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. Author manuscript; available in PMC: 2024 Sep 3.
Published in final edited form as: J Clin Child Adolesc Psychol. 2021 Sep 23;52(5):604–615. doi: 10.1080/15374416.2021.1969651

Dispositional active coping predicts patterns of adolescents’ cortisol responsivity in the context of school-related stressors

Vanesa M Perez 1,*, Nancy A Gonzales 1, Jenn-Yun Tein 1, Mariam Hanna Ibrahim 1, Linda J Luecken 1, Sandra Losoya 1
PMCID: PMC8940737  NIHMSID: NIHMS1736432  PMID: 34554861

Adolescence marks an important developmental period during which youth experience increased psychosocial stressors along with heightened biological sensitivity to social influences (Somerville, 2013; Sumter et al., 2010). These challenges can serve as opportunities for the development of the self-regulatory system in adolescence if the stressors are manageable and there are sufficient resources available to help the adolescent grow and learn from the challenges (Zimmer-Gembeck & Skinner, 2011). However, if stressors are poorly managed, the physiological stress response system may be negatively impacted, leading to increased susceptibility to psychopathology and long-term deleterious health and psychosocial consequences across adolescence (Adam et al., 2017; Dockray et al., 2009; Grant et al., 2003; Kessler et al., 2005; Shirtcliff & Essex, 2008). One way in which the physiological stress response system may be negatively impacted is if the Hypothalamic-Pituitary-Adrenal (HPA) axis fails to habituate (i.e., nonhabituation) and continuously becomes activated in response to repeated exposure to the same stressor (McEwen, 1998; Schommer et al., 2003).

The HPA axis is a particularly relevant physiological mechanism to examine in adolescence as it is a sensitive period of neurobiological development characterized by substantial neural and physiological reformation and increased HPA reactivity to psychosocial stressors (Gunnar et al., 2009; Spear, 2009). In response to the psychosocial stressors, the HPA axis produces the glucocorticoid hormone known as cortisol (Gunnar et al., 2009). Moreover, cortisol is part of a biological feedback loop involved in regulating the sympathetic nervous system, which prepares the body for stress conditions, including uncontrollable stressors and social evaluation (Dickerson & Kemeny, 2004; Sapolsky et al., 2000). Thus, cortisol can be assessed as a marker for varying forms of stress adaptation including habituation. Habituation of the HPA axis involves a reduction in stress-induced circulating hormone concentrations in response to repeated and prior exposure to the same or similar stressor (Grissom & Bhatnagar, 2009). Past research has found that approximately 50-75% of individuals in a laboratory setting display adaptive habituation to repeated exposure to the Trier Social Stress Test, a speech task conducted in front of an audience (Kirschbaum et al., 1995; Schommer et al., 2003). Variability in whether individuals are able to demonstrate habituation to a repeated stressor may be attributed to psychological resources that help modulate the impact of stress, such as coping strategies. To the extent that an individual is able to utilize effective coping mechanisms when faced with a particular type of stressor, they may come to appraise the stressor as being manageable versus an overwhelming experience with no remedy when they are presented with a similar challenge in the future (Lazarus & Folkman, 1984).

Alongside the calibration of the HPA axis, strategies used to cope with stressors become increasingly differentiated during adolescence and dispositional coping styles begins to emerge (Zimmer-Gembeck & Skinner, 2011). New social challenges in adolescence provide an opportunity to refine coping strategies and cultivate competence in dealing with stressors to promote positive development and prevent mental health problems. For early adolescents in middle school, stressors specific to the school context are particularly salient and may have important implications for the development of adolescents’ self-regulatory capacities and motivation in learning contexts (Mize & Kliewer, 2017). Being able to effectively cope with school-related stressors is also especially relevant for youth who are ethnic minorities or attend schools in low-income communities as they face a greater number of barriers to school success and engagement, such as racial/ethnic discrimination within the school context (Roche & Kuperminc, 2012) and lower achievement expectations from teachers (Peterson et al., 2016).

