Strong‐Ties and Weak‐Ties Rationalities: Predicting Public Stigma, Support Networks, and Health Behaviours During the COVID‐19 Pandemic Across Four Societies

ABSTRACT

In this study, we test the theory of strong‐ties and weak‐ties rationalities (STWTR) (Sundararajan 2020) and the criterion validity of its measures using strong‐ties rationality and weak‐ties rationality scales to predict COVID‐19 related perceptions and behaviours. These include public stigma, help‐seeking networks, and health behaviours across four societies (Han‐Chinese, Chinese‐Malaysians, Malay‐Malaysians, and White‐Australians, n = 918). The standardized coefficient results indicate that strong‐ties rationality, compared with weak‐ties rationality, has a stronger positive association with public stigma, help‐seeking from strong ties, and personal care behaviours. In contrast, weak‐ties rationality, compared with strong‐ties rationality, has a stronger positive association with public health behaviours. Between the Han‐Chinese and White‐Australians samples, the impact of strong‐ties rationality on public stigma is weaker among the Han Chinese, while the impact of weak‐ties rationality on public health behaviour is stronger among the White Australians. We attribute our nuanced analysis of these results to the explanatory power of STWTR theory, which decomposes culture into three units of analysis—rationality, ecological niche, and behaviour, enabling an examination of the match or mismatch among these cultural components characterizing any society. Indigenous features of a cultural system can then be more fully represented in cross‐cultural psychological research.

Strong‐Ties and Weak‐Ties Rationalities (STWTR) theory offers an alternative approach to understanding cultural influence that moves beyond the conventional Individualism and Collectivism framework (Sundararajan 2020). Rationality refers to reasoning about the world and the implicit logic underpinning such reasoning. According to Sundararajan (2020), strong‐ties (ST) and weak‐ties (WT) rationalities represent the logic and reasoning processes underpinning two primary ontological orientations that concern how we are related to others—to closely related others (ST), such as family and intimates, or to unrelated others (WT), such as acquaintances and strangers. Consistent with the theory of ecological rationality (Todd et al. 2012), which posits that rationality and ecological niche have co‐evolved, Sundararajan (2020) claims that ST and WT rationalities have co‐evolved with ST and WT ancestral niches, respectively.

Our ancestral niches vary in kinship intensity (Curtin et al. 2020). ST societies are those with intensive kinship, “characterized by extended family networks, cousin marriage, polygyny, endogamy, unilineal descent, and an increase in relatedness within kin groups” (p. 417). WT societies are those with extensive kinship that “tend to encourage the formation of broad social networks with unrelated individuals, and often feature exogamy and bilateral descent” (p. 417). Agriculture is the ancestral niche for hierarchical ST societies, whereas an extreme form of WT with weak and loose kin ties (Curtin et al. 2020) may trace its ancestral niche to Medieval Christianity (Schulz et al. 2019).

ST rationality (STR) and WT rationality (WTR) differ in many ways. First, in ST networks based on family lineage and blood ties, one is born into a set of pre‐established kinship relationships with little freedom of choice of association. By contrast, in WT networks based on unrelated acquaintances and strangers, the making and unmaking of relationships is a matter of individual choice. Thus, the well‐being and survival of the collective (the family and in‐group) are a primary concern for STR, whereas the well‐being and survival of the individual are the primary focus for WTR. Second, in the close‐knit ST network, personal recognition forms the basis of interpersonal associations. By contrast, in the anonymous society of WT networks, one relates to others based on one's group memberships or social categorizations, such as religious affiliation, employment type, or ethnicity (Sundararajan 2020).

Sundararajan (2020) argues that this difference in relationship logic results in different cognitive styles between STR and WTR. To the extent that face‐to‐face personal transactions with familiar others capitalize on touch, smell, and implicit, non‐verbal expressions, STR tends to privilege perceptual, experiential representations and holistic thinking. To the extent that transactions with strangers and persons sharing a social category (nationality, professional and voluntary associations, etc.) capitalize on conceptual and analytic thinking, WTR tends to privilege more abstract and explicit representations. This hypothetical difference in information processing between STR and WTR has found support in multiple studies: It was borne out in analyses of Chinese emotions (Sundararajan 2015); in the emotion expressions of the Yi minority group in China (Ting and Sundararajan 2018); in a psycholinguistic analysis of two different religious groups among the Yi (traditional Bimo group vs. Christian converts) (Ting et al. 2017; Sundararajan et al. 2022). In another, more recent (Thong et al. 2024) study of the impact of religious conversion on a group of hunter‐gatherers in Malaysia, Christian converts used more abstract and conceptual expressions than the Muslim converts and the traditional group of Temiar, with the effect on language use evident just within one generation of conversion. Another area of application for this hypothetical difference in information processing between STR and WTR is disease diagnosis. Modern medicine (WTR) makes abstract and conceptual diagnoses of viruses and bacteria, whereas the Yi healers (Bimo) depend on perceptual cues to determine the cause of a disease, such as ghosts and spirits. Support for this hypothesis was found in two pilot studies that investigated the epidemic of HIV/AIDS in a geographically isolated population of the Yi in Liangshan China (Ting et al. 2026; Sundararajan et al. 2026).

Lastly, the necessary corollary of STR and WTR is psychological distance, that is, up close and proximal versus far and distal. According to construal‐level theory (Trope and Liberman 2010; Trope et al. 2021), our regulatory strategies change in accordance with psychological distance. Lee and Fujita (2023) explain that one expands one's regulatory scope to address concerns that are psychologically distal and contracts regulatory scope to address concerns that are psychologically proximal. Thus, STR and WTR may fall along the divide between contractive (narrowing the focus and scope) versus expansive (widening the scope) regulatory strategies.

