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. Author manuscript; available in PMC: 2023 Nov 10.
Published before final editing as: Psychol Health. 2022 May 10:1–20. doi: 10.1080/08870446.2022.2074419

Affective Judgments, Environmental Determinants, and Physical Activity in Emerging and Young Adults

Taylor B Turrisi 1, Constantino M Lagoa 2, David E Conroy 1,3
PMCID: PMC9767299  NIHMSID: NIHMS1848233  PMID: 35535727

Abstract

Objective:

Affective judgements represent a promising target for promoting physical activity among adults. This study examined whether relations between affective judgments and physical activity are robust after adjusting for social, built, and natural environmental determinants.

Design:

Prospective cross-sectional study with 173 adults (70.1% female) aged 18–29 years who self-reported less than 90 minutes of moderate-to-vigorous physical activity.

Main Outcome Measure:

Physical activity volume (total daily step count, total activity counts) and durations of intensity-specific physical activity (light-intensity activity and moderate-to-vigorous intensity) were assessed for a seven-day period via waist-worn ActiGraph wGT3X-BT accelerometer.

Results:

Affective judgements were not statistically associated with measures of physical activity volume or intensity-specific physical activity after adjusting for environmental influences. Support for exercise from friends was positively associated with measures of physical activity volume and moderate-to-vigorous physical activity duration. More favorable perceptions of the built environment were positively associated with moderate-to-vigorous intensity physical activity and negatively associated with duration of light-intensity physical activity. Longer photoperiods were associated with more light-intensity physical activity.

Conclusion:

Physical activity interventions for young and emerging adults reporting inactivity should target environmental determinants first and possibly wait until participants have a motivational stake in physical activity before targeting affective judgments.

Keywords: Prospective studies, Social-ecological model, Multilevel influences, Exercise

Over 75% of U.S. adults aged 18–29 years fail to meet current aerobic physical activity guidelines, putting themselves at risk for poor health outcomes (2018 Physical Activity Guidelines Advisory Committee, 2018; Blewett, Rivera Drew, King, & Williams, 2019; Zenko, Willis, & White, 2019). Insufficiently active individuals within this age group have higher annual direct healthcare expenses than individuals meeting physical activity guidelines (Pratt, Macera, & Wang, 2000; Wang, Pratt, Macera, Zheng, & Heath, 2004). Physical activity is particularly important within this age group because physical activity behavioral patterns during this time may reduce the risk of midlife chronic disease (Racette, Deusinger, Strube, Highstein, & Deusinger, 2008). Physical activity volume and intensity-specific durations (referred to as physical activity herein) decrease from adolescence to early adulthood (Aira et al., 2021; Corder et al., 2019; Kwan, Cairney, Faulkner, & Pullenayegum, 2012). Thus, physical activity promotion efforts targeted towards individuals transitioning into adulthood may be particularly important in reducing midlife chronic disease risk.

Affective judgements, defined as the expectations corresponding to “the overall pleasure/displeasure, enjoyment, and feeling states expected from performing an activity” (Nasuti & Rhodes, 2013, p. 358), represent a promising target for physical activity promotion. Considerable evidence links affective judgments with physical activity but it is not clear whether those relations are robust across diverse environments or if those relations vary as a function of specific environmental features (Rhodes, Gray, & Husband, 2019; Williams, Rhodes, & Conner, 2019). The purpose of the present study was two-fold: (a) to estimate associations between affective judgments and device-based measures of physical activity volume and intensity-specific physical activity duration (adjusted for environmental features), and (b) to explore whether associations between affective judgments and device-based measures of physical activity volume and intensity-specific physical activity duration vary as a function of those environmental features.

Affective Judgments towards Physical Activity

Affective processes have emerged alongside cognitive beliefs as intrapersonal determinants of physical activity (Ekkekakis, Zenko, Ladwig, & Hartman, 2018; Williams & Evans, 2014). Affective experiences during physical activity shape affective judgments that “mediate relations between past affective experiences with physical activity and future physical activity performance” (Rhodes, 2017, p. 177). They are reflected in a person’s enjoyment of and intrinsic motivation for physical activity (Kendzierski & DeCarlo, 1991; Ryan, Frederick, Lepes, Rubio, & Sheldon, 1997).

Several prominent theories have incorporated aspects of affective judgments in their explanations for individual differences in physical activity. The multi-process action control model proposes that affective judgments, such as enjoyment, have a role in people both forming intentions to be physically active and in initiating physical activity behaviors (Rhodes, 2017). Self-determination theory proposes that affective judgments (i.e., intrinsic motivation) are directly involved in both the initiation and maintenance of physical activity behavior without any additional cognitive mediation (Deci & Ryan, 1985; Hagger & Chatzisarantis, 2007).

Whether affective judgments are defined as enjoyment or intrinsic motivation, they consistently exhibit positive associations with physical activity in both observational and experimental research. A meta-analysis of 112 independent samples (82 observational, 20 experimental) reported a significant medium-sized relationship between affective judgments and physical activity (r = 0.42, 95% CI: 0.37–0.46) (Rhodes, Fiala, & Conner, 2009). A separate meta-analysis that included 32 independent samples with experimental manipulations of affective judgments demonstrated that positive changes to affective judgments had a positive medium-to-large sized effect on physical activity (g = 0.43, 95% CI = 0.26–0.60) (Rhodes et al., 2019). This research has relied heavily on self-reports of physical activity frequency and volume (Rhodes et al., 2009, 2019). This literature does not provide a clear indication of how affective judgments of physical activity are associated with device-based measures of intensity-specific duration or total physical activity volume.

