The results indicate that UAV imaging combined with the modified U-Net model can accurately evaluate residual film pollution. This study provides technical support for the rapid and accurate evaluation of residual plastic film pollution in pre-sowing cotton fields.To accurately evaluate residual plastic film pollution in pre-sowing cotton fields, a method based on modified U-Net model was proposed in this research. Images of pre-sowing cotton fields were collected using UAV imaging from different heights under different weather conditions. Residual films were manually labelled, and the degree of residual film pollution was defined based on the residual film coverage rate. The modified U-Net model for evaluating residual film pollution was built by simplifying the U-Net model framework and introducing the inception module, and the evaluation results were compared to those of the U-Net, SegNet, and FCN models. The segmentation results showed that the modified U-Net model had the best performance, with a mean intersection over union (MIOU) of 87.53%. The segmentation results on images of cloudy days were better than those on images of sunny days, with accuracy gradually decreasing with increasing image-acquiring height. The evaluation results of residual film pollution showed that the modified U-Net model outperformed the other models. The coefficient of determination(R Plastic film mulching is an agricultural technique that can improve soil temperature, reduce soil water loss, suppress weed growth, and improve crop water use efficiency, yield, and quality . HoweverCotton is one of the major cash crops in the world . China iFarmland residual film pollution control is a systematic project. In addition to the development of residual film recycling machines, it is of great significance to carry out efficient and accurate residual film pollution monitoring to provide reference for reducing residual film pollution in farmlands.At present, artificial collection of residual films is mostly used for residual film pollution evaluation. For example, With the rapid development of UAV remote sensing and deep learning technology, UAV imaging combined with semantic segmentation has been increasingly widely used in agriculture. In recent years, some scholars have preliminarily explored UAV imaging-based plastic film-mulched area detection and residual film identification. It is of great significance to monitor whether the farmland reaches the qualified conditions for sowing by the rapid detection of residual film pollution in pre-sowing cotton field. Before sowing in the spring, the agricultural mulch turned into film fragments as the cotton field went through a series of operations, such as straw crushing, ploughing, and field preparation et al. Compared with plastic film mulch area detection after sowing in spring and plastic film residue detection after harvest in autumn, residual film pollution evaluation in pre-sowing cotton fields is more difficult.Aimed at detecting residual film coverage rate in pre-sowing cotton field surface, −2. After harvesting in autumn, straw return was performed after crushing, and films were recovered. Ploughing and other operations were carried out in cotton fields before sowing in spring.Residual film images were collected from Shihezi City, Xinjiang, China , where has a temperate continental climate. The main crops in this area were cotton, and drip irrigation - plastic film mulching has been widely adopted in cotton planting . The amoIn this study, UAV images of 20 residual plastic film-polluted cotton fields were collected using a DJI M200 aircraft  equipped with a Zen Zenmuse X4S camera from 10:00 to 19:00 on sunny and cloudy days from April 5 to April 15, 2021. The image resolution was 5,472 × 3,078 pixels. As shown in The images were manually annotated using Adobe Photoshop CS5 , and all residual films were manually annotated and filled with blue color. Then, the threshold segmentation method was used for binarization. Residual film pixels were labelled as 1, and background pixels such as soil were labelled as 0. The annotation results are shown in As the original images were too large to directly use for training, to accelerate the model calculation, the image resolution was resized to 1,200 × 600 pixels. In addition, the training set data were enhanced in the process of model training. In each epoch of training, random cutting (size: 1024 × 512 pixels), random flipping (left and right), random flipping (up and down), and brightness adjustment were used for data enhancement. Each training epoch obtained 480 new training data, and 55 epochs of training were conducted. Finally, a total of 26,400 enhanced images were obtained and used for training.The U-Net model is a common semantic segmentation network with an “U” shape  for imagDepth and width are important parameters that affect convolutional neural networks. While increasing the network depth and width, the inception module also solves the problem of too many parameters and reduces the amount of parameter calculation . The incThe deep learning model training hardware consisted of an Intel(R) Xeon(R) W-2223 CPU @ 3.60 GHz and 128 GB memory, and an NVIDIA GeForce RTX 3090 Graphics with 24 GB memory. The software environment was Windows 10, CUDA 11.2, CUDNN 8.1.1, Python 3.8, and TensorFlow-GPU 2.5.To simulate the actual application scenario, the hardware and software for the residual film pollution evaluation included an Intel (R) Xeon (R) CPU E3-1230 V2 @ 3.30 GHz, without GPU acceleration, 16 GB memory, Windows 10 operating system, Python 3.7, and TensorFlow-CPU 2.3.In this study, in the segmentation of residual films, a pixel is either classified as a residual film pixel or not. Similar to other binary classification networks, the “sparse categorical cross-entropy” function was used as the loss function. The neural networks were trained with a gradient descent method. The Adam optimizer algorithm was used to optimize the network, and the initial learning rate was 0.001. The batch of the training set was 6. During the iterative training process, changes in accuracy and loss were recorded, while only the best model was saved. When the number of training iterations reached 55, the training process converged and stopped.In this study, the accuracy, F1-score, and mean IOU (MIOU) were used to assess the segmentation performance. The F1-score represents the combined results of precision and recall. The segmentation time and parameters of model were used to assess the segmentation speed and size, respectively.Where TP is true positive, TN is true negative, FP is false positive, and FN is false negative.The residual film coverage rate was used as the evaluation index of residual film pollution. For images with a size of M × N, the residual film coverage rate L is the ratio of the total number of residual film pixels [p  =1] to the total number of pixels in the image .1) and true residual film coverage rate (L2) was evaluated by regression analysis. The coefficient of determination (R2), root mean square error (RMSE), and mean relative error (MRE) were selected as the evaluation indexes.To test the accuracy of the modified UNet in residual film pollution evaluation, the L values of 60 images were calculated. Then, the relationship between the predicted residual film coverage rate  were manually labelled one by one, and soil, straw, and other items were marked as non-residual films (0). As the surface of the residual film attached to soil, the reflection of soil block and other reasons, resulting the existence of false positive (FP) and false negative detections (FN) in this study. The FP represents the segmentation model mistakenly identifies soil, straw and other samples as residual film samples; the FN represents the segmentation model mistakenly identifies residual film samples as soil, straw, etc.This study proposed a model for residual film semantic segmentation based on a modified U-Net model. The image segmentation in this study is a binary classification, including identification and classification of residual films and non-residual films. Therefore, the feature extraction of the traditional U-Net model was simplified in this study to reduce the number of parameters and speed up the computation. Moreover, the multiscale feature extraction inception module was introduced to achieve accurate segmentation of residual films of different sizes by fusing multiscale image features. This modified network model may not perform as well on other more complex images but outperforms several traditional semantic segmentation models, including U-Net, SegNet, and FCN.This study compared the identification performance on sunny and cloudy days and found that the identification performance on cloudy days was better than that on sunny days. This may be due to that the reflection of soil blocks causing them to be misjudged as residual films on sunny days. In addition, by comparing the effect