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Willingness to Invest in Children: Psychological Kinship Estimates and Emotional Closeness


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In general, adults invest more in related children compared to unrelated children. To test whether this pattern reflects variations in psychological kinship estimates (i.e., putative relatedness weighted by certainty in relatedness), willingness to invest in children belonging to different categories (direct offspring, nieces/nephews, stepchildren, and friends’ children) was measured in a population-based sample of 1,012 adults. Respondents reported more willingness to invest in their own biological children, than in other related children (nieces and nephews), or in stepchildren and friends’ children. Compared to putative relatedness, respondents’ psychological kinship estimates better predicted the willingness to invest. This association was partially mediated by emotional closeness. Additionally, the age of a child and the number of children in the care of the respondent were negatively associated with willingness to invest. The association between psychological kinship estimates and willingness to invest supports evolutionary predictions. Investment in stepchildren was, however, higher than expected.
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Original Article
Willingness to Invest in Children:
Psychological Kinship Estimates
and Emotional Closeness
Jan Antfolk
, Linda C. Karlsson
, Johanna So
, and Anna Szala
In general, adults invest more in related children compared to unrelated children. To test whether this pattern reflects variations
in psychological kinship estimates (i.e., putative relatedness weighted by certainty in relatedness), willingness to invest in children
belonging to different categories (direct offspring, nieces/nephews, stepchildren, and friends’ children) was measured in a
population-based sample of 1,012 adults. Respondents reported more willingness to invest in their own biological children, than in
other related children (nieces and nephews), or in stepchildren and friends’ children. Compared to putative relatedness,
respondents’ psychological kinship estimates better predicted the willingness to invest. This association was partially mediated by
emotional closeness. Additionally, the age of a child and the number of children in the care of the respondent were negatively
associated with willingness to invest. The association between psychological kinship estimates and willingness to invest supports
evolutionary predictions. Investment in stepchildren was, however, higher than expected.
family, family relations, kinship, stepfamilies, childcare, parental investment
Date received: January 2, 2017; Accepted: March 24, 2017
Several studies investigating altruism and prosocial behaviors
have shown that people are most willing to invest time and
resources in individuals that they are closely related to (such
as children, siblings, and parents) and that the willingness
decreases as distance in biological relatedness increases (e.g.,
Burnstein, Crandall, & Kitayama, 1994; Rachlin & Jones,
2008; Stewart-Williams, 2007, 2008). For example, studies
have found that people report being more willing to help close
relatives (compared to distant relatives and acquaintances) both
with everyday challenges and in life-threatening situations
(Burnstein et al., 1994; Korchmaros & Kenny, 2006). People
are also willing to incur higher costs in the form of physical
pain if this benefits close relatives compared to more distant
relatives (Madsen et al., 2007). These patterns of favoring close
relatives over distant relatives are found especially when the
cost of the investment is high to the actor (Stewart-Williams,
2007, 2008).
The variation in altruistic investment in family members
has been explained as stemming from variations in emotional
closeness (Korchmaros & Kenny, 2001, 2006), such that
humans are more inclined to invest in individuals they feel
emotionally close to. At the same time, emotional closeness is
often higher in biological relationships than in sociolegal
relationships (Korchmaros & Kenny, 2001, 2006; Neyer &
Lang, 2003), and emotional closeness covaries with factors
such as proximity and similarity—cues that indicate true
biological relationship (Byrne, 1961; Korchmaros & Kenny,
2006). The degree to which investment in children is affected
by biological relatedness or by other social factors is debated
(Korchmaros & Kenny, 2006; Roberts & Dunbar, 2011;
Stewart-Williams, 2007).
In the current study, we focused on adults’ self-reported
willingness to invest in both biologically related and
unrelated children. With respect to these relationships, we also
measured the degree and type of putative biological relatedness
Department of Psychology, A
˚bo Akademi University, Turku, Finland
Corresponding Author:
Jan Antfolk, Department of Psychology, A
˚bo Akademi University,
Tuomiokirkontori 3, 20500 Turku, Finland.
Evolutionary Psychology
April-June 2017: 1–10
ªThe Author(s) 2017
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DOI: 10.1177/1474704917705730
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(i.e., self-reported relatedness without corroborating informa-
tion about true relatedness), the certainty of relatedness (i.e.,
self-reported certainty that putative relatedness actually reflects
true relatedness), and emotional closeness.
Investment in Related Children
Within an evolutionary framework, inclusive fitness theory
(Hamilton, 1964) defines the conditions under which “altruistic
investment” can evolve under natural selection. Inclusive fit-
ness theory explains how alleles underlying helping one’s kin
are naturally selected, even when the investment is costly to the
actor (i.e., decreases one’s direct fitness). Alleles associated
with increased investment in relatives are likely to be present
in our close biological kin as well, and therefore, when humans
invest in biological relatives, this investment increases the like-
lihood of this particular allele to be propagated to future gen-
erations. For example, investments in the well-being of direct
offspring and nieces/nephews—with whom we share 50%and
25%of our genetic material, respectively—can be evolutionary
advantageous to the allele even though investment comes at a
cost to the actor (i.e., the investing individual). The condition is
that the benefit to the recipient of the act is higher than the cost
to the actor, after accounting for the degree of relatedness
between the two. This means that in order for the disposition
to evolve, the benefit to a biological child must be at least twice
as high as the cost is to the parent. In the case of a niece or a
nephew, the benefit must be at least four times as high. In other
words, the cost of the investment, the benefit to the recipient,
and the degree of relatedness describe the level over which a
particular form of investment will be biologically advanta-
geous (Hamilton, 1964). This theoretical model has later been
applied to the human family and corroborated by vast amounts
of anthropological data (e.g., Daly & Wilson, 1988; Hughes,
1988). Self-report data (e.g., Antfolk, Lieberman, & Santtila,
2012; Lieberman, Tooby, & Cosmides, 2007) also suggest that
rather than following degrees of true relatedness, human kin
selection follows psychological kinship estimates and the cues
affecting them.
Within the same theoretical framework, parental investment
has been defined by Trivers (1972) to include all resources that
benefits a child while decreasing the parent’s possibilities to
produce and invest in other (earlier, current, or future) off-
spring. As such, the definition covers a wide variety of phe-
nomena, ranging from the provision of metabolic resources
associated with gestation to more overt, observable behaviors,
such as providing the child with shelter and food (Trivers,
1972). Some acts such as donating an organ to save someone’s
life are, evolutionarily speaking, very costly. Such costly acts
can be considered a particular form of investment. From an
evolutionary perspective, costly investment is biologically
advantageous only when the benefits to the recipient are high
and the recipient is a close relative.
