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The physical sacrifice of thinking: Investigating the relationship between thinking and physical activity in everyday life


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Physical activity level is an important contributor to overall human health and obesity. Research has shown that humans possess a number of traits that influence their physical activity level including social cognition. We examined whether the trait of "need for cognition" was associated with daily physical activity levels. We recruited individuals who were high or low in need for cognition and measured their physical activity level in 30-second epochs over a 1-week period. The overall findings showed that low-need-for-cognition individuals were more physically active, but this difference was most pronounced during the 5-day work week and lessened during the weekend. © The Author(s) 2015.
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DOI: 10.1177/1359105314565827
It has been clear for some time that physical
activity level is an important contributor to human
health (e.g. Pate et al., 1995) and is especially
influential in overall quality of life (Bize et al.,
2007). The importance of physical activity has
recently garnered a great deal of attention because
of the pandemic rise in obesity (Wang et al.,
2011) and negative health effects (Kohl et al.,
2012) associated with low activity levels. Perhaps
more striking is that many people believe they
can overcome their lack of physical activity by
taking a quick run through the gym. While this is
likely helpful, its effects on overall human health
are minimal compared to the impact of a person’s
overall daily activity level (Levine et al., 1999).
Maintaining a proper balance of physical activity
to promote good health and quality of life is a
centerpiece of the American College of Sports
Medicine (ACSM) and has been shown to sup-
port mental well-being (Fox, 1999) and good
mental health (Paluska and Schwenk, 2000).
Aside from physical activity, another domain in
which people vary is how much they like to think,
and one of the most widely used measures of dif-
ferences in thinking propensity is “need for cog-
nition” (NFC). NFC is defined as a tendency to
engage in and enjoy effortful cognitive endeavors
(Cacioppo and Petty, 1982). NFC is an individual
The physical sacrifice of thinking:
Investigating the relationship
between thinking and physical
activity in everyday life
Todd McElroy1, David L Dickinson2, Nathan
Stroh2 and Christopher A Dickinson2
Physical activity level is an important contributor to overall human health and obesity. Research has shown
that humans possess a number of traits that influence their physical activity level including social cognition.
We examined whether the trait of “need for cognition” was associated with daily physical activity levels.
We recruited individuals who were high or low in need for cognition and measured their physical activity
level in 30-second epochs over a 1-week period. The overall findings showed that low-need-for-cognition
individuals were more physically active, but this difference was most pronounced during the 5-day work
week and lessened during the weekend.
cognition, decision, obesity, physical activity, risk
1Florida Gulf Coast University, USA
2Appalachian State University, USA
Corresponding author:
Todd McElroy, Department of Psychology, Florida Gulf
Coast University, 10501 FGCU Blvd, South Fort Myers,
FL 33965, USA.
565827HPQ0010.1177/1359105314565827Journal of Health PsychologyMcElroy et al.
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2 Journal of Health Psychology
difference measure of thinking that allows
researchers to study thinking without placing
demands on cognitive resources. Furthermore,
NFC is driven by intrinsic motivation and is rela-
tively stable across a person’s lifetime (Cacioppo
et al., 1996). Researchers have used this measure
for over 30 years to examine the relationship
between enjoyment of effortful cognitive endeav-
ors and other variables related to cognition
(Cacioppo et al., 1996).
For example, research has shown that indi-
viduals high in NFC appear to perform better on
memory tasks (Boehm, 1994; Cacioppo et al.,
1983), are generally more positive toward cog-
nitively difficult tasks (Cacioppo et al., 1996),
spend more effort when making decisions
(Verplanken et al., 1992) and can make better
ones (Levin et al., 2000). Low-NFC individuals
have been shown to rely more on peripheral
information (Cacioppo and Petty, 1982) and
contextual cues such as attractiveness or a per-
son’s mood (Cacioppo et al., 1996) when think-
ing and forming attitudes.
Overall, these types of studies depict a psy-
chometric tool that reveals an important force
behind human cognition and its effects on eve-
ryday life. In the current investigation, we
explore how NFC may be associated with daily
physical activity levels. Although previous
research has not specifically examined such a
connection, related research suggests that it
may exist.