of different image-acquiring height on the residual film segmentation, it was found that the lower the height is, the better the residual film segmentation effect. This may be due to that images acquired at lower heights have higher definition. However, when the height was too low, wind from the UAV’s rotor could blow away residual films, affecting the residual film pollution evaluation. Therefore, in practical applications, the height of UAV should be considered while ensuring image definition.The residual film pollution evaluation method in this paper has application value for the control of residual film pollution. This evaluation system can achieve a rapid and accurate evaluation of residual film pollution. Moreover, rapid evaluation of the degree of residual film pollution can provide some reference for the objective evaluation of the seeding suitability of cotton fields during the spring sowing stage. In addition, this study also provides the theoretical support for the detection of residual film pollution in cotton field plough layer using UAV imaging, the rapid prediction of residual film pollution in cotton field plough layer can be realized by studying the residual film pollution correlation between the surface and plough layer. Compared to manual sampling to monitor residual film pollution, the approach in this study saves manpower and reduces time costs.In this paper, residual film pollution images in pre-sowing cotton fields were collected by UAV imaging system. The more suitable residual film segmentation model was built by modified U-Net model. Finally, the residual film pollution was evaluated based on residual film coverage rate. Through the analysis of the test results, it was found that:(1) The modified U-Net model was proposed by simplifying the U-Net model and introducing an inception module, which can realize the accurate segmentation of residual film from cotton fields before sowing. The MIOU of segmentation reached 87.53%.(2) The identification performance on cloudy days was better than that on sunny days. The identification performance of residual films gradually decreased with increasing image-acquiring height.2 of 0.9849, RMSE of 0.0563, MRE of 5.33% and the average evaluation time per image of 4.85 s on the CPU.(3) The modified U-Net model outperformed other models in residual film pollution evaluation, with R(4) This study provides a theoretical reference for further development of evaluation technology and equipment for residual film pollution based on UAV imaging.The original contributions presented in the study are included in the article/supplementary material; further inquiries can be directed to the corresponding author.ZZ: methodology, model design, data analysis, and original manuscript writing. FQ: data collection and data analysis. QM: data analysis and revision. JY: data collection and revision. HW: data collection. XC and RZ: methodology, editing, revision, supervision, and funding. All authors contributed to the article and approved the submitted version.The authors gratefully acknowledge the financial support provided by the National Natural Science Foundation of China (32060412), the High-level Talents Research Initiation Project of Shihezi University (CJXZ202104), the earmarked fund for China Agriculture Research System (CARS-15-17), and the Graduate Education Innovation Project of Xinjiang Autonomous Region (XJ2022G082).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The reviewer GY declared a shared affiliation with the authors to the handling editor at the time of review.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: In this study, we investigated the associations Lake Urmia’s drought to the prevalence of thyroid nodules (TNs) and metabolic syndrome (MetS) among local inhabitants of the lake. Methods: In this cross-sectional study which was started in 2014, we collected data on 992 adults who participated in the Azar cohort study, in Shabestar county, Iran. The sociodemographic status, smoking, and medical history of the subjects living in the areas adjacent to (n = 163) and far from (n = 829) Lake Urmia were collected through questionnaires. After obtaining written consent, anthropometric factors and blood pressure (BP) were measured. The lipid profile and fasting blood glucose (FBG) of the respondents were measured using colorimetric methods, and all underwent thyroid examination and sonography. Furthermore, the size and characteristics of nodules were determined with a fine-needle aspiration biopsy (FNAB) method. Results: We did not find any significant difference in the prevalence of TNs between the two groups (P=0.44), whereas the prevalence of MetS were significantly higher among the subjects from the regions that were far from the Lake (P=0.04). After adjustment for confounding factors (age and gender) in both groups, low risk of TNs  and high risk of TNs  were not significantly associated to MetS (P>0.05). Conclusion: In this study, Lake Urmia’s drought was identified to be with no contribution to the prevalence of TNs and MetS. Therefore, long term perspective studies are suggested to reach precise results. While most nodules are benign, 8–15% prove to be cancerous. The thyroid cancer is the fourth leading type of cancer worldwide, and the age-standardized incidence rate of the cancer in Iran was 1.57 in 1990, which increased by 131%, until 2019. The age-standardized prevalence rate of thyroid cancer was 30.19 in 2019,which increased by 164% from 11.44 in 1990.4 In northwest of Iran, Lake Urmia, the second largest saline lake, is drying due to several reasons, including climate change, excessive groundwater extraction, lack of efficient water management, industrial and domestic overuses, dam constructions and devoting uncontrolled water sources for agricultural use.2 A recent study conducted by Sadegh Tabrizi et.al showed that Lake Urmia’s drought has had serious effects on hypertension and anemia in the individuals living near to the lake, but it has not had significant effects on the prevalence of hyperlipidemia, overweight/obesity, asthma, angina, infraction, diabetes, and vitamin D insufficiency/deficiency in the area.5 Lake Urmia’s drought seems to be a serious threat to the environment, the health of people, local economy, and food security. The ecosystem of the area around the lake might be completely destroyed in parallel with the lake drought. It is shown that Lake Urmia’s drought created several centers of salt dust, and affected the agriculture, economy and public health of the area.6 Several reports have demonstrated a positive association between metabolic syndrome (MetS) and the prevalence of TNs. It was hypothesized that compensatory hyperinsulinemia following insulin resistance in previous MetS might be responsible for the rising trend of TNs.7 On the other hand, a previous study found that TNs were significantly related to an increased risk of MetS. Insulin resistance can directly activate the proliferation pathway, through insulin or insulin-like growth factor 1, regulating the expression of thyroid genes, and the proliferation and differentiation of thyroid cells. In addition, insulin resistance may also be related to thyroid vascular structure.8 In the past 30 years, TNs have become a common thyroid disorder worldwide, which may increase the possibility of thyroid cancer. Therefore, the risk factors associated with TNs have received significant attention, in recent years. A variety of metabolic diseases are considered to be important risk factors for TNs. To the best of our knowledge, there is no study that has examined the contribution of Lake Urmia’s drought to the prevalence of TNs and MetS. Therefore, the aim of the present study was to examine the association between Lake Urmia’s drought and the prevalence of TNs and MetS in the inhabitants of the area close to Lake Urmia.9 explained with more details elswhere.10 In this cross-sectional study, 2000 adult subjects aged 35-70 years were recruited. The Azar Cohort study is a part of the large Iranian prospective epidemiological research study (Persian Cohort), Multi-stage stratified random sampling was applied to select participants from five villages near/adjunct the lake (adjunct area at least 5 km), and six villages far from the lake areas. Eligible participants were invited through telephone call to take part in the survey. The research objectives and protocol were explained to the participants, and all signed written consent forms. Participants with the history of thyroid diseases were excluded. Thyroid examination and thyroid ultrasonography were performed by a trained general practitioner, according to the guideline developed for the cohort.2.11 Blood pressure (BP) was measured twice a day with 2-minute intervals in each arm in a sitting position after a 10-minute rest period using a mercury sphygmomanometer . The averages of these two measurements were used as the daily systolic and diastolic BP