Next Article in Journal
Wild Watermelon-Extracted Juice Ingestion Reduces Peripheral Arterial Stiffness with an Increase in Nitric Oxide Production: A Randomized Crossover Pilot Study
Previous Article in Journal
Vitamin D and Systems Biology
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Horticultural Therapy May Reduce Psychological and Physiological Stress in Adolescents with Anorexia Nervosa: A Pilot Study

1
Institute of Clinical Physiology, National Research Council of Italy, Via Moruzzi 1, 56124 Pisa, Italy
2
IRCCS Stella Maris Foundation, 56128 Pisa, Italy
3
Institute of Information Science and Technologies “Alessandro Faedo” (ISTI), National Research Council of Italy, Via Moruzzi 1, 56124 Pisa, Italy
4
Department of Agriculture, Food and Environment, University of Pisa, Via del Borghetto 80, 56124 Pisa, Italy
5
Child and Adolescent Rehabilitation Clinic “Gli Orti di ADA”, Via dei Giacinti, 4, 56128 Pisa, Italy
*
Author to whom correspondence should be addressed.
Nutrients 2022, 14(24), 5198; https://doi.org/10.3390/nu14245198
Submission received: 21 October 2022 / Revised: 2 December 2022 / Accepted: 3 December 2022 / Published: 7 December 2022
(This article belongs to the Section Clinical Nutrition)

Abstract

:
Studies in psychiatric populations have found a positive effect of Horticultural therapy (HCT) on reductions in stress levels. The main objective of the present pilot study was to evaluate the impact of the addition of HCT to conventional clinical treatment (Treatment as Usual, TaU) in a sample of six female adolescents with anorexia nervosa restricting type (AN-R), as compared to six AN-R patients, matched for sex and age, under TaU only. This is a prospective, non-profit, pilot study on patients with a previous diagnosis of AN-R and BMI < 16, recruited in 2020 in clinical settings. At enrolment (T0) and after treatment completion (TF), psychiatric assessment was performed. At T0, all the patients underwent: baseline electrocardiogram acquisition with a wearable chest strap for recording heart rate and its variability; skin conductance registration and thermal mapping of the individual’s face. An olfactory identification test was administered both to evaluate the olfactory sensoriality and to assess the induced stress. One-way analyses of variance (ANOVAs) were performed to analyze modifications in clinical and physiological variables, considering time (T0, TF) as a within-subjects factor and group (experimental vs. control) as between-subjects factors. When the ANOVA was significant, post hoc analysis was performed by Paired Sample T-tests. Only in the HCT group, stress response levels, as measured by the biological parameters, improved over time. The body uneasiness level and the affective problem measures displayed a significant improvement in the HCT subjects. HCT seems to have a positive influence on stress levels in AN-R.

1. Introduction

Eating disorders are burdened by a high rate of physical comorbidity, reaching, with anorexia nervosa (AN), the highest mortality rate of all mental disorders [1,2]. Thus, the need for multiple levels of treatment, including outpatient facilities as well as rehabilitation and hospital units, depends on the severity of the clinical picture. The onset of AN typically occurs during adolescence; the 15–19-year age group constitutes 40% of newly diagnosed cases; nearly 85% of cases have an onset within those of 20 years and, in almost all cases, symptoms start before the age of 25 years [3]. A lowering of the age of onset with an increase in new diagnoses at an early age (under 12 years) has been reported in the last few years [4,5,6].
Horticultural therapy and, more generally, Green therapy are considered natural complementary rehabilitation therapies, increasingly used in psychiatric pathologies in adult subjects [7]. Studies have also reported the contribution of such interventions on the reduction in stress levels and on the improvement in well-being of individuals at different ages, from healthy pediatric populations [8] to young adults [9], and even in elderly subjects [10,11]. Different studies have shown that the exposure to natural stimuli induces hyperactivity in the parasympathetic nervous system, ultimately resulting in a state of relaxation [12]. Exposure to nature implies a decrease in the autonomic arousal [13] and is beneficial to mood, through a decrease in negative emotions in favor of positive affective responses [14,15,16]. These responses to the exposure and the involvement in activities within natural environments occur in a few minutes and have a psycho-evolutionary value according to Ulrich. In other words, it would be an adaptive mechanism evolved in phylogeny to allow for rapid physical and emotional recovery after the recognition of a safe environment, especially after having faced an arousal phase. This rapid recovery, and the return to optimal operating conditions, would then be aimed at the quick reactivation of the necessary behaviors for survival, including the search for food and shelter. Studies in psychiatric [17] and non-psychiatric adult populations [9] have found a positive effect from Green and Horticultural therapy in reductions in stress levels. Such outcomes were evaluated through the variation in biological parameters, including cortisol [17], heart rate and its variability, measured by wearable sensors [9], as well as improvements in the subjective perception of stress [18]. However, there are no studies dealing with patients with Eating Disorders (EDs), specifically with AN, although the Green therapy setting should show several benefits to some specific vulnerabilities of these patients. In fact, while growing plants, the patients face the experience of taking care of other forms of life, getting them used to tolerate waiting times that are not always predictable: they have to deal with the imperfection of spontaneous growth of products in nature. Moreover, the horticultural products are characterized by specific and well-recognizable smells that may drive the selectivity of consumers toward food.
The main objective of the present pilot project was to evaluate the impact of Horticultural therapy, in addition to conventional clinical treatment (Treatment as Usual, TaU), in a sample of adolescents with anorexia nervosa restricting type (AN-R), as compared to a control group consisting of AN-R patients matched by sex, age, body mass index (BMI), duration of illness, and drug therapy, who carried out exclusively TaU. The standard multidisciplinary approach includes access to physical, nutritional, psychological, and psychiatric interventions.
The specific aims of the study were:
  • To evaluate the impact of Horticultural Therapy (HCT) on the anorexic core psychopathology and psychiatric comorbidities;
  • To assess the change in the stress level through the study of autonomic parameters (heart rate, heart rate variability, skin conductance, and facial thermography);
  • To explore the olfactory function and its relationship with autonomic parameters as a possible variable of interest in response to odorous stimuli for both edible and non-edible compounds.

2. Materials and Methods

2.1. Study Design

The present study is a prospective, non-profit, pilot study that involved patients recruited in two settings, the clinical Unit for Child and Adolescence with EDs of the IRCCS Stella Maris and the Rehabilitation Unit for Child and Adolescents with EDs, “Gli Orti di Ada”.
The study aimed at evaluating the effects of a complementary treatment, the HCT, in patients with AN-R in addition to TaU.

2.2. Participants

At the time of enrolment, occurring in 2020, given the COVID-19-related pandemic period, the patients’ and families’ availability was checked before enrolling the AN-R patients. Parents and patients in the experimental group were provided with specific information on HCT and its benefits in other psychiatric pathologies. Then, each patient was randomly assigned to the experimental or to the control group. The sample was composed of 12 Caucasian female adolescents with AN-R (mean age: 14.86 ± 1.92 years; range: 11–18 years old): 6 in the experimental (TaU plus HCT) and 6 in the control (under TaU only) group. One subject had an illness duration of less than 2 years; 9 subjects had an illness duration between 1 and 2 years; 2 subjects had an illness duration of more than 2 years. At the time of enrollment and subsequent execution of the project, all the subjects were in a stable clinical condition and displayed good compliance with the treatment. The two groups were matched by sex, age, BMI, duration of illness, intensity of treatment, and drug therapy (p > 0.05).
Inclusion criteria: Diagnosis of AN-R; BMI > 16.
Exclusion criteria: Patients with severe AN-R in intensive hospital treatment, including enteral nutrition (BMI < 16); patients with severe psychiatric comorbidity.
The project received approval from the Pediatric Ethics committee for Tuscany Region (Florence, Italy; Register Number: 138/2020).

