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. Author manuscript; available in PMC: 2025 Sep 7.
Published in final edited form as: Psychol Health. 2024 Apr 29;40(10):1612–1632. doi: 10.1080/08870446.2024.2347657

Managing children’s asthma: What role do caregivers’ mental representations of trigger and symptom management behaviors play?

Erika A Waters 1, Thorsten Pachur 2,3, Gabrielle Pogge 4, Jean Hunleth 1, Gregory D Webster 4, David A Fedele 4, James A Shepperd 4
PMCID: PMC11518878  NIHMSID: NIHMS1992914  PMID: 38682920

Abstract

Objective:

Pediatric asthma management is challenging for parents and guardians (hereafter caregivers). We examined (1) how caregivers mentally represent trigger and symptom management strategies, and (2) how those mental representations are associated with actual management behavior.

Methods:

In an online survey, N=431 caregivers of children with asthma rated 20 trigger management behaviors and 20 symptom management behaviors across 15 characteristics, and indicated how often they engaged in each behavior.

Results:

Principal components analysis indicated 4 dimensions for trigger management behaviors and 3 for symptom management behaviors. Bayesian mixed-effects models indicated that engagement in trigger management behavior was more likely for behaviors rated as affirming caregiver activities. However, trigger management behavior did not depend on how highly the behavior was rated as challenging for caregiver, burdensome on child, or routine caregiving. Engagement in symptom management behavior was more likely for behaviors rated as affirming and common and harmless to the child, but was unrelated to how highly a behavior was rated as challenging for caregivers.

Conclusion:

These results suggest that interventions might be particularly useful if they focus on the affirming nature of asthma management behaviors. However, such interventions should acknowledge structural factors (e.g., poverty) that constrain caregivers’ ability to act.

Keywords: Asthma, Parent, Child, Adolescent, Behavior

Introduction

Extensive research shows that the behaviors adults perform to improve and maintain their health—including actions taken to prevent, detect, and treat chronic disease—depends in part on the cognitions and emotions that comprise their mental representations of the disease and its treatment (Leventhal et al., 1992; Bishop, 1991; Kleinman et al., 1978). However, much less research has investigated how adults’ mental representations of a chronic health condition can affect their actual behavior related to their child’s medical care. This oversight is important; effectively managing children’s complex health conditions requires a partnership among the child, the child’s parent or guardian (hereafter caregiver), and the child’s health care provider (Katkin et al., 2017). Thus, understanding caregiver mental representations of their child’s health condition could provide insight into what drives their engagement (or lack thereof) in disease management behavior and, consequently, inform the development of interventions to improve children’s health.

In this article, we first explore caregivers’ mental representations of behaviors for managing their child’s asthma: specifically, for reducing their child’s exposure to asthma triggers (hereafter trigger management behaviors) and for alleviating their child’s asthma symptoms (hereafter symptom management behaviors). Second, we examine the link between these mental representations and caregivers’ engagement in asthma management behaviors. Although this article focuses on asthma (Asher and Pearce, 2014; Zahran et al., 2018), we provide a methodological map for investigating the mental representations and their relation to management behavior for other illnesses that require daily management in children (e.g., diabetes).

Contextualizing pediatric asthma

In the U.S., pediatric asthma is the most common lung disease among children (Zahran et al., 2018). Approximately 4.2 million children under age 18 have been diagnosed with asthma (Centers for Disease Control (CDC), 2020). Asthma exacerbations send over 640,000 children to U.S. emergency departments each year (Centers for Disease Control, 2018). Asthma disproportionately affects populations that experience other types of health disparities: children who are members of communities that are marginalized due to their race, including those who identify as Black, multiracial, Puerto Rican, or American Indian, Alaska Native, or Native Hawaiian (Centers for Disease Control, 2020; Asthma and Allergy Foundation of America, 2020), are diagnosed with asthma more often than children who are white. Asthma incidence is also higher among children whose caregivers have low incomes. Such asthma inequities are attributable, in part, to national, local, and corporate policies that expose marginalized communities to more asthma triggers and that limit access to health care services that help prevent and manage symptoms (Harris, 2019; Asthma and Allergy Foundation of America, 2020; Hunleth et al., 2022).

Children with asthma have chronically inflamed airways (National Heart Lung and Blood Institute, 2022). When a child with asthma encounters a trigger (e.g., irritant, allergen), their airways constrict, and their oxygenation is impaired. This can result in acute symptoms such as wheezing, coughing, fatigue, gasping for breath, and distress. Avoiding triggers can help prevent airway constriction. Home management of asthma symptoms involves treating the acute symptoms of asthma with inhaled bronchodilators (often referred to as rescue or quick relief medications), and for those with persistent subtypes, treating the chronic airway inflammation with inhaled corticosteroids (often referred to as a controller, preventer, or maintenance medication). However, if the rescue inhaler does not alleviate symptoms completely (i.e., the child has an exacerbation), the child needs more intense care, such as treatment at an urgent care center or emergency department, or a short course of oral steroids (Fuhlbrigge et al., 2012).

