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Pathways Mental Health
Psychiatric Patient EvaluationInstructions
Use the following case template to complete Week 2
Assignment 1. On page 5, assign
DSM-5-TR and Updated ICD-10 codes to
the services documented. You will add your narrative answers
to the assignment questions to the bottom of this template and
submit altogether as one document.
Identifying Information
Identification was verified by stating of their name and date of
birth.
Time spent for evaluation: 0900am-0957amChief Complaint
“My other provider retired. I don’t think I’m doing so well.”HPI
25 yo Russian female evaluated for psychiatric evaluation
referred from her retiring practitioner for PTSD, ADHD,
Stimulant Use Disorder, in remission. She is currently
prescribed fluoxetine 20mg po daily for PTSD, atomoxetine
80mg po daily for ADHD.
Today, client denied symptoms of depression, denied anergia,
anhedonia, amotivation, no anxiety, denied frequent worry,
reports feeling restlessness, no reported panic symptoms, no
reported obsessive/compulsive behaviors. Client denies active
SI/HI ideations, plans or intent. There is no evidence of
psychosis or delusional thinking. Client denied past episodes of
hypomania, hyperactivity, erratic/excessive spending,
involvement in dangerous activities, self-inflated ego,
grandiosity, or promiscuity. Client reports increased irritability
and easily frustrated, loses things easily, makes mistakes, hard
time focusing and concentrating, affecting her job. Has low
frustration tolerance, sleeping 5–6 hrs/24hrs reports nightmares
of previous rape, isolates, fearful to go outside, has missed
several days of work, appetite decreased. She has somatic
concerns with GI upset and headaches. Client denied any
current binging/purging behaviors, denied withholding food
from self or engaging in anorexic behaviors. No self-mutilation
behaviors. Diagnostic Screening Results
Screen of symptoms in the past 2 weeks:
PHQ 9 = 0 with symptoms rated as no difficulty in functioning
Interpretation of Total Score
Total Score Depression Severity 1-4 Minimal depression 5-9
Mild depression 10-14 Moderate depression 15-19 Moderately
severe depression 20-27 Severe depression
GAD 7 = 2 with symptoms rated as no difficulty in functioning
Interpreting the Total Score:
Total Score Interpretation ≥10 Possible diagnosis of GAD;
confirm by further evaluation 5 Mild Anxiety 10 Moderate
anxiety 15 Severe anxiety
MDQ screen negative
PCL-5 Screen 32Past Psychiatric and Substance Use Treatment
Entered mental health system when she was age 19 after raped
by a stranger during a house burglary.
Previous Psychiatric Hospitalizations: denied
Previous Detox/Residential treatments: one for abuse of
stimulants and cocaine in 2015
Previous psychotropic medication trials: sertraline (became
suicidal), trazodone (worsened nightmares), bupropion (became
suicidal), Adderall (began abusing)
Previous mental health diagnosis per client/medical record:
GAD, Unspecified Trauma, PTSD, Stimulant use disorder,
ADHD confirmed by school recordsSubstance Use History
Have you used/abused any of the following (include
frequency/amt/last use):
Substance Y/N Frequency/Last Use
Tobacco products Y ½
ETOH Y last drink 2 weeks ago, reports drinks 1-2 times
monthly one drink socially
Cannabis N
Cocaine Y last use 2015
Prescription stimulants Y last use 2015
Methamphetamine N
Inhalants N
Sedative/sleeping pills N
Hallucinogens N
Street Opioids N
Prescription opioids N
Other: specify (spice, K2, bath salts, etc.) Y reports one-
time ecstasy use in 2015
Any history of substance related:
Blackouts: +
Tremors: -
DUI: -
D/T's: -
Seizures: -
Longest sobriety reported since 2015—stayed sober maintaining
sponsor, sober friends, and meetingsPsychosocial History
Client was raised by adoptive parents since age 6; from Russian
orphanage. She has unknown siblings. She is single; has no
children.
Employed at local tanning bed salon
Education: High School Diploma
Denied current legal issues.Suicide / HOmicide Risk
Assessment
RISK FACTORS FOR SUICIDE:
Suicidal Ideas or plans - no
Suicide gestures in past - no
Psychiatric diagnosis - yes
Physical Illness (chronic, medical) - no
Childhood trauma - yes
Cognition not intact - no
Support system - yes
Unemployment - no
Stressful life events - yes
Physical abuse - yes
Sexual abuse - yes
Family history of suicide - unknown
Family history of mental illness - unknown
Hopelessness - no
Gender - female
Marital status - single
White race
Access to means
Substance abuse - in remission
PROTECTIVE FACTORS FOR SUICIDE:
Absence of psychosis - yes
Access to adequate health care - yes
Advice & help seeking - yes
Resourcefulness/Survival skills - yes
Children - no
Sense of responsibility - yes
Pregnancy - no; last menses one week ago, has Norplant
Spirituality - yes
Life satisfaction - “fair amount”
Positive coping skills - yes
Positive social support - yes
Positive therapeutic relationship - yes
Future oriented - yes
Suicide Inquiry: Denies active suicidal ideations, intentions, or
plans. Denies recent self-harm behavior. Talks futuristically.
Denied history of suicidal/homicidal ideation/gestures; denied
history of self-mutilation behaviors
Global Suicide Risk Assessment: The client is found to be at
low risk of suicide or violence, however, risk of lethality
increased under context of drugs/alcohol.
No required SAFETY PLAN related to low riskMental Status
Examination
She is a 25 yo Russian female who looks her stated age. She is
cooperative with examiner. She is neatly groomed and clean,
dressed appropriately. There is mild psychomotor restlessness.
Her speech is clear, coherent, normal in volume and tone, has
strong cultural accent. Her thought process is ruminative. There
is no evidence of looseness of association or flight of ideas. Her
mood is anxious, mildly irritable, and her affect appropriate to
her mood. She was smiling at times in an appropriate manner.
She denies any auditory or visual hallucinations. There is no
evidence of any delusional thinking. She denies any current
suicidal or homicidal ideation. Cognitively, She is alert and
oriented to all spheres. Her recent and remote memory is intact.
Her concentration is fair. Her insight is good. Clinical
Impression
Client is a 25 yo Russian female who presents with history of
treatment for PTSD, ADHD, Stimulant use Disorder, in
remission.
Moods are anxious and irritable. She has ongoing reported
symptoms of re-experiencing, avoidance, and hyperarousal of
her past trauma experiences; ongoing subsyndromal symptoms
related to her past ADHD diagnosis and exacerbated by her
PTSD diagnosis. She denied vegetative symptoms of depression,
no evident mania/hypomania, no psychosis, denied anxiety
symptoms. Denied current cravings for drugs/alcohol, exhibits
no withdrawal symptoms, has somatic concerns of GI upset and
headaches.
At the time of disposition, the client adamantly denies SI/HI
ideations, plans or intent and has the ability to determine right
from wrong, and can anticipate the potential consequences of
behaviors and actions. She is a low risk for self-harm based on
her current clinical presentation and her risk and protective
factors. Diagnostic Impression
[Student to provide DSM-5-TR and Updated ICD-10 coding]
Double click inside this text box to add/edit text. Delete
placeholder text when you add your answers.Treatment Plan
Medication:
Increase fluoxetine 40mg po daily for PTSD #30 1 RF
Continue with atomoxetine 80mg po daily for ADHD. #30 1 RF
Instructed to call and report any adverse reactions.
Future Plan: monitor for decrease re-experiencing,
hyperarousal, and avoidance symptoms; monitor for improved
concentration, less mistakes, less forgetful
Education: Risks and benefits of medications are discussed
including non-treatment. Potential side effects of medications
discussed. Verbal informed consent obtained.
Not to drive or operate dangerous machinery if feeling sedated.
Not to stop medication abruptly without discussing with
providers.
Discussed risks of mixing medications with OTC drugs, herbal,
alcohol/illegal drugs. Instructed to avoid this practice. Praised
and Encouraged ongoing abstinence. Maintain support system,
sponsors, and meetings.
Discussed how drugs/ETOH affects mental health, physical
health, sleep architecture.
Patient was educated about therapy and services of the MHC
including emergent care. Referral was sent via email to therapy
team for PET treatment.
Patient has emergency numbers: Emergency Services 911, the
national Crisis Line 800-273-TALK, the MHC Crisis Clinic.
Patient was instructed to go to nearest ER or call 911 if they
become actively suicidal and/or homicidal.
Time allowed for questions and answers provided. Provided
supportive listening. Patient appeared to understand discussion
and appears to have capacity for decision making via verbal
conversation.
RTC in 30 days
Follow up with PCP for GI upset and headaches, reviewed PCP
history and physical dated one week ago and include lab results
Patient is amenable with this plan and agrees to follow
treatment regimen as discussed.
Narrative Answers
[In 1-2 pages, address the following:
· Explain what pertinent information, generally, is required in
documentation to support DSM-5-TR and Updated ICD-10
coding.
· Explain what pertinent documentation is missing from the case
scenario, and what other information would be helpful to narrow
your coding and billing options.
· Finally, explain how to improve documentation to support
coding and billing for maximum reimbursement.]
Add your answers here. Delete instructions and placeholder text
when you add your answers.
References
[Add APA-formatted citations for any sources you referenced
Delete instructions and placeholder text when you add your
citations.
Page | 2
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REVIEW
published: 08 May 2020
doi: 10.3389/fspor.2020.00042
Frontiers in Sports and Active Living | www.frontiersin.org 1
May 2020 | Volume 2 | Article 42
Edited by:
Sophia Nimphius,
Edith Cowan University, Australia
Reviewed by:
Chris John Bishop,
Middlesex University, United Kingdom
Claudia Reardon,
University of Wisconsin-Madison,
United States
*Correspondence:
J. Bryan Mann
[email protected]
Specialty section:
This article was submitted to
Elite Sports and Performance
Enhancement,
a section of the journal
Frontiers in Sports and Active Living
Received: 05 October 2019
Accepted: 30 March 2020
Published: 08 May 2020
Citation:
Lopes Dos Santos M, Uftring M,
Stahl CA, Lockie RG, Alvar B,
Mann JB and Dawes JJ (2020) Stress
in Academic and Athletic Performance
in Collegiate Athletes: A Narrative
Review of Sources and Monitoring
Strategies.
Front. Sports Act. Living 2:42.
doi: 10.3389/fspor.2020.00042
Stress in Academic and Athletic
Performance in Collegiate Athletes: A
Narrative Review of Sources and
Monitoring Strategies
Marcel Lopes Dos Santos 1, Melissa Uftring 1, Cody A. Stahl 1,
Robert G. Lockie 2,
Brent Alvar 3, J. Bryan Mann 4* and J. Jay Dawes 1
1 School of Kinesiology, Applied Health and Recreation,
Oklahoma State University, Stillwater, OK, United States,
2Department of Kinesiology, California State University,
Fullerton, CA, United States, 3Department of Kinesiology,
Point Loma
Nazarene University, San Diego, CA, United States,
4Department of Kinesiology and Sport Sciences, University of
Miami,
Miami, FL, United States
College students are required to manage a variety of stressors
related to academic,
social, and financial commitments. In addition to the burdens
facing most college
students, collegiate athletes must devote a substantial amount of
time to improving
their sporting abilities. The strength and conditioning
professional sees the athlete on
nearly a daily basis and is able to recognize the changes in
performance and behavior an
athlete may exhibit as a result of these stressors. As such, the
strength and conditioning
professional may serve an integral role in the monitoring of
these stressors and may be
able to alter training programs to improve both performance
andwellness. The purpose of
this paper is to discuss stressors experienced by collegiate
athletes, developing an early
detection system through monitoring techniques that identify
the detrimental effects of
stress, and discuss appropriate stress management strategies for
this population.