2.3. Interventions

2.3.1. Treatment as Usual

In anorexia nervosa TaU is based on physical, nutritional, psychological, and psychiatric interventions. Multiple levels of this treatment are provided including hospitalization, outpatient treatments as well as rehabilitation units, according to the severity of the clinical symptoms. All the patients involved in this study underwent this kind of treatment that included nutritional counselling and rehabilitation, psychiatric, and psychopharmacological treatment as well as psychological intervention. All the patients underwent periodic clinical monitoring of biological parameters.

2.3.2. Horticultural Therapy

Horticultural Therapy consisted of 24 sessions carried out twice a week for a total duration of 12 weeks (September–November 2020), with each session lasting around 45 min. These activities were performed in the garden and/or in a PVC tunnel greenhouse of the clinical unit, under the supervision and support of experts from the Department of Agriculture, Food and Environment (DAFE) of the University of Pisa and educators from the clinical units.
In order to let the patient experience different sensory stimulations even without any specific sensorial training, the activities were organized in three workstations, each of which focused on six plant species selected to emphasize divergent colors, odors, and shapes (Figure 1). The colors group included (i) beach moonflower (Ipomea violacea L.), (ii) lupin (Lupinus polyphyllus L.), (iii) madwort (Alyssum maritimum L.), (iv) marigold (Tagetes erecta L.), (v) snapdragon (Antirrhinum majus L.), and (vi) sunflower (Helianthus annuus L.). The odors group included (i) common sage (Salvia officinalis L.), (ii) lavender (Lavandula angustifolia L.), (iii) lemon balm (Melissa officinalis L.), (iv) lesser calamint (Calamintha nepeta (L.) Savi), (v) parsley (Petroselinum crispum (Mill.) Fuss), and (vi) sweet basil (Ocimum basilicum L.). The shapes group included (i) Brussels sprouts (Brassica oleracea L. var. gemmifera), (ii) cauliflower (Brassica oleracea L. var. botrytis), (iii) pumpkin (Cucurbita maxima Duchesne), (iv) radish (Raphanus sativus L.), (v) romaine lettuce (Lactuca sativa var. longifolia), and (vi) zucchini (Cucurbita pepo L.). These species were also selected to include other variable plant characteristics such as the seed size and the growth timing and rate.
Patients from the experimental group were randomly sub-grouped in order to have two patients at each workstation. Sub-groups weekly alternated among the three workstations in order to let all the patients experience the different sensory stimulations.
At the beginning of the first session, DAFE experts (with the support of educators) introduced themselves and their work and provided the patients with some gadgets useful for HCT activities (e.g., backpacks, caps, notebooks, pens, and pencils). Then, they illustrated the HCT tools available at each workstation (e.g., seeds, pots, substrates, watering cans, fertilizers, tags, and sharpies) and explained the overall HCT design. A booklet prepared by DAFE experts and including major indications for growing the selected plant species (e.g., common and scientific names, pictures, and cultivation tips about the substrate to use, climatic needs, fertilizing, irrigation, and flowering) was also provided to each patient.
The next HCT sessions were organized as follows: (i) preparation for the session by educators, (ii) brief on-site explanation and fulfilment of the planned activities (e.g., substrate preparation, pot filling, sowing, labelling, watering, repotting, fertilizing, and taking care of plants) by DAFE experts, and (iii) observation and experiencing of developing plants.
At the end of the last session, a ‘green thumb’ certification, signed by a Full Professor of the DAFE and certifying the ability and commitment demonstrated in growing and taking care of plants, was given to each patient in the experimental group (Figure 2). An analogous certificate of merit, assessing the participation and commitment in the research activities, was given to each patient in the control group.

2.4. Procedure

During the whole testing procedure, patients were asked to sit comfortably in a chair and instructed to do nothing but relax.
At the enrolment, and after the treatment completion, within completely dedicated sessions, psychiatric assessment was performed by the administration of the following standardized instruments: Eating Disorder Inventory-3 (EDI-3) [19]; Body Uneasiness Test (BUT) [20]; and Children Depression Inventory (CDI) [21].
At T0, i.e., before the beginning of the HCT sessions, all the patients underwent a baseline acquisition of: (i) electrocardiogram (ECG) with a wearable chest strap; (ii) skin conductance (SC) with a wearable sensor placed on two adjacent fingers of the non-dominant hand; (iii) thermal mapping of the individual’s face with thermal imaging camera. The total duration of the acquisition was about 10 min.
Given that, among sensorial features, the smell profile of a food seems to have the main influence on consumers’ food choice, an olfactory identification test was also administered to evaluate the olfactory sensoriality relating to 12 smells (6 of them related to edible compounds and the other 6 related to non-edible ones), some of which were referring to the world of the garden. After a short introduction, the patients had to try to identify the olfactory compound contained within the solution developed ad hoc by researchers from DAFE of the University of Pisa. During the test, the response of the autonomic nervous system to olfactory stimuli was measured through the analysis of heart rate (HR) and heart rate variability (HRV), derived from the ECG and SC, as previously described [22,23]. A thermal video sequence (including subject acclimatization, olfactory stimuli, and subject relaxation) was also acquired to investigate the temperature changes in facial landmarks (e.g., nose tip, nasal septum, forehead) possibly related to physical or mental stress [24].
The Green and Ortho-Therapy sessions, according to the protocol described above, lasted 12 weeks, with 2 sessions per week, for a total of 24 sessions.
After the conclusion of the Green and Ortho-Therapy, a complete assessment of the stress-dependent autonomic parameters in resting condition (HR, HRV, SC, and facial thermal imaging) was repeated in all 12 subjects. Similarly, the olfactory identification test and the administration of psychopathological assessment by EDI-3, BUT, and CDI were repeated in all subjects in both groups.

2.5. Instruments

2.5.1. Model Solutions Used for the Olfactory Stimulation

In Table 1, the odorous solutions used for the olfactory stimulation are reported. To reduce bias derived from the repetition of the olfactory test, two subsets of odors slightly different were used during the two olfactory trials (i.e., at T0 and TF).