Health care providers are essential for helping caregivers understand how to effectively select and implement trigger and symptom management behaviors. However, the structural factors that limit access to health care services in general also limit access to health care providers who could engage in effective asthma education (Martinez et al., 2021; Yearby et al., 2022). In addition, some asthma management behaviors are expensive or outside the caregiver’s direct control (e.g., mold remediation in rental properties (Franzese et al., 2016)). These two factors make it difficult for caregivers to understand and/or manage their child’s asthma effectively. Consequently, caregivers may generate their own understandings of asthma, and of asthma management behaviors, that are only partially consistent with the biomedical model of asthma (Arcoleo et al., 2015; Hunleth et al., 2022; Peterson-Sweeney et al., 2003; Spray et al., 2021; Yoos et al., 2007).

How caregivers understand asthma and asthma management behaviors

Although inconsistencies between caregiver understandings of asthma and the biomedical model of asthma can be reasonable from the caregiver perspective (Spray et al., 2021) and given the structural constraints described above, they can also lead to improper use of asthma medications (Arcoleo et al., 2015; Yoos et al., 2007; Bokhour et al., 2008; Sonney et al., 2016). Consider, for example, caregivers who view asthma as an acute and episodic (yet severe, frightening, and unpredictable) condition that is only present when symptoms occur, rather than as a chronic health condition that is characterized by chronic lung inflammation (Halm et al., 2006; Spray et al., 2022). Consider further that the effects of taking quick relief medication are detectable and occur quickly (i.e., the child immediately stops wheezing audibly), but the effects of taking the controller medication are less immediately visible and occur over time (i.e., inflammation in the lung subsides). Under these circumstances, it is logical for caregivers to conclude that the controller medication is less effective in managing their child’s asthma than the quick relief medication. In this way, caregivers’ understandings of asthma and asthma management behaviors could lead to long-term engagement in an ineffective management behavior—discontinuation of a controller medication and increased reliance on quick relief medication—and poor asthma control.

Many interventions have attempted to educate caregivers about behaviors for managing their child’s asthma in a way that is consistent with the biomedical model (see systematic reviews: (Wolf et al., 2003; Culmer et al., 2020; Belice and Becker, 2016). However, their effectiveness in improving children’s health outcomes was often modest (Wolf et al., 2003; Culmer et al., 2020) or inconsistent (e.g., the intervention improved some outcomes but had no effect on other outcomes (Belice and Becker, 2016; Culmer et al., 2020). In some cases, the interventions did not improve caregivers’ asthma knowledge at all (Perry et al., 2018).

One possible reason for the modest effectiveness of prior asthma education interventions is that, although much is known about caregivers’ basic knowledge of asthma management behaviors, little is known about how caregivers conceptualize or mentally represent trigger management behaviors and symptom management behaviors. In other words, researchers know little about why certain trigger and symptom management behaviors are more appealing to caregivers than are other behaviors. Identifying caregivers’ mental representations of asthma management behaviors and how such mental representations are associated with actual engagement in asthma management behaviors would help researchers and health care providers understand the constellation of characteristics of trigger and symptoms management behaviors that prompts caregivers to engage in them. In addition, without information about caregivers’ mental representations, interventions that attempt to teach caregivers behaviors for avoiding triggers and for treating symptoms may fail to convey the information in a way that makes sense to caregivers within their contexts (Halm et al., 2006; Leventhal et al., 2003), thereby reducing the intervention’s effectiveness.

Identifying mental representations

Principal components analysis (PCA) is a common strategy for reducing data into a small number of meaningful dimensions. To leverage PCA to identify people’s mental representations for a given topic domain (e.g., asthma trigger management behaviors), participants rate a variety of objects related to the domain (e.g., vacuum regularly) according to several characteristics (e.g., disruptive). The analysis process yields components that reflect commonalities among the objects according to how they are rated on different characteristics (Stevens, 2002).

Researchers have used PCA—or its cousin exploratory factor analysis (EFA)—to identify people’s mental representations in for a variety of topics, including technological hazards (e.g., bicycling, nuclear waste, firearms; Fischhoff et al., 1978), automobile safety strategies (Slovic et al., 1987), prescription medications (Slovic et al., 2007), energy technologies (Bronfman et al., 2008), medication side effects (Waters et al., 2017), food products (Perkovic et al., 2022), and asthma triggers and symptoms (Waters et al., 2023). Researchers have also examined how objects’ scores on the resulting components (i.e., dimensions of mental representations) correlate with outcomes of interest (e.g., perceived risk of experiencing negative health outcomes (Fischhoff et al., 1978; Slovic et al., 1980; Slovic, 1987; Slovic et al., 1987; Bronfman et al., 2008; Waters et al., 2023), aversion to medication side effects (Waters et al., 2017), and perceived healthiness of food (Perkovic et al., 2022). As a concrete example, Slovic (1987) described how PCA revealed three dimensions comprising laypeople’s mental representations of technological and other health hazards: dread (comprised of characteristics including: uncontrollable, fatal, inequitable, involuntary, threat to future generations); unknown (comprised of: new risk, unknown to science, unknown to those exposed, delayed effect) and number of people exposed. Furthermore, to the extent the hazard elicited feelings of dread, was not well-known, and affected large numbers of people, the higher participants rated the riskiness of the hazard, the more they wanted to reduce the risk, and the more willing they were to approve of regulation designed to reduce risk.