Keywords: stress, load management, academic stress, stress
management, injury
INTRODUCTION
The college years are a period of time when young adults
experience a significant amount of change
and a variety of novel challenges. Academic performance, social
demands, adjusting to life away
from home, and financial challenges are just a few of the
burdens college students must confront
(Humphrey et al., 2000; Paule and Gilson, 2010; Aquilina,
2013). In addition to these stressors,
collegiate athletes are required to spend a substantial amount of
time participating in activities
related to their sport, such as attending practices and training
sessions, team meetings, travel, and
competitions (Humphrey et al., 2000; López de Subijana et al.,
2015; Davis et al., 2019; Hyatt and
Kavazis, 2019). These commitments, in addition to the normal
stress associated with college life,
may increase a collegiate-athlete’s risk of experiencing both
physical and mental issues (Li et al.,
2017; Moreland et al., 2018) that may affect their overall health
and wellness. For these reasons, it is
essential that coaches understand the types of stressors
collegiate athletes face in order to help them
manage the potentially deleterious effects stress may have on
athletic and academic performance.
Strength and conditioning coaches are allied health care
professionals whose primary
job is to enhance fitness of individuals for the purpose of
improving athletic performance
(Massey et al., 2002, 2004, 2009). As such, many universities
and colleges hire strength
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Lopes Dos Santos et al. Stress in College Athletes
and conditioning coaches as part of their athletic staff to help
athletes maximize their physical potential (Massey et al., 2002,
2004, 2009). Strength and conditioning coaches strive to
increase
athletic performance by the systematic application of physical
stress to the body via resistance training, and other forms of
exercise, to yield a positive adaptation response (Massey et al.,
2002, 2004, 2009). For this reason, they need to understand and
to learn how to manage athletes’ stress. Additionally, based on
the cumulative nature of stress, it is important that both mental
and emotional stressors are also considered in programming. It
is imperative that strength and conditioning coaches are aware
of
the multitude of stressors collegiate athletes encounter, in order
to incorporate illness and injury risk management education into
their training programs (Radcliffe et al., 2015; Ivarsson et al.,
2017).
Based on the large number of contact hours strength and
conditioning coaches spend with their athletes, they are in
an optimal position to assist athletes with developing effective
coping strategies to manage stress. By doing so, strength and
conditioning coaches may be able to help reach the overarching
goal of improving the health, wellness, fitness, and performance
of the athletes they coach. The purpose of this review article
is to provide the strength and conditioning professional with a
foundational understanding of the types of stressors collegiate
athletes may experience, and how these stressors may impact
mental health and athletic performance. Suggestions for
assisting
athletes with developing effective coping strategies to reduce
potential physiological and psychological impacts of stress will
also be provided.
Stress and the Stress Response
In its most simplistic definition, stress can be described as a
state of physical and psychological activation in response to
external demands that exceed one’s ability to cope and requires
a person to adapt or change behavior. As such, both cognitive
or environmental events that trigger stress are called stressors
(Statler and DuBois, 2016). Stressors can be acute or chronic
based on the duration of activation. Acute stressors may be
defined as a stressful situation that occurs suddenly and results
in physiological arousal (e.g., increase in hormonal levels,
blood
flow, cardiac output, blood sugar levels, pupil and airway
dilation,
etc.) (Selye, 1976). Once the situation is normalized, a cascade
of hormonal reactions occurs to help the body return to a
resting state (i.e., homeostasis). However, when acute stressors
become chronic in nature, they may increase an individual’s
risk of developing anxiety, depression, or metabolic disorders
(Selye, 1976). Moreover, the literature has shown that
cumulative
stress is correlated with an increased susceptibility to illness
and injury (Szivak and Kraemer, 2015; Mann et al., 2016;
Hamlin et al., 2019). The impact of stress is individualistic and
subjective by nature (Williams and Andersen, 1998; Ivarsson
et al., 2017). Additionally, the manner in which athletes respond
to a situational or environmental stressor is often determined
by their individual perception of the event (Gould and Udry,
1994; Williams and Andersen, 1998; Ivarsson et al., 2017). In
this
regard, the athlete’s perception can either be positive (eustress)
or negative (distress). Even though they both cause
physiological
arousal, eustress also generates positive mental energy whereas
distress generates anxiety (Statler and DuBois, 2016).
Therefore,
it is essential that an athlete has the tools and ability to cope
with
these stressors in order to have the capacity to manage both
acute
and chronic stress. As such, it is important to understand the
types of stressors collegiate athletes are confronted with and
how
these stressors impact an athlete’s performance, both
athletically
and academically.
METHODS
Literature Search/Data Collection
The articles included in this review were identified via online
databases PubMed, MEDLINE, and ISI Web of Knowledge
from October 15th 2019 through January 15th 2020. The
search strategy combined the keywords “academic stress,”
“athletic stress,” “stress,” “stressor,” “college athletes,”
“student
athletes,” “collegiate athletes,” “injury,” “training,”
“monitoring.”
Duplicated articles were then removed. After reading the titles
and abstracts, all articles that met the inclusion criteria were
considered eligible for inclusion in the review. Subsequently,
all eligible articles were read in their entirety and were either
included or removed from the present review.
Inclusion Criteria
The studies included met all the following criteria: (i) published
in English-language journals; (ii) targeted college athletes; (iii)
publication was either an original research paper or a literature
review; (iv) allowed the extraction of data for analysis.
Data Analysis
Relevant data regarding participant characteristics (i.e.,
gender, academic status, sports) and study characteristics
were extracted. Articles were analyzed and divided into two
separate sections based on their specific topics: Academic
Stress and Athletic Stress. Then, strategies for monitoring and
workload management are discussed in the final section.
ACADEMIC STRESS
Fundamentally, collegiate athletes have two major roles they
must balance as part of their commitment to a university: being
a college student and an athlete. Academic performance is a
significant source of stress for most college students (Aquilina,
2013; López de Subijana et al., 2015; de Brandt et al., 2018;
Davis et al., 2019). This stress may be further compounded
among collegiate athletes based on their need to be successful
in
the classroom, while simultaneously excelling in their
respective
sport (Aquilina, 2013; López de Subijana et al., 2015; Huml
et al., 2016; Hamlin et al., 2019). Davis et al. (2019) conducted
surveys on 173 elite junior alpine skiers and reported
significant
moderate to strong correlations between perceived stress and
several variables including depressed mood (r = 0.591), sleep
disturbance (r = 0.459), fatigue (r = 0.457), performance
demands (r = 0.523), and goals and development (r = 0.544).
Academic requirements were the highest scoring source of
stress
of all variables and was most strongly correlated with perceived
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Lopes Dos Santos et al. Stress in College Athletes
stress (r = 0.467). Interestingly, it was not academic rigor that
was viewed by the athletes as the largest source of direct stress;
rather, the athletes surveyed reported time management as being
their biggest challenge related to academic performance (Davis
et al., 2019). This further corroborates the findings of Hamlin
et al. (2019). The investigators reported that during periods
of the academic year in which levels of perceived academic
stress were at their highest, students had trouble managing sport
practices and studying. These stressors were also associated
with
a decrease in energy levels and overall sleep quality. These
factors
may significantly increase the collegiate athlete’s susceptibility
to illness and injury (Hamlin et al., 2019). For this reason,
coaches should be aware of and sensitive to the stressors
athletes
experience as part of the cyclical nature of the academic year
and
attempt to help athletes find solutions to balancing athletic and
academic demands.
According to Aquilina (2013), collegiate athletes tend to be
more committed to sports development and may view their
academic career as a contingency plan to their athletic career,
rather than a source of personal development. As a result,
collegiate athletes often, but certainly not always, prioritize
athletic participation over their academic responsibilities
(Miller
and Kerr, 2002; Cosh and Tully, 2014, 2015). Nonetheless,
scholarships are usually predicated on both athletic and
academic
performance. For instance, the National Collegiate Athletic
Association (NCAA) requires collegiate athletes to achieve and
maintain a certain grade point average (GPA). Furthermore,
they
are also often required to also uphold a certain GPA to maintain
an athletic scholarship. The pressure to maintain both high
levels
of academic and athletic performancemay increase the
likelihood
of triggeringmental health issues (i.e., anxiety and depression)
(Li
et al., 2017; Moreland et al., 2018).
Mental health issues are a significant concern among college
students. There has been an increased emphasis placed on the
mental health of collegiate athletes in recent years (Petrie et al.,
2014; Li et al., 2017, 2019; Reardon et al., 2019). Based on
the 2019 National College Health Assessment survey from the
American College Health Association (ACHA) consisting of
67,972 participants, 27.8% of college students reported anxiety,
and 20.2% reported experiencing depression which negatively
affected their academic performance (American College Health
Association American College Health Association-National
College Health Assessment II, 2019). Approximately 65.7%
(50.7% males and 71.8% females) reported feeling
overwhelming
anxiety in the past 12months, and 45.1% (37.1%males and
47.6%
females) reported feeling so depressed that it was difficult for
them to function. However, only 24.3% (13% males and 28.4%
females) reported being diagnosed and treated by a professional
in the past 12 months. Collegiate athletes are not immune to
these types of issues. According to information presented by
the NCAA, many certified athletic trainers anecdotally state that
anxiety is an issue affecting the collegiate-athlete population
(NCAA, 2014). However, despite the fact that collegiate
athletes
are exposed to numerous stressors, they are less likely to
seek help at a university counseling center than non-athletes
(NCAA, 2014), which could be related to stigmas that surround
mental health services (NCAA, 2014; Kaier et al., 2015; Egan,
2019). This not only has significant implications related to their
psychological well-being, but also their physiological health,
and
consequently their performance. For instance, in a study by
Li et al. (2017) it was found that NCAA Division I athletes
who reported preseason anxiety symptoms had a 2.3 times
greater injury incidence rate compared to athletes who did
not report. This same study discovered that male athletes who
reported preseason anxiety and depression had a 2.1 times
greater
injury incidence, compared to male athletes who did not report
symptoms of anxiety and depression. (Lavallée and Flint, 1996)
also reported a correlation between anxiety and both injury
frequency and severity among college football players (r = 0.43
and r = 0.44, respectively). In their study, athletes reporting
high
tension/anxiety had a higher rate of injury. It has been
suggested
that the occurrence of stress and anxiety may cause
physiological
responses, such as an increase in muscle tension, physical
fatigue,
and a decrease in neurocognitive and perception processes that
can lead to physical injuries (Ivarsson et al., 2017). For this
reason, it is reasonable to consider that academic stressors may
potentiate effects of stress and result in injury and illness in
collegiate athletes.
Periods of more intense academic stress increase the
susceptibility to illness or injury (Mann et al., 2016; Hamlin
et al., 2019; Li et al., 2019). For example, Hamlin et al. (2019)
investigated levels of perceived stress, training loads, injury,
and
illness incidence in 182 collegiate athletes for the period of one
academic year. The highest levels of stress and incidence of
illness arise during the examination weeks occurring within the
competitive season. In addition, the authors also reported the
odds ratio, which is the occurrence of the outcome of interest
(i.e., injury), based off the given exposure to the variables of
interest (i.e., perceived mood, sleep duration, increased
academic
stress, and energy levels). Based on a logistic regression, they
found that each of the four variables (i.e., mood, energy, sleep
duration, and academic stress) was related to the collegiate
athletes’ likelihood to incur injuries. In summary, decreased
levels of perceived mood (odds ratio of 0.89, 0.85–0.0.94 CI)
and
sleep duration (odds ratio of 0.94, 0.91–0.97 CI), and increased
academic stress (odds ratio of 0.91, 0.88–0.94 CI) and energy
levels (odds ratio of 1.07, 1.01–1.14 CI), were able to predict
injury in these athletes. This corroborates Mann et al. (2016)
who
foundNCAADivision I football athletes at a Bowl Championship
Subdivision university were more likely to become ill or injured
during an academically stressful period (i.e., midterm exams
or other common test weeks) than during a non-testing week
(odds ratio of 1.78 for high academic stress). The athletes were
also less likely to get injured during training camp (odds ratio
of 3.65 for training camp). Freshmen collegiate athletes may
be especially more susceptible to mental health issues than
older students. Their transition includes not only the academic
environment with its requirements and expectations, but also
the adaptation to working with a new coach and teammates.
