Viewing an alpine environment positively affects
emotional analytics in patients with stress-related
psychiatric disorders and healthy controls
Katharina Hüfner ( firstname.lastname@example.org )
Medizinische Universitat Innsbruck https://orcid.org/0000-0002-5453-8792
Medizinische Universitat Innsbruck
Medizinische Universitat Innsbruck
Medizinische Universitat Innsbruck
Medizinische Universitat Innsbruck
Medizinische Universitat Innsbruck
Keywords: alpine environment, resilience, self-perceived stress, self-assessment manikin, emotional
analytics, psychosomatic disorders
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
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Background: Patients with stress-related psychiatric (psychosomatic) disorders often don´t respond well
to medical treatment and experience many side effects. It is thus of clinical relevance to identify
alternative, scientically 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 benecial 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 stress-related psychiatric 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 feel less happy, less in control and had higher
levels of arousal than HC when viewing neutral stimuli. The comparison alpine>neutral stimuli showed a
signicant a 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 stress-related psychiatric disorders
should consider taking the benets of outdoor natural environments into account. Organizational barriers
which are preventing the implementation of such programs in clinical practice need to be identied and
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 (Gascon et al. 2016). Discovering blue (de Bell et al. 2017) and green (van den
Berg et al. 2016) spaces is associated with psychological benets. Stress is an important mediator of the
effect of natural outdoor environments and mental well-being (Triguero-Mas et al. 2017). Green spaces
have been shown to reduce cortisol levels as a marker of stress (Twohig-Bennett and Jones 2018). Stress
as important marker of mental health is signicantly reduced by the exposure to nature even by only the
visual stimulation with nature without physical exposure in a dose-response relationship (Hazer et al.
2018). Visual or auditory nature stimuli can facilitate recovery from psychological stressful events
(Brown et al. 2013; Alvarsson et al. 2010) and from physical disease (Ulrich 1984). In mental health,
chronic stress is among the strongest risk factors for depression but is also an important pathogenetic
factor in anxiety disorders, post-traumatic stress disorders or somatoform disorders (Slavich and Irwin
2014, Bangasser and Valentin 2014).
Another factor through which exposure to natural outdoor environments exerts its positive effect on
mental health might be through the strengthening of resilience (Ritchie et al. 2014; Panno et al. 2017).
Resilience can be dened as one’s 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 (Ower et al. 2018). 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 (Thompson Coon et al. 2011).
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 signicantly more connected to others, more
caring, and more spiritual after watching awe-inspiring nature condition (Joye and Bolderdijk 2015).
Hikers of alpine wilderness trails reported substantial stress reduction and mental rejuvenation following
a day or overnight hike (Cole and Hall 2010). Furthermore, in a crossover trial focusing on differences
between indoor and alpine activity, mountain hiking showed signicantly greater positive effects on
affective valence and activation compared to indoor physical activity (Niedermeier et al. 2017a). 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 (Gascon et al. 2015, Liu et al. 2020).
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 in mental health. There are only few
studies investigating therapeutic alpine interventions as treatment for patients in mental health care. In a
mountain hiking program for suicidal patients, participants reported signicant reduction in depression,
hopelessness and suicidal ideation (Sturm et al. 2012). In another study adults and youth with mental
illness experienced signicant improvements in self-esteem, mastery and resilience following activities
like mountain biking and raft building (Bowen et al. 2016).
The primary aim of the present study was to investigate whether stimuli depicting alpine environments
would elicit differential or similar emotional analytics in patients with stress-related psychiatric disorder
and healthy controls in order to judge the potential usefulness for a therapeutic intervention program.
This aim was approached by the following study setting:
We assessed emotional analytics upon viewing neutral and alpine stimuli in patients with stress-
related psychiatric disorders and healthy controls. The alpine stimuli depicted individuals while
engaged in physical activity in an alpine environment
We investigated whether there was a correlation of emotional analytics with resilience or perceived
stress in patients and healthy controls.
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.
2.1 Study design
This is a cross-sectional observational study including a quasi-experimental part (gure 1). The whole
study was performed online. The rst part of the study contained questionnaires, while the second part
recorded emotional 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 activity in an alpine
environment on mental health, part of which has been published (Ower et al. 2018). 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 Innsbruck reviewed and approved the
study protocol. After being informed in detail about the study aims and procedures, participants provided
informed written consent online (by ticking “agree” and clicking on the “consent” button) prior to study
participation. This mode of consent was approved by the reviewing ethics committee. Study recruitment
was conducted over a four-month period in 2016.