In daily transactions with familiar others, STR tends to have a narrow focus on personal, face‐to‐face recognition in order to track the other's unique and constantly changing cues. In dealing with strangers who are psychologically distant, WTR tends to expand the scope of its reach, such as having many followers on social media. As Hwang (2012) points out, in China (a ST society) family and friends are two different networks with clear boundaries. The family network is hierarchical with low relational mobility, whereas friendship is equalitarian and has high relational mobility. In sharp contrast is the tendency in the United States (a WT society) for parents to address their children as “buddies.” The differentiated ties with clear boundaries in the Chinese tradition can be understood as a contractive strategy of STR to make sure that one's social commitments do not spread across ties and become too thin. By contrast, the expansive strategy of WTR would privilege the universal, one‐size‐fits‐all categories, such as friendship, to accommodate a wide variety of networks, ranging from family to employment, and even to God (as a friend). This difference in expansive versus contractive networking strategies is reflected in the intergenerational difference in media use in modern China. A study by Lin et al. (2017) found that contemporary Chinese college students use social media in a way similar to Western (WT) societies—expansive networking with strangers in virtual environments for a variety of reasons (e.g., self‐expression, sharing personal lives, chatting, shopping, etc.). By contrast, their parents use social media in a more traditional (ST) way, namely highly selective (contractive), as evidenced by no networking with strangers nor engagement in virtual relationships, but instead for personal sharing within the actual social network, and mainly for interpersonal relationships.

In spite of some overlaps and affinities, the theory of STWTR (Sundararajan 2020) differs from the theory of Individualism and Collectivism in one major respect: STWTR (Sundararajan 2020) goes beyond the conventional notion of culture as one seamless piece of cloth by decomposing the construct into three components (see Sundararajan et al. 2025): (a). upstream ST or WT rationalities; (b). downstream ST or WT ancestral niches; (c). downstream cultural products (perceptions, behaviours, values, beliefs, etc.). The hypothetical connection between rationalities upstream and cultural practices downstream can be directly tested by a quantitative measure of ST/WT rationalities, Strong‐Ties Weak‐Ties Rationality Scale (STWTRS) (see the section on Measures).

Using STWTRS, a cross‐cultural study conducted by Yeh et al. (2024) with 1291 participants across four societies, China, India, Taiwan, and the United States, found that as predicted, STR was positively related to strong‐ties values and beliefs in reciprocal filial piety, authoritarian filial piety, Dharma (purity + authority), belief in a just world, and that WTR was positively related to weak‐ties belief in an unjust world. Another study (n = 2173) by Ting et al. (2023) across 2 Asian countries (China and Malaysia) and 2 Western countries (Australia and the United States) found that STR and WTR predicted COVID‐19 pandemic‐related perceptions and behaviours such as stigma and help‐seeking. In the cross‐indigenous study (society‐by‐society analysis) of Ting et al. (2023), a latent structure of STR and WTR rationalities was further revealed with different variability across the societies:

• WT‐A (Analytic) pertains to rational/analytic reasoning that is focused on cost and benefit analysis;

• WT‐I (Independent) pertains to a choice mindset (Markus and Kitayama 2003) that privileges independent self‐expression of a non‐relational self (often referred to as Individualism).

• ST‐C (Communal) pertains to communal sharing (Fiske 1991) that motivates a harmony orientation and manifests as relational reciprocity and concern for others.

• ST‐A (Authoritarian) pertains to the concerns for group survival that justifies authoritarian measures and privileges the group over the self (often referred to as collectivism).

These nuanced structures of STR and WTR suggest possible internal dynamics that may influence their effects on cultural practices downstream. A case in point is parasite‐related stigma. Kurzban and Leary (2001) point out that within parasite‐related stigma there may be an inherent tension “between mechanisms designed to deliver benefits to kin and systems designed to avoid parasites” (p. 201). This tension can be expected to be reinforced by that between ST‐C (communal sharing/caring) and ST‐A (authoritarian)—the former element of STR intends to care for sick members of the group, whereas the latter element of STR may want to exclude pathogen‐carrying members for the safety of the group. Thus, the effect of STR on disease stigma may be either mitigated or strengthened depending on which way the balance in STR is tipped between caring for versus excluding individuals perceived as a contaminant risk.

A related unpublished study of illnesses stigma among the Yi in Liangshan, China (Sundararajan et al. 2026) found that to the extent that the Yi privilege perceptual cues over abstract concepts, the visibility of a disease, rather than its diagnosis in modern medicine, is what would tip the balance toward stigmatizing. Thus, leprosy with missing eyebrows and limbs has been highly and consistently stigmatized by the Yi till this day. By contrast, HIV/AIDS, a contagious disease without any clear symptomatology until the late stage, is both stigmatized and not stigmatized in the Liangshan community, resulting in contradictions and ambiguities that contribute to the perpetuation of the AIDS epidemic in the region. This concludes the theory and application of STWTR.

1. Aims of the Study

To assess the explanatory power of STWTR in the present study, we employed the original dataset from a previous study (Ting et al. 2023) but re‐visioned it by using more refined samples based on ethnicity, additional measures, and measurement invariance to ensure cross‐cultural equivalence. To the extent that diverse ethnic groups have their own ancestral niches, distinguishing the ethnic groups within a given country sample will help to define “ancestral niche” more precisely using STWTR theorizing. Thus, in the current study, we divided the multi‐cultural Malaysians sample into two ethnic groups, viz., Chinese‐Malaysians and Malay‐Malaysians. In addition to the two outcome variables used in the previous study, viz., public stigma and help‐seeking preference, we added a pandemic‐relevant variable, namely health behaviours. To find out whether ST and WT rationalities predict variations in health behaviours during the pandemic, we assessed: (1) public health behaviours that were promoted by WHO (2020) during the COVID‐19 pandemic, such as mask wearing, social distancing, and hand sanitization; and (2) personal care behaviours, such as taking herbal supplements, engaging in physical exercise, and practicing meditation. Finally, we divided help‐seeking behaviours into two categories: (1) preference for help‐seeking from ST and WT support networks, and (2) scope of help‐seeking from a variety of sources.

