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. Author manuscript; available in PMC: 2025 Jan 1.
Published in final edited form as: Appl Dev Sci. 2022 Nov 7;28(1):22–32. doi: 10.1080/10888691.2022.2134131

Shifting and Persisting in the Face of Life Stressors: Consequences for Adolescent Health

Aprile D Benner 1,*, Celeste C Fernandez 1, Karen Límon 1
PMCID: PMC10904018  NIHMSID: NIHMS1863975  PMID: 38434488

Abstract

The current study assessed whether greater use of shift-and persist strategies, which entail the reappraisal of stressors (shifting) and endurance through optimism and meaning-making, buffered the associations between life stressors and adolescents’ psychological health (i.e., depressive symptoms, anxiety) and physical health and health behaviors (i.e., self-rated health, sleep quality). Survey data were drawn from a racially/ethnically and socioeconomically diverse sample of 750 9th grade adolescents (53% female). Path analysis revealed racial discrimination, neighborhood risk, and deportation exposure were linked to poorer psychological and physical health, while socioeconomic disadvantage was related to greater anxiety and poorer physical health. Some evidence suggested that shift-and-persist may be protective-reactive, wherein shift-and-persist typically promoted well-being across health domains but more so when the life stressors were at low versus high levels. Shift-and-persist strategies promote both mental and physical health, but the promotive effects appear to be maximized when adolescents’ exposure to life stressors is minimal.

Adolescents face a host of stressors in their lives, spanning mundane daily hassles to more chronic and severe stressors such as socioeconomic disadvantage. A myriad of research has documented the negative toll that stress can exact on the mental and physical health of young people and the inter- and intraindividual assets that can promote resilience in the face of stress (Masten & Obradović, 2006; Rutter, 2012). The identification of malleable resources that buffer the harmful impact of life stressors is posited as critically important (Luthar & Zelazo, 2003), particularly for intervention and prevention efforts that seek to promote resilience in the face of adversity at this time in the life course. One set of psychological resources gaining empirical and clinical interest are shift-and-persist strategies, which entail the reappraisal of stressors (shifting) and endurance through optimism and meaning-making (persisting; Chen & Miller, 2012). Much of the nascent research on shift-and-persist strategies has focused on their value for buffering the detrimental impact of low socioeconomic status (SES) on health outcomes. We seek to extend this research by examining a greater breadth of uncontrollable life stressors encountered during adolescence and a more extensive set of mental and physical health indicators.

Adversity, Adolescent Well-being, and Shift-and-Persist Strategies

Risk and resilience frameworks have elucidated the pernicious effects that chronic, severe, and uncontrollable stressors can exact on the minds and bodies of children and adolescents while acknowledging wide variation in the adaptation of those exposed to significant adversity (Luthar et al., 2000). No marker of adversity has received greater attention than socioeconomic disadvantage, with greater levels of socioeconomic disadvantage, broadly defined, consistently linked to a multitude of negative psychological and physical health challenges in childhood and adolescence (McLoyd, 1998). Yet adolescents can face a host of other significant stressors in the proximal contexts of their daily lives (Bronfenbrenner & Morris, 2006; García Coll et al., 1996) that have the potential to disrupt mental and physical health, including discrimination and marginalization (Benner et al., 2018) or risky neighborhood environments (Leventhal & Brooks-Gunn, 2000). Moreover, recent sociohistorical events have brought hostilities around documentation status to the forefront (Hickel & Bredbenner, 2020), which also can exact a toll on undocumented youth or those from mixed-status households (Giano et al., 2020). The current study investigates the unique role of each of these stressors for adolescents’ well-being.

In considering who is resilient in the face of substantial stress, much attention has been placed on psychological adaptation—specifically, those who exhibit high or better-than-expected levels of psychological adjustment given their exposure to stressful or traumatic events or life circumstances (Masten & Obradović, 2006). Resilience in physical health, in contrast, has received far less attention, yet psychobiological models of risk suggest that significant life stressors have consequences for both psychological and biological systems, getting under the skin to impact health and well-being (Chen & Miller, 2012). As such, in the current study, we place attention to both psychological well-being (i.e., depressive symptoms, anxiety), physical health (i.e., general health ratings), and health behaviors (i.e., disrupted sleep). Attention to a broad array of psychological and physical health indicators is purposeful, as much of the extant literature has focused on depression and health challenges (e.g., asthma, high BMI). Given that studies have documented higher rates of anxiety than depression in the population (Klaufus et al., 2022) and that ratings of general health are robust indicators of physical health across the life span (DeSalvo et al., 2006), both are included as key well-being indicators in the current study.

