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Abstract

Inequalities that emerged during COVID-19 pandemic highlight the need to examine parent constraints in their decision-making around work and early childhood education and care (ECEC). This paper draws on conjoint survey data from a representative sample of 976 parents from the four largest Canadian provinces to examine the trade-offs parents made regarding their child’s care during the pandemic. Demographic differences in parental income, employment status, and having a child with special needs shaped childcare preferences in different ways. Our analysis finds that the most important factor in parent decision-making was type of ECEC (with a strong preference for licensed arrangements), followed by choices related to health and safety during the pandemic. The conclusion considers policy implications, including the need for more targeted and inclusive approaches that address the varying needs and circumstances of parents to enhance the overall quality and accessibility of care services post-pandemic and beyond.

Keywords

child care family policy conjoint parental preference

Introduction

The onset of the COVID-19 pandemic dramatically disrupted the lives of parents and children around the world. As with other services, many early childhood education and care (ECEC) facilities—including both home- and center-based care—were forced to close their doors as governments urged people to stay home and instituted widescale shut-downs. With closures to ECEC facilities, parents faced having to juggle working from home while also caring for young children or quitting their jobs and losing their income (Calarco et al., 2020; Ruppanner et al., 2021). Others—particularly those in essential jobs—had to figure out temporary care arrangements while they continued to work in person.

As economies first began to reopen in the summer of 2020, parents had new concerns as they considered sending their children back into care environments deemed potentially unsafe only months earlier. In largely privately delivered ECEC systems such as the United States (US) and Canada, however, even in the best of times parents face constrained ECEC decisions (Davidson et al., 2022). Care tends to be expensive, with limited access to government subsidies for low-income parents. As well, it varies in quality (Bassok et al., 2016), and availability can be scarce, particularly in lower-income neighborhoods (Macdonald, 2018; Malik & Hamm, 2017).

In the context of the COVID-19 pandemic, parents’ decisions regarding ECEC environments became more complex as these sites became both sites of care and sites of public health, as they attempted to mitigate the spread of the COVID-19 virus (Calarco & Anderson, 2021). Some interventions were government-led (e.g., requiring ECEC centers to reduce capacity in the early phases of the pandemic, or requiring staff to mask indoors). Others were privately organized, with providers messaging new protocols to parents to keep staff and children safe. These measures included actions such as enhanced cleaning schedules, strict protocols around allowing sick children to return to care, and masking for staff (Friendly et al., 2020).

How parents reacted to and integrated these new public health measures into their ECEC preferences and decisions is unclear. While anecdotal reports suggest some parents tried to “make do” with children at home (Edwards & Snyder, 2020; Gillis, 2020), other parents did not have such options available. In the context of schools, recent research has found that parents held highly heterogenous views as to school-based public health initiatives to mitigate COVID-19 (Calarco & Anderson, 2021), with differences driven by sociodemographic characteristics such as gender, level of education, and political affiliation.

In this study, we rely on the case of Canada to probe parent preferences for ECEC care during the pandemic, including public health measures designed to mitigate the spread of COVID-19. Surveying parents from four Canadian provinces—British Columbia, Alberta, Ontario, and Quebec—we use a choice-based conjoint design to understand parental decision-making and care preferences in the wake of the COVID-19 pandemic. The findings of our study reveal that, on aggregate, even amidst public health crises, licensing remains the primary preference among most parents, reinforcing past research including Davidson et al. (2022). However, in the context of the pandemic, our findings also suggest that parents exhibited a stronger inclination towards assessing childcare options based on health and safety policies over and above the quality of interactions provided to their children.

However, we also know from extant research that parents were disproportionately impacted by the COVID-19 pandemic, resulting in increased levels of stress among other concerns (Brown et al., 2020; Gassman-Pines et al., 2020; Prime et al., 2020; Schmeer et al., 2023). While government policies such as the Canada Emergency Response Benefit (an income-replacement for parents whose employment was affected during the pandemic) helped to smooth some of the short-run economic impacts of the pandemic, the experiences of job loss, disease burden, and childcare burdens were felt unequally in the population (Gromada et al., 2020; Kalil et al., 2020). This study aims to investigate the embedded heterogeneity of parent preferences for care using a latent profile analysis (LPA) to construct profiles of parent choice, based on the individual utility models generated by parent decisions in the conjoint survey design. We identify eight profiles of parent choice and explore demographic factors that correlate with those preferences.

Our study contributes to a growing body of literature that explores the heterogeneity of parent preferences, and how these preferences are shaped by sociodemographic backgrounds and experiences. Beyond this, our results highlight what parent preferences for care are in the midst a public health crisis, and how public health measures are weighed in relation to personal preferences and logistical constraints.

Background—Parental Decision Making Around ECEC

Parents face complex decisions regarding the type of care they select for their young children. This is particularly true in market-based ECEC systems, such as the US and Canada, where care quality can vary significantly (Bigras et al., 2010), and where supply is often constrained such that parents must make trade-offs between cost, quality, availability, type of care, and a host of other factors (Cryer & Burchinal, 1997; Huff & Cotte, 2013). Parents are often expected to act as the arbiters of quality in the selection of a care environment, despite the fact that research has found that parents have difficulty discerning what a high-quality ECEC setting looks like (Bassok et al., 2018; Zellman & Perlman, 2006). While increasing information availability to parents—such as publishing information about dangerous incidents in ECEC settings, providing parents with plain-language overviews of licensing requirements, or through the availability of quality review systems such as the Quality Rating and Improvement System (QRIS) or Step Up to Quality (SUTQ)—can assist parents in making ECEC decisions, important gaps remain, and many parents end up placing their children in low quality care environments (Burns et al., 2022).