1.1. Hypothesis Development

To test STWTR theory, we first examined the connection between upstream rationalities and downstream pandemic‐related behaviours (Hypotheses [Link], [Link], [Link], [Link]), then explored the moderating effect of ancestral niche on the connections between rationality and behaviour (H4). First, based on STWTR theory (Sundararajan 2020), we predicted that upstream ST‐WT rationalities will impact public stigma (i.e., stigma toward others), preference for, and scope of, one's help‐seeking, and health behaviours during the COVID‐19 pandemic. Specifically, ST rationality would capitalize on contractive regulatory strategies to focus on things at a shorter mental distance, whereas WT rationality would prefer expansive regulatory strategies (Trope et al. 2021) to focus on matters at greater mental distance.

Stigma concerns negative evaluations of deviant individuals (Kurzban and Leary 2001). Thus, we hypothesize that stigmatization is a task highly relevant to ST rationality that has a narrow (contractive) focus on deviant individuals for harmony control within the group, whereas WT rationality is less focused on tracking individual deviance. Thus:

STR, compared with WTR, is more positively related to public stigma (PS).

Concerning preferences for, and scope of, help‐seeking, we hypothesize that the contractive regulatory strategy of STR will result in a preference for seeking help from those familiar and nearby, namely one's ST network, whereas the expansive regulatory strategy of WTR will result in seeking a wider variety of helping resources, including those less well acquainted and at greater social distance as well as intimate others. Thus:

STR, compared with WTR, is more positively related to a preference for help‐seeking from one's ST network (HS‐ST).

WTR, compared with STR, is more positively related to help‐seeking from a wider variety of sources (HS‐V), that is, help from one's ST network as well as help from one's WT network.

Considering health behaviours, STR will adopt the contractive regulatory strategy of focusing on tailoring healthcare resources according to one's personal needs, whereas WTR will adopt the expansive regulatory strategy of promoting public health policies in order to reach as many people in society as possible. Thus:

STR, compared with WTR, is more positively related to adopting personal care behaviours (PCB).

WTR, compared with STR, is more positively related to adopting public health behaviours (PHB).

STWTR theory stipulates that rationality has co‐evolved with its ecological niche (Sundararajan 2020). So, we predict that the associations hypothesized above will be reinforced by the matching ancestral niche. In our ideal‐type sampling, Han‐Chinese and White‐Australians fall at opposite ends along the divide between the ST and WT ancestral niches. Malaysians, however, due to their long history of colonization by Islamic and European powers, fall between ST and WT niches, resulting in a mix of ST and WT orientations (Ting et al. 2023). Thus, Han‐Chinese and White‐Australians are predicted to show more pronounced STR or WTR main effects, respectively. More specifically,

The relationship between STR and PS is stronger in the Han‐Chinese group than in the White‐Australians group.

The relationship between STR and HS‐ST is stronger in the Han‐Chinese group than in the White‐Australians group.

The relationship between STR and PCB is stronger in the Han‐Chinese group than in the White‐Australians group.

The relationship between WTR and the HS‐V is stronger in the White‐Australians group than in the Han‐Chinese group.

The relationship between WTR and PHB is stronger in the White‐Australians group than in the Han‐Chinese group.

Since Chinese Malaysians share the same ancestral roots with Han‐Chinese in China, and Malay Malaysians have been under the influence of Islam and British rule for centuries, the difference between the two Malaysian groups and the two other ethnic groups will be analysed without prior hypothesizing to further examine the interaction between ST‐WT rationalities and ecological niche.

2. Method

2.1. Procedure

After obtaining ethics approval, we collected data through the Qualtrics online platform in China, Malaysia, and Australia. Participants were recruited through posters, social media, researchers' personal networks, and emails. Eligibility (age 18–65 and citizenship) was confirmed through a screening question before requesting consent. Participants received an e‐voucher in appreciation, either through lucky draws or for the first limited number of participants, depending on the recruitment methods.

2.2. Participants

Data were collected during the COVID‐19 pandemic (2020–2021) as part of an international project, resulting in 1234 responses from citizens in three countries: China (n = 425), Malaysia (n = 415) and Australia (n = 394). Given the intent of this study, we first sampled the dataset based on ancestral niches from each country, including Han Chinese, Caucasian/European (White) Australians, Chinese Malaysians, and Malay Malaysians. To align the student to non‐student composition across all countries, we then randomly removed half of the student sub‐sample from China, reducing its student proportion from 49% to 34%. After data sampling and cleaning, the final sample comprised 918 participants across the four ethnic groups: Han Chinese (n = 295), Chinese Malaysians (n = 195), Malays (n = 150) and White Australians (n = 278), with a community sample comprising the majority of participants in each sample (66%, 69%, 80% and 86%, respectively). More details can be found in Table 1 below.

TABLE 1.

Demographics by Society.

		Age		Education		Socio‐economic status, SES			Religion (%)
Society	N	Mean	SD	Mean	SD	Mean	SD	Gender (% female)	Atheism	Buddhism	Christianity	Chinese folk/Taoism/Confucianism	Islam	No religion	Others/prefer not to say
Han Chinese	295	31.22	(11.68)	2.60	(1.10)	6.20	(1.70)	69.15	0	9.2	2	1	0	85.4	2.4
Chinese‐Malaysians	195	30.39	(11.17)	2.70	(0.90)	5.40	(1.60)	67.18	2.1	48.7	33.3	6.2	0.5	9.2	0
Malay‐Malaysians	150	31.77	(9.88)	2.70	(0.90)	5.90	(2.10)	64.67	0.7	0	0	0	99.3	0	0
White‐Australians	278	44.02	(15.51)	2.50	(0.80)	5.40	(1.90)	53.24	12.6	1.1	40.6	0	0	44.2	1.4
All	918	35.0	(13.90)	2.60	(0.90)	5.80	(1.90)	63.18	4.4	13.6	20	1.6	16.3	42.8	1.2

Note: Age in years; education attainment (1 = High School and below; 2 = Certification programs; 3 = Undergraduate; 4 = Postgraduate); SES (“1” lowest to “10” highest); gender (binary options: male and female).

