ArticlePDF Available

Comparison of surf and hike therapy for active duty service members with major depressive disorder: Study protocol for a randomized controlled trial of novel interventions in a naturalistic setting

Authors:
  • Naval Health Research

Abstract and Figures

Many active duty service members suffer from major depressive disorder (MDD). Although traditional treatments exist, alternative approaches may also be effective in treating depressive symptoms. Previous research has shown that physical activity has significant positive effects on depression symptoms in individuals with MDD, and that these benefits may be enhanced when physical activity occurs in a natural environment. Even though physical activity (i.e., hiking, walking) in natural environments has been shown to reduce depressive symptoms, water-based activity occurring in a natural environment (e.g., surfing) may produce even greater improvements in depressive symptoms. We detail an ongoing randomized controlled trial (RCT) comparing the efficacy of surf therapy and hike therapy with respect to immediate and longer-term psychological, physical, and functional outcomes in active duty service members with MDD. We describe the methodological development of this RCT evaluating novel treatment approaches and discuss considerations for evaluating physical activity interventions in a naturalistic setting.
Content may be subject to copyright.
Contents lists available at ScienceDirect
Contemporary Clinical Trials Communications
journal homepage: www.elsevier.com/locate/conctc
Research paper
Comparison of surf and hike therapy for active duty service members with
major depressive disorder: Study protocol for a randomized controlled trial
of novel interventions in a naturalistic setting
Kristen H. Walter
a,b,
, Nicholas P. Otis
a,b
, Lisa H. Glassman
a,b
, Travis N. Ray
a,b
,
Betty Michalewicz-Kragh
c
, Kim T. Kobayashi Elliott
c
, Cynthia J. Thomsen
b
a
Leidos, 140 Sylvester Road, San Diego, CA, 92106-3521, United States
b
Health and Behavioral Sciences Department, Naval Health Research Center, 140 Sylvester Road, San Diego, CA, 92106-3521, United States
c
Directorate of Public Health, Naval Medical Center San Diego, San Diego, CA, United States
ARTICLE INFO
Keywords:
Major depressive disorder
Surf therapy
Hike therapy
Physical activity
Military
ABSTRACT
Many active duty service members suffer from major depressive disorder (MDD). Although traditional treat-
ments exist, alternative approaches may also be effective in treating depressive symptoms. Previous research has
shown that physical activity has significant positive effects on depression symptoms in individuals with MDD,
and that these benefits may be enhanced when physical activity occurs in a natural environment. Even though
physical activity (i.e., hiking, walking) in natural environments has been shown to reduce depressive symptoms,
water-based activity occurring in a natural environment (e.g., surfing) may produce even greater improvements
in depressive symptoms. We detail an ongoing randomized controlled trial (RCT) comparing the efficacy of surf
therapy and hike therapy with respect to immediate and longer-term psychological, physical, and functional
outcomes in active duty service members with MDD. We describe the methodological development of this RCT
evaluating novel treatment approaches and discuss considerations for evaluating physical activity interventions
in a naturalistic setting.
1. Introduction
Many U.S. service members suffer from major depressive disorder
(MDD; [1,2], with prevalence estimated at 8% across services [3],
comparable to the 8.6% estimate for the U.S. population [4]. In-
dividuals with MDD are at increased risk of suicidal ideation, mortality,
and medical/psychological comorbidities [5,6] as compared to the
general population. In addition to the significant health consequences
of MDD, there are substantial financial costs associated with related
medical care and loss of productivity [2].
Traditional treatment approaches, such as cognitive behavioral
therapy (CBT; [7–10] and antidepressant medication [11,12] are ef-
fective in treating MDD. However, there is conflicting evidence re-
garding the relative benefits of CBT for MDD compared with other
active treatments [13]. Furthermore, nonadherence rates for anti-
depressant medication may be as high as 45% [14], which can reduce
their effectiveness [15] and increase the risk for relapse (e.g., Ref. [16].
Due to these observed variations in the efficacy and tolerance of
traditional treatments [17,18], there has been increasing interest in
other interventions for MDD, including physical activity. Exercise has
been theorized to lead to increases in neurotransmitters (e.g., serotonin)
and neurotrophins (e.g., brain-derived neurotrophic factor), alleviate
neuroendocrine abnormalities (e.g., hypothalamic-pituitary-adrenal
axis), and enhance perceived self-efficacy—all of which could lead to
feelings of well-being [19]. Indeed, certain types of physical activity
have demonstrated large and significant effects on depression symp-
toms [20], including among individuals with MDD [21–25]. Ad-
ditionally, exercise may be a viable adjunctive treatment to standard
care [26,27].
Physical activity occurring in the natural environment may have an
especially potent influence on mental health, providing greater benefits
than physical activity alone. Meta-analytic findings show that engaging
in physical activity outdoors (versus indoors) has greater effects on
tension, anger, and depression [28]. Furthermore, water-based
https://doi.org/10.1016/j.conctc.2019.100435
Received 7 June 2019; Received in revised form 31 July 2019; Accepted 19 August 2019
Corresponding author. Naval Health Research Center, 140 Sylvester Road, San Diego, CA, 92106-3521, United States.
E-mail addresses: kristen.h.walter.ctr@mail.mil (K.H. Walter), nicholas.p.otis.ctr@mail.mil (N.P. Otis), lisa.h.glassman.ctr@mail.mil (L.H. Glassman),
travis.n.ray2.ctr@mail.mil (T.N. Ray), betty.michalewiczkragh.civ@mail.mil (B. Michalewicz-Kragh), kim.t.elliott2.civ@mail.mil (K.T. Kobayashi Elliott),
cynthia.j.thomsen.civ@mail.mil (C.J. Thomsen).
Contemporary Clinical Trials Communications 16 (2019) 100435
Available online 21 August 2019
2451-8654/ © 2019 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T
activities in a natural environment may be particularly suited to im-
proving mental health. For example, [29] demonstrated that exercise
outdoors in the presence of water (versus without water) generated
greater improvements in symptoms associated with depression. These
results provide support for the beneficial effects of water-based en-
vironments, which is often referred to as ‘blue space’ (for a systematic
review, see Ref. [30]. Theoretical proponents of blue space suggest the
additive benefits of water may result from its unique sensory inputs
[31], such as the relaxing sounds of waves or the smell of salt water.
Based on the notion of blue space, surfing—a physical activity im-
mersed in water—could be expected to produce enhanced psycholo-
gical benefits when compared to physical activity occurring outside the
presence of water.
The current study compares the efficacy of two outdoor physical
activity-based interventions, surf therapy and hike therapy, for service
members with MDD. The robust study methodology allows for an
evaluation of both surf and hike therapy, providing valuable insight
into the immediate and longer-term psychological, physical, and func-
tional effects of each therapy on MDD symptomology. Further, the
randomized controlled trial (RCT) design allows for a direct comparison
of water-based and land-based activity, which may provide support for
the additive effects of physical activity in the presence of water. The
primary study objective is to evaluate whether surf therapy yields a
greater reduction in depression symptoms than hike therapy, which
may be due to the salutary effects of water, or “blue space.” It is hy-
pothesized that both programs will significantly reduce depression
symptoms; however, due to the added benefits of exercising in water,
surf therapy is expected to result in greater improvements in depressive
symptomology than hike therapy. Secondary study aims include com-
parisons across participants in surf and hike therapy of MDD remission
rates, changes in related symptoms both over the study period and
within session, drop-out rates, and self-monitored physical activity.
2. Design and methods
This prospective, longitudinal study will screen up to 125 active
duty service members seeking surf or hike therapy in order to identify
at least 86 eligible study participants and account for potential loss of
participants to attrition (see section 2.7). Recruitment began in January
2018 and is expected to be completed within 2 years of that date. Eli-
gible participants are randomly assigned to surf or hike therapy. Par-
ticipants complete clinical interviews and self-report measures prior to,
following, and 3 months after completion of the intervention; change in
depressive symptom severity will serve as the primary study outcome.
Additionally, participants complete brief self-report measures before
and after each of the physical activity sessions in order to evaluate
immediate effects. Participants are also issued a wearable activity
tracker (i.e., Fitbit Charge™ 2; Fitbit Inc., San Francisco, CA) to be worn
as often as possible throughout the study period from pre-program to 3-
month follow-up. All study procedures were approved by the Naval
Medical Center San Diego (NMCSD) Institutional Review Board.
2.1. Participants
The final sample will include 86–110 active duty service members
(i.e., 43–55 participants per condition) who meet current diagnostic
criteria for MDD and are seeking care at the Wounded, Ill, and Injured
(WII) Wellness Program at NMCSD. Service members are screened at
the initial assessment and provide voluntary written informed consent
prior to beginning any study-related procedures. If service members do
not consent to take part in the study, they may still participate in the
surf or hike therapy programs as standardly provided.
As the study intervention is incorporated into standard practice, the
current study features broad eligibility criteria. Individuals are eligible
for study participation if they (a) are active duty service members
seeking care at the WII Wellness Program at NMCSD, and (b) have a
current diagnosis of MDD based on the Diagnostic and Statistical
Manual of Mental Disorders (5th Edition [DSM-5]; [32] criteria, as
assessed by the Mini International Neuropsychiatric Interview 7.0
(MINI-7; [33]. Service members who have previously received or are
currently receiving surf or hike therapy are ineligible for the study; this
single exclusion criterion was selected to control for dose of the inter-
vention received. For ethical care provision reasons, we do not exclude
individuals who are engaged in psychotherapy or prescribed psycho-
tropic medication; however, data regarding other treatments received
are collected so that the use and effects of these treatments can be
empirically evaluated.
2.2. Treatment
The WII Wellness Program in the Health and Wellness Department
at NMCSD provides novel, 6-week surf and hike therapy programs as
part of standard medical treatment (i.e., a scheduled medical appoint-
ment) for active duty service members seeking care. Both surf and hike
therapy programs follow the same schedule, which consists of 6 con-
secutive weeks of the respective program, followed by a 2-week break
from programming prior to the start of the next cohort (and during
which pre- and post-program assessments are completed). Both pro-
grams are considered “progressive” in that individuals in each program
are anticipated to build skill and ability over the course of the 6-week
program. It is important to note that the programs do not include a
structured psychotherapy/therapy component; rather, engagement in
the activity within the natural environment and social interaction/
support are considered the therapeutic elements (e.g., Refs. [34–37].