True parental preferences for ECEC, and then ability of those preferences to be enacted, are themselves shaped by a host of structural and ideational factors. Parent decisions for ECEC are often heavily mediated by economic considerations including the cost of care, as well as access to government subsidies for lower-income families (Davidson et al., 2020, 2022; Lowe & Weisner, 2004; Rose & Elicker, 2010; Sandstrom & Chaudry, 2012). Preferences can be shaped by social dynamics such as the nature and range of parental networks, which can influence the information a parent has about what constitutes “quality” care (Burns et al., 2022; Torquati et al., 2011). Logistical constraints also undermine what ECEC options are available to parents. Many parents are limited to care environments located within walking distance or accessible by public transportation (Huff & Cotte, 2013). Meanwhile, chronic shortages of spaces in licensed care mean that parents and children living in licensed ECEC “deserts may have limited choice beyond unlicensed and lower quality options” (Hertzman, 2004; Malik & Hamm, 2017; Prentice, 2007).

At the best of times (e.g., not during a global pandemic), these factors—logistical constraints, informational constraints, and economic constraints—act together to affect the distribution of quality childcare such that children in lower socioeconomic backgrounds are much more likely to end up on lower quality care (Cloney et al., 2016). Childcare “deserts” are much more likely to be found in lower-income and racialized neighborhoods (Malik & Hamm, 2017; Prentice, 2007). Long waitlists for public subsidies for lower-income families present a barrier to accessing good quality center-based ECEC or regulated home-care spots. Furthermore, the complexity of regulatory oversight makes it hard for parents to understand the difference between a space that offers early years education as opposed to child minding. Past research has shown that parents may not know whether their child care provider is licensed or takes part in quality assessments (Mitchell, 2015). These distributional effects remain in place even in the universally subsidized systems (such as the province of Quebec), where research has shown that children from lower-income families and/or racial minorities more likely to end up in poorer quality care environments (Jenson, 2009). Given the known challenges regarding equitable access to good quality care, we are interested in understanding parent preferences for care during a crisis event, as well as the role that public health measures play in shaping parental preferences for care during the pandemic.

Parental Decision-Making in the Face of a Pandemic of Inequality

With the onset of the COVID-19 pandemic, parental decisions around their child’s ECEC became more fraught. Government rules around shut-downs and re-openings sent mixed messages about what was safe for children. For example, the Government of Ontario, Canada, shut down outdoor recreation facilities including children’s playgrounds in the first wave of the pandemic (DeClerq, 2020) and then again in April 2021 (although the subsequent parent backlash to the latter closure led to a quick reversal by politicians; Wilson, 2021). Research in the US and elsewhere that tracked the effects of school and ECEC closures on parents’ and particularly mothers’ mental health in the wake of ECEC and school disruptions found increased stress, anxiety, and frustrations with their children (Calarco et al., 2020; Johnston et al., 2020; Ruppanner et al., 2021). In the context of COVID-19, sending one’s child(ren) back into a care environment meant opening bubbles and exposing children (and therefore families) to the potential transmission of the COVID-19 virus.

These potential risks were not experienced equally, however. The disease burden of COVID was disproportionately experienced in lower income and racialized neighborhoods, varying the relative risks of transmission by neighborhood. Parents who worked front-line jobs in healthcare and elder care, food service preparation and delivery, warehousing and supply-chain management, and other similar jobs also faced risks outside the home, as congregate work environments were frequently sites of outbreak (Do & Frank, 2021; Nguyen et al., 2020). Meanwhile, families living in multi-generational households may have felt more risk-averse, as it became increasingly clear that morbidity and mortality associated with COVID was particularly acute among older generations or those with pre-existing health conditions (Lithander et al., 2020; Treskova-Schwarzbach et al., 2021). As such, these loci of inequality potentially shaped which features of ECEC mattered to parents during the pandemic, and bear considering in the study of childcare preferences.

Case Selection and Methods

This study surveyed parents across four provinces—British Columbia, Alberta, Ontario, and Quebec—in Canada in December 2020. These cases were chosen because the provinces have the largest populations in Canada, and because the governments in those provinces enacted reasonably varied policy approaches regarding child care and other services during the pandemic (Friendly et al., 2021). The case of Canada offers a good opportunity to investigate variation in parent decision-making regarding ECEC services during the COVID-19 pandemic. In Canada, the ECEC regulatory and policy framework falls under the jurisdiction of the subnational (provincial and territorial) order of government. While there are important similarities in policy regimes across provinces—for example, all provinces allow for some portion of the child care sector to remain unlicensed (White et al., 2019)—there are also key differences, such as in the design of the public subsidy systems for lower-income parents, and the amount of public investment in the provision of child care services. In the province of Quebec, the provincial government began investing in ECEC as public infrastructure in 1997, with the launch of its $5/day child care program (Burlone, 2022), increasing to $9/day currently. While issues have emerged over time related to quality and access (particularly for lower-income families; Jenson, 2009), we observe much greater ECEC utilization by parents in Quebec because the province has established an ECEC regime that is supply-focused, generally affordable, and more accessible to parents than in the rest of Canada (see Table 1 below).¹

Table 1.

ECEC Policy Environment by Province.^a

	BC	Alberta	Ontario	Quebec
% children 2–4 in formal ECEC	55%	43%	47%	73%
% mothers in workforce (youngest 0–5)	73%	65.9%	68.5%	79.2%
Per child government spending on ECEC	$3050	$2377	$2972	$8676

^aData compiled based on the provincial snapshots provided through the Early Education Report 2020.

Among the four provinces, a demographically representative panel of 1124 parents was collected by Maru/Blue, a survey firm based in Toronto. The survey sample was reasonably representative of the parent population in each province, based on income, education, ethnic/racial background, urban/rural residency, and other sociodemographic characteristics. The participants completed the survey online using the Qualtrics platform. A total of 148 participants did not complete the conjoint survey, resulting in a final sample size of 976.

