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Viewing an alpine environment positively affects emotional analytics in patients with somatoform, depressive and anxiety disorders as well as in healthy controls

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Background: Patients with somatoform, depressive or anxiety disorders often don't respond well to medical treatment and experience many side effects. It is thus of clinical relevance to identify alternative, scientifically based, treatments. Our approach is based on the recent evidence that urbanicity has been shown to be associated with an increased risk for mental disorders. Conversely, green and blue environments show a dose-dependent beneficial impact on mental health. Methods: Here we evaluate the effect of viewing stimuli of individuals in an alpine environment on emotional analytics in 183 patients with psychiatric disorders (mostly somatoform, depressive and anxiety disorders) and 315 healthy controls (HC). Emotional analytics (valence: unhappy vs happy, arousal: calm vs excited, dominance: controlled vs in control) were assessed using the Self-Assessment Manikin. Further parameters related to mental health and physical activity were recorded. Results: Emotional analytics of patients indicated that they felt less happy, less in control and had higher levels of arousal than HC when viewing neutral stimuli. The comparison alpine>neutral stimuli showed a significant positive effect of alpine stimuli on emotional analytics in both groups. Patients and HC both felt attracted to the scenes displayed in the alpine stimuli. Emotional analytics correlated positively with resilience and inversely with perceived stress. Conclusions: Preventive and therapeutic programs for patients with somatoform, depressive and anxiety disorders should consider taking the benefits of natural outdoor environments, such as alpine environments, into account. Organizational barriers which are preventing the implementation of such programs in clinical practice need to be identified and addressed.
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R E S E A R C H A R T I C L E Open Access
Viewing an alpine environment positively
affects emotional analytics in patients with
somatoform, depressive and anxiety
disorders as well as in healthy controls
Katharina Hüfner
1*
, Cornelia Ower
1
, Georg Kemmler
2
, Theresa Vill
1
, Caroline Martini
1
, Andrea Schmitt
3,4
and
Barbara Sperner-Unterweger
1
Abstract
Background: Patients with somatoform, depressive or anxiety disorders often dont respond well to medical
treatment and experience many side effects. It is thus of clinical relevance to identify alternative, scientifically based,
treatments. Our approach is based on the recent evidence that urbanicity has been shown to be associated with
an increased risk for mental disorders. Conversely, green and blue environments show a dose-dependent beneficial
impact on mental health.
Methods: Here we evaluate the effect of viewing stimuli of individuals in an alpine environment on emotional
analytics in 183 patients with psychiatric disorders (mostly somatoform, depressive and anxiety disorders) and 315
healthy controls (HC). Emotional analytics (valence: unhappy vs happy, arousal: calm vs excited, dominance:
controlled vs in control) were assessed using the Self-Assessment Manikin. Further parameters related to mental
health and physical activity were recorded.
Results: Emotional analytics of patients indicated that they felt less happy, less in control and had higher levels of
arousal than HC when viewing neutral stimuli. The comparison alpine>neutral stimuli showed a significant positive
effect of alpine stimuli on emotional analytics in both groups. Patients and HC both felt attracted to the scenes
displayed in the alpine stimuli. Emotional analytics correlated positively with resilience and inversely with perceived
stress.
Conclusions: Preventive and therapeutic programs for patients with somatoform, depressive and anxiety disorders
should consider taking the benefits of natural outdoor environments, such as alpine environments, into account.
Organizational barriers which are preventing the implementation of such programs in clinical practice need to be
identified and addressed.
Keywords: Alpine environment, Resilience, Self-perceived stress, Self-Assessment Manikin, Emotional analytics,
Somatoform, depressive and anxiety disorders
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* Correspondence: katharina.huefner@tirol-kliniken.at
1
Department of Psychiatry, Psychotherapy and Psychosomatics, Divison of
Psychiatry II (Psychosomatic Medicine), Medical University Innsbruck, Anichstr.
35, 6020 Innsbruck, Austria
Full list of author information is available at the end of the article
Hüfner et al. BMC Psychiatry (2020) 20:385
https://doi.org/10.1186/s12888-020-02787-7
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Background
The natural environment is known to improve physical
and mental health: A meta-analysis reported an 8%
reduction in all-cause mortality for residents with the
highest nature outdoor exposure compared with the
lowest exposure group [14]. Discovering blue [11] and
green [43] spaces is associated with psychological
benefits. Stress partly mediates the effect of natural out-
door environments on mental well-being [39]. Green
spaces have been shown to reduce cortisol levels as a
marker of stress [40]. Stress as an important marker of
mental health is significantly reduced by the exposure to
nature in a dose-response relationship, even if only visual
stimulation without physical exposure is used [17]. Vis-
ual or auditory nature stimuli can facilitate recovery
from psychological stressful events [1,5] and from phys-
ical disease [41]. In mental health, chronic stress is
among the strongest risk factors for depression but is
also an important pathogenetic factor in anxiety disor-
ders, post-traumatic stress disorders or somatoform dis-
orders [2,35].
Another factor through which exposure to natural
outdoor environments exerts its positive effect on
mental health might be through the strengthening of
resilience [33,34]. Resilience can be defined as ones
ability to cope with and recover from adverse life events.