2.5.2. ECG Acquisition and Processing

The acquisition of the ECG signal was performed using a commercial wearable, Bluetooth-equipped single-lead sensor, named Shimmer ECG (Shimmer Sensing, Dublin, Republic of Ireland), attached to a commercial fitness-like chest strap (Polar Electro Oy, Kempele, Finland) with a sampling frequency of 500 Hz. This device was already tested in AN in our previous studies [25,26].
The ECG signal was analyzed using a dedicated routine implemented in MATLAB (The MathWorks, Inc., Natick, MA, USA). ECG signals were pre-processed for artifact removal, QRS complexes were detected [27], and then the RR series were reconstructed and corrected. The correction was applied to remove non-sinusoidal beats in order to obtain an RR series that only contains variations due to the sinus node, thus, reflecting the activity of the ANS [28].
From the corrected RR series, a number of significant features was extracted [29]:
  • Time-domain features:
    o
    Heart rate (HR): number of heart pulses per unit of time. Measured in beats per minute (bpm);
    o
    Standard deviation of the normal R–R intervals (SDNN): measured in ms, it is an estimate of the HRV influenced by both the sympathetic and para-sympathetic branches of the ANS;
    o
    Root mean square of the successive differences (RMSSD): measured in ms, it represents the root mean square of the differences between neighboring R–R intervals. It is an estimate of the parasympathetic activity of the ANS;
    o
    Number of normal R–R intervals differing for more than 50 ms (NN50): it estimates the number (or the percentage) of the normal R–R intervals differing for more than 50 ms from each other. Under resting state short-term recordings, it refers to the parasympathetic activity of the ANS.
  • Frequency-domain features:
    o
    Low frequency (LF): power spectral density of the ECG signal at low frequencies (0.04–0.15 Hz), employed as an estimator of the sympathetic activity of the ANS;
    o
    High frequency (HF): power spectral density of the ECG signal at high frequencies (0.15–0.4 Hz), employed as an estimator of the sympathetic and parasympathetic activity of the ANS;
    o
    Low- to high-frequency component ratio (LF/HF): it indicates the overall balance between low- and high-frequency components of the ECG signal.

2.5.3. GSR Acquisition and Processing

The acquisition of the GSR signal was conducted with a commercial wearable sensor, Shimmer3GSR (Shimmer Sensing, Dublin, Republic of Ireland), communicating via Bluetooth to the manufacturer user interface, with a sampling frequency of 51.2 Hz. The GSR sensor captured the corresponding signal, being attached to two adjacent fingers of the subject’s non-dominant hand at the phalanx level with the support of two comfortable soft rings in turn worn by the individual studied. This device was also previously tested by our group in AN subjects [30].
Concerning the processing, the GSR signal was analyzed using the Matlab-based tool Ledalab [31]. The GSR signal was initially filtered with a first-order Butterworth low-pass filter at 5 Hz to remove high-frequency noise, and then continuous decomposition analysis was applied for the extraction of both tonic and phasic activities. As such, the following features were extracted:
o
Tonic GSR component: mainly refers to slow changes in the electrical skin signal, dominant at rest and during relaxing activities, not including specific stimuli;
o
Phasic GSR component: extracted to study the response to the sensory (olfactory) stimulation, as it refers to quick responses to specific stimuli (also known as Skin Conductance Response, SCR).

2.5.4. Thermal Imaging Acquisition and Processing

Thermography is a contactless measure that reflects subcutaneous blood distribution and sweat secretion. In the literature, stress elicited by mental tests was observed to induce an enhancement in blood flow in the forehead, supraorbital, and frontal vessels [32]. The mean temperature of the face could hardly be considered as a reliable stress indicator; so far, the most reliable facial feature to identify stress arising is the nose tip, which has been successfully exploited to design and develop a real-time classification algorithm to improve social robots’ interaction [33,34]. In a more recent work, the nose tip and the nasal septum were also established as stable stress indicators [24]. The only work studying the relation between AN and thermal measurements was published in 2016 and aimed at detecting the disturbance in thermoregulation mechanisms and body temperature of AN subjects [35] being more focused on providing clinical implications for the treatment of anorexic patients.
Hence, in our experimentation, we decided to focus on small circular Regions of Interest (ROIs) around the facial landmarks, which were found in the literature to be most likely related to stress: the nose tip, the nasal septum, and the forehead (left and right). The thermal signal was measured using an FLIR A65sc infrared camera with a focal length of 13 mm (spectral range of 7.5–13 µm (LWIR), resolution of 640 × 512 pixels, thermal sensitivity <0.05 °C, and streaming rate 7.5 Hz).
For each subject a long video sequence of about 10 min was acquired at T0 and at TF. The acquisition includes three main phases: the acclimatization of the subject in the room, the sequence of the olfactory stimuli, and the recovery (or resting phase). The thermal signal was extracted manually as the mean temperature of each ROI at three specific time steps: during the acclimatization, in the middle of the olfactory test, and at the end of the test, while relaxing. Thermal features were extracted from the nose tip, the nasal septum, the right forehead, the left forehead, and the mean of the two forehead ROIs normalized with respect to the nose tip temperature (the difference between the average of the two forehead ROIs and the nose tip). The statistical analysis was carried out only for the measurements acquired during acclimatization and resting phase, in order to observe how fast the recovery is from the stress status induced by the olfactory test.

2.6. Endpoint of the Study

The main endpoint of the study was to evaluate T0-TF differences (before and after the Green and Horticultural Therapy sessions), both in the experimental group and in the control group, of the following measures:
(1)
Psychometric questionnaires, clinical variables: Eating Disorder Inventory-3 (EDI-3) [19]; Body Uneasiness Test (BUT) [20]; and Children Depression Inventory (CDI) [21];
(2)
Basal level of stress evaluated by autonomic measures (values of Skin Conductance, SC; Heart Rate, HR and its variability, HRV; and facial thermal imaging);
(3)
Olfactory identification test (the number of correctly identified stimuli);
(4)
Level of stress during the olfactory test evaluated by autonomic response (values of Skin Conductance, SC, Heart Rate, HR, and its variability, HRV, and thermal mapping of the face, in response to olfactory stimuli).

2.7. Statistical Analysis of the Results

The normality of the variables was determined using the Shapiro–Wilk normality test. Since the variables were normally distributed, one-way analyses of variance (ANOVAs) were used to analyze variables considering time (i.e., T0, TF) as within-subjects factor and group (experimental vs. control) as between-subjects factor. When the ANOVA was significant, post hoc analysis was performed by Paired Sample T-tests. A value of p < 0.05 was considered as significant.

3. Results

3.1. Olfactory Stimuli

The number of correctly identified stimuli did not change over time (T0: control: 3.80 ± 1.85, experimental: 5.10 ± 1.08; TF: control: 4.20 ± 0.97, experimental: 5.30 ± 1.03) and it was not different between groups. This experimental evidence can be well explained by the fact that recruited subjects belonging to both the two groups were not involved in training specifically aimed at improving olfactory identification abilities in the time frame between the first (T0) and the last (TF) sessions.

3.2. Clinical Assessment: Core Psychopathology and Psychiatric Comorbidities Variation

Between T0 and TF, the experimental and the control groups showed significant differences in some dimensions of the questionnaires administered (Table 2). In particular, the BUT and the subscales Impulse to Thinness and Affective Problem of the EDI displayed a significant improvement in the experimental group and a significant worsening in the control group. The CDI displayed a significant improvement in both the two groups (see Table 2).