Psychological Kinship Estimates
As indicated, true biological relatedness cannot be perceived
directly. In differentiating between relatives and nonrelatives,
humans rely on so-called kinship cues such as proximity (e.g.,
cohabitation; Antfolk, Karlsson, Ba¨ckstro¨m, & Santtila, 2012;
Westermarck, 1891) and similarity (e.g., facial resemblance;
e.g., Alvergne, Faurie, & Raymond, 2009, 2010; Krupp, DeB-
ruine, & Jones, 2011). Apart from the mother–child relation-
ship, in which mothers can be certain a child they gave birth to
is their biological child, all other relationships contain varying
degrees of certainty. The certainty in relatedness is very high
for all links between a mother and her child—and higher than
the comparable link between a father and his child. Neverthe-
less, the link between two full siblings depends on both their
maternal and the paternal relatedness (e.g., Haig, 2009).
Although mothers can be sure of their relatedness to their child,
children report less than perfect certainty regarding their puta-
tive father and their putative mother (e.g., Antfolk, Lindqvist,
Albrecht, & Santtila, 2014). As a consequence, certainty in
relatedness to a nephew or niece born by one’s sister might
be affected by the certainty in relatedness to the sister.
A positive association between certainty in relatedness and
investment has been demonstrated by some previous research
investigating fathers and their children. Asking fathers how
certain they were in the biological relatedness to their child,
Fox and Bruce (2001) found this certainty to be positively
associated with fathers’ affective involvement in their children.
Furthermore, certainty in relatedness has been shown to be
positively associated with the time fathers devote to activities
with their child (Anderson, Kaplan, & Lancaster, 2007). Also,
the perceived fidelity of the mother has been found to be asso-
ciated with the amount of time and attention fathers report
spending on their child, presumably mediated by the certainty
in the relatedness to the child (Apicella & Marlowe, 2004).
The evolutionary model (Figure 1) assumes that kinship
cues are valid indicators of true relatedness. Putative related-
ness follows from the available kinship cues. Putative
Figure 1. The hypothesized relationship between true relatedness, kinship cues, putative relatedness, emotional closeness, and investment.
Each arrow denotes a positive association.
2Evolutionary Psychology
relatedness has an effect on investment. This effect may, partly
or fully, be mediated through emotional closeness. Moreover,
putative relatedness can also be regulated by certainty in relat-
edness (not visualized in the model).
Investment in Unrelated Children
Alongside investment in biologically related children, invest-
ment in unrelated children, such as stepchildren, is also pre-
valent. Comparing stepchildren to biological children, research
has shown that parents spend more time with and give more
financial support to biological children (Anderson, Kaplan,
Lam, & Lancaster, 1999; Henretta, Van Voorhis, & Soldo,
2014; Kalil, Ryan, & Chor, 2014; Zvoch, 1999) and that step-
children are at a higher risk of maltreatment, such as physical
abuse (Daly & Wilson, 1985, 1996) and sexual abuse (Sariola
& Uutela, 1996).
Adults can also invest in other unrelated children, such as
the children of friends. Because resources are unevenly distrib-
uted across individuals, situations, and time, a difficult situa-
tion (e.g., failing to provide for a child) can be resolved by
receiving help from a friend who has an abundance of the
resource needed. Later on, when the situation has changed, the
friend’s altruistic deed can be reciprocated. In this way, both
actor and friend can provide for their children. This theory of
reciprocal altruism (Trivers, 1971) can explain why adults also
invest in children outside their own family. Especially under
conditions where interactions endure over longer periods of
time, it can be advantageous to provide investment (e.g., Axel-
rod, 2006). Naturally, the same type of reciprocity can also take
place between biological relatives. In fact, the facilitating
aspect of long-lasting interactions is often in place in biological
dyads. However, differently from investment in unrelated indi-
viduals, investment in biological relatives can also be evolu-
tionarily beneficial even when not reciprocated. Hence, the
willingness to provide costly investment in a friend’s child or
a stepchild, with whom the actor has no biological relation, is
likely lower than it is to related children.
Number of Children and Their Ages
Another aspect that needs to be considered is age. Younger
adults tend to have younger children, and young children need
more parental investment to survive and reach nutritional inde-
pendence and to increase their reproductive value (e.g.,
Fischer, 1930; Haig, 2009). Because young children also tend
to have young parents, parental investment is expected to be
negatively associated with both parental age and child’s age.
Parental age is also related to the number of children: Young
parents are less likely to have many children. Because most
resources are limited and because of this, the number of off-
spring will also affect the amount of investment that can be
directed to a particular child. An adult cannot invest more than
the available resources, and in the case where an adult cares for
more than one child, the willingness to invest in one child
depends on the willingness to invest in another child (Becker
& Tomes, 1976). This trade-off between the willingness to
invest in a particular child and the number of children in an
adult’s care has, for example, been evidenced by adults being
less willing to pay for schooling for children in large families
(Ca´ceres-Delpiano, 2006). This suggests that the number of
children in an adult’s care should be negatively associated with
the willingness to invest in a particular child.
The Current Study
In the present study, we aimed to extend the current under-
standing of how psychological kinship estimates (i.e., putative
relatedness weighted by certainty of relatedness) and emotional
closeness are associated with the willingness to investment in
children. We also extended on earlier studies by examining
members outside the core family. Because we included
adult–niece/nephew dyads, we were able to measure certainty
of relatedness also in women. The main objective of the present
study was to investigate to what degree the respondents’ self-
reported hypothetical investment in different adult–child rela-
tionship types (i.e., toward one’s own biological children, sis-
ters’ and brothers’ children, stepchildren, and friends’ children)
relates to relatedness beyond emotional closeness.
With regard to earlier findings and the framework of evolu-
tionary theory, the following predictions regarding investment
were made:
Hypothesis 1: Psychological kinship estimates are posi-
tively associated with willingness to invest in children.
Hypothesis 2: The association between psychological kin-
ship estimates and willingness to invest in children is
mediated by emotional closeness.
We also explored the associations between respondent’s
age, gender, relationship status and number of children, child’s
age and gender, and the respondent’s willingness to invest.