Environmental Influences on Ambulatory Physical Activity

The majority of the evidence base linking affective judgments with physical activity has focused on intrapersonal factors that motivate physical activity. Few studies have adjusted for the influence of the heterogeneous social-ecological contexts within which physical activity unfolds in daily life (Rhodes, Saelens, & Sauvage-Mar, 2018). Three social-ecological determinants in particular may influence how affective judgments are associated with physical activity: the social, built, and natural environments (McLeroy, Bibeau, Steckler, & Glanz, 1988; Sallis, Owen, & Fisher, 2008; Spence & Lee, 2003).

The social environment refers to the intangible human-developed environment involving the people and organizations that they have interacted or currently interact with (Barnett & Casper, 2001). Social relationships provide support and establish norms that inhibit or promote healthy behaviors (Heaney & Israel, 2008). The support of parents and friends have shown consistent positive associations with self-reported measures of physical activity in adolescence and adulthood (Anderssen & Wold, 1992; Li et al., 2016; McNeill, Kreuter, & Subramanian, 2006; Mendonça, Cheng, Mélo, & de Farias Júnior, 2014; Raudsepp & Viira, 2000). There is an absence of evidence regarding interactions between measures of affective judgment about physical activity and aspects of the social environment. Family and friends’ broader concerns about a person’s well-being may provide differential encouragement and support for activities the person enjoys, leading to stronger associations between affective judgments and physical activity.

The built environment refers to the tangible human-developed environment including aesthetics, access to transportation, land use mix, neighborhood walkability, proximity to recreational facilities, and traffic safety. These aspects of the built environment can facilitate or inhibit physical activity (Rhodes, Zhang, & Zhang, 2020; Sallis, Adams, & Ding, 2012; Sallis et al., 2020). Despite the physical features of the built environment being identical for individuals living in the same area, perceptions about the built environment can vary from person to person. Perceived aesthetic quality, pedestrian safety, and residential density have all been shown to be associated with physical activity (Bracy et al., 2014; Hoehner, Brennan Ramirez, Elliott, Handy, & Brownson, 2005; Lightfoot & Blanchard, 2011; Su et al., 2014). Like affective judgments, these perceptions are cognitive-evaluative entities that can influence physical activity. It is not presently clear if these perceptions can override affective judgments or change how affective judgments are associated with physical activity.

The natural environment consists of all living and non-living things that exist organically, and tend to be more difficult to alter than aspects of the social and built environments (van den Bosch, 2017). Photoperiod, often referred to as day length or the duration of illumination, is a slow-changing continuous marker of seasonal differences that correlates with temporally-smoothed weather indices, aligns with our interest in between-person differences, and does not require ongoing location tracking. Photoperiod duration is associated with both physical activity volume and intensity-specific activity duration. People are more active during summer and spring (when days are longer and temperatures are warmer) than winter (when days are shorter and temperatures are colder) (Chan, Ryan, & Tudor-Locke, 2006; Tucker & Gilliland, 2007; Turrisi et al., 2021). These associations have been observed for moderate-to-vigorous intensity physical activity duration and physical activity volume (Turrisi et al., 2021). One example of an interaction between affective judgments, the natural environment and physical activity is participation in outdoor physical activity. Individuals participating in outdoor physical activities have reported greater enjoyment and intention to repeat the activity than those participating in indoor activities (Thompson Coon et al., 2011).

The Present Study

This study investigated how affective judgments and key environmental features are associated with physical activity volume and intensity-specific physical activity duration in emerging and young adults. A cross-sectional study was conducted with baseline assessments of affective judgments and environmental contexts followed by a one-week ambulatory monitoring period during which participants wore an activity monitor (ActiGraph wGT3X-BT). The hypotheses for the study were that (1) affective judgments would be positively associated with device-based measures of physical activity volume and intensity-specific physical activity duration after adjusting for environmental influences, and (2) more favorable environments (i.e., more social support, perceptions of a more accessible built environment, and monitoring during summer or spring relative to winter) would be positively associated with physical activity. Analyses were extended to explore whether environmental features moderated associations between affective judgments and either physical activity volume or intensity-specific durations (e.g., stronger associations between affective judgments and physical activity when people perceive more social support, a more accessible built environment, and during summer or spring relative to winter). All analyses controlled for sex, an established demographic covariate of physical activity volume and intensity-specific physical activity duration during this developmental transition (Caspersen, Pereira, & Curran, 2000; Corder et al., 2019; Gordon-Larsen, Nelson, & Popkin, 2004; Kwan et al., 2012; Nelson, Neumark-Stzainer, Hannan, Sirard, & Story, 2006).

Methods

Participants and Procedures

Participants were community-dwelling emerging and young adults recruited in central Pennsylvania who self-identified as being insufficiently active and expressed interest in a parent study utilizing a smartphone application to increase physical activity levels. Criteria for inclusion included English fluency, being between the ages of 18–29, owning an Apple (≥ iOS 10) or Android (≥ Android OS 7) smartphone (a requirement for the parent study), and reporting less than 90 min/week of moderate-to-vigorous physical activity. Participants with a visual impairment that would interfere with smartphone use were excluded because of parent study requirements. Recruitment was accomplished via fliers posted in the community and online. All participants provided written informed consent, and the study protocol was approved by the Institutional Review Board of Penn State University (study#00009455). Data for these analyses were collected from April 2019 to January 2020.