Abbreviation: SD, standard deviation.

2.3. Measures

Except for STWTRS, which was constructed bilingually with Chinese and English versions, the rest of the questionnaires were in English and translated into the respective national languages using forward and backward translation procedures based on established cross‐cultural adaptation guidelines (Beaton et al. 2000). Translations were reviewed by bilingual cultural experts to ensure conceptual equivalence and cultural appropriateness. In China and Australia, the questionnaire was presented in Chinese and English, respectively. In Malaysia, the questionnaire was available in three languages: Chinese, Malay, and English, allowing participants to choose their preferred language according to their educational background. Most of the Malay‐Malaysian participants chose either the Malay (89.3%) or English (10.7%) versions, while Chinese‐Malaysians chose the English (52.3%), Malay (32.3%) and Chinese (15.4%) versions. The full scales in English are provided in the Supporting Information (See Supporting Information: Appendix 1).

2.3.1. Strong‐Ties Weak‐Ties Rationality Scale (STWTRS)

We used the 20‐item scale developed during the early phase of the COVID‐19 pandemic by Sundararajan and Yeh (2022) to measure ST and WT rationalities. The STWTRS is a 20‐item scale of evaluative statements concerning COVID‐related precepts, propositions, and practices that are deemed congruent with the logic of either ST or WT rationality (for details, see Sundararajan and Yeh 2022; Yeh et al. 2022). Items were rated on a 6‐point Likert scale (1—“completely disagree” to 6—“completely agree”). A sample item of ST rationality is, “It is important not to complain or gripe during a lockdown, because these words spread negative energy and can hurt many people around you.” A sample item of WT rationality is, “In implementing a lockdown, it is important to balance the interests of the group with the interests of individuals, so that one is not served at the expense of the other.” Factor analyses confirmed the scale's validity (Ting et al. 2023; Yeh et al. 2022).

2.3.2. Public Stigma (PS)

Adapted from Abuhammad et al. (2021), Campo‐Arias et al. (2021), and Tomczyk et al. (2020), this 8‐item scale measured stigma toward COVID‐19 patients, such as blame and rejection toward individuals infected with COVID‐19, on a 4‐point Likert scale (1—“strongly disagree” to 4—“strongly agree”). A sample item is, “I do not want to associate with people infected with COVID‐19.”

2.3.3. Help‐Seeking Preference Scale (HS)

Adapted from Wilson et al.'s (2005) scale, this measure assessed preferences for strong‐ties (e.g., family, relatives) network and the weak‐ties (e.g., friends, professionals, helplines) network on a 4‐point Likert scale (1 “extremely unlikely” to 4 “extremely likely”). The guiding question was, “During the pandemic, if you were facing a personal or emotional problem, how likely are you to seek help from the following people?” In this study, we adopted then HS‐ST subscale (3 items) to assess help‐seeking preferences from strong‐ties networks.

2.3.4. Help‐Seeking Variety (HS‐V)

To assess the scope of help utilized, we created an index of varieties of help utilization that codes each of the 11 help‐seeking items according to its rated likelihood of utilization (items rated “extremely unlikely” or “unlikely” were coded as 0; and items rated “likely” or “extremely likely” were coded as 1), with a higher total score indicating a wider variety of help resources sought during the pandemic.

2.3.5. Public Health Behaviours (PHB) and Personal Care Behaviours (PCB)

We adapted the COVID‐19 prevention recommendations from the WHO (2020), the U.S. Centers for Disease Control and Prevention [CDC] (2021) and Hernández‐Padilla et al. (2020) to assess (1) Public Health Behaviours (PHBs) and (2) Personal Care Behaviours (PCBs). Examples of PHB included mask wearing, social distancing, and using hand sanitization; those of PCB included taking herbal supplements, doing physical exercise, and meditating. Participants rated each behaviour's adoption on a 5‐point Likert scale (1 “never” to 5 “all the time”).

2.3.6. Covariates

We controlled for participants' age, education, socio‐economic status, gender, and COVID‐positive history to discount potential confounding effects.

2.4. Measurement Invariance

We performed confirmatory factor analyses and multigroup confirmatory factor analyses to assess the measurement invariance of the four dependent variables. Based on the findings, one item was removed from the ST rationality subscale, five items from the WT rationality subscale, two items from the scale for HS‐ST, and two items from the scale for HS‐V. We retained all items in the measures of PHB and PCB. The details of the measurement invariance procedure are provided in the Supporting Information (See Supporting Information: Appendix 2 and Table S1).

The final scores used were the average scores of all the retained items in each measure. Table 2 provides the means, standard deviations, and reliability scores of all measures by society and the total sample. The Han‐Chinese cluster exhibited reliabilities < 0.60, somewhat low according to the standard for cross‐cultural comparisons (Fu and Yukl 2000) on WTR, PCB, while the Chinese‐Malaysians cluster had a low reliability on WTR. We tested H1, H2 and H3 with and without those clusters; the findings, despite variance in the values of their alpha coefficients, were highly similar. Therefore, we retained the fuller clusters of items in the analyses (See Supporting Information: Tables S2–S6).

TABLE 2.

Means, Standard Deviations and Cronbach's Alphas of the Study Variables by Cultural Groups.