For the present study, responses from 1,012 respondents (627
females, 385 males) between the age of 20–50, M
37.16, SD ¼7.06 and M
¼39.43, SD ¼6.09, t(902.64)
¼5.42, p< .001, were obtained from the population-based
Finn–Kin study (Albrecht et al., 2014). Respondents had
answered questions regarding their willingness to invest in
children belonging to the following categories: their own bio-
logical child, their sister’s and/or brother’s child, their step-
child, and a friend’s child. Only children who were 18 years
old or younger were included in the present study. Because all
respondents provided responses regarding several of their
actual relationships, our final data set consisted of a sample
of 2,246 responses (1,369 from females and 877 from males).
Out of these responses, 862 responses concerned a biological
child, 253 responses a sister’s child, 246 responses a brother’s
Antfolk et al. 3
child, 42 responses a stepchild, and 843 responses a friend’s
The Finn–Kin study was given ethical permission in by the
Institutional Review Board of the Department of Psychology
and Logopedics at A
˚bo Akademi University.
Willingness to invest. For each child, respondents were asked to
answer the three following questions: (1) “How willing would
you be to donate your kidney to [name] if she/he would need
it?” (2) “Imagine [name] being sentenced to jail for 12 months,
how willing would you be to serve the sentence instead of
[name]?” and (3) “How willing would you be to give half of
one month’s salary to [name]?.” The response scale ranged
from 0 (not at all) to 100 (very) for Questions 1 and 3. For
Question 2, the anchors were 0 (no time) and 100 (the whole
sentence). To calculate a composite score for each dyad, the
scores on these three variables were averaged. The scale’s
internal consistency (3 items; a¼.78) was sufficient.
Psychological kinship estimates. The measure of psychological
kinship estimates consisted of the putative relatedness between
the adult and the child (one’s own child ¼.50, brother’s child
¼.25, sister’s child ¼.25, and stepchild and friend’s child ¼
.00) multiplied by the certainty of relatedness for each dyad.
The certainty of relatedness to one’s own children and brothers’
and sisters’ children was assessed by asking respondents to
answer the question “How sure are you that [name] is related
to you?” using a scale from 0 (not at all) to 100 (completely
certain). Women were not asked this question with respect to
their biological child, because childbirth provides women with
full certainty. Women were therefore only asked about their
certainty of relatedness to a brother’s child and a sister’s child.
For direct offspring, the mean certainty of relatedness (includ-
ing only male respondents) was 98.43 (SD ¼8.53). For sisters’
and brothers’ children, the mean certainty of relatedness was
96.04 (SD ¼14.72) for sister’s child and 93.22 (SD ¼16.38)
for brother’s child. To get a psychological kinship estimate
value between 0 and 1, such that it could be compared to the
coefficient of relatedness (r), certainty of relatedness was first
divided by 100. For the children who were not biologically
related to the adult, the certainty of relatedness was set as 0,
meaning that all stepchildren and friends’ children had a
psychological kinship estimate of 0 (putative relatedness ¼0
multiplied by certainty of relatedness ¼0).
Emotional closeness. Emotional closeness was measured by ask-
ing respondents to answer the question “How emotionally close
areyouand[name]?”onascalefrom0(not at all)to10
For all measures mentioned above, respondents provided
information using a slider scale. In addition to the aforemen-
tioned measures, respondents gave information on their own
age, gender, and relationship status (single, in relationship and
living apart, in relationship and living together, or married); the
age and gender of each child; the number of years the respon-
dent had coresided with each child; as well as the total number
of children in his or her care.
The data used in the current study were collected from the Finn
Kin study (Albrecht et al., 2014). For this study, letters with
information about the study and a link to the online survey were
sent to addresses obtained from the Central Population Registry
in Finland containing information regarding all individuals cur-
rently residing in Finland; the addresses were selected randomly
from the registry. Four thousand men and 4,000 women were
invited to participate, and out of these 8,000 individuals, 25.2%
responded, and of these, 84.5%completed the survey. This pro-
vided a sample of 1,399 respondents. Some of these respondents
did, however, not provide information regarding some or all of
the variables of interest, and therefore the sample included in the
present study consisted of 1,012 respondents. When respondents
were compared with the general population on important
descriptive variables, Albrecht and her coauthors (2014) found
the sample to be representative of the whole population.
As part of the survey, respondents were asked questions
regarding actual children belonging to five categories: one’s
own biological child, a stepchild, a brother’s child, a sister’s
child, and a friend’s child. In the case respondents reported
having more than one actual relationship with a child within
any of the categories, only the oldest child within a category
was chosen for subsequent questioning. If no target individual
existed in a category (e.g., the respondent had no stepchildren
children), respondents were not presented with any questions
regarding these categories. To facilitate responding, the names
of the selected children were obtained (but were not for reasons
of confidentiality included in the data file) and displayed as a
part of the subsequent questions. This was done in order to
decrease the cognitive burden of responding (Albrecht et al.,
Statistical Analyses
Analyses were conducted using linear mixed-effects modeling
(LME) with the lmer function in the lme4 package in R (Bates,
Maechler, Bolker, & Walker, 2015; R Core Team, 2015). LME
was used in order to take into account the dependency between
responses within individuals (one individual provided response
regarding several of their adult–child relationships). In all LME
analyses, respondent was set as a random factor.
First, preliminary analyses investigated whether child gen-
der (female vs. male), child age, respondent age, respondent
relationship status (single vs. in relationship but living apart vs.
in relationship but living together vs. married), and the number
of children in the care of the respondent were associated with
willingness to invest. Each variable was included in separate
preliminary analyses as fixed factors with willingness to invest
(composite score) as outcome variable. Additionally, as the age
of the respondent and the age of the child are likely to be
4Evolutionary Psychology
associated with one another, we conducted an analysis with
both child age and respondent age included as fixed factors
in the same model. We also investigated the relationship
between coresidence duration and investment in stepchildren.