A central premise of the current study is that active coping may facilitate adaptive habituation in the HPA axis in response to an acute stressor. Accumulating evidence has identified certain dispositional coping styles, particularly those involving active coping, that are protective against a host of negative mental health outcomes and promotive of positive development during adolescence (Clarke, 2006; Compas et. al., 2017). Active coping, the process of taking active steps to remove the threat or ameliorate its effects, has been found to buffer against the negative effects of stress, conceivably through physiological mechanisms (Carver et al., 1989; Grant et al., 2003). Theoretically, the use of active coping may play an important role in regulating adolescents’ stress physiology, such as the HPA axis, because it prompts adolescents to directly confront challenging situations by practicing cognitive and behavioral strategies (e.g., direct problem solving) that enable them to modulate their arousal when faced with an acute stressor. Over time, successful coping outcomes may strengthen their sense of coping efficacy and physiological preparedness to actively confront or approach future challenges. Thus, active coping may help prevent nonhabituation of the HPA axis (characterized by high levels of cortisol responding) while still facilitating the recruitment of physiological resources – in moderation – to actively confront the challenge (characterized by reactivity with timely recovery). The current study examines whether active coping may facilitate stressor-specific adaptation of the HPA axis for adolescents.

Coping and cortisol indicators of stress adaptation

The limited research that has examined the link between coping and HPA axis activity comes from a mix of studies using diurnal cortisol indices (e.g., Foland-Ross et al., 2014; Sladek et al., 2017), or day-to-day fluctuations in cortisol in response to daily stressors (e.g., Hilt et al., 2017; Sladek et al., 2016), as well as studies examining cortisol reactivity and/or recovery to an experimentally-induced stress task (e.g., Bendezú et al., 2019; Bendezú et al., 2016; Bendezú & Wadsworth, 2017; Wadsworth et al., 2018). Research using diurnal cortisol measures generally supports the role of active coping in promoting more adaptive stress physiology. Across several studies, individuals who are more likely to use active coping strategies show more adaptive diurnal cortisol patterns, lower cortisol awakening response (CAR), and lower cortisol throughout the day (O’Donnell et al., 2008; Schmeelk-Cone, et al., 2003; Sladek et al., 2017). In contrast, individuals who are more likely to use avoidant or disengaged coping styles tend to show increased or heightened diurnal cortisol patterns (Foland-Ross et al., 2014; Hilt et al., 2017; Sladek et al., 2016).

A limitation of studies linking coping with diurnal cortisol is that they underestimate true cortisol “reactivity” due to potential error in the precision of timing naturally occurring real-world cortisol responses to perceived stress (Schlotz, 2019). Experimental research offers an alternative approach to examining the relation of coping to HPA axis stress response patterns under more controlled conditions, such as the Trier Social Stress Test (TSST; Kirschbaum et al., 1993) by which individuals are told they are being evaluated while performing a challenging speech task. In response to acute social stressors, such as public speaking, cortisol levels begin to rise as an adaptive mobilization of effort to meet the challenge within minutes of the stressor’s onset (Dickerson & Kemeny, 2004). Cortisol reactivity can be detected at approximately 20 to 25 minutes after the stressor, and full recovery can take up to one hour (Nicolson, 2008).

A prior study compared cortisol stress reactivity to the TSST among adolescents who were raised in their birth families and adolescents adopted from orphanages. Results from this study showed that cognitive reappraisal, an effortful and cognitive tool for emotion regulation, was related to higher cortisol reactivity to the TSST, but this was only shown among adolescents with relatively fewer early life stressors (Johnson et al., 2019). Another study with young adults found that trait use of cognitive reappraisal was associated with stronger HPA axis habituation (i.e., lower cortisol response on day two relative to day one) in response to a repeated exposure across two consecutive days to a standardized experimental stress paradigm (Roos et al., 2019). The limited findings in this literature suggest that youth who have dispositional tendencies to engage in active coping may display HPA axis habituation in response to an acute stressor and this pattern may be amplified with repeated exposure to the same stressor. This hypothesis is tested for the first time in this study with a focus on school-related stressors, using prior reports of school-related hassles as the amplifier (moderator) of adolescents’ responses to a school-related experimental stress task.

Present study

The present study examined whether dispositional active coping was associated with cortisol response patterns following exposure to an academically salient, social stress task in a school setting with an ethnically diverse sample of adolescents attending Title 1 middle schools. In addition, this study examined whether the effects of dispositional active coping on cortisol responding were conditioned on adolescent’s prior exposure to school-related stressors. We utilize piecewise latent growth curve modeling (PLGCM) to measure quantitative changes in cortisol responding and to facilitate comparisons with prior literature. We assessed the relation between active coping and reactivity and recovery separately given that previous studies have found differential effects of coping on reactivity and recovery (e.g., Bendezú et al., 2016; Stewart et al., 2013). We hypothesize that: H1) Dispositional active coping will be associated with increased capacity for adaptive physiological regulation (i.e., lower reactivity followed by recovery) in early adolescence; H2) The effects of active coping on cortisol stress responding to an acute school-related stressor will be conditional on adolescents’ prior exposure to school stressors, such that active coping will predict lower reactivity and faster recovery for adolescents with previous exposure to school hassles.