Information about people’s mental representations of health threats can be used to design public health interventions. For example, to decrease the public’s perceived risk of a novel infectious disease, one might liken it to less fatal and more familiar infectious diseases (e.g., the common cold, influenza), reassure people that children are not generally susceptible, and suggest that only a small subset of the population need be concerned (e.g., people who are elderly or have compromised immune systems). Critically, however, we know of no research linking mental representations of illness with actual engagement in health protective behaviors. Without such knowledge, it is unknown whether such interventions will be effective in real-world or clinical settings.

Study objective and research questions

Even if policy change overcomes structural barriers to receiving quality care, caregivers would still need interventions that bridge the gap between their understanding of asthma management behaviors and recommended biomedical approaches. Determining how caregivers think about their child’s asthma—particularly their mental representations of asthma trigger and symptom management behaviors—will help identify content for effective and efficient interventions for reducing exacerbations in children with asthma. Our study represents an early step towards improving asthma education interventions for caregivers. Specifically, we (1) used PCA to gain insight into caregivers’ mental representations about the different types of behaviors that caregivers could use to manage their child’s asthma, and (2) used mixed-effects logistic regression to understand how these mental representations (i.e., individual PCA components) are associated with caregivers’ actual asthma management behavior. We posed the following research questions:

  1. What are the key dimensions that structure caregivers’ mental representations of trigger and symptom management behaviors?

  2. How are the dimensions that structure caregivers’ mental representations of trigger and symptom management behavior related to their actual engagement in those behaviors?

Methods

All study procedures and materials were approved by the University of Florida Institutional Review board, approval #201802313. All participants provided informed consent. We pre-registered the approach and materials at the Open Science Framework: https://osf.io/awqf8/

Participants

We recruited participants from the Qualtrics market research survey panel of U.S. residents from September to December 2020. Individuals were eligible to participate if they reported having a child who (a) was diagnosed with asthma by a health provider, (b) still had asthma at the time of the survey, (c) was younger than 18 years of age, and (d) who resided with the caregiver at least 90 days in the previous year. Because asthma occurs more often and with greater severity in children whose caregivers have limited income (Centers for Disease Control, 2020), we stratified recruitment to limit the number of caregivers who reported an income greater than $50,000.

Qualtrics emailed invitations to 220,238 potentially eligible respondents. Of those, 2,363 potential participants clicked the survey link and 1,663 provided consent to participate. We removed 428 respondents with incomplete data, 11 respondents who indicated their child was 18 years or older (or who did not report their child’s age), and 3 caregivers who reported being younger than 18. Of the remaining 1,221 respondents, 624 completed either the trigger management condition or the symptom management condition We omitted from analysis data from 188 respondents who ‘failed’ two or more of five indicators of inattentive responding and five additional cases that Qualtrics flagged as potential duplicates. This left 431 participants in the dataset. See Online Supplemental Materials Section A for a full discussion of the data quality decisions. Caregiver characteristics and how they compare with U.S. Census data (when available) are in Table 1.

Table 1.

Caregiver and Child Socio-Demographic and Health Information

N = 431 % 2020 U.S. Census %
Caregiver Gender
  Male 209 48.5 49.6
  Female 222 51.5 50.4
  Transgender   0  0.0 -
Caregiver Race a
  Asian  10  2.3  6.3
  Black or African American  53 12.1 13.6
  Hawaiian/Pacific Islander   1  0.2  0.3
  Multiracial/Other  14  3.2  3.0
  Native American/Alaskan Native   8  1.8  1.3
  White 352 80.4 75.5
Caregiver Ethnicity
  Hispanic  47 10.9 19.1
  Non-Hispanic 382 88.6 80.9
  Don’t know   1  0.2 -
  Choose not to respond   1  0.2 -
Caregiver Formal Education
  Less than high school  12  2.8  9.8 f
  High school graduate, GED, or high school equivalent 126 29.2 27.8
  Vocational, trade, or technical school  24  5.6 17.5
  Associate degree  44 10.2 10.0
  Bachelor’s degree  82 19.0 22.1
  Post-graduate degree 140 32.5 12.7
  Choose not to respond   3  0.7 -
Household Income
  $25,000 or less 124 28.8  18.1 g
  $25,001 to $50,000  75 17.4 19.7
  $50,001 to $75,000  76 17.6 16.5
  $75,001 to $100,000  44 10.2 12.2
  $100,000 or more 108 25.0 33.6
  Choose not to respond   4  0.9 -
Financial Security b
  Can’t make ends meet  86 20.0 -
  Manage to get by 182 42.2 -
  Enough money to manage, plus extra 115 26.7 -
  Money is not a problem  30  7.0 -
  Choose not to respond   7  1.6 -
  Missing  11  2.5 -
Child Gender
  Male 262 60.8 -
  Female 164 38.0 -
  Transgender   2  0.5 -
  Gender non-conforming   3  0.7 -
  Choose not to respond   0 -
M SD
Subjective Social Status c [range: 1 (worst off) to 10 (best off)] 5.4 2.6 -
Caregiver Age [range: 18 to 60] 37.4 8.5 38.9 h
Child Age [range: 0 to 17] 9.4 4.5 -
Control of asthma symptoms d [range: 4 (low) to 20 (high)] 13.2 4.7 -
Subjective asthma control e [range: 1 (low) to 5 (high)] 4.0 0.9 -
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a