Finally, what promotes resilience, or thriving in the face of substantial stressors, has been the focus of extensive theorizing and scholarship, centering primarily on the individual psychological resources that resilient children possess and the external assets of young people’s everyday contexts (Luthar et al., 2000). In their psychobiological model, Chen and Miller (2012) posit that shift-and-persist strategies are a potential protective factor that can support adaptation when encountering adversity, resulting in resilience in psychological and physical health. Specifically, this model suggests that stressors trigger psychological responses that span cognition, emotion, and behavior as well as health behaviors. Psychological responses and health behaviors, in turn, are consequential for short-term physiological responses across endocrine (e.g., hypothalamic-pituitary-adrenocortical (HPA) axis), autonomic (e.g., sympathetic nervous system), and inflammatory response systems When chronically activated, these acute physiological responses can exact a pathogenic toll on the body in terms of chronic inflammation and dysregulation of other bodily systems (e.g., metabolic, cardiovascular). Chen and Miller (2012) argue that these problematic psychobiological processes can be disrupted by adaptive shift-and-persist strategies, which involve shifting one’s mindset to both accept and reappraise the stressor, maintaining optimism, and persisting through larger meaning making (Chen & Miller, 2012). In particular, shift-and-persist strategies are posited to promote psychological well-being both within and across time by attenuating negative appraisals and lowering the likelihood that individuals will engage in negative health behaviors.

Limited empirical tests of this model, much of it cross-sectional, suggest that shifting and persisting may indeed be protective, with higher levels of shift-and persist strategies buffering the associations between both general life stressors and economic hardship with adolescent depression (Christophe et al., 2019; Dulaney et al., 2018) as well as buffering the relations of economic adversity with asthma control and symptoms (Chen et al., 2011; Lam et al., 2018), body mass index (Kallem et al., 2013), and inflammatory processes (Chen et al., 2015). It is posited that shifting and persisting is a particularly effective coping resource when individuals are faced with uncontrollable stressors (Chen, 2012), and initial investigations have considered the buffering role of shift-and-persist in the face of uncontrollable stressors beyond economic hardship. For example, there is initial evidence that shift-and-persist strategies may attenuate the link between discrimination and depression for Latinx youth, although this buffering role varies by adolescents’ racial/ethnic identity (Christophe et al., 2019; Stein et al., in press). Likewise, in the adult literature, evidence has documented both concurrent and lagged protective effects of shift-and-persist on the relation between discrimination and depression (Christophe & Stein, 2021) as well in the links between subjective social status and both negative affect and health (O’Leary et al., 2021).

We seek to add to this burgeoning research base by examining whether shift-and-persist strategies can promote psychological and physical well-being when adolescents encounter various uncontrollable stressors in their everyday lives. Specifically, we seek to replicate existing work on the buffering role of shift-and-persist on low-SES and discrimination, expanding this to examine a broader set of psychological and physical health indicators. Moreover, the shift-and-persist model (Chen & Miller, 2012) also highlights the challenges of uncontrollable stressors in family and neighborhood environments, suggesting that shift-and-persist may be protective when adolescents face stressors within these contexts, which we seek to test through our attention to neighborhood risk and deportation exposure. It should also be noted that the initial shift-and-persist theoretical model focused on health outcomes, which is reflective of much of the extant research centered on asthma, BMI, and bodily inflammation.

