Coupled Changes in Daily Control Beliefs and Cognition: Variations by Education and Income

Abstract

Although the association between perceived control and long-term trajectories of cognitive functioning is well-established, little is known about how day-to-day changes in control are linked to daily cognition or how this relationship may differ across socioeconomic lines. This study examined whether daily changes in perceived control were coupled with dynamic shifts in episodic memory and the extent to which this association was pronounced for middle-aged and older adults with lower education or income. We analyzed 14 days of data from the Modifiable Antecedents of Memory and Behavior in Adulthood (MAMBA) Study using multilevel models (n = 208, M_age = 54 years, range = 30–81; 64% female). Main effect models showed that daily, within-person increases in perceived control were positively, but not significantly, associated with changes in episodic memory (γ = .055, p = .068). Moderation models indicated that this relationship depended on individual differences in income, but not education: The within-person association between daily perceived control and episodic memory emerged for those with lower (γ = .123, p = .002), but not higher (γ = −.014, p = .735), levels of income. Findings inform theories of lifespan development in providing initial evidence that micro-longitudinal increases in perceived control are linked to dynamic changes in daily cognition for socioeconomic populations at increased risk of cognitive declines.

Keywords

Motivation agency longitudinal study free recall daily control beliefs daily memory dynamic processes

Introduction

The beliefs people hold about their capacity to influence important outcomes in their lives matter. These perceptions of control reflect a central motivational resource that promotes positive health behaviors and buffers against risk of chronic disease, functional losses, and cognitive decline in midlife and old age (Hamm, Turner, et al., 2025; Hong et al., 2021; Robinson & Lachman, 2018). For example, Hong et al. (2021) showed that longitudinal increases in perceived control predicted lower odds of subsequent cognitive decline in a national U.S. sample of over 12,000 older adults. Although research has consistently shown perceived control predicts healthier cognitive aging over extended time periods, little is known about how daily fluctuations in control are linked to changes in daily cognition and the extent to which this relationship may depend on socioeconomic characteristics. Observational work on this topic based on multiple short-term assessments is important because it may identify changes in perceived control as a dynamic and modifiable psychosocial factor with implications for cognition. This study thus examined (a) whether increases in daily perceived control over memory predicted corresponding improvements in daily episodic memory and (b) the extent to which this association was pronounced for middle-aged and older adults with lower socioeconomic status (SES) in the form of less education or income.

Perceived Control and Cognitive Functioning

Prior research has largely focused on individual (between-person) differences in the relationship between perceived control and cognitive functioning. For instance, Infurna and Gerstorf (2013) found that higher baseline levels of perceived control prospectively predicted less episodic memory decline over a 4-year period in a sample of over 4,000 middle-aged and older adults. These results are consistent with a growing body of evidence suggesting that higher baseline levels of, and subsequent increases in, perceived control are associated with slower macro-longitudinal declines in cognition over time periods of up to 20 years (Hamm, Lachman, et al., 2025; Hamm, Turner, et al., 2025; Hong et al., 2021; Robinson & Lachman, 2018).

Less is known about the dynamic, within-person relationship between perceived control and cognition in daily life because past studies have typically assessed both variables infrequently and over extended time periods. This approach fails to capture ecological realities, wherein perceptions of control and cognitive performance are not static in nature, but rather exhibit dynamic and meaningful fluctuations from one day to the next (Cerino et al., 2020; Klepacz et al., 2026; Sliwinski et al., 2006). Lachman’s (2006) process model suggests that these daily fluctuations in perceived control and cognition should be coupled or linked via motivation (e.g., effort), affective (e.g., anxiety, stress), and health behavior pathways (e.g., physical activity). These processes are posited to be reciprocal in nature, such that day-to-day changes in perceived control are also theorized to occur, in part, due to the influence of day-to-day changes in motivation, affective, health behavior, and cognitive processes.¹