Cultural groups		ST rationality	WT rationality	Public stigma	Help‐seeking ST	Help seeking variety	Personal care behaviour	Public health behaviour
Han‐Chinese	Mean (SD)	4.81 (0.67)	4.70 (0.62)	1.50 (0.45)	2.93 (0.60)	7.36 (2.20)	2.93 (0.60)	4.06 (0.49)
	Alpha	0.79	0.47	0.88	0.64	n.a.	0.55	0.72
Chinese‐Malaysians	Mean (SD)	4.85 (0.51)	4.96 (0.56)	1.90 (0.50)	2.62 (0.74)	5.66 (2.65)	3.16 (0.74)	4.36 (0.43)
	Alpha	0.68	0.57	0.77	0.79	n.a.	0.62	0.65
Malay‐Malaysians	Mean (SD)	4.98 (0.56)	5.22 (0.50)	1.65 (0.48)	2.89 (0.66)	4.96 (2.67)	2.92 (0.80)	4.41 (0.48)
	Alpha	0.72	0.60	0.84	0.78	n.a.	0.62	0.68
White‐Australians	Mean (SD)	4.39 (0.79)	4.59 (0.80)	2.06 (0.59)	2.30 (0.80)	7.59 (2.69)	2.68 (0.92)	3.97 (0.82)
	Alpha	0.80	0.68	0.84	0.71	n.a.	0.73	0.82
Total	Mean (SD)	4.72 (0.70)	4.81 (0.69)	1.78 (0.56)	2.67 (0.75)	6.31 (2.76)	2.9 (0.79)	4.15 (0.62)
	Alpha	0.78	0.62	0.83	0.75	n.a.	0.64	0.78

Note: As scalar measurement invariance was not established for the above scales, the means reported above are for reference only and should not be compared across groups.

Abbreviation: SD, standard deviation.

2.5. Analytical Strategy

We used STATA 17.0 for all analyses and conducted regression analyses requesting standardized coefficients (i.e., beta coefficients) to assess the main effects (Keith 2019). When coefficients are standardized in a common scale, we can compare the numeric value of coefficients to determine which predictor has a stronger effect on the dependent variable. To assess societal moderating effects, we decomposed the total sample and created a series of dummy variables pairwise to assess if the ethnic group showed any interaction with the independent variable, as stated in H4a to H4e.

3. Results

3.1. Main Effects

The results of the correlation coefficient between all relevant variables could be seen in Table 3. Table 4 provides the regression results of the direct effects. In Model 1, the standardized coefficient for STR (β = 0.10, p < 0.001) was higher than that for WTR (β = −0.02, ns). This supports Hypothesis H1, indicating that STR compared with WTR had a stronger positive association with PS. In Model 2, the standardized coefficient for STR (β = 0.25, p < 0.001) was higher than that for WTR (β = 0.01, ns). This supports Hypothesis H2a by showing that STR had a stronger positive association with HS‐ST. In Model 3, the standardized coefficient for WTR was not significantly related to HS‐V (β = 0.01, ns), while STR was related to HS‐V (β = 0.26, p < 0.001). Hence, Hypothesis H2b was not supported. In Model 4, the standardized coefficient for STR (β = 0.26, p < 0.001) exceeded that for WTR (β = 0.12, p < 0.01), confirming Hypothesis H3a and indicating that STR, compared with WTR, had a stronger positive association with PCB. As shown in Model 5, the standardized coefficient for WTR (β = 0.26, p < 0.05) was higher than that for STR (β = 0.17, p < 0.001), supporting H3b that WTR, compared with STR, had a stronger positive association with PHB. In conclusion, all hypothesized direct effects were supported except that of Hypothesis H2b.

TABLE 3.

Means, Standard Deviations, and Zero‐order Correlation Coefficients.

	Mean	SD	1	2	3	4	5	6	7	8	9	10
1. ST Rationality	4.72	0.70
2. WT Rationality	4.81	0.69	0.63***
3. Public Stigma	1.78	0.56	0.11***	0.06
4. Help‐Seeking ST	2.67	0.75	0.27***	0.16***	−0.10***
5. Help‐Seeking Variety	6.31	2.76	0.26***	0.17***	−0.09**	0.69***
6. Personal Care Behaviour	2.90	0.79	0.34***	0.29***	0.09*	0.27***	0.29***
7. Public Health Behaviour	4.15	0.62	0.33***	0.37***	0.01	0.08*	0.08*	0.33***
8. Age	35.05	13.89	−0.03	0.04	0.14***	−0.24***	−0.10	0.00	−0.01
9. Gender	0.63	0.48	−0.03	−0.02	−0.13***	0.05***	0.04	0.04	0.06	−0.19***
10. Education	2.60	0.90	−0.11**	−0.02	−0.15***	−0.01***	0.05	−0.01	0.04	−0.07*	0.12***
11. SES	5.76	1.86	0.00	−0.04	−0.12***	−0.03	−0.05	−0.20***	−0.05	−0.16***	0.01	−0.20***

Note: *p < 0.05, **p < 0.01, ***p < 0.001. Gender (1 = female, 0 = male); education (1 = high school and below, 4 = postgraduate); SES, social economic status (“1” the lowest to “10” the highest).

Abbreviations: SD, standard deviation; ST, strong‐ties; WT, weak‐ties.

TABLE 4.

Main Effects of Rationalities on Pandemic Outcomes.

	Model 1		Model 2		Model 3		Model 4		Model 5
	Public stigma		Help‐seeking ST		Personal care behaviour		Help‐seeking variety		Public health behaviour
Dependent variable	Coeff.	SE	Coeff.	SE	Coeff.	SE	Coeff.	SE	Coeff.	SE
Intercept	1.86***	0.39	2.30***	0.32	2.01***	0.38	4.71**	1.42	2.04***	0.40
Age	0.10**	0.00	−0.24***	0.00	−0.02	0.00	−0.09**	0.01	−0.01	0.00
Gender	−0.10**	0.04	0.01	0.05	0.05	0.05	0.02	0.19	0.06	0.04
Education	−0.14***	0.02	−0.02	0.03	−0.03	0.03	0.07*	0.10	0.05	0.02
SES	−0.14***	0.01	−0.07.	0.01	−0.20***	0.01	−0.05	0.05	−0.03	0.01
COVID‐19 positive	0.00	0.18	−0.02	0.13	−0.04	0.17	−0.06**	0.57	0.02	0.17
ST Rationality	0.10**	0.03	0.25***	0.04	0.26***	0.04	0.26***	0.16	0.17***	0.04
WT Rationality	−0.02	0.03	0.01	0.05	0.12**	0.05	0.012	0.17	0.26***	0.04
N	918		918		918		918		918
F	10.47***		18.01***		21.77***		11.87***		16.12***
Adjusted R 2	0.08		0.13		0.17		0.09		0.16

Note: *p < 0.05, **p < 0.01, ***p < 0.001. Standardized coefficients are provided; s.e. = standard error; age in years; gender: 1 = female; 0 = male; SES socio‐economic status (coded “1” lowest, to “10” highest); education (1 = high school and below, 4 = postgraduate).

