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Published in final edited form as: Psychiatr Rehabil J. 2019 Apr 4;42(4):358–365. doi: 10.1037/prj0000364

An exploration of linear and curvilinear relationships between community participation and neurocognition among those with serious mental illnesses

Elizabeth C Thomas a, Gretchen Snethen b, Bryan McCormick b, Mark S Salzer b
PMCID: PMC6776709  NIHMSID: NIHMS1038505  PMID: 30945919

Abstract

Objective:

Longitudinal research supports an effect of participation in aspects of community life (e.g., leisure activity, employment) on neurocognition in the general population. This study examined the extent and nature of the relationship between community participation and neurocognition among people with serious mental illnesses.

Methods:

Participants included 168 adults with schizophrenia spectrum or affective disorder diagnoses who completed the Temple University Community Participation Measure and Brief Assessment of Cognition in Schizophrenia. Hierarchical multiple regression analyses explored linear and curvilinear effects of the amount and breadth of community participation on neurocognition.

Results:

Significant linear relationships existed between amount of community participation and overall neurocognitive functioning, motor speed, verbal fluency, and attention/processing speed, and between breadth of participation and verbal fluency. Significant curvilinear effects were noted between amount of community participation and verbal memory, and between breadth of community participation and overall neurocognitive functioning and motor speed.

Conclusions and Implications for Practice:

Findings suggest that enhanced community participation may contribute to improved neurocognitive functioning, further supporting the importance of this rehabilitation target.

Keywords: physical activity, environmental enrichment, psychiatric disabilities

Introduction

A significant body of research has examined functional outcomes, and factors associated with these outcomes, among individuals with serious mental illnesses. However, the manner in which functional outcomes are often operationalized – with a focus on skills performance in only a few specific areas of daily living, such as work, social interactions, and self-care (Lipskaya-Velikovsky, Jarus, & Kotler, 2017) – limits knowledge about how people are actually participating in their communities (Lepage, Bodnar, & Bowie, 2014). Community participation is defined as the “empowered, self-determined choice and action that individuals make to be active in valued roles in the communities of their choice, across a variety of domains in their life” (Burns-Lynch, Brusilovskiy, & Salzer, 2016, p. 47). Measures of community participation (Heinemann et al., 2013; Salzer, Brusilovskiy, Prvu-Bettger, & Kottsieper, 2014) differ from those evaluating functioning given that they assess time spent in such domains (e.g., leisure, civic, religious, vocational), regardless of skills performance. As the promotion of opportunity for community participation is an important target of psychiatric rehabilitation (Hogan, 2003), there is a need to capitalize on the development of these measures to examine participation more specifically and better understand factors that may relate to it.

Research has long documented a robust relationship between neurocognition and functional outcomes among individuals with serious mental illnesses (Green, Kern, Braff, & Mintz, 2000). A meta-analysis of 52 studies demonstrated that specific domains of neurocognition (e.g., verbal fluency, reasoning) were significantly associated with community functioning (i.e., independent living skills, social and work functioning), social problem solving, and social skills among individuals with non-affective psychosis (Fett et al., 2011). The strength of these relationships was similar in another meta-analysis including individuals with bipolar disorder (Depp et al., 2012). Other research has demonstrated that associations between neurocognition and functional outcomes remain relatively stable over time (Addington & Addington, 2000). However, the relationship between neurocognition and community participation has received disproportionately less attention.

A greater focus on the relationship between neurocognition and community participation is warranted because, while greater neurocognitive abilities are often presumed to be a necessary precursor of community participation and functioning, it is also plausible that participation itself may enhance neurocognitive abilities. One possible set of biological explanations for this relationship is based on recent research findings pertaining to the impact of physical activity on the brain (Erickson, Hillman, & Kramer, 2015; Phillips, Baktir, Srivatsan, & Salehi, 2014) and on cognitive functioning (Ratey & Loehr, 2011). Of note, studies have consistently demonstrated a link between physical activity and neurocognition among those with serious mental illnesses (Firth et al., 2017; Kimhy et al., 2014; Snethen, McCormick, & Lysaker, 2014; Stubbs, Ku, Chung, & Chen, 2017). Community participation involves both physical activity to ambulate to a location and often some degree of physical exertion while engaged in the act (Suetani et al., 2016), which could conceivably enhance neurocognition.