Abbreviations
AIMS Athletic Identity Measurement Scale
CBT cognitive behavioral therapy
CSQ-8 Client Satisfaction Questionnaire-8
DSM-5 Diagnostic and Statistical Manual of Mental Disorders (5th
Edition)
GAD-7 Generalized Anxiety Disorder 7-item scale
IPAQ-SF International Physical Activity Questionnaire – Short Form
ISI Insomnia Severity Index
MADRS Montgomery–Åsberg Depression Rating Scale
MDD major depressive disorder
MET metabolic equivalent
MINI-7 Mini International Neuropsychiatric Interview 7.0
MLM multilevel modeling
NMCSD Naval Medical Center San Diego
NPRS Numerical Pain Rating Scale
OSU TBI-ID-SF The Ohio State University Traumatic Brain Injury
Identification Method – Short Form
PANAS Positive and Negative Affect Schedule
PAS Positive Affect Schedule
PCL-5 PTSD Checklist for DSM-5
PHQ-4 Patient Health Questionnaire-4
PHQ-9 Patient Health Questionnaire-9
PTSD posttraumatic stress disorder
RCT randomized controlled trial
RSES-4 Response to Stressful Events Scale-4
SF-36v2®Short Form Health Survey – 36 Item, Version 2
TBI traumatic brain injury
WII Wounded, Ill, and Injured
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
2
The two programs are conducted as usual (i.e., service members
receive the same surf or hike intervention regardless of whether they
participate in the study), consistent with standard operating proce-
dures. Only three modifications are made to the programs' current
procedures for the study. First, clinical interview and self-report as-
sessments are completed before and after each program, as well as 3
months after each program's conclusion, to evaluate the effects of
program participation on patient outcomes. Brief self-report assess-
ments are also completed immediately before and after each activity
session. Second, only patients who currently meet diagnostic criteria for
MDD will qualify for participation in the study. Third, patients will be
randomized to either surf or hike therapy rather than choosing the
activity in which they will participate. However, all patients will have
the opportunity to receive the alternate activity after completion of the
program to which they were randomized (see section 2.4). Randomi-
zation of eligible study participants to either the surf or hike therapy
condition is conducted using a blocked randomization scheme (in
blocks of 10) designed to yield balanced groups across the recruitment
period. Once randomized, participants receive either surf or hike
therapy sessions once per week for 6 weeks.
2.3. Surf therapy
A master's degree-level exercise physiologist serves as the program
manager and coordinates all aspects of the surf therapy program. The
program is 6 weeks in duration; sessions occur on Thursday mornings at
the same Southern California beach. The program follows a cohort
format that accommodates about 20–25 service members per program
cycle. Each service member is paired with a volunteer surf instructor
who usually works with him or her each week for the duration of the
program. Goals are individually tailored to the service member using a
strengths-based approach that considers the service member's abilities,
skills, and comfort with the water-based environment (e.g., Ref. [36];
they can incorporate both physical and psychological objectives. All
volunteer surf instructors are required to be certified through the
Armed Services Young Men's Christian Association, and to attend an
initial clinic orientation given by the program manager and an annual
refresher training on program policies and patient safety. Volunteers
also attend a 15 min debrief prior to every surf therapy session. The
ratio of volunteer surf instructors to patients is 1:1 or 1:2. In addition to
the volunteer surf instructors, there are approximately 2–3 staff mem-
bers (including the program manager), land volunteers, and local life-
guards on site to monitor safety. For each session, participants are
provided with necessary equipment, including wet suits, surfboards,
boogie boards, leashes, fins, and rash guards.
Before each surf therapy session, coffee and fruit are available to all
individuals affiliated with the program. An elective hour of group yoga
integrating Ashtanga and Vinyasa elements is also offered at the same
beach location where the surf therapy occurs. At the start of each surf
therapy session, a briefing is provided that includes program policies
and procedures, as well current environmental conditions and safety
considerations. Participants then surf with their instructor for ap-
proximately 3 h. Following each surf session, a lunch is provided for all
patients, volunteers, and staff, and socialization is encouraged. The six
sessions of surf therapy follow a similar format, but participants work to
develop greater proficiency to surf safely and independently.
2.4. Hike therapy
The program manager of the hike therapy program is a Certified
Therapeutic Recreation Specialist who manages all aspects of the pro-
gram. Similar to surf therapy, the hike therapy program is 6 weeks in
duration. Hike therapy sessions occur on Wednesday mornings and take
place at various locations throughout a Southern California county. The
hike program is also structured in a cohort format that can include up to
20 service members per program cycle. Approximately four staff
members (including the program manager and student interns) and
volunteers hike alongside patients to ensure safety, yielding a max-
imum 1:4 ratio of staff to patients. During hike therapy, service mem-
bers may hike together or at a self-selected pace. Goals are also per-
sonalized for the service member using a strengths-based approach [36]
and can include both physical and mental health aims to facilitate each
participant's recovery (e.g., complete one hike independently, identify
community hiking groups).
During the first week, participants attend an orientation where
program policies, hiking etiquette, and safety information are provided.
Participants are also asked to download a specific hiking app that
provides extensive trail information to their cell phones. In the or-
ientation meeting, participants are typically divided into small groups
and work together to select a Southern California trail that program
participants will hike for their designated week (i.e., within weeks 3–6).
Following the orientation, participants hike an easy, flat urban trail so
that the physical endurance and speed of the group can be assessed. The
first two locations are consistent across program cycles, but the re-
maining four vary depending on the preferences of the small groups.
Hike therapy sessions are approximately 3 h in duration, with trails
Fig. 1. Time course of data collection and measures used. Both surf and hike therapy programs are 6 weeks in duration.
a
Assessor-administered. AIMS = Athletic
Identity Measurement Scale; Borg RPE Scale =Borg Rating of Perceived Exertion Scale; CSQ-8= Client Satisfaction Questionnaire-8; GAD-7 =Generalized Anxiety
Disorder 7-item scale; IPAQ-SF = International Physical Activity Questionnaire – Short Form; ISI = Insomnia Severity Index; MADRS = Montgomery–Åsberg
Depression Rating Scale; MINI-7 = Mini International Neuropsychiatric Interview 7.0; NPRS = Numerical Pain Rating Scale; OSU TBI-ID-SF = The Ohio State
University Traumatic Brain Injury Identification – Short Form; PANAS = Positive and Negative Affect Schedule; PAS = Positive Affect Schedule; PCL-5 = PTSD
Checklist for DSM-5; PHQ-4 = Patient Health Questionnaire-4; PHQ-9 = Patient Health Questionnaire-9; RSES-4 = Response to Stressful Events Scale-4; SF-
36v2®= Short Form Health Survey 36-Item, Version 2.
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
3
becoming progressively more challenging across the 6 weeks. After the
last hike at week 6, there is a potluck to celebrate program completion.
2.5. Assessments
Participants provide voluntary, written informed consent before
engaging in any study assessments. Upon consent, participants com-
plete a diagnostic, pre-program assessment (administered in person by
an independent evaluator/study assessor) that includes both clinical
interview measures and self-report questionnaires assessing MDD and
other related symptoms. The study assessor is blind to participants’
randomized condition. Participants are also provided with a wearable
activity tracker (Fitbit Charge 2) along with instructions on how to use
the device. They are informed that they will be permitted to keep the
device if they use it for more than 50% of the days between the pre-
program and 3-month follow-up assessments. Within 2 weeks of the
pre-program assessment, patients begin the program in the modality to
which they were randomly assigned (i.e., surf or hike therapy).
Throughout these programs, participants complete brief, on-site self-
report assessments before and after each of the six weekly sessions.
Within 2 weeks after the final session, participants complete an in-
person post-program assessment. The final, in-person follow-up as-
sessment occurs 3 months after the post-program assessment. Like the
pre-test assessment, these assessments are administered by the study
assessor and include both clinical interview measures and self-report
questionnaires. If an individual discontinues participation, they are still
contacted for assessment at post-treatment and follow-up time points
unless they request to be removed from study participation. A fidelity
assessor routinely reviews assessment recordings and provides quar-
terly feedback to the study assessor throughout the study.
2.5.1. MDD diagnosis and depressive symptoms
Change in depressive symptom severity serves as the primary study
outcome. Depression symptoms are evaluated at all three main assess-
ment time points using the Montgomery–Åsberg Depression Rating
Scale (MADRS; [38]. The MADRS is a semi-structured, clinical inter-
view for the assessment of depressive symptom severity and has been
shown to be sensitive to change after an intervention [38].
The MINI-7 [33], an assessor-administered diagnostic interview, is
used to evaluate MDD diagnostic status at main study assessment time
points (see Fig. 1 for all assessment details). Additionally, at pre-pro-
gram, it is used to determine participant eligibility for study partici-
pation. The MINI-7 is also presented in Section 2.5.2 because it is used
to assess for other comorbid conditions. Self-reported severity of de-
pression symptoms within the past 2 weeks is examined using the 9-
item Patient Health Questionnaire (PHQ-9; [39]. Each item is rated on a
scale (ranging from 0 to 3; higher scores reflect greater depression se-
verity) that can either be summed to create a total severity score or used
to evaluate diagnostic criteria. The PHQ-9 has demonstrated sound
psychometric properties, including good internal consistency and tes-
t–retest reliability [39].
Current depression and anxiety symptomatology is assessed before
and after each activity session with the 4-item Patient Health
Questionnaire (PHQ-4; [40]. The PHQ-4 consists of two depression
items from the PHQ-9 and two anxiety items from the Generalized
Anxiety Disorder (GAD) 7-item scale (GAD-7; discussed in 2.3.2.; [41].
Items are scored from 0 to 3 and summed to create a total score (with
higher scores indicating greater severity). Scores on the anxiety and
depression subscales of the PHQ-4 are highly correlated with scores on
longer measures of anxiety and depression, making it an efficient and
valid assessment instrument [40].
2.5.2. Other comorbid conditions
In addition to assessing MDD, the MINI-7 [33] is administered to
evaluate the presence of other comorbid psychological disorders, in-
cluding posttraumatic stress disorder (PTSD), anxiety disorders, other
mood disorders, and psychotic symptoms. Self-reported PTSD sympto-
matology in the past month is assessed using the PTSD Checklist for the
DSM-5 (PCL-5; [42]. This instrument contains the revised Life Events
Checklist for DSM-5 [43] and an extended Criterion A assessment. Items
on the PCL-5 directly correspond with the 20 DSM-5 diagnostic criteria
for PTSD and are rated on a scale ranging from 0 to 4 (higher scores
suggest greater symptom severity). The PCL-5 has high internal con-
sistency (α = 0.94) and good test–retest reliability (r= 0.82; [44].
Presence and severity of anxiety over the past 2 weeks is evaluated
using the self-report GAD-7 [41]. Each symptom item is rated from 0 to
3 (higher scores indicate greater anxiety severity). The GAD-7 has been
found to have an internal consistency of α = 0.92 [41].
Traumatic brain injury (TBI) history is evaluated using The Ohio
State University TBI Identification Method – Short Form (OSU TBI-ID-
SF; [45]. The OSU TBI-ID-SF is a 7-item structured interview for the
assessment of lifetime TBI history. The measure assesses for history of
head and neck injuries due to motor vehicle accident, sports, and
combat, as well as for the neurological aspects of each injury (e.g., loss
of consciousness). Summary indices of lifetime injury are generated to
reflect the likelihood that neurological consequences have resulted
from the TBI history. The predictive validity of these indices is sup-
ported in the literature [45,46].
The nature, severity, and impact of insomnia over the past week is
evaluated with the 7-item Insomnia Severity Index (ISI; [47]. Each item
is rated from 0 to 4 and summed to yield a total score (higher scores
reflect greater insomnia severity). The ISI has also demonstrated high
internal consistency (α = 0.90; [48].