Current Study

The current study draws on a racially/ethnically and socioeconomically diverse community sample in the Southwestern U.S. In the first research aim, we sought to replicate a host of prior research by documenting the negative relations between of a number of uncontrollable life stressors (i.e., racial/ethnic discrimination, deportation exposure, neighborhood risk, socioeconomic disadvantage) and adolescents’ psychological health (i.e., depressive symptoms, anxiety) and physical health and health behaviors (i.e., self-rated health, sleep quality). We then examined whether shift-and persist was associated with better health outcomes as well as whether it buffered the negative consequences of life stressors. Consistent with theory (Chen & Miller, 2012) and the prior empirical research reviewed above, we hypothesized that higher levels of shift-and-persist would promote better health and would attenuate the negative link between life stressors and adolescents’ health outcomes. We considered shifting and persisting together, as opposed to modeling the potential moderating effects separately, as Chen and Miller (2012) indicate that “there is something critical to the combination of shifting plus persisting that reduces risk” (p. 141). All modeled relations were considered cross-sectionally as well as longitudinally to better explicate both point-in-time relations as well as more persistent impacts of shift-and-persist as adolescents grow and develop. This allowed us to replicate existing cross-sectional work as well as add to the burgeoning longitudinal research on shift-and-persist.

METHODS

Participants and Procedures

The current study utilized survey data from the second and third waves of an ongoing project in the Southern U.S. entitled Project PISCES, which was approved by the University of Texas Institutional Review Board. The original sample of participants (N = 1,010) were first recruited in 8th grade (Wave 1) from 13 middle schools (10 public or charter, 3 private). All 8th grade students from the targeted middle schools were recruited in school during advisory periods, and 43% of students returned parent consent forms. Recruitment was divided into two cohorts: the first cohort began Wave 1 in the 2016-17 school year (n = 463), and cohort 2 began in the 2017-18 school year (n = 547). Wave 2 occurred one year later when most participants had transitioned to high school and were in 9th grade (N = 751), and Wave 3 occurred one year after Wave 2 (N = 692). The analytic sample included 750 participants from Wave 2 who attended 76 different schools (see Table 1 for demographic information); one adolescent was excluded because they lacked information on their Wave 2 school, the clustering variable. The analytic sample was 53% female and racially/ ethnically diverse (42% White, 32% Latino, 12% biracial/other, 8% Asian American, 6% Black). The mean highest level of education earned by the adolescents’ parents was an associate’s degree, and 39% of participants were economically disadvantaged (i.e., qualified for Free- or Reduced-price Lunch). Most participants completed surveys online in Waves 2 and 3, with a small number completing paper-and-pencil or phone-based surveys with trained research assistants; adolescents were compensated $25 for survey completion. The surveys were available in both English and Spanish.

Table 1.

Participant Demographics

N %
Race/ethnicity
   African American/Black 44 5.9
   Latino/a/x 241 32.1
   Asian American 62 41.5
   White 311 8.3
   Biracial/other 92 12.3
Gender
   Female 397 53.6
   Male 344 46.4
Generational Status
   1st generation (participant born outside of the U.S.) 54 7.3
   2nd generation (participant U.S.-born with at least one foreign-born parent) 237 31.9
   3rd generation (both participant and both parents U.S.-born) 451 60.8
Socioeconomic Disadvantage
   Student was economically disadvantaged 284 39.2
   Student was not economically disadvantaged 441 60.8
Type of School Attended by the Student in Wave 2
   Private 27 3.6
   Public 669 89.9
   Charter 48 6.5
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Note. Total possible N = 750.

Measures

All measures of life stressors and shift-and-persist strategies were assessed at Wave 2; psychological and physical health outcomes were assessed at Waves 2 and 3. Descriptive statistics and bivariate correlations appear in Table 2.

Table 2.

Descriptive Statistics and Bivariate Correlations among Study Variables

1 2 3 4 5 6 7 8 9 10 11 12 13
1. W2 Discrim
2. W2 Deport .22***
3. W2 Nbhd risk .32*** .19***
4. W2 Low SES .11** .15*** .33***
5. W2 Shift-Persist −.10** −.07* −.13*** −.03
6. W2 Depress .23*** .09* .23*** .05 −.55***
7. W3 Depress .18*** .07 .14*** .04 −.40*** .60***
8. W2 Anxiety .16*** .00 .12** −.02 −.34*** .58*** .47***
9. W3 Anxiety .10** .02 .06 −.01 −.29*** .41*** .54*** .67***
10. W2 Sleep −.17*** −.08* −.19*** −.05 .33*** −.56*** −.45*** −.43*** −.31***
11. W3 Sleep −.13** −.04 −.13** −.07 .27*** −.43*** −.58*** −.32*** −.38*** .59***
12. W2 Health −.13** −.13*** −.21*** −.20*** .39*** −.41*** −.31*** −.33*** −.25*** .24*** .23***
13. W3 Health −.15*** −.12** −.18*** −.19*** .29*** −.34*** −.41*** −.29*** −.34*** .27*** .34*** .57***
Mean .77 .17 .68 2.71 19.65 .90 1.01 1.04 1.09 2.52 2.43 2.41 2.35
SD .98 .38 .59 1.97 6.00 .56 .58 .55 .57 1.16 1.18 1.02 1.04
N 732 723 716 596 746 736 679 736 677 736 678 734 680
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Note. Total possible N = 750.