The survey was conducted across the four largest provinces, with sampling sizes determined relative to the provincial population. As such, the largest percentage of participants (40.4%) were in Ontario, followed by Quebec (24.8%), and then Alberta and British Columbia (with 17.5% and 17.3% of the survey sample, respectively). Table 2 provides the demographic characteristics of participants for the sample across each province. The survey is reasonably representative of the parent population of the provinces included. In this sample, close to half (51.9%) of the families fell above the average income cut off. A total of 90.6% of parents were either married/engaged or were in a civil/common law partnership, similar to the reported rate of 83% of parents with at least one child under 18 in 2021 Census survey (Statistics Canada, 2022). Between 20 to 30% of the participants were born outside the country (depending on province of residence). Nearly half of the sample reported receiving an ECEC subsidy from the government.² However, the participants in this sample are overrepresented in three characteristics, including: (1) a higher representation of women among participants (65.5%); (2) a greater proportion of participants identifying with a non-white ethnic or racial group (40.1%); and (3) a higher level of education among participants compared to the general parent population. The overrepresentation of women respondents is commonly found when doing research on early childhood education, as women are more likely to be the primary caregiver and assume much of the decision-making related to childcare (Horne & Breitkreuz, 2018). Meanwhile, assessing the representativeness of the ethnic and racial variable is a bit more challenging as these rates do vary considerably by region. While 25% of the Canadian population identifies as a racial minority, according to publicly available data from CANSIM (the Canadian Socioeconomic Information Management database), approximately 39% of parents with young children in Ontario and British Columbia identify as a racial minority, while the rates in Alberta and Quebec are 31% and 19%, respectively. Within the sample of parents, East Asian and South Asian racial backgrounds were the second and third largest categories after White (which corresponds with Canadian census data). Finally, we note overrepresentation in levels of education. In our survey sample, between 57% of parents (in Quebec) and 68% of parents (in Ontario) report having a university education or above, only 35% of parents in Canada are similarly educated (according to 2016 census data). These results (along with the racial characteristics of the sample) may be the result of over-sampling from large Canadian cities (such as Toronto, Montreal, and Vancouver).

Table 2.

Respondent Demographics (N = 976).

Demographic Characteristics	Alberta (N = 171)		BC (N = 169)		Ontario (N = 394)		QC (N = 242)
Demographic Characteristics	% Sample	N	% Sample	N	% Sample	N	% Sample	N
Child in special education (yes)	16.3	166	10.5	162	16.9	391	16.5	231
Race (Bipoc¹)	40.1	167	47.5	164	47.4	384	33.5	230
Parent gender (male)	34.5	168	43.3	164	34.9	392	36.3	232
Language of survey
English	100.0		99.4		99.7		32.2
French	0.0	171	0.6	169	0.3	394	67.8	242
Born out of Canada (yes)	25.0	168	25.5	165	29.6	392	20.9	234
Marital status (partnered)	90.6	171	89.3	169	85.3	394	83.9	242
Income (higher)	51.9	160	53.5	157	47.6	372	43.9	228
Subsidy (yes)	23.8	80	52.9	87	40.4	188	59.7	154
Education (University or above)	60.1	168	66.0	162	68.4	389	57.0	235
Employment
Full-time	67.3		71.6		71.8		76.4
Part-time	12.9	171	15.4	169	9.1	394	9.9	242
Homemaker	13.5		11.2		11.4		9.9
Other	6.4		1.8		7.6		3.2

¹Note. BIPOC as a descriptive category does not reflect the considerable diversity of racial and ethnic backgrounds of parents.

Measures

Conjoint Design

To assess parental preferences regarding new public health and regulatory measures in child care arrangements in response to the COVID-19 pandemic we developed a conjoint survey. The conjoint attributes selected to reflect the real considerations parents faced when choosing an ECEC setting during the COVID-19 pandemic. Safety and health factors were frequently discussed in the media, endorsed by political leaders, and incorporated into care providers’ reopening plans. They included policies on sick children attending care, social distancing, use of masks, and cleaning procedures. For the non-COVID-related attributes, factors were selected based on prior research (Davidson et al., 2022).

Conjoint design is a choice-based method where survey participants are asked to make decisions between discrete options that vary randomly on key attributes. In each decision scenario, the conjoint design requires participants to make trade-offs between the different options in front of them. These decisions reflect internalized but often competing preferences that individuals hold; for instance, a parent may prefer that providers are highly educated, and that care be close to home. However, they also may be willing to trade-off highly educated providers in favor of care that is close to home (making the latter preference stronger than the former). The discrete choice model pushes survey participants to engage in trade-off behaviors between even the attributes they care the most about, allowing researchers to estimate the relative impact of each attribute on final decisions and preferences (known as part-worth utilities) for each individual participant. Unlike other models which assume preferences are the same across all respondents, the Hierarchical Bayesian (HB) estimator used to estimate part-worth utilities allows for the estimation of individual-level preferences (coefficients), which in turn enable us to group or analyze respondents based on their preferences.

In this study, we probed parent preferences along three core features of ECEC care: (1) quality considerations related to oversight and regulations and provider-child interactions (licensing regime and caregiver-child interactions); (2) logistical constraints (availability of care); and (3) COVID-19 measures (i.e., health measures related to cleaning and masking, sickness policies, and social distancing). The levels were clearly stated and reflected trade-offs parents were asked to make when choosing ECEC during the pandemic (see Table 3).

Table 3.

Conjoint Attributes and Levels.

Attribute	Level 1	Level 2	Level 3
Type of care	Licensed child care center	Licensed home child care	Unlicensed home child care
Safety measures	Deep cleaning 2× per day, masks required	Deep cleaning 2× per day, masks recommended	Measures similar to pre-COVID
Health policy	Provider strictly enforces that children with runny noses stay home	Provider allows children with runny noses to attend
Social distancing	Children encouraged to physically distance	Children encouraged to reduce interactions with each other	Children interact fully together
Caregiver interactions	Caregiver engages my child in play and learning	Caregiver plays with my child	Caregiver supervises my child
Availability	Spot is available immediately	Spot is available in 2 weeks	Spot is available in 1 month

Building on existing research to understand conjoint preferences for care in general (Davidson et al., 2022; Leslie et al., 2000; Rose & Elicker, 2010), this study examines the trade-offs parents make, when prompted, when making decisions about their children’s ECEC settings, during the pandemic (e.g., the quality of ECEC, availability and health policies).

