human-nature.com/ep – 2006. 4: 394-405
High-K Strategy Scale: A Measure of the High-K Independent
Criterion of Fitness
Cezar Giosan, Department of Psychiatry, Weill Medical College of Cornell University, New York, NY
10021 E-mail: firstname.lastname@example.org
Abstract: The present study aimed at testing whether factors documented in the literature
as being indicators of a high-K reproductive strategy have effects on fitness in extant
humans. A 26-item High-K Strategy Scale comprising these factors was developed and
tested on 250 respondents. Items tapping into health and attractiveness, upward mobility,
social capital and risks consideration, were included in the scale. As expected, the scale
showed a significant correlation with perceived offspring quality and a weak, but
significant association with actual number of children. The scale had a high reliability
coefficient (Cronbach’s Alpha = .92). Expected correlations were found between the
scale and number of medical diagnoses, education, perceived social support, and number
of previous marriages, strengthening the scale’s construct validity. Implications of the
results are discussed.
Keywords: Fitness, adaptedness, high-K, life history theory, r/K, number of children,
Introduction: Fitness is a fundamental concept in evolutionary biology. Definitions of
fitness generally center on two dimensions: One is the resultant biological fitness,
operationalized through reproductive success, or number of offspring, (e.g., Fagerstrom,
1992; Fisher, 1958; Rosenberg, 1983; Sober, 1993), while the other one is the
independent criterion, largely referred to as overall adaptedness, that is, properties and
capacities that make an organism more successful (e.g., Burns, 1992; Dennett, 1995;
Dobzhansky, 1969; Lennox, 1991; Michod, 1999; Pianka, 1978).
The strategies by which an organism achieves resultant fitness are varied. Life
History Theory (LHT) (e.g., Bogaert and Rushton, 1989; Figueredo et al., 2006; Mac
Arthur and Wilson, 1967; Pianka, 1970), states that, for any given individual, the
available resources in any particular environment are finite, which translates in trade-offs
in the allocation of energy to solve particular fitness-relevant tasks. Thus, an individual
can allocate resources for somatic effort (e.g., growing a larger body), or reproductive
High-K Strategy Scale
effort (pursuing mates or investing in offspring). The extremes of these fundamental
dimensions of reproduction are traditionally termed the r/K theory. A K-selection
strategy is to produce a smaller number of ‘fitter’ offspring with higher chances of
survival, while an r-selected strategy is the production of a large number of offspring, of
whom only a minority may survive (e.g., Bogaert and Rushton, 1989; Figueredo et al.,
2006). These different co-adapted reproductive strategies result from psychosocial traits
that cluster together (e.g., Rushton, 1985; Thornhill and Palmer, 2004).
Examples of high K-strategists are elephants, humans, or whales. When applied
to humans, LHT is referred to as “differential K” (Rushton, 1985). Traits associated with
a high-K strategy in humans are long-term thinking and planning, commitment to long-
term relationships, extensive parental investment, existence of social support structures,
adherence to social rules (e.g., altruism and cooperation), and careful consideration of
risks (Figueredo et al., 2006).
Purpose of the study
The aim of the present study was to develop a high-K fitness optimization model. To this
end, a measure tapping into the high-K independent criterion of fitness (i.e., high-K
strategies) was developed and associations with certain fitness outcomes, such as quality
and number of offspring, were tested.
Construct development and predictions
A scale that taps into the components of a high-K reproductive strategy should have the
The items should be reflections of factors documented in the evolutionary
psychology literature as being related to high-K (e.g., upward mobility, health,
social capital, consideration of risks).
Since a high-K strategy is theorized to translate into increased parental investment
in the offspring, with the aim of making them more competitive, a significant
correlation between the construct and the perceived quality of the offspring is
High-K strategists emphasize on the quality, rather than quantity, of the
offspring, therefore the construct should show small correlations with actual
resultant biological fitness (number of children).
LHT tells us that many fitness-enhancing traits should be negatively correlated,
but traits consistent with a single coherent reproductive strategy should be
positively correlated. The present construct is conceptualized to tap into one
coherent reproductive strategy, high-K, therefore it should enjoy high internal
in somatic effort, educational opportunities and social
capital, therefore significant correlations between the construct and health,
educational level, and social support are also expected.