Current level of pain is rated using the Numerical Pain Rating Scale
(NPRS; [49]. The NPRS consists of a single item on which the partici-
pant rates their current level of pain on an 11-point scale (0 = no pain;
10 = worst possible pain).
2.5.3. Measures of affect, resilience, and function
Current emotions are assessed using the 20-item Positive and
Negative Affect Schedule (PANAS; [50]. Each affect item is rated on a
scale ranging from 0 to 4. The 10 positive affect items are summed to
create a positive affect scale (higher scores reflect greater positive af-
fect); the 10 negative affect items are added to yield a negative affect
scale (lower scores indicate less negative affect). Internal consistencies
for the PANAS subscales are acceptably high; for positive affect, they
range from α = 0.86 to 0.90; for negative affect, they range from
α = 0.84 to 0.87 [50].
Resilience to the most stressful events experienced by participants is
measured by the 4-item Response to Stressful Events Scale (RSES-4;
[51]. The RSES-4 is a brief self-report resilience measure that was de-
veloped from the 22-item Response to Stressful Events Scale (RSES-22;
[52]. Construct validity is supported by a strong correlation with the
RSES-22 (r= 0.90), as well as acceptable correlations (r= 0.29–0.39)
with measures of burnout and distress [51].
Functional physical and mental health are determined using re-
sponses to the Short Form Health Survey – 36 Item, Version 2 (SF-36v2®
[94]; QualityMetric Inc.). The SF-36 is a widely used questionnaire that
allows the computation of eight summary health measures: physical
functioning, role limitations due to physical health, pain, general
health, energy/fatigue, social functioning, role limitations due to
emotional problems, and emotional well-being. The SF-36, as well as
the eight summary measures, have been found to have good criterion
validity (r= 0.51 to 0.85; [53,54].
2.5.4. Demographic questionnaire
This questionnaire collects demographic information (e.g., age,
years of education, race, military service branch), which will be used to
describe the sample and to determine whether demographic factors
influence outcomes (and therefore need to be included as covariates in
study analyses).
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
4
2.5.5. Treatment use
The Treatment Utilization Questionnaire, created for this study, asks
participants about their use of outpatient counseling, psychotropic
medication, couples or family counseling, and support groups, as well
as any psychiatric hospitalizations. At the pre-program assessment,
information is collected over the participant's lifetime as well as within
the past 3 months; at the post-program and 3-month follow-up assess-
ments, information is only collected for the past 3 months.
2.5.6. Activity level and athletic identity
The subjective intensity of exertion a person experiences during
physical activity is evaluated using a modified version of the single-item
Borg Rating of Perceived Exertion Scale (Borg RPE Scale; [55]. The
modified response scale ranges from 0 (no exertion at all) to 10 (maximal
exertion) and has been used in prior research (e.g., Refs. [56–59]. Va-
lidity of the Borg RPE Scale is well-established against various phy-
siological criteria (e.g., r= 0.62 with heart rate), and correlations are
particularly high in activities involving swimming (e.g., r= 0.83 with
heart rate; [60]. Athletic identity is determined by the Athletic Identity
Measurement Scale (AIMS; [61]. The AIMS has displayed strong psy-
chometric properties including construct validity, internal consistency
(α = 0.93), and test–retest reliability (r= 0.89; [61].
Baseline physical activity is assessed with the 9-item self-report
International Physical Activity Questionnaire-Short Form (IPAQ-SF;
[62]. The measure yields a summary score reflecting the frequency and
intensity of activity over the last 7 days, as well as sedentary periods.
Criterion validity of the IPAQ-SF in measuring total activity has been
found to be acceptable (rs = 0.29–0.30) in relation to other established
self-report activity measures [62–64]. Because the IPAQ-SF lacks suf-
ficient specificity to identify physical activity change in small samples
[64,65], it is only administered once at the pre-program assessment.
Ongoing physical activity and physiological data are collected via
the Fitbit Charge 2 device. The Fitbit Charge 2 is a popular, consumer-
based, wrist-worn activity tracker. In this study, the device provides
additional information on physical activity. Heart rate is collected, and
sleep data serves as secondary data to augment self-report measures of
insomnia. The Fitbit Charge 2 displays good specificity (0.61–0.96) in
detecting sleep–wake states and sleep stage composition, but is less
accurate (0.49) at detecting deep sleep compared with poly-
somnography [66]. In research published since the start of the study,
the device has shown mixed results regarding heart rate accuracy
[67–69], active minutes [70], and energy expenditure [71,72]. Re-
search on step count reports modest accuracy (r= 0.58; [70]. Heart
rate, physical activity, and sleep pattern data are continuously synced
and collected throughout the duration of the study. Due to data privacy
issues and inability to reuse devices, and as an added incentive to ad-
here to the study protocol, participants who wear the Fitbit for more
than 50% of the study days are given the device to keep; otherwise,
devices are destroyed.
2.5.7. Program and surf/hike engagement
The extent of program participation at each session is assessed using
a self-report activity participation questionnaire that was developed for
this study. The measure asks participants to indicate the specific ac-
tivities they engaged in during each surf or hike therapy session. At pre-
program and 3-month follow-up, we also ask participants to report the
number of days on which they surfed and hiked within the past month.
This variable will be used to determine whether engagement in surf or
hike therapy affects longer-term levels of engagement in these activ-
ities.
2.5.8. Program satisfaction
The 8-item Client Satisfaction Questionnaire (CSQ-8; [73] evaluates
satisfaction with the therapy programs provided. Each of the eight
items is rated on a 4-point scale (response anchors vary by question).
The CSQ-8 has demonstrated strong psychometric properties, including
high levels of internal consistency [73,74] and validity through higher
satisfaction scores among individuals who completed treatment versus
those who dropped out [74].
2.6. Design considerations
A number of issues were considered in developing this RCT in a
naturalistic setting. A primary consideration was to develop study
methodology that would allow for the main study hypothesis to be
appropriately examined (i.e., to determine whether physical activity
that occurs in water has enhanced benefits for reducing depression
symptoms relative to physical activity that occurs on land).
Additionally, the literature on surf therapy often lacks methodological
rigor and we wanted to build not only upon our previous work [75], but
also the state of the science within the field. Specifically, we wanted to
address design limitations regarding incorporation of a comparison
group, use of a longitudinal design, and inclusion of multiple methods
of data collection.
2.6.1. Selection of a comparison group
To date, no study examining surf therapy has included a comparison
group in its design, which is critically important for understanding the
benefits that are specific to surf therapy. Not only was it imperative that
the study include a comparison group, but we carefully evaluated
several options. Data from the program evaluation phase of our surf
therapy study (which used a single-group design) demonstrated sig-
nificant improvements in psychological symptoms, as well as increases
in positive affect and decreases in negative emotions [75]. Because
significant changes in outcomes were observed for most of the study
variables, we wanted to compare surf therapy and an active control
condition rather than a minimal contact condition. Comparing two
active conditions can produce results that begin to address the question
of which interventions work for whom and under what circumstances.
When evaluating potential active control conditions, we considered
rock climbing, which, like surfing can be considered an “extreme
sport,” but that occurs on land. However, the WII Wellness Program at
NMCSD did not offer a rock climbing program, and comparing the WII
Wellness surf therapy program and a rock climbing program offered
elsewhere could introduce a variety of confounds. Furthermore, we
were concerned about potential differences in energy expenditure
during rock climbing (5–8 metabolic equivalents [METs]) compared
with surfing (3–6 METs; [76]; see also [77]. Cycling was another land
activity offered through the WII Wellness Program that was considered
but not selected for our comparison group. Similar to rock climbing,
there were potential energy expenditure differences between cycling
(3.5–10 METs; Ainsworth et al., n.d.; see also [77] and surfing. Finally,
and perhaps most importantly, we were concerned about the accessi-
bility of the comparison sport given that surf therapy is not widely
accessible. Surf therapy requires a large, dynamic body of water (or a
specially designed pool), so we wanted to select an activity that might
be more easily accessible to a broader population than either rock
climbing or cycling, which can require access to specific locations or
gear that can be resource prohibitive.
Hike therapy, as provided through the WII Wellness Program, was
considered and ultimately decided upon as the active comparison
condition in this RCT. Hike therapy is an option available to many
because the activity requires minimal gear and can take place on var-
ious types of terrain. As a comparative condition, hike therapy provides
an excellent parallel to surfing in several ways. First, hike therapy is a
physical activity where participants can progress at their own pace, and
the energy expenditure (5.3 METs) is comparable to surfing (3–6 METs;
Ainsworth et al., n.d.; see also [77]. Additionally, hike therapy is con-
ducted in a group setting, which may help to control for social inter-
action. Lastly, hike therapy takes place outdoors and allows for an
immersive experience in the natural environment. Taken together,
these factors ultimately led to the selection of hike therapy as the active
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
5
comparison condition for this RCT. The surf–hike comparison will allow
for the evaluation of any unique effects of water-based exercise while
controlling for several important components (i.e., physical activity,
social interaction, natural environment, level of exertion, and even
scheduling and department policies) of both programs.
2.6.2. Longitudinal study design
Another methodological weakness of extant surf and hike therapy
studies is the limited use of longitudinal study designs. Evaluating the
outcomes of both therapies over time is important to determine the
duration of the therapeutic effects and the dosing required to achieve
them. Although there have been some hiking studies that report long-
itudinal findings (e.g., Refs. [78–81] conducted the only surf therapy
study that reported follow-up assessment findings, and the follow-up
occurred only 30 days after the end of participation in surf therapy.
Including a follow-up assessment is critical to the current RCT because
it provides essential information about the duration of therapeutic ef-
fects. However, it is important to take into account that study partici-
pants are active duty service members, a transient population due to
temporary duty assignments, relocation, deployments, and transitions
out of the military. In psychotherapy treatment outcome studies with
military samples, follow-up periods typically range from 1 to 6 months.
We chose to conduct follow-up assessments 3 months following treat-
ment completion to longitudinally assess program effects while mini-
mizing attrition at follow-up caused by participant deployment or re-
location.
It is also important to examine the immediate outcomes of both surf
and hike therapy. Some evidence suggests that physical activity in the
natural environment produces positive effects on mental health im-
mediately following participation in the activity (e.g., Ref. [28]. Results
from our previous research showed significantly decreased depression
and anxiety symptoms, as well as increased positive affect, immediately
following engagement in a surf therapy session [75]. In order to assess
the immediate effects of both surf and hike therapy, participants in the
current RCT complete brief assessments immediately prior to and fol-
lowing their respective activity sessions. The brief assessments are ab-
breviated versions of the measures completed at the pre-program, post-
program, and 3-month follow-up assessments.
As a part of the longitudinal study design, we employed a cross-over
strategy in which participants can enroll in the other type of therapy
after they complete the post-program assessment. For program eva-
luation purposes, participants would ideally receive the intervention
(surf or hike therapy) to which they are randomized and complete any
longitudinal follow-up assessments prior to receiving the other inter-
vention. However, we determined that allowing participants to receive
the other intervention after completion of the post-program assessment
was more practical given the transient nature of our sample population.
