Predictors Of Physical Activity Levels Research Articles

Association of sociodemographic, anthropometric, and sleep quality factors with accelerometer-measured sitting and physical activity times among Emirati working women during the COVID-19 pandemic: A cross-sectional study.

Although a significant lack of physical activity has been linked to an increase in obesity among Emirati women, the factors associated with accelerometer-measured sitting and physical activity times in Emirati women remain unclear. To explore the association of accelerometer-measured sitting and physical activity times with sociodemographic, anthropometric, and sleep quality factors among Emirati working women. A cross-sectional study. A convenience sample of 163 healthy working Emirati women aged 18-45 years was used. Sedentary and physical activity times were measured using the Fibion accelerometers worn on the thighs for 4-7 days. General demographic information, anthropometric measurements, and self-reported sleep quality (Pittsburgh sleep quality index score) were collected. Only participants who had valid data (i.e. wear time of ⩾600 min (10 h) per day for a minimum of 4-7 days) were evaluated. All values were normalized to a 16-h day to mitigate differences in wear time among the participants. Overall, 110 Emirati women were included. The mean sitting time per 16-h day was 11.6 ± 1.1 h; mean moderate activity time per day, 40.88 ± 17.99 min; and mean vigorous activity time per day, 2.41 ± 1.21 min. Longer sitting time was associated with high body fat, secondary education, and divorce. Sitting time was reduced in those with good sleep quality. Moderate-to-vigorous physical activity time was increased in women with postgraduate education and was decreased in women with a longer work experience and with comorbidities. The total activity time increased with increasing age and good sleep quality, whereas it decreased with increasing body fat, presence of at least one comorbidity, secondary education, and divorce. Certain demographic, anthropometric, and sleep quality factors were associated with accelerometer-measured sitting and physical activity times among Emirati working women. Future longitudinal studies should consider these factors when investigating predictors of physical activity levels in this population.

Predictors of Physical Activity Levels in Ambulant/Semiambulant Children and Adolescents With Cerebral Palsy: A Clinical Cohort Study.

Children and adolescents with cerebral palsy (CP) show a reduced physical activity (PA) level compared with their typically developed peers. This study aimed to identify potential predictors of objectively evaluated habitual PA using data from a national clinical registry-the Cerebral Palsy Follow-Up Program(CPFP)-and proxy-reported questionnaires. Data from the CPFP database showed that female sex was associated with a lower PA level. Additional questionnaire data revealed age, popliteal angle limitation, Pediatric Outcomes Data Collection Instrument-Sports and Physical Functioning Scale score, screen time, Functional Mobility Scale score at 50m, and fatigue as predictors. The proposed models can be used for the prediction and early detection of the PA level and consequently for the potential improvement among ambulant/semiambulant individuals with CP. Further research should investigate the predictive impact of personal, social, and environmental factors on the PA level and the gap in PA levels between girls and boys.

The relationship between physical activity, structural deformity, and spinal mobility in adolescent idiopathic scoliosis patients.

Adolescent idiopathic scoliosis (AIS) patients experience structural spinal deformity, but the impact of AIS on physical activity is not widely studied. Reports of physical activity levels between children with AIS and their peers are mixed. This study sought to characterize the relationship between spinal deformity, spinal range of motion, and self-reported physical activity in AIS patients. Patients aged 11-21 completed self-reported measures of physical activity using the HSS Pedi-FABS and PROMIS Physical Activity questionnaires. Radiographic measures were obtained from standing biplanar radiographic imaging. Surface topographic (ST) imaging data was obtained using a whole-body ST scanning system. Hierarchical linear regression models analyzed the relationship between physical activity, ST, and radiographic deformity while controlling for age and BMI. 149 patients with AIS (mean age 14.5 ± 2.0years, mean Cobb angle 39.7° ± 18.9°) were included. In the hierarchical regression predicting physical activity from Cobb angle, no factors were significant predictors of physical activity. When predicting physical activity from ST ROM measurements, age and BMI served as covariates. No covariates or ST ROM measurements were significant predictors of physical activity levels for either activity measure. Physical activity levels of patients with AIS were not predicted by levels of radiographic deformity or surface topographic range of motion. Although patients may experience severe structural deformity and range of motion limitations, these factors do not appear to be associated with decreased physical activity level utilizing validated patient activity questionnaires. Level II.