3.3. Cardiac Variables

Results regarding the cardiac variables are reported in Table 3.
In the baseline condition, LF/HF decreased at TF compared to T0, specifically, in the experimental group. Since this index expresses the sympathetic/parasympathetic balance, a decrease at TF may indicate that the subjects are less stressed in the phase of preparation to the execution of the odor identification task compared to T0. This is more evident in the subjects who performed HCT, even without any improvement in their olfactory perception. Thus, this result suggests a possible reduction in the stress condition of the subjects during resting.
During olfactory stimulation (Task ON), the LFn decreased in both groups, with a slightly more marked decrease in the experimental group, coherently with the assumption above. This is in line with current literature, which indicates a suppression of the sympathetic stimuli due to olfactory stimulation.
The results during the inter-stimulus stimulation (Task OFF) are a bit more contradictory since we observed an increase in NN50, mainly related to the parasympathetic activity, but also an increase in LFn, mainly related to sympathetic activity, in particular in the experimental group. These results could indicate a realignment of the ANS during the inter-stimulus interval, with a more pronounced activation of the sympathetic system in the experimental group (LFn), whereas the contradictory result of NN50 could be even due to the small sample size analyzed.

3.4. Skin Conductance Responses

As for the GSR signal, a significant difference in Non-Specific Skin Conductance Responses (NSCRs) during the Task OFF between T0 and TF only in the experimental group was reported, suggesting that the experimental-group individuals had a higher tendency towards relaxation just after the end of each odor presentation compared to the control group, possibly due to the HCT protocol (Table 4).

3.5. Thermal Variables

As for the thermal imaging, Table 5 shows a list of the temperature features acquired from the facial ROIs considered most relevant to assess the stress status induced by the olfactory test. Table 5 reports the mean thermal variables at T0 and TF, both during the acclimatization and the resting phase, for control and experimental groups. It is worth mentioning that for all the thermal measurements (regarding both the time effect and the time effect per group), the statistical significance was assessed by computing the p-values. This meant that when considering the time effect, the p is always less than 0.01, while when considering the time effect per group, the p is always greater than 0.1.
Columns T0 and TF in Table 6 show the differences in temperature between the acclimatization and resting phase, at T0 and at TF, grouped with respect to the subject group (control and experimental) and to the specific ROI measured. In the last column in Table 6, it was remarked for which ROI the temperature variation between resting and acclimatization is reduced at TF (with respect to T0), as a cue of a better stress recovery, enhanced in the experimental group.
The analysis shows that the absolute value of the difference between the resting and the acclimatization phase decreases for all the ‘thermal markers’ but one (i.e., the frontal left), suggesting a generalized better recovery from the stress induced by the olfactory stimuli for the experimental group than for the control group.
Hence, even if we cannot consider this finding statistically sound, mainly due to the size of the population study, we believe that the results presented do justify further efforts in planning a larger experimentation, exploiting facial thermal markers to assess both the response to stress stimuli and, therefore, the effectiveness of HCT for the AN subject.

4. Discussion

The results presented in the previous section consistently point out that the HCT setting may positively affect the psychological status of the AN-R subjects enrolled in this pilot study, while reducing the stress induced by an olfactory test, specifically designed. The stress level was assessed at baseline, at the beginning and at the end of the experiment, through standard and experimental methodologies for physiological monitoring (HR, HRV, SC, facial thermal imaging). The statistical analysis carried out for all the acquired signals shows that for the clinical variables as well for HRV and SC, it is not possible to draw robust conclusions, due to the low significance of the differences between groups (experimental and control) from T0 to TF. On the contrary, the thermal variables seem to be more robust and statistically relevant.
Disregarding the statistical significance for now, the present study provides a preliminary confirmation of the benefits of HCT, both in reducing stress levels and in alleviating some specific psychological vulnerabilities of eating disorders. In fact, in the experimental group, the stress response level, as measured by various biological parameters, improved over time in comparison to the group of subjects who did not undergo HCT. In the subjects who participated in the HCT sessions, we observed an improvement in some psychological measures, i.e., the drive for thinness, body dissatisfaction, inadequacy, interpersonal insecurity, and affective problems. It is interesting to note that these dimensions represent the core constellation of the maintaining factor of EDs. Notably, the growth rhythms of the crops require patience, waiting, tolerance, and are beyond the control of the subject. In this sense, the HCT setting represents a good context for the development and recovery of emotional attitudes compromised in this disease condition. Obviously, the tutors, both the educators and the agronomist experts, had a fundamental role in mediating the experience, contributing with the transmission of knowledge and emotional reinforcement, so as to motivate the AN-R subjects.
Although throughout the HCT sessions, the subjects were exposed with greater intensity and regularity to the scents and odors of plants, without any specific training for olfactory assessment, the ability to discriminate odors did not show any improvement from T0 to TF, regardless of the group we consider.
However, at TF, the level of stress response to olfactory stimuli was decreased only in the subjects who underwent HCT, while this improvement was not observed in the control group. The reduction in the stress associated with the sensory experience is an encouragement to continue the research on this topic. In a future perspective, the effect of a specific olfactory training, arranged according to what was previously described by Tonacci and colleagues [23], in patients with AN, should also be explored, even in combination with HCT.
Indeed, the olfactory function has an important relationship with the area of emotional memory and may be involved in other psychiatric impairments. In our previous study, we observed that in AN patients, although the ability to discriminate olfactorily is not impaired overall, it is correlated with the autistic component [36]. It is also important to consider the effects of undernutrition on encephalic structures and neuroendocrine modulation, which affects many psychic functions [37]. On the other hand, improvement in this function could be an important therapeutic target given the central role of this sensory channel.

5. Conclusions

In this pilot study, we presented a preliminary assessment of the effect of horticultural therapy in adolescents with anorexia nervosa. To the best of our knowledge, this is the first study in which such treatment was experimented with in patients with eating disorders.
Despite the low sample size, the results of our study suggested that the group of patients who underwent the horticultural therapy showed a clinical improvement in the level of bodily distress and the measure of affective problems. Moreover, in this group of subjects, we also observed a reduction in the level of stress at resting as well as a reduction in the stressful response to olfactory stimuli, as measured by physiological parameters over time. Hence, we would like to remark that there is some evidence concurring in the direction of a positive assessment of the impact of HCT, in addition to conventional clinical treatment, for individuals with a diagnosis of AN-R. The experimentation protocol seems to be convincing as it is and possibly reproducible at a larger scale, to improve statistical robustness. In conclusion, Green therapy experiences and specifically HCT should be proposed as useful activities for reducing stress levels in adolescents with food-related issues diagnosed with AN-R. Reducing stress levels is related to improving clinical parameters and can go a long way toward affecting the subject’s psychopathology, particularly by going to work on the behavioral, cognitive, and emotional rigidities associated with the tendency toward food restriction and the more general psychopathological picture of these young patients.
For future research, we plan to initiate and carry out trials, in order to ensure a greater statistical robustness by increasing the size of the study population; in this perspective, a careful statistical power analysis is required in order to justify the sample size [38], taking into account that large sample size could be a challenge in the case of subjects with AN, who are often difficult to recruit [39].

