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Weekly Roundup: Sex differences in Partner Selection

Plus resource allocation in a pandemic, using Twitter to crowdsource symptoms, the relationship between being indebted and subjective well-being, and improving a hospital's public quality metrics.
Weekly Roundup: Sex differences in Partner Selection

The principle of attractive mates developed because humans wish to give good genes to their offspring. However, there are important differences between the sexes when it comes to recognising good partners. In the words of Whyte et. al. (2021):

Females are more selective, not only because their maximum fecundity is time limited but because choosing poorly increases the long-term opportunity costs of reproduction (internal gestation, ongoing lactation, and disproportionate maternal investment) and reduces the probability of offspring. Their mate preferences should thus reflect characteristics or traits that can compensate for disproportionate maternal investment and ensure offspring survival and reproductive success, especially with respect to economic proxies for resources and/or increased paternal investment such as educational level, intelligence, and income. In fact, research has shown females demonstrate far more stringent preferences than males for mates with good earning potential or higher education, particularly during the years of peak fertility. Males, in contrast, need only invest the time taken to copulate, which paucity of paternal investment implies the favouring of mates whose genetic fitness guarantees a maximum chance of offspring survival and reproduction.

The assumption humans go with is that certain characteristic of age, attractiveness, symmetry, etc. seem to imply a lower likelihood of disease or illness. However, this manifests itself differently in different ways in males than in females. It has been seen that males seem to value facial cues more in long-term mating contexts over short-term ones, in which they seem to value bodily cues more. This seems to be because females have oestrogen-dependent facial features (lips, cheeks, jaw line) as well as bodily features (waist-to-hip ratio and accentuated gait).

Aesthetics, Resources and Personality

  • Aesthetics is an extremely important part of the way humans judge each other in different social contexts. Since females have a shorter period in which they can have children, it has been found that males place more of a premium on aesthetics than females
  • Resources tend to be an interesting part of partner selection. Since females have to invest resources into childbirth and the associated activities, they tend to prioritise males who can make up for this shortfall. The Australian Bureau of Statistics has found that earnings tend to peak for women in their mid-30s, but they tend to peak for men in their mid-40s or later. Since earnings are associated with greater age in males, that leads to women going for older men. This also works in step with the ability of men to father children remaining fairly constant with age
  • Personality traits have started to become more important in mate selection as well. As the authors put it, "In addition to increasing pair bond strength through parental investment, such positive externalities in mate choice may also reinforce reciprocally altruistic behaviour between mates, increase complementary production in the household, promote kin selection towards genetic relatives, and increase the chances of long-term mate retention." The importance of personality traits seems to be increasing in developed countries where the differences between males and females when it comes to access to resources has been narrowed through legislation. In this study, the authors aim to see how the relative importance of difference personality traits changes with age

Results

Women rate the following around 9 - 14 points higher than men do:

  • Age
  • Education
  • Intelligence
  • Trust
  • Emotional Connection

It was found that women rated all nine factors a few points higher than men did. Some other interesting results were:

  • Males regard attractiveness and physical build as the most important factors, while women regard age as being more important
  • There is little difference between the ratings given by men and women to income: it's not considered a very important point in choosing a partner
  • While women on average rate openness higher than men, men rate it relatively higher. That is to say that men do not value it as much as women on average, but they value it relatively more than they value most other characteristics
The relative importance given to different metrics by men and women at different stages of their lives. Source: Whyte et. al. (2021)

There is considerable variation with age, as this series of graphs shows. Typically, preferences for attractiveness and age decrease over time, but the male preference for physical build remains constant and that for females actually increases with age. On the other hand the 60+ female cohort shows a strongly increased preference for education. But the preference for intelligence decreases over time across the sexes. The relative importance of emotional connection seems to remain constant across genders, and the importance of income, emotional connection and trust seem to increase with age (young people don't care about them as much).

Conclusions

On the surface, one may make the observation that for the population sampled, and compared with males, females care more about a greater number of characteristics when considering attractiveness in a potential mate. Such findings lend confirmatory weight to previous research findings and broader historical evolutionary theory that predicts that females tend to be choosier than men.

The authors also report that sex differences (across ages) are the least for those who do not rate aesthetics highly.

Here, we find a consistent statistical sex difference (males relative to females) that decreases linearly with age for aesthetics. The opposite is true for resources and personality, with females exhibiting a stronger relative preference, particularly in the younger cohort of our sample.
More highly educated females express a higher relative preference for aesthetics, and more attractive females exhibit a higher relative preference for personality. We also find absolute differences for females with offspring, who place more emphasis on personality, whereas males with offspring report this trait as less important.