Prior to enrolling in the study, individuals completed a brief telephone screening to establish eligibility (i.e., no medical contraindications to physical activity and self-reporting less than 90 minutes of past-week moderate-to-vigorous intensity physical activity). Interested eligible participants were scheduled for a study training session in the lab. At the training session, participants reviewed and signed an informed consent document, completed a battery of questionnaires, and were trained how to wear an activity monitor provided by the research team (ActiGraph wGT3X-BT) and instructed to wear the activity monitor for at least 10 hours/day, removing it for bathing or swimming, over a 7-day period. Participants were also provided with a wear log and instructed to record any period of time that the device was removed. At the end of the seven-day monitoring period, participants returned the activity monitor and wear log to the lab and received $25 as compensation for their participation. All data were collected between April 2019 and January 2020 (i.e., prior to the COVID-19 pandemic).

Measures

Device-measured physical activity.

Participants wore an ActiGraph wGT3X-BT accelerometer around their waist for seven consecutive days to measure physical activity (Actigraph, LLC, Pensacola, FL). This device was selected because it is widely viewed as a premier research-grade device for ambulatory assessment of physical activity and does not provide real-time behavioral feedback that could alter a participant’s behavior. The epoch length used for accelerometer-based data collection was set to 60 seconds. Accelerometer data was extracted using ActiLife software (v.6.6.1). Wear time was computed the Troiano algorithm in the Actilife software after entering the wear log data as a filter. For quality control, days with wear times of 10 hours or greater were considered valid, and participants were included in analyses if they had at least four valid days of accelerometer data (Migueles et al., 2017; Trost, McIver, & Pate, 2005). Outcome measures included measures of volume (daily step counts, total vector magnitude counts) and intensity-specific durations, expressed as mean values per valid day. The Freedson cut points for adults were used to classify sedentary (< 100 counts per minute [cpm]), light- (100–1951 cpm) and moderate-to-vigorous intensity physical activity (1952+ cpm; Freedson, Melanson, & Sirard, 1998).

Enjoyment.

The 18-item Physical Activity Enjoyment Scale (PACES) assessed the extent to which an individual enjoys performing physical activity over the previous four weeks (Kendzierski & DeCarlo, 1991). A sample item was, “I enjoyed the physical activity.” Items were rated on a five-point scale with the following options: 1 (strongly disagree), 2 (disagree somewhat), 3 (neither agree nor disagree), 4 (agree somewhat), and 5 (strongly agree). Eleven items were reverse-scored prior to averaging so higher scores represented greater levels of enjoyment towards performing physical activity. Enjoyment scores on the PACES have demonstrated acceptable internal consistency and test-retest reliability in young adults (Kendzierski & DeCarlo, 1991).

Intrinsic motivation.

The 7-item interest/enjoyment subscale from the 23-item Intrinsic Motivation Inventory (IMI – Interest and Enjoyment) was used to assess intrinsic motivation related to physical activity performed during the previous month (McAuley, Duncan, & Tammen, 1989). A sample item was, “The physical activities were fun to do.” Items were rated on a scale from 1 (not at all true for me) to 7 (very true for me). Two items were reverse-scored prior to averaging so higher scores represented greater levels of interest and enjoyment towards performing physical activity. Previous research has shown that the interest/enjoyment subscale scores have acceptable construct validity and reliability in young adults (McAuley et al., 1989).

Social environment.

The 26-item Social Support and Exercise Survey (SSES) measured support from family and friends towards exercising in the past three months (Sallis, Grossman, Pinski, Patterson, & Nader, 1987). A sample item was, “During the past three months, my family (or members of my household) exercised with me.” The scale contains three subscales: Family – Participation (10 items), Family – Rewards and Punishment (3 items), Friends – Participation (10 items). Items were rated based on frequency of perceived support on a scale ranging from 1 (none of the time), 2 (rarely), 3 (a few times), 4 (often), and 5 (very often). Higher scores represent greater amounts of perceived social support from that source. Scores from each subscale has demonstrated acceptable test-retest and internal consistency reliabilities in an adult population. The Friends – Rewards and Punishment subscale was not scored because it did not emerge as a distinct factor of the original validation study (Sallis et al., 1987).

Perceptions of the built environment.

The 7-item Built Environment Index (BEI) from the 17-item Physical Activity and Neighborhood Environment Scale was used to assess built environmental support for physical activity in the form of access to facilities, aesthetics, infrastructure, land use mix, residential density, and traffic safety (Sallis et al., 2010). Participants rated the area that can be walked to within 15 minutes of their residence. Item 1 asked respondents about the main type of housing in their neighborhood, with options including “detached single-family housing”, “townhouses/rowhouses/apartments/condos of 2–3 stories”, “mix of single-family residences, townhouses, row houses, apartments, or condos”, “apartments or condos of 4–12 stories”, “apartments or condos of more than 12 stories”, and “don’t know” (NA). Items 2–6 were rated as 1 (strongly disagree), 2 (somewhat disagree), 3 (somewhat agree), or 4 (strongly agree), and “don’t know” (NA). Responses to each item were dichotomized for scoring purposes (item 1: 0=single family housing, 1=all other housing types; items 2–6: 0=strongly or somewhat disagree, 1=strongly or somewhat agree). Dichotomized scores were summed to create an overall built environment score with higher numbers indicating greater perceived support for physical activity from the built environment. Responses to BEI items have been significantly associated with meeting physical activity guidelines (i.e., the more supportive the reported built-environmental attributes, the greater the likelihood of sufficient physical activity) (i.e., the more supportive the reported built-environmental attributes, the greater the likelihood of sufficient physical activity; Sallis et al., 2010).