Author Contributions

Conceptualization, S.M., O.C. and L.B.; methodology, M.A.M., S.C., A.T., M.A.P. and L.C.; software: L.B., A.T., M.A.P. and S.C.; validation, C.F.D.P., V.B., C.N., A.T. and N.Z.; formal analysis, M.A.P. and L.B.; investigation, C.N., F.V., N.Z., S.M., O.C. and A.T.; resources, L.C. and V.B.; data curation, L.B., A.T. and M.A.P.; writing—original draft preparation, O.C., S.M., F.V. and M.A.P.; writing—review and editing, M.A.M., L.B. and N.Z.; visualization, L.C. and C.N.; supervision, S.M.; project administration, V.B. and S.M.; funding acquisition, V.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The project received approval from the Pediatric Ethics committee for the Tuscany Region (Florence, Italy; Register Number: 138/2020). The study was conducted in accordance with the Declaration of Helsinki.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Written informed consent was obtained from the patient(s) to publish this paper.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

Our heartfelt thanks go to Davide Moroni for scientific support, the clinical staff of the therapeutic centers involved in the research, and the patients who participated in the trial.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Arcelus, J.; Mitchell, A.J.; Wales, J.; Nielsen, S. Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies. Arch. Gen. Psychiatry 2011, 68, 724–731. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Hoang, U.; Goldacre, M.; James, A. Mortality following hospital discharge with a diagnosis of eating disorder: National record linkage study, England, 2001–2009. Int. J. Eat. Disord. 2014, 47, 507–515. [Google Scholar] [CrossRef] [PubMed]
  3. Herpertz-Dahlmann, B. Adolescent eating disorders: Definitions, symptomatology, epidemiology and comorbidity. Child. Adol. Psych. Clin. 2008, 18, 31–47. [Google Scholar] [CrossRef] [PubMed]
  4. Favaro, A.; Tenconi, E.; Degortes, D.; Manara, R.; Santonastaso, P. Effects of obstetric complications on volume and functional connectivity of striatum in anorexia nervosa patients. Int. J. Eat. Disord. 2014, 47, 686–695. [Google Scholar] [CrossRef]
  5. Reas, D.L.; Rø, Ø. Time trends in healtHCTTare–detected incidence of anorexia nervosa and Bulimia nervosa in the Norwegian national patient register (2010–2016). Int. J. Eat. Disord. 2018, 51, 1144–1152. [Google Scholar] [CrossRef] [Green Version]
  6. van Eeden, A.E.; van Hoeken, D.; Hoek, H.W. Incidence, prevalence and mortality of anorexia nervosa and bulimia nervosa. Curr. Opin. Psychiatry 2021, 34, 515–524. [Google Scholar] [CrossRef]
  7. Oh, Y.A.; Park, S.A.; Ahn, B.E. Assessment of the psychopathological effects of a horticultural therapy program in patients with schizophrenia. Complement. Ther. Med. 2018, 36, 54–58. [Google Scholar] [CrossRef]
  8. Shao, Y.; Elsadek, M.; Liu, B. Horticultural Activity: Its Contribution to Stress Recovery and Wellbeing for Children. Int. J. Environ. Res. Public Health 2020, 17, 1229. [Google Scholar] [CrossRef] [Green Version]
  9. Lee, M.S.; Lee, J.; Park, B.J.; Miyazaki, Y. Interaction with indoor plants may reduce psychological and physiological stress by suppressing autonomic nervous system activity in young adults: A randomized crossover study. J. Physiol. Anthropol. 2015, 34, 21. [Google Scholar] [CrossRef] [Green Version]
  10. Nicholas, S.O.; Giang, A.T.; Yap, P.L.K. The Effectiveness of Horticultural Therapy on Older Adults: A Systematic Review. J. Am. Med. Dir. Assoc. 2019, 20, 1351.e1–1351.e11. [Google Scholar] [CrossRef]
  11. Blair, C.K.; Adsul, P.; Guest, D.D.; Sussman, A.L.; Cook, L.S.; Harding, E.M.; Rodman, J.; Duff, D.; Burgess, E.; Quezada, K.; et al. Southwest Harvest for Health: An Adapted Mentored Vegetable Gardening Intervention for Cancer Survivors. Nutrients 2021, 13, 2319. [Google Scholar] [CrossRef] [PubMed]
  12. Song, C.; Ikei, H.; Miyazaki, Y. Physiological Effects of Nature Therapy: A Review of the Research in Japan. Int. J. Environ. Res. Public Health 2016, 13, 781. [Google Scholar] [CrossRef] [PubMed]
  13. Rappe, E. The Influence of a Green Environment and Horticultural Activities on the Subjective Well-Being of the Elderly Living in Long-Term Care; University of Helsinki: Helsinki, Finland, 2005. [Google Scholar]
  14. Ulrich, R.S.; Simons, R.F.; Losito, B.D.; Fiorito, E.; Miles, M.A.; Zelson, M. Stress recovery during exposure to natural and urban environments. J. Environ. Psychol. 1991, 11, 201–223. [Google Scholar] [CrossRef]
  15. Korpela, K.; Klemettilä, T.; Hietanen, J. Evidence for rapid affective evaluation of environmental scenes. Environ. Behav. 2002, 34, 634–650. [Google Scholar] [CrossRef]
  16. Zhong, Y.-Q.; Tu, H.-M. Horticultural Activity Type, Psychological Well-Being, and Fruit and Vegetable Intake. Nutrients 2020, 12, 3296. [Google Scholar] [CrossRef] [PubMed]
  17. Han, A.R.; Park, S.A.; Ahn, B.E. Reduced stress and improved physical functional ability in elderly with mental health problems following a horticultural therapy program. Complement. Ther. Med. 2018, 38, 19–23. [Google Scholar] [CrossRef]
  18. Pálsdóttir, M.R.; Grahn, P.; Persson, D. Changes in Experienced Value of Everyday Occupations After Nature-Based Vocational Rehabilitation. Scand. J. Occup. Ther. 2014, 21, 58–68. [Google Scholar]
  19. Clausen, L.; Rosenvinge, J.H.; Friborg, O.; Rokkedal, K. Validating the Eating Disorder Inventory-3 (EDI-3): A comparison between 561 female eating disorders patients and 878 females from the general population. J. Psychopathol. Behav. Assess. 2011, 33, 101–110. [Google Scholar] [CrossRef] [Green Version]
  20. Cuzzolaro, M.; Vetrone, G.; Marano, G.; Garfinkel, P.E. The Body Uneasiness Test (BUT): Development and validation of a new body image assessment scale. Eat. Weight Disord. 2006, 11, 1–13. [Google Scholar] [CrossRef]