*

p < .05,

**

p < .01,

***

p < .001.

Discrim = Discrimination. Deport = Deportation Exposure. Nbhd = Neighborhood. Health = Self-Rated Health.

Life Stressors

Racial Discrimination.

The Adolescent Discrimination Distress Index (Fisher et al., 2000) assessed peer-perpetrated racial/ethnic discrimination with three items (e.g., “Were you called insulting names by other kids because of your race/ethnicity?”). Participants rated the frequency on a scale of 0 (never) to 4 (a whole lot). Consistent with prior work (Rivas-Drake et al., 2009), if the participant reported “never” experiencing the event, the participant received a score of zero; if the participant reported experiencing it “once/twice” or more, the participant received a score of one. The dichotomized items were summed to create a composite measure.

Deportation Exposure.

Two items assessed whether a close friend/family member or someone else they knew (but were not close to) had been deported (e.g., “Someone I know but do NOT feel close to has been deported.”). The response options were 0 (no) to 1 (yes). Endorsement of either item was coded as having deportation exposure (1); those endorsing neither received a score of zero.

Neighborhood Risk.

Using an 11-item scale (Bámaca et al., 2005; Supple et al., 2006), adolescents responded from 0 (strongly disagree) to 3 (strongly agree) how much they agreed with statements about various aspects of neighborhood risk (e.g., “There is a lot of crime”, “Many families are poor”). Higher mean scores indicated greater perceived neighborhood risk (α = .92).

Socioeconomic Disadvantage.

The socioeconomic status of adolescents’ families was determined by school records data indicating whether the student qualified for free or reduced-price lunch (1= Student is socioeconomically disadvantaged, 0 = Student is not socioeconomically disadvantaged).

Shift-and-Persist

Eight items assessed participants’ shift-and-persist strategies (Chen et al., 2015), with each rated on a scale of 0 (never) to 4 (always). The four shifting strategies (e.g., “When something stressful happens in my life, I think about what I can learn from the situation”) and four persisting strategies (e.g., “I believe there is a larger reason or purpose for my life”) were rates on a scale of 0 (not true at all) to 4 (true all the time). Higher summed scores indicated greater use of shift-and-persist strategies (α = .88).

Adolescent Health Outcomes

Depressive Symptoms.

The 10-item Center for Epidemiologic Studies Depression scale (CES-D) assessed depressive symptoms (Andresen et al., 1994). Participants rated the extent they experienced each item (e.g., “I felt depressed,” “I could not get going”) in the past week on a scale from 0 (rarely or none of the time (less than 1 day) to 3 (most of all the time (5-7 days)). Higher mean scores represented greater levels of depressive symptoms (α = .80).

Anxiety.

The 9-item generalized anxiety disorder subscale of the revised Screen for Child Anxiety Related Emotional Disorders measured anxiety (Muris et al., 1998). Items (e.g., “I worry about the future,” “People tell me I worry too much”) were rated on a scale from 0 (almost never) to 2 (often), with higher mean scores indicating greater anxiety (α = .89).

Sleep Quality.

Sleep quality was assessed using two items tapping into how often adolescents had trouble falling asleep and staying asleep through the night over the past four weeks. Ratings ranged from 0 (never in the past 4 weeks) to 4 (5 or more times a week). Items were reverse-coded and averaged, with higher scores indicating better sleep quality (r = .61**).

General Health.

Adolescents rated their general health using one item (i.e., “In general, how would you rate your health?”) on a scale 0 (poor) to 4 (excellent). This measure is commonly used in population health studies and is consistently related to measures of physical health and mortality (DeSalvo et al., 2006).