Methods

Participants

Adolescents were recruited for a larger randomized control trial (RCT) of a universal family intervention, Bridges, previously shown to promote school engagement and prevent mental health and substance use problems (Gonzales et al., 2012). The RCT examined effects of a streamlined (4 session) adaptation of the program delivered by school providers in Title 1 middle schools. Eligibility criteria for the study required that the adolescent was in seventh grade, attended one of the target schools, was not in a self-contained class for emotional or cognitive impairment, had at least one caregiver that was willing to participate and able to speak English or Spanish, and had agreement from the family to be randomized to the intervention (Bridges) or control group. Parents gave informed consent and adolescents assented for study participation. All materials were available in English and Spanish. The study protocol was approved by the Institutional Review Board (IRB) at Arizona State University.

Three cohorts of recruitment and data collection were completed during the Fall semester of the seventh grade. Data collection from all three cohorts was completed within approximately three months. Two methods for recruitment were used. As one method, adolescents and their families were randomly selected from school rosters and sent endorsement letters that outlined the purpose of the program and its benefits, as well as an invitation form, by school personnel. Families who completed the invitation form were then contacted to determine eligibility for the study. As another method, recruiters attended schedule pick-up events at the schools and parents were able to voluntarily request information about the program and participate in a recruitment and eligibility screen. After confirming eligibility and participation, parents and adolescents were interviewed in their homes for their pretest assessments. Afterwards, families were randomized to a workshop control group or the Bridges program. Recruitment rates and a study consort diagram have been reported elsewhere (Thamrin et al., 2021). The GPST-A was administered as part of a larger school assessment and cortisol samples were collected at school after classes. Families were given a reminder call a few days before the school assessment and were given instructions to not consume caffeine or food before the school assessment.

A total of 763 eligible families completed the pretest interview at home. The present study utilizes only the pretest data of the adolescents who provided usable cortisol data (n = 670). From the sample of 670 adolescents who agreed to participate in the GPST-A, three adolescents were further excluded a priori from the analyses due to cortisol values that exceeded four standard deviations from the mean. The final sample included 667 adolescents (51% female; 11 – 13 years old [M = 12.02, SD = .48]; 55% Hispanic, 8% mixed Hispanic, 12% non-Hispanic White, 11% non-Hispanic Black, 7% Native American, and 8% “other”). Median household income was $30,001 - $35,000 per year (range = < $5,000 to > $100,000 per year). Of the 667 adolescents, 95 (14%) endorsed taking at least one medication within the past month.1

Procedure

Youth assented and parents gave informed consent regarding study participation. Interviewers completed semi-structured interviews after-school in a classroom at the middle school adolescents attended. These school assessments were conducted on weekdays immediately after school. A minimum of 30 minutes elapsed between the start of the interview to the start of the GPST-A to ensure participants acclimated to the environment. Each adolescent participant had a designated research assistant to help them through the saliva collection procedure. Timers were set on laptops to ensure the research assistants collected the saliva sample at the appropriate times. Cortisol samples were collected from 3:45pm-6:45pm (M = 4:32pm; SD = 16.29 minutes). Adolescents were asked to report on their tendency to engage in various coping strategies and on school hassles that have occurred in the last three months, along with questions assessing behavioral factors that may affect cortisol levels (e.g., medication use, caffeine use, recent meals). After interviews, and immediately before the GPST-A, participants provided an initial, pretest saliva sample using the passive drool method. Groups of 5 to 8 randomly selected adolescents were then led to a separate room to participate in the Group Public Speaking Task for Adolescents (GPST-A; Hostinar et al., 2014). After the approximately 30-minute task, adolescents were then escorted back to their original classroom, whereby they provided the second, post-task saliva sample, and two samples 15- and 30-minutes after the second sample. Figure 1 depicts a visual timeline of the salivary cortisol collection procedure. At the end of the study, adolescents were compensated $40 for completing the school interview portion of the study and debriefed.

Figure 1.

Figure 1.

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Salivary cortisol collection procedure

Measures

Group Public Speaking Task for Adolescents (GPST-A).