measurements.12 Using National Institute of Health (NIH) guidelines, anthropometric factors, including body weight, height, and waist circumference were measured, and body mass index (BMI) was calculated using the formula kg/m Blood samples were collected after a 10–12 hours overnight fast. The fasting blood glucose (FBG), triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were determined by enzymatic methods.13 In this study, the National Cholesterol Education Program Adult Treatment Panel III report criteria (ATP III) was used to select participants with MetS. At least, three of the following criteria were defined as MetS: waist circumference ≥ 102 cm for men and ≥ 88 cm for women, TG ≥ 150 mg/dL or drug treatment for elevated TG as an alternate indicator, and HDL-C values of < 40 mg/dL for men and < 50 mg/dL for women. Hypertension was defined as systolic BP ≥ 130 mm Hg and/or diastolic BP ≥ 85 mm Hg or the use of antihypertensive medications. Elevated FBG was considered to be ≥ 100 mg/dL or the use of glucose-lowering medications.14 Ultrasound is the preferred imaging modality for TNs. Participant underwent thyroid examination and sonography using a device with a 7.5 MHz probe. Furthermore, the size and characteristics of nodules were determined with fine-needle aspiration biopsy (FNAB) method. FNAB is the accepted diagnostic test to determine whether a TN is benign or malignant. Nodules with 1 cm of diameter and larger, and/or nodules with suspicious sonographic appearance warrant cytological analysis to better quantify the risk for malignancy.P value less than 0.05 was considered as statistically significant. Data were analyzed using IBM SPSS Statistics . Descriptive statistics were performed to explore mean and standard deviation (SD) for continuous variables and prevalence (%) for categorical variables, respectively. The normality of the continuous variables was examined using descriptive statistics. The independent sample t-test and chi-square test were used for between-group comparisons. The relationships between prevalence of TNs, MetS and study variables were assessed using binary logistic regression analysis. The odds ratios (ORs) and 95% confidence intervals (CIs) were obtained using logistic regression analyses with/without adjustments for age and gender. A  General characteristics of the participants according to distance from Lake Urmia were presented in P = 0.01). However, the risk of TNs, diabetes, and hypertension was the same in both studied groups (P > 0.05). The prevalence of MetS was significantly higher in the regions far from the Lake Urmia in comparison with the regions near to the lake (P = 0.04). As presented in  The association between TNs risk (low risk vs. no risk participants) and MetS by distance from Lake Urmia, using binary logistic regression analysis, is shown in  The association between TNs risk (high risk vs. no risk participants) and MetS by distance from Lake Urmia, using binary logistic regression analysis, is shown in 15 However, in the previous studies conducted by Sanei Taheri et al16 and Rezaei-Delui et al,17 the prevalence of TNs in Iran was reported to be 52.3% and 28.6%, respectively. The statistical differences found in the prevalence of TNs in these studies may be due to the differences in evaluation time, age and gender of target populations, and iodine status (iodine deficiency) of the studied population by their living regions.18 Based on the results of this study, the overall prevalence of TNs was 37% , and the age range of participants with TNs was from 60 to 69 years. Multi-nodular (more than two nodules) was 46.9%  in the patients with ≥ 60 years of age. These findings were in accordance with the results of Jiang et al, who reported the prevalence of TNs to be 49% , among South Korean patients with 60-69 years of age.20 Previous clinical studies confirmed these results, based on the frequency of nodules in pregnant and infertile women.22 In the present study, we found age and gender in association with the prevalence of TNs. The prevalence of TNs in the patients with 70 years of age and older was higher than those in the patients with less than 70 years of age. In the present study and most of previous researches, the prevalence of TNs is reported to be higher in females. The reason for such a higher incidence of TNs in women might be related to the effect of estrogen on thyroid stimulating hormone. The effects of thyroid tissue and thyroid neoplasty on the expression of estrogen receptors in these tissues may indicate the role of estrogen on the growth of TNs.24 Our study findings showed that the Lake Urmia’s drought had no contribution to the prevalence of TNs, however, the prevalence of MetS was significantly high in the region far from the lake. In accordance with our results, Sadegh Tabrizi et al evaluated the effects of Lake Urmia’s drought on the health of residents near to the lake, and found significant differences in the mean levels of serum TC, LDL-C, HDL-C, and TG between those from the Lake Urmia’s adjacent areas and their control group.5 Several studies have revealed that geographical distance from sea and climate change have serious health outcomes, and may alter the prevalence of several chronic diseases.5 Such controversial findings between their study and ours may be explained by the difference in population groups in each study. For instance, Sadegh Tabrizi et al, only included the participants from urban areas, but we included participants from both urban and rural areas. Furthermore, they conducted sampling only from three cities in each area, but we selected five to six villages/cities in each group. In the present study, we did not find any difference in the prevalence of hypertension and BMI by residency in these two areas. Sadegh Tabrizi et al also found no significant difference in the prevalence of type 2 diabetes and obesity between the two groups, however, the prevalence of hypertension and prehypertension was significantly higher in the regions near to the lake.26In another study, the risk of TNs increased by increase in MetS components.27 In our study, however, we found no significant association between MetS and TNs, which may be justified by the differences in demographic characteristics and iodine status of the studied populations. Zhang et al in a recent meta-analysis revealed uncertainty on whether this association will be sustained in population with different demographic characteristics. They, also, reported that iodine has a crucial impact on the prevalence of thyroid diseases and MetS. Their findings, eventually, showed no association between TNs and MetS in iodine-deficient populations.8 In our study, even after adjustment for confounding factors (age and gender), no association was found between the risk of TNs and MetS in both groups. Previous reports suggest the components of MetS as possible risk factors for TNs. MetS is thought to trigger TNs via the stimulation of thyroid proliferation and angiogenesis induced by hyperinsulinemia, hyperglycemia, and dyslipidemia. As a strength, the present study is the first research that examined the effects of Lake Urmia’s drought on the prevalence of TNs and MetS. However, the cross-sectional design of the study might be considered as a limitation, and thus we warrant cause-effect relationship between Lake Urmia’s drought and metabolic changes in this population. Longitudinal studies are needed to confirm our results. In conclusion, for the first time, we revealed that Lake Urmia’s drought is not contributed to the prevalence of TNs and MetS among the population living in the lake area. Further studies with long-term perspectives are recommended to reach precise results. The authors are deeply indebted to all the patients who participated in this study. This work was financially supported by Endocrine Research Center, Tabriz University of Medical Sciences. We thank the contribution by the investigators and the staff of the Azar cohort study.Conceptualization: Alireza Ostadrahimi, Majid Mobasseri.Data curation: Jalil Hoshyar.Formal Analysis: Elnaz Faramarzi.Funding acquisition: Majid Mobasseri.Investigation: Jalil Hoshyar, Elnaz Faramarzi.Methodology: Majid Mobasseri.Project administration: Jalil Hoshyar, Elnaz Faramarzi.Resources: Alireza Ostadrahimi.Software: Samira Pourmoradian, Elnaz Faramarzi.Supervision: Majid Mobasseri.Validation: Elnaz Faramarzi.Visualization: Samira Pourmoradian.Writing – original draft: Samira Pourmoradian, Elnaz Faramarzi.Writing – review & editing: Elnaz Faramarzi, Helda Tutunchi. Endocrine Research Center of Tabriz University of Medical Sciences, Tabriz, Iran and the Liver and Gastrointestinal Diseases Research Center of Tabriz University of Medical Sciences supported this study (Grant number 700/108). The present study was approved by Ethics Committee in Tabriz University of Medical Sciences (Ethics code: IR.TBZMED.REC.1397.778). The authors declare no conflict of interest.