Second, we investigated the difference in the amount of
investment between the adult–child relationships. This LME
analysis included willingness to invest (composite score) as
outcome variable and adult–child relationship (biological
child, sister’s child, brother’s child, stepchild, and friend’s
child), as a fixed factor, and was followed up with pairwise
Third, to test whether putative relatedness or psychological
kinship estimates (i.e., putative relatedness weighted by cer-
tainty in relatedness) explained more variance in willingness to
invest, two LME analyses with willingness to invest as out-
come variable were run, one with putative relatedness as a
fixed factor and another one with psychological kinship esti-
mates as a fixed factor. These models were then compared
using an analysis of variance of the two models to examine
whether one explained significantly more variance than the
Fourth, to test for the mediating effects of emotional close-
ness on the relationship between psychological kinship esti-
mates and willingness to invest, the analyses were conducted
stepwise in accordance with a procedure suggested by Baron
and Kenny (1986). The stepwise analyses were conducted sep-
arately for male and female respondents. To enable comparison
of the regression coefficients, all continuous variables were
standardized by transforming the values into z-scores before
the stepwise analyses were conducted. Then, the zero-order
effect between all three variables of interest was assessed (Step
1–3). After this, an analysis including both psychological kin-
ship estimates and emotional closeness as predictors and
willingness to invest as the outcome variable was conducted
(Step 4). If the zero-order standardized bbetween the predictor
(psychological kinship estimates) and the outcome variable
(investment) decreases, but remains significant, after inclusion
of the mediating variable (emotional closeness), partial media-
tion is supported. If there no longer is a significant association
between the predictor and the outcome variable after including
the mediating variable, full mediation is supported. The differ-
ence between the zero-order association and the association
when the mediating variable is included in the model represents
the indirect effect of the predictor variable on the outcome
variable via the mediating variable. To test the significance
of the indirect effect, the Sobel (1982) test was performed by
using the mediation.test function in the R package (version
5.1.6) (Wang, 2015) in R. The Sobel test examines whether
the decrease in the effect of the predictor when the mediating
variable is introduced in the model is significant. In all analyses,
ap-value < .05 (two-tailed) was considered significant.
Preliminary Analysis
Descriptive information regarding the variables child age, will-
ingness to invest, emotional closeness, and psychological kin-
ship estimates is shown in Table 1. For the following analyses,
adjusted means and standard errors are reported. In the prelim-
inary analyses, no difference between willingness to invest in
female (M¼42.41, SE ¼0.96) and male (M¼42.74, SE ¼
0.78) children was found, b¼0.33, SE ¼1.23, t¼0.26, p¼
.789. Neither was there a difference in willingness to invest
between male (M¼42.30, SE ¼0.96) and female (M¼42.80,
SE ¼0.77) respondents, b¼0.50, SE ¼1.23, t¼0.41,
Table 1. Descriptive Information by Child Gender.
Female (n¼890) Male (n¼1356)
Variable Range MSDRange MSD
Child age 0–18 9.07 5.14 0–18 8.39 5.28
Kidney investment 0–100 68.46 33.37 0–100 72.75 32.37
Salary investment 0–100 31.01 34.54 0–100 32.99 35.03
Jail investment 0–100 27.76 36.65 0–100 22.48 33.51
Willingness to invest: Composite score 0–100 42.41 29.48 0–100 42.74 27.90
Biological child 0–100 67.28 22.66 0–100 66.37 21.99
Sister’s child 0–90 30.55 21.43 0–100 38.42 20.25
Brother’s child 0–87 31.25 20.90 0–100 37.81 20.39
Stepchild 6–79 38.29 20.30 0–98 38.24 25.20
Friend’s child 0–100 22.61 20.11 0–91 22.54 17.71
Emotional closeness 0–100 51.16 33.23 0–100 53.66 34.32
Biological child 0–100 80.62 17.24 0–100 85.26 15.15
Sister’s child 0–100 45.87 22.99 0–100 52.35 25.14
Brother’s child 0–92 38.16 25.80 0–97 44.26 26.09
Stepchild 0–83 44.00 28.68 2–90 39.08 27.12
Friend’s child 0–100 25.11 25.24 0–100 26.43 25.84
Psychological kinship estimates 0.00–0.05 0.24 0.22 0.00–0.50 0.24 0.22
Note. M ¼mean; SD ¼standard deviation.
Antfolk et al. 5
p¼.686. Furthermore, no effect of the marital status of the
respondent was found, F¼0.10, p¼.957.
Regarding the child’s age, we found a significant negative
association between child age and the willingness to invest, b¼
0.38, SE ¼0.11, t¼3.34, p< .001. Similarly, a significant
negative association was found between the age of the respon-
dent and willingness to invest, b¼0.21, SE ¼0.09, t¼2.22,
p¼.026. However, the significant effect of the respondent’s
age disappeared when both child and adult age were included in
the same model. In this model, only child age significantly
predicted willingness to invest, b¼0.38, SE ¼0.11, t¼
3.34, p< .001. The duration of coresidence between a steppar-
ent and stepchild can be assumed to be weakly correlated with
the child’s age. For this reason, we conducted an analysis
including both child’s age and coresidence duration. This anal-
ysis was limited to observations regarding stepchildren. We
found no association between coresidence and investment
when controlling for child’s age, b¼0.01, SE ¼1.03, t¼
0.01, p¼.995. Child’s age was on the other hand significantly
associated with investment also in stepchildren, b¼2.08,
SE ¼1.01, t¼2.06, p¼.046. Regarding the number of
children that a respondent had in his or her care, we found a
significant negative association with willingness to invest,
b¼1.55, SE ¼3.57, t¼0.41, p< .001. We decided to retain
child’s age and the number of children a respondent had in his
or her care as control variables in subsequent mediation analyses.
Further, an LME analysis with follow-up pairwise compar-
isons revealed that adults were significantly more willing to
invest in biological children (M¼66.97, SE ¼0.69) than in
sisters’ children (M¼36.84, SE ¼1.17), brothers’ children
(M¼35.51, SE ¼1.19), stepchildren (M¼36.89, SE ¼2.79),
or friends’ children (M¼22.64, SE ¼0.70, p< .001; Figure 2).
Furthermore, adults were significantly less willing to invest in
friend’s children compared to all other children (p< .001).
There was no significant difference in willingness to invest
between sisters’ children, brothers’ children, and stepchildren.
We also conducted an analysis to test the interaction between
respondent gender and relationship type. The interaction term
was significant (F¼4.61, p< .001). For a sister’s child, women
reported slightly more willingness to invest (M¼39.62, SE ¼
1.47) than men did (M¼32.12, SE ¼1.93), t[2,133.66] ¼3.09,
p¼.002. The same pattern was seen for a brother’s child.
Women reported more willingness to invest (M¼38.21, SE
¼1.59) than men (M¼32.29, SE ¼1.78), t(2,133.66) ¼2.48,
p¼.013. For biological child, stepchild and friend’s child, there
were no differences between men and women (all p>.05).