The Group Public Speaking Task for adolescents (GPST-A) is a group social stress task that is designed to elicit mild to moderate cortisol reactivity and has been found to be ecologically valid for use with racially diverse, urban adolescents (Hostinar et al., 2014). During this task, adolescents sat in individual chairs next to one another with collapsible dividers between them (as recommended by Hostinar et al., 2014). Adolescents were directed to provide a speech discussing why they should be chosen to receive an Outstanding Student Award and discuss their strengths and weaknesses. They were then instructed that they would be chosen in random order to deliver a speech to two expert judges who would evaluate their speech style and content. Adolescents were provided with three minutes to prepare their speech on a notepad. During preparation, two college-age judges (one male, one female) wearing professional attire entered the room. At the end of preparation, adolescents were told to put their notes under their chairs. Judges called on adolescents in random order to stand up and give their speech, one at a time, while a laptop that video-recorded the speech faced the adolescent who could see themselves on the screen. Judges maintained a neutral expression throughout the task and provided directives but no feedback in a neutral tone (e.g., “Remember you are being judged on style and content”). In cases where adolescents stopped speaking, judges provided reminders to prompt them (e.g., “If you have run out of things to say you can repeat what you have already said,” or “Your time is not up yet”).

Salivary Cortisol.

Salivary cortisol was collected during the speaking task using the passive drool method immediately pre- (T1) and post- (T2) the GPST-A, as well as 15- (T3) and 30-minutes (T4) post-task. Saliva samples were immediately frozen in a −20°C freezer. Cortisol levels were assayed in the Biological Psychology laboratory directed by Dr. Clemens Kirschbaum at the Technical University of Dresden in Dresden, Germany. The assay was conducted using the single-plate method.

School Hassles.

School hassles were assessed by a count of seven items reflecting stressful life events in the school domain (e.g., “A teacher or principal criticized you or tried to embarrass you in front of other students”). The measure is a subscale in the broader Multicultural Events Scale for Adolescents (MESA; Gonzales et al, 1999; Gonzales, et al., 2001) and asks whether a school- or class-related stressful life event has occurred in the past three months. The total number of school hassles endorsed by adolescents was used in these analyses as a count variable.

Active Coping.

Adolescents responded to the Children’s Coping Strategies Checklist- 2nd Revision (CCSC-R2; Sandler et al., 1990) that has been validated with low-income and ethnically diverse samples (Gonzales et al., 2001; Liu et al., 2011).The active coping dimension consisted of six subscales reflecting different strategies (α = .91) and adolescents reported on how often (1= Never to 4= Most of the time) they used each strategy in the past month to deal with stressful situations. The six subscales include: cognitive decision making (α = .74; 4 items; e.g., “You thought about what you could do before you did something.”), direct problem solving (α = .71; 4 items; e.g., “You did something to make things better.”), seeking understanding (α = .71; 4 items; “You thought about why the problem or situation happened”), positivity (α = .67; 4 items; e.g., “You tried to notice or think about only the good things in your life.”), control (α = .75; 4 items; e.g., “You told yourself that you could handle this problem.”), and optimism (α = .71; 4 items; e.g., “You told yourself that in the long run, things would work out for the best.”).

Economic Hardship.

Mothers responded to a measure of economic hardship (Barrera et al., 2001), which consists of four subscales of subjective economic hardship: financial strain (α = .80; 2 items; e.g., “How often do you think that you and the family members in your household will experience bad times, such as poor housing or not having enough food?”), inability to make ends meet (α = .71; 2 items; e.g., “How much difficulty have you had paying your bills?”), not enough money for necessities (α = .87; 4 items; e.g., “We had enough money to afford the kind of clothing we should have.”), and economic adjustment/cutbacks (α = .70; 9 items; e.g., “We shut down the heat or air conditioning to save money even though it made the house uncomfortable”). This scale was validated with a low-income and ethnically diverse sample (Barrera et al., 2001).

Pubertal Status.

Adolescents reported on the Pubertal Developmental Scales (PDS; Peterson et al., 1988), a 6-item self-report measure of pubertal change. Respondents indicate on a four-point scale their current level of development in various domains of growth. Males and females are asked both general and specific questions regarding their pubertal development. For example, males are asked, “Have you noticed a deepening of your voice?” Females are asked, “Have you started your period?” This measure was found to have good internal consistency for males and females in a study over-sampling Hispanic adolescents (Siegel et al. 1999) and demonstrated acceptable internal consistency for males (α = .72) and females (α = .68) in this sample.