Only two studies to date have examined the relationship between perceived control and cognition at the daily level. Seminal research by Neupert and Allaire (2012) assessed 36 older adults over 60 days and found that, on days when individuals reported increased perceived control, they had improved performance on executive functioning and episodic memory tasks. Subsequent research by Robinson and Lachman (2020) followed an adult lifespan sample of 145 individuals over 7 days and observed a similar pattern, such that increases in daily control were linked to corresponding shifts in daily cognition. These findings provide preliminary evidence that changes in perceived control may be coupled with corresponding shifts in cognition at the micro-longitudinal level. However, further research is needed to systematically evaluate this relationship in studies that combine larger adult lifespan samples with more frequent daily assessments.

The Moderating Role of Socioeconomic Status

Open questions also remain regarding whether perceived control is more or less protective for lower SES populations. Although there is mixed evidence linking SES to faster rates of cognitive decline (Seblova et al., 2020), low SES has consistently been associated with both lower levels of cognitive functioning and increased risk of cognitive impairment (Chapko et al., 2018; Wang et al., 2023). Theories of control and reserve capacity (Gallo & Matthews, 2003; Lachman, 2006) suggest perceived control should have pronounced benefits for individuals with lower SES who face more day-to-day adversities and encounter greater environmental stressors that can undermine cognitive functioning (Aguila & Casanova, 2020; Clouston et al., 2020; Neupert et al., 2006; Sliwinski et al., 2006). Under stressful low SES circumstances, perceived control is theorized to sustain motivation to overcome obstacles and effectively manage stressors, help regulate emotion, and promote adaptive health behaviors that protect against cognitive declines (Lachman & Weaver, 1998a; Matthews & Gallo, 2011). In contrast, perceived control may be less beneficial in the context of high SES lifestyles that are already imbued with protective socioeconomic resources and environmental scaffolds linked to preserved cognitive functioning (Chapko et al., 2018; Hamm et al., 2020; Turiano et al., 2014).

Prior research provides some preliminary support for this prediction in showing the cross-sectional (between-person) association between perceived control and cognitive functioning was strongest for individuals with lower SES (Agrigoroaei & Lachman, 2011; Zahodne et al., 2015). Indirect evidence for the potential moderating role of SES can also be gleaned from related work suggesting that, among populations with lower SES, perceived control was a stronger predictor of other health outcomes that included stress-related cortisol, chronic inflammation, and global health status (Elliot & Chapman, 2016; Lachman & Weaver, 1998a; Zilioli et al., 2017). Collectively, these findings provide initial (between-person) evidence that SES may moderate the link between perceived control and cognition. However, a systematic evaluation is needed using micro-longitudinal data that can capture dynamic, within-person changes in daily perceived control and daily cognition for individuals who differ in core socioeconomic resources such as education or income. Research on how dynamic changes in perceived control (a modifiable motivational resource) are linked to corresponding shifts in cognition is important because it has the potential to inform the future development of evidence-based interventions to promote healthy cognitive aging.

The Present Study

This study used daily data from an ongoing measurement-burst study to examine whether day-to-day changes in perceived control over memory were associated with dynamic shifts in episodic memory. We expected that daily increases in memory control would predict corresponding increases in episodic memory.^2,3 We focused on domain-specific indicators of perceived control (over memory) and cognition (episodic memory). This was because previous research has observed stronger links between domain-specific measures of control and corresponding health behaviors and outcomes, including cognitive functioning (Lachman, 1986; Lachman & Firth, 2004; Lachman & Weaver, 1998b).

Furthermore, this study focused on episodic memory as our indicator of daily cognition for both conceptual and practical reasons. Conceptually, episodic memory reflects a central component of cognitive functioning that underlies people’s ability to function effectively and independently in their everyday lives (Baddeley, 2001; Tulving, 1993). For example, episodic memory enables basic but critical tasks such as remembering whether daily medications were taken, where a car was parked, coworker names, details from conversations, and task deadlines (Ghetti & Bunge, 2012). Episodic memory declines have also been identified as a primary risk factor for, and earliest indicator of, cognitive impairment (Albert et al., 2011; Hughes et al., 2018; Kirova et al., 2015). Practically, we did not assess other forms of memory due to feasibility and to limit participant burden.