Factors associated with meeting physical activity guidelines during the COVID-19 pandemic

IntroductionThe COVID-19 pandemic impacted individual physical activity levels. Less is known regarding how factors such as sociodemographic and built environment were associated with physical activity engagement during the pandemic. Understanding these factors is critical to informing future infectious disease mitigation policies that promote, rather than hinder physical activity. The purpose of this study was to assess predictors of physical activity levels during the beginning of the pandemic (April-June 2020), including Stay-at-Home length and orders, neighborhood safety, and sociodemographic characteristics.MethodsData included 517 participants who responded to an anonymous online survey. Physical activity was assessed with a modified Godin Leisure-time exercise questionnaire. We used logistic regression models to estimate unadjusted and adjusted odds ratios (aOR) and their 95% confidence intervals (CI) for the associations between independent variables (e.g., demographic variables, neighborhood safety, COVID Stay-at-Home order and length of time) and physical activity levels that did not meet (i.e., < 600 metabolic equivalents of task [MET]-minutes/week) or met guidelines (i.e., ≥ 600 MET-minutes/week). We used R-Studio open-source edition to clean and code data and SAS V9.4 for analyses. ResultsMost participants were 18–45 years old (58%), female (79%), Hispanic (58%), and college/post-graduates (76%). Most (70%) reported meeting physical activity guidelines. In multivariate-adjusted analyses stratified by income, in the highest income bracket (≥ $70,000) pet ownership was associated with higher odds of meeting physical activity guidelines (aOR = 2.37, 95% CI: 1.23, 4.55), but this association did not persist for other income groups. We also found lower  perceived neighborhood safety was associated with significantly lower odds of meeting physical activity guidelines (aOR = 0.15, 95% CI:0.04–0.61), but only among individuals in the lowest income bracket (< $40,000). Within this lowest income bracket, we also found that a lower level of education was associated with reduced odds of meeting physical activity guidelines.DiscussionWe found that perceived neighborhood safety, education and pet ownership were associated with meeting physical activity guidelines during the early months of the COVID-19 pandemic, but associations differed by income. These findings can inform targeted approaches to promoting physical activity during subsequent waves of COVID-19 or future pandemics.

Applying the behavior change wheel to identify pandemic-related attitudes and feelings about physical activity as predictors of physical activity level among university students in Indonesia during the COVID-19 pandemic

A recent systematic review found a significant drop in physical activity (PA) among university students during the coronavirus disease 2019 (COVID-19) pandemic. Identifying students’ attitudes and feelings about PA and coronavirus, which could facilitate or hinder PA, is essential to guide intervention planning. Therefore, this study aimed to examine attitudes and feelings about PA and coronavirus as predictors of PA levels. We conducted a cross-sectional study among undergraduate university students in Indonesia to collect their PA levels using the global PA questionnaire version 2 and their attitudes and feelings about PA in pandemic situations. A binomial logistic regression has been conducted to predict whether students will sufficiently engage in PA based on their attitudes and feelings related to PA, coronavirus, and demographic characteristics. Results from 588 undergraduate students (75% female) showed that students perceived the health benefits of PA, perceived feeling guilty about wanting to do PA during the pandemic, body mass index (BMI), and field of study were statistically significant predictors of PA levels. An increase of one unit of perceived health benefits of PA increases the odds of meeting the PA guidelines by 2.313 (95% confidence interval 1.708–3.132, p &amp;lt; 0.001). On the other hand, raising one point of feeling guilty about conducting PA was associated with 1.285 times lower odds (95% confidence interval 1.062–1.558, p = 0.01) of meeting the PA guidelines. Thus, intervention should increase students’ awareness of the physical health benefits of PA during the pandemic and reduce their feeling of guilty about conducting the PA.