The conjoint design is useful to replicate the constraints that parents faced in deciding whether to utilize ECEC during COVID-19. Survey participants are placed in a simulated ECEC marketplace enabling us to then examine the choices and trade-offs that parents indicated they would make. We asked parents to imagine that widespread vaccination was still 9–12 months away, and that they were on a waitlist for an ECEC placement for their child and had been contacted by three different providers from which they could choose, with the additional option of selecting “none” of the choices for ECEC. Conjoint analyses were conducted in Sawtooth software. For more information about the description of the conjoint survey see Supplementary Appendix A.

Participant Characteristics

We collected the following child and family characteristics: province (British Columbia, Alberta, Ontario, and Quebec); marital status; parent gender (male or female); race (BIPOC or White); born outside of Canada; income (lower than the provincial average income); receiving subsidy (yes or no); education (university or above); employment (full-time, part-time, homemaker, other); employment location (not working, in person, from home); survey completion language (French or English); and having a child needing special education.

Data Analysis

Conjoint Utilities

A conjoint analysis encourages participants to weigh their preferences on some attributes against other attributes and to make trade-offs based on the discrete options available to them. Calculating individual preferences is based on the choices individuals make (or utilities). A model is constructed for each respondent based on these choices. Each level of an attribute is assigned a score (relative preference), called part-worth utilities. These utilities are estimated using a Hierarchical Bayesian process for each level of each attribute. Hierarchical Bayesian techniques use the choice patterns found in the whole sample and in individual participants to find the set of utilities that are most closely aligned with the choices made by both the individuals and the whole sample. This process requires many iterations of estimation that involves updating the whole sample estimates as the individual respondent estimates are updated.

Latent Profile Analysis and Associations with Parental Characteristics

Latent Profile Analysis (LPA) is used to identify unobserved groups based on continuous data, grouping similar parents based on the calculated probability of being in certain profiles. In the context of conjoint survey data, LPA is used to identify groups based on most-similar preferences as defined by their utility scores. R Software (Version 1.3.1093) and tidyLPA package was performed (Rosenberg et al., 2019) on the data. Model fit indices were produced, and an 8-group solution was selected as it had had the lowest log likelihood, AIC, and BIC (Table 4). In addition, entropy values were acceptable values above .8 (Clark & Muthén, 2009).

Table 4.

Model Fit Indices.^†

Profile	LogLik	AIC	BIC	Entropy	Min Prob	Max Prob	Min N	Max N
1	−12,955.78	25,983.56	26,159.36	1.00	1.00	1.00	1.00	1.00
2	−12,006.59	24,123.18	24,391.77	0.84	0.94	0.96	0.38	0.62
3	−11,592.26	23,332.51	23,693.89	0.83	0.90	0.94	0.31	0.35
4	−11,110.25	22,406.51	22,860.67	0.87	0.90	0.95	0.21	0.30
5	−10,772.08	21,768.16	22,315.11	0.88	0.91	0.94	0.16	0.26
6	−10,469.39	21,200.77	21,840.50	0.89	0.90	0.94	0.14	0.19
7	−10,287.82	20,875.63	21,608.15	0.90	0.90	0.95	0.11	0.18
8	−10,130.40	20,598.80	21,424.11	0.90	0.90	0.94	0.10	0.16
9	−9955.40	20,286.80	21,204.89	0.91	0.88	0.96	0.07	0.16

Note. ^† For each fit index, the model with the preferred number of groups is highlighted in bold.

We analyze each of the eight profiles identified in the LPA to assess the differences quantitatively and qualitatively in their revealed preferences, as indicated by the average part-worth utility scores for each profile group. To investigate differences in the demographic characteristics and ECEC experiences across the latent profile groups, we subsequently conducted a series of chi-squared tests. Statistically significant results were reported as a function of differences between groups.

Results

We present the results in two sections. First, we present the findings from the conjoint analysis. Specifically, we report the average utility scores for each attribute and within each attribute on parents’ ECEC preferences. Second, we present findings from the LPA. We document the different ECEC preferences of parents and then present findings on how the profiles are different across demographic characteristics and ECEC experiences.

Attribute Importance and Average Utility Scores of ECEC Preferences During COVID-19

The conjoint analysis generates both attribute and utility scores. Attribute scores (also called Attribute Importance scores) indicate the relative importance of each attribute as a measure of their weight on final decisions. These scores add up to 100 (but do not include the “None” option in their calculation), and thus represent the overall proportion by which different attributes or factors influence decision outcomes. Utility scores, by comparison, are generated for each level of an attribute; and are zero-centered and averaged across the sample (as such, the largest negative scores are associated with the least preferred option while the largest positive score is associated with the most preferred option).

The aggregate utility and attribute importance scores suggest parents in the survey are attuned to COVID-19 policies when making decisions around care (Table 5). Among parents, the most important attribute when selecting an ECEC setting for their child was the type of care (28.84), followed by the slate of COVID-19 health and safety considerations including Safety Measures (20.24), Health Policy (18.46), and Social Distancing (12.00). The two other metrics of care included—Caregiver Interactions and Availability—were the least influential attributes for parents making decisions about their child’s ECEC setting during the pandemic (at 11.34 and 9.12 in terms of their Attribute Importance scores, respectively).

Table 5.

Average Utility Scores Across All Participants.