Resilience is improved by physical activity performed in
a natural outdoor environment but is not associated with
physical activity performed indoors [32]. When the
natural environment is used to perform physical activity
the positive effects of physical activity and natural
environments can be combined: there is evidence that
exercising outdoors results in greater improvements of
mental well-being than exercising indoors with greater
feelings of delight, energy and revitalization, as well as
decreases in frustration, tiredness and anger [38].
The positive effects of the alpine natural environment
have rarely been examined. One of the few available
studies suggests that watching grand mountain scenes
triggers a greater mood improvement than mundane
nature. Furthermore, participants were feeling signifi-
cantly more connected to others, more caring, and
more spiritual after watching awe-inspiring nature con-
dition [20]. Hikers of alpine wilderness trails reported
substantial stress reduction and mental rejuvenation
following a day or overnight hike [8]. Furthermore, in a
crossover trial focusing on differences between indoor
and alpine activity, mountain hiking showed signifi-
cantly greater positive effects on affective valence and
activation compared to indoor physical activity [29]. It
is unknown whether the mechanisms linking different
natural environments (green space, blues space, alpine)
to mental health are due to similar or differential effects
[13,28].
Although studies report an improvement on various
psychological measures as a result of exposure to
alpine environments, they do not refer to a possible
therapeutic effect. There are only few studies investi-
gating therapeutic alpine interventions as treatment
for patients in mental health care. In a mountain hik-
ing program for suicidal patients, participants
reported significant reduction in depression, hopeless-
ness and suicidal ideation [37]. In another study
adults and youth with mental illness experienced
significant improvements in self-esteem, mastery and
resilience following activities like mountain biking and
raft building [4].
The primary aim of the present study was to investi-
gate whether stimuli depicting alpine environments
would elicit differential or similar emotional analytics in
patients with somatoform, depressive and anxiety disor-
ders and healthy controls in order to judge the potential
usefulness for a therapeutic intervention program. This
aim was approached by the following study setting:
1) We assessed emotional analytics upon viewing
neutral and alpine stimuli in patients with
somatoform, depressive and anxiety disorders and
healthy controls. The alpine stimuli depicted
individuals while engaged in physical activity in an
alpine environment.
2) We investigated whether there was a correlation of
emotional analytics with resilience or perceived
stress in patients and healthy controls.
3) We measured the amount of self-performed
physical activity in an alpine environment as a
marker of previous exposure to the depicted stimuli
in a natural environment.
Methods
Study design
This is a cross-sectional observational study including a
quasi-experimental part (Fig. 1). The whole study was
performed online. The first part of the study contained
questionnaires, while the second part recorded emo-
tional reaction to visual stimuli. It was not possible to
skip one question or a questionnaire. The current data is
part of a larger study examining the effect of physical ac-
tivity in an alpine environment on mental health, part of
which has been published [32]. Innsbruck is one of few
urban spaces located directly within the Alps and thus
allows for easy access to the alpine environment. The
ethics commission of the Medical University of Inns-
bruck reviewed and approved the study protocol. After
being informed in detail about the study aims and proce-
dures, participants provided informed consent prior to
study participation. Study recruitment was conducted
over a four-month period in 2016.
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Participants
Participants and recruiting procedure are described in
[32], participant numbers vary slightly compared to
the previous publication due to missing data in indi-
vidual participants. In brief, a total of 1029 individuals
participated in an open online-only survey. They were
recruited via email (mailing lists), social media and
classified websites or whilst treated at the Department
of Psychiatry, Psychotherapy and Psychosomatics
(Division of Psychiatry II/Psychosomatic Medicine) at
Innsbruck Medical University at the inpatient or
outpatient clinic. We included mainly patients with
the diagnosis of somatoform, depressive and anxiety
disorders. For the present analysis participants who
terminated the questionnaire early i.e. prior to the
Self-Assessment Manikin (SAM) ratings (missing data
n= 436, Fig. 2) were excluded from the study. This
high drop-out rate was mainly due to the fact that
SAM ratings of emotional analytics were performed
as the final phase of the questionnaire and it was not
possible to skip questions. Comparison of participants
terminating early with those included in the data
analysis showed that the former were significantly
older (mean age ± standard deviation, 33.5 ± 12.1 years
vs 29.7 ± 10.1 years, p< 0.001, Mann-Whitney U-test)
and that a larger proportion of them was female
(68.4% vs 61.2%, p= 0.017, Chi-square test). Despite
statistical significance, the differences in age (effect
size d = 0.34) and sex distribution (odds ratio = 1.37)
were comparatively small. Furthermore participants
that reported implausible values (n= 8), screened
positively for alcohol abuse only (n=54) or for an
eating disorder only (Anorexia nervosa and Bulimia
nervosa; n= 33) were excluded from the present
analysis (Fig. 2). In Anorexia nervosa or Bulimia
nervosa it is known that high levels of PA are used
as tool for losing weight and therefore are an expres-
sion of disease. Therefore, these patients were
excluded [3]. There were 4 to 13% missing values for
individual SAM ratings. The 498 participants included
in the present analysis consisted of two groups.
Patients screened positively for mental health disorder
on the Patient Health Questionnaire (PHQ, n= 183).
Participants without positive PHQ screening (n= 315)
formed the control group (HC).