The comparison between the two models including willing-
ness to invest as the outcome variable, and putative relatedness
and psychological kinship estimates, respectively, as fixed fac-
tor showed that psychological kinship certainty (R
Akaike information criterion [AIC] ¼19.73) explained more
variance in willingness to invest than putative relatedness (R
¼.46, AIC ¼19.80), w
¼78.73, p< .001.
The results from the stepwise LME analyses can be seen in
Table 2. As child age and number of children under the care of
the respondent were both associated with willingness to invest,
we included these variables in all models. For both male and
female respondents, the zero-order relationships between all
variables of main interest (psychological kinship estimates,
emotional closeness, and willingness to invest) were significant
(p< .001; Step 1–3) and positive. In the analyses including both
psychological kinship estimates and emotional closeness as
predictors and willingness to invest as outcome variable (Step
4), both variables significantly predicted the willingness to
invest (p< .001). The relationships between psychological kin-
ship estimates and willingness to invest were weaker (b
0.40, b
¼0.45) than in the zero-order analyses (b
0.71, b
¼0.67), but remained significant (p< .001), sug-
gesting that emotional closeness partially mediates the relation-
ship between psychological kinship estimates and willingness
to invest. The Sobel (1982) test showed that the indirect effect
was significant for both male, Z¼12.04, p< .001, and female,
Z¼11.39, p< .001, respondents.
In the current study, we aimed to investigate how putative
psychological kinship estimates and emotional closeness are
associated with parental investment. To do this, we measured
the willingness to invest in children belonging to different
Figure 2. Violin plot for adjusted means for adults’ willingness to invest in children belonging to the categories biological child, sister’s child,
brother’s child, stepchild, and friend’s child. Higher values indicate more willingness to invest. The violin shape gives the frequencies of responses
by each category, with broader frames indicating more responses.
6Evolutionary Psychology
categories (direct offspring, nieces/nephews, stepchildren, and
friends’ children) in a population-based sample of Finnish adults.
Psychological Kinship Estimates and Emotional Closeness
In accordance with predictions derived from inclusive fitness
theory, stating that when investing, close relatives are preferred
over more distant relatives, which, in turn, are preferred over
unrelated individuals (e.g., Burnstein et al., 1994; Rachlin &
Jones, 2008; Stewart-Williams, 2007, 2008), respondents
reported significantly more willingness to invest in their own
biological children than in other related children (nieces and
nephews), stepchildren, and friends’ children. As expected, the
willingness to invest in friend’s children was low.
An essential finding of the study is that the willingness to
invest is more strongly associated with respondents’ psycholo-
gical kinship estimates regarding a child than it is associated
with the putative relatedness to this child. The higher the kinship
estimate, the more willing adults were to make costly invest-
ments to their biological relatives. This finding is in accordance
with previous research suggesting that certainty in relatedness
has a positive effect on kin directed behavior, increasing, for
example, altruistic dispositions (Alvergne et al. 2009; Anderson
et al., 2007; Apicella & Marlowe, 2004; Webster, 2003).
Additionally, we tested whether the association between
psychological kinship estimates and the willingness to invest
is mediated by emotional closeness as hypothesized by Korch-
maros and Kenny (2001). Due to adult–niece/nephew dyads
being included in the analysis, we were able to also measure
psychological kinship certainty not only in men but also in
women. The results were similar for both men and women.
We found evidence of partial mediation, but contrary to earlier
findings (Korchmaros & Kenny, 2006), we also found that part
of the association between psychological kinship estimates and
the willingness to invest was independent of emotional close-
ness, which is in line with some previous findings (Burton-
Chellew & Dunbar, 2011; Danielsbacka, Tanskanen, Rotkirch,
2015). Interestingly, after the inclusion of psychological kin-
ship estimates, child age and number of children were associ-
ated with emotional closeness but not with investment. This
further suggests that emotional closeness and investment may
partly be independent of one another.
We also found an interaction between respondents’ gender
and the type of relationship, such that, compared to men,
women were more willing to invest in nieces and nephews.
In line with earlier research (e.g., Hrdy, 2007), these results
suggest a sex difference in kin-directed alloparenting, such that
women investment more effort in the caretaking of their sib-
ling’s children.
Age and Number of Children
We also found that both age of a child and the age of the parent
were negatively associated with willingness to invest. This
corroborates the evolutionary assumption that parental care is
mostly required at younger age, and therefore the requirement
Table 2. Results From the Stepwise Linear Mixed Effects Analyses Separately for Responses From Male and Female Respondents.
Step 1: Investment Step 2: Investment Step 3: Emotional Closeness Step 4: Investment
Fixed Factor bSE t bSE t b SE t bSE t
Intercept 0.02 0.03 0.61 0.05 0.03 1.52 0.04 0.03 1.49 0.03 0.03 1.17
Child age 0.02 0.03 0.91 0.02 0.03 0.79 0.08 0.02 3.16** 0.01 0.02 0.22
Number of children 0.03 0.03 1.04 0.01 0.03 0.44 0.07 0.03 2.63** 0.00 0.03 0.16
PKE 0.71 0.02 33.94*** 0.73 0.02 34.64*** 0.40 0.03 12.76***
Emotional closeness 0.76 0.02 32.30*** 0.42 0.03 12.54***
Log likelihood 959.6 959.4 876.0 887.4
AIC 1,931.2 1,930.7 1,764.0 1,788.8
BIC 1,959.9 1,959.4 1,792.7 1,822.2
Intercept 0.01 0.02 0.44 0.01 0.02 0.38 0.03 0.02 1.35 0.00 0.02 0.15
Child age 0.04 0.02 2.24* 0.01 0.02 0.69 0.09 0.02 4.70*** 0.02 0.02 0.98
Number of children 0.04 0.03 1.54 0.02 0.03 0.71 0.05 0.02 2.32* 0.03 0.02 1.10
PKE 0.67 0.01 47.23*** 0.76 0.02 46.75*** 0.45 0.02 19.26***
Emotional closeness 0.68 0.02 39.57*** 0.29 0.03 11.52***
Log likelihood 1,357.4 1,450.5 1,340.6 1,294.1
AIC 2,726.8 2,912.9 2,693.2 2,602.3
BIC 2,758.1 2,944.3 2,724.5 2,638.8
Note. The estimate represents the b value from the mixed-effects modeling analyses with the standardized (z-scored) variables; AIC ¼Akaike information
criterion; BIC ¼Bayesian information criterion; investment ¼willingness to invest; PKE ¼psychological kinship estimates; number of children ¼the number of
children in the care of the respondent; SE ¼standard error.