Abbreviations: ST, strong‐ties; WT, weak‐ties.

3.2. Societal Moderating Effects

We hypothesized that the impact of ST or WT rationality on dependent variables would be strengthened by the corresponding ST or WT social ecological niche of the responding group. As shown in Table 5, we found two significant moderating results related to H4a and H4e, while moderating effects for H4b, H4c, and H4d were not supported when comparing Han‐Chinese and White‐Australians. The result of H4a was contrary to our hypothesis—the impact of STR on PS was weaker (rather than stronger as hypothesized) in the Han‐Chinese cluster, compared with the White‐Australians cluster (β = −1.24, p < 0.001, Model 6; see Figure 1). As expected, the impact of WTR on PHB was stronger in the White‐Australians cluster than in the Han‐Chinese cluster (β = 0.72, p < 0.05, Model 10; Figure 2), supporting Hypothesis H4e.

TABLE 5.

Interaction of Rationality and Society Groups on Pandemic Outcomes.

	Model 6		Model 7		Model 8		Model 9		Model 10
	Public stigma		Help‐seeking ST		Personal‐care behaviour		Help‐seeking variety		Public health behaviour
Dependent variable	Coeff.	SE	Coeff.	SE	Coeff.	SE	Coeff.	SE	Coeff.	SE
Intercept	1.39***	0.38	2.27***	0.36	1.97***	0.45	6.34**	2.06	2.29***	0.58
Age	−0.02	0.00	−0.25***	0.00	−0.01	0.00	−0.05	0.01	−0.02	0.00
Gender	−0.08*	0.05	−0.01	0.06	−0.03	0.06	0.04	0.22	0.02	0.06
Education	−0.15***	0.02	−0.00	0.03	0.03	0.03	0.07	0.11	0.06	0.03
SES	−0.04	0.01	−0.13**	0.02	−0.20***	0.02	−0.13	0.06	0.01	0.01
COVID‐19 positive	−0.03	0.19	−0.00	0.16	−0.06*	0.21	−0.02	0.77	0.03	0.26
ST rationality	0.43***	0.05	0.18*	0.07	0.35***	0.08	0.19***	0.17	0.20***	0.05
WT rationality	−0.02	0.04	0.03	0.05	0.12*	0.06	−0.02	0.28	0.09	0.06
Han‐Chinese/White‐Australians	0.64**	0.25	0.31	0.36	0.48	0.41	−0.56*	1.52	−0.69*	0.41
ST Rationality × Han Chinese	−1.24***	0.05	−0.03	0.08	−0.38	0.09
WT Rationality × White Australians							0.17	0.32	0.72*	0.09
N	573		573		573		573		573
F	32.11***		22.49***		15.13***		22.85***		7.64***
Adjusted R 2	0.36		0.25		0.21		0.26		0.15

Note: *p < 0.05, **p < 0.01, ***p < 0.001. Standardized coefficients are provided; s.e. = standard error; age in years. All models had a sample size of 573, comprising Han‐Chinese (N = 295) and White‐Australians (N = 278). Models 6–8 treat Han Chinese as the focal moderator (Han‐Chinese = 1; White‐Australian = 0). Models 9–10 reverse the coding (White‐Australian = 1; Han Chinese = 0), so effects pertain to White‐Australians.

FIGURE 1.

Impact of Strong‐ties Rationality on Public Stigma.

FIGURE 2.

Difference of Societal niche on the impact of Weak‐ties Rationality on Public Health Behaviour.

Even though we assessed societal moderating effects between a pure ST niche (Han‐Chinese society) and a pure WT niche (White‐Australians society), we also performed a series of post hoc analyses to see if the two Malaysian clusters (with a mixed ST‐WT niche) also showed moderating effects on the above relationships. The results of these additional moderation regressions can be found in Supplementary Tables S7–S11. In sum, we found that the strength of STR and WTR on health behaviours did not significantly differ between Han‐Chinese and Chinese‐Malaysians. Chinese‐Malaysians and Malay‐Malaysians significantly differed in their relationship between STR on HS‐V and HS‐ST. Between Malays and White‐Australians, the impact of STR on PS was weaker among Malays, while the impact of WTR on HS‐V was stronger among the Malays. Between Chinese‐Malaysians and White‐Australians, the impact of STR on PS and that of WTR on PHB were both weaker among Chinese‐Malaysians.

4. Discussion

This study aims to test STWTR theory in different cross‐cultural settings, testing whether ST and WT rationalities predict variations in health behaviour during the COVID‐19 pandemic. We predicted main effects of STR and WTR on public stigma, health behaviours, preference for support networks, and varieties of help‐seeking of four societal groups that fall on a spectrum of ST and WT ancestral niches–Han‐Chinese, Chinese‐Malaysians, Malays‐Malaysians, White‐Australians. The moderating effects of these four societies on the likelihood of these outcomes were also explored.

4.1. Main Effects

Consistent with our predictions, main effects analysis revealed that STR, relative to WTR, is a better predictor of public stigma, help‐seeking preferences for the ST network, and personal care behaviours. We also found that WTR, relative to STR, is a better predictor of adopting public health practices. Thus, we found support for almost all the predictions based on STWTR theory for the effects of ST and WT rationalities on pandemic‐related behaviours.