Fig. 1 Flow chart of the overall study design including details of the
quasi experimental part with presentation of alpine stimuli and
emotional analytic ratings (boxed section shaded in grey). Specific
questionnaires are indicated. BRS = Brief Resilience Scale, GPAQ =
General Physical Activity Questionnaire, PHQ = Patient Health
Questionnaire, PSS = Perceived Stress Scale. () indicates that there
were questionnaires at the indicated point in the study design not
analyzed in the current study but in [32]
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Stimuli
Stimuli were alternating 5 neutral pictures (re-staged to
official International Affective Picture System (IAPS)
pictures (slide no. 6150, 7009, 5661, 5500, 7150)) and 5
alpine stimuli (Fig. 3). Neutral pictures displayed figural
subjects of daily life (e.g. mug, wall, umbrella). Alpine
stimuli displayed alpine environments with individuals
performing some sort of physical activity therein (e.g.
hiking, biking, skiing). The pictures were presented to all
participants in the same order. Two picture stimuli had
to be excluded due to considerations related to the
displayed content (canyon wall in the neutral stimuli
and paraglider in the mountains in the alpine stimuli)
and their mean ratings for at least one of the analyzed
dimensions ranging two standard deviations outside the
mean of the other stimuli in the group. Pictures were
displayed for 5 seconds before the page with the emo-
tional analytic ratings appeared. Each stimulus could
only be observed once (Fig. 1).
Measures
Socio-demographic parameters included information on
age, sex, education and marital status. Mental health was
assessed using the German version of Patient Health
Fig. 2 Flowchart of patient and healthy control recruitmen. Excluded cases terminated early, reported implausible values or had a single diagnose
of alcohol abuse or eating disorder. Abbreviations: BRS = Brief Resilience Scale, GPAQ = General Physical Activity Questionnaire, PHQ = Patient
Health Questionnaire, PSS = Perceived Stress Scale, SAM ratings = Self-Assessment Manikin for emotional analytic ratings. () indicates that there
were questionnaires at the indicated point in the study design not analyzed in the current study but in [32]
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Questionnaire [16]. Additionally, open text fields were
provided for entering psychiatric diagnoses. Resilience
was measured using the Brief Resilience Scale (BRS)
[36], self-perceived stress using the Perceived Stress
Scale (PSS) [7] and physical activity (PA) using the
Global Physical Activity Questionnaire (GPAQ-2) [6].
PA is calculated using metabolic equivalents of tasks
(METs) as a unit for energy expense. As proposed by the
World Health Organization we classified PA in
moderate and vigorous intensity. We adapted the
standard questionnaire to measure PA performed in the
alpine environment.
To measure emotional response we used the Self-
Assessment Manikin (SAM) 9-point Likert-scale. This
scale measures emotional analytics in the three
dimensions valence, arousal and dominance [25]. The
valence scale ranges from a frowning, unhappy (adjec-
tives used in the SAM manual: unhappy, annoyed,
unsatisfied, melancholic, despaired, bored; lower
values) to a smiling, happy figure (happy, pleased,
satisfied, contented, hopeful). The arousal scale
displays the lowest value with a calm, eyes-closed
figure (relaxed, calm, sluggish, dull, sleepy, unar-
oused), whilst the highest value is represented by an
excited figure (stimulated, excited, frenzied, jittery,
wide-awake, aroused). The lowest values in the
dominance scale are symbolized by a controlled small
figure (controlled, influenced, cared-for, awed, submis-
sive, guided) whilst highest values are represented by
a dominant and oversized figure (controlling, influen-
tial, in control, important, dominant, autonomous).
After presenting a picture for 5 seconds participants
were asked to rate their emotional reaction in the
three dimensions. For alpine stimuli, we added a
fourth dimension asking about ones attraction to the
situation, labelled motivational direction. The 9-point
Likert-scale ranged from Idontwanttobeinthis
situationto I want to be in the situation.
Statistical methods
Metric variables were analyzed for normal distribution
prior to applying further statistical tests by assessing
their skewness and their kurtosis, considering skewness
values > 0.5 or < 0.5 [27] and kurtosis values > 1 or <
1[18] as deviations from a normal distribution requiring
non-parametric testing. To compare emotional reactions
between overall neutral and alpine pictures we created a
mean score for each category. In each category one
picture was excluded due to statistical outliers (paraglide
in alpine pictures; red wall in neutral pictures). Mean
scores were calculated for each emotional dimension per
person if at least three scores were completed. Group
comparisons (patients vs. HC) were performed using t-
test, Mann-Whitney U-test and Chi-square test, depend-
ing on the variable type and distribution. As the two
groups differed significantly in their age, education,
marital status, and work situation, we also performed
analyses of covariance with adjustment for these poten-
tial confounders. As the emotional analytic ratings
displayed missing values (4 to 13%), we performed an
additional analysis where missing ratings were replaced
by imputed values. The SPSS Missing Value Analysis
procedure with Littles test for missingness completely at
random (MCAR) and imputation by expectation-
maximization (EM) was used for this purpose [19]. The
relationship between resilience, self-perceived stress, PA
and emotional analytics was investigated on a descriptive
level by means of correlation analysis. Spearman rank
correlation coefficients were used as most the variables
involved showed deviations from a normal distribution.