Natural environment.

Photoperiod duration was quantified as the distance between the first day of ambulatory monitoring and the equinox. The summer (June 21) and winter (December 21) solstices have the maximum and minimum photoperiods, respectively, in the Northern Hemisphere. Distance was measured in radians based on a cosine curve peaking on the summer solstice. Positive and negative values indicate longer and shorter photoperiods, respectively (values of zero coincide with the spring or autumnal equinox). The maximum value for photoperiod (in radians) was 1.0 (summer solstice) whereas the minimum value was −1.0 (winter solstice).

Data Analysis

All statistical analyses were performed using R Studio (R Studio Team, 2020). Descriptive statistics were calculated for all demographic, motivational and physical activity variables, whereas measures of reliability were calculated using the psych package (Revelle, 2020). Bivariate correlation analyses between continuous variables were performed using the Hmisc package (Harrell & Dupont, 2021). Standardized regression coefficients for multiple linear regression models were calculated using the lm.beta package (Behrendt, 2014).

The level to achieve statistical significance was set to α = .05. Listwise deletion was performed if individuals were missing ≥ 20% of responses for each psychological measures or subscales. All continuous independent variables were centered. A composite measure of affective judgment was calculated by calculating and averaging z-scores for each participant’s enjoyment and intrinsic motivation scores. The primary hypotheses and secondary hypothesis utilized multiple linear regression with separate models for each type of device-measured physical activity (i.e., mean daily activity counts, mean daily step counts, mean daily minutes of light-intensity physical activity, mean daily minutes of moderate-to-vigorous physical activity) and each affective judgment measure (i.e., enjoyment, intrinsic motivation, composite affective judgment). All models included variables relating to the perceived built, social, and natural environments and sex. Sensitivity analyses were performed using a sample selected on alternative wear-time criteria (≥5 days with ≥8 hours/day) (Carlson et al., 2012; Thabane et al., 2013).

Results

One hundred and seventy-three participants met inclusion criteria and wore an ActiGraph wGT3X-BT accelerometer around their waist for seven consecutive days to measure physical activity. Twenty-six individuals were excluded from the main analysis sample for not meeting wear time criteria (i.e., ≥4 days, ≥10 hours/day), whereas 11 individuals were excluded from the sensitivity analysis sample for not meeting wear criteria (i.e., ≥5 days, ≥8 hours/day). An additional 10 individuals were removed from the main analysis sample whereas 11 individuals were removed from the sensitivity analysis sample for not having sufficient data for included psychosocial measures (i.e., ≥80% for included measures and subscales). Descriptive statistics for the main analysis sample and sensitivity analysis sample are presented in Table 1. On average, participants in the main analysis sample (N = 137) were 22.82 years old (SD = 2.78), wore the accelerometer for 10.55 hours each day (SD = 1.23), and had a BMI of 26.63 (SD = 6.66).

Table 1.

Sample demographic and anthropometric characteristics

Main Analysis Sample (n = 137) Sensitivity Analysis Sample (n = 151)
Characteristic N (%) N (%)
Sex
 Male 41 (29.9) 48 (31.8)
 Female 96 (70.1) 103 (68.2)
Age (years)
 18–21 52 (38.0) 61 (40.4)
 22–25 55 (40.1) 57 (37.8)
 26–29 30 (21.9) 33 (21.9)
Ethnicity
 Not Hispanic/Latino 123 (89.8) 135 (89.4)
 Hispanic/Latino 14 (10.2) 16 (10.6)
Racial Identity
 Asian 27 (19.7) 29 (19.2)
 Black/African American 20 (14.6) 20 (13.2)
 Two or More Races 7 (5.1) 8 (5.3)
 White 82 (59.9) 93 (61.6)
Education
 Completed high school/received GED 18 (13.1) 19 (12.6)
 Trade/technical school certificate 3 (2.2) 3 (2.0)
 Some college/associate’s degree 50 (36.5) 56 (37.1)
 Completed college 44 (32.1) 48 (31.8)
 Graduate or professional degree 22 (16.1) 25 (16.6)
Work Status
 Employed full-time 15 (10.9) 18 (11.9)
 Employed part-time 10 (7.3) 13 (8.6)
 Student 109 (79.6) 117 (77.5)
 Unemployed 3 (2.2) 3 (2.0)
BMI (kg/m2)
 Underweight (< 18.5 kg/m2) 6 (4.4) 6 (4.0)
 Normal weight (18.5 – 24.9 kg/m2) 62 (45.3) 68 (45.0)
 Overweight (25.0 – 29.9 kg/m2) 35 (25.5) 43 (28.5)
 Obese (> 30.0 kg/m2) 33 (24.1) 33 (21.9)
2018 Physical Activity Guidelines for Americans
 Did not meet guidelines 69 (50.4) 71 (47.0)
 Met guidelines 68 (49.6) 80 (53.0)
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Note. Determination of whether participants met the 2018 Physical Activity Guidelines for Americans were based on data from the accelerometers during the one-week monitoring period.