Average Utilities (Zero-Centered Diffs)	Avg. Utilities	S.D.	Min	Max
Type	28.84	14.75	0.74	73.12
Licensed child care center	0.71	0.75	−1.15	2.88
Licensed home child care	0.39	0.43	−0.98	1.59
Unlicensed home child care	−1.10	1.00	−3.53	1.88
Safety measures	20.24	10.01	0.42	63.04
Measures similar to pre-COVID	−0.66	0.75	−2.53	2.15
Deep cleaning 2× per day, masks recommended	0.35	0.28	−0.60	1.12
Deep cleaning 2× per day, masks required	0.31	0.59	−1.56	1.96
Health policy	18.46	12.90	0.02	67.55
Provider strictly enforces children with runny noses stay home	0.41	0.73	−1.67	2.32
Provider allows children with runny noses to attend	−0.41	0.73	−2.32	1.67
Social distancing	12.00	7.90	0.21	44.84
Children interact fully together	0.02	0.57	−1.71	1.90
Children encouraged to reduce interactions	0.02	0.31	−1.00	1.00
Children encouraged to physically distance	−0.05	0.36	−1.11	1.13
Caregiver interactions	11.34	7.48	0.07	44.12
Caregiver supervises my child	−0.23	0.42	−1.53	1.07
Caregiver plays with my child	0.09	0.27	−0.71	1.02
Caregiver engages my child in play and learning	0.14	0.35	−1.04	1.22
Availability	9.12	6.12	0.42	47.82
Spot is available immediately	0.13	0.30	−1.04	1.09
Spot is available in 1 week	0.04	0.24	−0.76	0.89
Spot is available in 1 month	−0.17	0.29	−1.16	0.73
None	--	--	--	--
No care is preferred	−1.92	4.12	−7.66	7.07

Note. Bolded values indicate the highest proportion that is statistically significant.

On average, parents expressed a strong preference for licensed center-based care, while unlicensed home child care was generally not preferred. In terms of mask measures and cleaning protocols, parents, on average, indicated equal preference for masks being recommended or required (with a slight preference for the former over the latter). Similarly, parents, on average, preferred children with cold symptoms (e.g., a runny nose) to stay home during the pandemic. Regarding interactions during COVID-19, parents, on average, did not show a clear preference for whether their children should practice safe social distancing. Meanwhile, when considering non-COVID-19 specific attributes, parents exhibited clear preferences for ECEC settings where caregivers engaged their child in play and learning, rather than providing supervision only. In terms of availability of care, when parents expressed a preference, they tended to favor immediate availability rather than care that would be available within one month’s time.

Latent Profile Analysis

While we capture some important information about parent preferences during the COVID-19 pandemic, and their relatively strong attention to COVID-19 health and safety measures, we also know that aggregate utility scores can mask variability in preferences (Davidson et al., 2020). Therefore, an LPA was conducted on the utilities to capture “like” preferences amongst parents. We further conducted one-way ANOVAs to examine which groups significantly differ on the utility scores (Table 6). These latent profiles compare groups of parents by preference. Those with the most-similar preferences for care across the range of attributes are grouped together. This grouping allows us to analyze which aspects of ECEC matter to parents, and whether any group-level characteristics shape their preferences.

Table 6.

Utilities by Latent Profile Analysis.