Covariates

Analyses controlled for participant cohort (9th grade in 2017-18 versus 2018-19), race/ethnicity, gender, immigrant family status. Supplemental analyses included school mobility between Waves 2 and 3 as an additional covariate. For the supplemental analyses, we were not able to control for health indicators at Wave 2 due to poor model fit. We also did not account for Wave 1 health indicators as Wave 1 occurred before the transition to high school, which could potentially conflate school transition challenges with challenges related to the uncontrollable stressors under study (e.g., Benner, 2011).

Analysis Plan

Path analysis models were conducted in Mplus 8.2 using full information maximum likelihood to address missing data and CLUSTER to account for adolescents nested in high schools. The primary analyses used cross-sectional Wave 2 data to determine point-in-time associations between life stressors and adolescents’ psychological and physical health and health behaviors and the moderating impacts of shift-and-persist. Three hierarchical models were conducted for each stressor separately. We first regressed each of the health indicators (i.e., depressive symptoms, anxiety, sleep quality, self-reported health) on the life stressor and the covariates (Model 1). In Model 2, shift-and-persist was added as a predictor of psychological and physical health and health behaviors, and we then integrated the interaction between each life stressor and shift-and-persist as a predictor of well-being (Model 3). When significant interactions emerged, simple slope analyses were used to determine the extent to which the life stressor was associated with the health indicator when adolescents’ shift-and-persist use was high (1 SD above the mean) versus low (1 SD below the mean). Given the uncontrollable nature of the stressors under study combined with the fact that prior work on shift-and-persist has focused on single stressors and that not all students experience the same stressors, we chose to examine the associations for each life stressor in separate models in order to capture how the moderating role of shift-and-persist uniquely applies to each stressor. Supplemental longitudinal analyses included a parallel set of models using adolescents’ Wave 3 psychological and physical health outcomes.

Results

Primary Analyses

Results from Model 1 showed that greater life stress was linked to poorer psychological (see upper portion of Table 3) and physical health (see lower portion of Table 3). Specifically, greater racial discrimination was significantly associated with greater depressive symptoms and anxiety and poorer sleep quality and self-reported health. Likewise, for neighborhood risk, higher levels of risk were linked to greater depressive symptoms and anxiety and poorer sleep quality and self-rated health. Deportation exposure was significantly associated with greater depressive symptoms and poorer health but not significantly associated with sleep or anxiety. Lastly, lower SES was related to poorer self-reported health and greater anxiety but was not significantly related to sleep quality or depression.

Table 3.

