Effects of Information and Communication Technology Use on the Executive Function of Older Adults without Dementia: A Longitudinal Fixed-Effect Analysis

Hamin Lee; Sangmi Park; Seungho Han; Hyeon Dong Lee; Ickpyo Hong; Hae Yean Park

doi:10.4235/agmr.24.0073

Ann Geriatr Med Res > Volume 28(4); 2024 > Article

Lee, Park, Han, Lee, Hong, and Park: Effects of Information and Communication Technology Use on the Executive Function of Older Adults without Dementia: A Longitudinal Fixed-Effect Analysis

Original Article

Annals of Geriatric Medicine and Research 2024;28(4):445-452.

Published online: September 8, 2024

DOI: https://doi.org/10.4235/agmr.24.0073

Effects of Information and Communication Technology Use on the Executive Function of Older Adults without Dementia: A Longitudinal Fixed-Effect Analysis

Hamin Lee¹, Sangmi Park², Seungho Han¹, Hyeon Dong Lee¹, Ickpyo Hong², Hae Yean Park²

¹Department of Occupational Therapy, Graduate School, Yonsei University, Wonju, Korea

²Department of Occupational Therapy, College of Software Digital Healthcare Convergence, Yonsei University, Wonju, Korea

Corresponding Author: Hae Yean Park, PhD, OTR Department of Occupational Therapy, College of Software and Digital Healthcare Convergence, Yonsei University, 1 Yeonsedae-gil, Wonju 26493, Korea
E-mail: haepark@yonsei.ac.kr

This study was presented at the American Occupational Therapy Association Annual Conference & Expo (INSPIRE 2023) in Kansas City, MO, USA.

Received March 17, 2024 Revised August 10, 2024 Accepted August 31, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Impaired executive function is common in older adults. This study examined the causal relationship between the use of information and communication technology (ICT) and executive function in older adults over time.

Method

This study performed a secondary analysis of data from four waves (2016–2019) of the National Health and Aging Trends Study. A fixed-effect analysis was conducted to examine the effects of ICT on the executive function of older adults without dementia aged ≥65 years. This study analyzed data from 3,334 respondents.

Results

We observed significant positive effects of ICT use on executive function over time (standardized β=0.043–0.045; 95% confidence interval, 0.001–0.043; p<0.05).

Conclusion

The current findings support the use of ICT as a protective approach to prevent decline in executive function in community-dwelling older adults.

Key words: Aged, Computer literacy, Executive function, Information technology

INTRODUCTION

As cognitive function changes with age, decline of executive function is common in older adults, demonstrating an increasing risk with age.¹⁾ Executive function is an area of cognition related to flexible thinking, self-regulation, and working memory.²⁾ Although a consensus on the definition of executive function is lacking, it is generally understood to control cognition³⁾ and decision-making.⁴⁾

Executive function is a vital element of cognition in older adults. Executive function affects behaviors associated with health outcomes.⁵⁾ Executive function is also related to factors influencing daily living, including mood, functional task performance, and health conditions.⁶⁾ Executive function must be addressed from a preventive perspective because it is more associated with aging than other cognitive functions.⁷⁾ Therefore, identifying protective factors and developing early interventions to preserve the executive function of older adults is essential.

Various computer-based cognitive interventions have been investigated. For instance, Zaccarelli et al.⁸⁾ reported that a 12-week intervention improved the cognitive health status, mainly memory, and executive function. Chan et al.⁹⁾ demonstrated that a 10-week iPad-based training improved episodic memory function and processing speed. However, compared with findings from these and other experimental studies on the effects of computer-based cognitive interventions, evidence regarding the effectiveness of the daily use of information and communication technology (ICT) on cognition, especially executive function, is limited.

ICT refers to online technology and devices that enable people to gain information and enhance their communication with others.¹⁰⁾ Several studies have reported the cognitive advantages of ICT. For instance, Wu et al.¹¹⁾ observed lower cognitive function scores in the non-daily digital device usage group compared with the daily usage group among 323 older adults. Additionally, Myhre et al.¹²⁾ observed that the use of social networking sites was associated with significantly increased executive function among 47 older adults. As these results were obtained in cross-sectional studies with small sample sizes, the longitudinal association with ICT use remains unclear. Choi et al.¹³⁾ conducted longitudinal research to examine the association between ICT use and cognitive function.