We also examined whether the within-person association between daily changes in memory control and episodic memory differed across socioeconomic lines. We focused on education and income as central indicators of SES. We expected that daily increases in memory control would be more tightly coupled with increases in episodic memory for middle-aged and older adults experiencing socioeconomic disparities in education or income. That is, increases in memory control were expected to be linked with improved performance on the episodic memory task for individuals with lower SES who face greater daily environmental stressors that can otherwise undermine cognition (Almeida et al., 2005; Matthews & Gallo, 2011; Rickenbach et al., 2014).

Method

Participants and Procedure

We used data from Bursts 1 and 2 of the Modifiable Antecedents of Memory and Behavior in Adulthood (MAMBA) Study (Klepacz et al., 2026), an ongoing measurement-burst study of 218 community-dwelling adults aged 30–80 years at the time of recruitment. Data collection occurred from August to October 2023 for Burst 1 and from April to June 2024 for Burst 2. Both bursts involved a 10-day protocol that began with participants completing an online baseline survey and series of online cognitive tasks. This was followed by a 1-week daily diary protocol for both bursts that involved completing surveys and cognitive tasks each evening. Evening surveys collected data on daily beliefs (including perceived control), emotions, and health behaviors and were immediately followed by a brief series of daily cognitive tasks that assessed episodic memory, executive functioning, and processing speed.

Inclusion criteria for this study were that participants provided data on our focal predictor (daily perceived control), moderators (baseline education, income), and outcome (daily episodic memory). These criteria enabled us to examine how daily changes in perceived control predicted corresponding shifts in daily memory for individuals who differed in SES. Participants in the analyzed sample (n = 208) provided a total of 2,474 days of data. Strong compliance rates were observed: on average, participants completed 89% of the daily surveys (12.4 of 14) and 84% of the cognitive tasks (11.9 of 14). They were predominantly White (84%) and female (64%). Participants had an average age of 53.60 years, had completed 17.70 years of education (79% had bachelor’s degree or greater), and had a mean household income of $90,343 USD. Participant demographics are summarized in Supplementary Table S1. Informed consent was obtained from all participants prior to participation, and the North Dakota State University Institutional Review Board approved all procedures and methods (Protocol IRB0004387).

Measures

Sociodemographic Characteristics

Age, sex, education, and income were assessed in the baseline surveys. Participants self-reported their age in years (M = 53.60, SD = 14.80), sex (1 = male, 2 = female; 64% female), years of education (M = 17.70, SD = 2.41), and total household income in USD (M = 90,343, SD = 60,963). Person means across bursts were calculated for age and income because these measures varied from Burst 1 to Burst 2. Age was scaled in decades (i.e., age in years was rescaled by dividing by 10) and income in $10,000 increments (i.e., income in dollars was rescaled by dividing by 10,000) for the main analyses to facilitate interpretation. See Supplementary Table S2 for a summary of between-person correlations.

Daily Perceived Control Over Memory

Domain-specific measures of perceived control were assessed in the daily evening surveys using single-item measures derived from the national Midlife in the United States (MIDUS) study (Hamm et al., 2019; Lachman & Weaver, 1998b). Most relevant to our study, daily perceived control over memory was measured using the following item: “How much control did you have over your memory today?” Participants rated their daily control on an 11-point scale (0 = no control today, 10 = total control today). The average daily score was 7.32 (SD = 1.50), and the intraclass correlation (ICC) was .57, which indicated that a large proportion (43%) of the variance in perceived control was due to within-person, day-to-day fluctuations.