Physical activity data and scores from psychosocial measurements for the main analysis sample are summarized in Table 2. Participants in the main analysis sample averaged 4746.31 steps/day (SD = 1946.70), 145.67 minutes/day of light-intensity physical activity (SD = 49.10), 26.82 minutes/day of moderate-to-vigorous physical activity (SD = 18.02), and 297,185.30 total activity counts/day (SD = 109,151.90).

Table 2.

Descriptive statistics and bivariate correlations for study variables

Measure M SD α 1 2 3 4 5 6 7 8 9 10 11
Physical Activity
 1. TAC/day 297,185.30 109,151.90 -- --
 2. Steps/day 4746.31 1946.70 -- .83 --
 3. MVPA (min/day) 26.82 18.02 -- .81 .87 --
 4. LPA (min/day) 145.67 49.10 -- .60 .34 .14 --
Affective Judgment
 5. Enjoyment 64.70 9.40 .88 .03 .10 .05 .08 --
 6. Intrinsic Motivation 4.30 1.07 .90 .10 .13 .09 .10 .73 --
Social Environment
 7. Family – Participation 21.05 11.63 .93 .10 .14 .10 .03 −.07 −.01 --
 8. Family – Rewards and Punishment 4.91 4.43 .94 .00 .01 .04 −.09 −.13 −.06 .67 --
 9. Friends – Participation 20.10 9.12 .90 .21 .21 .19 .06 .07 .13 .53 .45 --
Perceptions of the Built Environment
 10. PANES – BEI 4.45 4.45 .57 .05 .14 .25 −.23 .07 .05 .03 .11 .03 --
 Natural Environment
 11. Photoperiod 0.05 0.72 -- .00 −.09 −.17 .20 −.21 −.13 .13 .11 .04 −.22 --
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Note: Bolded values denote statistical significance (p < .05). TAC = total activity counts. MVPA = moderate-to-vigorous intensity physical activity. LPA = light intensity physical activity. PANES – BEI = Physical Activity Neighborhood Survey – Built Environment Index.

Enjoyment and intrinsic motivation scores were positively associated (r = .73, p < .001). Neither measure of affective judgment demonstrated a significant bivariate association with any measure of physical activity. Average daily step count (r = .21, p = .01) and moderate-to-vigorous physical activity duration (r = .19, p = .004) were positively associated with support from friends. Overall perceptions of the built environment were positively associated with moderate-to-vigorous physical activity duration (r = .25, p = .004), but negatively associated with light-intensity physical activity duration (r = −.23, p = .007). Photoperiod was positively associated with light-intensity physical activity duration (r = .20, p = .02) and negatively associated with moderate-to-vigorous physical activity duration (r = −.17, p = .04). Average daily activity counts were positively associated with support from friends (r = .20, p = .01).

Multiple Regression Models

The primary hypotheses for the study were that (1) affective judgments would be positively associated with physical activity after adjusting for environmental influences (i.e., Hypothesis 1), and (2) more favorable environments would be positively associated with physical activity (i.e., Hypothesis 2). Table 3 presents coefficients from multiple linear regression models to test these hypotheses with measures of physical activity volume. Models of total daily activity counts were not statistically significant whether they included enjoyment (F[7, 129] = 1.22, p = .30, R2 = .06), intrinsic motivation (F[7, 129] = 1.28, p = .26, R2 = .06) or composite affective judgments (F[7, 129] = 1.23, p = .29, R2 = .06). Similarly, models of daily step counts were not statistically significant for enjoyment (F[7, 129] = 2.03, p = .06, R2 = .10) or composite affective judgments (F[7, 129] = 2.08, p = .06, R2 = .10). The model of daily step counts with intrinsic motivation was statistically significant (F[7, 129] = 2.13, p =.04, R2 = .10) but none of the coefficients for predictor variables were statistically significant in that model. Thus, Hypothesis 1 was rejected for total physical activity volume.

Table 3.

Coefficients for multiple linear regression of measures of physical activity volume on affective judgments, environmental determinants, and sex