Although Choi et al.¹³⁾ reported the positive effects of ICT use on executive function over time, the researchers defined depression as a time-invariant covariate. The depressive status of older adults tends to change depending on natural events in later life, including functional impairments (e.g., hearing loss)^14-¹⁶⁾ or loss of loved ones (e.g., bereavement).^17-¹⁹⁾ Hence, depression should be treated as a time-dependent factor. In addition, unmeasured confounders such as religion²⁰⁾ and socioeconomic status²¹⁾ also affect cognition and may need to be controlled for to more accurately examine the relationship between ICT use and executive function.²²⁾ Fixed-effects models have the advantage of controlling both observed and unobserved confounders.²³⁾ Therefore, this study analyzed the causal effect of ICT use on executive function in older adults by applying a fixed-effects model to more accurately examine the effect of ICT use.

MATERIALS AND METHODS

Study Data

This study analyzed data from the National Health and Aging Trends Study (NHATS). The NHATS is an annual survey of nationally representative samples of American adults aged ≥65 years.²⁴⁾ The NHATS provides diverse information about older adults’ daily lives, such as health, home, community, and everyday activities. NHATS participants are selected from among Medicare enrollees. The NHATS survey was first conducted in 2011, and by 2021, 11 annual surveys had been conducted. To maintain the ability of the sample to accurately represent the senior Medicare population, replenishment was conducted in 2015. Owing to the effects of the coronavirus disease 2019 (COVID-19) pandemic on ICT use, cognitive function, and depression,^25-²⁷⁾ this study used data from the four waves collected from 2016 to 2019, after replenishment and before the pandemic.

Study Participants

To analyze the causal relationship between ICT use and executive function in community-dwelling older adults without dementia, we excluded data using an exclusion criteria. Older adults with dementia were not included to eliminate those with obvious cognitive impairment to examine the efficacy of ICT as a preventive approach. Thus, the exclusion criteria were participants who (1) only completed the facility questionnaire interview; (2) had missing values in any of the analysis items (i.e., independent, dependent, or controlling variables) across four consecutive waves; and (3) were diagnosed with dementia. After merging the four waves (i.e., NHATS data from 2016, 2017, 2018, and 2019), we excluded participants with missing data on demographic characteristics at baseline. Fig. 1 illustrates the sample selection process for the analysis.

Study Variables

Dependent variable: executive function

This study used the Clock-Drawing Test (CDT) as a commonly used outcome measure for executive function.²⁸⁾ The CDT consists of scores ranging from 0 to 5, with higher scores indicating higher executive function.

Independent variable: ICT use

According to the definition of ICT, this study included questions on online activities as an ICT use variable.¹⁰⁾ We used six questions regarding ICT use during the previous month to measure ICT use. These questions included whether the respondent had sent a message via e-mail or texting, used the Internet in addition to e-mail or texting, shopped online, paid bills online or used online banking services, ordered or refilled prescriptions via the Internet, and visited social networking sites. In this study, responses stating “yes” were coded as 1, while “no” were coded as ‘0’ for each of the six questions. The summed scores of the six questions were used for the analysis (a minimum of 0 to a maximum of 6). Higher scores indicated higher ICT use.

Time-variant confounder: depression

We used two questions to measure depression according to the Patient Health Questionnaire-2 (PHQ-2). The questions enquired how often the respondents felt little pleasure in performing activities and how often they felt depressed over the past month. The respondents answered questions on a four-point scale with scores ranging from 1 to 4 (1, not at all; 2, several days; 3, more than half the days; 4, nearly every day). The scores for the two questions were summed to create a depressive variable (range, 2–8), in which higher scores indicated a higher sense of depression.

Data Analysis

We performed descriptive analyses on the demographic characteristics at baseline (i.e., NHATS data 2016) and repeated the measurements of other variables (i.e., independent variables, dependent variables, and time-varying confounders). A longitudinal fixed-effects analysis was performed to estimate the effects of ICT use on executive function. The fixed-effect analysis is suitable for controlling time-invariant confounding, which can create bias in the causal estimates between variables.²⁹⁾ This method can accurately predict the causal relationships between independent and dependent variables.^30,³¹⁾ The fixed-effects model provides within-person effects, in which the estimates are not confounded by time-invariant factors.³²⁾ Fig. 2 presents a conceptual diagram of the fixed-effect analysis modeling used in this study to examine the effects of ICT use on executive function. We applied four consecutive waves from 2016 to 2019 to the model. Depression was used as a time-dependent confounder. We controlled for time-invariant confounders related to executive function, such as race, sex, education, and religion,¹³⁾ by treating them as fixed effects (i.e., alpha).