Cognition and physical activity
The relationship between cognition and physi-
cal activity is important for health concerns, but
it also speaks to a more fundamental question of
how cognition interacts with the physical body
across the human lifespan. Research looking at
children and adolescents has shown many cog-
nitive variables that are related to physical
activity, including preferences, intentions
(Sallis et al., 2000), and self-efficacy (Strauss
et al., 2001). There is also evidence that neuro-
anatomical and neurochemical differences are
linked to more pervasive behavioral disorders
such as attention deficit hyperactivity disorder
(ADHD) (Swanson et al., 1998) and anxiety
(Fride and Weinstock, 1988). Similarly, research
looking at older adults has also consistently
shown a relationship between physical activity
and cognitive decline (Laurin et al., 2001;
Weuve et al., 2004). Thus, the relationship
between cognition and physical activity is an
important question for the human experience,
and the interaction likely extends across the
lifespan (e.g. Heyn et al., 2004; Kramer and
Erickson, 2007).
Research has also revealed a number of indi-
vidual difference variables that appear to be
associated with physical activity levels. For
example, intention to perform a physical activ-
ity (e.g. Petty et al., 2013) is associated with
physical behavior. Individual difference varia-
bles such as approach/avoidance motivation
(Hevey and Dolan, 2014), “Health Types”
(McGinty et al., 2012), sensation seeking in
adolescents (Sallis et al., 2000) and some com-
ponents of the Big Five personality traits
(Rhodes and Smith, 2006) influence the likeli-
hood of a person performing certain types of
physical activities. Second, there is strong evi-
dence that cognition is related to physical activ-
ity in daily life. This idea is highlighted in a
large-scale study by Godin et al., (2010). In this
study, Godin et al. tested the effects of several
variables on physical activity. These variables
were grouped by either social structure, which
represents a person’s hierarchical status, or
social cognition, which involves the processing
of social information. The findings revealed
that social structure had only a small effect on
physical activity, whereas social cognition was
determined to be the key factor in predicting
physical activity level.
Thus, existing research supports the view
that cognition and physical activity level are
associated, yet an important question is whether
individual preference toward cognitive endeav-
ors is associated with more or less physical
activity. While research has not directly exam-
ined this question, our search identified studies
that provide differing clues for how this rela-
tionship may unfold, and they provide a basis
for our investigation.
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McElroy et al. 3
First, it is possible that high- and low-NFC
individuals may be engaging in different strate-
gies that ultimately affect their physical behavior.
Specifically, it could be that an associative–
dissociative attentional strategy (Masters and
Ogles, 1998) dichotomy may be at play such that
low-NFC individuals engaged in more physical
activity because they are better able to dissociate
themselves from cues related to physical exertion
(e.g. Stanley et al., 2007). In other words, this dis-
sociation would make physical activity seem
easier to these individuals. Some support for this
can be found in a study by Watt and Blanchard
(1994). In this study, low-NFC individuals dem-
onstrated a greater propensity toward boredom
and more strongly experienced its associated
negative effect. High-NFC individuals appear to
avoid this because of their ability to provide their
own mental stimulation. Thus, high-NFC indi-
viduals seem more content to “entertain them-
selves” mentally, whereas low-NFC individuals
quickly experience boredom and experience it
more negatively.
In another study that involved a limited
behavioral task, participants were charged with
observing directionality of dots on a computer
monitor. The findings showed that low-NFC
individuals performed better individually than
collectively, and they tended to outperform
high-NFC persons during individual perfor-
mance (Smith et al., 2001). This suggests that
low-NFC individuals may “loaf” more in groups
but may be more active at the individual level.
While these studies seem to suggest that low
NFC will be associated with more physical
activity, another set of findings seems to sug-
gest an opposite relationship. For example, a
study by Hess et al. (2011) looked at longitudi-
nal effects of cognitive motivation across a
wide age range. They combined Personal Need
for Structure (PNS) with NFC scores to create a
composite measure of cognitive motivation.
Their results showed that this cognitive motiva-
tion measure was positively associated with
social activities and interactions. Thus, this
study would seem to suggest that high-NFC
individuals may be more physically active in
their daily lives. This finding is consistent with
research showing that high-NFC individuals
have a stronger tendency to seek out informa-
tion (Verplanken et al., 1992), and they appear
more motivated (Cacioppo et al., 1983).