In this regard, Yang et al. (2007) found an increase in the
likelihood of depression that freshmen athletes experienced,
as these freshmen were 3.27 times more likely to experience
depression than their older teammates. While some stressors
are recurrent and inherent in academic life (e.g., attending
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classes, homework, etc.), others are more situational (e.g.,
exams,
midterms, projects) and may be anticipated by the strength and
conditioning coach.
ATHLETIC STRESS
The domain of athletics can expose collegiate athletes to
additional stressors that are specific to their cohort (e.g., sport-
specific, team vs. individual sport) (Aquilina, 2013). Time
spent training (e.g., physical conditioning and sports practice),
competition schedules (e.g., travel time, missing class), dealing
with injuries (e.g., physical therapy/rehabilitation, etc.), sport-
specific social support (e.g., teammates, coaches) and playing
status (e.g., starting, non-starter, being benched, etc.) are just a
few of the additional challenges collegiate athletes must
confront
relative to their dual role of being a student and an athlete
(Maloney and McCormick, 1993; Scott et al., 2008; Etzel, 2009;
Fogaca, 2019). Collegiate athletes who view the demands of
stressors from academics and sports as a positive challenge
(i.e.,
an individual’s self-confidence or belief in oneself to
accomplish
the task outweighs any anxiety or emotional worry that is
felt) may potentially increase learning capacity and competency
(NCAA, 2014). However, when these demands are perceived as
exceeding the athlete’s capacity, this stress can be detrimental
to the student’s mental and physical health as well as to sport
performance (Ivarsson et al., 2017; Li et al., 2017).
As previously stated, time management has been shown to
be a challenge to collegiate athletes. The NCAA rules state
that collegiate athletes may only engage in required athletic
activities for 4 h per day and 20 h/week during in-season and
8 h/week during off-season throughout the academic year.
Although these rules have been clearly outlined, the most
recent NCAA GOALS (2016) study reported alarming numbers
regarding time commitment to athletic-related activities. Data
from over 21,000 collegiate athletes from 600 schools across
Divisions I, II, and III were included in this study. Although a
breakdown of time commitments was not provided, collegiate
athletes reported dedicating up to 34 h per week to athletics
(e.g., practices, weight training, meetings with coaches, tactical
training, competitions, etc.), in addition to spending between
38.5 and 40 h per week working on academic-related tasks. This
report also showed a notable trend related to athletes spending
an
increase of ∼2 more athletics-related hours per week compared
to the 2010 GOALS study, along with a decrease of 2 h of
personal time (from 19.5 h per week in 2010 to 17.1 in 2015).
Furthermore, ∼66% of Division I and II and 50% of Division
III athletes reported spending as much or more time in their
practices during the off-season as during the competitive season
(DTHOMAS, 2013). These numbers show how important it
is for collegiate athletes to develop time management skills to
be successful in both academics and athletics. Overall, most
collegiate athletes have expressed a need to find time to enjoy
their college experience outside of athletic obligations (Paule
and
Gilson, 2010). Despite that, because of the increasing demand
for
excellence in academics and athletics, collegiate athletes’ free
time
with family and friends is often scarce (Paule and Gilson,
2010).
Consequently, trainers, coaches, and teammates will likely be
the
primary source of their weekly social interactivity.
Social interactions within their sport have also been found
to relate to factors that may impact an athlete’s perceived
stress. Interactions with coaches and trainers can be effective or
deleterious to an athlete. Effective coaching includes a coaching
style that allows for a boost of the athlete’s motivation, self-
esteem, and efficacy in addition to mitigating the effects of
anxiety. On the other hand, poor coaching (i.e., the opposite of
effective coaching) can have detrimental psychological effects
on
an athlete (Gearity and Murray, 2011). In a closer examination
of the concept of poor coaching practices, Gearity and Murray
(2011) interviewed athletes about their experiences of receiving
poor coaching. Following analysis of the interviews, the authors
identified the main themes of the “coach being uncaring and
unfair,” “practicing poor teaching inhibiting athlete’s mental
skills,” and “athlete coping.” They stated that inhibition of
an athlete’s mental skills and coping are associated with the
psychological well-being of an athlete. Also, poor coaching
may result in mental skills inhibition, distraction, insecurity,
and ultimately team division (Gearity and Murray, 2011). This
combination of factors may compound the negative impacts
of stress in athletes and might be especially important for in
injured athletes.
Injured athletes have previously been reported to have
elevated stress as a result of heightened worry about returning
to pre-competition status (Crossman, 1997), isolation from
teammates if the injury is over a long period of time
(Podlog and Eklund, 2007) and/or reduced mood or depressive
symptoms (Daly et al., 1995). In addition, athletes who
experience prolonged negative thoughts may be more likely to
have decreased rehabilitation attendance or adherence, worse
functional outcomes from rehabilitation (e.g., on measures of
proprioception, muscular endurance, and agility), and worse
post-injury performance (Brewer, 2012).
MONITORING CONSIDERATIONS
In addition to poor coaching, insufficient workload management
can hinder an athlete’s ability to recover and adapt to training,
leading to fatigue accumulation (Gabbett et al., 2017).
Excessive
fatigue can impair decision-making ability, coordination and
neuromuscular control, and ultimately result in overtraining
and injury (Soligard et al., 2016). For instance, central fatigue
was found to be a direct contributor to anterior cruciate
ligament injuries in soccer players (Mclean and Samorezov,
2009). Introducing monitoring tools may serve as a means to
reduce the detrimental effects of stress in collegiate athletes.
Recent research on relationships between athlete workloads,
injury, and performance has highlighted the benefits of athlete
monitoring (Drew and Finch, 2016; Jaspers et al., 2017).
Athlete monitoring is often assessed with the measuring and
management of workload associated with a combination of
sport-
related and non-sport-related stressors (Soligard et al., 2016).
An
effective workload management program should aim to detect
excessive fatigue, identify its causes, and constantly adapt rest,
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recovery, training, and competition loads respectively (Soligard
et al., 2016). The workload for each athlete is based off their
current levels of physical and psychological fatigue, wellness,
fitness, health, and recovery (Soligard et al., 2016).
Accumulation
of situational or physical stressors will likely result in day-
to-day fluctuations in the ability to move external loads and
strength train effectively (Fry and Kraemer, 1997). Periods of
increased academic stress may cause increased levels of fatigue,
which can be identified by using these monitoring tools, thereby
assisting the coaches with modulating the workload during these
specific periods. Coaches who plan to incorporate monitoring
and management strategies must have a clear understanding of
what they want to achieve from athletemonitoring (Gabbett et
al.,
2017; Thornton et al., 2019).
Monitoring External Loads
External load refers to the physical work (e.g., number of
sprints, weight lifted, distance traveled, etc.) completed by the
athlete during competition, training, and activities of daily
living
(Soligard et al., 2016). This type of load is independent of
the athlete’s individual characteristics (Wallace et al., 2009).
Monitoring external loading can aid in the designing of training
programs which mimic the external load demands of an athlete’s
sport, guide rehabilitation programs, and aid in the detection of
spikes in external load that may increase the risk of injury
(Clubb
and McGuigan, 2018).
The means of quantifying external load can involve metrics
as simple as pitch counts in baseball and softball (Fleisig and
Andrews, 2012; Shanley et al., 2012) or quantifying lifting
session training loads (e.g., sum value of weight lifted during
an exercise x number of repetitions × the number of sets).
Neuromuscular function testing is another more common way
of analyzing external load. This is typically done using such
measures such as the counter movement jump, squat jump,
or drop jump. A force platform can be used to measure a
myriad of outcomes (e.g., peak power, ground contact time,
time to take-off, reactive strength index, and jump height), or
simply measure jump height in a more traditional manner.
Jumping protocols, such as the countermovement jump, have
been adopted to examine the recovery of neuromuscular
function
after athletic competition with significant decreases for up to
72 h commonly reported (Andersson et al., 2008; Magalhães
et al., 2010; Twist and Highton, 2013). (Gathercole et al., 2015)
found reductions in 18 different neuromuscular variables in
collegiate athletes following a fatiguing protocol. The variables
of eccentric duration, concentric duration, total duration, time
to peak force/power, and flight time:contraction time ratio,
derived from a countermovement jump were deemed suitable
for detecting neuromuscular fatigue with the rise in the use of
technology for monitoring, certain sports have adopted specific
software that can aid in the monitoring of stress. For example,
power output can be measured using devices such as SRMTM
or PowerTapTM in cycling (Jobson et al., 2009). This data can
be analyzed to provide information such as average power or
normalized power. The power output can then be converted into
a Training Stress ScoreTM via commercially available software
(Marino, 2011). More sophisticated measures of external load
may involve the use of wearable technology devices such
as Global Positioning System (GPS) devices, accelerometers,
magnetometer, and gyroscope inertial sensors (Akenhead and
Nassis, 2016). These devices can quantify external load in
several
ways, such as duration of movement, total distance covered,
speed of movement, acceleration, and decelerations, as well as
sport specific movement such as number and height of jumps,
number of tackles, or breakaways, etc. (Akenhead and Nassis,
2016). The expansion of marketing of wearable devices has
been
substantial; however, there are questions of validity and
reliability
related to external load tracking limitations related to
proprietary
metrics, as well as the overall cost that should be considered
when
considering the adoption of such devices (Aughey et al., 2016;
Torres-Ronda and Schelling, 2017).
Monitoring Internal Loads
While external load may provide information about an athlete’s
performance capacity and work completed, it does not provide
clear evidence of how athletes are coping with and adapting to
the external load (Halson, 2014). This type of information
comes
from the monitoring of internal loads. The term internal load
refers to the individual physiological and psychological
response
to the external stress or load imposed (Wallace et al., 2009).
Internal load is influenced by a number of factors such as daily
life
stressors, the environment around the athlete, and coping ability
(Soligard et al., 2016). Indirect measures, such as the use of
heart
rate (HR) monitoring, and subjective measurements, such as
perceived effort (i.e., ratings of perceived exertion), are
examples
of internal load monitoring. Using subjective measurement
systems is a simple and practical method when dealing with
large
numbers of athletes (Saw et al., 2016; Nässi et al., 2017).
Subjective
reporting of training load (Rating of Perceived Exertion—RPE)
(Coyne et al., 2018), Session Rating of Perceived Exertion—
sRPE)
(Coyne et al., 2018), perceived stress and recovery (Recovery
Stress Questionnaire for Athletes—RESTQ-S), and
psychological
mood states (Profile of Mood States—POMS) have all been
found
to be a reliable indicator of training load (Robson-Ansley et al.,
2009; Saw et al., 2016) and only take a few moments to
complete.
In addition, subjective measures can be more responsive to
tracking changes or training responses in athletes than objective
measures (Saw et al., 2016).
Heart rate (HR) monitoring is a common intrinsic measure
of how the body is responding to stress. With training, the
reduction of resting HR is typically a clear indication of the
heart
becoming more efficient and not having to beat as frequently.
Alternately, increases of restingHR over time with a
continuation
of training may be an indicator of too much stress. Improper
nutrition, such as regular or ongoing suboptimal intakes of
vitamins or minerals, may result in increased ventilation and/or
increased heart rate (Lukaski, 2004). It has been suggested that
the additional stress may lead to parasympathetic hyperactivity,
leading to an increase in resting HR (Statler and DuBois, 2016).