Shift-and-Persist as a Moderator of the Links between Life Stressors and Health

Depressive Symptoms Anxiety
Model 1 Model 2 Model 3 Model 1 Model 2 Model 3
β (SE) β (SE) β (SE) β (SE) β (SE) β (SE)
Discrimination
Peer racial discrimination .25 (.03) *** .18 (.03) *** .18 (.03) *** .18 (.03) *** .14 (.03) *** .14 (.03) ***
Shift-and-persist −.52 (.03) *** −.52 (.03) *** −.29 (.03) *** −.29 (.02) ***
Discrim-by-shift-and-persist .03 (.03) .06 (.02) **
R 2 .09*** .35*** .35*** .15*** .23*** .24***
Deportation Exposure
Deportation exposure .09 (.04) * .05 (.03) .05 (.03) .02 (.03) −.01 (.03) .00 (.03)
Shift-and-persist −.54 (.02) *** −.53 (.03) *** −.31 (.03) *** −.33 (.03) ***
Deport-by-shift-and-persist −.03 (.04) .06 (.02) **
R 2 .04** .32*** .32*** .12*** .22*** .22***
Neighborhood Risk
Neighborhood risk .27 (.04) *** .19 (.03) *** .19 (.03) *** .17 (.03) *** .12 (.03) *** .12 (.03) ***
Shift-and-persist −.51 (.03) *** −.51 (.03) *** −.29 (.02) *** −.29 (.02) ***
Nbhd risk-by-shift-and-persist −.04 (.03) .01 (.03)
R 2 .10*** .35*** .35*** .15*** .23*** .23***
Low SES
Low SES .00 (.06) .01 (.06) .02 (.05) −.09 (.04)* −.08 (.04) −.08 (.04)*
Shift-and-persist −.54 (.03) *** −.57 (.04) *** −.31 (.03) *** −.36 (.04) ***
Low SES-by-shift-and-persist .05 (.05) .09 (.04) *
R 2 .04** .32*** .32*** .13*** .22*** .23***
Sleep Quality Health
Model 1 Model 2 Model 3 Model 1 Model 2 Model 3
β (SE) β (SE) β (SE) β (SE) β (SE) β (SE)
Discrimination
Peer racial discrimination −.20 (.04) *** −.16 (.04) *** −.16 (.04) *** −.12 (.03) *** −.07 (.03) * −.07 (.03) *
Shift-and-persist .30 (.04) *** .29 (.03) *** .37 (.02) *** .37 (.03) ***
Discrim-by-shift-and-persist −.08 (.04) * −.03 (.03)
R 2 .07*** .15*** .16*** .09*** .23*** .23***
Deportation Exposure
Deportation exposure −.08 (.04) −.06 (.04) −.07 (.04) −.08 (.03) * −.05 (.03) −.06 (.03)*
Shift-and-persist .31 (.03) *** .34 (.04) *** .38 (.03) *** .40 (.03) ***
Deport-by-shift-and-persist −.08 (.04) * −.06 (.03) *
R 2 .04** .13*** .14*** .09*** .23*** .23***
Neighborhood Risk
Neighborhood risk −.21 (.04) *** −.16 (.03) *** −.16 (.03) *** −.18 (.04) *** −.12 (.03) *** −.12 (.03) ***
Shift-and-persist .29 (.03) *** .29 (.03) *** .36 (.03) *** .36 (.03) ***
Nbhd risk-by-shift-and-persist .01 (.04) −.02 (.04)
R 2 .07*** .15*** .15*** .11*** .24*** .24***
Low SES
Low SES −.05 (.04) .04 (.03) .04 (.03) −.10 (.04) * −.11 (.04) ** −.11 (.04) **
Shift-and-persist .32 (.03) *** .37 (.05) *** .38 (.02) *** .39 (.03) ***
Low SES-by-shift-and-persist −.09 (.05) −.02 (.05)
R 2 .03* .13*** .13*** .09*** .23*** .23***
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Note. Total possible N = 750. Psychological and physical health indicators included simultaneously for each stressor under study. Standardized coefficients are presented. Bold denotes significant associations.

*

p < .05,

**

p < .01,

***

p < .001. Covariate effects presented in Supplemental Table S1.

When shift-and-persist strategies were added to the models (see Model 2, Table 3), we found that greater use of shift-and-persist was significantly related to fewer depressive symptoms and less anxiety as well as better sleep quality and self-reported health. In general, the stressors under study continued to be associated with poorer health with the exception of deportation exposure and its link to both depressive symptoms and self-reported general health. Our final model (Model 3, Table 3) integrated interactions between each life stressor and shift-and-persist. Significant interactions were observed for each life stressor except neighborhood risk.

In examining interactions related to anxiety, more frequent discriminatory experiences were linked to greater anxiety, but this relation was stronger for adolescents high in shift-and-persist (b = .11, p < .001) and only marginally significant for those low in shift-and-persist (b = .05, p =.066; see Figure 1a). In addition, while a significant deportation exposure-by-shift-and-persist interaction effect was observed for anxiety, the simple slope analyses showed that the slopes for those high and low in shift-and-persist did not differ from zero (see Figure 1b). Finally, being socioeconomically disadvantaged was related to lower levels of anxiety for those low in shift-and-persist (b = −.17, p < .001), but this relation was not significant for those high in shift-and-persist (b = −.01, p = .850; see Figure 1c).

Figure 1.

Figure 1.

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The Moderating Role of Shift-and-Persist on the Link between Life Stressors and Psychological Health

Note. Unstandardized coefficients are presented.

In considering sleep quality, for adolescents high in shift-and-persist, more frequent discriminatory experiences were linked to poorer sleep quality (b = −.29, p < .001; see Figure 2a), whereas this association was not significant for adolescents low in shift-and-persist (b = −.10, p = .104). In addition, deportation exposure was linked to poorer sleep quality for adolescents high in shift-and-persist (b = −.44, p < .001; see Figure 2b), but these associations were not significant for adolescents low in shift-and-persist (b = .02, p = .902).