Does not sum to 431 because categories are not mutually exclusive. One participant responded “Don’t Know,” and three responded “Choose Not to Respond.”

b

We measured financial security using a single item: Which of these statements best describes your present financial status? 1 (can’t make ends meet), 2 (manage to get by), 3 (enough to manage plus some extra), and 4 (money is not a problem).

c

We measured subjective Social Status using the MacArthur ladder (Adler et al., 2000).

d

We measured asthma control using the sum of items 1-4 of the parent proxy asthma control test (PP-ACT) (duRivage et al., 2017).

e

We measured subjective asthma control using item 5 of the PP-ACT (duRivage et al., 2017).

-

Data not collected

g

Median household income in the U.S. $75,149. Proportion of population in each income category calculated from Table obtained from: https://www2.census.gov/programs-surveys/demo/tables/p60/273/tableA2.xlsx on the website https://www.census.gov/data/tables/2021/demo/income-poverty/p60-273.html

h

Median age of adults, obtained from: https://www.census.gov/newsroom/press-releases/2023/population-estimates-characteristics.html. The age of parents specifically was not available.

Design

As other research that investigated the underlying structure of people’s mental representations of concepts (e.g., Bronfman et al., 2008; Slovic, 1987), we used the psychometric paradigm to extract dimensions of people’s mental representations. Specifically, caregivers rated several objects (e.g., remove carpet) in various categories (e.g., trigger management behavior) across multiple characteristics (e.g., expensive). We assessed four categories of objects: asthma triggers (e.g., dust), asthma symptoms (e.g., wheezing), trigger management behaviors (e.g., remove carpet), and symptom management behaviors (e.g., pray). Each category comprised 20 objects, and each object comprised 15 characteristics. This resulted in 1,200 total possible ratings across the entire study (i.e., 4 categories x 20 objects x 15 characteristics).

To limit burden, we asked caregivers to rate only a fraction of all possible objects. Specifically, we randomly generated two sets of ten objects for each of the four categories. This resulted in eight sets of ten objects each. Caregivers were randomly assigned to rate objects across 15 characteristics for only one of the eight sets, resulting in 150 item ratings per caregiver (1 set of 10 objects x 15 characteristics). This approach ensured that each object had a similar number of responses.

In this article, we describe only the results for the categories asthma trigger management behaviors and symptom management behaviors; that is, all objects consisted of different types of management behavior. An article related to mental representations of asthma triggers and symptoms is already published (Waters et al., 2023).

Procedure

After consenting, we asked caregivers to report the number of children with asthma and the age and gender of their youngest child with asthma. Then, we randomly assigned caregivers to complete one of the eight sets of ten objects. Because all objects were behaviors, we refer to objects as behaviors henceforth. The description below is the procedure for participants assigned to sets assessing trigger and symptom management behaviors.

Caregivers rated each of the 10 behaviors in their assigned set according to each of the 15 characteristics (presented in random order). To break up the repetitive nature of the task, after rating the first five behaviors in their assigned set, caregivers provided information about their age, gender, race, ethnicity, and asthma status. Then they rated the characteristics for each of the remaining five behaviors in their assigned set. Next, caregivers responded to items (presented in random order) assessing the frequency with which they recently engaged in asthma management behavior. Caregivers who were assigned to rate trigger management behavior completed items assessing their engagement in the various trigger management behaviors; caregivers assigned to rate symptom management behavior completed items assessing their engagement in the various symptom management behaviors. Finally, caregivers responded to items assessing additional socio-demographic information (e.g., subjective social status), tobacco exposure, and an item gauging self-reported attention to the questions in the survey. The median completion time was approximately 25 minutes.

Materials

We generated an initial pool of characteristics based on characteristics reported in the literatures on illness and symptom representations (Bishop, 1987; Leventhal et al., 2003), risk perception (Slovic, 1987), and the role of affect and emotion in risk judgments (Lerner and Keltner, 2000). We also created additional characteristics ad-hoc, informed by the biomedical literature about asthma (Busse et al., 2012; Krishnan et al., 2012; National Heart Lung and Blood Institute, 2007), and our qualitative interviews of caregivers of children with asthma and health care providers of children with asthma (Spray et al., 2022). We narrowed the pools of behaviors and characteristics based on results from a pilot survey; behaviors and characteristics showing little variability were excluded. We based our final choices on maximizing conceptual breadth, minimizing conceptual redundancy, and ensuring adequate variability in responses. See the Online Supplemental Materials Section B, Tables S1–S3 for the exact wording for all behaviors, characteristics, and frequency of trigger management and symptom management behaviors.

Behaviors.