Since study participants may no longer be located in the area 3 months
following program completion, we thought it was important to provide
them with the opportunity to receive the other intervention after
completing the first one in order to reduce bias in both recruitment and
retention. To statistically evaluate the influence of the cross-over design
on results, we code participants to indicate whether they participated in
the other program (or elected to repeat the program to which they were
randomized) during their follow-up period. Analyses will test whether
program effects differ depending on whether participants received ei-
ther intervention during the follow-up period. Furthermore, data are
collected on the number of sessions attended by each participant to
allow for a more nuanced understanding of dosing effects.
2.6.3. Multimodal assessment
An over-reliance on self-report data is another limitation of prior
research on surf therapy outcomes. Four studies [34,75,81,82] have
examined the psychological effects of surfing, of which three
[75,81,82] collected quantitative data using validated measures. Fur-
thermore, all four studies used only self-report measures, which are
subject to biases due to variations in question interpretation, socially
desirable responses, and the like. Similarly, although many hiking
studies have used validated psychological self-report measures (e.g.,
Refs. [78,80,83], as well as physiological data (e.g., Refs. [84–86], none
have utilized diagnostic clinical interviews to measure diagnoses or
other primary outcome variables. While the assessments used in this
study include validated self-report measures, ours is the first surf
therapy study to also incorporate clinical interview data to strengthen
conclusions about the effects of surf and hike therapy on relevant
outcomes.
To augment information reported in both clinical interviews and on
self-report instruments, physiological data are also collected
throughout the program using the Fitbit Charge 2 device. The Fitbit
Charge 2 was selected because of its ability to collect relevant data
while still being cost effective. Additionally, Fitbit is a popular brand of
wearable activity trackers, and could be issued to and kept by partici-
pants after completion of the study if they used the device as stated in
the consent form. It should be mentioned that one limitation of the
Fitbit Charge 2 for this particular study is that the device is not water
resistant, so unlike participants randomized to hike therapy, those
randomized to surf therapy cannot wear their devices during their ac-
tivity sessions. Although Fitbit now has newer devices that are water
resistant, these were not available at the outset of this study.
2.7. Assessment fidelity
The clinical interview portion of each assessment at pre-program,
post-program, and 3-month follow-up is audio recorded. Participants
provide written informed consent for audio recording as a part of the
initial consent process. Twenty percent of participants (n= 22) will be
randomly selected for review to determine assessment fidelity, and all
assessment time points will be reviewed for each selected participant. A
fidelity assessor, who holds a doctoral degree in clinical psychology and
has expertise in the diagnosis of MDD, will be reviewing all cases se-
lected for fidelity and providing ratings for the MINI-7 and the MADRS.
Cohen's kappa statistic will be used to assess the interrater reliability of
MDD diagnoses between the initial assessor and the fidelity rater; in-
traclass correlations will be used to evaluate interrater reliability for
MADRS scores.
2.8. Data analysis
The study is a two (Group: surf therapy/hike therapy) by three
(Assessment time point: pre-program/post-program/3-month follow-
up) mixed effects design, where the first factor is between participants
and the second is within participants. The minimum sample size of
N= 86 (surf n= 43; hike n= 43) was determined based on the power
to test the primary study research question (i.e., do changes in de-
pression symptoms over time vary between participants in surf versus
hike therapy?). We assumed an effect size of d= 0.40, with α = 0.05;
1-β = 0.90; and r= 0.40 between repeated measures. The effect size of
d= 0.40 was derived from the program evaluation phase and reflects
the most conservative value found for pre- to post-program changes in
depression [75]. Using these parameters, the estimated required sample
size was N= 83. Based on our previous study, 27 additional partici-
pants were included to account for attrition and ensure sufficient
power, resulting in a final target sample size of at least 86.
Data will be analyzed as intent to treat, meaning that all eligible
participants will be included in study analyses. If study participants do
not complete the program or are discontinued from the study due to a
physician-determined change in medical clearance, then they will be
coded as such and analyses will be conducted to evaluate differences
between program completers and non-completers. Chi-square tests of
association (categorical variables) and independent samples ttests
(continuous variables) will be used to test for differences between
program completers and non-completers. Similarly, although the
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
6
purpose of randomization is to balance the effects of potentially con-
founding variables across treatment groups, chi-square tests of asso-
ciation and ttests will be used to explore whether any such confounds
exist; if so, they will be included as covariates in subsequent analyses.
Sensitivity analyses will also be conducted for variables that could in-
fluence the robustness of results (e.g., program completers; level of
participation). For all analyses, effect size indices will be examined, and
significance testing will be conducted.
The primary aims of this study are (1) to determine whether surf
and hike therapy result in significantly reduced depression symptoms,
and (2) to evaluate whether surf therapy results in greater symptom
reduction than hike therapy. The second aim is based on prior data
indicating a greater effect on mood for activities that occur near water
compared with those that do not [29]. To examine these aims, multi-
level modeling (MLM) will be used to examine depression symptom
trajectories over time for both surf and hike therapy conditions. The
same analytic strategy will be used to examine effects of both inter-
ventions – and any differential effects of each – on secondary outcomes
including PTSD symptom severity, anxiety symptom severity, pain se-
verity, insomnia severity, negative affect, positive affect, and functional
impairment.
To evaluate both immediate and longer-term effects of activity
sessions on psychological and physical symptoms, data from measures
completed before and after each activity session will be analyzed using
an MLM framework; each participant will have up to 12 data points for
each measure (i.e., six pre- and six post-session assessments). MLM will
be used to analyze the data from pre- and post-session assessments in
order to assess changes in symptoms within as well as across sessions.
The use of MLM is particularly advantageous for examining weekly
session data because it can account for variability in the amount of time
between measurements and can retain in analyses participants who
have missing data for one or more sessions.
Rates of remission from MDD (i.e., not meeting diagnostic criteria at
post-program or 3-month follow-up assessments) of service members
who participate in surf therapy versus hike therapy will also be statis-
tically compared using chi-square tests of association. The outcome
measures for this aim will be based on MINI-7 data (i.e., whether di-
agnostic criteria for MDD are met or not) from the post-program and
follow-up assessments (with separate analyses for each assessment).
Chi-square test of association will also be used to compare the number
of participants who did not complete each treatment condition (i.e.,
missed more than two sessions). Logistic regression will be used if
confounds are identified and need to be controlled for in analyses; odds
ratios will provide a measure of effect size.
Independent samples ttests will be used to compare patient sa-
tisfaction with the two interventions at post-program. The outcome
measure for this aim will be the continuous CSQ-8 score derived from
the post-program assessment.
Fitbit data for heart rate, physical activity, and sleep will be ex-
tracted from a non-identifiable data set and converted to an Excel file.
Continuous scores (e.g., average heart rate, number of steps, hours of
sleep) will be created and analyzed using ttests, and indices of effect
size will be calculated.
3. Discussion
For active duty service members and civilians alike, it is imperative
to identify alternative approaches to treating MDD and other related
symptoms that do not rely on traditional psychotherapy or pharma-
cotherapy. Although there are efficacious, evidence-based psy-
chotherapy and pharmacotherapy options for individuals with MDD,
some individuals may not have access to, desire, or benefit from these
treatments. Outdoor physical activity may address these issues given
that it may be readily accessible and could supplement evidence-based
treatments as an adjunctive intervention or prove beneficial as a stand-
alone treatment. Additionally, outdoor physical activity may offer
significant physical health benefits, which could address physical co-
morbidities associated with MDD [87] and other psychological dis-
orders [88]. Interventions involving outdoor physical activity may be
particularly appealing to service members since fitness is a core com-
ponent of mission readiness [89].
Although outdoor recreation programs are commonly offered to
service members and veterans in the United States, there have been few
evaluations of such programs, and those that exist yield limited in-
formation due to methodological shortcomings. Recent meta-analyses
[20,90] concluded that studies investigating the effect of exercise on
depression must improve their methodological rigor across several
domains. Those authors recommended several improvements to study
assessments, including masking assessors to study conditions and in-
creasing the use of validated and objective measures. Additionally, they
advised that exercise studies report greater levels of methodological
detail in order to enable replication of findings. Lastly, the authors also
recommended that longitudinal data be collected, and that these data
assess both activity engagement and symptom change over time.
Our study aims to provide a foundation for further research on
outcomes of outdoor activity programs, and to begin to understand the
specific outcomes of such programs and how they are best achieved. It
incorporates all of these recommendations, and not only increases the
scientific rigor of the extant body of research investigating psycholo-
gical and physical outcomes of exercise and outdoor activity interven-
tions, but also addresses whether water-based activities yield enhanced
benefit over land-based ones. Hike therapy was carefully selected as a
comparison condition because it occurs in a group setting within the
natural environment while differing in the type of environment (land
vs. water). Furthermore, participants in both activities are immersed in
their respective environment settings, and both activities incur similar
energy expenditures. This allows us to isolate the unique effect of water
on participant outcomes. Second, the RCT is conducted in naturalistic
settings (i.e., a military treatment facility; natural environment), which
has the advantage of allowing the use of stringent scientific methods
while maximizing generalizability. The use of minimal exclusion cri-
teria to determine participant eligibility further bolsters general-
izability. Third, data collected from the study use a variety of mod-
alities, with complementary strengths and limitations, including
structured clinical interviews, validated self-reports, and physiological/
activity data. Although some prior research on hiking has utilized
physiological measures, the literature on both hiking and surfing have,
to date, been limited by reliance on self-report measures. The inclusion
of structured clinical interviews and physiological/activity data in the
current study serves to validate data collected through self-report and
also allows for a more comprehensive examination of the range of
outcomes that may be impacted by engaging in outdoor physical ac-
tivity. Finally, the current study design incorporates a 3-month follow-
up, which is the longest for any surf therapy study to date, and com-
parable to the longest that has been used for any hike therapy study
[80]. In addition to the longer-term effects, the study methodology was
intended to test the immediate effects of engaging in each activity. In
combination, data collected in this study will provide evidence re-
garding immediate and longer-term effects of both surf and hike
therapy on a broad range of relevant outcomes, including continued
engagement in the focal physical activities.
