2. Gestión laboral
2.4. Modelo de una gestión laboral efectiva
The central aim of this thesis is to contribute to the understanding of the underlying key
mechanisms of learning across the lifespan on cognitive reinforcment learning by calculating
the RBc. Reward bias indicates an individual’s bias in terms of their propensity to act upon
previous positive or negative feedback events covering the age range from childhood until
adulthood. This research intends to examine developmental differences in behavioural
response during reward anticipation and/or receipt in children/adolescents (7-18 years old)
compared to adults (19-55 years old). The rationale for testing RBc until the age o f 55 is due
to time constrains of this thesis. We aimed to further test the RBc and aging in older adults (>
thesis completion. However, this could be taken into consideration as a future research in
reward processing and aging.
Cognitive reinforcement learning includes a variety of brain regions such as the striatum and
the prefrontal cortex (Schultz, 2000) both of which undergo significant age-related changes.
Therefore, an opportunity exists in this thesis to examine the underlying mechanisms of how
reward based learning progress from early childhood to adulthood. Results from this research
would lead to better insights associated in educational practice such as schools, colleges in
order to provide better means of investigating cognitive reinforcement learning from the early
stages of life since feedback learning has been found to lie in the basis of successful learning
(Galvan, 2010). Our primary goal is to develop a theoretical framework for understanding the
contribution of age-related differences to cognitive reinforcement learning and decision
making. How healthy individuals modify the likelihood of selecting a given response on the
basis of experienced outcomes across the lifespan? What enables individuals to make choices
that lead to positive outcomes and avoid making choices that would lead to negative
outcomes?
1.4.1. Summary o f the Experimental Chapters and Research Questions
Chapter Two reports an initial study (Study 1) designed to establish previous work by Frank
et al. (2004) utilising the cognitive reinforcement learning paradigm, which is a suitable
measurement of RBc for addressing the research aims of this thesis. Firstly, Study 1 was
designed to assess whether cognitive reinforcement learning exists in children and
adolescents by utilising the “carrot or stick” probabilistic task by Frank, Seeberger and
puberty (15-18 years old). Would children and adolescents comprehend reward processing as
adults? Would children and adolescents learn equally from positive and negative feedback?
Would children and adolescents comprehend the adult-appropriate task design by Frank et al.
(2004)? Would children and adolescents find the task design engaging? Would children find
the task demand more difficult and subsequently become less engaged in the task? Could age
and gender differentiations be associated to reward processing?
Chapter Three reports three studies (Study 2, 3 and 4) designed to evaluate negative and
positive feedback based learning from these age groups (7-10, 11-14, 15-18, 19-35 and 40-55
years of age). Initially, Study 2 introduced an adapted task design called “prince and
princess” which was implemented for the purposes of this thesis, aimed to maximise task
engagement and comprehension at the age of 7-18 years old and test whether overall
cognitive performance improves during the child-friendly task design. This reasoning is
based on developmental reward studies, which indicated that successful task performance lies
at the basis of task design (Bjork et al., 2004; Galvan et al., 2006; Ernst et al., 2005; May et
al., 2004; van Leijenhorst et al., 2009). Task choice plays a key role in reward processing
(Bjork et al., 2004; van Leijenhorst et al., 2009). In order to optimise task engagement and
comprehension, some studies have presented “cartoon-friendly” stimuli (van Leijenhorst et
al., 2009; Galvan et al., 2006) and introduced the task to participants in the form of a video
game. For example, in Study 2 during the “prince and princess” task children were told “you
have to help the prince to save the princess from the evil dragon, ” (see method section 3.2.3).
By introducing an action based on reinforcement learning feedback we want to ensure that
children and adolescents would comprehend the task as well as adults (e.g., ensuring that
anxiety behaviour). Additionally, ensure proper response time for children by making the task
more engaging. Studies have shown that children have longer reaction time than adults (Bjork
et al., 2004; Galvan, 2004; Galvan et al., 2006). Lastly, the purpose of this task adaptation is
to make the task as simple as possible without multiple rules that the chid could follow (Bjork
et al., 2004). Therefore, the research aim of this study is to investigate whether children and
adolescents would find this task more engaging compared to the adult-appropriate task (see
method section 3.2.3). Would children (aged 7-10) and adolescents (aged 11-14 and 15-18)
demonstrate different reward sensitivity compared to Study 1? How would RBc behave
relative to propensity within a fi*amed action based feedback? Is there a relationship between
age-related differences and reward processing during development? Would gender
differences affect the magnitude of the RBc?
These effortful responses have led to the design of Study 3. The first aim was to provide a
detailed analysis of the RBc based on the “prince and princess” paradigm within healthy
populations aged 19-35. Additionally, Study 3 aims to compare the propensity of reward bias
from these age groups (7-10, 11-14, 15-18 and 19-35 years o f age). How adults response to
positive and negative feedback? Do they learn better fi*om positive or negative feedback
events? Does RBc fluctuate after adolescence? Study 4 is a follow-up study to Study 3,
which employs the identical task design within older adults (40-55 years old) to test age
related differences in reward processing. This study provides the means to address the same
aims as Study 3 but in the context of reward processing and theory o f aging. Evidence
reviewed in this chapter demonstrated an asymmetry between positive and negative
emotional experiences across the lifespan (Carstensen & Mikels, 2005). Adults differ from
younger individuals (college age) in the kinds of information from past experience they focus
theory of aging, which posts that older adults place more emphasis on positive emotional
experiences as they approach the end of life (Carstensen, 2006). One understudied aspect of
this age-related optimization is how older adults respond to positive and negative feedback
versus positive and negative stimuli. A previous study has found that older adults have an
attention bias to positive versus negative stimuli, because positive stimuli generate feelings of
well-being (Charles, Mather, & Carstensen, 2003). For that reason. Study 4 aims to better
understand how healthy adults (40-55 years old) learn from their decisions (both good and
bad) and whether they to be more conservative relative to reward seeking behaviour. Finally,
Chapter Four will present an overall description of the main findings derived from this thesis
and provide the framework for future research in age-related differences in learning from