Participants and recruiting are described in Ower et al. 2018, participant numbers vary slightly compared
to the previous publication due to missing data in individual 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 classied 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 patients with the diagnosis of stress-related psychiatric
disorders mainly depressive disorders, anxiety disorders or somatoform disorders. For the present
analysis participants who terminated the questionnaire early (missing data n =436) were excluded from
the study. This high drop-out rate was mainly due to the fact that Self-Assessment Mannequin (SAM)
ratings of emotional analytics were performed as the nal 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 signicantly 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 signicance, 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 (Figure 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 expression of disease. Therefore, these patients were excluded
(Bezzina et al. 2019). 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).
Stimuli were alternating 5 neutral pictures (re-staged to ocial International Affective Picture System
(IAPS) pictures (slide no. 6150, 7009, 5661, 5500, 7150)) and 5 alpine stimuli (Figure 3). Neutral pictures
displayed gural 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 statistical outliers in the ratings. Pictures were displayed for 5 seconds before the page
with the emotional analytic ratings appeared. Each stimulus could only be observed once (Figure 1).
Socio-demographic parameters included information on age, sex, education and marital status. Mental
health was assessed using the German version of Patient Health Questionnaire (Gräfe et al. 2004).
Additionally, open text elds were provided for entering psychiatric diagnoses. Resilience was measured
using the Brief Resilience Score (BRS) (Smith et al. 2008), self-perceived stress using the Perceived Stress
Scale (PSS) (Cohen et al. 1983) and Physical activity (PA) using the Global Physical Activity
Questionnaire (GPAQ-2) (Bull et al. 2009). PA is calculated using metabolic equivalents of task (METs) as
a unit for energy expense. As determined of the World Health Organization we classied PA in moderate
and vigorous intensity. We adapted the standard questionnaire to measure PA performed in the alpine
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 (J Lang et
al. 2008). The valence scale ranges from a frowning, unhappy (adjectives used in the SAM manual:
unhappy, annoyed, unsatised, melancholic, despaired, bored; lower values) to a smiling, happy gure
(happy, pleased, satised, contented, hopeful). The arousal scale displays the lowest value with a calm,
eyes-closed gure (relaxed, calm, sluggish, dull, sleepy, unaroused), whilst the highest value is represented
by an excited gure (stimulated, excited, frenzied, jittery, wide-awake, aroused). The lowest values in the
dominance scale are symbolized by a controlled small gure (controlled, inuenced, cared-for, awed,
submissive, guided.) whilst highest values are represented by a dominant and oversized gure
(controlling, inuential, in control, important, dominant, autonomous). After presenting a picture for ve
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 “I don’t want to be in this situation” to “I want to be in the
2.4 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 (Lehman 1991)
and kurtosis values > 1 or <-1 (https://brownmath.com/stat/shape.htm) 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 score
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,
depending on the variable type and distribution. As the two groups differed signicantly in their age and
education, we also performed analyses of covariance with adjustment for these potential confounders.
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 coecients were used as
most the variables involved showed deviations from a normal distribution.
2.1 Sociodemographic characteristics and clinical features
The sociodemographic characteristics of patients and HC are displayed in Table 1. Patients diagnoses
according to PHQ were in decreasing frequency: somatoform disorder (n=101, 55.2 %), major depressive
syndrome (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 prevalent 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.
2.2 Resilience, self-perceived stress and emotional analytics in patients and controls
The mean score of the Brief Resilience Scale (BRS) was signicantly lower in patients than in HC (Mann-
Whitney U Test-Test, p<0.001; Table 2). Furthermore the total score of the PSS was signicantly 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
signicantly 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) indicating that they felt less in control than HC.
Arousal when viewing neutral stimuli was signicantly higher (p<0.001) for patients indicating that they
felt more aroused or jittery than the HC at baseline. In alpine pictures the difference in arousal was not
signicant 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 signicantly lower in patients as in HC (p< 0.001
table 2) although both groups showed a high attraction to the alpine stimuli. All statistically signicant
differences in Table 2 remained signicant when adjusting for age and education by analysis of
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 signicantly 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 > neutral stimuli
did not differ signicantly between patients and HC (Table 2). For arousal the difference was signicantly
smaller in patients than in HC due to higher baseline arousal values in patients (p<0.001; Table 2).
2.3 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 correlated 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 attraction in both neutral and alpine stimuli (all
ps<0.05; Table 3) demonstrating that higher stress levels were associated with lower emotional ratings
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 demonstrates 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 neutral
stimuli. Physical activity in an alpine environment correlated positively with all four emotional analytics in
alpine stimuli (all p<0.001), whilst there was no signicant correlation with neutral stimuli (Table 3).