Figure 2.

Figure 2.

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The Moderating Role of Shift-and-Persist on the Link between Life Stressors and Physical Health

Note. Unstandardized coefficients are presented.

For the final outcome—self-rated health—a significant interaction effect was observed for deportation exposure and shift-and-persist (see Figure 2c). Self-rated health was worse for those who had deportation exposure than those who did not for adolescents high in shift-and-persist (b = −.30, p < .01), but this relation was not significant for adolescents low in shift-and-persist (b = −.01, p = .899). Overall, the findings from the primary analyses suggest that those high in shift-and-persist were more reactive to life stressors than those who reported little use of shift-and-persist strategies; however, across all levels of each of the stressors under study, those high in shift-and-persist generally displayed better psychological and physical health compared to those low in shift-and-persist.

Supplemental Analyses

To determine whether the moderating effects of shift-and-persist endured over time, we conducted a parallel set of supplemental models that examined the direct and interactive effects of stressors and shift-and-persist on adolescents’ psychological and physical health outcomes one year later. Results of the supplemental longitudinal analyses generally reflected what was found in the primary analysis (see Supplemental Tables S2 and S3 in Supplemental Materials). For the direct relationships between life stressors and psychological and physical health, we observed results that were identical to those observed in the primary analyses—that is, life stressors (measured at W2) were linked to poorer psychological and physical health in Wave 3 (measured at W3). The one exception was that the link between deportation exposure and depressive symptoms was significant in the primary but not supplemental analyses. Likewise, the main effects of shift-and-persist strategies also paralleled those observed in the primary analyses, such that Wave 2 shift-and-persist was associated with better Wave 3 psychological and physical health outcomes across all models. That said, most of the interaction effects observed in the primary analyses did not persist in the longitudinal models. Instead, a new significant interaction emerged; the interaction effect between socioeconomic disadvantage and shift-and-persist was significant for self-rated general health. The test of simple slopes showed that being socioeconomically disadvantaged was related to poorer health for adolescents high in shift-and-persist (b = −.10, p < .01; see Figure S1), but this relation was not significant for those low in shift-and-persist (b = −.05, p = .056); this is reactivity to socioeconomic disadvantage for adolescents’ high in shift-and-persist is consistent with the patterns observed between socioeconomic disadvantage and shift-and-persist in the primary analysis.

Discussion

Adolescents encounter stressors great and small in all aspects of their daily lives, but significant stressors in particular can derail developmental trajectories. Theories of risk and resilience (Luthar & Zelazo, 2003; Masten & Obradović, 2006) seek to highlight the personal resources that young people possess that promote well-being in the face of adversity, and the current study investigated the extent to which one set of personal resources—shift-and-persist strategies—might buffer the detrimental impact of a host of significant life course stressors on adolescents’ mental and physical health and well-being. The stressors targeted were far-reaching, reflective of experiences in the proximal contexts that adolescents inhabit as the grow and develop (Bronfenbrenner & Morris, 2006), and were informed by both theories on shift-and-persist (Chen & Miller, 2012) and the larger empirical base (Christophe et al., 2019; Dulaney et al., 2018).

In line with prior research, the life stressors under study, which were uncontrollable in nature, were generally related to poorer psychological outcomes, lower ratings of general health, and poorer sleep quality, and this was most consistently observed when considering discrimination and neighborhood risk. The more limited direct effects of low SES (with the exception of its link to anxiety and general health) were particularly notable and likely due, at least in part, to issues of measurement. In the current study, students’ eligibility for free or reduced priced lunch served as a marker for SES; however, other measures such as family wealth, household income, income-to-needs ratios, or material deprivation might provide a more robust assessment of socioeconomic disadvantage (Diemer et al., 2013) and should be investigated in future research. Additional supplemental analyses tested the associations between SES, shift-and-persist, and physical and psychological health using parental education as the marker for SES, with these results, which were generally consistent with those using FRPL as a marker of economic disadvantage, found in Tables S4 and S5 and Figures S2 and S3 of the supplemental materials.