This largely stems from research examining the sensitivity of
various HR derived metrics, such as resting HR, HR variability
(HRV), and HR recovery (HRR) to fluctuations in training load
(Borresen and Ian Lambert, 2009). HRR in athlete monitoring is
the rate of HR decline after the cessation of exercise. A
common
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measure of HHR is the use of a 2min step test followed by a
60 s HR measurement. The combination of the exercise (stress)
on the cardiovascular system and then its subsequent return
toward baseline has been used as an indicator of autonomic
function and training status in athletes (Daanen et al., 2012). In
collegiate athletes it was found that hydration status impacted
HRR following moderate to hard straining sessions (Ayotte and
Corcoran, 2018). Athletes who followed a prescription
hydration
plan performed better in the standing long jump, tracked
objects faster, and showed faster HRR vs. athletes who followed
their normal self-selected hydration plan (Ayotte and Corcoran,
2018). To date, HR monitoring and the various derivatives have
mainly been successful in detecting changes in training load and
performance in endurance athletes (Borresen and Ian Lambert,
2009; Lamberts et al., 2009; Thorpe et al., 2017). Although
heart
rate monitoring can provide additional physiological insight for
aerobic sessions or events, it thus far has not been found to be
an
accurate measurement for quantifying internal load during many
explosive, short duration anaerobic activities (Bosquet et al.,
2008).
Amultitude of studies have reported the reliability and validity
of using RPE and sRPE across a range of training modalities
(Foster, 1998; Impellizzeri et al., 2004; Sweet et al., 2004).
This
measure can be used to create a number of metrics such as
session load (sRPE× duration in minutes), daily load (sum of all
session loads for that day), weekly training load (sum of all
daily
training loads for entire week), monotony (standard deviation
of weekly training load), and strain (daily or weekly training
load×monotony) (Foster, 1998). Qualitative questionnaires that
monitor stress and fatigue have been well-established as tools
to use with athletes (see Table 1 for examples of commonly
used questionnaires in research). Using short daily wellness
questionnaires may allow coaches to generate a wellness score
which then can be adjusted based off of the stress the athlete
may be feeling to meet the daily load target (Foster, 1998;
Robson-Ansley et al., 2009). However, strength and
conditioning
coaches need to be mindful that these questionnaires may
require
sports psychologist or other licensed professional to examine
and provide the results. An alternative that may be better
suited for strength and conditioning professionals to use could
be to incorporate some of the themes of those questionnaires
into programing.
A Multifaceted Approach
Dissociation between external and internal load units may
be indicative of the state of fatigue of an athlete. Utilizing
a monitoring system in which the athlete is able to make
adjustments to their training loads in accordance with how they
are feeling in that moment can be a useful tool for assisting
the athlete in managing stress. Auto-regulation is a method of
programming that allows for adjustments based on the results
of one or more readiness tests. When implemented properly,
auto regulation enables the coach or athlete to optimize training
based on the athlete’s given readiness for training on a
particular
day, thereby aiming to avoid potential overtraining (Kraemer
and
Fleck, 2018). Several studies have found that using movement
velocity to designate resistance training intensities can result
in significant improvements in maximal strength and athletic
performance (Pareja-Blanco et al., 2014, 2017; Mann et al.,
2015).
Velocity based training allows the coach and athlete to view
real time feedback for the given lifts, thereby allowing them to
observe how the athlete is performing in that moment. If the
athlete is failing to meet the prescribed velocity or the velocity
drops greater than a predetermined amount between sets, then
this should signal the coach to investigate. If there is a higher
than normal amount of stress on that athlete for the day, that
could be a potential reason. This type of combination style
program of using a quantitative or objective measurement (s)
and a subjective measure of wellness (qualitative questionnaire)
has recently been reported to be an effective tool in monitoring
individuals apart of a team (Starling et al., 2019). The
subjective
measure in this study was the readiness to train questionnaire
(RTT-Q) and the objective measures were the HRR6min test
(specifically the HRR60s = recorded as decrease in HR in the
60 s after termination of the test) to assess autonomic function
and the standing long jump (SLJ) to measure neuromuscular
function. The findings found that, based on the absolute typical
error of measurement, the HRR60s and SLJ could detect
medium
and large changes in fatigue and readiness. The test took
roughly
8min for the entire team, which included a group consisting
of 24 college-age athletes. There are many other combinations
of monitoring variables and strategies that coaches and athletes
may utilize.
Data Analysis – How to Utilize the
Measures
Regardless of what type of monitoring tool a coach or athlete
may incorporate, it is essential to understand how to analyze
this
data. There are excellent resources available which discuss this
topic in great detail (Gabbett et al., 2017; Clubb and McGuigan,
2018; Thornton et al., 2019). This section will highlight two
main conclusions from these sources and briefly describe two of
the main statistical practices and concepts discussed. The use of
z-scores or modified z-scores has been proposed as a method
of detecting meaningful change in athlete data (Clubb and
McGuigan, 2018; Thornton et al., 2019). For different
monitoring
tools listed in Table 1, the following formula would be an
example of how to assess changes: (Athlete daily score—
Baseline
score)/Standard deviation of baseline. The baseline would likely
be based off an appropriate period such as the scores across 2
weeks during the preseason.
In sports and sports science, the use of a magnitude-based
inference (MBI) has been suggested as more appropriate and
easier to understand when examining meaningful changes
in athletic data, than null-hypothesis significance testing
(NHST) (Buchheit, 2014). Additional methods to assess
meaningful change that are similar to MBI are using standard
deviation, typical error, effect sizes, smallest worthwhile
change (SWC), and coefficient of variation (Thornton et al.,
2019). It should be noted that all of these methods have faced
criticism from sources such as statisticians. It is important
to understand that the testing methods, measurements, and
analysis should be based on the resources and intended goals
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TABLE 1 | Overview of common tool/measures used by
researchers to monitor training load.
Category of training load Variable examined Tests or Methods
of collection References
External load: defined as
the work completed by the
athlete, measured
independently of their
individual characteristics
(Wallace et al., 2009)
Power output Various devices Pyne and Martin, 2011
Neuromuscular function Jump tests—CMJ or SJ performance
Twist and Highton, 2013
Sprint performance Twist and Highton, 2013
Time-motion analysis GPS tracking Aughey, 2011; Halson,
2014
Movement pattern analysis via digital video Taylor et al., 2012;
Halson (2014)
Internal load: related to
physiological and
psychological stress
imposed (Wallace et al.,
2009)
Perception of effort Rating of Perceived Exertion (RPE)
Borresen and Ian Lambert, 2009
Session Rating of Perceived Exertion (sRPE) Foster, 1998
Heart rate measures Heart rate (HR) Hopkins, 1991
HR to RPE Martin and Andersen, 2000
HR recovery (HRR) Daanen et al., 2012
HR variability (HRV) Plews et al., 2013
Training Impulse (TRIMP) Morton et al., 1990; Pyne and
Martin, 2011
Qualitative questionnaires* Profile of Mood States (ROMS)
Morgan et al., 1987
Recovery Stress Questionnaires for Athletes (REST-Q) Kallus
and Kellmann, 2016
Daily Analysis of Life Demands for Athletes (DALDA) Rushall,
1990
Total Recovery Scale (TQR) Kenttä and Hassmén, 1998
* indicates variable/monitoring tool that is most appropriate for
use by a sport psychologist or licensed psychologist.
from use, which will differ from every group and individual.
Once identified, it is up to the practitioner to keep this
system the same, in order to collect data that can then be
examined to understand meaningful information for each setting
(Thornton et al., 2019).
Managing and Coping Strategies
Once the collegiate-athlete has been able to identify the need to
balance their stress levels, the athlete may then need to seek out
options for managing their stress. Coaches are be able to assist
them by sharing information on health and wellness resources
available for the students, both on and off campus. Another way
a coach can potentially support their athletes is by establishing
an
open-door policy, wherein the team members feel comfortable
approaching a member of the strength and conditioning staff in
order to seek out resources for coping with challenges related
to stress.
There are some basic skills that strength and conditioning
coaches can teach (while staying within their scope of practice).
Coaches can introduce their athletes to basic lifestyle concepts,
such as practicing deep breathing techniques, positive self-talk,
and developing healthy sleep habits (i.e., turning off their
mobile
devices 1 h before bed and aiming for 8 h of sleep each night,
etc.).
A survey of strength and conditioning practitioners by Radcliffe
et al. (2015) found that strategies used by practitioners included
a mix of cognitive and behavioral strategies, which was used as
justification for recommending practitioners find opportunities
to guide professional development toward awareness strategies.
Practitioners reported using a wide variety of psychological
skills
and strategies, which following survey analysis, highlighted a
significant emphasis on strategies that may influence athlete
self-
confidence and goal setting. Themes identified by Radcliffe et
al.
(2015) included confidence building, arousal management, and
skill acquisition. Additionally, similar lower level themes that
are connected (i.e., goal setting, increasing, or decreasing
arousal
intensities, self-talk, mental imagery) are all discussed in the
4th
edition of the NSCA Essentials of Strength and Conditioning
book (Haff et al., 2016). When the interventions aiming to
improve mental health expand from basic concepts to mental
training beyond a coach’s scope, it would be pertinent for the
coach to refer the collegiate-athlete to a sport psychology or
other
mental health consultant (Fogaca, 2019). Moreover, strength
and conditioning coaches may find themselves in a position to
become key players in facilitating management strategies for
collegiate athletes, thereby guiding the athlete in their quest to
learn how to best manage the mental and physical energy levels
required in the quest for overall optimal performance (Statler
and
DuBois, 2016).
CONCLUSION AND FUTURE DIRECTIONS
This review article has summarized some of the ways that
strength and conditioning professionals may be able to gain
a better understanding of the types of stressors encountered
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Lopes Dos Santos et al. Stress in College Athletes
by collegiate athletes, the impact these stressors may have on
athletic performance, and suggestions for assisting athletes with
developing effective coping strategies to reduce the potential
negative physiological and psychological impacts of stress. It
has been suggested that strategies learned in the context of
training may have a carry-over effect into other areas such as
competition. More education is needed in order for strength and
conditioning professionals to gain a greater understanding of
how to support their athletes with stress-management techniques
and resources. Some ways to disseminate further education
on stress-management tools for coaches to share with their
athletes may include professional development events, such as
conferences and clinics.
AUTHOR CONTRIBUTIONS
All of the authors have contributed to the development of the
manuscript both in writing and conceptual development.
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Conflict of Interest: The authors declare that the research was
conducted in the
absence of any commercial or financial relationships that could
be construed as a
potential conflict of interest.
The handling editor declared a past collaboration with one of
the authors RL.
Copyright © 2020 Lopes Dos Santos, Uftring, Stahl, Lockie,
Alvar, Mann and Dawes.