Summary and predictions
Our review of the literature reveals good evi-
dence that individual differences as well as cog-
nition appear to be associated with physical
activity. However, the direction of this relation-
ship is not clear. One set of findings seems to
suggest a tradeoff of sorts between cognitive and
physical activity. Because high-NFC individuals
are more content and eager to be involved in cog-
nitive activities, the natural outcome is that they
may be less physically active. On the other hand,
another set of findings seems to suggest that high
NFC may reflect an overall increase in motiva-
tion level that could lead to greater exploration of
the environment and social activities. Thus,
because our assessment of findings in the litera-
ture appears to present a contradictory picture,
we designed the current investigation as a way to
test this relationship and determine whether a
person’s level of cognitive activity is associated
with more or less physical activity.
Participants and design
The participants in this study were 30 high- and
30 low-NFC individuals; 45 of the participants
were female.1 The conditions were roughly equal
in regard to gender; 20 females were in the high-
NFC condition and 25 in the low-NFC condition.
All participants were undergraduate students at
Appalachian State University. The experiment
utilized a one-way factorial design. The inde-
pendent variable in this study was NFC level
(high or low), and the dependent variable was the
participant’s activity levels across 1 week.
The primary screening procedure was conducted
through an online survey using the SONA
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4 Journal of Health Psychology
software system. This selection method was
necessary for several reasons: the relative scar-
city of low-NFC individuals in our sample pop-
ulation, the week-long sampling period, and the
monetary expense associated with compensat-
ing each participant. In this initial session, par-
ticipants were informed about the nature of the
study, including the potential for participation in
the second stage. They were then asked to com-
plete the NFC scale (Cacioppo et al., 1984).
After completing the NFC scale, participants
were awarded credit for their participation in
this initial screening stage.
Next, we established criteria for discerning
individuals who were high or low in NFC.
Relying on our initial NFC screening as a sample
population, we used the upper and lower 10 per-
cent of our distribution as the criteria for deter-
mining our maximum and minimum scores for
categorizing high and low NFC. Participants who
were eligible to take part in the study were con-
tacted via recruitment email; those who responded
affirmatively were scheduled for an initial lab
meeting. As a result of this recruitment classifica-
tion method, high-NFC participants had NFC
scores in the range of (4–62), whereas the range
for low-NFC participants was (−11 to −39).
The observation weeks were arranged ahead
of time so that they occurred during the semester
and did not include holidays. Participants were
contacted via email to set up the initial lab meet-
ing. Prior to the initial lab meeting, actigraphy
devices (described below) were configured and
assigned to each participant. During the initial
lab meeting, participants were informed about
the study and how to wear the device. Participants
were instructed to carry out their typical daily
routines. They were then assigned a follow-up
lab meeting time. The follow-up lab meeting
took place approximately 1 week later; schedul-
ing was based on participants’ availability. We
chose a 1-week observational period because
prior research has shown this to be the desirable
time period for assessing variability in activity
patterns (Matthews et al., 2002).
In the final lab meeting, participants returned
their actigraphy devices, and they were compen-
sated US$10.00 each for participation and return
of the device. They were given an overview of
the nature of the study and also offered an output
of their daily activity level data, which we prom-
ised to send them after the study concluded, and
the data were scored. At the end of the final lab
meeting, participants were asked several sets of
questions unrelated to this study. Data from the
actigraphy devices were downloaded using the
manufacturer’s software. Time periods when the
device was removed, which were rare, were
cleared from the dataset to avoid miscounting
them as periods of zero activity. Sleep episodes
were also removed from the data. The 1-week
period of measurement yielded ~20,000 activity
measurements per participant.
To assess participants’ level of NFC, we used
the NFC scale (Cacioppo et al., 1984). This
scale consists of 18 items; half have positive
orientations and half contain negative orienta-
tions. Participants indicated how much they
agreed or disagreed with each item on a 9-point
scale ranging from very strong disagreement
(−4) to very strong agreement (+4). Total scores
on this scale range from 72 to −72.
To measure participants’ activity levels, we
used an actigraphy device. The device is an
accelerometer worn on the non-dominant wrist
as a common means for measuring gross motor
activity (Ancoli-Israel et al., 2003). This device
resembles a common wrist watch and can be
conveniently worn by participants. Measurement
is made by internal accelerometers with sensi-
tivity of .05 g-force. This sensitivity generates
“activity counts” of varying strength and fre-
quency during each time epoch used for data
collection. We set the data sampling for the
device to occur at epoch lengths of 30 seconds.
The device is impact resistant, waterproof to
1-m depth for 30 minutes, and can be worn
24 hours a day with few exceptions.