The final list of 20 trigger management behaviors included, for instance, avoiding tobacco smoke, washing bedding, helping the child manage their emotions, and keeping the child away from people who are ill. The final list of 20 symptom management behaviors included, for instance, administering medications, praying, monitoring the child’s breathing as they sleep, and encouraging the child to change their posture. The behaviors varied in the extent to which they were supported by the biomedical model of asthma; because caregivers in prior research had mentioned behavior that were not supported by the biomedical model, excluding such behavior would result in an incomplete understanding of their mental representations, especially given the social context of asthma treatment in the U.S.

Characteristics.

The final list of 15 characteristics was the same for trigger management and symptom management behavior. It included items assessing the extent to which caregivers thought the management behavior was annoying, resource-intensive, disruptive, and effective. Each object was rated using a 5-point scale (1=do not agree at all; 5=agree completely).

Frequency of asthma management behavior.

We created the final list of 20 trigger management and 20 symptom management behaviors to parallel their respective objects. For example, if a caregiver rated the characteristics of vacuuming as a trigger management behavior, they would answer a parallel item about how frequently they vacuumed in the previous three months. We tailored the response scales to the content of the behavior using either 5-point (e.g., 1=never in the past 3 months; 2=rarely, 3=sometimes, 4=often, 5=always) or dichotomous (1=no; 2=yes) response formats. In the analyses, however, we only differentiated whether the person reported to engage in the behavior or not, irrespective of the frequency. Each item also included a “not relevant” response option (e.g., I haven’t needed to do this activity to manage my child’s asthma in the past 3 months; No one in my child’s life smokes cigarettes.”

Socio-demographic characteristics.

We assessed several socio-demographic characteristics that are related to asthma outcomes in children in the U.S. (see Table 1).

Results

We began by examining the proportion of caregivers who reported any engagement in each trigger and symptom management behavior. Overall engagement was high, with at least two-thirds of the sample engaging in most of the behaviors in each category (see Figure 1).

Figure 1. The proportion of caregivers who reported engagement in each asthma trigger management behavior (left-hand graph) and in each asthma symptom management behavior (right-hand graph).

Figure 1.

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Note. Behaviors are ordered by the proportion of caregivers reporting engagement in the respective management behavior from high (at the top of the graph) to low (at the bottom of the graph).

Next, consistent with other research exploring mental representations (Fischhoff et al., 1978), we determined the average (across caregivers) rating for each management behavior (e.g., filter air) on each of the characteristics (e.g., disruptive). Based on these average ratings, we conducted, separately for each category of behaviors (i.e., trigger management or symptom management), a PCA using the principal function from the psych package (Revelle, 2019) in R (R Core Team, 2020) with oblimin rotation. We used the Kaiser criterion (i.e., eigenvalues > 1) and the “elbow” criterion (i.e., the point in the scree plot where the eigenvalues of additional components level off) to decide the number of components to retain for each category (i.e., trigger management behavior, symptom management behavior).

Finally, we examined the extent to which the scores of the management behaviors on each component underlying the mental representation predicted whether caregivers engaged in a given behavior. For these analyses, we used the individual caregivers’ responses as unit of analysis (rather than aggregating across caregivers as was necessary for the PCA). To obtain component scores for each behavior for each individual caregiver (recall that the components were extracted based aggregate data), we averaged the individual caregivers’ responses on those characteristics that loaded highest on the respective component (as shown in bold in Table 2) and for which the caregiver actually provided a response. We then used the behavior’s score on each component based on the individual caregiver’s ratings to predict whether the caregiver engaged in the behavior. We conducted the analyses with Bayesian mixed-effects logistic regression using the brms package in R (Bürkner, 2017). Although each caregiver responded to only a subset of characteristics and behaviors, the mixed-effects approach is robust to missing data. For making inferences about the associations between the components and engagement in a behavior, we relied on the population (i.e., fixed) effects. In the analysis, we used the components as fixed effects and included random intercepts for caregivers and the different behaviors.

Table 2.

Results of principal components analysis (PCA): Loadings of characteristics on each component for trigger management and symptom management behavior.

Characteristic Trigger management behavior
 Symptom management behavior
Affirming caregiver activities Challenging for caregiver Burdensome for child Routine caregiving Affirming and common Harmless to the child Challenging for caregiver
Makes me calm 0.96 −0.10 0.11 −0.11 0.97 0.03 0.09
Shows care  0.95 −0.07  0.02 −0.18  0.60  0.28  0.16
Feel good  0.91 −0.04 −0.16 −0.01  0.85  0.08  0.13
Effective  0.87  0.02  0.03  0.20  0.93  0.03 −0.18
Common  0.83 −0.01  0.08  0.33  0.95  0.06 −0.12
Relevant  0.69 −0.18  0.23  0.41  0.90  0.05 −0.07
Disruptive −0.08  0.95 −0.12  0.03  0.16 −0.21  0.81
Memory-intensive  0.00  0.88  0.18  0.23 −0.58  0.46  0.48
Annoying −0.19  0.77  0.16 −0.17 −0.03  0.32  0.65
Dependent on others  0.25  0.08  0.94  0.03  0.30  0.46 −0.50
Makes child look weak −0.05  0.53  0.62 −0.20  0.70 −0.14  0.25
Could harm child −0.32  0.49  0.55 −0.03  0.24 −0.63  0.28
Often  0.28  0.17 −0.10  0.89  0.24  0.88  0.01
Uncertain −0.43  0.07  0.36 −0.46 −0.90 −0.05 −0.06
Resource-intensive  0.44  0.38 −0.46 −0.66  0.73 −0.24  0.23
Variance explained Individual components  42% 25%  17%  16%  65%  18%  17%
Total 88% 72%
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What are the key dimensions that structure caregivers’ mental representations of trigger and symptom management behaviors?