Moderating Effect Of Gender-Based Differences On Physical Activity And Fatigue Among Recovered COVID-19 Patients

PURPOSE: Clinical data point toward gender-based differences in COVID-19 severity. However, there is insufficient research examining whether gender differences predict physical activity (PA) and fatigue severity in patients recovering from COVID-19. Therefore, this study aimed to characterize the PA and fatigue severity in a cohort of patients recovering from COVID-19 and measure the extent to which gender-based differences moderate the relationship of PA with fatigue. METHODS: A cross-sectional study was conducted. The sample comprised patients recovering from COVID-19 over at least 3 months. Recovered patients were stratified into two groups based on gender. The survey included items pertaining to sociodemographic, a fatigue severity scale (FSS) and a self-reported international PA questionnaire (IPAQ). Mann-Whitney U tests were conducted in analysis. To assess the moderating effect of gender in this research, a simple moderator regression analysis was done using the PROCESS macro, version 3.5.3. The data were analyzed using statistical software. RESULTS: Eighty-seven patients (44 women and 43 men) met the inclusion criteria. Compared with men, most women were more likely to report sedentary behavior (70%) and high fatigue severity (64%). A significantly higher number of women had a low PA score on the IPAQ compared with men (p = .002). Compared with men, there was a significant difference in the proportions of women who had greater fatigue (p = .001). The results of multiple linear regression analyses for the association between gender and total METs of PA and fatigue severity as dependent variables showed that the gender is considered a significant independent predictor of total PA and fatigue severity (R2 = .17, p = .003; R2 = .34, p = .002), respectively. Gender moderates the relationship between self-perceived fatigue and total PA (= .001, SE = .006, p = .03), which suggests that gender is a moderator of the effect of total PA on fatigue severity. CONCLUSION: the current study illustrated the incidence of lower levels of PA and a higher FSS result in women who had recovered from COVID-19. Considering the importance of increasing PA levels and decreasing fatigue levels, longitudinal studies to encourage PA engagement among female and to control fatigue are recommended.

POST-CONCUSSION DIZZINESS SEVERITY PREDICTS DAILY STEP COUNT DURING RECOVERY AMONG ADOLESCENT ATHLETES

Background:Physical activity after concussion is an important aspect of appropriate management and may help to improve recovery time. However, symptom burden or functional deficits may be self-limiting and reduce activity level in the first weeks following a concussion.Purpose/Hypothesis:To examine dizziness and postural stability as potential predictors of physical activity level after concussion. We hypothesized that increased dizziness severity and more postural instability would predict lower step count acutely post-concussion.Methods:We initially evaluated athletes ages 12-18 years within 14 days of concussion using questionnaires and clinical tests to assess overall symptom burden, dizziness, and postural stability. Athletes were provided with an activity monitor that tracked daily step count for the subsequent two weeks after their initial care visit. Our primary outcome variable was daily step count (mean steps/day) during this two-week period. Potential predictor variables included participant characteristics (sex, age, time since injury, and history of: concussion, musculoskeletal injury, migraine, ADD, anxiety, depression), Post-Concussion Symptom Inventory (PCSI) total symptom burden, specific PCSI ratings of dizziness and balance impairment, and postural stability assessments [single and dual-task tandem gait (TG) and modified balance error scoring system (mBESS)]. To examine clinical predictors of activity we calculated Pearson correlation coefficients between mean steps/day and each potential predictor, and then included significantly correlated variables in a multiple linear regression model.Results:Athletes who participated in the study (n=35, mean 15.2±1.7 years of age, 49% female, mean steps/day=9195±3779) were initially evaluated a mean of 7.3±3.0 days post-concussion. PCSI dizziness rating (Pearson R=-0.49, p=0.003; Figure 1) and sex (mean difference=2449 steps/day, p=0.05) were associated with daily step count upon univariable evaluation and included in the multiple linear regression model. No other participant characteristics, symptom ratings, or objective balance or postural stability measures were significantly associated with steps/day (Table 1). In the multivariable model, PCSI dizziness rating (β=-1035; 95% CI: -191, -1880; p=0.018), but not sex, predicted average steps/day in the two weeks after initial clinical care visits.Conclusion:Self-reported dizziness severity assessed within 14 days of concussion predicted daily step count in the subsequent two weeks, while other measures of overall symptom severity and postural stability did not. Given the importance of physical activity for concussion recovery, identifying individuals with acute post-concussion dizziness may facilitate timely treatment of dizziness, potentially reducing a barrier to physical activity to improve recovery trajectories.Figure 1.Scatterplot and line of best fit of the relationship between PCSI dizziness rating and average step count per day.Table 1.Symptom ratings, postural stability measures, and balance assessments and associations with average steps/day.