  21. Kovacs, M. Children’s Depression Inventory; Multi-Health Systems, Inc.: North Tonawanda, NY, USA, 1992. [Google Scholar]
  22. Tonacci, A.; Di Monte, J.; Meucci, M.B.; Sansone, F.; Pala, A.P.; Billeci, L.; Conte, R. Wearable Sensors to Characterize the Autonomic Nervous System Correlates of Food-Like Odors Perception: A Pilot Study. Electronics 2019, 8, 1481. [Google Scholar] [CrossRef] [Green Version]
  23. Tonacci, A.; Billeci, L.; Di Mambro, I.; Marangoni, R.; Sanmartin, C.; Venturi, F. Wearable Sensors for Assessing the Role of Olfactory Training on the Autonomic Response to Olfactory Stimulation. Sensors 2021, 21, 770. [Google Scholar] [CrossRef] [PubMed]
  24. Gioia, F.; Pascali, M.A.; Greco, A.; Colantonio, S.; Scilingo, E.P. Discriminating Stress From Cognitive Load Using Contactless Thermal Imaging Devices. In Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Virtual, 1–5 November 2021; pp. 608–611. [Google Scholar]
  25. Billeci, L.; Tonacci, A.; Brunori, E.; Raso, R.; Calderoni, S.; Maestro, S.; Morales, M.A. Autonomic Nervous System Response during Light Physical Activity in Adolescents with Anorexia Nervosa Measured by Wearable Devices. Sensors 2019, 19, 2820. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Billeci, L.; Tartarisco, G.; Brunori, E.; Crifaci, G.; Scardigli, S.; Balocchi, R.; Pioggia, G.; Maestro, S.; Morales, M.A. The role of wearable sensors and wireless technologies for the assessment of heart rate variability in anorexia nervosa. Eat. Weight Disord. 2015, 20, 23–31. [Google Scholar] [CrossRef] [PubMed]
  27. Bachi, L.; Billeci, L.; Varanini, M. QRS Detection Based on Medical Knowledge and Cascades of Moving Average Filters. Appl. Sci. 2021, 11, 6995. [Google Scholar] [CrossRef]
  28. Billeci, L.; Marino, D.; Insana, L.; Vatti, G.; Varanini, M. Patient-specific seizure prediction based on heart rate variability and recurrence quantification analysis. PLoS ONE 2018, 13, e0204339. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Shaffer, F.; Ginsberg, J.P. An Overview of Heart Rate Variability Metrics and Norms. Front. Public Health 2017, 5, 258. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  30. Crifaci, G.; Billeci, L.; Tartarisco, G.; Balocchi, R.; Pioggia, G.; Brunori, E.; Maestro, S.; Morales, M.A. ECG and GSR measure and analysis using wearable systems: Application in anorexia nervosa adolescents. In Proceedings of the 8th International Symposium on Image and Signal Processing and Analysis (ISPA), Trieste, Italy, 4–6 September 2013; pp. 499–504. [Google Scholar]
  31. Benedek, M.; Kaernbach, C. A continuous measure of phasic electrodermal activity. J. Neurosci. Methods 2010, 190, 80–91. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Puri, C.; Olson, L.; Pavlidis, I.; Levine, J.; Starren, J. Stresscam: Non-contact measurement of users’ emotional states through thermal imaging. In Proceedings of the CHI’05 Extended Abstracts on Human Factors in Computing Systems, Portland, OR, USA, 2–7 April 2005; pp. 1725–1728. [Google Scholar]
  33. Sorostinean, M.; Ferland, F.; Tapus, A. Reliable stress measurement using face temperature variation with a thermal camera in human-robot interaction. In Proceedings of the 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), Seoul, Republic of Korea, 3–5 November 2015; pp. 14–19. [Google Scholar]
  34. Filippini, C.; Spadolini, E.; Cardone, D.; Merla, A. Thermal imaging based affective computing for educational robot. Proceedings 2019, 27, 27. [Google Scholar]
  35. Chudecka, M.; Lubkowska, A. Thermal Imaging of Body Surface Temperature Distribution in Women with Anorexia Nervosa. Eur. Eat. Disord. Rev. 2016, 24, 57–61. [Google Scholar] [CrossRef]
  36. Tonacci, A.; Calderoni, S.; Billeci, L.; Maestro, S.; Fantozzi, P.; Ciuccoli, F.; Morales, M.A.; Narzisi, A.; Muratori, F. Autistic traits impact on olfactory processing in adolescent girls with Anorexia Nervosa restricting type. Psychiatry Res. 2019, 274, 20–26. [Google Scholar] [CrossRef]
  37. Curzio, O.; Calderoni, S.; Maestro, S.; Rossi, G.; De Pasquale, C.F.; Belmonti, V.; Apicella, F.; Muratori, F.; Retico, A. Lower gray matter volumes of frontal lobes and insula in adolescents with anorexia nervosa restricting type: Findings from a Brain Morphometry Study. Eur. Psychiatry 2020, 63, e27. [Google Scholar] [CrossRef] [PubMed]
  38. Poldrack, R.A.; Baker, C.I.; Durnez, J.; Gorgolewski, K.J.; Matthews, P.M.; Munafò, M.R.; Nichols, T.E.; Poline, J.B.; Vul, E.; Yarkoni, T. Scanning the horizon: Towards transparent and reproducible neuroimaging research. Nat. Rev. Neurosci. 2017, 18, 115–126. [Google Scholar] [CrossRef] [PubMed]
  39. McDermott, C.; Agras, W.S.; Crow, S.J.; Halmi, K.; Mitchell, J.E.; Bryson, S. Participant recruitment for an anorexia nervosa treatment study. Int. J. Eat. Disord. 2004, 35, 33–41. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Plant species grown by patients in order to experience different sensory stimulations during the HTC. Color workstation: beach moonflower (a), lupin (b), madwort (c), marigold (d), snapdragon (e), sunflower (f). Odor workstation: common sage (g), lavender (h), lemon balm (i), lesser calamint (j), parsley (k), sweet basil (l). Shape workstation: Brussels sprouts (m), cauliflower (n), pumpkin (o), radish (p), romaine lettuce (q), zucchini (r).
Figure 1. Plant species grown by patients in order to experience different sensory stimulations during the HTC. Color workstation: beach moonflower (a), lupin (b), madwort (c), marigold (d), snapdragon (e), sunflower (f). Odor workstation: common sage (g), lavender (h), lemon balm (i), lesser calamint (j), parsley (k), sweet basil (l). Shape workstation: Brussels sprouts (m), cauliflower (n), pumpkin (o), radish (p), romaine lettuce (q), zucchini (r).
Nutrients 14 05198 g001
Figure 2. A ‘green thumb’ certification given to each patient in the experimental group at the end of the HCT.