The ethics behind resource allocation in a pandemic

When it comes to the allocation of scarce resources among people in the context of absolute scarcity, there have been many principles proposed:

  • Maximising Individual benefits
  • Treating people equally
  • Maximising social benefits (instrumental value)
  • Priority given to the sickest
  • Lifecycle principle

Of course, it is well-recognised that ethical values are not islands: there is no single value which can define the outcome of a resource allocation problem. One needs to use a combination of them in order to be as fair as possible to as many as possible. Currently, the model being used in Portugal uses the following criteria in the order given:

  1. “Maximising health benefits” (efficiency consideration – Priorities should be set according to patient’s survival/prognosis)”
  2. “Severity of health condition” (used whenever patients have similar prognosis)
  3. “Instrumental value” (frontline health professionals deserve priority whenever patients present similar prognosis and severity of the health condition)
  4. “Random selection” (used whenever patients have similar prognosis and similar health condition severity)

Pinho (2021) set out to validate whether the Portuguese public also believes in these ideas as well as ethicists do. In general, it was found that respondents gave the most importance to the principle of maximising benefits, as do ethicists. However, it was found that younger generations cared less maximal benefits and were more concerned with responsible stewardship of resources. The second most important criteria identified matched up with what most ethicists believe to be important: the severity of the health condition. The third criteria, surprisingly, was age. People preferred younger patients getting access to more resources. Instrumental value ended up receiving the least support as a criterion for resource distribution.

Prognosis was seen to be the most overriding concern in the minds of respondents. It was seen that if confronted with a situation in which one of two patients had to be chosen, the first with a good chance of survival and a severe impact on the rest of their life if not given treatment, and the second with a bad chance of survival yet minimal impact upon their lives if they survive, people would choose the former. They emphasised prognosis, not the probability of survival. Saving the sickest does not seem to be the intuition of most people. However, the one exception seemed to be people with a prior experience of COVID-19. They were more likely to give more importance to the severity of sickness.

It was also seen that participants in the survey, regardless of age, preferred to allocate resources to younger people. This tendency was more pronounced among younger respondents, reflecting rational choice behaviour theory. This is an interesting result, because age is typically not seen as a valid strategy for the allocation of resources. It also contradicts the supposition that older generations would put more stock in the "fairness" principle. One possible explanation could be that COVID-19 has been extremely lethal for older people and has generated specific fear for their lives in them. However, regarding the principle of instrumental value:

Our findings indicate that Portuguese participants moderately agree with the idea of giving frontline healthcare professionals priority in access to critical medical resources. Younger respondents, health professionals and respondents who tested positive to coronavirus showed greater preference than older respondents, respondents from other professional occupations and those that never had the disease, for the instrumental value principle. Again, an adherence to the rational choice theory seems evident among health professional’s participants. Empirical evidence on population support for the instrumental value principle is lacking but one study (Krutli et al., 2016) reached results contrary to ours. They concluded that older respondents consider more than younger respondents this principle as fair. Additionally, the fact that respondents previously infected support more the instrumental value principle may be because they felt the sacrifice and the risk that frontline health professionals are experiencing and exposed to.

The lottery principle, on the other hand, was seen to be unfair by almost all the respondents.

Policy Implications

It is important for politicians to make sure that they consider the population's idea of what constitutes ethical resource distribution before attempting to impose a framework on the population. While the Portuguese people, in general, seem to be happy about their national policy, it might be a good idea for the leaders of other countries to attempt to understand these principles. In certain cases, they may conflict with utilitarian principles and those of efficiency, but getting the population on board with such strategies is pivotal to actually getting a generalised national strategy for pandemics in place.

Improving Public Quality Metrics in Hospitals

Photo by jodie covington on Unsplash

In the USA,  providing high-quality care is a central element in the mission of a hospital. Further, quality of care contributes to a hospital’s reputation and affects its financial performance. Wernz, Song and Hughes (2021) develop a model to analyse how hospital interventions may affect physicians' CT scan decisions. This particular area was chosen because medical imaging is one place where patients tend to pay a lot of attention to quality. According to the authors:

The hospital interventions that we consider in our model are (1) incentivization, (2) training, and (3) nudging. The model captures the physicians’ CT scan decision process, clinical uncertainties, and physicians’ varying diagnostic abilities.