We used model fit indices to check the appropriateness of the model fit, including chi-square (χ²), root mean square error of approximation (RMSEA), comparative fit index (CFI), and standardized root mean square residual (SRMR). A χ² value >0.05 is a standard benchmark for statistical significance,³³⁾ while an RMSEA value <0.05 suggests a good fit³⁴⁾ and CFI value ≥0.95 and SRMR ≤0.08 indicate a fair fit.³⁵⁾ The Tucker-Lewis index (TLI) value ≥0.95 is a common cutoff for goodness of fit.³⁶⁾ The maximum likelihood estimation with robust standard errors (MLR) estimator was also used.

We used SAS version 9.4 to manage the data and analyze the descriptive characteristics of the participants, and Mplus version 8.0 (https://www.statmodel.com/demo.shtml) to examine the effects of ICT on executive function in older adults. Unstandardized coefficient estimates (β) and standardized coefficient estimates (β) are presented with standard errors. The standardized coefficient estimate is presented with a 95% confidence interval (CI).

Ethical Considerations

The Institutional Review Board of Yonsei University Mirae Campus approved (No. 1041849-202301-SB-003-01) and waived the requirement of a review for this study.

RESULTS

Descriptive Analysis

The analysis included a total of 3,334 participants. Table 1 presents a descriptive analysis of their general characteristics. Originally, the NHATS data provided age information within a 5-year interval. In this study, age was reclassified as old (65–74 years), older (75–84 years), and oldest (85+ years) to represent the proportions of different age groups among older adults. Women comprised 56% of the participants, while non-Hispanic European American accounted for 75.22% of the total population. Most participants (28.06%) had a college degree or higher level of education. Table 2 presents the scores for executive function, ICT use, and depression among the participants over time. However, contrary to our expectations, the depression score did not change much over time; thus, we modified the research model by excluding depression from the time-variant confounders (Fig. 3). Descriptive data on ICT use, executive function, and depression at baseline according to general characteristics are presented in Supplementary Table S1.

Longitudinal Fixed-Effect Analysis of the Effects of ICT Use on Executive Function

The final research model demonstrated a good model fit (χ²=34.21, p=0.0051, RMSEA=0.018, CFI=0.993, TLI==0.991, SRMR=0.015). The unstandardized coefficients (B) and standardized coefficients (β) of ICT on executive function are presented in Table 3. The positive effects of ICT use on executive function over time were statistically significant. The correlation matrix for ICT use, executive function, and depression over 4 years is shown in Supplementary Table S2.

DISCUSSION

The results of the longitudinal panel data analysis in this study revealed the positive effect of ICT use on executive function in older adults. As these results controlled for time-variant and time-invariant covariates, they provided a more accurate longitudinal relationship between ICT use and executive function in community-dwelling older adults compared with previous studies. These findings support the notion that more diverse ICT use may be beneficial for protecting executive function in older adults.

The positive effects of ICT use on executive function in older adults in this study are consistent with those in previous studies.^11,¹³⁾ The protective effects of ICT on executive function can be attributed to the advantages of brain stimulation. Brain function is altered, maintained, and strengthened in response to environmental stimulus.³⁷⁾ Environmental stimuli include social, mental, and physical activities. Based on the cognitive enrichment theory,³⁸⁾ ICT use, including activities such as emailing, texting, and social networking sites, can provide social stimuli to older adults. Thus, ICT use in daily life and the consequent brain stimulation may contribute to maintaining executive function over time in older adults.

Our findings indicate the potential effectiveness of ICT use in preventing cognitive health decline, specifically in executive function, in older adults. However, disparities in ICT use exist across age and race, referred to as the “digital divide” among older adults. In 2015, the International Telecommunication Union reported that only 56% of American older adults aged ≥75 years used the Internet, compared with the overall average of 86%.³⁹⁾ Thus, the use of ICT as an intervention for the cognitive health of older adults must consider ways to reduce inequality in ICT use in this population. Further, future studies should identify and address the causes of the digital divide among older adults, including verified ICT education protocols for older adults.

This study has several limitations. First, the results may be limited to non-Hispanic European American older adults, as this population comprised >75% of the total sample. Second, we did not measure the frequency or proficiency of ICT use because the scale of the items for ICT use was dichotomous (i.e., yes or no). In addition, only the CDT was used to assess executive function. Owing to these factors, the effect of ICT use on executive function may have been overestimated. Future studies should include additional executive function assessments, such as the Trail Making or Stroop tests, for accurate estimation. Furthermore, the effects of the frequency or proficiency of ICT use on executive function should also be considered as a preventive approach to improve executive function in older adults. Third, the participants included in this study might be familiar with ICT use because their cognitive function was fairly good, as we excluded people with severe cognitive impairment. Thus, future studies should compare the rate of cognitive decline according to ICT use levels by observing participants for a longer period to capture the exact effect of ICT use on executive function.