Personal, social, and environmental correlates of physical activity and sport participation in an adolescent Turkish population

BackgroundBenefits of physical activity has been shown for adolescents; however, there is a decline trend in number of adolescents meeting current WHO recommendations. This trend underlines the importance of identifying factors associated with adolescents’ physical activity level (PAL) with considerations of regional and cultural differences to plan and implement effective policies. Therefore, the aim of this study was to determine personal, ecological, and social factors associated with PAL and sport participation in Turkish adolescents aged 11–14 years. A cross-sectional study was conducted by including 996 adolescents aged between 11 and 14 years from 39 secondary schools in İstanbul, Turkey. Logistic regression analyses performed to identify the significant personal (age, gender, sleep time, screen time, BMIz score, having siblings), ecological (presence of playground, type of school transportation), and social (family income, engaging a physical activity with family, and preferred activity at school breaks) predictors of PAL and sport participation.ResultsAdolescents who were active during break time at school (p < 0.001), engaging a physical activity with family (p < 0.001), and did not have a sibling (p = 0.029) were more likely to be physically active. Adolescents behaved active during break time at school (p < 0.001), had a playground at home (p < 0.001), spending time with family for physical activity (p < 0.001), and did not have a sibling (p = 0.021) were more likely to participate in a sport activity.ConclusionsPredictors of PAL in this study indicates the need to promote active break time in school, increased physical activity time with family, and to design environmental policies to increase number of playgrounds.

Differences in self-control, self-efficacy and depressive symptoms between active and inactive middle-aged and older adults after 1 year of COVID restrictions

Objectives The psychological impact of the prolonged lockdown measures in the UK as a response to the COVID-19 pandemic is unclear. Our aim was to determine if there are significant differences in self-control, self-efficacy, depressive symptoms and leisure motivation between UK older adults with differing levels of physical activity, and which of these variables can be used to predict activity level after 1 year of lockdown restrictions, Methods 521 adults aged 50–92 years completed an online survey consisting of several validated measures relating to physical activity, self-control, self-efficacy, depressive symptoms, and leisure motivation. Participant’s responses were grouped into active (≥150minutes activity per week) and inactive (<150minutes activity per week). Data was analysed using ANOVA, Pearson’s Correlation and Multiple Regression (forward stepwise). Results We found significant differences in self-efficacy, self-control, and depressive symptoms between physically active vs inactive subjects. High levels of self-control and self-efficacy were associated with higher levels of activity and fewer depressive symptoms. Self-control, amotivation, depressive symptoms and self-efficacy were predictors of physical activity level. Conclusion Psychological variables including self-control, self-efficacy, depressive symptoms and amotivation can be used to predict physical activity levels in UK middle-aged and older adults following 1 year of Covid restrictions.

Physical activity level is associated with gait performance and five times sit-to-stand in Parkinson's disease individuals.

Physical activity (PA) level is decreased in individuals with Parkinson´s disease (PD). To increase the PA level improves both motor and non-motor symptoms of this population. It is known that gait performance and five times sit-to-stand (FTSTS) are associated with PA level; therefore, it is of great relevance for rehabilitation purposes to understand whether these variables may predict PA level of individuals with PD. To investigate whether gait performance and FTSTS are predictors of PA level. Cross-sectional study with individuals with idiopathic PD modified Hoehn and Yahr staging scale between 1.0 and 3.0. The gait performance was measured by Functional Gait Assessment (FGA) and PA level was measured by an accelerometer for one week, during day and night through their time spend in locomotion (locomotion time-LT). Multiple linear regression was conducted with gait performance and FTSTS as independent variables and PA level (LT) as dependent variable. Twenty-two participants were included, mean age 64.82 (8.39) and the mean storage of accelerometer time was 9.866min (0.33). Both gait performance and FTSTS have moderate significant correlation with PA level (r =  - 0.538 p < 0.01 and r = 0.625 p < 0.001, respectively). The linear regression model with FGA and FTSTS was significant (p < 0.05) and predicted 41% of LT. Gait performance and FTSTS have important interaction with PA level measured by LT in individuals with PD, and it provides insights on the importance of these variables in predicting the PA level of its population.

Predictors of Physical Activity Levels in University Physical Education Implementing Sport Education.

