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The current study surveyed 234 traditional college-aged students to investigate expectancies that romantic partners had of cell phone usage during face-to-face interactions, how expectancy violations were managed, and whether violations ultimately detracted from the perceived quality of the relationship. Results revealed that cell phone usage behaviors occurring in public settings were viewed as significantly more unexpected, negatively valenced, and atypical than behaviors that occurred in private settings. Integrative communication strategies were the most common responses to partners’ negative cell phone usage behaviors; these strategies included talking to and sharing feelings with romantic partners. Romantic partners with higher relational satisfaction were more likely to use constructive communicative responses in response to negative cell phone usage behaviors. Additionally, cell phone satisfaction was positively correlated with relational satisfaction. Although mean scores indicated that romantic partners were generally indifferent to the use of the cell phone in face-to-face interactions in both public and private settings, results revealed through thematic analysis indicated that participants were indeed bothered by cell phone usage behaviors. Thus, the current study suggests that among college-aged students, the cell phone itself has become so integrated into individuals’ lives that cell phone-related behaviors have become normalized, and therefore, highly tolerated., Published as part of the University of Wisconsin-La Crosse Journal of Undergraduate Research, Volume 21 (2018)

Impaired strength adversely influences an older person’s ability to perform activities of daily living. A cross-sectional study of 117 independently living men and women (age = 73.4 ± 9.4 year; body mass index (BMI) = 27.6 ± 4.8 kg/m2) aimed to assess the association between body composition and: (1) upper body strength (handgrip strength, HGS); (2) lower extremity performance (timed up and go (TUG) and sit to stand test (STS)); and (3) endurance (6-minute walk (SMWT). Body composition (% fat; lean body mass (LBM)) was assessed using bioelectrical impedance. Habitual physical activity was measured using the Minnesota Leisure Time Physical Activity Questionnaire (MLTPA) and dietary macronutrient intake, assessed using 24 h recalls and 3-day food records. Regression analyses included the covariates, protein intake (g/kg), MLTPA, age and sex. For natural logarithm (Ln) of right HGS, LBM (p < 0.001) and % body fat (p < 0.005) were significant (r2 = 46.5%; p < 0.000). For left LnHGS, LBM (p < 0.000), age (p = 0.036), protein intake (p = 0.015) and LnMLTPA (p = 0.015) were significant (r2 = 0.535; p < 0.000). For SMW, % body fat, age and LnMLTPA were significant (r2 = 0.346; p < 0.000). For STS, % body fat and age were significant (r2 = 0.251; p < 0.000). LBM is a strong predictor of upper body strength while higher % body fat and lower physical activity are associated with poorer outcomes on tests of lower extremity performance.

Impaired strength adversely influences an older person’s ability to perform activities of daily living. A cross-sectional study of 117 independently living men and women (age = 73.4 ± 9.4 year; body mass index (BMI) = 27.6 ± 4.8 kg/m2) aimed to assess the association between body composition and: (1) upper body strength (handgrip strength, HGS); (2) lower extremity performance (timed up and go (TUG) and sit to stand test (STS)); and (3) endurance (6-minute walk (SMWT). Body composition (% fat; lean body mass (LBM)) was assessed using bioelectrical impedance. Habitual physical activity was measured using the Minnesota Leisure Time Physical Activity Questionnaire (MLTPA) and dietary macronutrient intake, assessed using 24 h recalls and 3-day food records. Regression analyses included the covariates, protein intake (g/kg), MLTPA, age and sex. For natural logarithm (Ln) of right HGS, LBM (p < 0.001) and % body fat (p < 0.005) were significant (r2 = 46.5%; p < 0.000). For left LnHGS, LBM (p < 0.000), age (p = 0.036), protein intake (p = 0.015) and LnMLTPA (p = 0.015) were significant (r2 = 0.535; p < 0.000). For SMW, % body fat, age and LnMLTPA were significant (r2 = 0.346; p < 0.000). For STS, % body fat and age were significant (r2 = 0.251; p < 0.000). LBM is a strong predictor of upper body strength while higher % body fat and lower physical activity are associated with poorer outcomes on tests of lower extremity performance.