After completion of the study, daily activity
counts were obtained by averaging the 30-second
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McElroy et al. 5
epoch readings across all waking hours for each
individual participant. There was a malfunction
with the actigraphy for 1 day of a low-NFC par-
ticipant’s data, and so that day was not obtainable
and excluded from the analysis. With this excep-
tion, the daily activity counts for each participant
were combined within each of the 7 days; subse-
quent analyses relied on the entire daily activity
counts within each individual day.
Because the one-way analysis of variance
(ANOVA) F-test and t-test produce statistically
identical outcomes, we relied on the ANOVA
because the analysis yields more variance infor-
mation. First, to test whether a person’s level of
NFC was associated with his or her physical
activity levels, we performed an ANOVA with
NFC level as our independent variable and over-
all daily activity level as our dependent variable.
The results from this analysis revealed that think-
ing does seem to be associated with less physical
activity. As shown in Figure 1, the difference
between high- and low-NFC individuals in over-
all weekly physical activity level was highly sig-
nificant (F(1, 58) = 7.4, p < .009, η2 = .113) such
that high-NFC individuals were far less active
overall than low-NFC participants.
Prior research directed toward measuring
daily differences in physical activity levels has
shown that weekday activity levels (Monday–
Friday) differ substantially from weekend lev-
els (Matthews et al., 2002). To test whether this
weekend effect might be present in this study,
we first performed an analysis of the weekday
activity levels comparing high- and low-NFC
individuals for Monday–Friday activity levels
(see Figure 1), and, as suspected, they differed
greatly across the 5-day typical work week
(F(1, 58) = 9.94, p < .003, η2 = .146). Next, we
tested whether this effect remained for the
weekend days. Collapsing across the weekend
days, we see that activity levels for high- and
low-NFC individuals did not differ significantly
(F(1, 58) = 2.53, p < .117, η2 = .042) on the
weekend. The results revealed that this lack of a
statistical difference in activity levels is true for
Saturday data (F(1, 58) = 2.4, p < .127, η2 = .04)
and even more so for Sunday data (F(1,58) = .21,
p > .65, η2 = .004).2
Figure 1. Average daily physical activity level for high-NFC individuals and low-NFC individuals as
measured in 30-second epochs and based on .05 g-force sensitivity. These data include the average daily
physical activity level for each group across the 1-week period. Error bars indicate the standard error of
the mean.
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6 Journal of Health Psychology
In this study, we tested whether people who pre-
fer to think more will be less physically active
in their daily lives than people who do not pre-
fer to think. Our findings build upon prior
research (e.g. Godin et al., 2010) and provide
support for our hypothesis by revealing robust
physical activity level differences during the
5-day work week and attenuated differences
over the weekend. Furthermore, it is important
to note that these differences were found using
a robust measure of physical activity over a
1-week period. This type of objective measure
has been called for to help validate other types
of self-report measures (see Godin et al., 2010).
However, the sampling method used in our
study created potential limitations that should
be noted.
First, it is important to note that part of the
“weekend effect” in our study may be due to
our sample population, which consisted of col-
lege students. Although college students are a
standard participant pool in the vast majority of
experimental psychology studies, their behav-
ior and habits may be more indicative of young
adult behavior than adult behavior in general. It
is reasonable to assume that this “weekend
effect” may change as people progress through
different life stages, which is a question that
future researchers may want to consider. A sim-
ilar limitation with our methodology was that
the participants were all involved in course-
work, a time in their lives that should revolve
around cognitively focused events. While this
was true for both high- and low-NFC partici-
pants, it may limit the external validity of this
study to cognitively oriented life situations. In
conclusion, it seems noteworthy to point out
that if this association between physical activ-
ity and cognition leads to health issues such as
obesity, it may be prudent for more thoughtful
individuals to consider lifestyle changes as
countermeasures to the negative health out-
comes associated with their lower activity lev-
els. For example, research has shown that
simply being active in mundane behaviors such
as moving about, fidgeting, or even walking to
the bathroom increases non-exercise activity
thermogenesis (NEAT). These types of activi-
ties have been shown to expend excess energy
the body has taken in, which will help avoid fat
storage and promote leanness (Levine et al.,
1999). An example of a more dramatic counter-
measure would be to replace one’s workstation
with a walking treadmill desk. These have been
shown to increase energy expenditure of
100 kcal/hour in the neighborhood, which can
result in substantial benefits (Levine and
Miller, 2007). Ultimately, an important factor
that may help more thoughtful individuals
combat their lower average activity levels is
awareness. Awareness of their tendency to be
less active, coupled with an awareness of the
cost associated with inactivity, more thoughtful
individuals may then choose to become more
active throughout the day.