A second possible explanation for the relationship between community participation and neurocognition comes from the relatively long tradition in experimental psychology of examining the cognitive effects of enriched environments. This work has consistently demonstrated that, in addition to physical activity, elements such as social interaction and environmental novelty contribute to cognitive reserve and improvements in cognition (Nithianantharajah & Hannan, 2006; Pang & Hannan, 2013), and that cognitive improvements have been manifested in rodent models of schizophrenia, depression, and anxiety disorders (Hannan, 2010). From this perspective, community participation may represent an enriched environment, as it frequently involves physical activity, social interaction, and environmental novelty.

Longitudinal studies demonstrate predictive relationships between various areas of community participation and different neurocognitive domains in the general population. Richards et al. (2003) found that individuals who participated in leisure activities (e.g., religious activities, going to the movies, civic involvement) had higher verbal memory scores 6 years later, and that those who engaged in physical exercise had a slower rate of verbal memory decline over a subsequent 10-year period. Similarly, participation in civic activities during middle-age predicted executive functioning and memory abilities after age 50, even after controlling for covariates such as health, socio-economic status, and gender (Bowling, Pikhartova, & Dodgeon, 2016). Another large longitudinal study suggested that intellectually stimulating work environments may sustain verbal memory (Yu, Ryan, Schaie, Willis, & Kolanowski, 2009).

While still in its infancy, there is also some literature suggesting that community participation is related to neurocognition among people with schizophrenia and related disorders. Studies have shown that being employed is associated with better attention, working memory, executive functioning, and vigilance (McGurk & Meltzer, 2000; Midin et al., 2011). In addition, greater diversity of participation across the areas of domestic life, recreation and leisure, child care, learning and applying knowledge, physical activities and sport, self-care and quiet activities (e.g., watching television) was related to a measure of ‘construction,’ which included tasks of visual perception, visual-motor coordination, and executive functioning (Lipskaya-Velikovsky et al., 2017). The degree to which individuals with early psychosis were engaged in leisure and social activities was considered to be a proxy for cognitive reserve, that, along with premorbid IQ and years of education, predicted neurocognitive functioning in the areas of working memory and attention two years later (Amoretti et al., 2016; de la Serna et al., 2013). These findings offer a novel orientation to our understanding of associations between community participation and neurocognition among those with serious mental illnesses that could lead to additional support for participation-based interventions to enhance cognitive functioning.

An additional issue in the neurocognition/functional outcome research area is that it has almost entirely been presumed to be a linear relationship (Andreou & Bozikas, 2013; Fett et al., 2011). However, the relationship between community participation and neurocognition may be more complicated, as incremental growth in one of these variables may not consistently map onto fixed increases in the other. For example, Kaplan and Berman (2010) noted that high self-regulatory demands, consistent with those that might be seen during community participation, can deplete neurocognitive resources such as executive function. This is consistent with notions of cognitive load, which assert that humans have finite cognitive capacity, whereby increases in resources needed to accomplish tasks deplete those left for the execution of cognitive processes, such as problem solving and learning (Sweller, 1988). Therefore, it is plausible that cognitive demands associated with higher levels of participation might outweigh available neurocognitive resources, resulting in a curvilinear (i.e., inverted U-shape or negative asymptotic) relationship between community participation and neurocognition. This might especially be true as breadth of participation increases; that is, as individuals participate in a greater number of unique participation areas and are exposed to a greater diversity of tasks and roles. The impacts of cognitive load may, or may not, be different for people with and without a serious mental illness.

This study contributes to current knowledge by using a large sample of adults with either a psychotic or affective disorder to be among the first to examine the following two questions: 1) Are there relationships between amount and breadth of community participation and various domains of neurocognition? and 2) What is the nature of these relationships? Amount of participation was operationalized as the number of days over the previous month that individuals reported participating in a variety of community-based activities, while breadth of participation was defined as the number of unique areas in which some participation was reported over the preceding month. Domains of neurocognition assessed included verbal memory, working memory, motor speed, attention/processing speed, executive functioning, and verbal fluency. We hypothesized that significant relationships (regardless of their shape) would be observed, especially between community participation and verbal memory, verbal fluency, and executive functioning. These neurocognitive domains were selected given that they are consistently related to community participation in other research (Bowling et al., 2016; Lipskaya-Velikovsky et al., 2017; McGurk & Meltzer, 2000; Richards et al., 2003; Yu et al., 2009) and have been shown to be particularly related to functional outcomes in meta-analytic studies (Fett et al., 2011; Green et al., 2000). Following cognitive load theory (Sweller, 1988), we also hypothesized that curvilinear relationships would exist, especially between breadth of community participation and neurocognition.