Impaired strength adversely influences an older person’s ability to perform activities of daily living. A cross-sectional study of 117 independently living men and women (age = 73.4 ± 9.4 year; body mass index (BMI) = 27.6 ± 4.8 kg/m2) aimed to assess the association between body composition and: (1) upper body strength (handgrip strength, HGS); (2) lower extremity performance (timed up and go (TUG) and sit to stand test (STS)); and (3) endurance (6-minute walk (SMWT). Body composition (% fat; lean body mass (LBM)) was assessed using bioelectrical impedance. Habitual physical activity was measured using the Minnesota Leisure Time Physical Activity Questionnaire (MLTPA) and dietary macronutrient intake, assessed using 24 h recalls and 3-day food records. Regression analyses included the covariates, protein intake (g/kg), MLTPA, age and sex. For natural logarithm (Ln) of right HGS, LBM (p < 0.001) and % body fat (p < 0.005) were significant (r2 = 46.5%; p < 0.000). For left LnHGS, LBM (p < 0.000), age (p = 0.036), protein intake (p = 0.015) and LnMLTPA (p = 0.015) were significant (r2 = 0.535; p < 0.000). For SMW, % body fat, age and LnMLTPA were significant (r2 = 0.346; p < 0.000). For STS, % body fat and age were significant (r2 = 0.251; p < 0.000). LBM is a strong predictor of upper body strength while higher % body fat and lower physical activity are associated with poorer outcomes on tests of lower extremity performance.

Impaired strength adversely influences an older person's ability to perform activities of daily living. A cross-sectional study of 117 independently living men and women (age = 73.4 9.4 year; body mass index (BMI) = 27.6 4.8 kg/m2) aimed to assess the association between body composition and: (1) upper body strength (handgrip strength, HGS); (2) lower extremity performance (timed up and go (TUG) and sit to stand test (STS)); and (3) endurance (6-minute walk (SMWT). Body composition (% fat; lean body mass (LBM)) was assessed using bioelectrical impedance. Habitual physical activity was measured using the Minnesota Leisure Time Physical Activity Questionnaire (MLTPA) and dietary macronutrient intake, assessed using 24 h recalls and 3-day food records. Regression analyses included the covariates, protein intake (g/kg), MLTPA, age and sex. For natural logarithm (Ln) of right HGS, LBM (p < 0.001) and % body fat (p < 0.005) were significant (r2 = 46.5%; p < 0.000). For left LnHGS, LBM (p < 0.000), age (p = 0.036), protein intake (p = 0.015) and LnMLTPA (p = 0.015) were significant (r2 = 0.535; p < 0.000). For SMW, % body fat, age and LnMLTPA were significant (r2 = 0.346; p < 0.000). For STS, % body fat and age were significant (r2 = 0.251; p < 0.000). LBM is a strong predictor of upper body strength while higher % body fat and lower physical activity are associated with poorer outcomes on tests of lower extremity performance.

Impaired strength adversely influences an older person's ability to perform activities of daily living. A cross-sectional study of 117 independently living men and women (age = 73.4 9.4 year; body mass index (BMI) = 27.6 4.8 kg/m2) aimed to assess the association between body composition and: (1) upper body strength (handgrip strength, HGS); (2) lower extremity performance (timed up and go (TUG) and sit to stand test (STS)); and (3) endurance (6-minute walk (SMWT). Body composition (% fat; lean body mass (LBM)) was assessed using bioelectrical impedance. Habitual physical activity was measured using the Minnesota Leisure Time Physical Activity Questionnaire (MLTPA) and dietary macronutrient intake, assessed using 24 h recalls and 3-day food records. Regression analyses included the covariates, protein intake (g/kg), MLTPA, age and sex. For natural logarithm (Ln) of right HGS, LBM (p < 0.001) and % body fat (p < 0.005) were significant (r2 = 46.5%; p < 0.000). For left LnHGS, LBM (p < 0.000), age (p = 0.036), protein intake (p = 0.015) and LnMLTPA (p = 0.015) were significant (r2 = 0.535; p < 0.000). For SMW, % body fat, age and LnMLTPA were significant (r2 = 0.346; p < 0.000). For STS, % body fat and age were significant (r2 = 0.251; p < 0.000). LBM is a strong predictor of upper body strength while higher % body fat and lower physical activity are associated with poorer outcomes on tests of lower extremity performance.