	Profile Mean (SD)
Utilities	P1 (N = 117)	P2 (N = 122)	P3 (N = 160)	P4 (N = 101)	P5 (N = 132)	P6 (N =124)	P7 (N = 121)	P8 (N = 99)	Total (N = 976)
Licensed daycare/preschool	1.20 (0.47)^b	−0.04 (0.50)^d	0.64 (0.37)^c	0.29 (0.44)^d	1.72 (0.46)^a	0.23 (0.50)^d	1.29 (0.46)^b	0.19 (0.42)^d	0.71 (0.75)
Approved family day home	0.51 (0.35)^b	−0.12 (0.34)^f	0.38 (0.25)^c	0.24 (0.28)^d	0.80 (0.32)^a	0.38 (0.36)^c	0.70 (0.34)^a	0.11 (0.36)^e	0.39 (0.43)
Unlicensed private provider/day home	−1.71 (0.49)^d	0.16 (0.61)^a	−1.02 (0.40)^d	−0.52 (0.49)^c	−2.52 (0.40)^g	−0.61 (0.62)^c	−1.99 (0.49)^f	−0.30 (0.52)^b	−1.10 (1.00)
Measures similar to pre-COVID	−0.30 (0.51)^c	0.22 (0.56)^a	−0.82 (0.40)^d,e	−0.90 (0.60)^d,e	−0.79 (0.51)^d	−0.99 (0.56)^e	−1.56 (0.47)^f	−0.01 (0.68)^b	−0.66 (0.75)
Deep cleaning 2x per day, masks recommended	0.34 (0.27)^c	0.12 (0.28)^d	0.46 (0.20)^b	0.32 (0.26)^c	0.33 (0.24)^c	0.36 (0.28)^c	0.55 (0.24)^a	0.31 (0.29)^c	0.35 (0.28)
Deep cleaning 2x per day, masks required	−0.04 (0.36)^e	−0.34 (0.42)^f	0.36 (0.33)^d	0.58 (0.43)^b,c	0.46 (0.37)^c,d	0.63 (0.47)^b	1.01 (0.36)^a	−0.30 (0.50)^f	0.31 (0.59)
Provider strictly enforces that children with runny noses stay home	−0.21 (0.42)^f	0.39 (0.44)^d	0.72 (0.30)^c	1.53 (0.34)^a	0.19 (0.37)^e	0.15 (0.42)^e	1.02 (0.44)^b	−0.65 (0.46)^g	0.41 (0.73)
Provider allows children with runny noses to attend	0.21 (0.42)^b	−0.39 (0.44)^d	−0.72 (0.30)^e	−1.53 (0.34)^g	−0.19 (0.37)^c	−0.15 (0.42)^c	−1.02 (0.44)^f	0.65 (0.46)^a	−0.41 (0.73)
Children interact fully together	0.53 (0.43)^a	0.06 (0.45)^c	0.33 (0.34)^b	−0.43 (0.41)^e	−0.22 (0.41)^d	−0.50 (0.43)^e	−0.23 (0.44)^d	0.62 (0.46)^a	0.02 (0.57)
Children encouraged to reduce interactions with each other	−0.14 (0.28)^c	−0.06 (0.30)^c	−0.16 (0.20)^d	0.15 (0.24)^b	0.20 (0.23)^b	0.28 (0.29)^a	0.15 (0.27)^b	−0.22 (0.27)^d	0.02 (0.31)
Children encouraged to physically distance	−0.40 (0.28)^d	0.00 (0.31)^b	−0.17 (0.21)^c	0.27 (0.26)^a	0.02 (0.27)^b	0.22 (0.31)a	0.09 (0.25)^b	−0.39 (0.31)^d	−0.05 (0.36)
Caregiver supervises my child	−0.25 (0.42)^b	−0.16 (0.46)^b	−0.02 (0.31)^a	−0.22 (0.40)^b	−0.22 (0.37)^b	−0.45 (0.46)^c	−0.24 (0.36)^b	−0.38 (0.43)^c	−0.23 (0.42)
Caregiver plays with my child	0.07 (0.31)^b,c	0.13 (0.32)^a,b	0.02 (0.23)^c	0.05 (0.23)^b,c	0.02 (0.24)^c	0.19 (0.28)^a	0.04 (0.23)^b,c	0.22 (0.28)^a	0.09 (0.27)
Caregiver engages my child in play & learning	0.18 (0.37)^a	0.03 (0.41)^b	0.00 (0.27)^b	0.17 (0.30)^a	0.20 (0.32)^a	0.25 (0.37)^a	0.20 (0.31)^a	0.17 (0.36)^a	0.14 (0.35)
Spot is available immediately	0.28 (0.31)^a	0.15 (0.38)^b	0.10 (0.20)^b,c	0.09 (0.27)^b,c	0.19 (0.27)^b	0.01 (0.34)^c	0.12 (0.24)^b	0.13 (0.32)^b	0.13 (0.30)
Spot is available in 2 weeks	0.04 (0.23)^c,d	−0.06 (0.29)^e	0.00 (0.18)^c,d,e	−0.04 (0.18)^e	0.14 (0.20)^a,b	0.18 (0.25)^a	0.07 (0.20)^b,c	−0.02 (0.26)^d,e	0.04 (0.24)
Spot is available in 1 month	−0.33 (0.31)^c	−0.09 (0.34)^a,b	−0.10 (0.20)^a,b	−0.05 (0.24)^a	−0.33 (0.25)^c	−0.18 (0.34)^b	−0.19 (0.22)^b	−0.11 (0.32)^a,b	−0.17 (0.29)
None	−2.66 (3.31)^c	−3.85 (3.01)^d	3.95 (3.41)^a	−2.26 (2.91)^c	−3.83 (2.46)^d	−3.87 (2.82)^d	−0.54 (3.01)^b	−4.50 (2.72)^d	−1.92 (4.12)

Note. When subscripts share the same letter, it indicates that there is no statistically significant difference between the profiles they represent.

A series of chi-squared tests of independence were conducted to examine the relationship between the profiles and demographic characteristics of parents; the associations are documented in Table 7 below with superscripts noting where statistically significant differences are found.

Table 7.

Demographic Differences Across Parent Profiles.

	% Distribution Within Profile (N)
Demographics	P1 (117)	P2 (122)	P3 (160)	P4 (101)	P5 (132)	P6 (124)	P7 (121)	P8 (99)	X ²	p
Province
Alberta	17.9^a,b	13.1^a,b	21.9 ^b	23.8 ^b	12.9^a,b	22.6 ^b	19.0^a,b	7.1^a	69.39	>.001
British Columbia	14.5^a,b	14.8^a,b	16.3^a,b	16.8^a,b	23.5^a,b	12.1^b	28.1 ^a	11.1^a,b
Ontario	34.2^a	42.6^a	41.9^a	44.6^a	43.9^a	41.1^a	38.0^a	35.4^a
Quebec	33.3^a,b	29.5^a,b,c	20.0^b,c	14.9^c	19.7^b,c	24.2^b,c	14.9^c	46.5 ^a
Child special needs	19.6^a,b	26.3 ^b	10.3^a	10.3^a,b	13.6^a,b	15.1^a,b	8.5^a	23.2^a,b	26.30	>.001
BIPOC	41.4	50.8	39.1	51.0	45.0	36.7	40.0	39.2	9.85	0.197
Parent: Male	36.9	41.3	31.8	32.3	39.4	43.1	31.9	36.4	7.26	0.403
Born: Out of Canada	26.8	32.0	24.5	30.3	19.7	22.3	26.1	28.3	7.27	0.401
Respond: French	22.2^a,b,c	26.2^c	11.3^b,d	6.9^d	9.8^b,d	19.4^a,b,c,d	9.1^b,d	35.4^a,c	54.88	>.001
Not partnered	20.5	16.4	11.9	8.9	11.4	9.7	9.1	21.2	17.19	0.016
Income: <Average	58.2^a	53.0 ^a	57.9 ^a	48.4^a,b	33.1^b	50.8^a,b	50.9^a,b	62.1 ^a	26.41	>.001
ECEC subsidy	42.9	46.9	41.2	30.6	43.2	49.2	47.2	62.3	12.52	0.085
Below BA	33.3	41.3	42.2	33.3	31.1	36.1	29.9	41.8	9.38	0.226
Employment
Full-time	76.1 ^a	72.1^a,b	55.6^b	73.3^a,b	83.3 ^a	79.0 ^a	67.8^a,b	74.7^a,b	49.62	>.001
Part-time	7.7^a	13.9^a	15.0^a	10.9^a	7.6^a	8.1^a	10.7^a	14.1^a
Stay at home	11.1^a,b	9.0^a,b	22.5 ^b	8.9^a,b	6.8^a	6.5^a	13.2^a,b	9.1^a,b
Other	5.1^a	4.9^a	6.9^a	6.9^a	2.3^a	6.5^a	8.3^a	2.0^a

Note. When subscripts share the same letter, it indicates that there is no statistically significant difference between the profiles they represent. Bolded values indicate the highest proportion that is statistically significant.