The only hypothesis not supported was the main effect of WTR on the variety of help‐seeking behaviours. Contrary to our prediction, WTR was not significantly related to the help‐seeking variety, while STR was. This unexpected finding may be attributable to the framing question of the help‐seeking scale, which states, “If you were facing a personal or emotional problem…” This question could have inadvertently triggered the concern of burdening intimates with one's problems. Discomfort in receiving such social support is known to show varying sensitivity across cultures (Miller et al. 2017). Participants sensitive to this issue may seek help from their WT network when they are compelled by concerns of STR not to burden intimate others with their personal problems. This concern would have reduced the difference in varieties of help‐seeking between ST and WT rationalities.

4.2. Societal Moderating Effects

Through moderation analysis, we found that the impact of STR on public stigma was weaker (rather than stronger as predicted) in the Han‐Chinese cluster, compared with the White‐Australians cluster. We also found a significant difference in moderating effects across the ST versus WT ancestral niches, as evidenced by a stronger relationship between WTR and public health behaviours among the White‐Australians relative to both Han Chinese and Chinese Malaysians. In moderating effects, we found some anomalies that can be explained by the theory of STWTR.

4.2.1. STWTR and Stigma

Contrary to our expectations, the impact of STR on public stigma was weaker (rather than stronger) in the Han‐Chinese cluster, compared with the White‐Australians cluster. For an explanation of this contradictory finding, we integrate evolutionary psychology (Kurzban and Leary 2001) with STWTR theory, which decomposes culture into three components—the phenomenon, rationality, and ancestral niche.

4.2.2. The Phenomenon—Stigma

There are many types of stigmas; our investigation focused on disease‐related stigma, namely blaming and rejection of people infected with COVID.

4.2.3. Rationality

Contagious diseases may present a particular challenge to ST communities. According to evolutionary psychology (Kurzban and Leary 2001), when “members of a social species spend time in proximity to one another, a critical problem that must be solved is how individual members can avoid or fight off the parasites that are communicated from one host to another” (p. 197). Thus, the concern of STR to reduce parasitic infection in close‐knit groups may contribute to parasite‐related stigma. This hypothesis is supported by our finding of a significant main effect for the relationship between STR and disease‐related stigma.

4.2.4. Ancestral Niches

Concerning stigmatizing the pathogen‐carriers, there may be a tension between ST‐C (a communal factor of ST Rationality pertaining to caring and empathy for members of the in‐group) and ST‐A (an authoritarian factor of ST Rationality that ensures group survival at the expense of individuals) (Ting, Choo, et al. 2026). Although the current cross‐cultural design could not reveal the two latent factors of STR, the moderation analysis found that the relationship between STR and public stigma is weakened in the ST societies (all Asian groups), suggesting a possible mitigating effect due to the tension between ST‐C and ST‐A.

To the extent that COVID‐19 does not always manifest with observable symptoms, it may not tip the balance between ST‐C and ST‐A toward exclusion of infected individuals in ST societies; conversely, concealability of the disease symptoms may allow the caring component of STR to mitigate the stigmatization of people associated with COVID. By contrast, to the extent that stigmatization in WT societies has traditionally relied on abstract categories (pagans, barbarians, retarded persons, etc.), a diagnosis of COVID‐19 suffices to cue fitness threats to activate the antiparasitic defence mechanism of stigmatization. This is a plausible explanation for why STR scores showed a weaker association with public stigma in the three subgroups from Asian countries (Han‐Chinese, Chinese‐Malaysians, Malays‐Malaysians) in comparison to White‐Australians, due to the caring factors embedded under STR (Ting et al. 2023).

To the extent that COVID‐19 does not always have visible symptoms, it may not tip the balance toward exclusion of infected individuals in ST societies in which concealability of the disease may allow the caring component of the ST rationality to mitigate the stigmatization of people associated with COVID. Conversely, to the extent that stigmatization in WT societies has traditionally relied on abstract categories (pagans, barbarians, retarded persons, etc.), a diagnosis of COVID‐19 suffices to cue fitness threats to activate the antiparasitic defence mechanism of stigmatization. This explains why STR scores showed a weaker association with public stigma in the three subgroups from Asian countries (Han‐Chinese, Chinese‐Malaysians, Malays‐Malaysians) in comparison to White‐Australians, due to the caring factors embedded under STR (Ting et al. 2023).

4.2.5. Help‐Seeking Discomfort Within ST Societies

The absence of moderating effects on the relationship between ST‐WT rationality and help‐seeking behaviours could be attributed to the issue of discomfort in social support that the help‐seeking scale has inadvertently introduced. Kim et al. (2008) found that Asians (primarily Chinese, Korean, Japanese) and Asian Americans show significantly less use of social support from close others, such as friends and family, compared with European Americans, due to relationship concerns of the Asians not to burden or disrupt interpersonal harmony with their personal problems. Importantly, Miller et al. (2017) found that the difference in sensitivity to the discomfort in seeking social support did not vary along the divide of collectivism (having roots in the ST ancestral niche) versus individualism (having roots in the WT ancestral niche, see Schulz et al. 2019).

Consistent with the findings of Miller et al. (2017), our post hoc analysis suggests that discomfort in help‐seeking is a component of ST rationality that varies within the ST ancestral niche (Han‐Chinese, Chinese‐Malaysians, Malay‐Malaysians), instead of along the divide between ST and WT ancestral niches. Thus, future studies should control the sensitivity to discomfort in seeking social support when assessing the relationship between STWTR and help‐seeking preferences.

4.3. Implication for Cultural Psychology

One major contribution of the STWTR framework as an explanatory model of culture is that it allows us to examine the match (ST vs. ST; WT vs. WT) and mismatch (ST vs. WT; WT vs. ST) between rationality and ecological niche. Preliminary findings suggest that rationality may function optimally in a society with a matching ancestral niche. Thus, the relationship between WT rationality and public health practices is relatively stronger in WT society; the impact of ST rationality on public stigma is mitigated in ST societies. Conversely, there is no mitigation of the effect of ST rationality on stigma in a mismatching WT society (the White Australians). This finding suggests the possibility that in a mismatching ecological niche, the internal checks and balances of the ST rationality (caring for versus exclusion of the intimate other) may be lost, rendering the antiparasitic defence mechanism of stigmatization less flexible.