High-K strategists are also committed to long-term relationships therefore a
negative correlation between the construct and number of previous marriages is
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In our modern society, a high-K strategy can be realized through: 1) preserving
or increasing health of self, offspring and kin, 2) achieving upward mobility, which may
translate into better access to healthcare and educational and career opportunities for the
offspring, 3) social capital, which may translate into receiving help from others when in
need and 4) careful consideration of risks, (e.g., securing safe shelter or avoiding risky
activities). The scale content was thus centered on these factors, described in more
Health and attractiveness: High-K strategists invest in somatic effort, which
should translate into better health and increased lifespan (Figueredo et al.,
2006). Health and fertility in women were associated with attractiveness
(Singh, 2003), which, in turn, was associated with increased likelihood of
marrying (Udry and Eckland, 1984). In men, judgments of health were
associated with facial symmetry (Jones et al., 2001), which, in turn, was
associated with psychological and physiological health (e.g., Shackelford and
Larsen, 1997). Unhealthy individuals are at increased risks of becoming
debilitated, dying, or transferring communicable disease to their mates and/or
offspring (Buss, 2004). In a study of 37 cultures, Buss, et al., (1990) found that
health was judged to be highly important by both men and women, while in
studies of parenting, health of the offspring was associated with more parental
investment (Mann, 1992). Health can be maintained not only through active
somatic effort: A preference for natural environments, which, in evolutionary
sense, may mean multiple places for concealment and multiple routes for
escape, has been documented in the literature (Kaplan, 1992; Kaplan and
Kaplan, 1982; Ulrich, 1983), and lower physiological distress and quicker
recovery from surgery, for instance, were associated with viewing nature
scenes (Ulrich, 1986). Thus, living in such “evolutionarily healthy”
environments is likely to alleviate stress (Appleton, 1975; Ulrich, 1984;
Watson and Burlingame, 1960), and generally improve well-being, which
should translate into positive effects on fitness.
Upward mobility. Upward social and financial mobility are important factors
universally preferred in mates, especially in men, and associations between
male status and accessibility to desirable mates are well-documented (e.g.,
Betzig, 1993; Elder, 1969; Grammer, 1992; Perusse, 1993). Upward mobility
is a status-gaining factor in men, but female beauty enjoys higher status than
men’s in the mating world (Wright, 1982). Status serves not only the purpose
of attracting more desirable mates: Elsewhere, it has been shown that
increased status is linked to increased resistance to communicable infectious
diseases, especially respiratory infections, in both humans and monkeys
(Cohen, 1999), and that children from lower classes are more likely to develop
them (e.g., Cruz et al., 1990; Power, 1992) and to miss school days because of
such illnesses (Egbuonu and Starfield, 1982). All this body of research
suggests that status and resource control can mediate reproductive success in
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High-K Strategy Scale
different ways, such as resources available to invest in offspring, or better
parental and offspring health.
Social capital and extended family. Inclusive fitness theory proposed that
fitness is realized not only through investments in one’s own offspring, but also
in their relatives who carry copies of their genes (Hamilton, 1964). Access to
the resources (e.g., time, caregiving, money) of one’s extended family
increases fitness. The ‘grandmother hypothesis’ even states that inclusive
fitness can explain increased longevity in people who are well past their
reproductive years (Hill and Hutardo, 1989). High-K strategists invest in
somatic effort, which increases their likelihood to have an extended lifespan
and thus to increase inclusive fitness through grandparenting (Figueredo et al.,
2006). Humans are also a very social species, and survival and reproduction
have been affected by social interactions in cooperative and coalitional
relationships, which in many cases are not blood-related, but are based on
similar values and goals (Axelrod, 1984; Axelrod and Hamilton, 1981;
Williams, 1966). High-K strategists maintain and cultivate substantial social
support structures and adhere to social rules such as cooperation and altruism
(Figueredo et al., 2006). Cultivating uniqueness, irreplaceability, and
individuality, in a network of individuals whom one can rely on when in need
should affect fitness positively, as this may attract more help from others
(Tooby and Cosmides, 1996). In short, having social capital, access to the
investment of the extended family – which is sometimes challenging in our
mobile world -, and belonging to a network of people with similar values,
interests, and goals, should increase fitness, as one’s offspring is likely to
receive extra care and investment.
Consideration of risks. High-K strategists display careful consideration of
risks (Figueredo et al., 2006). Living or working in unsafe places are likely
factors that can decrease fitness because of health consequences or direct
threats to the survival of self or kin. Channeling resources and efforts to avoid
working or living in such places should have positive effects on fitness.
Twenty-six items tapping into these factors were developed into a High-K
Strategy Scale (HKSS) (see Appendix 1). A pilot study on 20 people revealed no issues
with the meaning of any particular item.
HKSS total score was calculated by summing up the items. Health was
operationalized by summing up all the non-similar diagnosis categories the respondent
sought medical assistance for in the past five years through his/her employer’s
occupational health services, therefore, a higher number of such diagnoses was seen as
indicative of poorer health. This coding modality was chosen over summing up the sheer
number of diagnoses, because it was unclear when similar diagnoses or diagnosis
categories related to independent similar medical conditions or to multiple medical visits
for the same condition.
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Correlations between total HKSS score and offspring quality, resultant fitness,
education, number of medical diagnoses, perceived social support, and number of
previous marriages were then tested, and Cronbach’s Alpha was also calculated.
The scale was tested on a sample of 250 respondents. Participants were full-time
utility workers of a utility company in Northeast America. Permission was obtained to
administer these measures as a part of these respondents’ mandatory annual health
assessment, therefore the return rate was 100%. Demographic information, including
self-reported number of children, and health records obtained from their employer’s
occupational health service, were also collected. The turnaround time was approximately
1) High-K Strategy Scale (HKSS). The 26-item scale is presented in Appendix 1. The
items were coded on a 5-point Likert scale, from “strongly disagree” to “strongly
agree”, with the exception of one item – item nr. 19, “Are you married or
cohabitating?” - which was coded dichotomously (no = 1 and yes = 5).