Results
Sociodemographic characteristics and clinical features
The sociodemographic characteristics of patients and
HC are displayed in Table 1. Patientsdiagnoses accord-
ing to PHQ were in decreasing frequency: somatoform
disorder (n= 101, 55.2%), major depressive syndrome
Fig. 3 Examples of alpine stimuli depicting individuals performing physical activity in an alpine environment. Neutral stimuli are not depicted
since this is not considered good scientific practice for the IAPS picture collection [25]
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(n= 67, 36.6%), other anxiety syndrome (n= 45, 24.6%),
panic syndrome (n= 36, 19.7%), other depressive
syndrome (n= 34, 18.6%), alcohol abuse (n= 31, 16.9%),
binge eating disorder (n= 23, 12.6%), bulimia nervosa
(n= 10, 5.5%) and others (n= 2, 1.1%). More than half
of the patients (n= 100, 51.9%) were diagnosed with
more than one mental health disorder, the most preva-
lent combination was somatoform disorder and major
depressive syndrome (n= 42, 23.0%).
Comparison of resilience, self-perceived stress and
emotional analytics in patients and HC
The mean score of the Brief Resilience Scale (BRS) was
significantly lower in patients than in HC (Mann-Whitney
U-test, p<0.001; Table 2). Furthermore the total score of
the Preceived Stress Scale (PSS) was significantly higher in
patients than in HC (Mann-Whitney U-test, p<0.001;
Table 2).
Comparing the mean emotional analytics score in
neutral and alpine stimuli, patients reported significantly
lower values for valence (both ps < 0.001) indicating that
they felt less happy than HC, and dominance (neutral: p=
0.021, alpine: p< 0.001; Table 2)indicatingthattheyfelt
less in control than HC. Arousal when viewing neutral
stimuli was significantly higher (p< 0.001) for patients in-
dicating that they felt more aroused or jittery than the HC
at baseline. In alpine pictures the difference in arousal was
not significant between patients and HC (p=0.223; Table
2). In the fourth dimension asking about attraction to the
displayed alpine situation, the mean score was significantly
lower in patients as in HC (p< 0.001 Table 2)although
both groups showed a high attraction to the alpine stimuli.
All statistically significant differences in Table 2remained
significant when adjusting for age, education, marital sta-
tus, and work situation by analysis of covariance. Missing
value analysis for emotional analytics revealed that SAM
ratings were not missing completely at random (Littles
test, χ
2
= 3607.5, d.f. = 3314, p< 0.001). Replacement of
missing emotional analytics ratings by the EM imputation
method led to comparable results as the analysis without
replacement. Mean ratings changed by less than 0.1 in
both groups. Moreover, all significant group differences
were retained.
To measure the effect of the alpine stimuli normalized
to the neutral baseline, we evaluated the difference of each
emotional dimension between alpine and neutral pictures.
The comparison alpine > neutral stimuli was significantly
greater than 0 for both patients and HC indicating a
positive effect of alpine stimuli on emotional analytics. For
valence and dominance this comparison of alpine > neu-
tral stimuli did not differ significantly between patients
and HC (Table 2). For arousal the difference was signifi-
cantly smaller in patients than in HC due to higher base-
line arousal values in patients (p<0.001; Table2).
Table 1 Sociodemographic characteristics of patients and healthy controls (adapted with participant numbers for the current
analysis from [32])
Variable Groups Comparison
Patients (n= 183) Controls (n= 315) Test statistics D.f. p-value
Age in years
a
36.0 ± 12.8 32.8 ± 11.7 Z = 2.42
c
0.016
Female gender
b
117 (63.9) 187 (58.4) χ
2
= 1.02
d
1 0.313
Education
b
–– χ
2
= 30.989
d
3 < 0.001
University 41 (22.4) 111 (35.2) ––
Secondary school 62 (33.9) 133 (42.2) ––
Vocational training 53 (29.0) 34 (10.8) ––
Compulsory school and other 27 (14.8) 37 (11.7) ––
Marital status
b
–– χ
2
= 13.699
d
2 0.001
Single 105 (57.4) 194 (61.6) ––
Married 56 (30.6) 110 (34.9) ––
Separated/divorced/widowed 22 (12.0) 11 (3.5) ––
Employment
b
–– χ
2
= 66.81
d
2 < 0.001
Full/part-time employment 75 (41.0) 177 (56.2)
In education/study/vocational training 49 (26.8) 122 (38.7)
Unemployed 59 (32.2) 16 (5.1)
a
mean ± standard deviation
b
absolute number (percent)
c
test statistic for Mann-Whitney U-test
d
test statistics for Chi-Square test
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Correlation between resilience, self-perceived stress,
physical activity in an alpine environment and emotional
analytics
For the correlation analysis between resilience, self-
perceived stress and emotional response, we combined the
patient and HC group to one total sample. Resilience corre-
lated positively in both neutral and alpine stimuli with the
emotional analytics for valence, dominance and attraction
(all ps < 0.001, Table 3) indicating that greater resilience
was associated with higher emotional ratings. Self-perceived
stress correlated negatively with valence, dominance and at-
traction in both neutral and alpine stimuli (all ps < 0.05;
Table 3) demonstrating that higher stress levels were asso-
ciated with lower emotional ratings (Table 3).