Special thanks to Sarah Pollard for her devoted assis-
tance with the early data gathering in the project. The
data set of daily averages as well as the entire set of
daily activity measurements is available from the
first author.
Partial support for this research was provided by the
National Science Foundation (NSF Grant number:
1229067) and the Division of Research and
Sponsored Programs, Appalachian State University.
Some subject payments were funded by a grant from
the Office of Student Research, Appalachian State
1. The study was approved by the University’s
Institutional Review Board (IRB No. 11-0067),
which is governed by the Office of Research
Protections. Written consent was obtained from
all participants.
2. We performed an additional analysis by collaps-
ing weekdays and weekends into two separate
variables. We then performed a repeated meas-
ures analysis with these two new variables as a
within factor and NFC level as a between factor.
This approach to treat our data as a mixed design
yielded a marginally significant main effect for
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McElroy et al. 7
NFC; F(1, 58) = 3.59, p < .07, a non-significant
main effect for the weekday/weekend variable;
F < 1 and a non-significant interaction F < 1.
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... Energy is a scarce resource, wasting appears irrational and counterproductive, thus laziness can be a rational strategy for survival. Some authors even presume that a trade-off between physical and intellectual activity might lead to physical or intellectual lazinessa higher need for cognition can correlate with physical inactivity and vice versa (McElroy et al. 2016). In the rest of my paper, I consider laziness vice as recognized in the writings of early modern philosophers. ...
... However, they were less likely to try new foods due to lower materialism scores (Tuncdogan & Ar, 2018) and no association was found to red meat consumption (Vainio, 2019). Even though NFC was not associated with the motivation to use a fitness tracker (Attig et al., 2019) and H-NFC individuals were less active during the week, they were equally active on the weekend (McElroy et al., 2016) or even more active than L-NFC individuals (Yazdani & Siedlecki, 2021). NFC in general was associated with higher intentions to use sun protection (Occa et al., 2020) but with lower skin appearance concern in sunbathing students (McMath & Prentice-Dunn, 2005). ...
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Need for Cognition (NFC) describes one’s inclination towards and enjoyment of effortful cognitive activities and has been associated with favourable academic outcomes. Yet, recent evidence also points to beneficial outcomes regarding well-being. This review gives an overview of the literature on the role of NFC in well-being in healthy adults by combining random-effects meta-analyses and a qualitative integration of evidence. Studies investigating NFC and facets of well-being were acquired via database searches and a call for unpublished results. Higher NFC was found to be associated with lower neuroticism, anxiety, negative affect, burnout, public self-consciousness, and depression and with higher positive affect, private self-consciousness, and satisfaction (|𝜌| ~ .20 with 95% confidence intervals excluding zero for all examined outcomes). While tests for publication and selection bias in the meta-analyses were negative, heterogeneity was often observed. NFC was further associated with aspects of a more stable identity and higher social confidence, while associations with addictive behaviours and physical health were inconsistent. One mechanism driving these patterns seems to be a higher perceived control in individuals with higher NFC that increases active coping, but also reduces the effectiveness of health interventions by fostering a sense of overconfidence in own resources. Thus, this review provides a leverage point for future research on NFC and well-being to improve prevention and intervention.
... Posteriormente, Cacioppo & Petty (1982) conceptualizan las necesidades cognitivas (NC) como la tendencia de buscar, participar y disfrutar de las actividades cognitivas, con aprecio por la evaluación de las ideas y resolución problemas, todas actividades guiadas por el disfrute del esfuerzo cognitivo, siendo esto una medida estable a lo largo de la vida. La relación entre NC y ejercicio físico ha sido estudiada, ya que se especulaba sobre la relación entre esfuerzo cognitivo y esfuerzo físico, mostrando en algunos casos que nivel alto de NC se relaciona con más actividad física y en otros estudios, un nivel bajo de NC se asocia con más ejercicio físico (McElroy, Dickinson & Dickinson, 2016). ...