Analytic Strategy

To test the hypotheses that 1) active coping will be associated with increased capacity for adaptive physiological regulation and 2) the effects of active coping on cortisol stress responding to an acute school-related stressor will be conditional on adolescents’ prior exposure to school stressors, we utilized PLGCM to simultaneously model distinct aspect of cortisol responding (Gonzales et al., 2018). The piecewise model was based on theoretical understanding of cortisol reactivity suggesting that cortisol levels will be highest in the saliva sample collected immediately after the GPST-A. Thus, cortisol reactivity was modeled to reflect the change in cortisol levels from T1 to T2 and cortisol recovery was modeled to reflect the change in cortisol levels from T2 to T4. Utilizing a piecewise model affords the ability to simultaneously model three relevant HPA indices (i.e., basal cortisol level – intercept growth factor, reactivity – first slope growth factor, and recovery – the second slope growth factor). The main and interactive effects of active coping and school hassles, along with covariates (i.e., gender, time of day, economic hardship, pubertal status, cohort membership, and medication use), were then modeled as predictors of these cortisol growth factors (i.e., intercept and slopes). Gender, cohort membership, and medication use were dummy coded. The measure of school hassles was centered at the median (Med = 1). If the interaction was significant, we then probed for simple effects at different count values of school hassles. Specifically, we examined the effect of active coping on the growth factor at different values of school hassles (i.e., at 0, 1, …, 5; range of school hassles = 0-5).

Mplus (Version 8; Muthen & Muthen, 1998-2017) was employed for all hypothesis testing in which we used maximum likelihood estimation with robust standard errors (i.e., “estimator=mlr” in Mplus) for the PLGCM analysis to handle potentially skewed data and adjust for the clustering effect by speech group (i.e., adding “cluster” command and “type=complex” in Mplus). We conducted Little’s missing complete at random (MCAR) test which show that the hypothesis of MCAR was not rejected (χ2 (df=137) = 145.269, p = .298). Therefore, missing data was handled using full information maximum likelihood. Unstandardized regression coefficients are reported. Table 1 provides descriptive statistics for all study variables.

Table 1.

Descriptive Statistics of Measured Variables

M SD Range Skewness Kurtosis
Active coping 3.07 .51 1.13-4 −.59 .33
School Hassles 1.24 1.14 0-5 .81 .09
Cortisol T1 (nmol/l) 2.31 1.45 .30-10.91 1.79 4.71
Cortisol T2 (nmol/l) 2.56 2.21 .27-15.81 2.67 9.67
Cortisol T3 (nmol/l) 2.27 2.30 .19-18.97 3.26 14.15
Cortisol T4 (nmol/l) 1.7 1.51 .16-13.25 3.07 13.85
Gender .51 .50 0 or 1a −.027 −2.00
Economic hardship .10 1.92 −3.85-6.50 .80 .147
Puberty status 2.21 .63 1-4 .20 −.62
Time of day (in hours) 16.53 .27 15.60-18.75 1.131 7.36
Cohort membership 2.08 .84 1-3 −.144 −1.55
Medication use .14 .33 0 or 1b 2.05 2.19
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a

0 = male, 1 = female.

b

0 = no medication endorsed, 1 = at least one medication endorsed.

Results

Main and Interactive Effects of Active Coping and School Hassles on Cortisol Responses: Piecewise Latent Growth Curve Modeling

Figure 2 illustrates PLGCM and the effects of active coping, school hassles and the interaction between the two on the growth factors of cortisol intercept, reactivity, and recovery to the GPST-A, controlling for gender, time of day, economic hardship, pubertal status, cohort membership, and medication use. Table 2 also presents the estimated parameters and statistics for the effects of these variables along with the covariates. There was no significant effect of active coping, school hassles, or the interaction between the two on cortisol intercept (basal cortisol). Consistent with our hypothesis, there was a main effect of active coping on cortisol reactivity such that a greater dispositional tendency to use active coping significantly predicted lower cortisol reactivity to the GPST-A (B = −.44, p = .03). The interaction between active coping and school hassles was not significantly associated with cortisol reactivity. Note that gender, time of the day, economic hardship, and medication use did not relate to any of the growth factors; however, pubertal development significantly predicted higher basal cortisol levels (B = .29, p < .001).

Figure 2:

Figure 2:

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Active coping, school hassles, and interaction on piecewise latent growth curve model

Table 2.