Although this study improves considerably on the research metho-
dology used in prior work in this area, it is not without limitations. The
surf and hike therapy programs are both available through the WII
Wellness Program at NMCSD, which provides some assurance that they
follow similar policies, procedures, and schedules. However, there may
be differences between the two programs due to inherent differences in
their focal activities or to differences between instructors and program
managers. Furthermore, optional yoga is provided immediately prior to
the surf therapy program whereas it is not available immediately prior
to the hike therapy program. The influence of optional yoga on surf
outcomes will be statistically explored in a manner consistent with our
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
7
prior work [75], where it was found to have no associations with
treatment outcomes for the overall sample or MDD subsample; this may
be due to the fact that 40% of participants did not attend any of the
optional yoga sessions, and the mean number of yoga sessions attended
was 1.7 (out of a potential 6). Another limitation is that, although both
activities occur in a group-based setting and are administered within
the same department, the extent to which the programs deliver quan-
titatively comparable opportunities for social interaction are unclear. A
third limitation is that the Fitbit Charge 2 devices used in the study are
not water resistant. This creates a difference between conditions in that
participants randomized to the hike condition can wear their device
during their weekly program activity whereas those randomized to the
surf condition cannot. This prohibits a direct comparison of activity
data collected during the respective activity sessions. A fourth limita-
tion derives from the cross-over design, which allows participants to
participate in the other activity option following completion of the
therapy activity to which they were randomized (i.e., to participate in
the activity to which they were not originally randomized or re-en-
rollment in the activity they originally received). This means that some
participants may be participating in the other activity—or additional
“doses” of the original treatment—during the follow-up period. As
mentioned previously, we elected to use this design to maximize re-
cruitment and retention, given that study participants, as service
members, are transient. To statistically address this limitation, partici-
pants who choose the cross-over option are coded as such and will be
examined in sub-analyses. A fifth limitation is that we do not exclude
participants who are receiving current psychotherapy or pharma-
cotherapy due to ethical considerations. Although existing research has
supported exercise as an intervention for individuals with MDD
[21–26,91,92], the data do not conclusively indicate that physical ac-
tivity is superior to (or equally effective as) evidenced-based treatments
(e.g., Refs. [90,93]; as such, we did not want to withhold evidence-
based treatments from participants. Further, our previous research
found that 75% of surf therapy study participants used surf therapy as
an adjunctive treatment to psychotherapy or pharmacotherapy [75];
thus, outcome data for surf therapy as a primary treatment are limited.
In order to investigate the relationship between intervention condition
and concurrent treatments, we are collecting data regarding engage-
ment in various forms of therapy as well as psychotropic medication use
at pre-program, post-program, and 3-month follow-up assessments.
Lastly, the study sample includes active duty service members, but re-
sults could be relevant to populations such as law enforcement, fire-
fighters, and other first responders. However, it is important that any
observed benefits of surf or hike therapy for individuals varying in age
or fitness level be addressed in future research. Furthermore, activity-
based interventions that take place outdoors may require specific en-
vironmental settings or equipment that may not be readily accessible,
thus potentially limiting generalizability.
The current study explores novel interventions—surf and hike
therapy—for treating depression and related symptoms among active
duty service members with MDD. The use of an RCT evaluating these
approaches in a naturalistic setting aims to provide efficacy data that
are externally valid. The study methodology was developed to advance
the current state of surf therapy and outdoor activity research by in-
cluding a comparison group, random assignment, multimodal data, and
a moderately long follow-up period, which sets this study apart from
other research in this area. In addition to understanding the unique
outcomes associated with surf and hike therapy, the study may provide
a methodological framework for future research evaluating outcomes of
outdoor physical activity in both military and civilian settings.
Importantly, results from this RCT will provide information regarding
the extent to which outdoor activities can serve as a potential inter-
vention option for symptoms associated with MDD.
Funding
This work was supported by the U.S. Navy Bureau of Medicine and
Surgery [work unit no. N1600].
Clinical trials identifier
NCT03302611.
Disclaimer
I am a military service member or employee of the U.S.
Government. This work was prepared as part of my official duties. Title
17, U.S.C. §105 provides that copyright protection under this title is not
available for any work of the U.S. Government. Title 17, U.S.C. §101
defines a U.S. Government work as work prepared by a military service
member or employee of the U.S. Government as part of that person's
official duties.
Report No. 19–41 was supported by the U.S. Navy Bureau of
Medicine and Surgery under work unit no. N1600. The views expressed
in this article are those of the authors and do not necessarily reflect the
official policy or position of the Department of the Navy, Department of
Defense, nor the U.S. Government.
The study protocol was approved by the Naval Medical Center San
Diego Institutional Review Board in compliance with all applicable
Federal regulations governing the protection of human subjects.
Research data were derived from an approved Naval Medical Center
San Diego Institutional Review Board protocol number
NMCSD.2017.0007.
Acknowledgments
The authors would like to acknowledge Jody DeLaPeña Murphy,
Renée G. Dell’Aqua, Robyn M. Highfill-McRoy, Andrew M. Kewley,
Casey B. Kohen, James E. LaMar, and Alexandra L. Powell for their
significant efforts on this study. We are grateful to Naval Medical
Center San Diego (NMCSD) and to the Wounded, Ill, and Injured
Wellness Program at NMCSD for their openness to collaborate on this
research study. We deeply thank all surf therapy volunteers, Del Mar
lifeguards, yoga instructors, study participants, and student interns for
their efforts and commitment to these programs. We are also appre-
ciative for the support and hospitality of the Del Mar community.
Additionally, the Challenged Athletes Foundation (including Nico
Marcolango) and the Semper Fi Fund provide considerable support to
the NMCSD Surf Therapy Program and we would like to recognize these
beneficent organizations.
References
[1] K. Blakeley, D.J. Jansen, Post-traumatic Stress Disorder and Other Mental Health
Problems in the Military: Oversight Issues for Congress, (2013) Retrieved from
https://fas.org/sgp/crs/natsec/R43175.pdf.
[2] T. Tanielian, L.H. Jaycox (Eds.), Invisible Wounds of War: Psychological and
Cognitive Injuries, Their Consequences, and Services to Assist Recovery, RAND
Corporation, Santa Monica, CA, 2008.
[3] A.M. Gadermann, C.C.C. Engel, J.A. Naifeh, M.K. Nock, M. Petukhova,
L.P.N. Santiago, R.C. Kessler, Prevalence of DSM-IV major depression among U.S.
military personnel: meta-analysis and simulation, Mil. Med. 177 (Suppl. 8) (2012)
47–59, https://doi.org/10.7205/MILMED-D-12-00103.
[4] R.C. Kessler, M. Petukhova, N.A. Sampson, A.M. Zaslavsky, H. Wittchen, Twelve-
month and lifetime prevalence and lifetime morbid risk of anxiety and mood dis-
orders in the United States, Int. J. Methods Psychiatr. Res. 21 (3) (2012) 169–184
https://doi.org/10.1002/mpr.1359.
[5] G.K. Brown, A.T. Beck, R.A. Steer, J.R. Grisham, Risk factors for suicide in psy-
chiatric outpatients: a 20-year prospective study, J. Consult. Clin. Psychol. 68 (3)
(2000) 371–377, https://doi.org/10.1037/0022-006X.68.3.371.
[6] P. Cuijpers, F. Smit, Excess mortality in depression: a meta-analysis of community
studies, J. Affect. Disord. 72 (3) (2002) 227–236, https://doi.org/10.1016/S0165-
0327(01)00413-X.
[7] A.C. Butler, J.E. Chapman, E.M. Forman, A.T. Beck, The empirical status of cog-
nitive-behavioral therapy: a review of meta-analyses, Clin. Psychol. Rev. 26 (1)
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
8
(2006) 17–31, https://doi.org/10.1016/j.cpr.2005.07.003.
[8] P. Cuijpers, M. Berking, G. Andersson, L. Quigley, A. Kleiboer, K.S. Dobson, A meta-
analysis of cognitive-behavioural therapy for adult depression, alone and in com-
parison with other treatments, Can. J. Psychiatr. 58 (7) (2013) 376–385, https://
doi.org/10.1177/070674371305800702.
[9] S.G. Hofmann, A. Asnaani, I.J. Vonk, A.T. Sawyer, A. Fang, The efficacy of cognitive
behavioral therapy: a review of meta-analyses, Cogn. Ther. Res. 36 (5) (2012)
427–440, https://doi.org/10.1007/s10608-012-9476-1.
[10] S.D. Hollon, A.T. Beck, Cognitive and cognitive behavioral therapies, in:
M.J. Lambert (Ed.), Bergin and Garfield's Handbook of Psychotherapy and Behavior
Change, sixth ed., John Wiley & Sons, Hoboken, NJ, 2013, pp. 393–443.
[11] Jc C. Fournier, R.J. DeRubeis, S.D. Hollon, S. Dimidjian, J.D. Amsterdam,
R.C. Shelton, J. Fawcett, Antidepressant drug effects and depression severity: a
patient-level meta-analysis, J. Am. Med. Assoc. 303 (1) (2010) 47–53, https://doi.
org/10.1001/jama.2009.1943.
[12] A. Khan, R.M. Leventhal, S.R. Khan, W.A. Brown, Severity of depression and re-
sponse to antidepressants and placebo: an analysis of the Food and Drug
Administration database, J. Clin. Psychopharmacol. 22 (1) (2002) 40–45.
[13] P. Cuijpers, A. van Straten, E. Bohlmeijer, S.D. Hollon, G. Andersson, The effects of
psychotherapy for adult depression are overestimated: a meta-analysis of study
quality and effect size, Psychol. Med. 40 (2) (2010) 211–223, https://doi.org/10.
1017/S0033291709006114.
[14] A.G. Bulloch, S.B. Patten, Non-adherence with psychotropic medications in the
general population, Soc. Psychiatry Psychiatr. Epidemiol. 45 (1) (2010) 47–56,
https://doi.org/10.1007/s00127-009-0041-5.
[15] G.I. Papakostas, Tolerability of modern antidepressants, J. Clin. Psychiatry 69
(Suppl. E1) (2008) 8–13.
[16] J.R. Geddes, S.M. Carney, C. Davies, T.A. Furukawa, D.J. Kupfer, E. Frank,
G.M. Goodwin, Relapse prevention with antidepressant drug treatment in depres-
sive disorders: a systematic review, The Lancet 361 (9358) (2003) 653–661,
https://doi.org/10.1016/S0140-6736(03)12599-8.
[17] M. Fava, A.J. Rush, M.H. Trivedi, A.A. Nierenberg, M.E. Thase, H.A. Sackeim,
D.J. Kupfer, Background and rationale for the sequenced treatment alternatives to
relieve depression (STAR*D) study, Psychiatr. Clin. N. Am. 26 (2) (2003) 457–494,
https://doi.org/10.1016/S0193-953X(02)00107-7.
[18] R. Kessler, P. Berglund, O. Demler, R. Jin, D. Koretz, K. Merikangas, P. Wang, The
epidemiology of major depressive disorder: results from the national comorbidity
Survey replication (NCS-r), J. Am. Med. Assoc. 289 (23) (2003) 3095–3105,
https://doi.org/10.1001/jama.289.23.3095.
[19] M. aan het Rot, K.A. Collins, H.L. Fitterling, Physical exercise and depression, MSJM
(Mt. Sinai J. Med.) 76 (2) (2009) 204–214, https://doi.org/10.1002/msj.20094.
[20] S. Rosenbaum, A. Tiedemann, C. Sherrington, J. Curtis, P.B. Ward, Physical activity
interventions for people with mental illness: a systematic review and meta-analysis,
J. Clin. Psychiatry 75 (9) (2014) 964–974, https://doi.org/10.4088/JCP.13r08765.
[21] M. Babyak, J.A. Blumenthal, S. Herman, P. Khatri, M. Doraiswamy, K. Moore,
K.R. Krishnan, Exercise treatment for major depression: maintenance of therapeutic
benefit at 10 months, Psychosom. Med. 62 (5) (2000) 633–638.
[22] L.L. Craft, D.M. Landers, The effect of exercise on clinical depression and depression
resulting from mental illness: a meta-analysis, J. Sport Exerc. Psychol. 20 (4) (1998)
339–357, https://doi.org/10.1123/jsep.20.4.339.