Methods

Participants

This study utilized baseline data from 168 adults (between the ages of 18 and 65 years) taking part in either a randomized controlled trial of an intervention to enhance community participation (n = 102) or a study of environmental factors that facilitate community participation (n = 66). Participants were recruited from community mental health agencies in a large city in the northeastern United States. All were English speaking, and had a diagnosis of a psychotic disorder, bipolar disorder, or major depression as determined by a diagnostic screener (Sheehan et al., 1998). The Institutional Review Boards of the researchers’ academic institution and local municipality approved both studies. All participants provided informed consent.

Measures

Community participation.

Community participation was assessed using the Temple University Community Participation (TUCP) measure (Salzer et al., 2014), a self-report instrument examining the amount, sufficiency, and importance of participation in 26 different areas of community-based activity over the previous 30 days. Individuals are asked to report the number of days that they participated in each activity without a staff person (amount), whether their level of participation in these activities was “enough,” “not enough,” or “too much” (sufficiency), and whether the activities were important to them (“yes/no”; importance). The TUCP demonstrates good test-retest reliability (Salzer et al., 2014). We extracted the following to serve as independent variables in our analyses: amount of participation, defined as total participation days across all items [range 0–780 (30 days × 26 participation areas)], and breadth of participation [sometimes referred to as diversity of participation in other research (Lipskaya-Velikovsky et al., 2017)], defined as the number of unique participation areas (i.e., items) with at least one day of participation reported.

Neurocognition.

Participants completed the Brief Assessment of Cognition in Schizophrenia [BACS; (Keefe et al., 2004)], a neurocognitive battery assessing verbal memory, working memory, motor speed, attention/processing speed, executive functioning, and verbal fluency. The BACS demonstrates sensitivity to neurocognitive challenges in individuals with serious mental illnesses, good test-retest reliability, and strong concurrent validity (Keefe et al., 2004). It is also strongly correlated with measures of functional capacity and independent living skills (Keefe, Poe, Walker, Kang, & Harvey, 2006). While another version of this instrument exists to assess neurocognition among individuals with affective disorders [BAC-A; (Keefe et al., 2014)], the core cognitive subtests are consistent with the BACS and thus we elected to administer the BACS to all participants regardless of diagnosis. All individuals were administered the same form of the BACS. Composite and subtest T-scores that accounted for age and gender were calculated according to recommendations by Keefe et al. (2004), and were utilized as dependent variables in the present analyses.

Statistical Analysis

In order to examine the relationship between community participation and neurocognition, a series of hierarchical multiple regression analyses in blocks were performed. For each analysis, neurocognition (i.e., composite or subscale score) was regressed on community participation (i.e., amount or breadth). Amount and breadth were not included in the same model given that they were correlated independent variables (r = .64, p < .01). The linear term of community participation was entered in block 1, and the quadratic term of community participation was entered in block 2. In order to mitigate multicollinearity issues, the linear term of community participation was mean-centered before creation of the quadratic term (Aiken & West, 1991). The significance of omnibus F tests, coefficients for each term, and R2 change tests were examined to determine which model provided the best fit. We followed Cohen (1988) in calculating and categorizing the magnitude of f2 effect sizes (small = .02, medium = .15, large = .35). All analyses were conducted using SPSS version 24.

Results

Participant Characteristics

Participant demographic characteristics are reported in Table 1. As shown, the majority of individuals were middle-aged and single. Most had a diagnosis of schizophrenia or bipolar disorder. There was an approximately equal proportion of males versus females. Over three quarters of participants identified as belonging to a racial/ethnic minority group.

Table 1.