... Priorities  Time spent on PA depends on the level of priority [63].  Priorities other than PA [67,82], PA not a priority [86] and lack of time management [55,80] are barriers to PA.  Some reported activities prioritized before PA are Internet use [87], TV use [53] and cognitive endeavours [88].  In some cases, prioritization can be perceived lack of time, which has been reported to sometimes be incongruent with a real lack of time [52,89]. ...
BACKGROUND Physical inactivity is a main risk factor of death worldwide, and contributes to psychological and physical problems, including obesity. Physical activity (PA) is critical to preventing health deterioration. Many technological interventions designed to promote PA have limited efficacy as some critical variables affecting PA are not considered. This study aims to understand the variables affecting PA, including barriers or facilitators for doing PA to facilitate the design of effective interventions OBJECTIVE (1) To investigate the mediating non-demographic variables of physical (in)activity, with emphasis on psychological variables, (2) to study which PA variables are considered in the design of intervention technologies to promote PA, (3) to provide a tool – a questionnaire- that allows the identification of PA variables when exploring the design space, (4) to investigate the relationship of PA variables with individuals' weight and actual PA level. METHODS We conducted two literature reviews on PA barriers/facilitators, using PsycINFO and ACM Digital Libraries. The PsycINFO literature search yielded 470 articles of which 50 articles were finally selected; PA barriers/facilitators were studied from these articles and used to design the Barriers Questionnaire for PA (BQPA) with 63 items. The ACM literature search yielded 123 articles, of which 15 articles were finally selected and used to evaluate the attention given to the PA variables in the design of technologies for PA. We then conducted a survey study using the BQPA, the International Physical Activity Questionnaire and demographic questions. The survey was filled out by a representative sample of the Spanish population (N=1012), including participants from all PA and weight levels. RESULTS 38 variables were identified as PA barriers/facilitators. Few studies evaluate their relationship with the actual PA level, and most lack an actual PA measure. The same barriers are reported for the overweight/obese and the normal-weight population, but some barriers are stronger in the obese. Only 17 out of the 38 variables were considered when developing PA technologies. On the survey data, we related the item scores with the participant’s PA level and weight. We found significant correlations between PA level and 62 BQPA items (all P<=.027) and between weight group and 35 BPQA items (all P<=.049). CONCLUSIONS Our contribution is three-fold. First, the literature reviews provide an in-depth account of barriers to PA in normal-weight, overweight and obese populations, and illustrate the lack of consideration of these in the design of PA technologies. Second, we propose a novel questionnaire on barriers to PA, specifically designed to ensure consideration of factors identified in the literature review. Third, we show high correlations between many identified variables and PA participation, and demonstrate how actual PA levels and body weight must also be considered. These results can guide future work on technological interventions for PA.
... En este estudio no se encontró evidencia suficiente para respaldar los hallazgos presentados por McElroy et al. (2016), que indican que las necesidades cognitivas son menores en los jóvenes universitarios que realizan mayor actividad física. Al no existir relación significativa entre la dimensión cognitiva y física, evaluada a través de pruebas selectivas autoadministradas, se sugiere continuar estos estudios midiendo ambas dimensiones con equipo tecnológico especializado. ...
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El ser humano sano mantiene un equilibrio biopsicosocial. La salud física y mental están estrechamente vinculadas e impacta en la productividad, funcionalidad y adaptabilidad a las exigencias cotidianas. Se espera que la interrelación de las distintas dimensiones humanas se manifieste proporcionalmente, esto es, a mayor salud física, mayor capacidad intelectual o viceversa. Este estudio parte del supuesto de que las personas que hacen ejercicio frecuentemente pueden gozar de mayor salud y registrar un mayor rendimiento cognitivo o mental que las personas que no se ejercitan con regularidad.El principal objetivo de esta investigación ha sido describir la relación entre la dimensión cognitiva y la dimensión física en estudiantes de licenciatura en cultura física y deporte de una universidad pública del noroeste de México. Lo anterior para conocer las características psicofísicas de los alumnos y poder proponer estrategias educativas adecuadas a su nivel de maduración, buscando potenciar su rendimiento y aprovechamiento escolar.El diseño de la investigación fue no experimental con enfoque cuantitativo. Se aplicó una batería de diversas pruebas cognitivas y físicas a 90 estudiantes de tercer semestre de dicha carrera para obtener un indicador global de la dimensión física y se recolectaron cuatro indicadores que constituyeron la dimensión cognitiva. Las variables se cruzaron para obtener el coeficiente de correlación de Pearson y verificar su significatividad estadística.En ambos sexos se encontró una relación positiva estadísticamente significativa entre las variables de inteligencia general obtenidas con el test de Dominó y el Exhcoba, que se utiliza como filtro de ingreso a la universidad. Además, se encontró correlación positiva entre las variables abdominales y salto horizontal. Se destaca, asimismo, la heterogeneidad de la población estudiada con respecto a sus hábitos para la ejercitación física y el desarrollo de las capacidades cognitivas. Finalmente, se concluye que la existencia de un dimorfismo sexual establece marcadas diferencias entre los sexos. Sin embargo, no se encontró correlación significativa entre la dimensión física y la dimensión cognitiva. Los resultados sugieren que es la apropiación de la cultura, la educabilidad del ser humano, la que impulsará un mayor desarrollo cognitivo y físico.