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https://www.frontiersin.org/journals/sports-and-active-
living#articlesStress in Academic and Athletic Performance in
Collegiate Athletes: A Narrative Review of Sources and
Monitoring StrategiesIntroductionStress and the Stress
ResponseMethodsLiterature Search/Data CollectionInclusion
CriteriaData AnalysisAcademic StressAthletic StressMonitoring
ConsiderationsMonitoring External LoadsMonitoring Internal
LoadsA Multifaceted ApproachData Analysis – How to Utilize
the MeasuresManaging and Coping StrategiesConclusion and
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Pathways Mental Health Psychiatric Patient Evaluatio.docx

  • 1. Pathways Mental Health Psychiatric Patient EvaluationInstructions Use the following case template to complete Week 2 Assignment 1. On page 5, assign DSM-5-TR and Updated ICD-10 codes to the services documented. You will add your narrative answers to the assignment questions to the bottom of this template and submit altogether as one document. Identifying Information Identification was verified by stating of their name and date of birth. Time spent for evaluation: 0900am-0957amChief Complaint “My other provider retired. I don’t think I’m doing so well.”HPI 25 yo Russian female evaluated for psychiatric evaluation referred from her retiring practitioner for PTSD, ADHD, Stimulant Use Disorder, in remission. She is currently prescribed fluoxetine 20mg po daily for PTSD, atomoxetine 80mg po daily for ADHD. Today, client denied symptoms of depression, denied anergia, anhedonia, amotivation, no anxiety, denied frequent worry, reports feeling restlessness, no reported panic symptoms, no reported obsessive/compulsive behaviors. Client denies active SI/HI ideations, plans or intent. There is no evidence of psychosis or delusional thinking. Client denied past episodes of hypomania, hyperactivity, erratic/excessive spending, involvement in dangerous activities, self-inflated ego, grandiosity, or promiscuity. Client reports increased irritability
  • 2. and easily frustrated, loses things easily, makes mistakes, hard time focusing and concentrating, affecting her job. Has low frustration tolerance, sleeping 5–6 hrs/24hrs reports nightmares of previous rape, isolates, fearful to go outside, has missed several days of work, appetite decreased. She has somatic concerns with GI upset and headaches. Client denied any current binging/purging behaviors, denied withholding food from self or engaging in anorexic behaviors. No self-mutilation behaviors. Diagnostic Screening Results Screen of symptoms in the past 2 weeks: PHQ 9 = 0 with symptoms rated as no difficulty in functioning Interpretation of Total Score Total Score Depression Severity 1-4 Minimal depression 5-9 Mild depression 10-14 Moderate depression 15-19 Moderately severe depression 20-27 Severe depression GAD 7 = 2 with symptoms rated as no difficulty in functioning Interpreting the Total Score: Total Score Interpretation ≥10 Possible diagnosis of GAD; confirm by further evaluation 5 Mild Anxiety 10 Moderate anxiety 15 Severe anxiety MDQ screen negative PCL-5 Screen 32Past Psychiatric and Substance Use Treatment Entered mental health system when she was age 19 after raped by a stranger during a house burglary. Previous Psychiatric Hospitalizations: denied Previous Detox/Residential treatments: one for abuse of stimulants and cocaine in 2015 Previous psychotropic medication trials: sertraline (became suicidal), trazodone (worsened nightmares), bupropion (became suicidal), Adderall (began abusing)
  • 3. Previous mental health diagnosis per client/medical record: GAD, Unspecified Trauma, PTSD, Stimulant use disorder, ADHD confirmed by school recordsSubstance Use History Have you used/abused any of the following (include frequency/amt/last use): Substance Y/N Frequency/Last Use Tobacco products Y ½ ETOH Y last drink 2 weeks ago, reports drinks 1-2 times monthly one drink socially Cannabis N Cocaine Y last use 2015 Prescription stimulants Y last use 2015 Methamphetamine N Inhalants N Sedative/sleeping pills N Hallucinogens N Street Opioids N Prescription opioids N Other: specify (spice, K2, bath salts, etc.) Y reports one- time ecstasy use in 2015 Any history of substance related: Blackouts: + Tremors: - DUI: - D/T's: - Seizures: - Longest sobriety reported since 2015—stayed sober maintaining sponsor, sober friends, and meetingsPsychosocial History Client was raised by adoptive parents since age 6; from Russian orphanage. She has unknown siblings. She is single; has no children.
  • 4. Employed at local tanning bed salon Education: High School Diploma Denied current legal issues.Suicide / HOmicide Risk Assessment RISK FACTORS FOR SUICIDE: Suicidal Ideas or plans - no Suicide gestures in past - no Psychiatric diagnosis - yes Physical Illness (chronic, medical) - no Childhood trauma - yes Cognition not intact - no Support system - yes Unemployment - no Stressful life events - yes Physical abuse - yes Sexual abuse - yes Family history of suicide - unknown Family history of mental illness - unknown Hopelessness - no Gender - female Marital status - single White race Access to means Substance abuse - in remission PROTECTIVE FACTORS FOR SUICIDE: Absence of psychosis - yes Access to adequate health care - yes Advice & help seeking - yes Resourcefulness/Survival skills - yes Children - no Sense of responsibility - yes Pregnancy - no; last menses one week ago, has Norplant Spirituality - yes Life satisfaction - “fair amount”
  • 5. Positive coping skills - yes Positive social support - yes Positive therapeutic relationship - yes Future oriented - yes Suicide Inquiry: Denies active suicidal ideations, intentions, or plans. Denies recent self-harm behavior. Talks futuristically. Denied history of suicidal/homicidal ideation/gestures; denied history of self-mutilation behaviors Global Suicide Risk Assessment: The client is found to be at low risk of suicide or violence, however, risk of lethality increased under context of drugs/alcohol. No required SAFETY PLAN related to low riskMental Status Examination She is a 25 yo Russian female who looks her stated age. She is cooperative with examiner. She is neatly groomed and clean, dressed appropriately. There is mild psychomotor restlessness. Her speech is clear, coherent, normal in volume and tone, has strong cultural accent. Her thought process is ruminative. There is no evidence of looseness of association or flight of ideas. Her mood is anxious, mildly irritable, and her affect appropriate to her mood. She was smiling at times in an appropriate manner. She denies any auditory or visual hallucinations. There is no evidence of any delusional thinking. She denies any current suicidal or homicidal ideation. Cognitively, She is alert and oriented to all spheres. Her recent and remote memory is intact. Her concentration is fair. Her insight is good. Clinical Impression Client is a 25 yo Russian female who presents with history of treatment for PTSD, ADHD, Stimulant use Disorder, in remission. Moods are anxious and irritable. She has ongoing reported
  • 6. symptoms of re-experiencing, avoidance, and hyperarousal of her past trauma experiences; ongoing subsyndromal symptoms related to her past ADHD diagnosis and exacerbated by her PTSD diagnosis. She denied vegetative symptoms of depression, no evident mania/hypomania, no psychosis, denied anxiety symptoms. Denied current cravings for drugs/alcohol, exhibits no withdrawal symptoms, has somatic concerns of GI upset and headaches. At the time of disposition, the client adamantly denies SI/HI ideations, plans or intent and has the ability to determine right from wrong, and can anticipate the potential consequences of behaviors and actions. She is a low risk for self-harm based on her current clinical presentation and her risk and protective factors. Diagnostic Impression [Student to provide DSM-5-TR and Updated ICD-10 coding] Double click inside this text box to add/edit text. Delete placeholder text when you add your answers.Treatment Plan Medication: Increase fluoxetine 40mg po daily for PTSD #30 1 RF Continue with atomoxetine 80mg po daily for ADHD. #30 1 RF Instructed to call and report any adverse reactions. Future Plan: monitor for decrease re-experiencing, hyperarousal, and avoidance symptoms; monitor for improved concentration, less mistakes, less forgetful Education: Risks and benefits of medications are discussed including non-treatment. Potential side effects of medications discussed. Verbal informed consent obtained. Not to drive or operate dangerous machinery if feeling sedated.
  • 7. Not to stop medication abruptly without discussing with providers. Discussed risks of mixing medications with OTC drugs, herbal, alcohol/illegal drugs. Instructed to avoid this practice. Praised and Encouraged ongoing abstinence. Maintain support system, sponsors, and meetings. Discussed how drugs/ETOH affects mental health, physical health, sleep architecture. Patient was educated about therapy and services of the MHC including emergent care. Referral was sent via email to therapy team for PET treatment. Patient has emergency numbers: Emergency Services 911, the national Crisis Line 800-273-TALK, the MHC Crisis Clinic. Patient was instructed to go to nearest ER or call 911 if they become actively suicidal and/or homicidal. Time allowed for questions and answers provided. Provided supportive listening. Patient appeared to understand discussion and appears to have capacity for decision making via verbal conversation. RTC in 30 days Follow up with PCP for GI upset and headaches, reviewed PCP history and physical dated one week ago and include lab results Patient is amenable with this plan and agrees to follow treatment regimen as discussed. Narrative Answers [In 1-2 pages, address the following:
  • 8. · Explain what pertinent information, generally, is required in documentation to support DSM-5-TR and Updated ICD-10 coding. · Explain what pertinent documentation is missing from the case scenario, and what other information would be helpful to narrow your coding and billing options. · Finally, explain how to improve documentation to support coding and billing for maximum reimbursement.] Add your answers here. Delete instructions and placeholder text when you add your answers. References [Add APA-formatted citations for any sources you referenced Delete instructions and placeholder text when you add your citations. Page | 2 Walden University, LLC rev 6.2022 image1.png image2.svg .MsftOfcThm_Accent1_lumMod_40_lumOff_60_Fill { fill:#B1D1E3; } image3.png
  • 9. image4.svg .MsftOfcThm_Accent1_lumMod_60_lumOff_40_Fill { fill:#8ABAD4; } REVIEW published: 08 May 2020 doi: 10.3389/fspor.2020.00042 Frontiers in Sports and Active Living | www.frontiersin.org 1 May 2020 | Volume 2 | Article 42 Edited by: Sophia Nimphius, Edith Cowan University, Australia Reviewed by: Chris John Bishop, Middlesex University, United Kingdom Claudia Reardon, University of Wisconsin-Madison, United States
  • 10. *Correspondence: J. Bryan Mann [email protected] Specialty section: This article was submitted to Elite Sports and Performance Enhancement, a section of the journal Frontiers in Sports and Active Living Received: 05 October 2019 Accepted: 30 March 2020 Published: 08 May 2020 Citation: Lopes Dos Santos M, Uftring M, Stahl CA, Lockie RG, Alvar B, Mann JB and Dawes JJ (2020) Stress in Academic and Athletic Performance in Collegiate Athletes: A Narrative
  • 11. Review of Sources and Monitoring Strategies. Front. Sports Act. Living 2:42. doi: 10.3389/fspor.2020.00042 Stress in Academic and Athletic Performance in Collegiate Athletes: A Narrative Review of Sources and Monitoring Strategies Marcel Lopes Dos Santos 1, Melissa Uftring 1, Cody A. Stahl 1, Robert G. Lockie 2, Brent Alvar 3, J. Bryan Mann 4* and J. Jay Dawes 1 1 School of Kinesiology, Applied Health and Recreation, Oklahoma State University, Stillwater, OK, United States, 2Department of Kinesiology, California State University, Fullerton, CA, United States, 3Department of Kinesiology, Point Loma Nazarene University, San Diego, CA, United States, 4Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States College students are required to manage a variety of stressors related to academic, social, and financial commitments. In addition to the burdens facing most college
  • 12. students, collegiate athletes must devote a substantial amount of time to improving their sporting abilities. The strength and conditioning professional sees the athlete on nearly a daily basis and is able to recognize the changes in performance and behavior an athlete may exhibit as a result of these stressors. As such, the strength and conditioning professional may serve an integral role in the monitoring of these stressors and may be able to alter training programs to improve both performance andwellness. The purpose of this paper is to discuss stressors experienced by collegiate athletes, developing an early detection system through monitoring techniques that identify the detrimental effects of stress, and discuss appropriate stress management strategies for this population. Keywords: stress, load management, academic stress, stress management, injury INTRODUCTION The college years are a period of time when young adults experience a significant amount of change and a variety of novel challenges. Academic performance, social demands, adjusting to life away
  • 13. from home, and financial challenges are just a few of the burdens college students must confront (Humphrey et al., 2000; Paule and Gilson, 2010; Aquilina, 2013). In addition to these stressors, collegiate athletes are required to spend a substantial amount of time participating in activities related to their sport, such as attending practices and training sessions, team meetings, travel, and competitions (Humphrey et al., 2000; López de Subijana et al., 2015; Davis et al., 2019; Hyatt and Kavazis, 2019). These commitments, in addition to the normal stress associated with college life, may increase a collegiate-athlete’s risk of experiencing both physical and mental issues (Li et al., 2017; Moreland et al., 2018) that may affect their overall health and wellness. For these reasons, it is essential that coaches understand the types of stressors collegiate athletes face in order to help them manage the potentially deleterious effects stress may have on athletic and academic performance. Strength and conditioning coaches are allied health care professionals whose primary job is to enhance fitness of individuals for the purpose of improving athletic performance (Massey et al., 2002, 2004, 2009). As such, many universities and colleges hire strength https://www.frontiersin.org/journals/sports-and-active-living https://www.frontiersin.org/journals/sports-and-active- living#editorial-board https://www.frontiersin.org/journals/sports-and-active- living#editorial-board https://www.frontiersin.org/journals/sports-and-active- living#editorial-board https://www.frontiersin.org/journals/sports-and-active-