By adopting Sport Education into the university context, this study examined how lesson content and teacher interaction contribute to university students' physical activity levels during physical education lessons. Following a continuing professional development workshop, a 10-week Sport Education season was designed collaboratively and implemented at a university, taking into account the university's facilities. This study used the momentary time sampling tool, System for Observing Fitness Instruction Time, in which eight teachers and 202 students (72% male) were videotaped in 156 lessons. The data on physical activity levels, lesson content, and teacher behavior were collected and analyzed. The student-participants engaged in an average of 38.77 (±18.78) moderate-to-vigorous physical activity (MVPA) minutes which did not meet the recommendation of 50% lesson time. Findings of hierarchical linear regression indicated that knowledge (β = 0.29) and general content (β = 0.29) contributed to the sitting physical activity while skill practices (β = 0.25) and gameplay (β = 0.38) predicted the MVPA. Practical implications of utilizing the features of Sport Education in boosting the intensity of activities are discussed, especially team affiliation, formal competition, and record keeping. Further investigations are proposed on the interaction of gameplay content and teacher behavior with larger sample size.

Development and Validation of a Perceived Barriers to Physical Activity Scale for Low-Income Adolescents.

Low-income adolescents' physical activity (PA) levels fall below current recommendations. Perceived barriers to physical activity (PBPA) are likely significant predictors of PA levels; however, valid and reliable measures to assess PA barriers are lacking. This manuscript describes the development of the PBPA Survey for Low-Income Adolescents. A mixed-method approach was used. Items identified from the literature and revised for clarity and appropriateness (postcognitive interviews) were assessed for test-retest reliability with 74 adolescents using intraclass correlation coefficient. Items demonstrating low intraclass correlation coefficients or floor effects were removed. Both exploratory factor analysis and confirmatory factor analysis analyses (n = 1914 low-income teens) were used to finalize the scale; internal consistency was assessed by Cronbach's alpha. Concurrent validity was established by correlating the PBPA with the PA questionnaire for adolescents using a Spearman correlation. The exploratory factor analysis yielded a 38-item, 7-factor solution, which was cross-validated by confirmatory factor analysis (comparative-fit index, nonnormed fit index = .90). The scale's Cronbach's alpha was .94, with subscales ranging from .70 to .88. The PBPA Survey for Low-Income Adolescents' concurrent validity was supported by a negative PA questionnaire for adolescents' correlation values. The PBPA Survey for Low-Income Adolescents can be used to better understand the relationship between PBPA among low-income teens. Further research is warranted to validate the scale with other adolescent subgroups.

Parental and Familial Factors Influencing Physical Activity Levels in Early Adolescence: A Prospective Study.

Parental/familial factors are important determinants of the physical activity level (PAL) in children and adolescents, but studies rarely prospectively evaluate their relationships. This study aimed to evaluate the changes in physical activity levels among adolescents from Bosnia and Herzegovina over a two-year period and to determine parental/familial predictors of PAL in early adolescence. A total of 651 participants (50.3% females) were tested at baseline (beginning of high school education; 14 years old on average) and at follow-up (approximately 20 months later). The predictors included sociodemographic characteristics (age, gender) and parental/familial factors (socioeconomic status of the family, maternal and paternal education, conflict with parents, parental absence from home, parental questioning, and parental monitoring). Physical activity levels were evidenced by the Physical Activity Questionnaire for Adolescents (PAQ-A; criterion). Boys were more active than girls, both at baseline (t-test = 3.09, p < 0.001) and at follow-up (t-test = 3.4, p < 0.001). Physical activity level decreased over the observed two-year period (t-test = 16.89, p < 0.001), especially in boys, which is probably a consequence of drop-out from the sport in this period. Logistic regression evidenced parental education as a positive predictor of physical activity level at baseline (OR [95% CI]; 1.38 [1.15–170], 1.35 [1.10–1.65]), and at follow-up (1.35 [1.11–1.69], 1.29 [1.09–1.59], for maternal and paternal education, respectively). Parents with a higher level of education are probably more informed about the importance of physical activity on health status, and thus transfer this information to their children as well. The age from 14 to 16 years is likely a critical period for maintaining physical activity levels in boys, while further studies of a younger age are necessary to evaluate the dynamics of changes in physical activity levels for girls. For maintaining physical activity levels in adolescence, special attention should be paid to children whose parents are less educated, and to inform them of the benefits of an appropriate physical activity level and its necessity for maintaining proper health and growth.

Association between Physical Literacy and Physical Activity: A Multilevel Analysis Study among Chinese Undergraduates.