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The article aims to analyze the possibility of creative processes in artificial intelligence neural networks. In the past, AI was used to help people complete routine tasks. Whether automating functions, delivering optimized solutions, or a personal assistant, artificial intelligence is excellent at recognizing patterns and generating results that would be hard for the human brain to detect. Now we are seeing a shift in the use of AI in creative projects. AI can showcase a wide variety of work, and artists are using it as a tool to push creative boundaries in ways we have never seen before. Artificial intelligence is shaking the foundations of our existence, demonstrating how much of what people do, machines can do just as well, if not better. Based on the study of the functioning of modern artificial networks, the idea is substantiated that AI can participate at certain stages in the creative process as an independent actor. The creative process includes the steps of discovery and composition. At the same time, the latter in artificial neural networks takes place as a choice of known algorithmic combinations for creating a new object. The study explores the abilities of AI neural networks and determines the advantages of human creativity as a conception of new knowledge about the globe.
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The article aims to consider the practices and contemporary trends in the development of human resources by optimizing the mechanisms of public-private partnership in the domain of higher education: legal regulation, improvement of legal provision, updating the state personnel policy in the strategy of continuing education, integrating the use of state and industry resources to create conditions, introduce productive models and structures of cooperation employers and educational institutions of all levels in the practical training of young professionals to meet the staffing needs of the development of economic sectors. Sufficient interaction between the labor market and the education system is realized when the shared interests of all its issues are conjoined, in particular through the orientation of the personnel management of companies towards the preliminary technology in the selection of personnel, as well as the development, together with professional higher education institutions, of in-house corporate training and retraining of personnel.
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Background: Many technological interventions designed to promote physical activity (PA) have limited efficacy and appear to lack important factors that could increase engagement. This may be due to a discrepancy between research conducted in this space, and software designers' and developers' use of this research to inform new digital applications. Objectives: This study aimed to identify (1) what are the variables that act as barriers and facilitators to PA and (2) which PA variables are currently considered in the design of technologies promoting PA including psychological, physical, and personal/contextual ones which are critical in promoting PA. We emphasize psychological variables in this work because of their sparse and often simplistic integration in digital applications for PA. Methods: We conducted two systematized reviews on PA variables, using PsycInfo and Association for Computing Machinery Digital Libraries for objectives 1 and 2. Results: We identified 38 PA variables (mostly psychological ones) including barriers/facilitators in the literature. 17 of those variables were considered when developing digital applications for PA. Only few studies evaluate PA levels in relation to these variables. The same barriers are reported for all weight groups, though some barriers are stronger in people with obesity. Conclusions: We identify PA variables and illustrate the lack of consideration of these in the design of PA technologies. Digital applications to promote PA may have limited efficacy if they do not address variables acting as facilitators or barriers to participation in PA, and that are important to people representing a range of body weight characteristics.
Online, virtual group interactions may help adherence to health promotion programs. The purpose of this study was to explore longitudinal relationships among dimensions of group cohesion and group-interaction variables to inform and improve group-based strategies within programs aimed at promoting physical activity in virtual communities. In all, 56 online virtual users completed a group dynamics–based physical activity promotion intervention and assessments of group cohesion and group interaction at baseline and 4 weeks. Friendly competition and cooperation were consistently strong predictors of cohesion. Facilitating a sense of friendly competition and cooperation may increase engagement in physical activity programs by bolstering group cohesion.