  • 14. living#editorial-board https://doi.org/10.3389/fspor.2020.00042 http://crossmark.crossref.org/dialog/?doi=10.3389/fspor.2020.0 0042&domain=pdf&date_stamp=2020-05-08 https://www.frontiersin.org/journals/sports-and-active-living https://www.frontiersin.org https://www.frontiersin.org/journals/sports-and-active- living#articles https://creativecommons.org/licenses/by/4.0/ mailto:[email protected] https://doi.org/10.3389/fspor.2020.00042 https://www.frontiersin.org/articles/10.3389/fspor.2020.00042/f ull http://loop.frontiersin.org/people/822589/overview http://loop.frontiersin.org/people/879261/overview http://loop.frontiersin.org/people/822591/overview http://loop.frontiersin.org/people/750861/overview http://loop.frontiersin.org/people/879373/overview Lopes Dos Santos et al. Stress in College Athletes and conditioning coaches as part of their athletic staff to help athletes maximize their physical potential (Massey et al., 2002, 2004, 2009). Strength and conditioning coaches strive to increase athletic performance by the systematic application of physical stress to the body via resistance training, and other forms of exercise, to yield a positive adaptation response (Massey et al., 2002, 2004, 2009). For this reason, they need to understand and to learn how to manage athletes’ stress. Additionally, based on the cumulative nature of stress, it is important that both mental and emotional stressors are also considered in programming. It is imperative that strength and conditioning coaches are aware of the multitude of stressors collegiate athletes encounter, in order
  • 15. to incorporate illness and injury risk management education into their training programs (Radcliffe et al., 2015; Ivarsson et al., 2017). Based on the large number of contact hours strength and conditioning coaches spend with their athletes, they are in an optimal position to assist athletes with developing effective coping strategies to manage stress. By doing so, strength and conditioning coaches may be able to help reach the overarching goal of improving the health, wellness, fitness, and performance of the athletes they coach. The purpose of this review article is to provide the strength and conditioning professional with a foundational understanding of the types of stressors collegiate athletes may experience, and how these stressors may impact mental health and athletic performance. Suggestions for assisting athletes with developing effective coping strategies to reduce potential physiological and psychological impacts of stress will also be provided. Stress and the Stress Response In its most simplistic definition, stress can be described as a state of physical and psychological activation in response to external demands that exceed one’s ability to cope and requires a person to adapt or change behavior. As such, both cognitive or environmental events that trigger stress are called stressors (Statler and DuBois, 2016). Stressors can be acute or chronic based on the duration of activation. Acute stressors may be defined as a stressful situation that occurs suddenly and results in physiological arousal (e.g., increase in hormonal levels, blood flow, cardiac output, blood sugar levels, pupil and airway dilation, etc.) (Selye, 1976). Once the situation is normalized, a cascade of hormonal reactions occurs to help the body return to a resting state (i.e., homeostasis). However, when acute stressors
  • 16. become chronic in nature, they may increase an individual’s risk of developing anxiety, depression, or metabolic disorders (Selye, 1976). Moreover, the literature has shown that cumulative stress is correlated with an increased susceptibility to illness and injury (Szivak and Kraemer, 2015; Mann et al., 2016; Hamlin et al., 2019). The impact of stress is individualistic and subjective by nature (Williams and Andersen, 1998; Ivarsson et al., 2017). Additionally, the manner in which athletes respond to a situational or environmental stressor is often determined by their individual perception of the event (Gould and Udry, 1994; Williams and Andersen, 1998; Ivarsson et al., 2017). In this regard, the athlete’s perception can either be positive (eustress) or negative (distress). Even though they both cause physiological arousal, eustress also generates positive mental energy whereas distress generates anxiety (Statler and DuBois, 2016). Therefore, it is essential that an athlete has the tools and ability to cope with these stressors in order to have the capacity to manage both acute and chronic stress. As such, it is important to understand the types of stressors collegiate athletes are confronted with and how these stressors impact an athlete’s performance, both athletically and academically. METHODS Literature Search/Data Collection The articles included in this review were identified via online databases PubMed, MEDLINE, and ISI Web of Knowledge
  • 17. from October 15th 2019 through January 15th 2020. The search strategy combined the keywords “academic stress,” “athletic stress,” “stress,” “stressor,” “college athletes,” “student athletes,” “collegiate athletes,” “injury,” “training,” “monitoring.” Duplicated articles were then removed. After reading the titles and abstracts, all articles that met the inclusion criteria were considered eligible for inclusion in the review. Subsequently, all eligible articles were read in their entirety and were either included or removed from the present review. Inclusion Criteria The studies included met all the following criteria: (i) published in English-language journals; (ii) targeted college athletes; (iii) publication was either an original research paper or a literature review; (iv) allowed the extraction of data for analysis. Data Analysis Relevant data regarding participant characteristics (i.e., gender, academic status, sports) and study characteristics were extracted. Articles were analyzed and divided into two separate sections based on their specific topics: Academic Stress and Athletic Stress. Then, strategies for monitoring and workload management are discussed in the final section. ACADEMIC STRESS Fundamentally, collegiate athletes have two major roles they must balance as part of their commitment to a university: being a college student and an athlete. Academic performance is a significant source of stress for most college students (Aquilina, 2013; López de Subijana et al., 2015; de Brandt et al., 2018; Davis et al., 2019). This stress may be further compounded among collegiate athletes based on their need to be successful in
  • 18. the classroom, while simultaneously excelling in their respective sport (Aquilina, 2013; López de Subijana et al., 2015; Huml et al., 2016; Hamlin et al., 2019). Davis et al. (2019) conducted surveys on 173 elite junior alpine skiers and reported significant moderate to strong correlations between perceived stress and several variables including depressed mood (r = 0.591), sleep disturbance (r = 0.459), fatigue (r = 0.457), performance demands (r = 0.523), and goals and development (r = 0.544). Academic requirements were the highest scoring source of stress of all variables and was most strongly correlated with perceived Frontiers in Sports and Active Living | www.frontiersin.org 2 May 2020 | Volume 2 | Article 42 https://www.frontiersin.org/journals/sports-and-active-living https://www.frontiersin.org https://www.frontiersin.org/journals/sports-and-active- living#articles Lopes Dos Santos et al. Stress in College Athletes stress (r = 0.467). Interestingly, it was not academic rigor that was viewed by the athletes as the largest source of direct stress; rather, the athletes surveyed reported time management as being their biggest challenge related to academic performance (Davis et al., 2019). This further corroborates the findings of Hamlin et al. (2019). The investigators reported that during periods of the academic year in which levels of perceived academic stress were at their highest, students had trouble managing sport practices and studying. These stressors were also associated with a decrease in energy levels and overall sleep quality. These
  • 19. factors may significantly increase the collegiate athlete’s susceptibility to illness and injury (Hamlin et al., 2019). For this reason, coaches should be aware of and sensitive to the stressors athletes experience as part of the cyclical nature of the academic year and attempt to help athletes find solutions to balancing athletic and academic demands. According to Aquilina (2013), collegiate athletes tend to be more committed to sports development and may view their academic career as a contingency plan to their athletic career, rather than a source of personal development. As a result, collegiate athletes often, but certainly not always, prioritize athletic participation over their academic responsibilities (Miller and Kerr, 2002; Cosh and Tully, 2014, 2015). Nonetheless, scholarships are usually predicated on both athletic and academic performance. For instance, the National Collegiate Athletic Association (NCAA) requires collegiate athletes to achieve and maintain a certain grade point average (GPA). Furthermore, they are also often required to also uphold a certain GPA to maintain an athletic scholarship. The pressure to maintain both high levels of academic and athletic performancemay increase the likelihood of triggeringmental health issues (i.e., anxiety and depression) (Li et al., 2017; Moreland et al., 2018). Mental health issues are a significant concern among college students. There has been an increased emphasis placed on the mental health of collegiate athletes in recent years (Petrie et al.,
  • 20. 2014; Li et al., 2017, 2019; Reardon et al., 2019). Based on the 2019 National College Health Assessment survey from the American College Health Association (ACHA) consisting of 67,972 participants, 27.8% of college students reported anxiety, and 20.2% reported experiencing depression which negatively affected their academic performance (American College Health Association American College Health Association-National College Health Assessment II, 2019). Approximately 65.7% (50.7% males and 71.8% females) reported feeling overwhelming anxiety in the past 12months, and 45.1% (37.1%males and 47.6% females) reported feeling so depressed that it was difficult for them to function. However, only 24.3% (13% males and 28.4% females) reported being diagnosed and treated by a professional in the past 12 months. Collegiate athletes are not immune to these types of issues. According to information presented by the NCAA, many certified athletic trainers anecdotally state that anxiety is an issue affecting the collegiate-athlete population (NCAA, 2014). However, despite the fact that collegiate athletes are exposed to numerous stressors, they are less likely to seek help at a university counseling center than non-athletes (NCAA, 2014), which could be related to stigmas that surround mental health services (NCAA, 2014; Kaier et al., 2015; Egan, 2019). This not only has significant implications related to their psychological well-being, but also their physiological health, and consequently their performance. For instance, in a study by Li et al. (2017) it was found that NCAA Division I athletes who reported preseason anxiety symptoms had a 2.3 times greater injury incidence rate compared to athletes who did not report. This same study discovered that male athletes who reported preseason anxiety and depression had a 2.1 times greater
  • 21. injury incidence, compared to male athletes who did not report symptoms of anxiety and depression. (Lavallée and Flint, 1996) also reported a correlation between anxiety and both injury frequency and severity among college football players (r = 0.43 and r = 0.44, respectively). In their study, athletes reporting high tension/anxiety had a higher rate of injury. It has been suggested that the occurrence of stress and anxiety may cause physiological responses, such as an increase in muscle tension, physical fatigue, and a decrease in neurocognitive and perception processes that can lead to physical injuries (Ivarsson et al., 2017). For this reason, it is reasonable to consider that academic stressors may potentiate effects of stress and result in injury and illness in collegiate athletes. Periods of more intense academic stress increase the susceptibility to illness or injury (Mann et al., 2016; Hamlin et al., 2019; Li et al., 2019). For example, Hamlin et al. (2019) investigated levels of perceived stress, training loads, injury, and illness incidence in 182 collegiate athletes for the period of one academic year. The highest levels of stress and incidence of illness arise during the examination weeks occurring within the competitive season. In addition, the authors also reported the odds ratio, which is the occurrence of the outcome of interest (i.e., injury), based off the given exposure to the variables of interest (i.e., perceived mood, sleep duration, increased academic stress, and energy levels). Based on a logistic regression, they found that each of the four variables (i.e., mood, energy, sleep duration, and academic stress) was related to the collegiate athletes’ likelihood to incur injuries. In summary, decreased levels of perceived mood (odds ratio of 0.89, 0.85–0.0.94 CI)
  • 22. and sleep duration (odds ratio of 0.94, 0.91–0.97 CI), and increased academic stress (odds ratio of 0.91, 0.88–0.94 CI) and energy levels (odds ratio of 1.07, 1.01–1.14 CI), were able to predict injury in these athletes. This corroborates Mann et al. (2016) who foundNCAADivision I football athletes at a Bowl Championship Subdivision university were more likely to become ill or injured during an academically stressful period (i.e., midterm exams or other common test weeks) than during a non-testing week (odds ratio of 1.78 for high academic stress). The athletes were also less likely to get injured during training camp (odds ratio of 3.65 for training camp). Freshmen collegiate athletes may be especially more susceptible to mental health issues than older students. Their transition includes not only the academic environment with its requirements and expectations, but also the adaptation to working with a new coach and teammates. In this regard, Yang et al. (2007) found an increase in the likelihood of depression that freshmen athletes experienced, as these freshmen were 3.27 times more likely to experience depression than their older teammates. While some stressors are recurrent and inherent in academic life (e.g., attending Frontiers in Sports and Active Living | www.frontiersin.org 3 May 2020 | Volume 2 | Article 42 https://www.frontiersin.org/journals/sports-and-active-living https://www.frontiersin.org https://www.frontiersin.org/journals/sports-and-active- living#articles Lopes Dos Santos et al. Stress in College Athletes classes, homework, etc.), others are more situational (e.g., exams,