The COVID-19 pandemic had a large consequence on healthcare systems, increasing the risks of psychological issues in health professionals. Nurses, in particular, have been exposed to multiple psychosocial stressors and struggled with intensive work, insufficiency of resources and uncertainty in the face of an unknown disease. Life satisfaction might protect nurses from the consequences of chronic stress. The aim of this study was to explore the mediating role of satisfaction with life in the relationship between depression, stress, anxiety and burnout .A cross-sectional, descriptive, correlational study design was performed, using an online questionnaire distributed via social networks. A total of 379 nurses completed the survey, comprising standardized measures of satisfaction with life, resilience , depression, anxiety, stress , and burnout . A hierarchical regression model was estimated for each burnout dimension.Participants showed high levels of work, personal and client-related burnout, 57.3%, 57%, and 35.1%, respectively. More than 70% of the respondents had a normal level of depressive symptoms, 66.8% presented normal level of anxiety and 33.5% of the respondents reported mild, moderate, severe or extremely severe symptoms of stress. The results revealed that life satisfaction partially mediated the association between stress and personal burnout, depression and work-related burnout, and the association between anxiety and client-related burnout in nurses.The COVID-19 pandemic brought added difficulties for nurses’ work conditions, whereby it became necessary to develop adaptative measures that reduce stressors in work environment and promote nurses’ life satisfaction. Nurses are subject to high stress levels in their professional roles that can lead to numerous mental health disorders. With the emergence of the pandemic caused by the COVID-19 virus, the challenges facing nurses are diverse, given that they have a greater number of patients to attend to, they face a disease about which there are still many doubts and uncertainties, and they are faced with organizational issues in the workplace that lead to feelings of fear and insecurity .In a recent study with nurses and physicians from Wuhan, it was verified that female nurses who work directly with COVID-19 patients, were generally more vulnerable to depression, anxiety and stress than male nurses, in these particular working conditions . In a saBurnout is a psychological syndrome of physical, emotional, and mental exhaustion, caused by the prolonged exposure to high emotional demands in the workplace , 10. AcaMore is known about the risk factors that predict mental health problems than the protective factors and tactics that foster positive development for individuals to cope with atypical stress levels. The pandemic of COVID-19 as an extremely adverse life event became a factor that may contribute for the development of mental health problems , 6, 8. IThe subjective well-being is defined under two distinctive angles “a person’s cognitive and affective evaluations of his or her life” . The affResearch shows that job burnout has a high correlation with subjective well-being and that a high level of job burnout may cause a decline in subjective well-being . Oates eResearch shows that there is a negative correlation between life satisfaction and mental health symptoms of depression, anxiety and stress , 27 and The COVID-19 pandemic has affected the mental health and well-being of nurses, as it exposes them to extremely stressful work conditions. There are not many studies about the relation of the COVID-19 pandemic and the mediating role of life satisfaction in mental health of nurses, whereby we decided to deepen this topic and study the variables that may be related with this. Based on the previous research it was hypothesized that lesser stress, anxiety, depression, and burnout would be associated with higher subjective well-being, as such, this study aims to analyze the mediating role of life satisfaction in the relationships between anxiety, stress, depression, and burnout among nurses.th and June 8th, 2020, applied to nurses working in Portugal. This study received approval from the Ethics Committee of Faculty of Medicine of University of Porto  and was in line with the Declaration of Helsinki. All nurses gave their online informed consent previous to the survey. The questionnaire was made available through nurses’ professional organizations, institutional webpages and social media platforms.This is a descriptive cross-sectional and correlational study. It was a web-based survey implemented in Google Forms platform, from May 9The questionnaire included sociodemographic data , the Copenhagen Burnout Inventory, the Resilience Scale, the Depression Anxiety and Stress Scale and the Satisfaction with Life Scale.Burnout was measured by the validated Portuguese version of the Copenhagen Burnout Inventory (CBI) , 11, whiPsychological resilience was obtained by the Resilience Scale . This scThe EADS is the Portuguese version of DASS-21  , 32 is aThe Portuguese version of the Satisfaction with Life Scale  , 34 was 1; Q3) if non-normally distributed. The normality of distributions was verified by observation of the respective Q-Q plots. Correlation between variables was analyzed by Spearman coefficient. Internal consistency of the subscales was verified using Cronbach’s alpha (α). For each outcome of the burnout subscales , a separated multiple linear regression was performed. To decide which independent variables to include in each multiple regression, simple linear regressions were performed with each of the following variables: sex, marital status , parental status , educational level , lives with a person at risk for COVID-19 infection (no/yes), years of professional experience , diagnosed health problem (no/yes), direct contact with infected people (no/yes), resilience, depression, anxiety, stress and satisfaction with life scale. All variables that have correlation with the outcomes at p ≤ 0.20 in a simple regression were included in the multiple linear regressions. Then the variables were removed in descending order of the p-value, until only the significant variables were maintained in the final multiple models. Stress was the variable that proved to be associated with personal burnout and that met the requirements of mediation, considering life satisfaction as a mediating variable. The same was found between depression and work-related burnout and between anxiety and client related burnout. Hierarchical regression models were estimated to examine the mediating role of satisfaction with life in the relationship between stress and personal burnout; depression and work-related burnout; and anxiety and client-related burnout.Data analysis was performed using Jamovi software  and SPSS® Statistics . Categorical variables were presented using absolute and relative frequencies. Quantitative variables were described by the mean and the respective standard deviation (SD) if normally distributed or by the median (Mdn) and the respective interquartile interval (Q2), and R2-changes (ΔR2) for each step were provided. Multicollinearity was verified through tolerances and variance inflation factors ranges, then the Sobel test was pursued to assess the mediation effect. Values of p ≤ 0.05 were considered significant.Standardized estimates (β), F statistics, determination coefficient . Regarding age, nurses had an age range between 22 and 65 years old, and the average age was 41 years old.The participants worked mainly in primary healthcare n = 139, 36.7%), 58 in inpatient