The current study findings also illustrate the consistent promotive impact that shift-and-persist has for psychological well-being and physical health and health behaviors both within and across time. In their psychobiological model, Chen and Miller (2012) highlight the benefits of shift-and-persist for psychological responses when individuals are faced with life stressors or are embedded within difficult family or neighborhood environments, and the findings observed here are consistent with this theoretical model and related empirical findings (Chen et al., 2011, 2015; Lam et al., 2018). It is possible that bidirectional effects may be at play, such that positive mental and physical health may enable adolescents to enact more shift-and-persist strategies, a line of inquiry ripe for future investigation.

Much of the theorizing around and empirical research on shift-and-persist has suggested that such strategies would be most promotive for those facing the greatest stressors (e.g., those experiencing economic disadvantage), something not found in the current study. Instead, the results of the current study highlight the potential protective-reactive nature (Luthar et al., 2000) of shift-and-persist, wherein shift-and-persist promoted well-being across domains but generally moreso when the uncontrollable stressors under study were at low versus high levels. The protective-reactive role of shift-and-persist was quite consistent across the stressors considered in the current study, although replication work is necessary to provide additional evidence of these moderated relations. The inconsistencies with prior literature on shift-and-persist may be related, in part to sample composition, as much of the nascent scholarship on shift-and-persist has focused on White and/or Asian samples (e.g., Chen et al., 2011, 2015; Christophe et al., 2021; O’Leary et al., 2021), and much of this work is laboratory based. Future research with large and diverse samples of minoritized youth are critical for replicating current findings. It is also possible that shift-and-persist strategies are more in line with high-effort coping, which has been found to exacerbate rather than mitigate the impact of stress on well-being (Hill & Hoggard, 2018; Hsieh et al., 2014). Likewise, to the extent that the accumulation of stressors across time chip away at adolescents’ use of shift-and-persist strategies, this could also compromise its effectiveness as a stress buffer (Evans & Kim, 2013). That said, given the strong biological underpinnings of the shift-and-persist model (Chen & Miller, 2012) and the fact that much of the nascent research base on shift-and-persist has focused on outcomes more strongly tied to physical health (e.g., asthma control, cardiovascular risk, inflammatory regulation, BMI; Chen et al., 2011, 2013; Kallem et al., 2013; Lam et al., 2018), more investigation is warranted examining the links between stressors such as those included in the current study, shift-and-persist, and both specific health indicators and related “under-the-skin” responses (e.g., allostatic load, inflammatory response) that can be elicited by significant and chronic stressors (McEwen, 1998; Steptoe et al., 2007). Such work is critical for determining whether shift-and-persist might serve a stronger buffering role for more biologically-based outcomes.

Taken together, the current study, employing a large and racially-ethnically and socioeconomically diverse sample of adolescents, highlighted the unique role of shift-and-persist when considering the links between a host of relevant significant stressors and adolescents’ mental and physical health. While this study provides unique insights into shift-and-persist, limitations must be acknowledged as well. As noted above, some measures, such as socioeconomic disadvantage, were more limited in scope. This is also an issue with the deportation exposure measure. Given the larger sociohistorical context during the time of the data collection, the study team opted to not inquire specifically about the documentation status of participants and their families, which is a major stressor in individuals’ lives (Cavazos-Rehg et al., 2007) and should be examined in future scholarship. Additionally, the majority of the evidence for the protective-reactive nature of shift-and-persist was observed cross-sectionally versus longitudinally; however, the promotive nature of the main effects of shift-and-persist persisted across time. These findings suggest that shift-and-persist may make adolescents more reactive to stress in the short- but not long-term, and this is an important area of inquiry for future studies. The findings reported in the current study highlight the promise of shift-and-persist for supporting adolescents facing adversity, but the nuances of the protective effects indicate the importance of additional study before integrating the promotion of shift-and-persist strategies into intervention and prevention studies.

Supplementary Material

Supp 1

Acknowledgements:

The authors acknowledge grants from the National Institute for Child Health and Human Development (NICHD; K01HD087479) to the first author and from NICHD to the Population Research Center at UT Austin (P2CHD042849). Opinions reflect those of the authors and not necessarily those of the granting agencies.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, Aprile D. Benner, upon reasonable request.

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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
NIHMS1863975-supplement-Supp_1.docx (91.5KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, Aprile D. Benner, upon reasonable request.

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