  • 23. midterms, projects) and may be anticipated by the strength and conditioning coach. ATHLETIC STRESS The domain of athletics can expose collegiate athletes to additional stressors that are specific to their cohort (e.g., sport- specific, team vs. individual sport) (Aquilina, 2013). Time spent training (e.g., physical conditioning and sports practice), competition schedules (e.g., travel time, missing class), dealing with injuries (e.g., physical therapy/rehabilitation, etc.), sport- specific social support (e.g., teammates, coaches) and playing status (e.g., starting, non-starter, being benched, etc.) are just a few of the additional challenges collegiate athletes must confront relative to their dual role of being a student and an athlete (Maloney and McCormick, 1993; Scott et al., 2008; Etzel, 2009; Fogaca, 2019). Collegiate athletes who view the demands of stressors from academics and sports as a positive challenge (i.e., an individual’s self-confidence or belief in oneself to accomplish the task outweighs any anxiety or emotional worry that is felt) may potentially increase learning capacity and competency (NCAA, 2014). However, when these demands are perceived as exceeding the athlete’s capacity, this stress can be detrimental to the student’s mental and physical health as well as to sport performance (Ivarsson et al., 2017; Li et al., 2017). As previously stated, time management has been shown to be a challenge to collegiate athletes. The NCAA rules state that collegiate athletes may only engage in required athletic activities for 4 h per day and 20 h/week during in-season and 8 h/week during off-season throughout the academic year. Although these rules have been clearly outlined, the most recent NCAA GOALS (2016) study reported alarming numbers
  • 24. regarding time commitment to athletic-related activities. Data from over 21,000 collegiate athletes from 600 schools across Divisions I, II, and III were included in this study. Although a breakdown of time commitments was not provided, collegiate athletes reported dedicating up to 34 h per week to athletics (e.g., practices, weight training, meetings with coaches, tactical training, competitions, etc.), in addition to spending between 38.5 and 40 h per week working on academic-related tasks. This report also showed a notable trend related to athletes spending an increase of ∼2 more athletics-related hours per week compared to the 2010 GOALS study, along with a decrease of 2 h of personal time (from 19.5 h per week in 2010 to 17.1 in 2015). Furthermore, ∼66% of Division I and II and 50% of Division III athletes reported spending as much or more time in their practices during the off-season as during the competitive season (DTHOMAS, 2013). These numbers show how important it is for collegiate athletes to develop time management skills to be successful in both academics and athletics. Overall, most collegiate athletes have expressed a need to find time to enjoy their college experience outside of athletic obligations (Paule and Gilson, 2010). Despite that, because of the increasing demand for excellence in academics and athletics, collegiate athletes’ free time with family and friends is often scarce (Paule and Gilson, 2010). Consequently, trainers, coaches, and teammates will likely be the primary source of their weekly social interactivity. Social interactions within their sport have also been found to relate to factors that may impact an athlete’s perceived stress. Interactions with coaches and trainers can be effective or
  • 25. deleterious to an athlete. Effective coaching includes a coaching style that allows for a boost of the athlete’s motivation, self- esteem, and efficacy in addition to mitigating the effects of anxiety. On the other hand, poor coaching (i.e., the opposite of effective coaching) can have detrimental psychological effects on an athlete (Gearity and Murray, 2011). In a closer examination of the concept of poor coaching practices, Gearity and Murray (2011) interviewed athletes about their experiences of receiving poor coaching. Following analysis of the interviews, the authors identified the main themes of the “coach being uncaring and unfair,” “practicing poor teaching inhibiting athlete’s mental skills,” and “athlete coping.” They stated that inhibition of an athlete’s mental skills and coping are associated with the psychological well-being of an athlete. Also, poor coaching may result in mental skills inhibition, distraction, insecurity, and ultimately team division (Gearity and Murray, 2011). This combination of factors may compound the negative impacts of stress in athletes and might be especially important for in injured athletes. Injured athletes have previously been reported to have elevated stress as a result of heightened worry about returning to pre-competition status (Crossman, 1997), isolation from teammates if the injury is over a long period of time (Podlog and Eklund, 2007) and/or reduced mood or depressive symptoms (Daly et al., 1995). In addition, athletes who experience prolonged negative thoughts may be more likely to have decreased rehabilitation attendance or adherence, worse functional outcomes from rehabilitation (e.g., on measures of proprioception, muscular endurance, and agility), and worse post-injury performance (Brewer, 2012). MONITORING CONSIDERATIONS In addition to poor coaching, insufficient workload management
  • 26. can hinder an athlete’s ability to recover and adapt to training, leading to fatigue accumulation (Gabbett et al., 2017). Excessive fatigue can impair decision-making ability, coordination and neuromuscular control, and ultimately result in overtraining and injury (Soligard et al., 2016). For instance, central fatigue was found to be a direct contributor to anterior cruciate ligament injuries in soccer players (Mclean and Samorezov, 2009). Introducing monitoring tools may serve as a means to reduce the detrimental effects of stress in collegiate athletes. Recent research on relationships between athlete workloads, injury, and performance has highlighted the benefits of athlete monitoring (Drew and Finch, 2016; Jaspers et al., 2017). Athlete monitoring is often assessed with the measuring and management of workload associated with a combination of sport- related and non-sport-related stressors (Soligard et al., 2016). An effective workload management program should aim to detect excessive fatigue, identify its causes, and constantly adapt rest, Frontiers in Sports and Active Living | www.frontiersin.org 4 May 2020 | Volume 2 | Article 42 https://www.frontiersin.org/journals/sports-and-active-living https://www.frontiersin.org https://www.frontiersin.org/journals/sports-and-active- living#articles Lopes Dos Santos et al. Stress in College Athletes recovery, training, and competition loads respectively (Soligard et al., 2016). The workload for each athlete is based off their current levels of physical and psychological fatigue, wellness,
  • 27. fitness, health, and recovery (Soligard et al., 2016). Accumulation of situational or physical stressors will likely result in day- to-day fluctuations in the ability to move external loads and strength train effectively (Fry and Kraemer, 1997). Periods of increased academic stress may cause increased levels of fatigue, which can be identified by using these monitoring tools, thereby assisting the coaches with modulating the workload during these specific periods. Coaches who plan to incorporate monitoring and management strategies must have a clear understanding of what they want to achieve from athletemonitoring (Gabbett et al., 2017; Thornton et al., 2019). Monitoring External Loads External load refers to the physical work (e.g., number of sprints, weight lifted, distance traveled, etc.) completed by the athlete during competition, training, and activities of daily living (Soligard et al., 2016). This type of load is independent of the athlete’s individual characteristics (Wallace et al., 2009). Monitoring external loading can aid in the designing of training programs which mimic the external load demands of an athlete’s sport, guide rehabilitation programs, and aid in the detection of spikes in external load that may increase the risk of injury (Clubb and McGuigan, 2018). The means of quantifying external load can involve metrics as simple as pitch counts in baseball and softball (Fleisig and Andrews, 2012; Shanley et al., 2012) or quantifying lifting session training loads (e.g., sum value of weight lifted during an exercise x number of repetitions × the number of sets). Neuromuscular function testing is another more common way of analyzing external load. This is typically done using such measures such as the counter movement jump, squat jump,
  • 28. or drop jump. A force platform can be used to measure a myriad of outcomes (e.g., peak power, ground contact time, time to take-off, reactive strength index, and jump height), or simply measure jump height in a more traditional manner. Jumping protocols, such as the countermovement jump, have been adopted to examine the recovery of neuromuscular function after athletic competition with significant decreases for up to 72 h commonly reported (Andersson et al., 2008; Magalhães et al., 2010; Twist and Highton, 2013). (Gathercole et al., 2015) found reductions in 18 different neuromuscular variables in collegiate athletes following a fatiguing protocol. The variables of eccentric duration, concentric duration, total duration, time to peak force/power, and flight time:contraction time ratio, derived from a countermovement jump were deemed suitable for detecting neuromuscular fatigue with the rise in the use of technology for monitoring, certain sports have adopted specific software that can aid in the monitoring of stress. For example, power output can be measured using devices such as SRMTM or PowerTapTM in cycling (Jobson et al., 2009). This data can be analyzed to provide information such as average power or normalized power. The power output can then be converted into a Training Stress ScoreTM via commercially available software (Marino, 2011). More sophisticated measures of external load may involve the use of wearable technology devices such as Global Positioning System (GPS) devices, accelerometers, magnetometer, and gyroscope inertial sensors (Akenhead and Nassis, 2016). These devices can quantify external load in several ways, such as duration of movement, total distance covered, speed of movement, acceleration, and decelerations, as well as sport specific movement such as number and height of jumps, number of tackles, or breakaways, etc. (Akenhead and Nassis, 2016). The expansion of marketing of wearable devices has
  • 29. been substantial; however, there are questions of validity and reliability related to external load tracking limitations related to proprietary metrics, as well as the overall cost that should be considered when considering the adoption of such devices (Aughey et al., 2016; Torres-Ronda and Schelling, 2017). Monitoring Internal Loads While external load may provide information about an athlete’s performance capacity and work completed, it does not provide clear evidence of how athletes are coping with and adapting to the external load (Halson, 2014). This type of information comes from the monitoring of internal loads. The term internal load refers to the individual physiological and psychological response to the external stress or load imposed (Wallace et al., 2009). Internal load is influenced by a number of factors such as daily life stressors, the environment around the athlete, and coping ability (Soligard et al., 2016). Indirect measures, such as the use of heart rate (HR) monitoring, and subjective measurements, such as perceived effort (i.e., ratings of perceived exertion), are examples of internal load monitoring. Using subjective measurement systems is a simple and practical method when dealing with large numbers of athletes (Saw et al., 2016; Nässi et al., 2017). Subjective reporting of training load (Rating of Perceived Exertion—RPE) (Coyne et al., 2018), Session Rating of Perceived Exertion— sRPE)
  • 30. (Coyne et al., 2018), perceived stress and recovery (Recovery Stress Questionnaire for Athletes—RESTQ-S), and psychological mood states (Profile of Mood States—POMS) have all been found to be a reliable indicator of training load (Robson-Ansley et al., 2009; Saw et al., 2016) and only take a few moments to complete. In addition, subjective measures can be more responsive to tracking changes or training responses in athletes than objective measures (Saw et al., 2016). Heart rate (HR) monitoring is a common intrinsic measure of how the body is responding to stress. With training, the reduction of resting HR is typically a clear indication of the heart becoming more efficient and not having to beat as frequently. Alternately, increases of restingHR over time with a continuation of training may be an indicator of too much stress. Improper nutrition, such as regular or ongoing suboptimal intakes of vitamins or minerals, may result in increased ventilation and/or increased heart rate (Lukaski, 2004). It has been suggested that the additional stress may lead to parasympathetic hyperactivity, leading to an increase in resting HR (Statler and DuBois, 2016). This largely stems from research examining the sensitivity of various HR derived metrics, such as resting HR, HR variability (HRV), and HR recovery (HRR) to fluctuations in training load (Borresen and Ian Lambert, 2009). HRR in athlete monitoring is the rate of HR decline after the cessation of exercise. A common Frontiers in Sports and Active Living | www.frontiersin.org 5 May 2020 | Volume 2 | Article 42 https://www.frontiersin.org/journals/sports-and-active-living