One important thing to note is that while imaging is important and often necessary to get imaging done to diagnose certain diseases, overuse of imaging as a diagnostic tool is not a good idea. It is costly and increases the chance of misdiagnosis.

Certain points which they make:

  • Models using partially observable Markov decision processes (POMDPs) for optimal breast cancer screening account for uncertain patient and cancer states
  • Zhang et al. in 2018 as well as 2016 analyzed CT scan related decisions of payers, hospitals, physicians, and radiologists, and the multi-level effects of payment innovations using a multiscale decision theory (MSDT) model. They found that payment innovations, while effective, can have unintended consequences, especially across multiple system levels, and their design needs to be data-informed and the program parameters carefully chosen
  • While a few models have accounted for some aspects of physicians’ CT scan decision-making, none have incorporated physicians’ varying ability levels in diagnosing a patient

CDRs (Clinical Decision Rules) have seen to be an effective tool against over-prescribing imaging, specifically same day brain and CT scans. The authors use the #Model developed by Zhang et. al. through the inclusion of CDRs to actually build their own model.

Model

It is assumed that the physicans wish to maximise each patient's health utility, which is denoted by \(\mu_{S,A}\). The \(S \in {b,s}\) state variable describes whether the patient suffers from a brain ailment or a sinus ailment. The \(A \in {B, B + S }\) action variable shows whether the doctor prescribes a brain or a CT scan.

Thus, there are 4 prospects a patient can be have: \((b, B), (b, B + S), (s, B), (s, B + S)\). Since \((b, B)\) is always preferred over \((b, B + S)\) because it avoids unnecessary radiation, thus one can sat that \(\mu_{(b, B)} > \mu_{(b, B + S)}\). Similarly, one can also state that \(\mu_{(s, B + S)} > \mu_{(s, B)}\) because it is always better to get a brain + sinus CT scan in case one has a sinus infection. Of course, the point is that the first inequality always holds, whereas the second is mostly about avoiding treatment delay.

Next in the decision process, the physician assigns the patient a rank as the basis for their CT scan modality decision. As stated earlier, the more convinced the physician is that the patient suffers from a brain ailment, the lower the rank. Conversely, the physician assigns high ranks to patients who appear to be suffering from sinus ailments. To then decide whether a patient should receive a brain CT or a brain+sinus CT, the physician compares the patient rank to a chosen threshold \(\theta\). For \(x < \theta\) the patient receives a brain CT, and for \(x \geq \theta\), the patient receives a brain+sinus CT. The patient then experiences the corresponding health utility, whose expected value the physician seeks to maximize.

Discussion

The authors actually look at 3 different ways in which this can happen: incentivisation, nudging, and training. The authors did this through the use of a decision-theoretic model.

The authors state that a targeted approach for giving incentives might be used (in a world without ethics) by hospitals for maximising their own metrics (OP-14). However, targeting has the problem that it would incentivise the physicians best at doing their jobs the least. Training costs are the highest among the interventions assessed, even though it might be the best. Nudging is seen as, perhaps, the most cost-effective way of achieving what the hospital wants. However, it will probably not be enough by itself and will need to be supplemented with training.

Crowdfunding Pandemic Communication

Most countries have been very bad at co-ordinating their pandemic responses. While the list of issues is too long to list in full, the most egregious issue among these was the delay in compiling a good list of symptoms of COVID-19. It took quite a while before it was properly understood what symptoms even constituted an infection by the novel coronavirus.

Zolbanin, Zadeh and Davazdahemami (2021) point out that the CDC referred to the symptoms of MERS as the basis of its list of symptoms for Covid. The lack of haste in compiling symptoms may have lead to its alarming spread in the US. As the authors say:

First, the cause of the disease was a novel coronavirus, and as a result, the information about the possible signs and symptoms of the disease was accumulated as the virus infected more and more people. Second, the variation in geographical presentation of diseases and the ease of traveling from one corner of the world to another created challenges for the identification of a complete list of symptoms. Third, a lack of international cooperation hindered the dissemination of experiences and sharing of knowledge among the global and national agencies. Fourth, the global and national agencies did not fully utilize the power of social media platforms in obtaining and spreading information about the symptoms of the new disease.

The obvious question, of course, is whether it was even possible for countries to reduce the amount of time required for this exercise. The authors use Twitter to create a symptom surveillance system (SSS) which has the advantage of being able to avoid the question of national pride and its like. This is because people tend to use social media for sharing health related issues long before they actually become a blip on the radar for healthcare authorities. As the authors state:

The utility of these platforms, however, extends beyond states of emergency to allow for public health surveillance and the exchange of health information, including information about illnesses and associated treatments.