services with no COVID-19 patients (15.3%), 49 in services with no inpatient wards (12.9%), 44 in emergency services (11.6%), 29 in COVID-19 inpatient areas exclusively (7.7%), 27 in intensive care units (7.1%), 20 in palliative care units (5.3%) and 13 in operating rooms (3.4%). From the participants, 123 (32.5%) had health problems and 37 (9.8%) stated they had started medication for health problems during COVID-19 pandemic  presented normal levels of anxiety, followed by moderate symptoms (12.9%) and severe or extremely severe symptoms (13%). From the sample, 33.5% of the respondents reported mild, moderate, severe or extremely severe symptoms of stress.1; Q3] of 18  points.In general, participants showed high levels of work, personal and client-related burnout, 57.3%, 57%, and 35.1%, respectively. Nurses also showed high satisfaction with life with a median [Qp < 0.001) as shown in Table Burnout subscales, particularly personal and work-related burnout were significantly associated with anxiety, depression and stress, with Spearman’s rho correlations ranging from 0.51 to 0.60 (p < 0.001), and a negative association between personal burnout and satisfaction with life, accounting for an increase of 2% in the explained variance .In the first step, all the independent variables considered associated with personal burnout  were adjusted in a multiple linear regression. The obtained model Table  showed ap = 0.020), satisfaction with life was shown to have a partial mediating role in the association between stress and personal burnout  reduced from 0.37 to 0.33 after the inclusion of satisfaction with life in the model , and a negative association between work-related burnout and satisfaction with life, accounting for an increase of 4% in the explained variance .In the first step, all the independent variables considered associated with work-related burnout (anxiety and stress) were adjusted in a multiple linear regression. The obtained model Table  showed ap < 0.001), satisfaction with life showed to have a partial mediating role in the association between depression and work-related burnout , and a negative association between client-related burnout and satisfaction with life, accounting for an increase of 6% in the explained variance .In the first step, all the independent variables considered associated with client-related burnout  were adjusted in a multiple linear regression. The obtained model Table  showed ap < 0.001), satisfaction with life was shown to have a partial mediating role in the association between anxiety and client-related burnout  in Portuguese nurses during COVID-19. A preliminary analysis showed a significant positive correlation between depression, anxiety, stress and burnout dimensions. These data are in line with the literature review and studies that supports that these emotional states are predictors of burnout –37. In aOf particular interest are the differential relationships found between negative mental states  and the three burnout dimensions through life satisfaction. These data support the tripartite model , accordiParticularly, nurses who perceived higher level of depression would feel dissatisfied with their life, reported more physical and psychological fatigue and exhaustion related to their work. In fact, work overload, recurrent and prolonged exposure to situations of suffering, the absence of effective means to resolve the situation of illness, the change in paradigm of action due to the demand for physical distance, the substantial increase in deaths, are only some of the factors that may be at the origin of the development of depressive symptoms .With regard to the relationship between depression and burnout, the data from this study reinforces prior findings which states that burnout and depression may develop in tandem , or thatOn the other hand, nurses perceiving a higher level of stress would feel unsatisfied with life and feel more physical and psychological fatigue and exhaustion as related to their personal life. In fact, stress arises from situations which exceed the physical and/or psychological capacities of individuals . The focIn turn, nurses who perceive a higher level of anxiety have greater client-related burnout. Anxiety is an aversive emotional response to stress, which results from a threat assessment and is characterized by subjective feelings of worry and apprehension regarding the possibility of physical or psychological harm, often accompanied by increased physiological activation . In thisThese data showed that males perceived significantly higher client-related burnout in comparison with females. A possible reason for this result can be framed within Eagly's  gender rThese results are quite interesting, as they corroborate the idea that burnout is context free and can therefore result from chronic stress from any domain of life, as advocated by several authors , 49.Regarding satisfaction with life acting as a mediator between mental states  and burnout , we verified that this mediation is important in explaining how depression, anxiety or stress affects nurse’s well-being. Indeed, life satisfaction seems to be as a substantive variable in psychological health and well-being , 51. ThuAlso, some interventions focusing more on the professional, may be teaching methods for stress management and resilience-building and behavioral and mental change processes , 60 as wThis study has some limitations. The study is based on a web‐based survey, disseminated through social networks and email, which might have been influenced by self‐selection bias. The study was carried out during the first wave and is related to only a specific pandemic period, and only enabled us to assess the burnout experienced during a specific period. It would be interesting to replicate this web‐survey in other waves to compare changes in levels of different psychological and occupational variables. Further investigation could employ a longitudinal design which examines the long-term effects of the pandemic in nurses and the level of life satisfaction. No retrospective information was collected. In this sense, we cannot know if depressive symptoms, stress and anxiety, for example, pre-date the pandemic context and whether or not they were exacerbated by the global phenomenon COVID-19. Also, there were a large number of female nurses compared to males, which may underrepresent male nurses. The sample dimension and distribution does not allow us to relate the place where nurses work with the level of life satisfaction as Bartosiewicz et al.  found, aPortuguese nurses experienced a high prevalence of physical, emotional, and mental exhaustion. After controlling independent variables (such as sociodemographic and context factors), depression was positively associated with work-related burnout and negatively associated with life satisfaction; anxiety was positively associated with client-related burnout and negatively associated with life satisfaction; stress was positively associated with personal burnout and negatively associated with life satisfaction. Moreover, life satisfaction could partially mediate the relationship between depression, anxiety, stress and different dimensions of burnout. In this sense, when individuals experience several stress and adverse circumstances, such as the COVID-19 pandemic, life satisfaction could protect against distressing events, and can be an operative variable in sustaining mental health. These findings corroborate the role that institutions and nurses’ leaders have in the promotion of better work conditions and strategies that enhance life satisfaction in nurses .