In the present study we evaluated the effect of viewing alpine stimuli on emotional analytics in patients
with stress-related psychiatric disorders and healthy controls. The major ndings were: 1) the emotional
analytics valence and dominance were signicantly lower in patients compared to HC for both alpine and
neutral stimuli. Baseline arousal when viewing neutral stimuli was signicantly higher in patients, 2) the
emotional analytic scores were signicantly higher for alpine compared to neutral pictures for patients as
well as for HC, 3) Emotional analytics of alpine pictures correlated positively with resilience and physical
activity in an alpine environment and inversely with perceived stress.
Resilience and psychosomatic stress in patients with psychosomatic disorders
In patients with stress-related psychiatric disorders we observed lower levels of resilience and higher
levels of perceived stress compared to HC. These ndings are in line with previous studies showing that
patients with mental disorders often lack strategies of a resilient mindset, which can improved during
recovery (Lee et al. 2017). Likewise perceived stress has been shown to be elevated in states of
emotional-ill being (Kadzikowska-Wrzosek 2012). Impaired resilience and higher perceived stress, are part
of the current vulnerability-stress-model of psychosomatic disorders (Fava et al. 2017).
Emotional analytics in response to neutral and alpine stimuli in patients with stress-related psychiatric
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) reect the fact that our largest subgroup in our
patient group was „depressive disorders” (55,2%). This conrms 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 (Dai et al. 2016). A dysfunction in emotional processing might be the
underlying pathophysiological concept (Kemmis et al. 2017). 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 nding previously described in individuals with
depressive symptoms (Gilbert et al. 2019). This led to a signicantly 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 stress-related psychiatric disorders but also in healthy controls. This underlines the theory
that there is a continuum of health and disease also for stress-related psychiatric disorders, and that
mechanisms of overtly ill patients are also present in individuals with sub-syndromal forms of
psychosomatic disorders pointing towards general mechanisms of mental health (Keyes 2007). 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
ts well with their predominant diagnoses of stress-related psychiatric disorders (Jung et al. 2016).
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 signicant increase in valence, arousal and dominance compared to
neutral stimuli. This nding of a positive impact on emotional analytics is in line with previous studies
evaluating psychological and physical reactions to visual natural stimuli. Comparing reactions to urban
with those to natural scenery a signicant increased positive affect in emotional response could be found
in nature condition only using virtual reality stimuli (Valtchanov et al. 2010). 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 (Valtchanov et al. 2010). 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 (Davis 2004). One possible explanation of our diverging nding 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 (J Lang et al. 2008). People living in
perceived safe, lively and beautiful neighborhoods were more likely to engage in physical activity, and
people living in perceived boring and depressing neighborhoods were less likely (Wang et al. 2019).
Multilevel modeling results showed that after controlling for depressive symptoms at baseline,
symptoms decreased in neighborhoods where physical environment and social environment were better
(Wang et al. 2018).
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 conrm the positive effect of the alpine
environment when performing physical activity (Sturm et al. 2012; Niedermeier et al. 2017a; Ower et al.
2018). This is in line with our nding 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 differences in affective response when comparing alpine to indoor physical
exercise (Niedermeier et al. 2017b). Furthermore, no effect of anthropogenic elements in the alpine
environment on acute stress-related physiological responses was found (Niedermeier et al. 2019).
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.
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 exposure in our study was applied in form
of visual stimuli instead of actually spending time in an alpine environment. The present study does not
allow the differentiation 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 emotional analytics. Due to the spread of the study invitation via social
media, yers, classied websites and mailing list, we cannot report the response rate.
Conclusion And Consequences For Clinical Practice
Therapeutic programs for patients with stress-related psychiatric 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 stress-related psychiatric 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 practical barriers to the implementation of such programs
are primarily of a nancial origin, since in our medical system money for medications and inpatient
hospital stays is readily available while therapeutic programs including physical activity in an alpine
environment are not nanced by public healthcare. To further elucidate the effect of physical activity in
an alpine environment on mental health longitudinal intervention studies are needed. The current study
indicates that such studies could be promising.
BRS = Brief Resilience Scale, GPAQ = General Physical Activity Questionnaire, HC = healthy controls, MET:
metabolic equivalents, PA = physical activity, PHQ = Patient Health Questionnaire, PSS: Perceived Stress
Scale, SAM = Self-Assessment Mannequin
Ethics approval and consent to participate
The study was appoved by the ethics committee of Innsbruck Medical University (AN2014-0243).