Daily Episodic Memory

Cognitive assessments were completed daily following the evening surveys via computer using online Inquisit software. The daily episodic memory task was based on previously validated procedures employed in MIDUS (Lachman et al., 2014). Specifically, episodic memory was assessed using a 15-word immediate recall task that presented participants with one word at a time and then had them type as many words as they could remember (Klepacz et al., 2026; Lachman et al., 2014). A new word list was used each day. Scores were based on the number of words correctly recalled. The average daily score was 6.00 (SD = 2.01), and the ICC was .60, which indicated that 40% of the variance in episodic memory was due to within-person fluctuations.

Rationale for Analyses

Multilevel models (MLMs) were estimated in a stepwise fashion using the nlme package for R (Pinheiro et al., 2026) to assess whether within-person changes in perceived control over memory predicted corresponding changes in daily episodic memory. Missing data were handled using full information maximum likelihood (FIML). Step 1 (main effects) models assessed whether changes in daily memory control predicted corresponding shifts in daily episodic memory at the within-person level. We estimated two-level models with daily measurement occasions (Level-1) nested within participants (Level-2). Level-1 models included an intercept, person-centered day (time) in study, person-centered memory control score, and a residual term. Day was coded from 1 to 7 in each burst to reflect the day within each burst, but we also conducted sensitivity analyses that coded day continuously from 1 to 14. The Level-1 intercepts and day slopes in these models represented average levels and linear rates of daily change (practice effects) in episodic memory across the study period. The Level-1 memory control slopes reflected coupled change in daily memory control and episodic memory. Level-2 models included correlated random effects for the intercept, day slope, and memory control slope. Level-2 predictors of the intercept were grand-mean centered and included individual differences in age, sex, income, education, and perceived control.

We also included burst as a covariate in all models rather than as a nesting variable (0 = Burst 1, 1 = Burst 2). This decision was based on the methodological literature which recommends a data structure with ⩾3 Level 2 units (ideally 10 or more Level 2 units) when employing a three-level MLM to avoid biased parameter estimates (Maas & Hox, 2005; Nezlek, 2012; Snijders & Bosker, 2012). We thus employed a two-level model in our analyses because we had only two units at Level 2 (i.e., two bursts), but we also conducted sensitivity analyses that sought to replicate our main findings using a 3-level model. See the Supplementary File for Step 1 and Step 2 model equations.

Separate Step 2 (interaction effect) models assessed whether within-person associations between daily perceived control over memory and episodic memory were independently moderated by between-person differences in education and income. The Level-1 and Level-2 models were specified as described in Step 1. The primary difference was that the Level-2 models included education or income as predictors of the Level-1 memory control slope (i.e., tested cross-level interactions between Level-1 Memory Control × Level-2 Education or Level-1 Memory Control × Level-2 Income in separate models).

Results

Step 1 results are summarized in Table 1. Within-person changes in perceived control over memory were positively, but not significantly, associated with changes in episodic memory (γ = .055, SE = .030, p = .068). A between-person association indicated that individuals with higher memory control than their peers also had higher average levels of episodic memory performance over the 2-burst study period (γ = .255, SE = .085, p < .001). Sensitivity analyses replicated the within-person (γ = .079, SE = .028, p = .005) and between-person (γ = .266, SE = .084, p = .002) main effects of memory control when employing a three-level model (days nested in bursts, bursts nested in individuals). Sensitivity analyses also replicated the within-person (γ = .073, SE = .029, p = .011) and between-person (γ = .253, SE = .085, p = .003) effects when day in study was coded continuously from 1 to 14. These sensitivity analyses suggest that participants’ episodic memory was slightly improved on days when they reported increased perceived control over their memory.

Table 1.

Main Effect Multilevel Models Predicting Daily Changes in Episodic Memory.