Demographic Characteristics of the Study Sample (N=168)

Variable N (%) M SD
Gender
 Men 90 (54)
 Women 78 (46)
Ethnicitya
 Black 85 (51)
 White 49 (30)
 Native American 6 (4)
 Latino 5 (3)
 Native Hawaiian or Pacific Islander 3 (2)
 Asian 1 (<1)
 Other 35 (21)
Marital Status
 Single 124 (74)
 Married 4 (2)
 Significant Other but Not Married 50 (30)
Age (years) 168 47.64 10.32
Diagnosis
 Schizophrenia 57 (34)
 Bipolar 46 (27)
 Major Depressive Disorder 38 (23)
 Schizoaffective 20 (12)
 Mood Disorder NOS 2 (1)
 Missing 5 (3)
TUCP: Amount of Community Participation 168 72.43 54.76
TUCP: Breadth of Community Participation 168 9.07 3.71
BACS: Verbal Memory 168 30.47 12.81
BACS: Motor Speed 168 46.12 12.03
BACS: Working Memory 168 31.31 13.41
BACS: Verbal Fluency 168 40.66 11.48
BACS: Attention/Processing Speed 168 32.07 11.78
BACS: Executive Functioning 168 32.15 16.77
BACS: Composite 168 26.77 14.31
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Note. TUCP = Temple University Community Participation measure; BACS = Brief Assessment of Cognition in Schizophrenia.

a

Ethnic categories are not mutually exclusive.

Community Participation and Neurocognition

Amount.

As shown in Table 2, there was a significant (positive) linear, but not quadratic, relationship between amount of community participation and the BACS composite score. This relationship appeared to have been primarily driven by positive linear effects pertaining to motor speed, verbal fluency, and attention/processing speed scores. Verbal memory was the only BACS domain for which there was a significant quadratic effect of amount of community participation. The negative sign of the quadratic term indicated that there was a decrease in the magnitude of the linear effect with additional days of community participation. The scatterplot of this relationship (depicted in supplemental file 1) shows an inflection point at about 100 days of participation, wherein this decrease in magnitude began to take place. The models explained 0.1–5% of the variance in various domains of neurocognition (small effect sizes). There were no significant relationships between amount of community participation and working memory or executive functioning scores.

Table 2.

Hierarchical Multiple Regression Analyses Predicting Neurocognition from Amount of Community Participation (N=168)

Predictor Outcome
Verbal Memory Token Motor Digit Sequencing Verbal Fluency Symbol Coding Tower of London Composite
∆R2 β ∆R2 β ∆R2 β ∆R2 β ∆R2 β ∆R2 β ∆R2 β
Block 1: .03* .03* .001 .03* .05** .01 .04*
Linear Term .16* .16* .03 .17* 23** .09 .21*
Block 2: .03* .01 .01 .004 .002 .01 .02
Linear Term .33** .25* .14 .24* .28* .17 .35**
Quadratic Term −.24* −.12 −.14 −.09 −.07 −.10 −.19
Total R2† .05 .03 .001 .03 .05 .01 .04
F-value† 4.48* 4.32* .19 5.19* 9.30** 1.46 7.29**
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*

p < .05.

**

p < .01.

†

Reported values pertain to the best fitting model, or to the linear model if no model fit the data well.

Breadth.

As indicated in Table 3, there was a significant quadratic relationship between breadth of community participation and the BACS composite score, such that the magnitude of the linear effect decreased with additional unique community participation areas. The scatterplot (supplemental file 1) demonstrates that this decrease in magnitude began to occur after about 5 unique participation areas. Similarly, there was a significant, negative quadratic effect of breadth pertaining to motor speed scores, with a decrease in the magnitude of the linear effect after about 3 participation areas (supplemental file 1). There was a significant (positive) linear, but not quadratic, relationship between breadth and verbal fluency scores. The models explained 0.1–11% of the variance in various domains of neurocognition (small effect sizes). There were no significant relationships between breadth and verbal memory, working memory, attention/processing speed, and executive functioning scores.

Table 3.