Arousal while viewing neutral pictures correlated in an
inverse way: negatively with resilience and positively with
perceived stress. Subanalyses demonstrated that this was
mostly due to patients´ values (not shown). This demon-
strates that individuals with low resilience and high levels
of stress feel more aroused or jittery at baseline compared
to resilient individuals who feel calmer when viewing neu-
tral stimuli. Physical activity in an alpine environment cor-
related positively with all four emotional analytics in
alpine stimuli (all p< 0.001), whilst there was no signifi-
cant correlation with neutral stimuli (Table 3).
Discussion
In the present study we evaluated the effect of viewing
alpine stimuli on emotional analytics in patients with
somatoform, depressive and anxiety disorders and healthy
controls. The major findings were: 1) the emotional ana-
lytics valence and dominance were significantly lower in
patients compared to HC for both alpine and neutral
stimuli. Baseline arousal when viewing neutral stimuli was
significantly higher in patients, 2) the emotional analytic
scores were significantly higher for alpine compared to
neutral pictures for patients as well as for HC, 3) Emo-
tional analytics of alpine pictures correlated positively with
resilience and physical activity in an alpine environment
and inversely with perceived stress.
Resilience and perceived stress in patients with
psychosomatic disorders
In patients with somatoform, depressive and anxiety
disorders we observed lower levels of resilience and higher
levels of perceived stress compared to HC. These findings
are in line with previous studies showing that patients with
mental disorders often lack strategies of a resilient mindset,
which can improved during recovery [26]. Likewise per-
ceived stress has been shown to be elevated in states of
emotional-ill being [22]. Impaired resilience and higher
Table 2 Resilience, self-perceived stress and emotional analytics (SAM ratings) in patients and controls
Variable Group Comparison
Patients (N= 183)
Mean ± SD
Controls (N= 315)
Mean ± SD
Test statistics Effect size, d p-value
a
Resilience (BRS score) 2.78 ± 0.85 3.76 ± 0.66 Z = -11.84 1.33 < 0.001
Stress (PSS score) 9.53 ± 3.61 4.73 ± 2.50 Z = -13.47 1.62 < 0.001
SAM Rating
Neutral pictures
Valence 5.09 ± 1.06 5.65 ± 1.21 Z = -4.696 0.48 < 0.001
Arousal 4.13 ± 1.31 3.38 ± 1.23 Z = 5.848 0.60 < 0.001
Dominance 4.78 ± 1.08 5.13 ± 1.35 Z = -2.312 0.15 0.021
Alpine pictures
Valence 6.99 ± 1.68 7.85 ± 1.12 Z = -5.661 0.64 < 0.001
Arousal 5.01 ± 1.76 5.17 ± 1.94 Z = -1.218 0.09 0.223
Dominance 5.85 ± 1.52 6.42 ± 1.58 Z = -3.655 0.37 < 0.001
Attraction 6.62 ± 2.10 7.52 ± 1.48 Z = -4.106 0.52 < 0.001
Comparison (Alpine>Neutral)
Valence 1.91 ± 1.80 *** 2.19 ± 1.42 *** Z = -1.466 0.18 0.143
Arousal 0.87 ± 2.11 ** 1.79 ± 1.91 *** Z = -4.741 0.46 < 0.001
Dominance 1.09 ± 1.61 *** 1.29 ± 1.67 *** Z = -1.465 0.12 0.143
Abbreviations:BRS Brief Resilience Scale 13, PSS Perceived Stress Scale, SAM Self-Assesment Manikin, SD standard deviation
a
p-values were calculated using Mann-Whitney U-test
Significantly higher scores in patients than in healthy controls.
Significantly lower scores in patients than in healthy controls.
** Difference alpine neutralsignificantly greater than 0, Z = 3.25, p< 0.01
*** Difference alpine neutralsignificantly greater than 0, always Z 4.5, p< 0.001
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perceived stress, are part of the current vulnerability-stress-
model of psychosomatic disorders [12].
Emotional analytics in response to neutral and alpine
stimuli in patients with somatoform, depressive and
anxiety disorders
We found lower levels of valence and dominance in
patients than in HC over all (neutral and alpine) stimuli.
The lower levels of valence (i.e. more unhappy) reflect the
fact that our largest subgroup in our patient group was
depressive disorders(55.2%). This confirms previous
studies showing that patients suffering from depression
tend to show lower levels of valence as they describe a
feeling of numbness und joylessness in their lives [9]. A
dysfunction in emotional processing might be the under-
lying pathophysiological concept [23]. Viewing alpine
stimuli lead to a comparable increase in valence (feeling
happier) and dominance (feeling more in control) in
patients and controls. Baseline arousal was higher in the
patients than HC a finding previously described in individ-
uals with depressive symptoms [15]. This led to a signifi-
cantly smaller increase in arousal between neutral and
alpine stimuli for patients than controls.
Association of resilience, perceived stress and emotional
analytics
The association of resilience and perceived stress with
emotional analytics was found not only in patients with
somatoform, depressive and anxiety disorders but also in
healthy controls. This underlines the theory that there is
a continuum of health and disease also for somatoform,
depressive and anxiety disorders, and that mechanisms
of overtly ill patients are also present in individuals with
sub-syndromal forms of psychosomatic disorders point-
ing towards general mechanisms of mental health [24].