Predictor variables	Est. (SE)	95% CIs
Level-1 (within-person)
Intercept (γ₀₀)	5.906 (.131)**	5.649, 6.162
Day (γ₁₀)	.005 (.019)	−.032, .042
Memory control (γ₂₀)	.055 (.030)	−.004, .114
Burst (γ₃₀)	.199 (.070)**	.062, .337
Level-2 (between-person)
Age (γ₀₁)	−.474 (.089)**	−.651, −.298
Sex (female) (γ₀₂)	.474 (.269)	−.055, 1.003
Education (γ₀₃)	.011 (.056)	−.098, .121
Income (γ₀₄)	−.002 (.021)	−.044, .040
Memory control (γ₀₅)	.255 (.085)**	.087, .423
Random effects
Random intercept ( $τ_{u 0}^{2}$ )	3.087
Random day slope ( $τ_{u 1}^{2}$ )	.013
Random memory control slope ( $τ_{u 2}^{2}$ )	.019
Residual variance ( $σ_{e}^{2}$ )	2.765

Note. Memory control = perceived control over memory. Participants in the analyzed sample (n = 208) provided a total of 2,474 days of data.

p < .05; **p < .01.

Step 2 analyses subsequently tested whether the Level-1 within-person relationship was moderated by Level-2 between-person, individual differences in central measures of SES involving education or income (see Table S3). Partially supporting our hypotheses, income (γ = −.011, SE = .005, p = .013), but not education (γ = .022, SE = .012, p = .068), moderated the within-person relationship between perceived control over memory and episodic memory. The significant cross-level interaction with income suggested that the positive within-person association between daily memory control and episodic memory was pronounced for individuals with lower levels of household income (see Figure 1). We subsequently probed the interaction with tests of simple slopes at lower (−1SD = $29,380 USD) and higher (+1SD = $151,306 USD) levels of income. Tests of simple slopes revealed that within-person increases in memory control were associated with corresponding increases in episodic memory for those with lower (γ = .123, SE = .039, p = .002), but not higher (γ = −.014, SE = .041, p = .735), income levels. We replicated the cross-level interaction between Level-1 memory control and Level-2 income (γ = −.011, SE = .004, p = .016) in sensitivity analyses that employed a 3-level model. Sensitivity analyses also replicated this cross-level interaction (γ = −.012, SE = .005, p = .009) when day in study was coded continuously from 1 to 14.

Figure 1.

Cross-level interaction predicting daily changes in episodic memory.

Discussion

We sought to shed light on the dynamic relationship between perceived memory control and episodic memory in daily life. Findings inform theories of lifespan motivation and development by showing that day-to-day changes in perceived control over memory are dynamically linked to daily shifts in episodic memory (Heckhausen et al., 2010; Lachman, 2006). Results also advance the literature in providing initial evidence on the socioeconomic populations for whom this relationship holds, wherein memory control had daily benefits for only middle-aged and older adults with limited incomes (Lachman & Weaver, 1998a; Matthews & Gallo, 2011).

Our study is among the few studies to document the dynamic coupling of micro-longitudinal changes in perceived control and cognition and the first to examine this relationship using domain- or memory-specific measures of both variables. Extending prior macro-longitudinal work that has examined changes over decades (Hamm, Lachman, et al., 2025; Hong et al., 2021; Infurna & Gerstorf, 2013; Robinson & Lachman, 2018), this approach captured how perceptions of control over memory and memory performance can, and do, exhibit changes at the daily level. ICCs showed that nearly half of the variance in both memory control (43%) and episodic memory (40%) was due to day-to-day, within-person changes. Findings from our main effect models provide mixed evidence for our hypothesis that episodic memory would be improved on days when middle-aged and older adults reported increased perceived control relative to their average level. These results partially replicate and extend earlier micro-longitudinal research that had documented coupled changes between (domain-general) perceived control and cognition in smaller samples or over shorter timespans (Neupert & Allaire, 2012; Robinson & Lachman, 2020).