Enjoyment Model Intrinsic Motivation Model Composite Affective Judgment Model
b (SE) B p b (SE) B p b (SE) B p
Total Activity Counts
 Intercept 296,603.20 (17,261.45) 0.00 <.001 295,759.40 (17,283.80) 0.00 <.001 296,477.00 (17,258.30) 0.00 <.001
 Affective Judgment −77.62 (1032.21) −0.01 0.94 5743.20 (8984.80) 0.06 0.52 3168.50 (10,392.40) 0.03 0.76
 Family - Participation 759.48 (1167.07) 0.08 0.52 758.80 (1165.00) 0.08 0.52 764.90 (1166.40) 0.08 0.51
 Family - Rewards & Punishment −4163.03 (2929.35) −0.17 0.16 −3919.50 (2919.60) −0.16 0.18 −4017.00 (2929.10) −0.16 0.17
 Friends - Participation 2902.73 (1236.05) 0.24 <.05 2746.90 (1240.90) 0.23 <.05 2822.80 (1241.50) 0.24 <.05
 Perceived Built Environment 3963.69 (6000.82) 0.06 0.51 3753.40 (5993.80) 0.06 0.53 3854.60 (6000.90) 0.06 0.52
 Photoperiod 2745.34 (13,580.78) 0.02 0.84 3928.40 (13,426.20) 0.03 0.77 3589.80 (13,525.40) 0.02 0.79
 Sex (Female) 830.71 (20,776.93) 0.00 0.97 2034.90 (20,827.90) 0.01 0.92 1010.80 (20,774.40) 0.00 0.96
Step Counts
 Intercept 4496.89 (301.73) 0.00 <.001 4470.49 (301.81) 0.00 <.001 4486.26 (301.35) 0.00 <.001
 Affective Judgment 8.88 (18.04) 0.04 0.62 149.64 (156.89) 0.08 0.34 141.36 (181.46) 0.07 0.44
 Family - Participation 23.67 (20.40) 0.14 0.25 23.38 (20.34) 0.14 0.25 23.60 (20.37) 0.14 0.25
 Family - Rewards & Punishment −76.51 (51.20) −0.17 0.14 −74.17 (50.98) −0.17 0.15 −74.53 (51.15) −0.17 0.15
 Friends - Participation 43.02 (21.61) 0.20 <.05 40.87 (21.67) 0.19 0.06 41.62 (21.68) 0.19 0.06
 Perceived Built Environment 150.01 (104.89) 0.13 0.16 147.17 (104.66) 0.12 0.16 148.13 (104.78) 0.12 0.16
 Photoperiod −167.20 (237.39) −0.06 0.48 −162.37 (234.45) −0.06 0.49 −158.95 (236.17) −0.06 0.50
 Sex (Female) 355.94 (363.18) 0.08 0.33 393.62 (363.70) 0.09 0.28 371.11 (362.74) 0.09 0.31
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Note: Bolded values denote statistical significance (p < .05). b = unstandardized beta coefficient, SE = standard error, B = standardized beta coefficient. Outcomes for the enjoyment, intrinsic motivation, and composite affective judgment models were the Physical Activity Enjoyment Scale, the Intrinsic Motivation Inventory (interest/enjoyment scale), and a composite score based on standardized scores from those measures, respectively.

Table 4 summarizes coefficients from multiple regression models of intensity-specific activity duration. Models of daily moderate-to-vigorous physical activity duration were statistically significant whether they included enjoyment (F[7, 129] = 2.56, p = .02, R2 = .12), intrinsic motivation (F[7, 129] = 2.60, p = .02, R2 = .12), or composite affective judgments (F[7, 129] = 2.56, p = .02, R2 = .12). Moderate-to-vigorous physical activity duration was not significantly associated with affective judgments in any of these models but it was associated with friends’ support of physical activity in the models with enjoyment and composite affective judgments (but not in the model with intrinsic motivation; p = .06). Duration of moderate-to-vigorous physical activity was positively associated with perceptions of the built environment in all three models. Neither photoperiod nor sex was found to be significantly associated with duration to moderate-to-vigorous physical activity duration in any of the three models. Thus, Hypothesis 1 was rejected for moderate-to-vigorous intensity physical activity duration. Hypothesis 2 was partially supported based on positive associated between moderate-to-vigorous intensity physical activity duration and both the social and perceived built environments.

Table 4.

Coefficients for multiple linear regression of intensity-specific activity duration on affective judgments, environmental determinants, and sex

Enjoyment Model Intrinsic Motivation Model Composite Affective Judgment Model
b (SE) B p b (SE) B p b (SE) B p
Moderate-to-Vigorous Activity
 Intercept 25.13 (2.76) 0.00 <.001 25.04 (2.76) 0.00 <.001 25.13 (2.76) 0.00 <.001
 Affective Judgment −0.03 (0.16) −0.02 0.85 0.69 (1.44) 0.04 0.63 0.26 (1.66) 0.01 0.88
 Family - Participation 0.09 (0.19) 0.06 0.64 0.09 (0.19) 0.06 0.64 0.09 (0.19) 0.06 0.64
 Family - Rewards & Punishment −0.40 (0.47) −0.10 0.39 −0.36 (0.47) −0.09 0.44 −0.38 (0.47) −0.09 0.42
 Friends - Participation 0.40 (0.20) 0.20 <.05 0.38 (0.20) 0.18 0.06 0.39 (0.20) 0.20 <.05
 Perceived Built Environment 2.36 (0.96) 0.21 <.05 2.33 (0.96) 0.21 <.05 2.35 (0.96) 0.21 <.05
 Photoperiod −3.25 (2.17) −0.13 0.14 −3.05 (2.15) −0.12 0.16 −3.12 (2.16) −0.13 0.15
 Sex (Female) 2.40 (3.32) 0.06 0.47 2.53 (3.33) 0.06 0.45 2.40 (3.32) 0.06 0.47
Light Intensity Activity
 Intercept 143.66 (7.54) 0.00 <.001 142.60 (7.55) 0.00 <.001 143.11 (7.53) 0.00 <.001
 Affective Judgment 0.57 (0.45) 0.11 0.21 5.44 (3.93) 0.12 0.17 6.48 (4.53) 0.12 0.16
 Family - Participation 0.35 (0.51) 0.08 0.50 0.33 (0.51) 0.08 0.52 0.34 (0.51) 0.08 0.51
 Family - Rewards & Punishment −1.85 (1.28) −0.17 0.15 −1.86 (1.28) −0.17 0.15 −1.82 (1.28) −0.16 0.16
 Friends - Participation 0.43 (0.54) 0.08 0.43 0.40 (0.54) 0.07 0.47 0.40 (0.54) 0.07 0.47
 Perceived Built Environment −5.67 (2.62) −0.19 <.05 −5.72 (2.62) −0.19 <.05 −5.72 (2.62) −0.19 <.05
 Photoperiod 12.62 (5.93) 0.19 <.05 12.20 (5.87) 0.18 <.05 12.60 (5.90) 0.19 <.05
 Sex (Female) 2.87 (9.08) 0.03 0.75 4.39 (9.10) 0.04 0.63 3.66 (9.06) 0.03 0.69
Open in a new tab