  • 31. https://www.frontiersin.org https://www.frontiersin.org/journals/sports-and-active- living#articles Lopes Dos Santos et al. Stress in College Athletes measure of HHR is the use of a 2min step test followed by a 60 s HR measurement. The combination of the exercise (stress) on the cardiovascular system and then its subsequent return toward baseline has been used as an indicator of autonomic function and training status in athletes (Daanen et al., 2012). In collegiate athletes it was found that hydration status impacted HRR following moderate to hard straining sessions (Ayotte and Corcoran, 2018). Athletes who followed a prescription hydration plan performed better in the standing long jump, tracked objects faster, and showed faster HRR vs. athletes who followed their normal self-selected hydration plan (Ayotte and Corcoran, 2018). To date, HR monitoring and the various derivatives have mainly been successful in detecting changes in training load and performance in endurance athletes (Borresen and Ian Lambert, 2009; Lamberts et al., 2009; Thorpe et al., 2017). Although heart rate monitoring can provide additional physiological insight for aerobic sessions or events, it thus far has not been found to be an accurate measurement for quantifying internal load during many explosive, short duration anaerobic activities (Bosquet et al., 2008). Amultitude of studies have reported the reliability and validity of using RPE and sRPE across a range of training modalities (Foster, 1998; Impellizzeri et al., 2004; Sweet et al., 2004). This measure can be used to create a number of metrics such as
  • 32. session load (sRPE× duration in minutes), daily load (sum of all session loads for that day), weekly training load (sum of all daily training loads for entire week), monotony (standard deviation of weekly training load), and strain (daily or weekly training load×monotony) (Foster, 1998). Qualitative questionnaires that monitor stress and fatigue have been well-established as tools to use with athletes (see Table 1 for examples of commonly used questionnaires in research). Using short daily wellness questionnaires may allow coaches to generate a wellness score which then can be adjusted based off of the stress the athlete may be feeling to meet the daily load target (Foster, 1998; Robson-Ansley et al., 2009). However, strength and conditioning coaches need to be mindful that these questionnaires may require sports psychologist or other licensed professional to examine and provide the results. An alternative that may be better suited for strength and conditioning professionals to use could be to incorporate some of the themes of those questionnaires into programing. A Multifaceted Approach Dissociation between external and internal load units may be indicative of the state of fatigue of an athlete. Utilizing a monitoring system in which the athlete is able to make adjustments to their training loads in accordance with how they are feeling in that moment can be a useful tool for assisting the athlete in managing stress. Auto-regulation is a method of programming that allows for adjustments based on the results of one or more readiness tests. When implemented properly, auto regulation enables the coach or athlete to optimize training based on the athlete’s given readiness for training on a particular day, thereby aiming to avoid potential overtraining (Kraemer and
  • 33. Fleck, 2018). Several studies have found that using movement velocity to designate resistance training intensities can result in significant improvements in maximal strength and athletic performance (Pareja-Blanco et al., 2014, 2017; Mann et al., 2015). Velocity based training allows the coach and athlete to view real time feedback for the given lifts, thereby allowing them to observe how the athlete is performing in that moment. If the athlete is failing to meet the prescribed velocity or the velocity drops greater than a predetermined amount between sets, then this should signal the coach to investigate. If there is a higher than normal amount of stress on that athlete for the day, that could be a potential reason. This type of combination style program of using a quantitative or objective measurement (s) and a subjective measure of wellness (qualitative questionnaire) has recently been reported to be an effective tool in monitoring individuals apart of a team (Starling et al., 2019). The subjective measure in this study was the readiness to train questionnaire (RTT-Q) and the objective measures were the HRR6min test (specifically the HRR60s = recorded as decrease in HR in the 60 s after termination of the test) to assess autonomic function and the standing long jump (SLJ) to measure neuromuscular function. The findings found that, based on the absolute typical error of measurement, the HRR60s and SLJ could detect medium and large changes in fatigue and readiness. The test took roughly 8min for the entire team, which included a group consisting of 24 college-age athletes. There are many other combinations of monitoring variables and strategies that coaches and athletes may utilize. Data Analysis – How to Utilize the Measures
  • 34. Regardless of what type of monitoring tool a coach or athlete may incorporate, it is essential to understand how to analyze this data. There are excellent resources available which discuss this topic in great detail (Gabbett et al., 2017; Clubb and McGuigan, 2018; Thornton et al., 2019). This section will highlight two main conclusions from these sources and briefly describe two of the main statistical practices and concepts discussed. The use of z-scores or modified z-scores has been proposed as a method of detecting meaningful change in athlete data (Clubb and McGuigan, 2018; Thornton et al., 2019). For different monitoring tools listed in Table 1, the following formula would be an example of how to assess changes: (Athlete daily score— Baseline score)/Standard deviation of baseline. The baseline would likely be based off an appropriate period such as the scores across 2 weeks during the preseason. In sports and sports science, the use of a magnitude-based inference (MBI) has been suggested as more appropriate and easier to understand when examining meaningful changes in athletic data, than null-hypothesis significance testing (NHST) (Buchheit, 2014). Additional methods to assess meaningful change that are similar to MBI are using standard deviation, typical error, effect sizes, smallest worthwhile change (SWC), and coefficient of variation (Thornton et al., 2019). It should be noted that all of these methods have faced criticism from sources such as statisticians. It is important to understand that the testing methods, measurements, and analysis should be based on the resources and intended goals Frontiers in Sports and Active Living | www.frontiersin.org 6 May 2020 | Volume 2 | Article 42 https://www.frontiersin.org/journals/sports-and-active-living
  • 35. https://www.frontiersin.org https://www.frontiersin.org/journals/sports-and-active- living#articles Lopes Dos Santos et al. Stress in College Athletes TABLE 1 | Overview of common tool/measures used by researchers to monitor training load. Category of training load Variable examined Tests or Methods of collection References External load: defined as the work completed by the athlete, measured independently of their individual characteristics (Wallace et al., 2009) Power output Various devices Pyne and Martin, 2011 Neuromuscular function Jump tests—CMJ or SJ performance Twist and Highton, 2013 Sprint performance Twist and Highton, 2013 Time-motion analysis GPS tracking Aughey, 2011; Halson, 2014 Movement pattern analysis via digital video Taylor et al., 2012;
  • 36. Halson (2014) Internal load: related to physiological and psychological stress imposed (Wallace et al., 2009) Perception of effort Rating of Perceived Exertion (RPE) Borresen and Ian Lambert, 2009 Session Rating of Perceived Exertion (sRPE) Foster, 1998 Heart rate measures Heart rate (HR) Hopkins, 1991 HR to RPE Martin and Andersen, 2000 HR recovery (HRR) Daanen et al., 2012 HR variability (HRV) Plews et al., 2013 Training Impulse (TRIMP) Morton et al., 1990; Pyne and Martin, 2011 Qualitative questionnaires* Profile of Mood States (ROMS) Morgan et al., 1987 Recovery Stress Questionnaires for Athletes (REST-Q) Kallus and Kellmann, 2016 Daily Analysis of Life Demands for Athletes (DALDA) Rushall, 1990
  • 37. Total Recovery Scale (TQR) Kenttä and Hassmén, 1998 * indicates variable/monitoring tool that is most appropriate for use by a sport psychologist or licensed psychologist. from use, which will differ from every group and individual. Once identified, it is up to the practitioner to keep this system the same, in order to collect data that can then be examined to understand meaningful information for each setting (Thornton et al., 2019). Managing and Coping Strategies Once the collegiate-athlete has been able to identify the need to balance their stress levels, the athlete may then need to seek out options for managing their stress. Coaches are be able to assist them by sharing information on health and wellness resources available for the students, both on and off campus. Another way a coach can potentially support their athletes is by establishing an open-door policy, wherein the team members feel comfortable approaching a member of the strength and conditioning staff in order to seek out resources for coping with challenges related to stress. There are some basic skills that strength and conditioning coaches can teach (while staying within their scope of practice). Coaches can introduce their athletes to basic lifestyle concepts, such as practicing deep breathing techniques, positive self-talk, and developing healthy sleep habits (i.e., turning off their mobile devices 1 h before bed and aiming for 8 h of sleep each night, etc.). A survey of strength and conditioning practitioners by Radcliffe et al. (2015) found that strategies used by practitioners included a mix of cognitive and behavioral strategies, which was used as
  • 38. justification for recommending practitioners find opportunities to guide professional development toward awareness strategies. Practitioners reported using a wide variety of psychological skills and strategies, which following survey analysis, highlighted a significant emphasis on strategies that may influence athlete self- confidence and goal setting. Themes identified by Radcliffe et al. (2015) included confidence building, arousal management, and skill acquisition. Additionally, similar lower level themes that are connected (i.e., goal setting, increasing, or decreasing arousal intensities, self-talk, mental imagery) are all discussed in the 4th edition of the NSCA Essentials of Strength and Conditioning book (Haff et al., 2016). When the interventions aiming to improve mental health expand from basic concepts to mental training beyond a coach’s scope, it would be pertinent for the coach to refer the collegiate-athlete to a sport psychology or other mental health consultant (Fogaca, 2019). Moreover, strength and conditioning coaches may find themselves in a position to become key players in facilitating management strategies for collegiate athletes, thereby guiding the athlete in their quest to learn how to best manage the mental and physical energy levels required in the quest for overall optimal performance (Statler and DuBois, 2016). CONCLUSION AND FUTURE DIRECTIONS This review article has summarized some of the ways that strength and conditioning professionals may be able to gain a better understanding of the types of stressors encountered
  • 39. Frontiers in Sports and Active Living | www.frontiersin.org 7 May 2020 | Volume 2 | Article 42 https://www.frontiersin.org/journals/sports-and-active-living https://www.frontiersin.org https://www.frontiersin.org/journals/sports-and-active- living#articles Lopes Dos Santos et al. Stress in College Athletes by collegiate athletes, the impact these stressors may have on athletic performance, and suggestions for assisting athletes with developing effective coping strategies to reduce the potential negative physiological and psychological impacts of stress. It has been suggested that strategies learned in the context of training may have a carry-over effect into other areas such as competition. More education is needed in order for strength and conditioning professionals to gain a greater understanding of how to support their athletes with stress-management techniques and resources. Some ways to disseminate further education on stress-management tools for coaches to share with their athletes may include professional development events, such as conferences and clinics. AUTHOR CONTRIBUTIONS All of the authors have contributed to the development of the manuscript both in writing and conceptual development. REFERENCES Akenhead, R., and Nassis, G. P. (2016). Training load and player monitoring
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  • 65. symptoms of depression in competitive collegiate student athletes. Clin. J. Sport Med. 17, 481–487. doi: 10.1097/JSM.0b013e31815aed6b Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past collaboration with one of the authors RL. Copyright © 2020 Lopes Dos Santos, Uftring, Stahl, Lockie, Alvar, Mann and Dawes. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not
  • 66. comply with these terms. Frontiers in Sports and Active Living | www.frontiersin.org 10 May 2020 | Volume 2 | Article 42 https://doi.org/10.1519/JSC.0000000000000919 https://doi.org/10.1136/bjsports-2019-100715 https://doi.org/10.1080/02640410802702186 https://doi.org/10.1080/10413209008406420 https://doi.org/10.1136/bjsports-2015-094758 https://doi.org/10.1123/jis.1.2.202 https://doi.org/10.1136/bjsports-2016-096581 https://doi.org/10.1080/17461391.2019.1612951 https://doi.org/10.1519/14153.1 https://doi.org/10.1519/JSC.0000000000001073 https://doi.org/10.1123/ijspp.2018-0169 https://doi.org/10.1123/ijspp.2016-0434 https://doi.org/10.1519/SSC.0000000000000339 https://doi.org/10.1123/ijspp.8.5.467 https://doi.org/10.1519/JSC.0b013e3181874512 https://doi.org/10.1080/10413209808406375 https://doi.org/10.1097/JSM.0b013e31815aed6b http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ https://www.frontiersin.org/journals/sports-and-active-living https://www.frontiersin.org https://www.frontiersin.org/journals/sports-and-active- living#articlesStress in Academic and Athletic Performance in Collegiate Athletes: A Narrative Review of Sources and Monitoring StrategiesIntroductionStress and the Stress ResponseMethodsLiterature Search/Data CollectionInclusion CriteriaData AnalysisAcademic StressAthletic StressMonitoring ConsiderationsMonitoring External LoadsMonitoring Internal
  • 67. LoadsA Multifaceted ApproachData Analysis – How to Utilize the MeasuresManaging and Coping StrategiesConclusion and Future DirectionsAuthor ContributionsReferences