*p < .05. **p < .01. ***p < .001.
Antfolk et al. 7
for investment decreases with child’s age; consequently,
investment in older children decreases the amount of resources
that could be directed toward younger offspring (e.g., Clutton-
Brock, 1991). This also pertains to age-related variation in
reproductive value. An individuals reproductive value
increases from birth to be maximized at the age of peak
fertility, after which it declines toward 0 at different rates for
men and women (e.g., Fischer 1930; Hughes, 1983). A young
child therefore increases its reproductive value, while its parent’s
reproductive value tends to decrease year by year. Because
reproductive potential is dependent on nutrition and care, parents
nevertheless benefit from investing in their young, ensuring they
reach nutritional independence and sexual maturity.
When including emotional closeness in the analysis, we no
longer found an association between the child’s age and the
willingness to invest. It is important to here consider the type of
investment measured in the current study: the items (donating a
kidney, serving a prison sentence) might not measure the type
of investment that most strongly is related to a child’s age-
related dependency on parental care.
In line with earlier research (Becker and Tomes, 1976;
Ca´ceres-Delpiano, 2006), we also found that the number of
children in the care of an adult was negatively associated with
investment. This association was no longer significant after
including child’s age, emotional closeness, and/or psychologi-
cal kinship cues.
Investment in Stepchildren
Interestingly, stepchildren received as much investment as
nieces/nephews and more investment than friends’ children.
Investment in stepchildren can be understood as the indirect
effect of mating efforts (Anderson et al., 1999; Bjorklund &
Shackelford, 1999; Trivers, 1972). As children need continuous
care in order to survive and thrive, parents are likely to choose a
new partner displaying traits of parental care (Anderson et al.,
1999; Trivers, 1972), and investment in stepchildren can thus
be a way of gaining access to the child’s parent (Anderson
et al., 1999). Although most stepparents invest in their stepchil-
dren, this investment is generally smaller than that of biological
parents (Tifferet, Jorev, & Nasanovitz, 2010; Zvoch, 1999).
For stepchildren, we also investigated the effect of coresi-
dence and investment. We found no indication that coresidence
duration was associated with investment.
Study Limitations
Some limitations to the current study need to be considered.
The sample of responses regarding stepchildren was small (n¼
42, 4.2%). While this reflects the proportion of Finnish families
that contain at least on stepchild under the age of 18 (3.4%;
Statistics Finland, 2016), the small sample size means that
estimates can be unreliable. The small sample size also
increases the possibility of failing to detect a true association
between the duration of coresidence and investment for
It should also be noted that the present study measured the
adults’ self-reported willingness to invest in children. This
willingness was measured as responses to hypothetical and
very costly forms of investment. Because of this, the results
of the present study should be generalized to real investment
with caution.
Because we did not have measures more directly measuring
reciprocity included in the current study, it is difficult to rule
out that the observed patterns are due to reciprocal altruism. As
the potential cost of the measured investment was very high, it
is, however, likely that reciprocity played a relatively small
role in the current study. This is because as investment costs
increases, genetic relatives become preferred over others (e.g.,
Stewart-Willians, 2007).
It has been shown that men who currently live together with
the mother of a biological child invest more in that child com-
pared to men who do not live together with the mother (Ander-
son et al., 1999). In the current study, our measure of
relationship status did not capture whether respondents lived
together with the other parent of a biological child or not.
Because of this, the absence of association between relation-
ship status and investment should be interpreted with caution.
With these limitations in mind, the results in the study partly
provide empirical support for the evolutionary predictions
regarding adults’ investment in children, that is, an adult’s
willingness to invest in a child is dependent on psychological
estimates of the biological relatedness between the adult and
the child. The only exception from this was stepchildren who
received more investment than predicted from inclusive fitness
theory alone.
Children with access to parents who estimate their kinship to
be high are thus expected to receive more investment than other
children. It is, however, important to remember that stepchil-
dren generally have access to at least one biological parent, and
thereby it is likely to assume that, in most cases, they also
receive high levels of investment. From an evolutionary stand-
point, investing in stepchildren is costly. From this perspective,
it is interesting to note that the observed willingness to invest in
stepchildren was considerable.
The study also implies that an important factor mediating
adult’s will to invest in child is emotional closeness. In sum,
psychological kinship estimates and emotional closeness are
important factors to consider for understanding adult–child
relationships, but these do not fully explain variations in the
willingness to invest in children.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to
the research, authorship, and/or publication of this article.
The author(s) received no financial support for the research, author-
ship, and/or publication of this article.
8Evolutionary Psychology
Albrecht, A., Antfolk, J., Lieberman, D., Harju, C., Sandnabba, K., &
Santtila, P. (2014). The Finn-Kin study: A sample and method
description of a Finnish population-based study of kin-
recognition, incest aversion and altruism. Journal of Social
Sciences Research,6, 915–926.
Alvergne, A., Faurie, C., & Raymond, M. (2009). Father–offspring
resemblance predicts paternal investment in humans. Animal
Behaviour,78, 61–69. doi:10.1016/j.anbehav.2009.03.019
Alvergne, A., Faurie, C., & Raymond, M. (2010). Are parents’ percep-
tions of offspring facial resemblance consistent with actual resem-
blance? Effects on parental investment. Evolution and Human
Behavior,31, 7–15. doi:10.1016/j.evolhumbehav.2009.09.002
Anderson, K. G., Kaplan, H., Lam, D., & Lancaster, J. (1999). Paternal
care by genetic fathers and stepfathers II: Reports by Xhosa
high school students. Evolution and Human Behavior,20,
433–451. doi:10.1016/S1090-5138(99)00022-7
Anderson, K. G., Kaplan, H., & Lancaster, J. B. (2007). Confidence of
paternity, divorce, and investment in children by Albuquerque
men. Evolution and Human Behavior,28, 1–10. doi:10.1016/j.
Antfolk, J., Karlsson, M., Ba¨ckstro¨m, A., & Santtila, P. (2012). Dis-
gust elicited by third-party incest: The roles of biological related-
ness, co-residence, and family relationship. Evolution and Human
Behavior,33, 217–223. doi:10.1016/j.evolhumbehav.2011.09.005
Antfolk, J., Lieberman, D., & Santtila, P. (2012). Fitness costs predict
inbreeding aversion irrespective of self-involvement: Support for
hypotheses derived from evolutionary theory, PLoS One,7, 1–7.