Parameter estimates for the effects of key predictor variables on the growth factors of cortisol responsivity to the GPST-A

Predictor Outcome Unstandardized B 95% CI [lower, upper] t values Standardized β
Active coping Basal cortisol −0.028 [−0.195, .139] −0.329 −0.012
Active coping Reactivity −0.444* [−0.845, −0.043] −2.176 −0.134
Active coping Recovery 0.087 [−0.164, 0.338] 0.679 0.071
School Hassles Basal cortisol −0.006 [−0.117, 0.104] −0.107 −0.006
School Hassles Reactivity −0.112† [−0.228, 0.005] −1.898 −0.075
School Hassles Recovery 0.039 [−0.045, 0.124] 0.907 0.071
Active coping X School hassles Basal cortisol 0.140 [−0.039, 0.320] 1.538 0.067
Active coping X School hassles Reactivity 0.192 [−0.127, 0.512] 1.178 0.066
Active coping X School hassles Recovery −0.222* [−0.442, −0.002] −1.982 −0.205
Gender Basal cortisol −0.162 [−0.404, 0.079] −1.317 −0.067
Gender Reactivity −0.061 [−0.331, 0.209] −0.442 −0.018
Gender Recovery 0.061 [−0.116, 0.238] 0.670 0.049
Economic hardship Basal cortisol −0.001 [−.0.072, 0.070] −0.027 −0.001
Economic hardship Reactivity −0.012 [−0.101, 0.077] −0.266 −0.014
Economic hardship Recovery −0.008 [−0.073, 0.042] −0.320 −0.024
Puberty status Basal cortisol 0.287** [0.126, 0.447] 3.500 0.149
Puberty status Reactivity −0.022 [−0.240, 0.196] −0.198 −0.008
Puberty status Recovery 0.022 [−.160, 0.204] 0.236 0.022
Medication use Basal cortisol 0.065 [−.271, 0.401] 0.380 0.019
Medication use Reactivity −0.256 [−.590, 0.078] −1.497 −0.053
Medication use Recovery 0.186 [−.064, 0.436] 1.464 0.104
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Note: Covariates are adolescent gender, economic hardship, pubertal status, time of day, and cohort membership (the last two were omitted from the table).

†

p ≤ .10;

*

p ≤ .05;

**

p ≤ .01.

In predicting cortisol recovery to the task, there was a significant interaction between active coping and school hassles on cortisol recovery (B = −.22, p = .048). For ease of interpretation, a negative coefficient of the (second) growth factor indicates faster recovery as recovery is a process of cortisol levels declining over time and a steeper negative coefficient indicates faster recovery. There were no significant simple effects of active coping on recovery when the interaction was probed at lower counts of school hassles (i.e., non-significant for 0-2 school hassles, 84.7% of the adolescents; e.g., at 0 count: B = .31, 95% CI [−0.121, 0.738], p = .159). Probing of the interactive effect at higher counts of school hassles revealed a significant simple effect of active coping on cortisol recovery, such that active coping was associated with faster recovery for adolescents who reported having experienced 3 or more school hassles in the past three months (15.3% for 3-4 school hassles; e.g., 3 counts of school hassles: B = −.36, 95% CI [−0.691, −0.023], p = .036). Figure 3 further illustrates the growth trajectories of reactivity and recovery together for having 0 school hassles and having 3 counts of school hassles for applying low (−1 SD) and high (+1 SD) levels of active coping.

Figure 3.

Figure 3.

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Effect of active coping on growth trajectories of cortisol reactivity and recovery at various counts of school hassles

Note. nmol/L= Nanomoles per liter.

Discussion

Individual differences in the capacity to adapt to stressors have been demonstrated by prior studies and it has been suggested that psychological resources may influence whether an individual can effectively regulate their physiological stress response system to achieve habituation. One such psychological resource may be a dispositional tendency to use active coping strategies. Specifically, active coping may facilitate habituation of the HPA axis, because individuals who have dispositional tendencies to confront challenging situations with active, approach-oriented coping strategies are theoretically better able to modulate their stress response by effectively mounting physiological resources necessary to confront the challenge and subsequently recover. This pattern of responding may lead to habituation over time as active coping allows for greater efficacy in dealing with the stressor and the challenge is gradually perceived as being less stressful. Although prior research has reported a link between dispositional active coping and diurnal measures of cortisol, suggesting that active coping facilitates adaptive stress physiology, the current study tests whether dispositional active coping predicts patterns of cortisol reactivity and recovery to an acute social stressor. Given that habituation of the HPA axis system is partially determined by prior exposure to a stressor that is the same as, or similar to, the acute stressor and the school-relevant nature of the experimental stress task (GPST-A) that was used to generate a stress response, the study also examined whether the active coping would facilitate habituation (i.e., lower reactivity and faster recovery) conditional on prior history of school-related difficulties. Overall, our findings are consistent with the theory of habituation and stressor-specific adaption. Furthermore, findings from this study highlight active coping as a promising psychological resource that may aid in facilitating habituation among adolescents, particularly those who have experienced school-related challenges.