Figure 2. A ‘green thumb’ certification given to each patient in the experimental group at the end of the HCT.
Nutrients 14 05198 g002
Table 1. Odorous solutions used for the stimulation. Solutions were stored for 24 h in the dark at room temperature (20 ± 1 °C).
Table 1. Odorous solutions used for the stimulation. Solutions were stored for 24 h in the dark at room temperature (20 ± 1 °C).
Sample CodeOdour FamilySpecific DescriptorRecipe
First trial
1FruityApricot80 mL of commercial juice + 100 mL of white table wine
2Fresh vegetalTomato80 mL of commercial juice + 100 mL of white table wine
3Fresh vegetalAsparagus60 mL of cooking water + 100 mL of white table wine
4Balsamic/woodySwiss PineCommercial essential oil diluted in white table wine (1% v/v)
5FruityOrange80 mL of commercial juice + 100 mL of white table wine
6FloralLavenderCommercial essential oil diluted in white table wine (1% v/v)
7Mediterranean spicyBasilCommercial essential oil diluted in white table wine (1% v/v)
8Fresh vegetalOlive oilPure EVOO
9FruityGrapefruit80 mL of commercial juice + 100 mL of white table wine
10BalsamicMintCommercial essential oil diluted in white table wine (1% v/v)
11EarthyDirtPure topsoil
12Mediterranean spicyThymeCommercial essential oil diluted in white table wine (1% v/v)
Second trial
1FruityPeach80 mL of commercial juice + 100 mL of white table wine
2Fresh vegetalTomato80 mL of commercial juice + 100 mL of white table wine
3Fresh vegetalSageCommercial essential oil diluted in white table wine (1% v/v)
4Balsamic/woodySwiss PineCommercial essential oil diluted in white table wine (1% v/v)
5FruityOrange80 mL of commercial juice + 100 mL of white table wine
6FloralLavenderCommercial essential oil diluted in white table wine (1% v/v)
7Mediterranean spicyBasilCommercial essential oil diluted in white table wine (1% v/v)
8Fresh vegetalOlive oilPure EVOO
9FruityTangerine80 mL of commercial juice + 100 mL of white table wine
10BalsamicPeppermintCommercial essential oil diluted in white table wine (1% v/v)
11ResinousScots pineCommercial essential oil diluted in white table wine (1% v/v)
12Mediterranean spicyThymeCommercial essential oil diluted in white table wine (1% v/v)
Table 2. Difference in clinical variables from T0 to TF in control and experimental groups. Variables are expressed as Mean (SD). * p < 0.05, ** p < 0.01.
Table 2. Difference in clinical variables from T0 to TF in control and experimental groups. Variables are expressed as Mean (SD). * p < 0.05, ** p < 0.01.
VariableT0TFTime EffectTime × Group EffectPost-Hoc
Body Mass Index p = 0.17p = 0.96
 Control16.56 (1.18)17.12 (0.86)
 Experimental17.33 (1.31)17.92 (1.23)
Child Depression Inventory p = 0.04 *p = 0.47
 Control42.50 (29.08)22.50 (3.42) p = 0.25
 Experimental30.00 (8.12)19.60 (12.28) p = 0.02 *
Body Uneasiness Test p = 0.96p = 0.005 **
 Control2.18 (1.27)3.39 (1.71) p = 0.02 *
 Experimental3.40 (0.74)2.23 (1.49) p = 0.08
Eating Disorder Inventory
Impulse to thinness p = 0.46p = 0.04 *
 Control17.60 (8.82)21.40 (10.41) p = 0.02 *
 Experimental23.80 (4.55)16.20 (8.89) p = 0.08
Bulimia p = 0.70p = 0.45
 Control4.40 (3.67)5.60 (5.86)
 Experimental2.80 (2.17)2.40 (3.91)
Dissatisfaction p = 0.37p = 0.18
 Control24.60 (14.08)26.60 (15.29)
 Experimental29.20 (9.06)19.80 (15.07)
Risk p = 0.47p = 0.11
 Control46.60 (25.09)53.60 (29.16)
 Experimental55.80 (13.77)38.40 (29.50)
Ineffectiveness p = 0.28p = 0.08
 Control25.60 (17.30)29.20 (17.08)
 Experimental36.80 (8.95)23.20 (14.82)
Interpersonal Problems p = 0.05p = 0.15
 Control22.80 (11.77)21.00 (10.29)
 Experimental29.80 (6.38)19.20 (12.26)
Affective Problems p = 0.53p = 0.03 *
 Control23.60 (16.56)34.00 (20.83) p = 0.17
 Experimental38.25 (7.54)21.25 (17.84) p = 0.03 *
Overcontrol p = 0.72p = 0.15
 Control21.60 (10.94)28.40 (16.30)
 Experimental25.20 (10.13)21.00 (13.07)
Table 3. Difference in cardiac variables from T0 to TF in control and experimental groups. Variables are expressed as Mean (SD). * p < 0.05, ** p < 0.01.
Table 3. Difference in cardiac variables from T0 to TF in control and experimental groups. Variables are expressed as Mean (SD). * p < 0.05, ** p < 0.01.
VariableT0TFTime EffectTime × Group EffectPost-Hoc
Baseline
HR p = 0.35p = 0.21
 Control69.41 (21.01)71.07 (6.17)
 Experimental80.32 (10.56)69.84 (13.24)
SDNN p = 0.21p = 0.86
 Control0.04 (0.15)0.05 (0.02)
 Experimental0.04 (0.19)0.06 (0.02)
RMSSD p = 0.23p = 1.00
 Control0.05 (0.02)0.06 (0.02)
 Experimental0.04 (0.03)0.05 (0.03)
NN50 p = 0.19p = 0.47
 Control25.00 (6.83)32.43 (7.05)
 Experimental19.00 (21.04)21.33 (17.57)
LFn p = 0.27p = 0.29
 Control0.17 (0.04)0.17 (0.04)
 Experimental0.29 (0.13)0.23 (0.12)
HFn p = 0.38p = 0.14
 Control0.96 (0.79)0.85 (0.35)
 Experimental0.51 (0.48)0.92 (0.69)
LF/HF p = 0.03 *p = 0.35
 Control0.62 (0.79)0.26 (0.14) p = 0.31
 Experimental1.64 (1.53)0.86 (1.08) p = 0.04 *
Task ON
HR p = 0.82p = 0.59
 Control73.73 (22.21)75.34 (5.33)
 Experimental82.61 (10.35)78.74 (14.44)
SDNN p = 0.15p = 0.49
 Control0.05 (0.02)0.05 (0.02)
 Experimental0.07 (0.03)0.06 (0.02)
RMSSD p = 0.28p = 0.80
 Control0.05 (0.03)0.06 (0.02)
 Experimental0.03 (0.02)0.04 (0.02)
NN50 p = 0.02 *p = 0.54
 Control10.23 (2.65)4.87 (1.38) p = 0.05
 Experimental6.93 (7.15)3.46 (2.32) p = 0.20
LFn p < 0.001 **p = 0.25
 Control0.21 (0.04)0.11 (0.01) p = 0.007 **
 Experimental0.25 (0.05)0.11 (0.01) p = 0.002 **
HFn p = 0.15p = 0.09
 Control0.65 (0.60)0.23 (0.13)
 Experimental0.21 (0.17)0.25 (0.19)
LF/HF p = 0.05p = 0.22
 Control1.49 (1.60)0.94 (0.62)
 Experimental3.18 (2.44)1.06 (0.88)
Task OFF
HR p = 0.45p = 0.47
 Control74.50 (21.01)74.40 (6.81)
 Experimental85.29 (9.06)78.23 (14.60)
SDNN p = 0.69p = 0.26
 Control0.08 (0.03)0.05 (0.02)
 Experimental0.06 (0.02)0.06 (0.02)
RMSSD p = 0.47p = 0.41
 Control0.06 (0.03)0.05 (0.02)
 Experimental0.04 (0.02)0.04 (0.02)