Table 2 shows how each characteristic loaded on the resulting principal components for the trigger and symptom management behaviors. The table also reports the percentage of variance explained by each of the retained components and the amount of total variance explained by each model. Figure 2 shows how the individual behaviors scored on the extracted components, using the behaviors’ factor scores.

Figure 2.

Figure 2.

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Two-dimensional factor space depicting caregivers’ mental representations of (A) trigger management behaviors and (B) symptom management behaviors.

Note. The label on the bottom of each factor space represents the horizontal axis (e.g., “affirming caregiver behaviors” located on the left-hand side of panel A). The label to the left of each factor space represents the vertical axis (e.g., “challenging for caregiver” located on the left-hand side of panel A).

For trigger management behavior, we retained four components. The highest loadings for the first component were for characteristics such as “makes me calm”, “shows care”, and “effective” (see Table 2). Management behaviors scoring high on this component were avoiding smokers and filtering air; management behaviors with low scores were limiting outdoor activity and removing carpets (see Figure 2A). We interpreted this component as affirming caregiver behaviors. The highest loadings for the second component were “disruptive”, “memory-intensive”, and “annoying” (see Table 2) Management behaviors scoring high on this component were avoid non-household members and dusting; management behaviors with low scores were avoiding strong smells and managing humidity (see Figure 2A). We interpreted this component as challenging for caregivers. The highest loadings for the third component were “dependent on others”, “makes child look weak”, and “could harm child” see Table 2) Behaviors with high scores on this component were limiting the child’s physical activity, limiting the child’s outdoor activity, and managing excitement; behaviors with low scores were removing carpets and moving to another house (see Figure 2A). We chose the label burdensome on child for this component. The highest loadings for the fourth component were “often” and for “resource-intensive” (negative loading; see Table 2)). Behaviors scoring high on this component were washing bedclothes, vacuuming, and dusting; behaviors with low scores were moving house and mold remediation (see Figure 2A). We called this component routine caregiving.

For symptom management behaviors, we retained three components. The highest loadings for the first component included the characteristics “makes me calm”, “common”, “feel good”, and “effective” (see Table2). Management behaviors scoring high on this component were giving medication when the child has trouble breathing, going to the emergency room, and taking the child to the doctor. Behaviors scoring low on this component were giving massage and praying (see Figure 2B). We interpreted the component as affirming and common. The highest loadings for the second component were for the characteristics “could harm child” (negative loading) and “often” (see Table 2). Behaviors scoring high on this component were praying and giving controller medication; behaviors scoring low were going to the emergency room and providing home remedies (see Figure 2B). We labeled this component as harmless to the child. The highest loading for the third component were for the characteristics “disruptive,” “annoying,” and “dependent on others” (negative loading; see Table 2). Behaviors that scored high on this component included monitoring sleep and going to the emergency room; behaviors that scored low were giving albuterol medication when having trouble breathing and encouraging deep breathing 9see Figure 2B). We refer to this component as challenging for caregiver.

How are the dimensions that structure caregivers’ mental representations of trigger and symptom management behavior related to the frequency of their actual engagement in those behaviors?

The estimated regression coefficients for the mixed-effect logistic regression predicting whether caregivers engaged in the different management behaviors are shown in Table 3. For trigger management, only the component affirming caregiver activities was associated with engaging in the behaviors (b=0.99, 95% CI [0.72, 1.26]. That is, the higher a caregiver rated a trigger management behavior on the characteristics that loaded strongly on this component, the higher the probability that the caregiver reported to engage in the behavior. Similarly, for symptom management, both the affirming and common component—which is conceptually similar to the affirming caregiver activities component for trigger management—and the harmless to the child component were credibly associated with behavior (b=1.12, 95% CI [0.65, 1.65] for affirming and common; b=0.53 [0.17, 0.93] for harmless to the child).

Table 3.

Results of the mixed-effects logistic regression model analysis predicting whether caregivers engaged in an asthma management behavior based on the dimensions underlying their mental representations of the behavior. Credible effects are bolded. 95% confidence intervals (CI) are in brackets.