Contrary to the universal claim of the public health protocol that has been propagated by WHO for COVID prevention and implemented by all governments across the globe, we found the effect of WTR on these practices to be stronger in a WT society relative to ST societies. This set of findings suggests that outside WT societies the effect of modern (WTR‐based) public health practices, even when propagated globally, may be compromised by local ST cultures. A case in point is the Liangshan Yi in China. Recently, two studies of the HIV/AIDS perception in Liangshan (Ting, Choo, et al. 2026) revealed that due to the incompatibility between the STR of the local Yi population and the WTR of modern Western medicine, implementation of the WHO public health policies for prevention and control of HIV/AIDS in the region has been an ongoing challenge for the Chinese government.

What turned out to be universal is the effect of STR on self‐care behaviours that holds across all societies with no significant variations in strength. Note that personal care is not group‐focused but self‐focused health behaviours and self‐care. When it comes to relationality, the self is arguably the nearest and dearest of all the intimate others who fall within the zone of concern for STR. In addition to shedding some light on STR‐related practices, our analysis has revealed nuanced similarities and differences among ethnic groups across the two Asian countries (China and Malaysia). This set of findings fills a vacuum in psychology—WEIRD cultural traits associated with WT rationality have been well investigated and documented, but cultural traits associated with ST rationality in the non‐WEIRD majority world have been insufficiently investigated and imprecisely measured (Muthukrishna et al. 2020).

4.4. Limitations and Future Directions

Since the measurement for STWTR was developed during the COVID‐19 pandemic, the scales tapping STWTR may need to be updated in the post‐pandemic era. Due to the cultural invariance requirement for cross‐cultural analysis, the latent factors of measures underpinning STR and WTR were not revealed in this study. Future analysis could consider factor analysing scales for STWTR within each culture group and comparing the structures across all groups before determining the most consistent structure for STWTR. In both the previous studies (Ting et al. 2023; Yeh et al. 2022) and the current study, the reliability of the WTR subscale is consistently modest (Cronbach alpha = 0.62). Future studies should consider revising items of the WTR subscale to increase its reliability.

As scalar measurement invariance was not established, the mean score difference on major variables could not be compared across groups in this study. Future study could further test the societal difference in the scores of public stigma and public health behaviours based on relevant theory and measures. Our Help‐seeking preference scale guiding question narrowed the scope of help‐seeking to “personal and emotional problems”. Future studies can frame the survey question in more general terms such as, “When you need help during the pandemic, how likely are you to seek help from the following sources of support?” This re‐framing captures a general tendency in help‐seeking that may vary across cultures.

Lastly, our four‐sample, cross‐cultural analysis has limited generalizability. As advocated by Smith and Bond (2019), future studies need to extend the measurement and prediction of STWTR‐associated cognition, motivations, and behaviours to many more societies, especially those societies typically neglected in cross‐cultural work, for example, Middle Eastern, African, and Latin American.

5. Conclusion

This study on rationality and pandemic‐related outcomes across four societies yielded several significant findings and implications. It has demonstrated the heuristic value of STWTR theory as an explanatory model which decomposes culture into three units of analysis—rationality, ecological niche, and behaviour—enabling an examination of the match or mismatch among these cultural components in any society. STWTR provides a promising model of culture for international researchers to apply in examining other behaviours across diverse societies.

Author Contributions

Rachel Sing‐Kiat Ting: conceptualization, project administration, funding acquisition, writing – original draft, writing – review and editing, data curation, investigation, resources, methodology. Yi‐Fan Chen: investigation. May Kyi Zay Hta: project administration, investigation, methodology, software, formal analysis, writing – original draft, writing – review and editing, visualization. Louise Sundararajan: conceptualization, methodology, writing – original draft, writing – review and editing, supervision. Michael Harris Bond: supervision, writing – original draft, writing – review and editing. Jane Terpstra‐Tong: formal analysis, data curation, writing – review and editing, conceptualization, validation, writing – original draft. Zhong‐Yao Xie: investigation. Kuang‐Hui Yeh: investigation, data curation, writing – original draft, writing – review and editing.

Funding

This work was supported by Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, SED 0000‐55.

Ethics Statement

Ethics approval for this study was obtained from the first author's institution, Monash University Human Research Ethics Review Committee. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee at Monash University and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Consent

Informed consent was obtained from all individual adult participants included in the study.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: Measurement Invariance.

Table S2: Comparison of Main Effects on Public Stigma Across Three Samples.

Table S3: Comparison of Main Effects on Help‐Seeking from ST Network across Three Samples.

Table S4: Comparison of Main Effects on Personal Care Behaviour across Three Samples.

Table S5: Comparison of Main Effects on Help‐Seeking Variety across Three Samples.

Table S6: Comparison of Main Effects on Public Health Behaviour across Three Samples.

Table S7: Interaction of Rationality and Society (Han Chinese versus Chinese Malaysians) on Pandemic Outcomes.

Table S8: Interaction of Rationality and Society (Malays versus Chinese Malaysians) on Pandemic Outcomes.

Table S9: Interaction of Rationality and Society (Malays versus Han‐Chinese) on Pandemic Outcomes.

Table S10: Interaction of Rationality and Society (Malays versus Australians) on Pandemic Outcomes.

Table S11: Interaction of Rationality and Society (Chinese Malaysians versus Australians) on Pandemic Outcomes.

Appendix 1: Measurement items used in the final analysis.

Appendix 2: Measurement Invariance.

Data Availability Statement

The dataset has been deposited on the Open Registry platform (https://data.mendeley.com/datasets/2xxvg6xzgf/1) and is available for public access.