The inverse correlation of arousal while viewing neutral
pictures (negatively with resilience and positively with
perceived stress) were mostly due to patients´ values:
They are more jittery or aroused at baseline which fits
well with their predominant diagnoses of somatoform,
depressive and anxiety disorders [21].
The effect of alpine stimuli on emotional analytics
The effect the alpine environment on mental health has
rarely been researched to date, most studies where
performed on other natural environments. In the present
study we found that both patients and HC reacted to
alpine stimuli in form of a significant increase in valence,
arousal and dominance compared to neutral stimuli.
This finding of a positive impact on emotional analytics
is in line with previous studies evaluating psychological
and physical reactions to visual natural stimuli. Compar-
ing reactions to urban with those to natural scenery a
significant increased positive affect in emotional
response could be found in nature condition only using
virtual reality stimuli [42]. The restorative effect of the
natural environment, even if only present within visual
stimuli, might be explained by a reduction in stress
levels induced by exposure to views of nature [42].
Patients and HC showed higher emotional analytics for
valence and dominance, but we also detected an increase
in arousal in response to the alpine stimuli. This is in
contrast with several studies pointing towards relaxation
and tranquility felt while viewing natural environment
[10]. One possible explanation of our diverging finding
is that most of the alpine pictures shown in this study
displayed physically active persons (e.g. downhill skiing).
Comparable data were published by IAPS showing high
arousal ratings in the SAM scale when viewing stimuli
of physically active persons in alpine surroundings [25].
People living in perceived safe, lively and beautiful
neighborhoods were more likely to engage in PA, and
Table 3 Correlation of emotional analytics (SAM) with resilience,
self-perceived stress and PA in alpine environment
Total sample (n= 498)
BRS PSS PA in alpine environment
(MET)
Neutral pictures
Valence r
s
0.188*** 0.249*** 0.081
p 0.000 0.000 0.078
Arousal r
s
0.183*** 0.187*** 0.091
p 0.000 0.000 0.051
Dominance
r
s
0.227*** 0.150** 0.021
p 0.000 0.002 0.656
Alpine pictures
Valence r
s
0.303*** 0.276*** 0.440***
p 0.000 0.000 0.000
Arousal r
s
0.073 0.096* 0.225***
p 0.121 0.040 0.000
Dominance
r
s
0.209*** 0.172*** 0.277***
p 0.000 0.000 0.000
Attraction r
s
0.222*** 0.172*** 0.413***
p 0.000 0.000 0.000
Comparison (Alpine>Neutral)
Valence r
s
0.125** 0.043 0.316***
p 0.007 0.358 0.000
Arousal r
s
0.175*** 0.188*** 0.266***
p 0.000 0.000 0.000
Dominance
r
s
0.043 0.025 0.278***
p 0.368 0.604 0.000
Abbreviations:MET metabolic equivalents, BRS Brief Resilience Scale, PA
physical activity, PSS Perceived Stress Scale
r
s
: Spearman rank correlation coefficient, p: p-value, *p< 0.05,
**p< 0.01. ***p< 0.001
Hüfner et al. BMC Psychiatry (2020) 20:385 Page 8 of 10
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
people living in perceived boring and depressing
neighborhoods were less likely to engage in PA [44].
Multilevel modeling results showed that after controlling
for depressive symptoms at baseline, symptoms
decreased in neighborhoods where physical environment
and social environment were better [45].
The effect of physical activity in an alpine environment
on mental health
Physical activity by itself and especially when performed
in an outdoor/green/alpine environment is known to
improve mental health. Few pilot studies could confirm
the positive effect of the alpine environment when
performing physical activity [29,32,37]. This is in line
with our finding that self-performed physical activity
(METs) correlates with higher valence and dominance
felt by participants after viewing alpine but not neutral
stimuli. Conversely, some studies did not detect any dif-
ferences in affective response when comparing alpine to
indoor physical exercise [30]. Furthermore, no effect of
anthropogenic elements in the alpine environment on
acute stress-related physiological responses was found
[31]. Though importantly the latter studies as well as the
present one showed a positive correlation of outdoor
physical activity on parameters of mental well-being.
Limitations
The main limitation of the study is that in a survey study
no causal relationship between the emotional analytics
and mental health can be obtained. Furthermore, the ex-
posure in our study was applied in form of visual stimuli
instead of actually spending time in an alpine environ-
ment. The present study does not allow the differenti-
ation which components of viewing alpine environment
lead to the observed positive effects on the emotional
analytics. This was a cross sectional study which cannot
give any evidence about the long term effects on emo-
tional analytics. Due to the spread of the study invitation
via social media, flyers, classified websites and mailing
list, we cannot report the response rate.
Conclusion and consequences for clinical practice
Therapeutic programs for patients with somatoform,
depressive and anxiety disorders should contain physical
activity and according to our results, also consider taking
the effect of nature into account. The results from the
current study indicate that patients with somatoform,
depressive and anxiety disorders have a positive attitude
towards physical activity in an alpine environment and
that emotional analytics such as valence and dominance
increase in patients and HC in a comparable manner.