Antfolk, J., Lindqvist, H., Albrecht, A., & Santtila, P. (2014). Self-
reported availability of kinship cues during childhood is associated
with kin-directed behavior to parents in adulthood. Evolutionary
Psychology,12, 148–166.
Apicella, C. L., & Marlowe, F. W. (2004). Perceived mate fidelity and
paternal resemblance predict men’s investment in children. Evolu-
tion and Human Behavior 25, 371–378. doi:10.1016/j.evolhumbe-
Axelrod, R. (2006). The evolution of cooperation. New York, NY:
Basic Books.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable
distinction in social psychological research: Conceptual, strategic,
and statistical considerations. Journal of Personality and Social
Psychology,51, 1173–1182. doi:10.1037/0022-3514.51.6.1173
Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). lme4: Linear
mixed-effects models using Eigen and S4. R package version 1.1-9.
Retrieved from https://CRAN.R¼lme4
Becker, G. S., & Tomes, N. (1976). Child endowments and the quantity
and quality of children. Journal of Political Economy,84, 143–162.
Bjorklund, D. F., & Shackelford, T. K. (1999). Differences in parental
investment contribute to important differences between men and
women. Current Directions in Psychological Science,8, 86–89.
Burnstein, E., Crandall, C., & Kitayama, S. (1994). Some neo-
Darwinian decision rules for altruism: Weighing cues for inclusive
fitness as a function of the biological importance of the decision.
Journal of Personality and Social Psychology,67, 773–789. doi:
Burton-Chellew, M. N., & Dunbar, R. I. M. (2011). Are affines treated
as biological kin? Current Anthropology,52, 741–746.
Byrne, D. (1961). The influence of propinquity and opportunities for
interaction on classroom relationships. Journal of Abnormal and
Social Psychology,67, 1–7. doi:10.1177/001872676101400106
Ca´ceres-Delpiano, J. (2006). The impacts of family size on investment
in child quality. Journal of Human Resources,41, 738–754.
Clutton-Brock, T. H. (1991). The evolution of parental care. Prince-
ton, NJ: Princeton University Press.
Daly, M., & Wilson, M. (1985). Child abuse and other risks of not
living with both parents. Ethology and Sociobiology,6, 197–210.
Daly, M., & Wilson, M. (1988). Evolutionary social psychology and
family homicide. Science,242, 519–524.
Daly, M., & Wilson, M. I. (1996). Violence against stepchildren.
Current Directions in Psychological Science,5, 77–81.
Danielsbacka, M., Tanskanen, A. O., & Rotkirch, A. (2015). Impact of
genetic relatedness and emotional closeness on intergenerational
relations. Journal of Marriage and Family,77, 889–907.
Fischer, R. (1930). The genetical theory of natural selection. Oxford,
England: Oxford University Press.
Fox, G. L., & Bruce, C. (2001). Conditional fatherhood: Identity the-
ory and parental investment theory as alternative sources of expla-
nation of fathering. Journal of Marriage and Family,63, 394–403.
Haig, D. (2009). Transfers and transitions: Parent-offspring conflict,
genomic imprinting, and the evolution of human life history. Pro-
ceedings of the National Academy of Sciences,107, 1731–1735.
Hamilton, W. D. (1964). The genetical evolution of social behaviour.
I. Journal of Theoretical Biology,7, 1–16.
Henretta, J. C., Van Voorhis, M. F., & Soldo, B. J. (2014). Parental
money help to children and stepchildren. Journal of Family Issues,
35, 1131–1153. doi:10.1177/0192513X13485077
Hrdy, S. B. (2007). Evolutionary context of human development: The
cooperative breeding model. In C. Salmon & T. K. Shackelford
(Eds.), Family relationships: An evolutionary perspective
(pp. 39–68). New York, NY: Oxford University Press.
Hughes, A. (1983). Kin selection of complex behavioral strategies.
The American Naturalist,122, 181–190.
Hughes, A. (1988). Evolution and human kinship. New York, NY:
Oxford University Press.
Kalil, A., Ryan, R., & Chor, E. (2014). Time investment in children across
family structures. The ANNALS of the American Academy of Political
and Social Science,654, 150–168. doi:10.1177/0002716214528276
Korchmaros, J. D., & Kenny, D. A. (2001). Emotional closeness as a
mediator of the effect of genetic relatedness on altruism. Psycho-
logical Science,12, 262–265.
Korchmaros, J. D., & Kenny, D. A. (2006). An evolutionary and close-
relationship model of helping. Journal of Social and Personal
Relationships,23, 21–43. doi:10.1177/0265407506060176
Krupp, D. B., DeBruine, L. M., & Jones, B. C. (2011). Cooperation
and conflict in the light of kin recognition systems. In C. Salmon
& T. K. Shackelford (Eds.), The Oxford handbook of evolutionary
family psychology (pp. 345–361). New York, NY: Oxford
University Press.
Antfolk et al. 9
Lieberman, D., Tooby, J., & Cosmides, L. (2007). The architecture of
human kin detection. Nature,445, 727–731.
Madsen, E. A., Tunney, R. J., Fieldman, G., Plotkin, H. C., Dunbar, R.
I. M., Richardson, J.-M., & McFarland, D. (2007). Kinship and
altruism: A cross-cultural experimental study. British Journal of
Psychology,98, 339–359. doi:10.1348/000712606X129213
Neyer, F. J., & Lang, F. R. (2003). Blood is thicker than water: Kin-
ship orientation across adulthood. Journal of Personality and
Social Psychology,84, 310–321. doi:10.1037/0022-3514.84.2.310
R Core Team. (2015). R: A language and environment for statistical
computing. Vienna, Austria: R Foundation for Statistical Comput-
ing. Retrieved from
Rachlin, H., & Jones, B. A. (2008). Altruism among relatives and non-
relatives. Behavioural Processes,79, 120–123. doi:0.1016/j.
Roberts, S. G. B., & Dunbar, R. I. M. (2011). The cost of family and
friends: An 18-month longitudinal study of relationship mainte-
nance and decay. Evolution and Human Behavior,32, 186–197.
Sariola, H., & Uutela, A. (1996). The prevalence and context of
incest abuse in Finland. Child Abuse & Neglect,20,843859.