This study examines the self-rated health and well-being of Icelandic teachers just before and over a year after COVID-19 first appeared. We ask, what was the stress level in 2021 compared to 2019 and the impact of mental and physical health and health symptoms on perceived stress? Were there any changes in self-assessed mental and physical health? Were there any changes in self-assessed mental and physical health symptoms? The study is based on an online survey conducted in 2019 and 2021. A total of 920 primary school teachers answered the questionnaire in part or in full, after three reminders. The main findings show increased stress, worsening mental and physical health, and increasing mental and physical symptoms in 2021 compared to 2019. The results also show a higher percentage of women than men reporting high stress, with women scoring higher on the PSS scale, but the gender patterns for mental and physical health are less clear. The results show that the COVID-19 pandemic had negative consequences on the health and well-being of the teachers. The study demonstrates the importance of school authorities keeping an exceptionally watchful eye on the welfare and well-being of teachers in the wake of the COVID-19 pandemic. In numerous studies, teaching has been identified as a profession with high stress levels . Unfortunately, economic crises regularly plague societies. Studying the health and well-being of key professions in society, such as teachers, during a period of economic crisis is, therefore, essential. Marmot and Bell  predicteThe most recent global economic crisis was the one that followed the COVID-19 pandemic. Studying teachers in Spain, García et al.  showed tThe COVID-19 pandemic affected various other factors that can be directly attributed to the virus, such as gender equality , work–liThe study presented here was conducted in Iceland; the virus was confirmed to have reached the country in February 2020. The infection rate was one of the highest in the world (possibly due to extensive screening), and the pandemic influenced the operations of schools, as in many other countries. However, around 92% of primary schools remained open, albeit with some restrictions to minimise the risk of spreading the pandemic among schoolchildren. These restrictions included grouping students and organising their attendance in school at different times or days. Almost all schools started distance teaching in one way or another to support students’ homework . They haThat different groups of teachers experienced the situation during the pandemic differently in Iceland is in line with Mondragon et al. , who shoThe studies mentioned above were all conducted after the COVID-19 pandemic took place. The strength of our study presented here, and what separates it from the above-mentioned studies, is that the study uses data from a longitudinal panel study conducted among teachers both before and after the pandemic—more concretely, one year before and one year after the virus reached Iceland. Therefore, the aim of the study was to measure what changes, if any, occurred in self-rated occupational health among teachers between the two time points of the study. More concretely, our research questions are as follows:What was the stress level in 2021 compared to 2019 and the impact of mental and physical health and health symptoms on perceived stress?Were there any changes in self-assessed mental and physical health?Were there any changes in self-assessed mental and physical health symptoms?We analysed the data with regard to gender, age, marital and family status, number of years in teaching, and employment rate.Health and well-being of Icelandic municipal employees, conducted between 2010 and 2021. The data used here were collected using pretested questionnaires sent electronically to the participants in 2019 and 2021. The participants came from 12 of the 64 municipalities in Iceland. The ethics committee of the University of Iceland approved the research.Data used in this study were from the longitudinal panel study, called The participants in this study were 920 primary school teachers in 12 municipalities in Iceland who participated at time 1 (2019) and 2 (2021). Public schools are run by the municipalities, which is by far the most common form of school in Iceland.In 2019, a total of 2125 teachers (73%) completed the questionnaire in full or in part; 920 also answered the questionnaire in 2021. The 10-item Perceived Stress Scale (PSS-10) was used to measure the respondents’ perceptions of stress . The purMental and physical health was measured with three questions: (1) ‘Is your mental health better or worse than it was 12 months ago?’ and (2) ‘Is your physical health better or worse than it was 12 months ago?’ There were five response options for those two questions: 1 = much better than 12 months ago; 2 = somewhat better than 12 months ago; 3 = the same as 12 months ago; 4 = somewhat worse than 12 months ago; and 5 = much worse than 12 months ago. Regarding health symptoms, the question was, (3) ‘Do any of the following symptoms interfere with your daily life: lack of strength, myositis, pain in the back/shoulders, frequent headaches, abdominal pain, dyspnoea, sleep disturbances, extreme worry, anxiety, sadness, arrhythmias, hypertension, colon spasms, and colds/fevers?’ There was a choice of four responses: 1 = Yes, last month; 2 = Yes, last three months; (3) Yes, last six months; and 4 = No, never. In addition, there were questions about gender , age (year of birth), marital status , parental status (with children/no children), working experience as a teacher (less than a year/1–5/6–10/11–20/21 years and longer), and employment rate (full-time/part-time).p-values. A paired-samples t-test was conducted to evaluate the stress level in 2021 compared to 2019. An independent-samples t-test was conducted to explore the difference between PSS score and gender, marital status, parental status, and employment rate in 2019 and 2021. A one-way ANOVA was conducted to explore the difference between PSS score and age and working experience as a teacher in 2019 and 2021. McNemar’s test was used to evaluate if there were any changes in self-assessed mental and physical health and mental and physical health symptoms between 2019 and 2021. Generalised estimating equations (GEEs) were used to evaluate the impact of mental and physical health and mental and physical symptoms, gender, age, marital status, parental status, work experience as a teacher, and a full-time or part-time position on perceived stress over time. In Model 1, the main effects of mental and physical health and mental and physical symptoms were examined. In Model 2, gender, age, marital status, and parental status were added to Model 1. In Model 3, teacher experience and full-time or part-time positions were added to Model 2. This shows an interaction between time and mental symptoms, time and physical symptoms, time and worse mental health, and time and worse physical health. We obtained the odds ratio (OR) and associated p-value for each predictor in the GEE models. Statistical tests were conducted at a 5% level of significance, and data analyses were conducted using SPSS version 22.0. The number of participants varied slightly in the analysis because of some missing values for the predictor variables.The results are presented as numbers, percentages, averages, standard deviations, odds ratios, and associated t(815) = −7.59; p = 0.001), indicating higher stress levels in 2021 than in 2019. In 2019, 18.8% of the teachers scored 20 or higher on the PSS scale, showing high stress, according to Cohen (1983), and in 2021, the proportion was higher, at 28.0%. p = 0.001). The results also show that the average score for stress turned out to be significantly higher in 2021 than in 2019 in all groups examined (p < 0.05), except for teachers aged 30 and younger and teachers who worked for less than a year for the municipality (p > 0.05).The results revealed an increased mean score on the PSS, from 13.5 to 15.4 (t(845) = −2.51; p = 0.012) and in 2021 (t(863) = −2.37; p = 0.018). There was also a significant difference in mean PSS score by age in 2019  = 7.97; p = 0.001) and in 2021  = 17.53; p = 0.001). The post hoc tests revealed a lower mean score on the PSS by the 51–60 age group than the other age groups in 2019 and 2021. There was no difference in the mean score for the PSS by marital status in 2019, but, in 2021, the mean score for the PSS was higher among teachers living alone than among teachers who were married