[23] J. Mota-Pereira, J. Silverio, S. Carvalho, J.C. Ribeiro, D. Fonte, J. Ramos, Moderate
exercise improves depression parameters in treatment-resistant patients with major
depressive disorder, J. Psychiatr. Res. 45 (8) (2011) 1005–1011, https://doi.org/
10.1016/j.jpsychires.2011.02.005.
[24] F.B. Schuch, D. Vancampfort, J. Richards, S. Rosenbaum, P.B. Ward, B. Stubbs,
Exercise as a treatment for depression: a meta-analysis adjusting for publication
bias, J. Psychiatr. Res. 77 (2016) 42–51, https://doi.org/10.1016/j.jpsychires.
2016.02.023.
[25] H. Silveira, H. Moraes, N. Oliveira, E.S.F. Coutinho, J. Laks, A. Deslandes, Physical
exercise and clinically depressed patients: a systematic review and meta-analysis,
Neuropsychobiology 67 (2) (2013) 61–68, https://doi.org/10.1159/000345160.
[26] J. Gourgouvelis, P. Yielder, S.T. Clarke, H. Behbahani, B.A. Murphy, Exercise leads
to better clinical outcomes in those receiving medication plus cognitive behavioral
therapy for major depressive disorder, Front. Psychiatry 9 (2018) 37, https://doi.
org/10.3389/fpsyt.2018.00037.
[27] J. Knapen, D. Vancampfort, Y. Moriën, Y. Marchal, Exercise therapy improves both
mental and physical health in patients with major depression, Disabil. Rehabil. 37
(16) (2015) 1490–1495, https://doi.org/10.3109/09638288.2014.972579.
[28] J. Thompson Coon, K. Boddy, K. Stein, R. Whear, J. Barton, M.H. Depledge, Does
participating in physical activity in outdoor natural environments have a greater
effect on physical and mental wellbeing than physical activity indoors? A sys-
tematic review, Environ. Sci. Technol. 45 (5) (2011) 1761–1772, https://doi.org/
10.1021/es102947t.
[29] J. Barton, J. Pretty, What is the best dose of nature and green exercise for improving
mental health? A multi-study analysis, Environ. Sci. Technol. 44 (10) (2010)
3947–3955, https://doi.org/10.1021/es903183r.
[30] E. Britton, G. Kindermann, C. Domegan, C. Carlin, Blue care: a systematic review of
blue space interventions for health and wellbeing, Health Promot. Int. (2018) 1–20,
https://doi.org/10.1093/heapro/day103.
[31] M. Haeffner, D. Jackson-Smith, M. Buchert, J. Risley, Accessing blue spaces: social
and geographic factors structuring familiarity with, use of, and appreciation of
urban waterways, Landsc. Urban Plan. 167 (2017) 136–146, https://doi.org/10.
1016/j.landurbplan.2017.06.008.
[32] American Psychiatric Association, Diagnostic and Statistical Manual of Mental
Disorders, fifth ed., American Psychiatric Association, Washington, DC, 2013.
[33] D.V. Sheehan, Mini International Neuropsychiatric Interview 7.0, Medical
Outcomes Systems, Jacksonville, FL, 2015.
[34] N. Caddick, C. Phoenix, B. Smith, Collective stories and well-being: using a dialo-
gical narrative approach to understand peer relationships among combat veterans
experiencing post-traumatic stress disorder, J. Health Psychol. 20 (2015) 286–299,
https://doi.org/10.1177/1359105314566612.
[35] N. Caddick, B. Smith, C. Phoenix, The effects of surfing and the natural environment
on the well-being of combat veterans, Qual. Health Res. 25 (1) (2015) 76–86,
https://doi.org/10.1177/1049732314549477.
[36] B. Hawkins, J. Townsend, B. Garst, Nature-based recreational therapy for military
service members, Ther. Recreat. J. 50 (2016) 55–74, https://doi.org/10.18666/
TRJ-2016-V50-I1-6793.
[37] J. Marshall, P. Kelly, A. Niven, “When I go there, I feel like I can be myself.”
Exploring programme theory within the Wave Project surf therapy intervention, Int.
J. Environ. Res. Public Health 16 (2019) 2159, https://doi.org/10.3390/
ijerph16122159.
[38] S.A. Montgomery, M. Åsberg, A new depression scale designed to be sensitive to
change, Br. J. Psychiatry 134 (1979) 382–389, https://doi.org/10.1192/bjp.134.4.
382.
[39] K. Kroenke, R. Spitzer, J. Williams, The PHQ-9: validity of a brief depression se-
verity measure, J. Gen. Intern. Med. 16 (9) (2001) 606–613, https://doi.org/10.
1046/j.1525-1497.2001.016009606.x.
[40] K. Kroenke, R.L. Spitzer, J.B. Williams, B. Löwe, An ultra-brief screening scale for
anxiety and depression: the PHQ-4, Psychosomatics 50 (6) (2009) 613–621,
https://doi.org/10.1016/S0033-3182(09)70864-3.
[41] R.L. Spitzer, K. Kroenke, J.B. Williams, B. Löwe, A brief measure for assessing
generalized anxiety disorder: the GAD-7, Arch. Intern. Med. 166 (10) (2006)
1092–1097, https://doi.org/10.1001/archinte.166.10.1092.
[42] F.W. Weathers, B.T. Litz, T.M. Keane, P. Palmieri, B. Marx, P. Schnurr, The PTSD
checklist for DSM-5 (PCL-5) [measurement instrument], Retrieved from, 2013.
https://www.ptsd.va.gov/professional/assessment/adult-sr/ptsd-checklist.asp#
obtain.
[43] F.W. Weathers, D. Blake, P. Schnurr, D. Kaloupek, B. Marx, T. Keane, The Life
events checklist for DSM-5 (LEC-5) [measurement instrument], Retrieved from,
2013. https://www.ptsd.va.gov/professional/assessment/te-measures/life_events_
checklist.asp.
[44] C.A. Blevins, F.W. Weathers, M.T. Davis, T.K. Witte, J.L. Domino, The posttraumatic
stress disorder checklist for DSM-5 (PCL-5): development and initial psychometric
evaluation, J. Trauma. Stress 28 (2015) 489–498, https://doi.org/10.1002/jts.
22059.
[45] J.D. Corrigan, J. Bogner, Initial reliability and validity of the Ohio state university
TBI identification method, J. Head Trauma Rehabil. 22 (6) (2007) 318–329,
https://doi.org/10.1097/01.HTR.0000300227.67748.77.
[46] J. Bogner, J.D. Corrigan, Reliability and predictive validity of the Ohio State
University TBI Identification method with prisoners, J. Head Trauma Rehabil. 24
(4) (2009) 279–291, https://doi.org/10.1097/HTR.0b013e3181a66356.
[47] C.M. Morin, D.H. Barlow, Insomnia: Psychological Assessment and Management vol
104, Guilford Press, New York, NY, 1993.
[48] C.M. Morin, G. Belleville, L. Bélanger, H. Ivers, The Insomnia Severity Index: psy-
chometric indicators to detect insomnia cases and evaluate treatment response,
Sleep 34 (5) (2011) 601–608, https://doi.org/10.1093/sleep/34.5.601.
[49] M. McCaffery, A. Beebe, Pain: Clinical Manual for Nursing Practice, C.V. Mosby
Company, St. Louis, MO, 1989.
[50] D. Watson, L.A. Clark, A. Tellegen, Development and validation of brief measures of
positive and negative affect: the PANAS scales, J. Personal. Soc. Psychol. 54 (6)
(1988) 1063–1070.
[51] G.M. De La Rosa, J.A. Webb-Murphy, S.L. Johnston, Development and validation of
a brief measure of psychological resilience: an adaptation of the Response to
Stressful Experiences Scale, Mil. Med. 181 (3) (2016) 202–208, https://doi.org/10.
7205/MILMED-D-15-00037.
[52] D.C. Johnson, M.A. Polusny, C.R. Erbes, D. King, L. King, B.T. Litz, S.M. Southwick,
Development and initial validation of the response to stressful experiences scale,
Mil. Med. 176 (2) (2011) 161–169, https://doi.org/10.7205/MILMED-D-10-00258.
[53] I. McDowell, Measuring Health: A Guide to Rating Scales and Questionnaires, third
ed., Oxford University Press, New York, NY, 2006.
[54] J.E. Ware Jr., SF-36 health Survey update, Spine 25 (24) (2000) 3130–3139.
[55] G.A. Borg, Psychophysical bases of perceived exertion, Med. Sci. Sport. Exerc. 14
(5) (1982) 377–381.
[56] M.L. Day, M.R. McGuigan, G. Brice, C. Foster, Monitoring exercise intensity during
resistance training using the session RPE scale, J. Strength Cond. Res. 18 (2) (2004)
353–358, https://doi.org/10.1519/R-13113.1.
[57] K.R. Kendrick, S.C. Baxi, R.M. Smith, Usefulness of the modified 0-10 Borg scale in
assessing the degree of dyspnea in patients with COPD and asthma, J. Emerg. Nurs.
26 (3) (2000) 216–222, https://doi.org/10.1016/S0099-1767(00)90093-X.
[58] R.C. Wilson, P.W. Jones, A comparison of the visual analogue scale and modified
Borg scale for the measurement of dyspnoea during exercise, Clin. Sci. 76 (3) (1989)
277–282, https://doi.org/10.1042/cs0760277.
[59] R.C. Wilson, P.W. Jones, Long-term reproducibility of Borg scale estimates of
breathlessness during exercise, Clin. Sci. 80 (4) (1991) 309–312, https://doi.org/
10.1042/cs0800309.
[60] M.J. Chen, X. Fan, S.T. Moe, Criterion-related validity of the Borg ratings of per-
ceived exertion scale in healthy individuals: a meta-analysis, J. Sport. Sci. 20 (11)
(2010) 873–899, https://doi.org/10.1080/026404102320761787.
[61] B. Brewer, J. Van Raalte, D. Linder, Athletic identity: hercules' muscles or Achilles
heel? Int. J. Sport Psychol. 24 (1993) 237–254.
[62] C.L. Craig, A.L. Marshall, M. Sjöström, A.E. Bauman, M.L. Booth, B.E. Ainsworth,
P. Oja, International physical activity questionnaire: 12-country reliability and
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
9
validity, Med. Sci. Sport. Exerc. 195 (9131/03) (2003), https://doi.org/10.1249/
01.MSS.0000078924.61453.FB 3508–1381.
[63] M.K. Dinger, T.K. Behrens, J.L. Han, Validity and reliability of the international
physical activity questionnaire in college students, Am. J. Health Educ. 37 (6)
(2006) 337–343, https://doi.org/10.1080/19325037.2006.10598924.
[64] P.H. Lee, D.J. Macfarlane, T. Lam, S.M. Stewart, Validity of the international
physical activity questionnaire short form (IPAQ-SF): a systematic review, Int. J.
Behav. Nutr. Phys. Act. 8 (1) (2011) 115, https://doi.org/10.1186/1479-5868-8-
115.