Note: Bolded values denote statistical significance (p < .05). b = unstandardized beta coefficient, SE = standard error, B = standardized beta coefficient. Outcomes for the enjoyment, intrinsic motivation, and composite affective judgment models were the Physical Activity Enjoyment Scale, the Intrinsic Motivation Inventory (interest/enjoyment scale), and a composite score based on standardized scores from those measures, respectively.

Models of light-intensity activity duration were statistically significant whether they included enjoyment (F[7, 129] = 2.33, p = .03, R2 = .11), intrinsic motivation (F[7, 129] = 2.38, p = .03, R2 = .11), or composite affective judgments (F[7, 129] = 2.40, p = .02, R2 = .12). Light-intensity physical activity duration was not significantly associated with any of the affective judgments. It was negatively associated with perceptions of the built environment, positively associated with photoperiod, and not significantly associated with the social environment. Thus, Hypothesis 1 was rejected for light intensity-specific physical activity duration but Hypothesis 2 was partially supported based on positive associations between light-intensity physical activity and both the perceived built environment and natural environment.

Exploratory Moderation Analyses

When two-way interactions between affective judgments and environmental factors were added to the multiple linear regression models of total physical activity volume and intensity-specific durations, none of the models in the main analysis sample achieved statistical significance (all p < .05).

Sensitivity Analyses

All variables that achieved significance in bivariate correlation and multiple linear regression analyses in the main analyses sample also achieved significance in the sensitivity analysis sample. Conclusions about the main hypotheses did not change; however, a limited number of additional associations achieved significance in the sensitivity analysis sample due to the increased sample size and statistical power.

Discussion

This study tested associations between device-based measures of physical activity volume and intensity-specific physical activity, affective judgments towards physical activity, and the social, built, and natural environments. The hypothesis that affective judgments would be positively associated with physical activity after adjusting for environmental influences was not supported. The hypothesis that more favorable environments would be positively associated with physical activity was partially supported. Support from friends (i.e., more favorable social environment) was positively associated with measures of physical activity volume and moderate-to-vigorous physical activity duration. More favorable perceptions of the built environment were positively associated with moderate-to-vigorous intensity physical activity and negatively associated with duration of light-intensity physical activity. A longer photoperiod (i.e., more favorable natural environment) was associated with more light-intensity physical activity. This study made four important contributions to the literature on physical activity during the transition into adulthood.

First, results indicated that conclusions from a recent meta-analysis may not generalize to samples reporting (though not necessarily not recording) low levels of physical activity (Rhodes et al., 2009). Point estimates for bivariate correlations between affective judgements and device-based measures of physical activity in the current study ranged were small, whereas estimates from the recent meta-analysis were medium-sized (Rhodes et al., 2009). This meta-analysis consisted of 85 independent samples of individuals aged ≥18 whereas the current study examined individuals that identified as being insufficiently active (i.e., do not meet federal guidelines for physical activity) between 18–29 years old. It is possible that believing that one is not physically active weakens the association between affective judgments and physical activity. Future research should investigate the possibility that self-schemas (e.g., exercise identity), physical self-perceptions, or other self-related beliefs may moderate the influence of affective judgments on physical activity (Sabiston, Whitehead, & Eklund, 2012). Activity judgments may also vary by activity type so future research should examine whether type-specific judgments predict specific physical activities better than others.

Second, this study raises the possibility that measurement methods for physical activity may impact conclusions about relations with affective judgments. The vast majority of the existing evidence used self-report measures of physical activity. In a seminal meta-analysis, only five of the 82 correlational studies used device-based measures of physical activity (Rhodes et al., 2009). Of those five studies, only two used accelerometers to measure physical activity. In contrast, the present study used accelerometers to measure both physical activity volume and intensity-specific duration when estimating associations with affective judgements towards physical activity. The limitations of self-reported physical activity are well-known (e.g., recall bias, memory errors; Prince et al., 2008). Future research on affective judgments should prioritize device-based measures to evaluate the impact of measurement methods on conclusions. Although it is possible that prior conclusions about relations between affective judgments and physical activity were incorrect, we believe that judgment is premature for two reasons. First, as noted above, our sample was selected for insufficient physical activity. Excluding the most active people will restrict the range of variance in physical activity and attenuate associations with other variables (e.g., affective judgments). Second, this study suggests a boundary condition for the role of affective judgments because they “are not just about what is, but also about what matters” (Dukes et al., 2021, p. 1). For people who report being insufficiently active, physical activity may not be a sufficiently-salient goal for affective judgments to regulate behavior. Our working conclusion based on this study is that affective judgments are not a validated target for promoting activity among those who identify as insufficiently active, but that hypothesis should be tested directly in future work to refine the operating conditions for affective judgments as an intervention target. In the meantime, interventions should prioritize other targets, such as environmental variables.