Hierarchical Multiple Regression Analyses Predicting Neurocognition from Breadth of Community Participation (N=168)

Predictor Outcome
Verbal Memory Token Motor Digit Sequencing Verbal Fluency Symbol Coding Tower of London Composite
∆R2 β ∆R2 β ∆R2 β AR2 β ∆R2 β ∆R2 β ∆R2 β
Block 1: .02 .03* .002 .05** .02 .001 .03*
Linear Term .12 .18* .05 23** .14 .03 .18*
Block 2: .02 .08** .03* .001 .01 .003 .03*
Linear Term .19* .31** .13 .25** .20* .06 27**
Quadratic Term −.15 −.31** −.19* −.04 −.13 −.06 −.20*
Total R2† .02 .11 .002 .06 .02 .001 .07
F-value† 2.59 10.15** 2.66 9 49** 3.31 .16 5.81**
Open in a new tab
*

p < .05.

**

p < .01.

†

Reported values pertain to the best fitting model, or to the linear model if no model fit the data well.

Discussion

This study is among the first to examine relationships between amount and breadth of community participation and neurocognition among those with serious mental illnesses. Particularly novel are findings indicating that there are both linear and curvilinear relationships between these variables. As such, this study informs hypotheses that can be tested in future research and has important implications for psychiatric rehabilitation.

Findings related to our first research question were consistent with expectation, in that there were significant relationships between community participation and verbal memory and verbal fluency. Both community participation variables were consistently associated with overall neurocognitive functioning, motor speed, and verbal fluency. Amount (but not breadth) of participation was significantly associated with verbal memory and attention and processing speed. In light of the plausible biological and environmental explanations for the relationship between community participation and neurocognition, these findings appear consistent with studies demonstrating a relationship between physical activity and motor speed, verbal fluency, verbal memory, and attention and processing speed among those with and without serious mental illnesses (Chen, Steptoe, Chung, & Ku, 2016; Daly, McMinn, & Allan, 2015; Firth et al., 2017; Kim et al., 2016; Kurebayashi & Otaki, 2017; Richards et al., 2003), and between social interaction and social connectedness and verbal fluency, working memory, spatial ability, and executive functioning in this population (Alptekin et al., 2005; Caplan, Schutt, Turner, Goldfinger, & Seidman, 2006; Cook, Liu, Tarasenko, Davidson, & Spaulding, 2013; Santosh, Roy, & Kundu, 2013).

Contrary to expectation, there were no significant relationships between amount or breadth of community participation and executive functioning. This finding may be due to differences in the way executive functioning was measured in the present study compared to previous research. The BACS’ Tower of London task, which is intended to measure executive functioning, assesses planning and problem-solving skills (Keefe et al., 2004), whereas other research has assessed executive functioning according to verbal fluency tasks (Bowling et al., 2016), cognitive flexibility tasks such as the Wisconsin Card Sorting Task or Trail Making Test (McGurk & Meltzer, 2000; Midin et al., 2011) or other subtests (Lipskaya-Velikovsky et al., 2017). It may be that the enhancement of complex neurocognitive processes such as problem-solving and planning may require more than simply participation in the community, or more advanced participation than that captured by the TUCP. In addition to supporting community participation, psychiatric rehabilitation providers may need to offer additional supports and services to affect these neurocognitive domains. For example, these skills have been shown to improve through training in domain specific cognitive remediation, especially among those with the most significant neurocognitive challenges (Rodewald et al., 2014).

In accordance with predictions related to our second research question, curvilinear relationships were detected, especially among breadth and neurocognition. There was a significant quadratic effect of amount of community participation on verbal memory, such that after about 100 days of participation (indicating some participation in at least three participation areas), the magnitude of the linear effect began to decline. There were also significant quadratic effects of breadth of community participation on overall neurocognitive functioning and motor speed, with a decline in magnitude occurring after about three to five participation areas. These specific findings are consistent with notions of cognitive load (Sweller, 1988), and are unsurprising given that verbal memory is a domain of neurocognition that has been shown to be particularly sensitive to the effects of anxiety and stress (Dorenkamp & Vik, 2018), while motor speed may be impeded by muscle fatigue in the face of increasing task demands and diversification (Gates & Dingwell, 2008). It may especially be the case that increased breadth, combined with the numerous socio-contextual barriers that individuals with serious mental illness often face [e.g., poverty (Pratt, 2012)], depletes neurocognitive resources (Gennetian & Shafir, 2015). This is a hypothesis that could be tested in future experimental studies. If supported, this would suggest that rehabilitation efforts that are focused on helping individuals reduce or cope with socio-contextual barriers to participation may also confer benefits for neurocognition.