[65] A. Bauman, B.E. Ainsworth, F. Bull, C.L. Craig, M. Hagströmer, J.F. Sallis,
M. Sjöström, Progress and pitfalls in the use of the International Physical Activity
Questionnaire (IPAQ) for adult physical activity surveillance, J. Phys. Act. Health 6
(Suppl. 1) (2009) S5–S8, https://doi.org/10.1123/jpah.6.s1.s5.
[66] M. de Zambotti, A. Goldstone, S. Claudatos, I.M. Colrain, F.C. Baker, A validation
study of Fitbit Charge 2™ compared with polysomnography in adults, Chronobiol.
Int. 35 (4) (2018) 465–476, https://doi.org/10.1080/07420528.2017.1413578.
[67] S. Benedetto, C. Caldato, E. Bazzan, D.C. Greenwood, V. Pensabene, P. Actis,
Assessment of the Fitbit Charge 2 for monitoring heart rate, PLoS One 13 (2) (2018)
e0192691, , https://doi.org/10.1371/journal.pone.0192691.
[68] V.E. Salazar, N.D. Lucio, M.D. Funk, Accuracy of Fitbit Charge 2 worn at different
wrist locations during exercise, Proc. Int. J. Exerc. Sci.: Conf. Proc. 2 (9) (2017).
[69] E. Thomson, Validity of heart rate measurements for the apple watch and Fitbit
Charge HR 2, Med. Sci. Sport. Exerc. 50 (5S) (2018) 666, https://doi.org/10.1249/
01.mss.0000538196.40788.41.
[70] I.A. Figueroa, N.D. Lucio, J.L. Gamez Jr., V.E. Salazar, M.D. Funk, Validity of daily
physical activity measurements of Fitbit Charge 2, Int. J. Exerc. Sci.: Conf. Proc. 2
(10) (2018).
[71] K. Li, K. Nuss, E.A. Thomson, A. Comstock, S. Blake, S. Reinwald, B. Tracy,
Validation of overall energy expenditure measurements in the Fitbit Charge HR 2
and apple watch, Med. Sci. Sport. Exerc. 50 (5S) (2018) 661, https://doi.org/10.
1249/01.mss.0000538181.87422.7a.
[72] N.D. Lucio, E.V. Salazar, I.A. Figueroa, J.L. Gamez, R.D. Russell, M.D. Funk,
Accuracy of Fitbit Charge 2 at estimating VO2max, calories, and steps on a tread-
mill, Int. J. Exerc. Sci.: Conf. Proc. 2 (10) (2018).
[73] D.L. Larsen, C.C. Attkisson, W.A. Hargreaves, T.D. Nguyen, Assessment of client/
patient satisfaction: development of a general scale, Eval. Program Plann. 2 (1979)
197–207, https://doi.org/10.1016/0149-7189(79)90094-6.
[74] C.C. Attkisson, R.J. Zwick, The Client Satisfaction Questionnaire: psychometric
properties and correlation with service utilization and psychotherapy outcome,
Eval. Program Plann. 5 (1982) 233–237, https://doi.org/10.1016/0149-7189(82)
90074-X.
[75] K.H. Walter, N.P. Otis, T.N. Ray, A.L. Powell, L.H. Glassman, B. Michalewicz-Kragh,
C.J. Thomsen, Psychol. Sport Exerc. (2019), https://doi.org/10.1016/j.psychsport.
2019.101551.
[76] B.E. Ainsworth, W.L. Haskell, S.D. Herrmann, N. Meckes, D.R. Bassett Jr., C. Tudor-
Locke, A.S. Leon, Compendium of Physical Activities Tracking Guide (n.d),
Retrieved from, https://sites.google.com/site/compendiumofphysicalactivities/.
[77] B.E. Ainsworth, W.L. Haskell, S.D. Herrmann, N. Meckes, D.R. Bassett Jr., C. Tudor-
Locke, A.S. Leon, 2011 Compendium of physical activities: a second update of codes
and MET values, Med. Sci. Sport. Exerc. 43 (8) (2011) 1575–1581, https://doi.org/
10.1249/MSS.0b013e31821ece12.
[78] T. Hartig, M. Mang, G.W. Evans, Restorative effects of natural environment ex-
periences, Environ. Behav. 23 (1) (1991) 3–26, https://doi.org/10.1177/
0013916591231001.
[79] Q. Li, K. Morimoto, M. Kobayashi, H. Inagaki, M. Katsumata, Y. Hirata, T. Kawada,
Visiting a forest, but not a city, increases human natural killer activity and ex-
pression of anti-cancer proteins, Int. J. Immunopathol. Pharmacol. 21 (1) (2008)
117–127, https://doi.org/10.1177/039463200802100113.
[80] M.R. Marselle, K.N. Irvine, S.L. Warber, Examining group walks in nature and
multiple aspects of well-being: a large-scale study, Ecopsychology 6 (3) (2014)
134–147, https://doi.org/10.1089/eco.2014.0027.
[81] R.T. Crawford, The Impact of Ocean Therapy on Veterans with Posttraumatic Stress
Disorder (Doctoral dissertation). Retrieved f rom, ProQuest, 2016 (10252268).
[82] C.M. Rogers, T. Mallinson, D. Peppers, High-intensity sports for posttraumatic stress
disorder and depression: feasibility study of ocean therapy with veterans of
Operation Enduring Freedom and Operation Iraqi Freedom, Am. J. Occup. Ther. 68
(4) (2014) 395–404, https://doi.org/10.5014/ajot.2014.011221.
[83] E. Morita, S. Fukuda, J. Nagano, N. Hamajima, H. Yamamoto, Y. Iwai, ...
T. Shirakawa, Psychological effects of forest environments on healthy adults:
shinrin-yoku (forest-air bathing, walking) as a possible method of stress reduction,
Public Health 121 (1) (2007) 54–63, https://doi.org/10.1016/j.puhe.2006.05.024.
[84] Q. Li, T. Otsuka, M. Kobayashi, Y. Wakayama, H. Inagaki, M. Katsumata, H. Suzuki,
Acute effects of walking in forest environments on cardiovascular and metabolic
parameters, Eur. J. Appl. Physiol. 111 (11) (2011) 2845–2853, https://doi.org/10.
1007/s00421-011-1918-z.
[85] G.X. Mao, X.G. Lan, Y.B. Cao, Z.M. Chen, Z.H. He, Y.D. Lv, Y.A.N. Jing, Effects of
short-term forest bathing on human health in a broad-leaved evergreen forest in
Zhejiang Province, China, Biomed. Environ. Sci. 25 (3) (2012) 317–324, https://
doi.org/10.3967/0895-3988.2012.03.010.
[86] B.J. Park, Y. Tsunetsugu, T. Kasetani, T. Morikawa, T. Kagawa, Y. Miyazaki,
Physiological effects of forest recreation in a young conifer forest in Hinokage
Town, Japan, Silva Fenn. 43 (2) (2009) 291–301.
[87] S. Moussavi, S. Chatterji, E. Verdes, A. Tandon, V. Patel, B. Ustun, Depression,
chronic diseases, and decrements in health: results from the world health surveys,
Lancet 370 (2007) 851–858, https://doi.org/10.1016/S0140-6736(07)61415-9.
[88] S. Rosenbaum, B. Stubbs, P.B. Ward, Z. Steel, O. Lederman, D. Vancampfort, The
prevalence and risk of metabolic syndrome and its components among people with
posttraumatic stress disorder: a systematic review and meta-analysis, Metabolism
64 (8) (2015) 926–933, https://doi.org/10.1016/j.metabol.2015.04.009.
[89] Chief of Naval Operations, Physical Readiness Program Policy Changes (OPNAVINST
6110.1), (2011) Retrieved from https://navadmin.dodreads.com/2018/03/03/
opnavinst-6110-1j-physical-readiness-program-policy-changes/.
[90] G. Cooney, K. Dwan, C. Greig, D. Lawlor, J. Rimer, F. Waugh, G. Mead, Exercise for
depression, Cochrane Database Syst. Rev. (9) (2013) 1–157, https://doi.org/10.
1002/14651858.CD004366.pub6 2013.
[91] J.A. Blumenthal, M.A. Babyak, K.A. Moore, W.E. Craighead, S. Herman, P. Khatri,
P.M. Doraiswamy, Effects of exercise training on older patients with major de-
pression, Arch. Intern. Med. 159 (19) (1999) 2349–2356, https://doi.org/10.1001/
archinte.159.19.2349.
[92] J.A. Blumenthal, M.A. Babyak, P.M. Doraiswamy, L. Watkins, B.M. Hoffman,
K.A. Barbour, A. Hinderliter, Exercise and pharmacotherapy in the treatment of
major depressive disorder, Psychosom. Med. 69 (7) (2007) 587–596, https://doi.
org/10.1097/PSY.0b013e318148c19a.
[93] P. Ekkekakis, Honey, I shrunk the pooled SMD! Guide to critical appraisal of sys-
tematic reviews and meta-analyses using the Cochrane review on exercise for de-
pression as example, Ment. Health Phys. Act. 8 (2015) 21–36, https://doi.org/10.
1016/j.mhpa.2014.12.001.
[94] QualityMetric Inc. SF-36v2: Short Form Health Survey Instrument - 36 Item Version
(Version 2). Lincoln, RI.
K.H. Walter, et al. Contemporary Clinical Trials Communications 16 (2019) 100435
10
... With the exception of one study (Snelling, 2015), all programs that have published results reported benefits to participants. These benefits have been measured primarily through observational pretest-posttest designs on outcomes such as wellbeing and health although there have been two studies that utilized a randomized controlled trial design (Snelling, 2015;Walter, et al., 2019a). While the observational pretest-posttest design is an accepted practice among community-based organizations, and serves as a means of reporting to funders -critical to program sustainability -it does not offer sufficient rigor to clearly provide causal inference for changes in outcomes. ...
... RCTs -a design where each participant is equally likely to be assigned to an intervention/group within a study -provide rigorous evidence for intervention efficacy. Although RCTs have been used in the field of surf therapy (e.g., Snelling, 2015;Walter et al., 2019a), these trials may not be feasible in some surf therapy programs due to practical, ethical, or resource limitations. To date, the majority of surf therapy research has focused on program evaluation that measures changes in participants over the course of a surf therapy program. ...
... This 'blue gym' provides strength training, balance rehabilitation as well as cognitive performance, which may increase the maintenance of autonomy. Also, it may work as group supportive therapy (Fleischmann et al., 2011;Rogers et al., 2014;Caddick et al., 2015;Pérez et al., 2017;Walter et al., 2019). Other social benefits identified involved local communities, which may profit from surf tourism in the form of socio-cultural benefits, Fig. 6. ...