An example provided for the issue of communication was:

While there was anecdotal evidence on the effectiveness of hydroxychloroquine in treating some patients, WHO hastily halted trials of the drug based on the results of a single study but soon after restarted the process when it was known that the study had validity problems. This and other examples, such as recommending to not wear masks at the end of March and then advising to wear them in public areas, suggest there is a lot of room for improvement in future pandemics.

The authors were able to demonstrate the face that social media is perfectly able to tell us about these issues as and when they crop up. They did so by performing a network analysis and a time series analysis: the first to see which symptoms were being reported the most, and the second to see the chronology of these reports.

Conclusions

The authors state that there was very good correlation between the actual progress of symptoms as observed and those reported on Twitter. They also state that these symptoms and their progression became evident on English-speaking twitter in during February itself and continued on till mid-March. They posit that checking Chinese and Italian social media might have led to those dates shifting even earlier.

The relationship between indebtedness and subjective well-being

Over-indebtedness is truly a malaise on society: it tends to affect people extremely negatively. Researchers have converged on four features of over-indebtedness in a bid to characterise it:

  • Making high repayments relative to income (e.g., households spending more than 30% of their gross monthly income on unsecured repayments)
  • Having a high number of credit commitments (e.g., four or more credit loans)
  • Being in arrears
  • The subjective perception of debt as a burden

Ferreira et. al. (2001) begin by stating some objections with this characterisation. The first two metrics are fairly inflexible. The third does not really try to understand the seriousness of the arrears themselves (which depends on the financial state of the household), and the fourth, of course, is very subjective. The authors thus choose a very distinctive measure for understanding over-indebtedness: people who chose to go to a debt advise expert.

Looking at the literature, one sees that being over-indebted has many specific negative effects:

  • Increased risk of suicide and depression
  • Poorer subjective health and increased physical illness
  • Low sleep quality
  • Increased risk of chronic diseases

However, there is little work performed on the effect of over-indebtedness on subjective well-being (SWB). Previous work done on this subject has found a tenuous link between SWB and indebtedness. However, most such studies do not distinguish between indebtedness and over-indebtedness. As the authors point out, there is a correlation between over-indebtedness and both careless consumer behaviour and financial imprudence, often leading to social stigmatisation of the people under these circumstances.

Two different reasons for over-indebted individuals having lower SWB are considered in this paper. The first is that since financial well-being is literally the feeling of being satisfied with one's financial status, SWB is directly correlated to it. The second is the fact that being overly indebted tends to greatly reduce a person's chances of actually achieving their goals. Thus, over-indebtedness might not just cause financial anxiety but also reduce the perception of control a person has over their lives.

The authors utilised surveys in Portugal to get the data they required.

Results

It was seen that over-indebted people displayed lower life satisfaction than non-over-indebted people. Surprisingly, despite their lower satisfaction with their lives, it was seen that over-indebted people seemed to be more optimistic about their futures as they tended to anticipate a steeper increase in their life satisfaction very soon.

The results for emotional well-being also matched up to the ones found for life satisfaction. It was also seen that emotional well-being seemed to deteriorate going from morning to evening. It also seemed to affect patterns of sleep, with over-indebted people sleeping less than non-over-indebted people. A similar result was found for self-reported health.

All of this data pretty much agrees with the data found in literature. The subjects in this study were mostly medium-to-long term sufferers of over-indebtedness. This lends one to believe that unlike many other life-changing circumstances, over-indebtedness is not a temporary phenomenon. Other circumstances which are routinely compared to being over-indebted are long-term unemployment and chronic back pain.

Out of the three variables that constitute SWB, it was found that perceived control (or a lack of it) was found to explain a great deal about the relationship between over-indebtedness and all dependent variables (life satisfaction, emotional well-being, health, and sleep). In the authors own words:

A lack of control over one’s life not only contributes to fully explaining the relationship between over-indebtedness and emotional well-being, but also partially explained the relationship between indebtedness status and life satisfaction. Furthermore, perceived control was also found to partially explain sleep quality and to fully explain reported overall health.

Policy implications

Efforts to combat over-indebtedness exist in many countries. However, most of them primarily focus on reducing the financial issues faced by people. This study posits that not only should policymakers focus on that metric, they should look at factors which can influence an individual's perception of control over their own lives better. A mixed approach consisting of both primary and secondary approaches might better serve the population being targeted. Better mental health may be a driving factor in getting people out of debt and getting them to feel better about their situations.