Decision Typologies of Parents in Market-Based Models of ECEC

Licensed Care Now (11.99%): These parents were responsive to the types of ECEC settings they selected for their children, preferring center-based care over than licensed home-based care, and not wanting unlicensed care. Notably, parents in this profile had the strongest preference for an ECEC space that was available immediately. Parents in this profile had the strongest preferences for children to fully play together compared to parents in other profiles. They also preferred providers who allowed their children to attend with runny noses and wanted educators who would engage in play and learning. A significantly higher proportion of these parents worked full-time than parents in a number of other profiles.

Unlicensed Care Now (12.5%): These parents were the least responsive to the types of ECEC settings they select for their child, and the only profile that had a positive preference for unlicensed, home-based care. Parents in this profile had the strongest preference for an ECEC setting that had cleaning and mask policies that were similar to pre-COVID and showed a clear aversion to centers with deep cleaning twice per day, masks required. A significantly higher proportion of parents in this profile had a child needing special education and had below average income. A significantly lower proportion of parents in this profile completed the survey in French.

Don’t Need Care So Don’t Care (16.39%): Parents in this profile did not appear to be attuned to any of the attributes, compared to other parents. Notably, parents in this profile said no to care. There was a significantly lower proportion of parents who worked full-time and had a child needing special education than parents in other profiles. There was a significantly higher proportion of parents who stayed at home (i.e., were homemakers), had below average income, and were from Alberta.

Minimize Risks Through Reduced Interactions (10.35%): Parents in this profile were not differentiated based on the importance they placed on type of care. Notably, this profile had the highest preference for stricter sick policies (i.e., children with runny noses staying home). A significantly lower proportion of parents in this profile were from Quebec and completed the survey in French, whereas a significantly higher proportion of parents in this profile were from Alberta.

Center Care with Good Staff (13.52%): Parents in this profile had the strongest preference for center-based care and strongest aversion to unlicensed home care. They also showed a strong aversion to waiting a month to access care. A significantly higher proportion of parents in this profile worked full-time than parents in several other profiles, whereas a significantly lower proportion of parents had below average income and were stay at home parents.

Peer and Educator Play, and Learning (12.70%): Parents in this profile had stronger preferences for caregivers who engaged their children in play and learning. They also showed preferences for children being physical distanced from one another. Significantly more parents in this profile worked full-time and were from Alberta than parents in other profiles, whereas a significantly lower proportion of parents were from British Columbia and were stay at home parents.

Licensed Care and COVID Cautious (12.40%): Parents in this profile had strong preferences for licensed care and the strongest preference for deep cleaning procedures (i.e., 2× per day, masks required) than any other profile of parents. A significantly lower proportion of parents in this profile had a child needing special education and were from British Columbia, whereas a lower proportion of parents in this profile were from Quebec.

Need Care and Normalcy (10.42%): These parents had the strongest preferences for providers who allow children with runny noses to attend a care setting and to have no physical distancing. They also preferred caregivers playing with their children and engaging them in play and learning. A significantly higher proportion of parents in this profile were from Quebec, completed the survey in French, and were below average income. A significantly lower proportion of parents in this profile were from Alberta.

Discussion and Conclusion

Prior to the COVID-19 pandemic, existing literature demonstrated that parents overwhelmingly prioritized licensing when selecting childcare services (Davidson et al., 2022). Results from this study reveal that this preference has persisted despite the many challenges and additional considerations brought about by the pandemic. The unwavering emphasis parents place on licensing underscores its fundamental importance in parental decision-making, regardless of context. This finding holds significant implications, particularly in light of the current shortage of high-quality child care spaces across Canada (Dhuey, 2024) and many other countries. As shortages persist, understanding and addressing parents’ preferences for licensed care becomes essential for informing the development of a responsive and effective child care system.

This study also found that the demographic profile of parents who did not express a preference for licensed care tended to include families with lower incomes and those with children who have special needs. This finding reveals a potential vulnerability within these families, as they may be more likely to opt for unlicensed home-based care, which has traditionally been more affordable than licensed options. The preference for unlicensed care among families with children with special education needs may reflect the perceived flexibility or accessibility that home-based care offers compared to center-based care. However, this trend also raises concerns about the accessibility of high-quality, licensed care for these families. The intersection of having a child with special education needs and a lower income suggests that financial constraints may limit these families’ access to licensed, quality services.

Another interesting finding was the significant variation in parental preferences for and aversions to pandemic policies. This variation is important to understand because while some parents strongly prefer policies that prevent sick children from attending, others may be more lenient. This variation has important implications for the implementation of early childhood education, as it highlights the challenge of meeting the diverse needs and desires of families. Additionally, ECEC services have the potential to serve as sources of information, educating parents on the benefits of these policies to promote more informed decision-making.

All parents care about keeping their children safe and well-cared for, whether in the context of a pandemic or not. Yet, what parents perceive as safe, what they consider to be attributes of quality, and what they value in the care provided is not universal and it is inherently constrained by the options available to them. During the COVID-19 pandemic, the options available to parents became much more limited (and in many cases disappeared entirely for at least a portion of time), and as care options reopened, parents faced much more complex decisions about what they considered to be safe, what they considered to be reasonable, and what they considered to be necessary.