Article
Full-text available
Marine ecosystems contribute to human well-being, e.g. through the promotion of nature-based recreational activities such as surfing, which is a benefit obtained from Cultural Ecosystem Services (CES). Our research objective is to identify the benefits and impacts associated to surfing, and who are the main affected subjects and/or objects, achieving a better understanding of the sustainability status of this recreational activity. To this end, a bibliometric study and systematic review was carried out for the period 1965–2021. Benefits and impacts were collated and grouped according to their dimensional focus and type of effects in 6 groups (3-dimensional focus × 2 type of effects). The results revealed that since the beginning of 21st century surfing research topics are growing and diversifying. This review shows that implications of surfing go beyond direct users (i.e., surfers) and has consequences in diverse dimensions (environmental, socio cultural and economic), involving many stakeholders (e.g., scientific, and local communities). Most of the pieces of evidence collated in this research were related with the people who practice the activity and its social implications (psychological benefits as main benefit and injuries as main impact). Following an interdisciplinary approach, we obtained a holistic understanding of the surfing activity, not only in terms of the different dimensions addressed but on the sectors of the society that obtain benefits or are impacted by the activity. All of them should be considered and integrated to guarantee the sustainable management of this CES benefit.
Article
Full-text available
O presente trabalho caracteriza-se como uma revisão sistemática de estudos que tenham utilizado medidas psicológicas para avaliar atletas e praticantes de surfe. Utilizando os descritores “Surf” AND “Sport” e “Surf” AND “Psychology”, após aplicação dos critérios de exclusão, obteve-se uma amostra final de 28 artigos. Foram identificados estudos diversificados explorando aspectos psicológicos diferenciados nesse contexto, como questões de gênero, processos psicossociais, produção da subjetividade, efeitos terapêuticos e aspectos psicológicos concernentes ao universo da competição. Os resultados foram discutidos em categorias temáticas específicas, dentre as quais, destacam-se o estudo de processos psicológicos diretamente associados à prática do surfe; produções sobre o potencial terapêutico desencadeado pela prática do surfe; e também algumas evidências sobre efeitos adversos, principalmente no contexto competitivo. As evidências reforçam a necessidade da assistência psicológica aos atletas de alto rendimento para promoção e a manutenção da saúde mental, bem como para melhorias no desempenho esportivo.
Book
Full-text available
The present work consists of the meeting of works of researchers and professionals linked to the field of Psychology of Sport and related areas, which address surfing and many of its aspects socio-cultural and psychological. Counting with authors linked to various research groups from various regions of Brazil, the book features a compilation of texts, which contribute to that the reader can have a expanded view of the world social and the subjective dynamics that configures surfing as a body and sport practice.
Article
Full-text available
There is increasing interest in the potential use of outdoor water environments, or blue space, in the promotion of human health and wellbeing. However, therapeutic nature-based practices are currently outpacing policy and the evidence base for health or wellbeing benefits of therapeutic interventions within blue space has not been systematically assessed. This systematic review aims to address the gap in understanding the impacts of blue space within existing interventions for targeted individuals. A systematic review was carried out, searching Google Scholar, SCOPUS, PubMed, etc. through to August 2017. Only blue space interventions were included that were specifically designed and structured with a therapeutic purpose for individuals with a defined need and did not include nature-based promotion projects or casual recreation in the outdoors. Thirty-three studies met the inclusion criteria and were assessed. Overall, the studies suggest that blue care can have direct benefit for health, especially mental health and psycho-social wellbeing. The majority of papers found a positive or weak association between blue care and health and wellbeing indicators. There was also some evidence for greater social connectedness during and after interventions, but results were inconsistent and mixed across studies with very few findings for physical health. This is the first systematic review of the literature on blue care. In summary, it has been shown that mental health, especially psycho-social wellbeing, can be improved with investment in blue spaces. Key areas for future research include improving understanding of the mechanisms through which blue care can improve public health promotion.
Article
Full-text available
Mental health issues in young people are a priority for health and social care. Surf therapy is an innovative intervention that may help address this health burden globally. While increasing evidence demonstrates the effectiveness of surf therapy, there has been limited exploration as to how it achieves its outcomes. Such theoretical exploration is important for service optimisation, monitoring and proliferation. This research aimed to adopt, for the first time, a rigorous grounded theory approach to explore underlying programme theory within the Wave Project surf therapy intervention. Participants (n = 22, 14 males and 8 females; mean age = 14 years, SD = 3.5, range 8–23) were interviewed about their intervention experiences. Data were analysed through constant comparative analysis and memo writing. Two core categories reflected mediators by which surf therapy may achieve its outcomes: “Self-Selected Pacing and Progression While Surfing” and “Creation of Emotional and Physical Safe Space at Beach”. Three antecedent (linking known inputs to core categories) and three consequent categories (linking core categories to associated outputs) were also identified. These demonstrate theorised pathways from known inputs to associated outcomes within the intervention. These important findings provide plausible evidence on how to optimise the Wave Project’s delivery in tackling mental health burden.
Article
Full-text available
Objective The aim of this study is to investigate the effects of exercise as an add-on therapy with antidepressant medication and cognitive behavioral group therapy (CBGT) on treatment outcomes in low-active major depressive disorder (MDD) patients. We also explored whether exercise reduces the residual symptoms of depression, notably cognitive impairment and poor sleep quality, and aimed to identify putative biochemical markers related to treatment response.Methods Sixteen low-active MDD patients were recruited from a mental health day treatment program at a local hospital. Eight medicated patients performed an 8-week exercise intervention in addition to CBGT, and eight medicated patients attended the CBGT only. Twenty-two low-active, healthy participants with no history of mental health illness were also recruited to provide normal healthy values for comparison.ResultsResults showed that exercise resulted in greater reduction in depression symptoms (p = 0.007, d = 2.06), with 75% of the patients showing either a therapeutic response or a complete remission of symptoms vs. 25% of those who did not exercise. In addition, exercise was associated with greater improvements in sleep quality (p = 0.046, d = 1.28) and cognitive function (p = 0.046, d = 1.08). The exercise group also had a significant increase in plasma brain-derived neurotrophic factor (BDNF), p = 0.003, d = 6.46, that was associated with improvements in depression scores (p = 0.002, R2 = 0.50) and sleep quality (p = 0.011, R2 = 0.38).Conclusion We provide evidence that exercise as an add-on to conventional antidepressant therapies improved the efficacy of standard treatment interventions. Our results suggest that plasma BDNF levels and sleep quality appear to be good indicators of treatment response and potential biomarkers associated with the clinical recovery of MDD.
Article
Full-text available
Fitness trackers are devices or applications for monitoring and tracking fitness-related metrics such as distance walked or run, calorie consumption, quality of sleep and heart rate. Since accurate heart rate monitoring is essential in fitness training, the objective of this study was to assess the accuracy and precision of the Fitbit Charge 2 for measuring heart rate with respect to a gold standard electrocardiograph. Fifteen healthy participants were asked to ride a stationary bike for 10 minutes and their heart rate was simultaneously recorded from each device. Results showed that the Fitbit Charge 2 to underestimates the heart rate. Although the mean bias in measuring heart rate was modest -6 bpm (95% CI: -6.11 to -5.60 bpm), the limits of agreement, which indicate the precision of individual measurements, between the Fitbit Charge 2 and criterion measure were wide (+17 to -29 bpm) indicating that an individual heart rate measure could plausibly be underestimated by almost 30 bpm.
Article
Full-text available
Are urban waterways amenities, and if so, are there inequities in household access? While urban waterways represent a potential site for access to nature within the urban environment, there have been few studies on the accessibility and interactions with water features in particular, what we refer to as “blue spaces." This study drew on a sample of households in Northern Utah living in neighborhoods with a nearby river or canal to ask if local waterways provide positive impacts to households and if proximity to them increased the likelihood of households spending time at them and being familiar with them. We used multivariate regression to demonstrate that socio-structural and accessibility characteristics shape patterns of familiarity and use, and mediate the impacts of blue space characteristics on households. We found evidence supporting the idea that urban waterways are positive amenities for neighborhood quality of life. We also found that the farther away a household lived from the blue space, the less likely they were to be aware of or use the amenity. Surprisingly, we also found that while high socio-economic status (SES) and white respondents generally lived further from points of access to urban waterways, they reported higher familiarity and were more likely to spend time at them than lower SES and nonwhite Hispanic households. Results suggest that future research and community engagement related to urban blue spaces should be attentive to how social structure and the characteristics of the built environment mediate access to these amenities.
Article
Objectives: Although surf programs for individuals with psychological and physical conditions exist, data evaluating such programs are limited. This study examined psychological outcomes among 74 active duty service members participating in the Naval Medical Center San Diego surf therapy program. Design: The study used a single-group, longitudinal design involving repeated measurement to assess outcomes following the program and within sessions. Method: Service members completed self-report questionnaires before and after the 6-week program and before and after each surf therapy session. Results: Total scores for symptoms of depression (β = −2.31, p < .01), anxiety (β = −3.55, p < .001), PTSD (probable PTSD subgroup only; β = −14.55, p < .001), and negative affect (β = −6.40, p < .001) significantly decreased from pre-to post-program, while positive affect significantly increased (β = 9.46, p < .001). During each session, depression/anxiety symptoms significantly lessened (β = −3.35, p < .001) and positive affect significantly improved (β = 8.97, p < .001). The magnitude of within-session changes did not differ across sessions (p > .05). Results for subgroups with probable PTSD or major depressive disorder were comparable to those of the full sample. Conclusions: Immediate benefits of surf therapy included significantly reduced depression/anxiety and increased positive affect. As a complementary intervention, surf therapy may improve depression, anxiety, and PTSD symptoms with potentially unique benefits on affect.
Article
We evaluated the performance of a consumer multi-sensory wristband (Fitbit Charge 2™), against polysomnography (PSG) in measuring sleep/wake state and sleep stage composition in healthy adults. In-lab PSG and Fitbit Charge 2™ data were obtained from a single overnight recording at the SRI Human Sleep Research Laboratory in 44 adults (19—61 years; 26 women; 25 Caucasian). Participants were screened to be free from mental and medical conditions. Presence of sleep disorders was evaluated with clinical PSG. PSG findings indicated periodic limb movement of sleep (PLMS, > 15/h) in nine participants, who were analyzed separately from the main group (n = 35). PSG and Fitbit Charge 2™ sleep data were compared using paired t-tests, Bland–Altman plots, and epoch-by-epoch (EBE) analysis. In the main group, Fitbit Charge 2™ showed 0.96 sensitivity (accuracy to detect sleep), 0.61 specificity (accuracy to detect wake), 0.81 accuracy in detecting N1+N2 sleep (“light sleep”), 0.49 accuracy in detecting N3 sleep (“deep sleep”), and 0.74 accuracy in detecting rapid-eye-movement (REM) sleep. Fitbit Charge 2™ significantly (p < 0.05) overestimated PSG TST by 9 min, N1+N2 sleep by 34 min, and underestimated PSG SOL by 4 min and N3 sleep by 24 min. PSG and Fitbit Charge 2™ outcomes did not differ for WASO and time spent in REM sleep. No more than two participants fell outside the Bland–Altman agreement limits for all sleep measures. Fitbit Charge 2™ correctly identified 82% of PSG-defined non-REM–REM sleep cycles across the night. Similar outcomes were found for the PLMS group. Fitbit Charge 2™ shows promise in detecting sleep-wake states and sleep stage composition relative to gold standard PSG, particularly in the estimation of REM sleep, but with limitations in N3 detection. Fitbit Charge 2™ accuracy and reliability need to be further investigated in different settings (at-home, multiple nights) and in different populations in which sleep composition is known to vary (adolescents, elderly, patients with sleep disorders).