Practical strategies to implement such programs should
be discussed. Obvious barriers to the implementation of
such programs are primarily of a financial origin, since
in our medical system money for medications and in-
patient hospital stays is readily available while thera-
peutic programs including physical activity in an alpine
environment are not financed by public healthcare. To
further elucidate the effect of physical activity in an al-
pine environment on mental health longitudinal inter-
vention studies are needed. The current study indicates
that such studies could be promising.
Acknowledgements
We thank Dr. Thomas Post, Dr. Ulrike Weber-Lau, Dr. Barbara Mangweth-
Matzek, for help with patient recruitment and Dr. Christian Widschwendter
for helpful discussion. This study is part of the doctoral thesis of Cornelia
Ower.
Authorscontributions
Study design: K.H., C.O., C.M., G.K., B.S-U. Data collection: K. H, C.O., C. M. Data
analysis: K.H., C.O., G.K., T.V., A.S. Data interpretation: all authors. Writing and
review of manuscript: all authors. The author(s) read and approved the final
manuscript.
Funding
This research did not receive any specific grant from funding agencies in the
public, commercial, or not-for-profit sectors.
Availability of data and materials
Data are available from the first author upon request.
Ethics approval and consent to participate
The study was approved by the ethics committee of Innsbruck Medical
University (AN20140243). After being informed in detail about the study
aims and procedures, participants provided informed written consent prior
to study participation.
Consent for publication
Not applicable.
Competing interests
The authors report no conflict of interest.
Author details
1
Department of Psychiatry, Psychotherapy and Psychosomatics, Divison of
Psychiatry II (Psychosomatic Medicine), Medical University Innsbruck, Anichstr.
35, 6020 Innsbruck, Austria.
2
Department of Psychiatry, Psychotherapy and
Psychosomatics, Divison of Psychiatry I, Medical University Innsbruck,
Innsbruck, Austria.
3
Department of Psychiatry and Psychotherapy, University
Hospital, Ludwig Maximilians-University (LMU) Munich, Munich, Germany.
4
Laboratory of Neuroscience (LIM27), Institute of Psychiatry, University of São
Paulo, São Paulo, Brazil.
Received: 10 December 2019 Accepted: 13 July 2020
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... Several intervention studies were identified [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. Of them, a minority included patients with MDD only [24][25][26][27][28][29], and the majority [21,[30][31][32][33][34][35][37][38][39] recruited mixed samples including patients with depressive disorders, although separate results for that group were not reported. ...
... In a laboratory investigation, Hüfner et al. [36] exposed healthy controls and patients with mental disorders, such as somatoform, depressive, and anxiety disorders, to visual stimuli from alpine environments vs. neutral stimuli. A positive effect of alpine vs. neutral visual stimuli, assessed by Self-Assessment Manikin, was observed on emotional analytics for both groups. ...
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Background: The health benefits of greenspaces have demanded the attention of policymakers since the 1800s. Although much evidence suggests greenspace exposure is beneficial for health, there exists no systematic review and meta-analysis to synthesise and quantify the impact of greenspace on a wide range of health outcomes. Objective: To quantify evidence of the impact of greenspace on a wide range of health outcomes. Methods: We searched five online databases and reference lists up to January 2017. Studies satisfying a priori eligibility criteria were evaluated independently by two authors. Results: We included 103 observational and 40 interventional studies investigating ~100 health outcomes. Meta-analysis results showed increased greenspace exposure was associated with decreased salivary cortisol -0.05 (95% CI -0.07, -0.04), heart rate -2.57 (95% CI -4.30, -0.83), diastolic blood pressure -1.97 (95% CI -3.45, -0.19), HDL cholesterol -0.03 (95% CI -0.05, <-0.01), low frequency heart rate variability (HRV) -0.06 (95% CI -0.08, -0.03) and increased high frequency HRV 91.87 (95% CI 50.92, 132.82), as well as decreased risk of preterm birth 0.87 (95% CI 0.80, 0.94), type II diabetes 0.72 (95% CI 0.61, 0.85), all-cause mortality 0.69 (95% CI 0.55, 0.87), small size for gestational age 0.81 (95% CI 0.76, 0.86), cardiovascular mortality 0.84 (95% CI 0.76, 0.93), and an increased incidence of good self-reported health 1.12 (95% CI 1.05, 1.19). Incidence of stroke, hypertension, dyslipidaemia, asthma, and coronary heart disease were reduced. For several non-pooled health outcomes, between 66.7% and 100% of studies showed health-denoting associations with increased greenspace exposure including neurological and cancer-related outcomes, and respiratory mortality. Conclusions: Greenspace exposure is associated with numerous health benefits in intervention and observational studies. These results are indicative of a beneficial influence of greenspace on a wide range of health outcomes. However several meta-analyses results are limited by poor study quality and high levels of heterogeneity. Green prescriptions involving greenspace use may have substantial benefits. Our findings should encourage practitioners and policymakers to give due regard to how they can create, maintain, and improve existing accessible greenspaces in deprived areas. Furthermore the development of strategies and interventions for the utilisation of such greenspaces by those who stand to benefit the most.