The Role of Active Coping in the Habituation of the HPA Activity

Results from the PLCGM model supported a main effect of active coping such that adolescents who have a greater tendency to use active coping displayed lower cortisol reactivity to the stress task. Furthermore, the interaction between active coping and school hassles significantly predicted cortisol recovery from the stress task. Adolescents who reported greater use of active coping demonstrated faster recovery to the stress task if they had experienced a higher number of school hassles in the recent past (i.e., three or more). This finding supports the hypothesis that dispositional active coping facilitates adaptive HPA responding in the context of a school-related challenge, and that the overall benefits of active coping may be greatest for those with a history of repeated stress exposure in the school domain. These findings thus lend support to our hypothesis that active coping may contribute to individual differences in the ability to habituate.

Findings indicate that active coping, as a main effect, may have played a protective role by providing youth with strategies to reduce their reactivity to the GPST-A. Presumably, these youth may have benefitted from their ability to actively confront the uncontrollable challenge presented by the GPST-A (i.e., through direct problem-solving or positive cognitive restructuring) as well as increased efficacy to meet such challenge. It is important to note that the benefits of active coping to reduced reactivity overall were shown in a sample of youth attending schools in low resource schools with a high proportion of students from minoritized and immigrant families. These youth are often exposed to stressors that are beyond their control, particularly in the school context (Peterson et al., 2016; Roche & Kuperminc, 2012), and some prior studies have shown that active coping may have reduced benefits with respect to psychological and emotional outcomes for these youth (Grant et al., 2003; Liu et al., 2011; Theall et al., 2012). These findings add to the evidence that active coping does indeed have important benefits for this population, supporting reduced HPA reactivity overall in response to the GPST-A.

Dispositional active coping also predicted faster recovery, but this was only shown for adolescents who reported a greater number of prior school hassles (three or more). Recovery rates were not related to active coping for adolescents who reported two or fewer school-related stressors in the past month. Active coping, as measured by this study, encompassed two general strategies for actively approaching a challenge: problem-focused coping and positive cognitive restructuring. These coping styles reflect the practice of either directly solving the problem or changing how you feel/think about the problem if it cannot be solved. It is possible these youths who had recently confronted multiple challenges in the school context may have had more successful experiences applying these coping strategies to deal with school hassles and this form of stress inoculation may have contributed to their faster recovery.

Although our findings lend support to our hypothesis that prior school related stressors would facilitate habituation to the GPST-A, it is not possible to tease out the complex processes and feedback loops involved. Consistent with prior theory (Lazarus & Folkman, 1984) and evidence that stress appraisals are important in HPA axis habituation (Roos et al., 2019), it is possible the youths who had prior experiences navigating school challenges were are also more likely to appraise the speech task as being a manageable challenge rather than an overwhelming threat to their sense of self. The reduced arousal to the task also may have enabled these youth to engage the task and perform successfully. An important consideration is that the GPST-A protocol withholds feedback on the participants’ performance, intentionally placing adolescents in the uncontrollable and uncomfortable position of being judged while not receiving any external cues about the effectiveness of their coping efforts. Adolescents who have had recent struggles in school may be more adept in persisting with their coping efforts. For example, they may have been better able to identify and apply problem-solving techniques in order to develop and deliver a speech. Additionally, they may have been better prepared to accept that their best efforts may not always fully resolve their difficulties and to employ active coping strategies, such as positive cognitive restructuring, that involve changing how they think or feel about the situation. In contrast, adolescents who had not experienced any school hassles in the recent past may have displayed slower recovery to the task partially due to the added novelty of the experience and their relative inexperience in applying these coping strategies to socially-evaluative stressors in the academic domain.

Study Limitations

While there was great care involved in collecting, analyzing, and measuring cortisol samples, there are many other factors beyond the scope of this study that could affect adolescents’ cortisol stress responses. On a logistical level, the cortisol samples in this study were assayed using the single-plate method. As a result, inter- and intra-assay coefficients of variability were not available. In addition, it is possible that stressful experiences spanning as early as the prenatal period could have already impacted the HPA axis system such that the stress responses captured in this study may reflect influences independent of the context being measured. School hassles are also likely to be correlated with other race- and income-related stressors ranging from the neighborhood to family-level environment, that may also influence stress response. Although this study cannot capture all possible influences, it does consider key factors such as economic strain and pubertal stage, which reflect important macro- and micro-level processes, respectively.