or cohabiting (t(863) = −2.46; p = 0.014). Furthermore, the mean score for the PSS was higher among teachers living with children both in 2019 (t(845) = −3.30; p = 0.014) and in 2021 (t(840) = −6.25; p = 0.001). However, the results revealed no differences in the mean score for PSS depending on whether the teachers were in full-time employment or part-time employment (p > 0.005).The results showed that the mean score for the PSS was higher for women than men in 2019 (p < 0.05), but the time point of the study was not (p > 0.05). These results indicate that teachers with worse mental health (OR = 5.649), teachers with measured mental symptoms (OR = 4.509), teachers with worse physical health (OR = 0.671), and teachers with physical symptoms (1.602) were likelier to score higher on the PSS scale, controlling for other factors in the model. Even after adding gender, age, marital status, and parental status (Model 2) plus years in teaching and full-time or part-time positions (Model 3) to the model, worse mental health (OR = 5.380), worse physical health (OR = 0.743), mental symptoms (OR = 4.414), and physical symptoms (OR = 1.340) remained significant factors (controlling for other factors in the model).The goodness of fit of the models in p < 0.001). Furthermore, the results show a significantly higher proportion of worse mental health in 2021 than in 2019 for all groups examined (p < 0.05), except for teachers 30 years old and younger, teachers older than 60 years, and teachers who had worked for less than a year as a teacher (p > 0.05).p < 0.001). There was a significantly higher proportion of worse physical health in 2021 than in 2019 for most groups examined (p < 0.05), but not for teachers 61 years and older, teachers not living with children, teachers who had worked as teachers for 11 years or longer, and teachers in part-time employment (p > 0.05).The proportion of those who reported much worse and somewhat worse physical health rose from 16.5% in 2019 to 26.5% in 2021 (p > 0.05). Anxiety, extreme worry, and sadness increased statistically between the time points of the study (p < 0.05). The biggest change over time was in sadness, the incidence of which rose from 32.0% in 2019 to 47.9% in 2021. The most common physical symptom reported was pain in the back/shoulder and myositis; however, the proportion of teachers who reported that pain in the back/shoulder had interfered with their daily lives in the last 12 months almost stayed the same in 2019 and 2021, but the proportion of myositis decreased between 2019 and 2021 (p > 0.05). Five out of ten physical health symptoms increased statistically between the two time points of the study: lack of strength, frequent headaches, abdominal pain, dyspnoea, and arrhythmias (p < 0.05). The biggest change over time was in frequent headaches, the incidence of which rose from 43.7% in 2019 to 58.0% in 2021.Of those teachers who had physical symptoms in 2021, 12.4% said they were due to COVID-19, as did 15.0% of those who had mental symptoms.The aim of this research was to study possible changes in self-rated health and well-being among primary school teachers one year before the pandemic (2019) and two years later (2021), when the pandemic had lasted for over a year. We compared possible changes in stress levels between the two points of the study and the impact of mental and physical health and health symptoms on perceived stress. Furthermore, we determined whether there were any changes in mental and physical health and health symptoms. We considered a possible link between health and well-being outcomes and gender, age, marital and family status, years in teaching, and employment rate.In general, the results show increased stress, worsening mental and physical health, and increasing mental and physical symptoms in 2021 compared to 2019. Worse mental health and mental health symptoms were the strongest predictor of high stress levels. The interaction between the time point of the study and mental health symptoms indicated that the influence of time was greater for teachers who reported mental symptoms than others. In other words, the COVID-19 pandemic has had a negative correlation with these health and well-being factors, indicating the deteriorating health and well-being of the teachers. Therefore, efforts should be made both to improve the health and well-being of employed teachers and to organise preventive measures to improve the working arrangements and ensure the well-being of future teachers. Now, we will discuss the results in more details.The proportional stress level increased by around 10% in 2021 compared to 2019, and the result revealed that 28% of the teachers were categorised with high stress. This is in line with Rubilar and Oros’  results,In line with other studies e.g., ,29), our, our29])In our data, teachers who were not married or cohabiting were likelier to experience high stress during COVID-19, but no difference was found between the groups before the pandemic. The reason might be the well-known isolation that younger and single individuals experienced during the pandemic, due to severe restrictions on social activities.In line with the stress, our data show changes in self-assessed mental health for the worse among the teachers between 2019 and 2021 in all groups examined, except for teachers 30 years old and younger, teachers 61 years old and older, and teachers who had worked for less than a year as a teacher. The trend was similar for physical health in most of the groups examined, both related to age and children in the home, where teachers not living with children felt better than others. The proportion of participants reporting much worse and somewhat worse mental health rose from 10% in 2019 to 31% in 2021. In line with MacIntyre et al. , deterioThe gender patterns for mental and physical health are less clear than regarding stress. We cannot explain with our data why the results show more differences between women and men in relation to stress than mental and physical health, but Sigursteinsdottir and Rafnsdottir  and SiguThe measured increase in stress among teachers in our study are of a great concern, as the results show that worse mental and physical health, as well as mental and physical symptoms, were all significantly associated with perceived stress, after controlling for other factors in the models. This shows the importance of doing everything possible to improve work-related well-being among teachers. In line with Lizanna and Lera , who shoThe strength of the study is that it is based on panel data, in which employees answered questionnaires both before and during the COVID-19 pandemic—more concretely, one year before and after the virus reached the country. Therefore, we can measure if and what kinds of changes in health and well-being took place among teachers during the pandemic. In addition, the response rate was high (73%). The fact that we are not working with a sample, as all the teachers received the survey, makes the data strong. It could be seen as a limitation that we are only working with self-measured health assessments, without confirmation by physicians. Nevertheless, self-reported health has proven to be successful as a predictor of individuals’ future health and can be an early warning signal of future sick leave . MoreoveThe theoretical contribution of the research lies mainly in the increased knowledge it creates of the connection between the COVID-19 pandemic and the lack of well-being among teachers as well as the interaction between stress and mental and physical well-being. The main practical contribution should appeal to those in charge of occupational health and prevention in the schools and school authorities. Since the negative effects of the economic crisis in 2008 on teachers’ health prevailed for years, the study demonstrates the importance of school authorities keeping an exceptionally watchful eye on the welfare and well-being of teachers in the wake of the COVID-19 pandemic. As economic crises tend to come periodically, organisations should be aware of this and take active measures to ensure that the workplace is a healthy and secure place for every employee. This knowledge is also important for those who work with policy development regarding teachers’ occupational health and safety. Although our study was on primary teachers in schools operated by Icelandic municipalities, we believe that the main results touch on such a fundamental element in well-being at work that they can be applied to different workplaces and other countries as well.