Type of behavior Term Estimate CI95%
Trigger management
Intercept −1.17 [−2.37, 0.05]
Affirming caregiver activities  0.99 [0.72, 1.26]
Challenging for caregiver  0.08 [−0.23, 0.39]
Burdensome on child  0.13 [−0.19, 0.47]
Routine caregiving −0.04 [−0.37, 0.29]
Symptom management
Intercept −2.13 [−3.35, −0.98]
Affirming and common  1.12 [0.65, 1.65]
Harmless to the child  0.53 [0.17, 0.93]
Challenging for caregiver  0.10 [−0.30, 0.53]
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Discussion

Our results show that caregivers have multidimensional mental representations of behaviors for reducing their child’s exposure to asthma triggers and for managing their child’s asthma symptoms. Furthermore, certain aspects of these representations may shape caregivers’ engagement in asthma management behavior. Although other studies have examined caregivers’ knowledge about asthma management behaviors, such studies often sought to describe similarities and differences between caregivers’ knowledge of asthma management behaviors and behaviors that are promoted by the biomedical model of asthma (e.g., Culmer et al., 2020; Bokhour et al., 2008). In contrast, our methodological and conceptual approach drew not on a deficit model of caregiver knowledge, but instead on lay knowledge and epidemiology perspectives (Kleinman et al., 1978; Davison et al., 1991; Popay and Williams, 1996) that assume caregivers’ behavior emerges from their unique social context and personal understandings of how different asthma management behaviors affected their child’s health. Leveraging the psychometric paradigm to explore the multidimensional nature of caregivers’ mental representations of asthma management behaviors, and how those dimensions were associated with actual engagement in asthma management behavior, extends prior asthma research. Specifically, we provide insight about what characteristics of asthma management behaviors make them more (or less) likely to be performed, rather than simply identifying beliefs about a small number of individual behaviors (e.g., use of inhaled corticosteroids). Such insights could make asthma education interventions more manageable for health care providers, who may not understand why their patients are not following standard asthma management guidelines, or who may be having difficulty using a piecemeal strategy to address disparate activities that may or may not represent a given family’s situation.

We identified three key similarities in the mental representations of trigger and symptom management behaviors. Both categories of management behaviors have dimensions related to caregiver experiences of affirmation (i.e., behaviors that make the caregiver feel good, show care, are effective, calm the caregiver, are performed by many people, and are relevant to the child) and challenge (i.e., behaviors that are annoying or disruptive for the caregiver to perform), as well as potentially burdensome on the child (i.e., behaviors that are potentially physically harmful to the child and/or negatively affect others’ perceptions of their child). Critically, engagement was more likely only for management behaviors that caregivers perceived as affirming and/or harmless to the child. Furthermore, as counterevidence to the argument that caregivers do not want to perform difficult behaviors, behavioral engagement was not associated with the extent to which the caregiver found the behavior challenging to enact or the routineness of the behavior. Closer investigation of the characteristics that comprise the dimensions that are most closely associated with asthma management behavior suggests some overlap with traditional theories of health behavior (Conner and Norman, 1995). For example, subjective norms and the characteristic “common” both address (albeit in slightly different ways) the extent to which other people find the behavior acceptable. Similarly, outcome expectancies, response efficacy, attitudes, and the characteristic “effective” all include beliefs about whether the action will reduce risk or solve the health problem.

However, health behavior theories do not explicitly account for one key consideration: for caregivers, caregiving is not only about logistical considerations—it also represents ways of showing and feeling care. Actions that are affirming are often seen by other people and are perceived by the caregiver and other observers as actions that are performed by a “good” parent, especially a “good” mother (Dao and McMullin, 2019). These can involve self-sacrifice, such as carrying out challenging trigger and symptom management behaviors (e.g., seeking medical care despite feeling unsupported by—and mistrustful of—medical providers (Spray et al., 2021; Fawcett et al., 2019). In this study, caregivers viewed several activities as very challenging, including avoiding non-household members and limiting the child’s outdoor activities. However, caregivers were no less likely to engage in challenging behaviors than unchallenging behaviors. Instead, those behaviors seen as affirming were preferred (e.g., working with schools, avoiding smokers). Nevertheless, the extent to which someone is able to engage in an affirming behavior may be shaped and constrained by structural factors such as poverty, environmental pollution, and an inadequate health care system (Harris, 2019; Hunleth et al., 2022). That is, engaging in affirming behavior could have greater economic costs for caregivers constrained by structural factors, meaning that the caregivers who carry them out might need more support to do so (Fawcett et al., 2019). Further, providers who naturalize such expressions of “good” mothering and assume that caregivers are not engaging in appropriate asthma management behaviors may report caregivers for medical neglect. This not only shames and blames caregivers, but may result in a cascade of events whereby the child is sent to foster care (Knox et al., 2020).

Strengths and Limitations

This research has several methodological and conceptual strengths. Our recruitment strategy leveraged a large Internet survey panel comprised of members from across the U.S. This decision may have resulted in selection bias related to the types of people who are willing to take surveys as a part of survey panels. However, this decision also resulted in increased geographic generalizability in terms of recruiting a national (vs. local) sample of caregivers who did not need to be connected to a clinic setting to be recruited. In addition, recruiting via the survey panel had logistical benefits in terms of lower cost and faster recruiting, which allowed us to recruit a very large sample of caregivers, despite the relative rarity of “caregivers of children with asthma” in the general U.S. population. Consequently, we can generalize our research findings beyond what is typically seen in research that investigates caregivers’ beliefs about asthma management behaviors.