Aim: To examine the association between the perceived physical literacy (PL) and physical activity (PA) levels among Chinese undergraduates. Methods: Simplified Chinese version of the Perceived Physical Literacy Instrument and the International Physical Activity Questionnaire were used to measure 536 students’ perceived PL and PA levels. Pearson’s product-moment correlation and multiple linear regression were then used to examine the relationship between the perceived PL and PA levels. Additionally, standard regression analysis was conducted to test for the effects at different demographics. Results: The correlation between perceived PL and PA level was low but significant (r = 0.350, p < 0.01). The multiple linear regression equation was significant (F = 25.228, p < 0.01, ΔR2 = 0.120). Metabolic equivalent values were used to predict PA levels of participants, which were −3818.582 + 272.535 (motivation) + 249.848 (confidence and physical competence) + 149.899 (interaction with the environment). The association of factors such as socio-economic status (SES) (p = 0.092) and grade point average (GPA) (r = 0.119, p = 0.022) were examined using Pearson’s product-moment correlation. Gender (p < 0.01) and body mass index (BMI) (p < 0.01) were also explored for their differences. Conclusions: Perceived PL and PA levels were significantly related. The association between PL and GPA was identical. GPA and BMI showed significant difference between each group. The study offers a path to explore the concept of PL and how it can affect the PA of Chinese undergraduates. Furthermore, on the basis of this study, more research could develop practical interventions for Chinese undergraduates to enhance their PL and engagement in a lifetime of PA.

Predictors of physical activity levels in individuals with Parkinson's disease: a cross-sectional study.

To investigate whether modifiable predictors (depressive symptoms, impairment in behavior and mood, balance impairments, and knee extensor muscle strength) are determinants of the physical activity level in Parkinson's disease. A cross-sectional study with individuals diagnosed with idiopathic Parkinson's disease. Regression analysis of the data was used to investigate whether depressive symptoms, impairments in behavior and mood, balance impairments, or dominant knee extensor muscle strength are predictors of physical activity levels in Parkinson's disease. A total of 50 individuals with mild to moderate Parkinson's disease participated in this study, with a mean age of 67 ± 8 years and 68% male. Balance impairments explained 29% of the variation in the physical activity levels. The explained variance increased to 34% when depressive symptoms were included in the model. Among the predictor variables investigated in our study, only balance impairments and depressive symptoms explained the variance in physical activity levels in individuals with Parkinson's disease.

Predictors Of Physical Activity Level Among Brazilian Military Law Enforcement Personnel

Predictors Of Physical Activity Level Among Brazilian Military Law Enforcement Personnel

The Relationship Of Physical Activity And Motor Ability Development In Children Aged 7-8 Years

Two thirds of children does not meet physical activity (PA) guidelines in China. The fundamental movement skills (FMS) level is a good predictor of physical activity levels and weight status in children. Also, early motor skill has long-term effect on individual’s PA level. So, understanding the relationship of FMS and PA is important for physical activity intervention planning. PURPOSE:To analyze the relationship of daily physical activity participation and the motor ability of children aged 7-8 years. METHODS: The Movement Assessment Battery for Children-2 (M-ABC-2) and the Test of Gross Motor Development - 2nd edition (TGMD-2) were used to test the motor ability of 91 children aged 7-8 years. The ActiGraph GT3X+ accelerometer was used to measure the physical activity participation for 7 consecutive days. RESULTS: The total time of boys spent in moderate physical activity (MPA) and moderate-to-vigorous physical activity (MVPA) was 21.4±7.5min and 27.3±11.2min, respectively, which was higher than those of girls (17.5±7.4min and 22.2±9.7min, P<0.05). The score of object control subscale in boys was 6.73±2.49, which is better than that of girls (5.71 ± 2.14, P <0.05); children's fine motor skill and locomotor skill were positively correlated with VPA, MPA and MVPA (r = 0.2 ~ 0.3). CONCLUSION: In this study, children spent less time in MVPA, especially in girls. The development of object control ability in boys is better than that of girls; there is a positive correlation between children's fine motor skills and physical activity. Therefore, children need to learn and practice FMS for participation and maintenance of PA. FMS should be tested in primary schools, so weaknesses could be identified in children and improved via proper intervention. Supported by The National Social Science Fund of China(Key Project of National Education Science, ALA190015)