There are a few limitations to this study that merit discussion and point to future research directions. This study was cross-sectional and correlational in nature; thus, future research should explore the directionality of the relationship between community participation and neurocognition among those with serious mental illnesses through longitudinal and experimental methods. While there is longitudinal evidence to suggest that community participation positively impacts neurocognition (Bowling et al., 2016; Richards et al., 2003; Yu et al., 2009), it is also possible that greater neurocognitive abilities shape community participation in some way (i.e., increase amount, narrow breadth after a certain point), or that the relationship is bidirectional. Second, the number of analyses conducted may have yielded spurious findings and it is important that follow- up studies be implemented to verify the relationships detected. Third, only a small percentage of the variance in neurocognition was explained by community participation in all models, indicating that additional predictors should be explored. These might include more direct measures of physical activity (Kurebayashi & Otaki, 2017), or social- contextual variables such as social isolation or loneliness (Badcock et al., 2015) or socioeconomic status (Mollon et al., 2016). Additionally, research should consider whether different types of community-based activities, for example, those that vary according to how physically rigorous or socially and environmentally stimulating they are, may have differential effects on neurocognition. Future research could also examine whether intermediary factors, such as motivation, explain the relationship between participation and neurocognition through approaches such as structural equation modeling. Finally, while relationships between community participation and neurocognition are not expected to differ between diagnostic groups, future research might explore this issue further.

Conclusions

Several important applications may be drawn from this study to further improve rehabilitation services for individuals with serious mental illnesses. First, in addition to interventions such as cognitive remediation, this study suggests that the promotion of opportunity for community participation may itself lead to improvement in neurocognitive functioning, presumably through the neurocognitive benefits associated with physical activity and environmental enrichment. Given that both personal problems (e.g., psychiatric symptoms) and socio-contextual/environmental obstacles (e.g., stigma, discrimination, and poverty) can limit participation in the community, rehabilitation services and supports that address both are needed in order to have maximal impact (Salzer, Baron, Menkir, & Breen, 2014). For example, rehabilitation providers and other supporters can assist individuals with prioritizing areas of community participation that are personally meaningful and help them access community-based resources to pursue these areas of participation, while also striving to make community spaces more welcoming and inclusive (Salzer et al., 2014).

Second, study findings indicate that the relationship between community participation and neurocognition varies depending on the manner in which participation is operationalized and the specific domain of neurocognition assessed. The relationship between amount and neurocognition appeared to be predominantly linear, while associations between breadth and various neurocognitive domains were mostly curvilinear. As stated previously, breadth may be more sensitive to the effects of cognitive load, presumably because it requires diversification and balancing of tasks and roles. Psychiatric rehabilitation providers may especially need to assist individuals with managing the cognitive demands of engaging in the variety of participation areas that are important to them. Based on the findings reported here, it also appears that domains of neurocognition that might benefit most from community participation are verbal fluency and, to a degree, motor speed (given that both amount and breadth of participation were significantly related to these particular domains). Further exploration of these relationships in future research will enhance clinical decision-making and assist rehabilitation providers and those whom they support with selection of participation- based interventions to more precisely target specific areas of neurocognition.

Finally, as research continues to elucidate optimal levels of community participation for neurocognition, rehabilitation providers can better assist individuals with making decisions about the amount and breadth of their participation.

Supplementary Material

Supplemental Material

Impact and Implications.

These findings suggest that there is a relationship between the amount and breadth of community participation and enhanced neurocognitive abilities, but are more complex than a direct linear relationship. Rehabilitation services and supports that focus on increasing opportunities for community participation may plausibly contribute to improved neurocognitive functioning among people with serious mental illnesses.

Acknowledgments

Source of Funding: Support for the research studies described herein was provided by two grants (90RT5021 and 90IF0065) from the National Institute on Disability, Independent Living and Rehabilitation Research (NIDILRR). The contents of this paper were developed with assistance from grant K08MH116101–01 from the National Institute of Mental Health (NIMH). However, the contents are solely the responsibility of the authors and do not necessarily represent the policy of the U.S. Department of Health and Human Services or the official views of the National Institutes of Health, and endorsement by the Federal government should not be assumed.

Footnotes

Conflicts of Interest: All authors declare that there are no financial, consultant, institutional, or other conflicts of interest associated with this research.

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