A third contribution of the study was in identifying different patterns of built and natural environmental determinants for different physical activity intensities. Bivariate correlation analyses demonstrated that a longer photoperiod was positively associated with light-intensity physical activity duration and negatively associated with moderate-to-vigorous intensity physical activity duration. However, it is noteworthy that the positive association between photoperiod and light-intensity physical activity duration achieved significance in regression analyses whereas the negative association between photoperiod and moderate-to-vigorous intensity physical activity duration was not present in regression analyses. This discrepancy may indicate that seasonality and photoperiod influence activity selection, with these selections having potential consequences for intensity-specific duration. The positive association between photoperiod and light-intensity physical activity duration is consistent with previous findings (Turrisi et al., 2021). The present study provides additional insight into the relationship between photoperiod and intensity-specific physical activity duration as this topic had not been explored in young and emerging adults who report being insufficiently active.

Both bivariate and multiple linear regression analyses demonstrated that more favorable perceptions of the built environment were positively associated with moderate-to-vigorous physical activity duration and negatively associated with light-intensity physical activity duration. The positive association between moderate-to-vigorous physical activity duration and perceptions of the built environment was consistent with prior finding. Perceived infrastructure, safety, proximity to recreational facilities, and aesthetics have all demonstrated positive associations with moderate-to-vigorous physical activity duration (Sallis et al., 2020). The negative association between light-intensity physical activity duration and perceptions of the built environment appears to be a novel finding. Considerable research has investigated associations between perceptions of the built environment and step count, but only one other study has investigated associations between perceptions of the built environment and light-intensity physical activity (Jago, Baranowski, & Baranowski, 2006). That study found that perceptions of the built environment demonstrated a null association with light-intensity physical activity; however, it sampled youth rather than young and emerging adults. Additional research in this area is warranted to replicate these findings in young and emerging adults that identify as being insufficiently active.

The subscale used to measure perceptions of the built environment did so in a residential context, although many individuals spend a significant portion of their time in other contexts. Future research should also consider either capturing perceptions of the built environment in areas where an individual spends considerable time (e.g., home, work) and the greater context of the individuals’ residence (i.e., municipality) and/or capturing time-in place as a potential moderating variable between perceptions of the built environment and device-based measures of physical activity (Matthews, 2017).

The fourth contribution of this study was based on the differing pattern of results within the context of the social environment. Support from friends in physical activity participation was found to be positively associated with moderate-to-vigorous physical activity duration. These findings are consistent with previous research on intensity-specific physical activity duration and social support including similar populations (De Bourdeaudhuij, Sallis, & Vandelanotte, 2002; Dowda, Ainsworth, Addy, Saunders, & Riner, 2003; Treiber et al., 1991). Support from friends in physical activity participation was also found to be positively associated with total daily activity counts and total daily step counts. Friend-based social support towards exercise and measures of physical activity volume activity have demonstrated similar associations in youth and older adults but remains understudied in young and emerging adults (Mendonça et al., 2014; Smith, Banting, Eime, O’Sullivan, & van Uffelen, 2017).

Neither support from parents in physical activity participation nor parental rewards and punishments for participating in physical activity were found to be significantly associated with either measure of physical activity volume or intensity-specific duration. Future research should investigate whether these associations can be replicated longitudinally, as high turnover among friendships occurs during young and emerging adulthood and parental units may present stability during an otherwise unstable time (Arnett, 2000).

Key limitations of this study should be noted. First, environmental variables were assessed as narrow, static influences; future work should consider conducting multi-dimensional audits of the built environment, collecting measures of support for physical activity from parents and friends, capturing a broader range of features from the natural environment, and quantifying exposure differences as a function of mobility. Second, waist worn accelerometers systematically undercount activities such as cycling, strength training, and swimming. Although four days of ambulatory monitoring is widely viewed as sufficient to estimate reliability individual differences (Migueles et al., 2017), it was not clear whether activity during the ambulatory monitoring period was representative of their usual physical activity. Third, participants were excluded if they did not own a smartphone so conclusions may not generalize to the approximately 4% of young adults who do not own smartphones (Pew Research Center, 2021). Fourth, analyses focused on person-level variation and were not sensitive to daily fluctuations in behavior or environmental context. Fifth, the sample size was not large enough to detect unexpectedly weak associations. Finally, the research design was cross-sectional so strong causal inferences are not possible.

In sum, affective judgments were not significantly associated with device-based measures of physical activity volume or intensity-specific duration in a population that reported low levels of physical activity. Features of the social environment were positively associated with physical activity volume and intensity-specific duration. Features of the built and natural environments demonstrated mixed associations with measures of intensity-specific physical activity duration. These results can contribute to the development of multilevel physical activity interventions for college students. Specifically, the findings suggest that including friends in promotion efforts to increase physical activity volume and moderate-to-vigorous physical activity in emerging adults may be beneficial. Future efforts to promote moderate-to-vigorous activity should also try to enhance perceptions of the built environment. Interventions seeking to promote light-intensity physical activity may be needed most between the spring and autumnal equinox.

Supplementary Material

Supp 1

Acknowledgments

We thank Ms. Deborah Brunke-Reese for her contributions to this study.

The project was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH) through Grant R01 HL142732. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The authors declare that there are no competing interests.

Data Availability Statement.

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

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Associated Data

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Supplementary Materials

Supp 1
NIHMS1848233-supplement-Supp_1.docx (80KB, docx)

Data Availability Statement

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

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