On a broader conceptual level, the current study applied a stress habituation paradigm to offer hypotheses about the role of prior and repeated stress exposure on future physiological adaptation to a repeated stressor (Pitman et al., 1988; Thompson & Spencer, 1966). However, while drawing on basic assumptions of this paradigm, we expanded the definition of repeated stress to include a broader range of social challenges that adolescents had experienced within the school domain. This decision was partially supported by one of the nine theoretical criteria for habituation as identified by Thompson & Spencer (1966) that posits habituation of a response to a given stimulus exhibits stimulus generalization to other stimuli that are similar in modality. One important distinction to make regarding the application of the habituation framework is that this framework has often been tested with animal models that afford the ability to control and simplify stimuli. Although this study does not apply the same exact stressor to the participants, it does allow for interpretations of results that are more comparable to the real world where repeated stressors are rarely simple and identical in nature. Future replications will be needed to further test our hypotheses and the interpretations we have offered for the significant moderating effects of prior school stressors in our analyses. Future research should also include other aspects of the habituation process, such as stress appraisals, to understand the mechanisms by which prior experiences lead to habituation and the resources that facilitate habituation and generalization to other challenges.

Certainly, the relation between coping and habituation of HPA activity to repeated stressors is more complex than modeled in this study. For one, habituation is a form of nonassociative learning that involves several interacting mechanisms including negative feedback loops involving repeated stress-induced release of glucocorticoids, response habituation, and an intricate learning and memory system crucial for encoding information regarding previous stress exposures (Grissom & Bhatnagar, 2009). The process of coping is also complex and involves many systems operating at multiple levels. For example, coping efforts can start at the physiological level, which is thought to generate action through psychological mechanisms such as the attentional, emotional, and motivational systems that serve to ameliorate psychological and physiological stress (Zimmer-Gembeck & Skinner, 2016). Thus, coping efforts in relation to habituation of the HPA axis may involve complex interactions at any one of these levels. The current study tests a simpler aspect of this process upon which future studies can build, and also highlights a need for experimental paradigms that can model the relations among coping, HPA activity, and stress exposure.

Study Implications and Future Directions

This study highlights the role active coping may play in the habituation of the HPA axis among ethnically diverse adolescents attending Title 1 middle schools. Adolescents who reported a greater dispositional tendency to use active coping strategies when confronting challenges appeared to have lower cortisol reactivity unconditional on prior exposure to a similar stressor. Thus, adolescents may generally benefit from learning problem-focused coping skills, such as problem-solving or making decisions prior to acting, as these strategies provide concrete and action-oriented approaches to challenges. Adolescents may also benefit from learning positive cognitive restructuring strategies that help increase a sense of positivity, optimism, and control under stressful experiences, as these strategies may reduce psychological distress and promote adaptive physiological responding. The unconditional effects of active coping suggest that youth may be able to apply these strategies to a range of stressful situations and increase their capacity to modulate their physiological stress levels.

Results from this study also raise the question of how to best intervene with adolescents as they navigate through the middle school years. This is especially important for adolescents who are of minoritized ethnic backgrounds or attend schools in low-income communities as they face many psychological threats to feeling like they belong in school, which can impact school attachment and performance. Findings from this study suggest that active coping may be a promising avenue through which to promote adaptive physiological responses to school-related stressors that allow youth to actively confront and persist through the challenge, with potential implications for reducing academic as well as mental health disparities. Beyond learning active coping skills in a general sense, adolescents may benefit from interventions that teach active coping skills and apply them to specific challenging topics that are salient for teens, such as conflict with peers, parents, and teachers. Furthermore, it may be just as important to support adolescents’ understanding that life challenges and adversity are valuable to promote growth and resilience (Yeager & Dweck, 2012). Adolescents may also benefit from the practice of “coping ahead”, which involves the imaginal exposure to a stressor paired with imaginal application of coping strategies. This practice may act as a form of stress inoculation which can help prepare youth to effectively respond to challenges without heightened stress responses. Further research is needed to determine whether this practice may still yield effects on the HPA axis to impact cortisol stress responding.

Footnotes

1

The majority of adolescents reported taking a non-narcotic class of medication (e.g., ibuprofen; n = 39), followed by antihistamines (e.g., Claritin, Zyrtec; n = 14), bronchodilators (n = 12), stimulants (e.g., Adderall; n = 9), antibiotics, (n = 2), antipsychotics (e.g., melatonin; n = 2), expectorants (n = 2), hormonal (i.e., insulin; n = 2), salicylates (i.e., aspirin; n = 2), and antidepressants (n = 1). A subset of adolescents endorsing medication use did not provide enough informatin for classification (n = 6).

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