After being informed in detail about the study aims and procedures, participants provided informed
written consent online (by ticking “agree” and clicking on the “consent” button) prior to study
participation. This mode of consent was approved by the reviewing ethics committee.
Consent for publication
Availability of data and materials
Data are available from the rst author upon request.
The authors report no conict of interest.
This research did not receive any specic grant from funding agencies in the public, commercial, or
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.,
Data interpretation: all authors
Writing and review of manuscript: all authors
We thank Dr. Thomas Post, Dr. Ulrike Weber-Lau, Dr. Barbara Mangweth-Matzek, for help with patient
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Table 1: Sociodemographic characteristics of patients and healthy controls (adapted with participant
numbers for the current analysis from Ower et al. 2018)
Variable Groups Comparison
117 (63.9) 187
c²=1.02 1 0.313
41 (22.4) 111
53(29.0) 34 (10.8) - -
27 (14.8) 37 (11.7) - -
Single 105 (57.4) 194
Married 56 (30.6) 110
22 (12.0) 11 (3.5) - -
--c²=66.81 2 <0.001
75 (41.0) 177
49 (26.8) 122
59 (32.2) 16 (5.1)
babsolute number (percent)
Table 2: Resilience, self-perceived stress and emotional analytics (SAM ratings) in patients and controls
Variable Group Comparison
Mean ± SD
Mean ± SD
Effect size, d p-valueb
Resilience (BRS mean
Z=-11.84 -1.33 <0.001
Stress (PSS score) 9.53 ±
Z=-13.47 1.62 <0.001
Valence 5.09 ±
Z=-4.696 -0.48 <0.001
Arousal 4.13 ±
Z= 5.848 0.60 <0.001
Dominance 4.78 ±
Z=-2.312 -0.15 0.021
Valence 6.99 ±
Z=-5.661 -0.64 <0.001
Arousal 5.01 ±
Z=-1.218 -0.09 0.223
Dominance 5.85 ±
Z=-3.655 -0.37 <0.001
Attraction 6.62 ±
Z=-4.106 -0.52 <0.001
Valence 1.91 ±
Z=-1.466 -0.18 0.143
Arousal 0.87 ±
Z=-4.741 -0.46 <0.001
Dominance 1.09 ±
Z=-1.465 -0.12 0.143
bp-values were calculated with Chi Square Test for categorical variables and Mann
Whitney U Test for continuous variables
Signicantly higher scores in patients than in healthy controls
¯ Signicantly lower scores in patients than in healthy controls
** Difference “alpine – neutral” signicantly greater than 0, Z=3.25, p<0.01
*** Difference “alpine – neutral” signicantly greater than 0, always Z ≥ 4.5, p<0.001
Abbreviations: BRS: Brief Resilience Scale, PSS: Perceived Stress Scale
Correlation of emotional analytics (SAM) with resilience, self-perceived stress and PA in alpine
Total sample (n=498)
BRS PSS PA in alpine
Valence rs0.188** -0.249** 0.081
p 0.000 0.000 0.078
Arousal rs-0.183** 0.187** -0.091
p 0.000 0.000 0.051
Dominance rs0.227** -0.150** -0.021
p 0.000 0.002 0.656
Valence rs0.303** -0.276** 0.440**
p 0.000 0.000 0.000
Arousal rs0.073 -0.096* 0.225**
p 0.121 0.040 0.000
Dominance rs0.209** -0.172** 0.277**
p 0.000 0.000 0.000
Attraction rs0.222** -0.172** 0.413**
p 0.000 0.000 0.000
Valence rs0.125** -0.043 0.316**
p 0.007 0.358 0.000
Arousal rs0.175** -0.188** 0.266**
p 0.000 0.000 0.000
Dominance rs0.043 -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
rs: Spearman rank correlation coecient, p: p-value, *p<0.05, **p<0.01. ***p<0.001
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). Specic questionnaires
are indicated BRS = Brief Resilience Scale, PHQ = Patient Health Questionnaire, PSS = Perceived stress
scale, GPAQ = General Physical Activity Questionnaire. (…) indicates that there were questionnaires at the
indicated point in the study design not analyzed in the current study but in Ower et al. 2018.
Flowchart of patient and healthy control recruitment (adapted with participant numbers for the current
analysis from Ower et al. 2018). Missing data occurred due to early termination of the questionnaire.
Examples of alpine stimuli depicting individuals performing physical activity in an alpine environment.
Neutral stimuli are not depicted since this is not considered good scientic practice for the IAPS picture
collection (Lang et al. 2008).