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects
in structural equations models. In S. Leinhart (Ed.), Sociological
methodology (pp. 290–312). San Francisco, CA: Jossey-Bass.
Statistics Finland. (2016). Retrieved from
Stewart-Williams, S. (2007). Altruism among kin vs. nonkin: Effects
of cost of help and reciprocal exchange. Evolution and Human
Behavior,28, 193–198. doi:10.1016/j.evolhumbehav.2007.01.
Stewart-Williams, S. (2008). Human beings as evolved nepotists:
Exceptions to the rule and effects of cost of help. Human Nature,
19, 414–425. doi:10.1007/s12110-008-9048-y
Tifferet, S., Jorev, S., & Nasanovitz, R. (2010). Lower parental invest-
ment in stepchildren: The case of the Israeli “Great Journey”.
Journal of Social, Evolutionary, and Cultural Psychology,4,
62–67. doi:10.1037/h0099300
Trivers, R. L. (1971). The evolution of reciprocal altruism. The Quar-
terly Review of Biology,46, 35–57.
Trivers, R. L. (1972). Parental investment and sexual selection. In B.
Campbell (Ed.), Sexual selection and the descent of man
(pp. 136–179). Chicago, IL: Aldine.
Wang, B. (2015). bda: Density estimation for grouped data. R package
version 5.1.6. Retrieved from
Webster, G. D. (2003). Prosocial behavior in families: Moderators of
resource sharing. Journal of Experimental Social Psychology,39,
644–652. doi:10.1016/S0022-1031(03)00055-6
Westermarck, E. (1891). The history of human marriage. London,
England: Macmillan.
Zvoch, K. (1999). Family type and investment in education: A com-
parison of genetic and stepparent families. Evolution and Human
Behavior,20, 453–464. doi:10.1016/S1090-5138(99)00024-0
10 Evolutionary Psychology
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... Studies comparing the rate of stepchildren in familicides to the general population show that step relationships are overrepresented in the familicide samples (Wilson et al., 1995;Wilson & Daly, 1997). This finding is in line with research indicating that parents do not invest in stepchildren to the same degree as in biological children (Antfolk, Karlsson, Söderlund, & Szala, 2017;Henretta, Van Voorhis, & Soldo, 2014;Kalil, Ryan, & Chor, 2014) and that children have a higher risk of becoming physically and sexually abused by a stepparent than by a biological parent (Archer, 2013;Daly & Wilson, 1985Hilton, Harris, & Rice, 2015;Sariola & Uutela, 1996). This "Cinderella effect" can be partially explained by parents being emotionally more close to biological children, and by evolutionary assumptions, stipulating that natural selection has promoted parental investment in biological children, as these, in contrast to stepchildren, share the parent's genetic material Karlsson, Malén, Kaakinen, & Antfolk, 2018;Trivers, 1972). ...
An increasing number of children are growing up in reconstituted households, formed by a couple and a non-common child. Reconstituted households tend to be poorer, which is associated with worse behavioural and developmental outcomes. Additionally, there is evidence that non-common children receive less economic support from their parents upon leaving the parental home. Using age-specific deprivation data collected in the 2014 European Survey on Income and Living Conditions this article compares the allocation of resources in reconstituted and intact couple households. It shows that indeed, children in reconstituted households are more likely to be deprived compared to those in intact households. However, it finds no evidence that reconstituted households are less likely to prioritise children. The findings hold across welfare regimes. Women are more likely to go without compared with men, although differences are small.
This study uses data from the American Community Survey to examine the relationship between race, family configurations, and inequalities in private school enrollment among adoptees. We find that private school enrollment is higher in transracial than in same-race families. This disparity is driven by the outcomes of adoptees in transracial families with zero rather than one same-race parent. Among adoptees themselves, there are diverging patterns of racial stratification in same-race and transracial families. White adoptees in same-race families are more likely to be enrolled in private school than Black, Asian, or Hispanic adoptees in such families. However, among adoptees in transracial families, the highest odds of private school enrollment are found among Asians. Finally, we argue that our findings have important implications for understanding how kinship cues, compensation, and social disadvantage shape parental investment in adopted children.
The current Chapter analyzes the universal aspects of the form and function of human families, the important cultural variations in families, and the implications of those universalities and cultural variations for practice aimed at enhancing family functioning. I begin by examining families through an evolutionary lens to identify what is universal about human families. The next section of the Chapter describes how culture affects human adaptation, and how culture and families reciprocally influence each other. The last section of the Chapter synthesizes knowledge about interventions to promote family functioning across diverse cultures.
This paper reports Phase II findings of an exploratory study of 26 families who have adopted children with Asian heritage, where at least one parent is Asian American. In-depth interviews provided a rich exploration of parents’ motivations to kin through adoption, the ways in which race and ethnicity factored into their child-selection preferences (if at all), their assumptions about their ability to create kinship bonds with an adopted child, and strategies for racial and ethnic socialization. The themes of approximating or performing family and inconspicuousness were repeated by parents when they considered how race and ethnicity factored into child-selection preferences and their assumptions about creating kinship bonds. The adoptive parents in this study were measured and nuanced in weighing the role of race and ethnicity for Asian adoptees, but the implicit strategies of modeling, mentoring, and intergenerational transmission were described less as strategies, and more about belonging and being a part of an extended tribe that was more authentic because of a shared identity as Asian Americans. Ultimately the question of whose interests are being served when race and ethnicity are considered has been dynamic and shifting throughout adoption history. This study sought to contribute in a small part to moving the conversation beyond the polarized Black-White racialized paradigm and provides direction for further research.
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In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators. (46 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Technical Report
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Description Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' ``glue''.
Both emotional closeness and genetic relatedness are known to influence helping behavior between family generations, yet few studies have explored them together. The authors investigated the associations between (a) parenthood and perceived emotional closeness toward own parents and parents-in-law and (b) emotional closeness and receiving child care from grandparents across and within lineage lines. The data include information on the 8 dyads of possible parent–grandparent relations from a nationally representative survey of young adults in Finland (born 1962–1990, sample N = 1,216). The results show that parenthood was associated with women's emotional closeness to their own mothers and men's emotional closeness to their parents-in-law. Maternal grandmothers provided the most grandchild care. After controlling for emotional closeness, the difference in child care provision between one's own mother and one's mother-in-law disappeared for women but was accentuated in men. Thus, emotional closeness shapes intergenerational relations differently for kin and in-laws.