NN50 p = 0.001 **p = 0.35
 Control5.14 (0.75)13.13 (2.68) p = 0.01 *
 Experimental2.78 (2.07)8.32 (5.33) p = 0.03 *
LFn p = 0.001 *p = 0.17
 Control0.11 (0.03)0.18 (0.05) p = 0.11
 Experimental0.10 (0.03)0.23 (0.04) p = 0.004 **
HFn p = 0.12p = 0.38
 Control0.37 (0.36)0.44 (0.21)
 Experimental0.15 (0.07)0.40 (0.34)
LF/HF p = 0.46p = 0.46
 Control0.78 (0.60)0.79 (0.43)
 Experimental1.39 (1.00)2.16 (2.58)
Recovery
HR p = 0.96p = 0.40
 Control66.89 (17.77)70.81 (2.52)
 Experimental78.95 (9.34)74.61 (14.81)
SDNN p = 0.25p = 0.48
 Control0.05 (0.02)0.05 (0.02)
 Experimental0.04 (0.01)0.05 (0.02)
RMSSD p = 0.68p = 0.29
 Control0.05 (0.02)0.05 (0.01)
 Experimental0.03 (0.02)0.04 (0.02)
NN50 p = 0.78p = 0.07
 Control31.91 (5.39)26.50 (8.02)
 Experimental19.54 (18.39)23.66 (16.15)
LFn p = 0.81p = 0.83
 Control0.26 (0.12)0.24 (0.12)
 Experimental0.27 (0.12)0.27 (0.14)
HFn p = 0.74p = 0.13
 Control1.03 (0.72)0.78 (0.27)
 Experimental0.44 (0.34)0.82 (0.67)
LF/HF p = 0.45p = 0.44
 Control0.59 (0.77)0.58 (0.61)
 Experimental1.42 (1.25)3.54 (6.56)
Table 4. Difference in skin conductance variables from T0 to TF in control and experimental groups. Variables are expressed as Mean (SD). * p < 0.05.
Table 4. Difference in skin conductance variables from T0 to TF in control and experimental groups. Variables are expressed as Mean (SD). * p < 0.05.
VariableT0TFTime EffectTime x Group EffectPost-Hoc
Baseline
Tonic p = 0.09p = 0.21
 Control1.31 (0.94)1.07 (0.60)
 Experimental2.16 (1.22)0.81 (0.44)
Task ON
Tonic p = 0.05p = 0.47
 Control2.74 (2.30)1.29 (0.87)
 Experimental4.16 (1.94)1.42 (1.33)
Phasic p = 0.15p = 0.70
 Control0.24 (0.24)0.04 (0.02)
 Experimental0.51 (0.50)0.17 (0.34)
nSCR p = 0.05p = 0.89
 Control6.33 (2.82)2.82 (1.98)
 Experimental6.83 (1.93)3.88 (3.24)
Task OFF
Tonic p = 0.05p = 0.41
 Control2.73 (2.21)1.30 (0.86)
 Experimental4.38 (2.11)1.42 (1.31)
Phasic p = 0.06p = 0.34
 Control0.14 (0.31)0.06 (0.05)
 Experimental0.30 (0.21)0.08 (0.12)
nSCR p = 0.01 *p = 0.10
 Control14.94 (7.31)11.19 (5.47) p = 0.41
 Experimental23.78 (4.33)10.71 (4.52) p = 0.01 *
Recovery
Tonic p = 0.06p = 0.32
 Control1.80 (0.89)0.92 (0.55)
 Experimental3.87 (1.83)1.42 (1.14)
Table 5. Thermal variables from T0 to TF in control and experimental groups. Variables are expressed as Mean (SD). * p < 0.05, ** p < 0.01.
Table 5. Thermal variables from T0 to TF in control and experimental groups. Variables are expressed as Mean (SD). * p < 0.05, ** p < 0.01.
VariableT0TFTime EffectTime × Group EffectPost-Hoc
Acclimatization
Nose p = 0.01 *p = 0.94
 Control31.38 (5.68)26.14 (2.08) p = 0.10
 Experimental35.15 (1.63)30.15 (4.49) p = 0.09
Septum p = 0.04 *p = 0.875
 Control33.36 (3.55)31.37 (2.21) p = 0.26
 Experimental35.03 (1.46)32.40 (2.15) p = 0.09
Frontal right p = 0.005 **p = 0.61
 Control35.80 (1.75)34.39 (1.03) p = 0.14
 Experimental36.14 (0.39)34.27 (0.66) p = 0.006 **
Frontal left p = 0.04 *p = 0.31
 Control35.47 (2.06)34.79 (0.57) p = 0.52
 Experimental36.23 (0.39)34.43 (0.55) p = 0.005 **
Nose-frontal § p = 0.03 *p = 0.77
 Control4.25 (3.98)8.16 (1.15) p = 0.10
 Experimental1.03 (1.30)4.11 (4.26) p = 0.22
Resting
Nose p = 0.005 **p = 0.78
 Control33.71 (5.21)27.45 (3.53) p = 0.07
 Experimental35.60 (2.09)30.22 (3.51) p = 0.02 *
Septum p = 0.01 *p = 0.81
 Control34.43 (3.12)31.66 (2.38) p = 0.18
 Experimental35.71 (1.23)32.48 (1.95) p = 0.01 *
Frontal right p < 0.001 **p = 0.94
 Control36.42 (1.45)34.21 (1.28) p = 0.02 *
 Experimental36.41 (0.41)34.25 (0.70) p = 0.003 **
Frontal left p = 0.001 **p = 0.35
 Control36.12 (1.70)34.62 (0.60) p = 0.09
 Experimental36.55 (0.79)34.28 (0.60) p = 0.005 **
Nose-frontal § p = 0.01 *p = 0.58
 Control2.56 (3.97)7.25 (3.41) p = 0.07
 Experimental0.87 (1.84)4.13 (3.45) p = 0.11
§ Nasal-frontal = the difference between: the mean between the two ROIs of the forehead and the nose tip.
Table 6. Difference in facial ROI from T0 to TF in control and experimental groups, with a focus on the reduction in temperature variation between acclimatization and resting phase at TF with respect to TF.
Table 6. Difference in facial ROI from T0 to TF in control and experimental groups, with a focus on the reduction in temperature variation between acclimatization and resting phase at TF with respect to TF.
Facial ROISubject Group T0TFTemp. Variation (%)Temp. Variation
Reduced
NoseControl2.33−1.3143.78TRUE
Experimental0.450.0784.44
Septum Control1.070.2972.90TRUE
Experimental0.680.0888.23
Frontal rightControl0.62−0.1870.97TRUE
Experimental0.27−0.0292.59
Frontal leftControl−1.35−0.1787.41FALSE
Experimental0.32−0.1553.13
Nose-Frontal Control−1.69−0.9146.15TRUE
Experimental−0.160.0287.5
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Curzio, O.; Billeci, L.; Belmonti, V.; Colantonio, S.; Cotrozzi, L.; De Pasquale, C.F.; Morales, M.A.; Nali, C.; Pascali, M.A.; Venturi, F.; et al. Horticultural Therapy May Reduce Psychological and Physiological Stress in Adolescents with Anorexia Nervosa: A Pilot Study. Nutrients 2022, 14, 5198. https://doi.org/10.3390/nu14245198

AMA Style

Curzio O, Billeci L, Belmonti V, Colantonio S, Cotrozzi L, De Pasquale CF, Morales MA, Nali C, Pascali MA, Venturi F, et al. Horticultural Therapy May Reduce Psychological and Physiological Stress in Adolescents with Anorexia Nervosa: A Pilot Study. Nutrients. 2022; 14(24):5198. https://doi.org/10.3390/nu14245198

Chicago/Turabian Style

Curzio, Olivia, Lucia Billeci, Vittorio Belmonti, Sara Colantonio, Lorenzo Cotrozzi, Carlotta Francesca De Pasquale, Maria Aurora Morales, Cristina Nali, Maria Antonietta Pascali, Francesca Venturi, and et al. 2022. "Horticultural Therapy May Reduce Psychological and Physiological Stress in Adolescents with Anorexia Nervosa: A Pilot Study" Nutrients 14, no. 24: 5198. https://doi.org/10.3390/nu14245198

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop