectiveness ratios […] it is quite misleading to calculate average cost-effectiveness ratios, as they ignore the alternatives available.”
“A life table provides a method of summarizing the mortality experience of a group of individuals. […] There are two main types of life table. First, there is a cohort life table, which is constructed based on the mortality experience of a group of individuals […]. While this approach can be used to characterize life expectancies of insects and some animals, human longevity makes this approach difficult to apply as the observation period would have to be sufficiently long to be able to observe the death of all members of the cohort. Instead, current life tables are normally constructed using cross-sectional data of observed mortality rates at different ages at a given point in time […] Life tables can also be classified according to the intervals over which changes in mortality occur. A complete life table displays the various rates for each year of life; while an abridged life table deals with greater periods of time, for example 5 year age intervals […] A life table can be used to generate a survival curve S(x) for the population at any point in time. This represents the probability of surviving beyond a certain age x (i.e. S(x)=Pr[X>x]). […] The chance of a male living to the age of 60 years is high (around 0.9) [in the UK, presumably – US] and so the survival curve is comparatively flat up until this age. The proportion dying each year from the age of 60 years rapidly increases, so the curve has a much steeper downward slope. In the last part of the survival curve there is an inflection, indicating a slowing rate of increase in the proportion dying each year among the very old (over 90 years). […] The hazard rate is the slope of the survival curve at any point, given the instantaneous chance of an individual dying.”
“Life tables are a useful tool for estimating changes in life expectancies from interventions that reduce mortality. […] Multiple-cause life tables are a way of quantifying outcomes when there is more than one mutually exclusive cause of death. These life tables can estimate the potential gains from the elimination of a cause of death and are also useful in calculating the benefits of interventions that reduce the risk of a particular cause of death. […] One issue that arises when death is divided into multiple causes in this type of life table is competing risk. […] competing risk can arise ‘when an individual can experience more than one type of event and the occurrence of one type of event hinders the occurrence of other types of events’. Competing risks affect life tables, as those who die from a specific cause have no chance of dying from other causes during the remainder of the interval […]. In practice this will mean that as soon as one cause is eliminated the probabilities of dying of other causes increase […]. Several methods have been proposed to correct for competing risks when calculating life tables.”
“the use of published life-table methods may have limitations, especially when considering particular populations which may have very different risks from the general population. In these cases, there are a host of techniques referred to as survival analysis which enables risks to be estimated from patient-level data. […] Survival analysis typically involves observing one or more outcomes in a population of interest over a period of time. The outcome, which is often referred to as an event or endpoint could be death, a non-fatal outcome such as a major clinical event (e.g. myocardial infarction), the occurrence of an adverse event, or even the date of first non-compliance with a therapy.”
“A key feature of survival data is censoring, which occurs whenever the event of interest is not observed within the follow-up period. This does not mean that the event will not occur some time in the future, just that it has not occurred while the individual was observed. […] The most common case of censoring is referred to as right censoring. This occurs whenever the observation of interest occurs after the observation period. […] An alternative form of censoring is left censoring, which occurs when there is a period of time when the individuals are at risk prior to the observation period.
A key feature of most survival analysis methods is that they assume that the censoring process is non-informative, meaning that there is no dependence between the time to the event of interest and the process that is causing the censoring. However, if the duration of observation is related to the severity of a patient’s disease, for example if patients with more advanced illness are withdrawn early from the study, the censoring is likely to be informative and other techniques are required”.
“Differences in the composition of the intervention and control groups at the end of follow-up may have important implications for estimating outcomes, especially when we are interested in extrapolation. If we know that the intervention group is older and has a lower proportion of females, we would expect these characteristics to increase the hazard mortality in this group over their remaining lifetimes. However, if the intervention group has experienced a lower number of events, this may significantly reduce the hazard for some individuals. They may also benefit from a past treatment which continues to reduce the hazard of a primary outcome such as death. This effect […] is known as the legacy effect“.
“Changes in life expectancy are a commonly used outcome measure in economic evaluation. […] Table 4.6 shows selected examples of estimates of the gain in life expectancy for various interventions reported by Wright and Weinstein (1998) […] Gains in life expectancy from preventative interventions in populations of average risk generally ranged from a few days to slightly more than a year. […] The gains in life expectancy from preventing or treating disease in persons at elevated risk [this type of prevention is known as ‘secondary-‘ and/or ‘tertiary prevention’ (depending on the circumstances), as opposed to ‘primary prevention’ – the distinction between primary prevention and more targeted approaches is often important in public health contexts, because the level of targeting will often interact with the cost-effectiveness dimension – US] are generally greater […one reason why this does not necessarily mean that targeted approaches are always better is that search costs will often be an increasing function of the level of targeting – US]. Interventions that treat established disease vary, with gains in life-expectancy ranging from a few months […] to as long as nine years […] the point that Wright and Weinstein (1998) were making was not that absolute gains vary, but that a gain in life expectancy of a month from a preventive intervention targeted at population at average risk and a gain of a year from a preventive intervention targeted at populations at elevated risk could both be considered large. It should also be noted that interventions that produce a comparatively small gain in life expectancy when averaged across the population […] may still be very cost-effective.”
i. “Ideas have consequences, and totally erroneous ideas are likely to have destructive consequences.” (Steve Allen)
ii. “I always pass on good advice. It is the only thing to do with it. It is never of any use to oneself.” (Oscar Wilde, An Ideal Husband)
iii. “[Sir Robert Chiltern:] No one should be entirely judged by their past.
[Lady Chiltern, sadly:] One’s past is what one is. It is the only way by which people should be judged.” (-ll-)
iv. “Extremists think “communication” means agreeing with them.” (Leo Rosten)
v. “The purpose of life is not to be happy at all. It is to be useful, to be honorable. It is to be compassionate. It is to matter, to have it make some difference that you lived.” (-ll-)
vi. “Don’t commit suicide, because you might change your mind two weeks later.” (Art Buchwald)
vii. “I honestly believe it is better to know nothing than to know what ain’t so.” (Josh Billings)
viii. “Better make a weak man your enemy than your friend.” (-ll-)
ix. “I hate plays. I’ve never seen the point of paying money to watch people shout a lot and pretend to die, and now that I’m the father of three young children I don’t have to.” (Tim Moore)
x. “Any given generation gives the next generation advice that the given generation should have been given by the previous generation but now it’s too late.” (Roy Blount, Jr.)
xi. “People don’t necessarily want or need to be done unto as you would have them do unto you. They want to be done unto as they want to be done unto.” (-ll-)
xii. “From the moment I picked up your book until I laid it down, I was convulsed with laughter. Someday I intend reading it.” (Groucho Marx, on S. J. Perelman’s novel Dawn Ginsbergh’s Revenge)
xiii. “I find television very educational. Every time someone switches it on I go into another room and read a good book.” (Groucho Marx)
xiv. “This is my perspective and has always been my perspective on life: I have a very grim, pessimistic view of it. I always have, since I was a little boy. It hasn’t gotten worse with age or anything. I do feel that it’s a grim, painful, nightmarish, meaningless experience, and that the only way that you can be happy is if you tell yourself some lies and deceive yourself.” (Woody Allen)
xv. “It’s not that I’m afraid to die, I just don’t want to be there when it happens.” (-ll-)
xvi. “Nine-tenths of the value of a sense of humor in writing is not in the things it makes one write but in the things it keeps one from writing. […] without knowing what is funny, one is constantly in danger of being funny without knowing it.” (Robert Benchley)
xvii. “Only the mediocre are always at their best.” (Jean Giradoux)
xviii. “The world is divided into people who do things and people who get the credit. Try, if you can, to belong to the first class. There’s far less competition.” (Dwight Morrow)
xix. We are all inclined to judge ourselves by our ideals; others by their acts. (-ll-)
xx. Who speaks the truth stabs Falsehood to the heart. (James Russell Lowell)
As mentioned in my first post about the book, I realized late in the writing process that I’d be unable to cover it in one post, so this post will not cover nearly as much of the book as did the first post and it will not be particularly long. However some of the observations in the last part I found interesting, so I wanted to talk a little bit about them here.
“The definition of violence indicates that the aggressor is the one who deliberately hurts the partner, and the victim is the one deliberately hurt by the partner. The definition is indifferent to the reasons leading up to the act of violence and its goals. I collaborated in a study that examined how partners perceive the violence between them […] In some cases, the research participants argued that the injury was extremely mild. In other cases, they claimed that the injury was not intentional. Some cases combined both arguments. But even when intentionally hurtful behavior was acknowledged, the tendency to reject responsibility and blame was still identified. In such cases, it was argued that the intentionally hurtful behavior is not to be considered as violence if the offender was not an aggressor or if the offended was not a victim. Such cases emphasize that examining behavior in terms of intentional injury to identify violence produces inadequate results; the causality sequence and the conduct of the offender and offended during the incident should also be examined. […] intentional infliction is insufficient to establish violence. […] Despite the limitations […] of the definition of violence as an intentional hurtful behavior, it was […] and still is used by numerous studies to design the individual behavioral observation unit of partner violence.”
On a related note, this part was really interesting to me:
“I had the opportunity to hold a series of sessions with adolescents at the ages of 12–16 within the framework of a project for coping with school violence, conducted in 2007. […] One of the sessions addressed boys’ and girls’ methods of initiating a dating relationship. The students mentioned that when a boy likes a girl, is attracted to her and would like to have an intimate relationship with her, he can approach her and make a direct intimate proposition. If she accepts, then “everyone is happy,” but if she turns him down, then “it is a huge embarrassment.” The session participants explained that such rejection is usually a difficult, humiliating, and intimidating experience, and therefore, many are deterred from initiating in this way. Many boys and girls avoid a direct, clear, and unequivocal approach and prefer other, more indirect methods of “checking” the other party’s willingness to start a relationship with them. These methods often employ violence, which can be interpreted as expressions of either hostility or affection. For example, the boy can playfully grab the girl’s hand while pinning her against a wall. If the girl chooses a hostile, nonreceptive response, the boy will interpret this as evidence that she is not interested in a relationship with him and in most cases will retreat. If the girl chooses to respond playfully or display vague affection and receptiveness, the boy can interpret this as an invitation. A negative response on behalf of the girl will not be experienced as rejection by the boy because he did not express his interest clearly. A positive, tolerant response by the girl can encourage the boy to continue approaching her, maybe with less aggression next time. The students considered this behavior to be an acceptable and reasonable method of dating initiation. […] It is a widespread behavior which many people, and not only adolescents, do not regard as violent behavior (Playful Violence) (Denzin, 1984). Such behaviors are especially frequent among youth and […] may include holding/grasping/pinning down, pushing, and shoving by boys, and pushing, pinching, hair pulling, and mild blows by girls.” (my bold).
Part of why the above observations were interesting to me was that during my own childhood/youth I had no idea such behaviour was an approach tactic, and I was at a loss to explain such behaviours the few times in the past that I observed such behaviours myself. While reading the chapter I suddenly came to realize that I may have been the target of such behaviour myself during my childhood (let’s just say that one particular sequence of events which I had a great deal of difficulty making sense of in the past makes a lot more sense in light of the above observations). My lack of awareness of the relevant social dynamics embedded in such interactions of course means that my response to the approach behaviour may not have been the response I would have employed had I known about these things (due to being completely clueless, I probably treated that girl very badly. Oh well, as Rochefoucauld’s aptly put it: ‘Il n’y a guère d’homme assez habile pour connaître tout le mal qu’il fait’).
“Although most of the quantitative research [on violence] is based on data regarding individual single violent behaviors isolated from the immediate situational context, in many cases, the analyses, the interpretations, and conclusions are performed as if the behaviors are sequenced (the hurtful behaviors of one party are regarded as a defensive response to the violence of the other party). This is similar to looking at a series of photos set in no particular order while trying to make sense of the timeline of the incident that they describe. […] Defining the boundaries of a conflict (where it starts and ends) is crucial to the identification of the relevant interactions to be studied.”
“Swann, Pelham, and Roberts (1987) argued that, as a rule, individuals simplify their interactions by forming, arranging, and perceiving them in “discrete causal chunks.” These chunks affect individuals’ awareness of the effect of their actions upon others, and the effect of others’ actions upon themselves. They form “self-causal chunks” when they believe that their behavior has affected others. They form “other-causal chunks” when they believe that others have affected their behavior. It is likely that in partner violence, most individuals feel that they are responding rather than initiating (Winstok, 2008).”
“Same-gender involvement in conflicts may enhance status, and avoiding a same-gender conflict may diminish it. On the other hand, involvement in conflicts with the opposite gender might work the other way around. For example, a man who avoids aggressive conflict with another man can be regarded as weak or cowardly. A man who gets involved in aggressive conflict with a woman can be regarded as a bully, which is also an indication of weakness and cowardice. […] Women in general are aware of men’s chivalry code by which they are expected not to hurt women (Felson, 2002; Felson & Feld, 2009). […] Men’s chivalry code commitment and their female partners’ awareness of it may increase men’s vulnerability in partner conflicts.”
The comments and results below relate to repondents’ answers to questions dealing with how they thought they would respond in various different conflict contexts (involving their own partner, or strangers of both gender), with a specific focus on the (hypothetical) willingness to escalate, not actual observed conflict behaviour, so you may take the responses with a grain of salt – however I think they are still interesting:
“First, let me begin with the escalatory intention of men in response to the verbal aggression of various aggressors: the highest escalation level was toward male strangers and lower toward female strangers; the lowest escalation level was toward their female partners. The same rates with larger values were found also for the escalatory intentions of men in response to physical aggression by the various opponent types. As to the escalatory intentions of women in response to verbal aggression, the highest level was toward their male partners, and a little less so, but not significantly, toward female strangers. The lowest escalation intention level was toward male strangers. The same rates with similar values were also found in the women’s escalatory intentions in response to physical aggression of various opponents. The most important finding of these comparisons is that relative to the escalation levels of research participants toward strangers, the escalation levels of men toward their partners’ aggression was the lowest, and of women, the highest. […] in intimate relationships, women’s tendency was more escalatory than men’s. […] escalatory intentions of men are more affected by the severity of aggression toward them than those of women. This study provides initial evidence of the lack of gender symmetry in escalatory intentions. In partner conflicts, women tend to escalate more than men.”
Below I have added some observations and quotes from the book. When I started out writing the post my intention was to cover the book in one post, however I realized quite late in the process that this was not feasible, so you can expect me to cover the rest of the book later on (I decided not to cover the rest because there’s some stuff in the last chapters which I thought was really quite interesting, and I did not want these things to get lost in a very long post, and/or covered in too little detail). After I’ve now written this blog post, I’m actually strongly considering changing my goodreads rating to a two star evaluation; this is a very selective account of the material covered in the book, but it did actually include quite a lot of interesting observations. Given the length of the post I decided to bold a few key observations from the book’s coverage (the bolded sections below are not bolded in the book).
“let us focus on the empirical evidence regarding the differences in aggressive tendencies within the couple. The research in this area is led by two groups with opposing outlooks. One is dubbed “feminist scholars,” who view the problem as asymmetric in terms of gender: they maintain that intimate violence is perpetrated by the man against his female partner […] In this case, using the term “asymmetry” reflects the notion that a significant difference exists between men’s tendency toward violence against their female partners and women’s tendency toward violence against their male partners. The second group is referred to as “family violence scholars,” who view the problem of partner violence as gender symmetric: the violence is perpetrated by both men and women […]. They use the term “symmetry” to convey the idea that a significant (not necessarily equal) proportion of both genders use violence in their intimate relationships. […] for feminist scholars, gender is a primary significant factor in predicting partner violence, whereas for family violence scholars, gender is secondary and marginal. […] The only fact on which both approaches agree is that the rates of injury caused by male violence are higher than those caused by female violence […] there is broad agreement that the results of partner violence are more severe for women than for men […]. Most family violence scholars do not view this information as a relevant factor in challenging their approach to the role of gender in partner violence because they focus their attention on aggression. They do not consider victimization to be a straightforward derivative of aggression but rather an issue that warrants independent empirical testing.”
“The cumulative empirical evidence, mostly presented by family violence scholars, supports gender symmetry of violence in intimate relationships. […] An examination of research findings on the gender aspects of partner violence leads many scholars, specifically of family violence, to the conclusion that gender plays a minor, secondary role in the problem: both men and women use violence in their intimate relationships and for the same reasons. Despite the empirical evidence, it is widely accepted that in intimate relationships, the violence is perpetrated by men against their female partners.”
“It is my opinion, based on conversations with social workers treating partner violence, that in Israel, much like in other parts of the Western world, feminist thinking is predominant in intervention. Men’s violence against women is the major, if not the only, problem focused on and addressed by practitioners. Even if the practitioners acknowledge female partner violence, they regard it as marginal and inherently different from male partner violence. Practice, guided by feminist thinking, leads many professionals to assume the following: (1) in partner violence, the woman is the victim and (2) the main goal of intervention in partner violence is to stop the man from perpetrating any kind of mild or severe violence against the woman. These assumptions dictate several widely accepted intervention principles: (1) the treatment must serve primarily what is perceived to be the woman’s needs and wishes; (2) the treatment must change the man’s behavior. The response to the man’s perceived needs is secondary and marginal in the process; and (3) the woman’s treatment is best provided by a woman and not a man.”
“A considerable group of family violence scholars believes that violence against women is a particular case (unique or not) of partner violence. […] They have difficulty understanding why feminist scholars can make theoretical arguments on the one hand and then object to them being empirically tested on the other.” One of the reasons may be this one: “a significant group of feminist scholars view the link between politics and research as unbreakable, and in this reality, feel free to emphasize their association with the feminist agenda. They even regard the seemingly apolitical position of family violence scholars as double standard and a sham, because they do not believe that research can be devoid of politics.”
“[An] association between threats and battering among intimate partners has been extensively documented” (…so if your partner threatens you, it seems like a good idea to take the threat seriously).
“It is incorrect to assume that emotions drive people to behave irrationally, and that if one wants to make a rational decision, emotions must be set aside. Not only are rational choices not devoid of emotions but they also play a vital role in the process of choosing an action to attain a certain goal — from focusing attention on details most relevant in a situation, to choosing the most suitable behavior to achieve the goals called for in that situation […] Emotions are a central component of decision making […]. They help to focus attention on details, such as what the opponent is saying, his/her tone of voice, what his/her facial expression and body gestures convey, what means of defense and offence are available and the possible escape routes. Anger might focus attention on the details most relevant in the case of a fight, whereas fear might focus attention on the details more relevant to flight […] Emotions speed up the information collection process, because they switch it on to automatic, or semi-automatic, pilot mode. […] [Anger and fear are] emotions that [have] received special attention in the study of violence [, as they have been] found to be highly relevant to the development of conflict […]. Fear is future oriented and emerges when a negative event is perceived as possible or imminent. On the other hand, anger is past oriented and emerges when a negative event has already occurred […] Anger is associated with the tendency to fight, whereas fear is associated with the tendency to flight […]. Studies have shown that anger boosts the frequency and severity of aggression […], whereas fear inhibits them […] As in many other fields, men and women differ in the case of emotional experience […]. Women tend to experience emotions more intensely than men […] and this includes negative emotions […]. Campbell (1999) suggested that fear is the mechanism that considers costs. When men and women face the same risks, women would experience fear with greater intensity than men. […] gender differences in the experience of anger are less evident than in experiences of fear (Winstok, 2007). […] interviews [with violent offenders] taught me that we are not dealing with loss of control, but rather with a temporary, voluntary forfeit of control. […] The ability to control the loss of control seriously contradicts the suggestion of irrationality.”
“The study of deterrence in partner violence is mainly focused on men using violence against their female partners. It is maintained that men would avoid violent behavior if they perceive its cost as severe and certain […]. In this context, the first line of deterrence is based on women’s willingness and readiness to act against their violent partners and includes seeking the support of informal and formal agents, and/or leaving the violent partner. […] I conducted a study of a sample of 218 men […]. It examined the association between men’s evaluation of their partner’s willingness to breach the dyadic boundaries in response to aggression, and their evaluation of their own tendency to use aggression against their partner. Findings indicated that the men tended to restrain aggression if they evaluated that in response, their partners would involve informal and formal agents, or would even leave them. Based on these findings, it can be hypothesized that such actions by women threaten, deter, and restrain men’s aggressive tendencies.”
“In most cases, the combination of causes that bring about partner violence is not completely known or clear. Therefore, evaluations of the probability of the occurrence of future violence are based, at least in part, on behavioral history. Predictions based solely on behavioral history are prone to false-negative and false-positive errors, at least in cases in which the unknown causes of past violent behavior have changed. One critical example is that this approach will always fail to predict the first time that violence is used. […] interviews with men and women who were perpetrators or victims of partner violence demonstrate that violence is often part of a behavioral move rather than a single action. The move is based on a series of behaviors resulting from several cycles of information processing […] Studying one incident of violent behavior rather than a series of incidents resembles an attempt to understand a branch (interaction between partners), a tree (an incident), and a forest (a series of incidents) by looking merely at the leaves. […] The term “escalation” is at the core of the discussion on conflict dynamics. Most often, in the context of partner conflicts, escalation describes a trend of increasing aggression severity. The term can describe escalation of aggressive acts within a specific conflict, or escalation of aggression across relationship periods (from one incident to the next) […] It is commonly argued that once partner violence erupts, it continues until the end of the relationship (by separation or death) and increases over time (in frequency, intensity, and form), especially when the violence is against women […] Although these arguments sound plausible, they are not supported by research findings […] [Only] in a small portion of cases [does violence] increase over time. […] in a given conflict, violence is the outcome of escalation. This has led many to believe that from one conflict to the next, escalation itself escalates. Despite evidence showing that most cases of partner violence subside over time […] such statements as “once a batterer, always a batterer” and “violence increases over time” are still frequent and widespread.”
“Those who use violence, as compared to those who do not, invest less time and effort in collecting situational cues, and assign higher value to internal rather than external cues while interpreting a situation. Their attention is more focused on aggressive than on nonaggressive cues. They rely more than others on cues that appear at the end of a social interaction and less on those at its beginning […] Studies of children provide a strong support for a link between the types of responses they generate to particular situations and the behavior that they exhibit in those situations. Aggressive children access a fewer number of responses to social situations than do their peers […] They also access responses that are more aggressive than those accessed by peers for provocation, group entry, object acquisition, and friendship initiation situations”.
“When I started studying partner violence, I expected to be able to identify the aggressor and the victim easily. I was surprised to find that these definitions are often blurred, and this is an understatement. Men and women who used violence against their partners often perceived themselves to be the victims, and not the aggressors.” [I should note that this notion comes across as much less far-fetched/outrageous than you’d think once you read a few of the cases included in the book]. […] Dynamics of partner conflict is a direct result of a series of interactions between the partners. It takes a short step from here to maintain that violence in escalatory conflicts is a result of actions and reactions by both parties. Hence, an examination of these interactions, that is, causal analysis, may lead to the blurring of the distinction between victim and aggressor. For those who associate causality with guilt and accountability, this blur is problematic because they need the clear distinction to allocate guilt and accountability. This, in my view, is why no real attempts are made by scholars to study escalatory dynamics. Their moral stance against violence goes beyond their obligation to examine and propose approaches for effective coping with the problem.”
“Violence […] is age related. […] The use of violence is common in very young children [and] [i]ncreasing evidence indicates that from adolescence onward, the use of interpersonal violence tends to decrease in various life contexts […] A cross study by Straus, Gelles, and Steimetz (1980), examining four age groups (18–30, 31–50, 51–65, 65, and up) in the general population found that with the increase in the age of the partners, the violence between them decreases. Short and mid-range longitudinal studies (3–10 years) […] as well as studies that analyzed life paths […] identified similar trends: over time, there was significant decrease in the incidence of partner violence. These studies contradict the perception that partner violence persists and even escalates over time. […] no single typical pattern of partner violence over time exists. Violence between intimate partners can become more moderate, can subside, can continue at a steady severity level and, at times, can escalate. However, accumulating evidence indicates that in most cases, in the short term, violence can escalate, and in the long term, it can cease. It is clear that changes in violence patterns over time (severity and frequency) are not random. Conflicts that escalate to violence in which the aggressor draws “positive” results that exceed negative ones may encourage the said party to continue using this tactic. Negative outcomes may encourage the aggressor to increase the severity of violence or stop using it and look for alternative tactics […] Conflict opportunities on the one hand and the perception of violence as an effective or noneffective means of dealing with conflict on the other, shape the problem to a large extent.”
“Many of the studies reporting comparable rates of violence perpetration by men and women do not examine contextual factors, such as who initiated the violence, who was injured, whether the violence was in self-defense, and the psychological impact of victimization […] when contextual factors are examined, a complex picture of gender dynamics […] begins to emerge […] [For example, in Allen and Swan (2009)] the scholars found that women’s use of mild violence exceeds that of men.”
“Studies [have] showed that violence can be a result of [both] low self-control and restraint capability […] as well as a means of achieving some desired goals […]. As the need to control the partner increases and the capability for self-control and restraint decreases, violence erupts and becomes increasingly severe. The use of violence at one level of severity (e.g., verbal aggression), increases the probability that another level of violence, of higher severity, will be used as well (e.g., threatening with physical violence). […] escalation to and of violence is a tactic that ensures minimum investment in achieving a goal, whether it is eventually achieved or not. Escalatory dynamics deteriorates the conflict because it increases the severity of violence, but at the same time, it also puts on the breaks, as it ensures that the violence ceases when it becomes of no value. […] By using mild violence that becomes increasingly severe, the aggressor demonstrates the possibility of imminent severe danger to the victim. Thus, the aggressor ensures that the victim complies long before the threat is fully executed.”
“when force is used according to the tit for tat principle, it [may escalate]. [Research] findings […] support the suggestion that people are more sensitive to the force exerted on them by others than to the force they exert upon others. If we replace the term ‘force’ with ‘injury,’ this would read: people are more sensitive to the injury exerted on them by others than to the injury they exert upon others. In light of this sensitivity gap in interpersonal conflicts, the injured party wishing to retaliate with an equally severe injury (balancing) may generate a more serious injury. This sensitivity gap works the same way on the second party and will cause him/her to retaliate with a more serious injury, even when attempting an equally severe (balancing) response. In this fashion, the actions and injuries escalate. […] Hurt that is perceived as unfair will be evaluated as more severe than an identical hurt (in terms of form, intensity, and duration) that is perceived as fair. It can be assumed that those who hurt their partners believe, at least at the moment of perpetration, that their action is justifiable. […] Whereas the offender perceives the offense as justified at the time of offending, the offended will probably not take it as such. Such perception gaps between the partners regarding the actions taken during their conflict may [also] promote escalation.”
Below is an updated list of the 71 books I read to completion in 2013.
I decided to update the list as the original 2013 book list was the first list of this kind I posted here on the blog, and compared to the 2014 and 2015 lists it did not contain much information about the books or many links to relevant blog-posts – for example in the original version of the post I only provided one link to blog-coverage of each of the books, regardless of how many posts I’d written about them on the blog, and there were almost no goodreads links.
Here’s a goodreads overview of the books with covers and ratings of the books on the list. On the list below the links over the titles are to the books’ goodreads profiles. The numbers in the parentheses are my goodreads ratings of the books. The rating scale goes from 1 to 5 – I try to use the rating scale the way it was suggested it be used on goodreads, meaning that a 1 star rating corresponds to me disliking the book; 2 stars indicate that it was ‘okay’; 3 stars indicate that I ‘liked it’; 4 stars indicate that I ‘really liked it’; and 5 stars indicate that I thought the book was ‘amazing’. The ‘f’ and ‘nf’ indicate whether or not it’s a fiction (f) or a non-fiction (‘nf’) book. Aside from that I provide author names in the case of fiction books and publisher information in the case of non-fiction books. Perhaps the main difference between this list and the one I first posted is that this list provides, as far as I’m aware, links to all the posts I’ve written about the books on this blog.
I noted in the first version of this post that I tend not to write very much about fiction books I read, whereas my coverage of non-fiction books generally is much more detailed, so you should expect more detailed coverage of the non-fiction books in the links below than of the fiction books.
Okay, here are the books and links:
3. Adult Development and Aging: Biopsychosocial Perspectives (3, nf. John Wiley & Sons). Blog coverage here, here, here, and here.
5. The Great Sea – A Human History of the Mediterranean (4, nf. Penguin Canada). Blog coverage here and here. This book is quite long (783 pages).
6. Making Choices in Health: WHO Guide to Cost-Effectiveness Analysis (4, nf. World Health Organization). Blog coverage here.
7. Causal Models – How People Think about the World and Its Alternatives (1, nf. Oxford University Press). Blog coverage here.
30. The murder of Roger Ackroyd (5, f). Agatha Christie.
36. Calculated Risks: Understanding the Toxicity of Chemicals in Our Environment (3, nf. Cambridge University Press). Blog coverage here and here.
41. The Knowledgeable Patient: Communication and Participation in Health (A Cochrane Handbook) (2, nf. Wiley-Blackwell). Blog coverage here.
47. The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature (3, nf. Vintage). Short goodreads review here. Blog coverage here and here.
49. The Incas and their Ancestors: The Archaeology of Peru (3, nf. Thames and Hudson). Blog coverage here and here.
61. The Causes and Behavioral Consequences of Disasters: Models informed by the global experience 1950-2005. (2, nf. Springer). Blog coverage here.
62. The Ethics of Screening in Health Care and Medicine. (3, nf. Springer). Blog coverage here.
64. Suicide risk management: A manual for health professionals (2, nf. Wiley-Blackwell). Blog coverage here.
66. Antibiotic Policies: Controlling Hospital Acquired Infection (4, nf. Springer). Blog coverage here.
68. Type 1 Diabetes: Etiology and Treatment (4, nf. Humana Press). Blog coverage here and here. I never wrote a ‘final post’ after I’d finished the book, but I’d here like to recommend the book (or an updated version of it) to people who are ‘fluent in the medical textbook language’ and have any interest in this disease – the book is a very useful reference tool).