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Cross-sectional methods were utilized to investigate if greenspace (GS) exposure predicts stress, a known factor affecting health outcomes. Data included publicly accessible Community Statistical Area (CSA) level information and survey (mailed and online) results of residents in Baltimore, Maryland. The convenience sample was re- cruited in spring 2013 using random (by CSA) and snowball techniques. The survey included demographic information, GS exposure, recent stressful life events, and the validated Perceived Stress Scale (PSS). Individuals reported (hours per week, type) where they see (visual exposure) or spend time in (physical exposure) GS around their home, work and/or school, and during recreation. Duration of GS exposure was defined as hours of visual exposure, hours of physical exposure, and total hours of exposure (both visual and physical). Multivariable linear regression assessed the effect of GS on perceived stress. Respondents (N=323) reported a mean 25.5 total hours/week exposed to GS. Mean PSS scores were 15.75 for females and 13.45 for males. Controlling for all covariates, there was a statistically significant reduction in PSS score (0.049, p=0.007) for every hour/week exposed to GS. This means that an individual who spent 25.5 h/week exposed to GS would have a PSS score 3.1% lower than those who were not exposed to GS. Total hours/week exposed to GS, and the individual effects of visual and physical exposure were all statistically significant. These findings indicate the stress reducing effects of GS exposure may be part of complex set of factors behind the relationship between GS and health outcomes.
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Green exercise, defined as physical activity in natural environments, might have positive effects on stress-related physiological measures. Little is known about the acute effects of green exercise bouts lasting longer than 60 min. Therefore, the aim of the present study was to analyze the acute effects of a three-hour green exercise intervention (mountain hiking) on stress-related physiological responses. Using a randomized crossover design, 42 healthy participants were exposed to three different conditions in a field-based experiment: outdoor mountain hiking, indoor treadmill walking, and sedentary control condition (three hours each). At baseline and at follow-up (five minutes after the condition), stress-related physiological responses (salivary cortisol, blood pressure, and heart rate variability) were measured. Salivary cortisol decreased in all conditions, but showed a larger decrease after both mountain hiking and treadmill walking compared to the sedentary control situation (partial η² = 0.10). No differences were found between mountain hiking and treadmill walking in salivary cortisol. In heart rate variability and blood pressure, changes from baseline to follow-up did not significantly differ between the three conditions. The results indicate that three hours of hiking indoors or outdoors elicits positive effects on salivary cortisol concentration. Environmental effects seem to play a minor role in salivary cortisol, blood pressure, and heart rate variability.
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Background and objectives: Psychological inflexibility exhibits across multiple facets of functioning, including thinking styles, personality, cognitive shifting, emotion, and physiology, with many of these manifestations showing associations with depression. As such, these facets might be part of an overarching latent construct of psychological inflexibility that explains associations with depression. We predicted that (1) five facets of inflexibility (perseverative thinking, personality rigidity, attention-shifting, negative emotional inertia, and low respiratory sinus arrhythmia reactivity) would load onto a unique latent construct of psychological inflexibility. Further, we hypothesized this latent construct of psychological inflexibility would be (2) significantly associated with higher depression; and (3) associated with depression to a greater extent than anxious arousal. Methods: Seventy-five adult community participants completed measures assessing the five indices of inflexibility and self-report measures of depression and anxious arousal. Results: Structural equation modeling identified a latent inflexibility construct reflected by perseverative thinking, personality rigidity, and emotional inertia, but did not include attention-shifting or RSA reactivity. The inflexibility construct was positively associated with depression and anxious arousal, but more strongly associated with depression than with anxious arousal. Limitations: Limitations included a small sample size, cross-sectional approach, and dimensional measures of depression and anxious arousal. Conclusions: Findings provide preliminary support that multiple facets of inflexibility may emerge from a broader overarching vulnerability for internalizing psychopathology. This overarching inflexibility construct may have stronger associations with depression than with anxious arousal.
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Introduction: Better mental health has been associated with exposure to natural outdoor environments (NOE). However, comprehensive studies including several indicators of exposure and outcomes, potential effect modifiers and mediators are scarce. Objectives: We used novel, objective measures to explore the relationships between exposure to NOE (i.e. residential availability and contact) and different indicators of mental health, and possible modifiers and mediators. Methods: A nested cross-sectional study was conducted in: Barcelona, Spain; Stoke-on-Trent, United Kingdom; Doetinchem, Netherlands; Kaunas, Lithuania. Participants' exposure to NOE (including both surrounding greenness and green and/or blue spaces) was measured in terms of (a) amount in their residential environment (using Geographical Information Systems) and (b) their contact with NOE (using smartphone data collected over seven days). Self-reported information was collected for mental health (psychological wellbeing, sleep quality, vitality, and somatisation), and potential effect modifiers (gender, age, education level, and city) and mediators (perceived stress and social contacts), with additional objective NOE physical activity (potential mediator) derived from smartphone accelerometers. Results: Analysis of data from 406 participants showed no statistically significant associations linking mental health and residential NOE exposure. However, NOE contact, especially surrounding greenness, was statistically significantly tied to better mental health. There were indications that these relationships were stronger for males, younger people, low-medium educated, and Doetinchem residents. Perceived stress was a mediator of most associations, and physical activity and social contacts were not. Conclusions: Our findings indicate that contact with NOE benefits mental health. Our results also suggest that having contact with NOE that can facilitate stress reduction could be particularly beneficial.