In conclusion, this study examined the association between ICT use and executive function in older adults over four years. The findings revealed that individuals who were involved in more daily ICT use were more likely to have higher executive function over time. These findings support the use of ICT as a protective strategy to prevent executive function decline in community-dwelling older adults.

ACKNOWLEDGMENTS

CONFLICT OF INTEREST

The researchers claim no conflicts of interest.

FUNDING

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (No. NRF-2021S1A3A2A02096338).

AUTHOR CONTRIBUTIONS

Conceptualization, HL, SH, HL; Data curation, HL; Investigation, HL, SH, HL; Methodology, HL; Project administration, SP, IH, HYP; Supervision, SP, IH, HYP; Writing–original draft, HL, SH, HL; Writing–review & editing, HL, SP.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.4235/agmr.24.0073.

Supplementary Table S1.

Descriptive data of ICT use, executive function, depression according to general characteristics.at baseline

agmr-24-0073-Supplementary-Table-S1.pdf

Supplementary Table S2.

Correlation matrix (n=3,334)

agmr-24-0073-Supplementary-Table-S2.pdf

Fig. 1.

Flowchart of study sample selection. NHATS, National Health and Aging Trends Study; ICT, information and communication technology.

Fig. 2.

Conceptual research model for longitudinal fixed-effect analysis. The effects of ICT use on executive function were examined in four waves. Depression across four waves were applied as time-varying variables. ICT, information and communication technology.

Fig. 3.

Final research model for longitudinal fixed-effect analysis. ICT, information and communication technology.

Table 1.

Demographic characteristics of the participants at the baseline (n=3,334)

Variable	Observation from baseline
Age group (y)
65–74	1,465 (43.94)
75–84	1,431 (42.92)
≥85	438 (13.14)
Sex
Male	1,467 (44.00)
Female	1,867 (56.00)
Race
European American, non-Hispanic	2,508 (75.22)
African American, non-Hispanic	579 (17.37)
Hispanic	159 (4.77)
Other^a)/unknown/refusal	88 (2.64)
Marital status
Single^b)	1,471 (44.12)
Not single^c)	1,863 (55.88)
Education
Less than high school^d)	448 (13.44)
High school graduate	827 (24.81)
Some college or vocational school^e)	790 (23.70)
College or higher^f)	1,269 (28.06)

Values are presented as number (%).

^a)American Indian, Asian, Native Hawaiian, Pacific Islander, and other specifics were included.

^b)Separated (n=54), divorced (n=412), widowed (n=907), and never married (n=98) were combined.

^c)Married (n=1,789) and living with partner (n=74) were combined.

^d)No schooling (n=4), 1st–8th grades (n=173), and 9th–12th grades with no diploma (n=271) were combined.

^e)Vocational, technical, business, or trade school certificate or diploma (n=250) and attended college but did not receive degree (n=282) were combined.

^f)Associate’s degree (n=100), bachelor’s degree (n=297), and master’s professional or doctorate degree (n=262) were combined.

Table 2.

Scores for repeated measured variables

	NHATS data^a)
	2016	2017	2018	2019
Executive function	3.99±0.98	3.99±0.99	3.95±1.03	3.97±1.03
ICT use	2.35±1.95	2.35±1.99	2.36±2.00	2.38±2.02
Depression	2.69±1.13	2.73±1.16	2.74±1.12	2.75±1.15

Values are presented as mean±standard deviation

NHATS, National Health and Aging Trends Study; ICT, information and communication technology

^a)Range of executive function is 0–5; range of ICT use, 0–6; and range of depression, 2–8.

Table 3.

Effects of ICT use on executive function in older adults across 4 years

Independent variable	Unstandardized B (SE)	Executive function
Independent variable	Unstandardized B (SE)	Standardized β (SE)	95% CI	p-value
ICT 2016	0.022 (0.011)^a)	0.044 (0.021)	0.002–0.086	0.042
ICT 2017	0.022 (0.011)^a)	0.045 (0.022)	0.002–0.088	0.041
ICT 2018	0.022 (0.011)^a)	0.043 (0.021)	0.002–0.084	0.040
ICT 2019	0.022 (0.011)^a)	0.040 (0.022)	0.002–0.087	0.041

ICT, information and communication technology; SE, standard error; CI, confidence interval.

^a)95% CI is 0.001 to 0.044 (p=0.041).

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