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Objective: To encourage increased participation in physical activity among Americans of all ages by issuing a public health recommendation on the types and amounts of physical activity needed for health promotion and disease prevention. Participants: A planning committee of five scientists was established by the Centers for Disease Control and Prevention and the American College of Sports Medicine to organize a workshop. This committee selected 15 other workshop discussants on the basis of their research expertise in issues related to the health implications of physical activity. Several relevant professional or scientific organizations and federal agencies also were represented. Evidence: The panel of experts reviewed the pertinent physiological, epidemiologic, and clinical evidence, including primary research articles and recent review articles. Consensus process: Major issues related to physical activity and health were outlined, and selected members of the expert panel drafted sections of the paper from this outline. A draft manuscript was prepared by the planning committee and circulated to the full panel in advance of the 2-day workshop. During the workshop, each section of the manuscript was reviewed by the expert panel. Primary attention was given to achieving group consensus concerning the recommended types and amounts of physical activity. A concise "public health message" was developed to express the recommendations of the panel. During the ensuing months, the consensus statement was further reviewed and revised and was formally endorsed by both the Centers for Disease Control and Prevention and the American College of Sports Medicine. Conclusion: Every US adult should accumulate 30 minutes or more of moderate-intensity physical activity on most, preferably all, days of the week.
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Association and dissociation (A/D) have been identified as important cognitive strategies in the literature on running and exercise. This paper is a comprehensive review of the 20 years of research in the area. Specific topics addressed include historical context, definition and terminology considerations, measurement and design issues, and findings as they pertain to performance, injury, and pain. Several research recommendations are made including change from using the term dissociation, use of multiple measurement methods, diversity of research designs, and study of topics, such as injury, exercise adherence, and emotionality, as they relate to A/D. Finally, practical findings indicate that association relates to faster performance, dissociation relates to lower perceived exertion and possibly greater endurance, and dissociation is not related to injury but association may be.
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The validity effect is the increase in perceived validity of repeated statements. In the first experiment, subjects rated repeated and nonrepeated statements for validity, familiarity, and source recognition. Validity and familiarity were enhanced by repetition, but source dissociation was not. A path analysis suggested that familiarity mediates perceived validity. In Experiment 2, statements presented in a natural setting were later rated for perceived validity, familiarity, and source recognition. Repetition had parallel effects on validity and familiarity ratings, but source dissociation was unaffected. Controlling for familiarity statistically eliminated the validity effect. In Experiment 3, the effect of prior knowledge on validity judgments was studied. Subjects rated the validity of statements that were related or unrelated to their field of expertise. Those most knowledgeable about the topic were most likely to exhibit the validity effect. Overall, the results suggest that familiarity is the basis of judged validity.
Physical activity may play an important role in the management of mild-to-moderate mental health diseases, especially depression and anxiety. Although people with depression tend to be less physically active than non-depressed individuals, increased aerobic exercise or strength training has been shown to reduce depressive symptoms significantly. However, habitual physical activity has not been shown to prevent the onset of depression. Anxiety symptoms and panic disorder also improve with regular exercise, and beneficial effects appear to equal meditation or relaxation. In general, acute anxiety responds better to exercise than chronic anxiety. Studies of older adults and adolescents with depression or anxiety have been limited, but physical activity appears beneficial to these populations as well. Excessive physical activity may lead to overtraining and generate psychological symptoms that mimic depression. Several differing psychological and physiological mechanisms have been proposed to explain the effect of physical activity on mental health disorders. Well controlled studies are needed to clarify the mental health benefits of exercise among various populations and to address directly processes underlying the benefits of exercise on mental health.
This study examined the effects of attentional intervention strategies upon perceived exertion in female exercisers (N = 13). Interventions were based upon Stevinson and Biddle's (1999) coping strategy model, from which 4 variations of attentional style are derived: internal and external association, and internal and external dissociation. The first of 5 sessions consisted of a sub-maximal VO2 test aimed at assessing aerobic capacity of the participants. In the following 4 sessions, participants pedaled on stationary cycling ergometer at 75% VO2max for 10 minutes, and rated their perceived exertion (RPE) in 1-minute intervals. Significant (p < .01) differences in RPE between the associative and dissociative treatments emerged. The 2 associative treatments resulted in higher RPE levels than the 2 dissociative treatments for the same physical load. However, non-significant differences in RPE emerged between the internal and external dimensions, suggesting that the associative-dissociative dimension is the main determinant of RPE. Pragmatic applications of these findings and future research directions are offered.