This study also demonstrates that the psychometric paradigm can be useful to identify people’s mental representations of their own health conditions and the mental representations of health conditions that other people experience. With this approach, researchers can gain understanding of other caregiving and public health contexts (e.g., other childhood health conditions, elder care situations, public health policy). Finally, the study design allowed us to draw conclusions about the relationship between each dimension comprising the mental representations and caregivers’ engagement in asthma management behaviors. To our knowledge, this study is one of the first to use the psychometric paradigm to draw links from each component/dimension to an individual’s behavior (cf. Perkovic et al., 2022). Our findings provide an important conceptual advance for the psychometric paradigm, but also highlights the potential to develop behavior change interventions by targeting specific dimensions of people’s mental representations. We also believe that this methodology could be extended for use in interventions to improve young people’s self-management of their own asthma.

This research also has limitations. First, compared to 2020 U.S. Census estimates of the total U.S. population, our study sample included a disproportionately high proportion of individuals who reported that they were white, non-Hispanic, and had more formal education. However, as planned, the sample also included a disproportionately higher proportion of people with limited incomes. In addition, our sample included caregivers who identified as Black, Native American/Alaska Native, and multiracial in proportions similar to the U.S. population. These same populations experience disproportionately high rates of asthma compared to white children (Centers for Disease Control, 2020; Asthma and Allergy Foundation of America, 2020). Thus, although we do not have sufficient numbers of individuals from these groups to perform subgroup analyses, they are represented in the study sample in proportions similar to the U.S. population overall.

Second, like much research investigating people’s mental representations, this study relied on a cross-sectional research design. Therefore, it is possible that caregivers’ behavior may be driving their mental representations (instead of their mental representations driving their behavior). Third, to limit burden, we asked caregivers to rate only one of four possible categories of objects related to asthma: triggers, symptoms, trigger management behaviors, and symptom management behaviors. This design choice prevents us from being able to directly compare a single caregiver’s mental representations of trigger and symptom management behaviors. To further limit burden, we did not include items assessing other psychological or health outcomes (e.g., quality of life). Research that assesses such outcomes could extend the findings reported in this manuscript. Fourth, we relied on caregivers’ self-reports of their child’s asthma diagnosis. These findings could be enriched by a study that pairs self-reported diagnosis with clinical validation.

Finally, although we included management behaviors that were not supported by the biomedical model to understand the complexity of caregivers’ mental representations, we were unable to assess more nuanced situations. For example, there are some situations in which a management behavior might be contraindicated (e.g., sleeping with breathing problems) or are advisable only when used in combination with biomedically-supported behaviors (e.g., supplementing praying with albuterol, but not replacing albuterol with praying). Thus, it is important to highlight that the component harmless to the child is named so because caregiver ratings indicated they perceived certain behaviors as harmless to the child—regardless of the circumstances under which this is—or is not—true. Future research needs to unpack how caregivers view the interaction of multiple management behaviors.

Conclusion

The results from this study suggest a new direction for improving asthma education. Caregivers were more likely to perform asthma management behaviors that they viewed as more affirming, regardless of how challenging it was to actually perform the behavior. Therefore, interventions might be particularly useful if they focus on or amplify the affirming nature of key asthma management behavior. Providing logistical and pragmatic support for caregivers whose socio-contextual situations unduly constrain their choices might also be useful; even though challenging for caregiver was not statistically significantly associated with management behavior, providing such support would likely benefit families who are most in need (Hunleth et al., 2022). However, such interventions should avoid inadvertently stigmatizing or blaming caregivers who are unable to overcome powerful structural forces that limit the extent to which personal action can improve health.

Supplementary Material

Supp 1

Funding acknowledgements:

This research was supported by the U.S. National Institutes of Health (R01HL137680, Principal Investigators Erika A. Waters, James Shepperd).

Footnotes

Declaration of Conflicts of Interest: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Research ethics: All research has been conducted in accordance with the Declaration of Helsinki. All study methods and procedures were approved by the University of Florida Institutional Review Board, approval #201802313. Informed consent was obtained from all participants.

Geolocation: All work has been performed in the United States.

Declaration of Conflicts of Interest

The Authors declare that there are no conflicts of interest.

Data availability, deposition, and sharing:

The de-identified data, the analytic code used to conduct the analyses presented in this manuscript, and all materials used to conduct the study are freely available in the Open Science Framework public archive: https://osf.io/awqf8/. We do not submit them with this manuscript because the dataset includes data points that (a) are not relevant to this paper, and (b) are relevant to other manuscripts that will be submitted to other publication venues.

Data availability and sharing

The de-identified data, the analytic code used to conduct the analyses presented in this manuscript, and all materials used to conduct the study are freely available in the Open Science Framework public archive: https://osf.io/awqf8/?view_only=b965206c97684ab094e96e960826bf63

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supp 1
NIHMS1992914-supplement-Supp_1.docx (50.5KB, docx)

Data Availability Statement

The de-identified data, the analytic code used to conduct the analyses presented in this manuscript, and all materials used to conduct the study are freely available in the Open Science Framework public archive: https://osf.io/awqf8/. We do not submit them with this manuscript because the dataset includes data points that (a) are not relevant to this paper, and (b) are relevant to other manuscripts that will be submitted to other publication venues.

The de-identified data, the analytic code used to conduct the analyses presented in this manuscript, and all materials used to conduct the study are freely available in the Open Science Framework public archive: https://osf.io/awqf8/?view_only=b965206c97684ab094e96e960826bf63

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