2) Interpersonal Support Evaluation List (ISEL) (Cohen and Hoberman, 1983; Cohen et
al., 1985), is a 40-item measure of perceived availability of social support, which has
good internal consistency (Cronbach’s Alpha = .88).
3) Perceived offspring quality. This short scale was developed by the author and
consisted of three items tapping into three components: health,
intelligence/industriousness, and physical ability of the offspring. The items were
“My children did not take many days off from school for medical reasons”, “My
children do/did well in school”, and “My children are good at sports”. The items
were coded on a five-point Likert scale from “strongly disagree” to “strongly agree”.
The Cronbach’s Alpha for this three-item scale was acceptable (Cronbach’s Alpha =
Demographics and HKSS score
Table 1 depicts the demographic characteristics of the sample (N = 250). Overall,
the sample consisted of primarily middle-aged, white, married men with the majority
having at least a high-school education. The mean number of children the sample
reported was 1.68 (SD = 1.29) and the mean age of the children of the respondents was
16.98 (SD = 8.54).
Of the 250 respondents, 25.6% reported having no children, 16.8% reported
having one child, 30.8% reported having two children, 17.2% reported having three
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children, and 9.6% reported having four or more children. The mean HKSS score was
The next step in the analyses was to correlate the total HKSS score with perceived
offspring quality and number of children. As expected, HKSS correlated highly
significantly with perceived offspring quality (r = .46, p = .001), and showed a small
correlation with number of children (r = .16, p = .01). Next, correlations between HKSS
and number of medical diagnoses, education, and perceived social support, were tested.
HKSS correlated significantly with number of medical diagnoses (r = -.14, p =.05), with
education (r = .21, p = .001), and with perceived social support (r = .53, p = .001).
Finally, correlations between HKSS and number of previous marriages were performed.
HKSS correlated significantly with number of previous marriages (r = -.14, p = .05).
Table 1. Sociodemographic Characteristics
Characteristics of Sample (N=250)
Age, M (SD)
Number of children, M(SD)
Average age of children M (SD) 16.98 (8.55)
Some or no high-school 1.7
Some college or training 31.9
More than college
Separated or divorced
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The reliability coefficient was very high, suggesting that the items are internally
consistent (Cronbach’s Alpha = .92, number of items = 26). Item-total analyses showed
that removing any item from the scale made Cronbach’s Alpha range between .916 -
Drawing from insights from the evolutionary psychology literature, this study proposed a
high-K strategy fitness optimization model and assessed it with a scale tested on a sample
of 250 US respondents. It was theorized that these indicators, making up the high-K
independent criterion of fitness, will be associated with certain fitness outcomes. The
results showed that the factors proposed in the model have significant effects on fitness as
operationalized through perceived offspring quality and number of children. Moreover,
the scale enjoyed excellent internal consistency and also showed good construct validity,
correlating with number of medical diagnoses (negative), education (positive), social
support (positive), and number of previous marriages (negative).
Although the results of this study are promising, some caveats are in order. First,
the constraints of the data collection biased the sample to predominantly white males,
which may raise questions about generalizability to other US populations. Further
research needs to be done to investigate the ecological validity and robustness of this
scale, by testing it on different US populations, at different times, and in different
contexts. Second, the scale was tested on an American sample, which may raise
questions about cross-cultural generalizability. Although it can be argued that the sample
tested is representative of the US population, or, in general, of the developed nations, in
that it consisted of people integrated in the society with full-time regular jobs, it is
nonetheless essential to examine whether these results can be replicated in other cultures.
Third, the study constraints did not allow for a more sensitive coding of medical
diagnoses. Indeed, while it can be argued that generally fewer number of different
illnesses are indicators of increased adaptedness and stronger immune system,
nevertheless, the severity of each illness should also be factored in (several relatively
mild respiratory and digestive problems may present a much lower threat to survival and
reproduction than one diagnosis of an aggressive malignant tumor).
Despite these caveats, however, the study presents an evolutionary theory-driven
measure of the indicators that seem to make up the high-K independent criterion of
fitness. It was shown, as expected, that this measure is strongly associated with perceived
offspring quality, and weakly, but significantly, with number of children. The results of
this study suggest that these indicators are relatively accurate, which translates into
specific and significant effects on fitness.
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Directions for further research
There are multiple directions for further research stemming from this study. One avenue
of research is to examine the relationships between this scale and objective measurements
of offspring quality, such as health records, school/job performance records, income, and,
importantly, number and quality of grandchildren. Longitudinal studies are required to
address this latter relationship.
Another avenue of research would be examining the associations between this
scale and objective measures of functioning, including measures of mental health. Indeed,
testing whether a high-K strategy is associated with mental health, stress, or social and
occupational disability, can have important theoretical implications and may have
practical clinical implications.
Received 1 August 2006; Revision received 5 October 2006; Accepted 5 October
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