Findings from our moderation analyses provide initial evidence that the relationship between daily perceived memory control and episodic memory may differ across socioeconomic lines. Specifically, individual differences in income moderated this relationship such that within-person increases in memory control were associated with corresponding increases in episodic memory for only those with lower household incomes. This finding builds on seminal cross-sectional (between-person) research that observed stronger associations between perceived control and physical health outcomes for middle-aged and older adults with lower income (Lachman & Weaver, 1998a). The pronounced association we observed for individuals with lower income also supports and extends theories of control and reserve capacity. Consistent with our findings, these frameworks suggest psychosocial resources such as perceived control can sustain motivation to effectively manage daily environmental stressors that arise more frequently in lower SES circumstances and that can otherwise undermine cognitive functioning (Lachman & Weaver, 1998a; Matthews & Gallo, 2011).

Education did not moderate the link between daily perceived control over memory and episodic memory. This differs in part from prior cross-sectional (between-person) research that found control-related constructs were more strongly linked to cognitive functioning for individuals with less education (Agrigoroaei & Lachman, 2011; Zahodne et al., 2015). Several methodological differences may account for this discrepancy. Chief among these is this study’s micro-longitudinal approach that focused on daily dynamic changes in, rather than levels of, perceived control and cognition. When examining daily cognition, it is possible that income better captures the socioeconomic experience of day-to-day adversities and stressors that can erode cognitive functioning (Almeida et al., 2020; Rickenbach et al., 2014). Our study findings may also be due in part to the more meaningful range and variability observed for income compared to education. Middle-aged and older adults with “low” income (−1SD) had limited household incomes of roughly $30,000 USD, which fall in the bottom 21% in the United States (U.S. Census Bureau, 2024b). In contrast, those with “low” education (−1SD) were moderately well-educated with 15 years of schooling (i.e., had completed 2 years of postsecondary), which falls in bottom 36% in the United States (U.S. Census Bureau, 2024a). Thus, our study may have better captured greater variability and socioeconomic imbalances in income rather than education. Further research on populations with more variability and lower levels of education is needed to better understand whether education may play a moderating role.

Although our study is supported by the use of measurement-burst data that captured dynamic changes in perceptions of control over memory and episodic memory over a 14-day period, it is not without limitations. First, due to the correlational nature of the study, we are unable to make any causal or directional conclusions regarding the relationship between daily memory control and episodic memory. However, our study design ensured that participants’ memory performance on a given day could not influence their perceived memory control on that same day because the daily surveys occurred prior to the daily cognitive assessments (i.e., there was a brief lag, with the surveys taken before the cognitive tasks). Second, participants in our sample were predominantly White and fairly-well educated. Future research is needed to replicate and extend our findings in samples with more racial and educational diversity.

In sum, the present findings provide initial evidence for dynamic, coupled changes in daily perceived control over memory and episodic memory for middle-aged and older adults with limited incomes. These findings inform theories of lifespan development by documenting the potential daily benefits of increased memory control for socioeconomic populations at risk of adverse cognitive outcomes. Future research is needed to identify the extent to which domain-general and/or domain-specific perceived control (over memory) is a viable target mechanism for interventions designed to promote healthy cognitive aging (cf. Lachman et al., 1992).

Supplemental Material

sj-docx-1-jbd-10.1177_01650254261454866 – Supplemental material for Coupled Changes in Daily Control Beliefs and Cognition: Variations by Education and Income

Supplemental material, sj-docx-1-jbd-10.1177_01650254261454866 for Coupled Changes in Daily Control Beliefs and Cognition: Variations by Education and Income by Jeremy M. Hamm, Margie E. Lachman, Laura M. Klepacz and Dyari S. Hama-Amin in International Journal of Behavioral Development

Footnotes

ORCID iD

Jeremy M. Hamm

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by the National Institute on Aging (NIA; Grant R01AG075117). Study data were from the Modifiable Antecedents of Memory and Behavior in Adulthood (MAMBA) Study.

Declaration of Conflicting Interests

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

Supplemental Material

Supplemental material for this article is available online.

Notes

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