We observe these considerations in the aggregate preferences of parents revealed in the conjoint survey, where we note the particular importance of health and safety measures (cleaning and masking, and stringent sickness policies for children) in parent preferences. On aggregate, these attributes of care are more influential for parent decision-making above care quality attributes and availability attributes. However, even in aggregate, there are indications of heterogeneity in preferences, as the relative strength of the aggregate preferences are relatively weak (insofar as the distance between most preferred and least preferred attribute level is reasonably small; see Table 2). As such, the results of the LPA present a much better look at discrete profiles of parent preference.

As we can observe in the profiles present in the LPA, parents differ across groups most dramatically on preferences regarding the health and safety metrics, and to a more moderate degree on licensing. Across all profile groups, parents prefer play or play/learning models of care (choosing away from supervision alone) and prefer care immediately. However, we know from the aggregate results that these are not the preferences driving parent choice (in terms of relative importance). Instead, parents are choosing based on the metrics of health and safety, making decisions about the relative importance of social distancing (more contentious), sick policies, and the mandatory masking of care providers.

Based on the demographic profiles, we note that parents across British Columbia, Alberta and Ontario had strong preferences for ECEC centers with COVID-19 safe health policies (in that they were most likely to appear in Profiles 1–4). In contrast, Quebec parents were much more likely to appear in Profile 5—the “Get Kids Back to ‘Normal’ (Not COVID Cautious)” profile. This desire for normalcy may be linked to external factors; compared to other provinces in December 2020, the Quebec government had much more stringent public health measures in place to mitigate the spread of COVID-19 (Breton et al., 2021). As well there was a much earlier dialogue about the importance of a return to normalcy for children, and Quebec was the only province in Canada that opened schools (on a voluntary basis) in the spring of 2020.

We see also observe the importance of family characteristics and demographics in shaping how parents respond to the various trade-offs present in the conjoint design. Participants who reported having children with special educational or developmental needs, for instance, appear to have a different set of preferences and needs that are more acute (see Profile 1 in particular). These parents likely faced greater pressures, in attempting to manage work and child care, and in the context of the survey—feel they need care immediately. These participants also appear more mindful of quality indicators and may be better versed in care quality considerations by virtue of the needs of their child(ren).

Meanwhile, the implications for licensed ECEC providers are that in the face of a public health crisis such as the COVID-19 pandemic, there is not necessarily an easy way forward in attempting to satisfy the highly divergent preferences of parents. While there is a need for these settings to address the duality of the safety-focused considerations (in an effort to keep both children and providers well and healthy), these goals may run up against parents’ principled beliefs about the importance of factors such as face-to-face interaction between caregivers and children, the importance of play-based learning based on children interacting together, or parents needs for stable and consistent care (e.g., not needing to keep their child home at every sniffle).

Beyond the immediate concerns raised by the pandemic, these findings suggest that ECEC providers may need to adopt flexible or tiered policy approaches to accommodate different family preferences while maintaining health and safety standards. Moreover, the variation in parental preferences underscores the importance of ongoing communication between parents and providers to ensure that policies are responsive to changing parental concerns and public health guidelines. Future research could also explore how these varying preferences influence overall satisfaction with and trust in ECEC services, as well as the long-term impacts on child health and development.

ECEC services offer a unique opportunity as early intervention points—not only for supporting children’s development but also for providing parents with valuable information about public health guidelines. These settings are a critical access point for families, making them an ideal platform for increasing public awareness and understanding of the importance of pandemic policies. By leveraging the trusted relationships that often exist between families and ECEC providers, these services can play a pivotal role in shaping informed attitudes and behaviors around health and safety measures. It is essential, therefore, that ECEC settings be actively considered in efforts to enhance public awareness and compliance with health and safety policies.

Limitations and Future Directions

This study has noteworthy limitations. First, while we identified associations between parents’ demographic characteristics and their ECEC preferences, this research did not collect qualitative data to explore how these demographic characteristics shaped their experiences. Future research should consider conducting mixed-methods studies to address this gap. Additionally, the cross-sectional nature of this study limits our understanding of how preferences change over time and what factors shape preferences and cause parents to make these decisions. This is particularly relevant as Canada has implemented a new child care policy that reduces parental costs and increases demand. Therefore, future research should investigate the effects of such policy implementations on parental preferences. Finally, although the conjoint method is designed to approximate parents’ real-world decision-making, it relies on self-reported data. Future research should include studies that track the actual trade-offs parents make when making ECEC decisions.

Conclusion

When navigating the complex landscape of childcare choices in a post-COVID world, our analysis underscores the critical importance of addressing the diverse needs and preferences of parents. In line with pre-COVID research, licensing remained the primary driver of parent decision-making. However, considerations related to health and safety during the pandemic significantly influence choices, for some parents. Recognizing this, actionable items for policymakers involve implementing more targeted and inclusive approaches that accommodate the varying needs and circumstances of parents, thereby enhancing the overall quality and accessibility of care services beyond the pandemic. This may involve the development of flexible models that balance safety measures, acknowledging regional variations and demographic nuances, while fostering a supportive environment for licensed ECEC providers to navigate the complexities posed by divergent parental preferences. Furthermore, findings from this study highlight the need for policies to foster a collaborative dialogue between providers, parents, and policymakers to create a resilient and adaptable childcare system post-pandemic.

Footnotes

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.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Samantha Burns

Adrienne Davidson

Linda White

Delaine Hampton

Notes

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Navigating Parenthood in the Pandemic: Revealing the Trade-offs of Childcare Choices Through Conjoint Analysis

Abstract

Keywords

Introduction

Background—Parental Decision Making Around ECEC

Parental Decision-Making in the Face of a Pandemic of Inequality

Case Selection and Methods

Measures

Conjoint Design

Participant Characteristics

Data Analysis

Conjoint Utilities

Latent Profile Analysis and Associations with Parental Characteristics

Results

Attribute Importance and Average Utility Scores of ECEC Preferences During COVID-19

Latent Profile Analysis

Decision Typologies of Parents in Market-Based Models of ECEC

Discussion and Conclusion

Limitations and Future Directions

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iDs

Notes

References