Özel Eğitim İhtiyacı Olan Türk Bireylerin Fiziksel Aktivite Düzeyleri ve Bunun Yordayıcıları

Objective: It is known that physical activity levels of disabled individuals are lower than those of healthy individuals, both among adolescence and adulthood. This study aims to compare the physical activity levels of individuals with disabilities from various diagnosis groups and try to define the predictors of physical activity levels of individuals with disabilities. Material and Methods: A total of 275 participants (103 women and 172 men) with either one of the following disabilities (or their representatives) filled in the International Physical Activity Questionnaire-Short Form and a Participant Information Form: intellectual disabilities, hearing impairment, language- speech disorders, specific developmental disorder and pervasive developmental disorder. Results: Fifteen per cent of the participants were highly active (n=42), 20% were moderately active (n=54) and 65% were low level active (n=179). Total physical activity, high-intensity physical activity, walking amounts and daily average sitting time of the participants differed significantly between the diagnostic groups. (p<0.001, p=0.037, p=0.002 and p=0.001, respectively). People with hearing impairment were the most active and people with severe intellectual disability were the least active. Sex, diagnosis and the father's having postgraduate training were significant predictors of physical activity levels. Conclusion: Majority of the individuals with disabilities do not meet the minimum physical activity recommendations. Physical activity levels differ among various diagnoses groups and people with severe intellectual disability require the most attention.

Can Fear of Movement, Depression and Functional Performance be a Predictor of Physical Activity Level in Patients With Knee Osteoarthritis?

This study aims to explore whether fear of movement, depression and functional performance are predictors of physical activity levels in patients with knee osteoarthritis (OA). A total of 200 patients (80 males, 120 females; mean age 53.23±5.99 years; range, 40 to 65 years) with knee OA participated in this cross-sectional, correlational-design study. Oxford Knee Score (OKS) was used to evaluate physical function and pain through patient perspective. Six-Minute Walk Test (6-MWT) was used to evaluate functional performance. International Physical Activity Questionnaire-Short Form (IPAQ-SF) was used to assess subjective physical activity level. A 17-item of the self-reported Tampa Scale for Kinesiophobia (TSK) questionnaire was used to determine the fear of movement level. Beck Depression Inventory (BDI) was used as a self-reported measure for depression level. Spearman correlation analysis and the linear regression model with R-square (R2) were used to correlate and explain the total variance. International Physical Activity Questionnaire-Short Form was significantly correlated to OKS (r=-0.550), 6-MWT (r=-0.561), TSK (r=-0.693) and BDI (r=-0.429) in patients with OA (p<0.001). Linear regression analysis revealed that OKS, 6-MWT test, TSK and BDI were independently associated with IPAQ-SF in predicting physical activity level in patients with knee OA (p≤0.001; R2=0.621). This study increases the understanding of the predictors of physical activity level related to fear of movement, depression and functional performance in patients with knee OA. Improving physical activity levels in OA population is necessary to implement early treatment strategies before the disease progresses and more costly solutions are needed.

Predicting physical activity levels in individuals with schizophrenia through integrated global positioning system and accelerometer data

Research has documented that individuals with schizophrenia spend a significant amount of time in sedentary activity and often do not meet physical activity (PA) guidelines (Stubbs et al., 2016). Environmental factors have long been studied as facilitators or barriers to PA. Among individuals with schizophrenia, environmental factors are known to predict walking and moderate to vigorous PA (Vancampfort et al., 2013). Additionally, environmental characteristics explain 16.8% of sitting time of individuals with schizophrenia (Vancampfort et al., 2014), with factors such as neighborhood infrastructure (e.g., sidewalks or parks) or access to fitness equipment in the home reducing time spent in sedentary behavior. Consistent with Barker’s Behavior Settings Theory (Schoggen, 1989) this study is predicated on the expectation that certain locations are associated with behaviors that involve more or less PA. Thus, there is a need to study current PA levels associated with certain locations in the community, which could lead to development of ecological interventions that are personalized to a person’s time and location preference to maximize PA performance. To address this need, we propose a new methodology called Personalized PA level estimation for specific Locations over time (PerPAL) to better predict PA levels by location. The development of the personalized models involves identifying recurring locations (Townley et al., 2018) for an individual and using their baseline PA data, location, and time-window to predict future PA levels for specific locations (Brusilovskiy et al., 2016) and time-windows.