However, users' perspectives about such apps are vital in better bridging the gap between their design intention and effective practical usage. In this vein, a modified technology acceptance model (mTAM) is proposed here, to explain the relationship between users' perspectives when using an AI-based smartphone app for personalized nutrition and healthy living, namely, PROTEIN, and the mTAM constructs toward behavior change in their nutrition and physical activity habits. In particular, online survey data from 85 users of the PROTEIN app within a period of 2 months were subjected to confirmatory factor analysis (CFA) and regression analysis (RA) to reveal the relationship of the mTAM constructs, i.e., perceived usefulness (PU), perceived ease of use (PEoU), perceived novelty (PN), perceived personalization (PP), usage attitude (UA), and usage intention (UI) with the users' behavior change (BC), as expressed via the acceptance/rejection of six related hypotheses (H1–H6), respectively. The resulted CFA-related parameters, i.e., factor loading (FL) with the related p-value, average variance extracted (AVE), and composite reliability (CR), along with the RA results, have shown that all hypotheses H1–H6 can be accepted (p < 0.001). In particular, it was found that, in all cases, FL > 0.5, CR > 0.7, AVE > 0.5, indicating that the items/constructs within the mTAM framework have good convergent validity. Moreover, the adjusted coefficient of determination (R2) was found within the range of 0.224–0.732, justifying the positive effect of PU, PEoU, PN, and PP on the UA, that in turn positively affects the UI, leading to the BC. Additionally, using a hierarchical RA, a significant change in the prediction of BC from UA when the UI is used as a mediating variable was identified. The explored mTAM framework provides the means for explaining the role of each construct in the functionality of the PROTEIN app as a supportive tool for the users to improve their healthy living by adopting behavior change in their dietary and physical activity habits. The findings herein offer insights and references for formulating new strategies and policies to improve the collaboration among app designers, developers, behavior scientists, nutritionists, physical activity/exercise physiology experts, and marketing experts for app design/development toward behavior change.The ubiquitous nature of smartphone ownership, its broad application and usage, along with its interactive delivery of timely feedback are appealing for health-related behavior change interventions  Moreover, these mobile apps may also enable greater self-monitoring and disease management by individuals with chronic diseases such as obesity, cardiovascular disease, osteoporosis, and type 2 diabetes -based personalized nutrition mobile application for healthy living) are considered, and a modified Technology Acceptance Model (mTAM) is proposed. The main research problem that is examined here is whether specific interdependencies exist between the main constructs of a mTAM-based users' behavior model that could shed light upon the intention of the users to change their behavior and adopt a healthier living, undertaking personalized plans regarding their activity and nutrition, scaffolded by their interaction with the PROTEIN app.Motivated by the aforementioned, this work aims to identify the main constructs and model their contributions to users' behavior change toward healthier living Successful use of information technology (IT) applications and what influences such success have been thoroughly explored, and great attention has been paying by the information systems (IS) community for the past decades –37 as prPerceived Entertainment, in an effort to understand if the users have different feelings when interacting with smartphone-based games across different settings and locations; b) Kim et al.  Morosan  Lee and Wan , Effort Expectancy (the degree of ease associated with the use of the system), Social Influence , and Facilitating Conditions  (Hedonic Motive (the fun or pleasure derived from using technology), Cost/Perceived Value (trade-off between perceived benefits and monetary cost of using the IT application), and Habit   . Age, ge system) , 59. The system) , 41, 59,haviors) , whereasUse construct and thus was later revised  and to explore the role of the PROTEIN app as the technology artifact that could help its users to change their behavior and adopt a healthier living, in terms of improved nutrition and activity.Several digital mobile health technologies for self-management of nutrition  and physhttps://protein-h2020.eu/). The latter involves a multidisciplinary team of 20 partners from a total of 11 European countries, including partners from industry, research, and technology organizations, aiming to promote a healthy lifestyle by combining the latest technologies, such as smartphones and sensors, to offer personalized nutrition and physical activity plans , namely, “PROTEIN: PeRsOnalized nutriTion for hEalthy livINg” (ty plans . Alreadyhttps://gdpr.eu), the PROTEIN app allows the users to download and have access to their data, withdraw from the application at any time and delete all previously collected data.The PROTEIN app also provides a “Help center” portal for questions and/or suggestions to improve the functionalities of the PROTEIN app. However, it is important to underline that the PROTEIN app is not a medical device, meaning that information and advice that PROTEIN app provides does not constitute medical advice. Finally, complying with the General Data Protection Regulation (EU GDPR)  and then to participate in an online PROTEIN survey  least time consuming, i.e., no more than 20 min for completing it; ii) simple, objective, and quantitative structure, i.e., as little free text as possible; iii) inclusion of demographic information; and iv) feedback acquisition on what is more/less appealing to users. After review rounds within the PROTEIN Consortium, the final version of the online PROTEIN survey resulted in an efficient version. The online survey consisted of 28 questions, divided into sections, including rating scale, multiple-choice, dichotomous, and open-ended questions  provided online consent and fully completed the online PROTEIN survey; hence, only their responses were kept for the modeling analysis, described next.Taking into consideration the TAM model , this study adopts the PU, PEoU, UA, and UI from TAM model and introduces two additional constructs, i.e., the “Perceived Novelty” (PN) and the “Perceived Personalization” (PP), toward the model output of “Behavior Change” (BC). This results in a modified TAM (mTAM) framework, as depicted in via the influence of UA. Moreover, the study of Holden and Karsh : Users' perceived usefulness toward the AI-based smartphone PROTEIN app positively influences usage attitude.Hypothesis 2 (H2): Users' perceived ease of use toward the AI-based smartphone PROTEIN app positively influences usage attitude.A crucial characteristic of any innovation is its novelty. Wells et al.  tried toHypothesis 3 (H3): Users' perceived novelty toward the AI-based smartphone PROTEIN app positively influences usage attitude.Personalized approaches seem to be needed to promote healthy behaviors. Personalization concepts associated with behavior change in mobile health can be categorized into four different dimensions, namely: users , system functionalities , information , and mobile app properties  . In addiHypothesis 4 (H4): Users' perceived personalization toward the AI-based smartphone PROTEIN app positively influences usage attitude.Davis et al.  and RobbHypothesis 5 (H5): Usage attitude of the users toward the AI-based smartphone PROTEIN app positively influences usage intention.Usage intention defines the degree to which an individual is willing to engage in a particular behavior . When inHypothesis 6 (H6): Usage intention of the users toward the AI-based smartphone PROTEIN app positively influences behavior change.2), adjusted R2  was used for the statistical analysis. Descriptive statistics were calculated for demographics and the related questions from the online survey  –110, as p-value, average variance extracted (AVE), and composite reliability (CR) parameters were estimated. According to Nunnally  volunteers coming from eight European countries  with average age of 49.3 years , who responded anonymously to the online survey . The highest percentage of the respondents, 32%, were in the 35–44 age groups followed by 30% of 25–34 years old, then 16% of 18–24 years old, 12.5% of 44–54, 7% of 55–64, and the least, 2.5% was for 65 and over years old. Moreover, the distribution of male/female was 56% male and 41.5% female. In terms of body weight and body height, the means were 72.5 kg (±std = 16.5 kg) and 164 cm (±std = 8.4 cm). The majority of users (74%) were classified as general public and therefore did not belong to any clinically defined group .The PROTEIN app was evaluated by eighty-five , or fast and easy-to-use functionalities of adding a meal and/or an activity.Ease of use: this was perceived by the users Personalization: adaptation to the personalized characteristics of each user was considered important in the user profile of the PROTEIN app, covering many important attributes related to potential allergies, insufficiencies, intolerances, or personal diet. In addition, the personalized feedback, in terms of personalized notifications and achievements, contributed to boosting the user perception of PROTEIN app personalization feature.via the uniqueness and variety of the features provided by the PROTEIN app, compared to the other apps that relate to nutrition and physical activity, especially mentioning the feature of recording the meal/activity.Novelty: the users expressed their perception of novelty The aforementioned perspectives are propagated through the usage attitude and intention as means for activity and eating behavior change, as reflected in the adopted mTAM and the related hypothesis testing results as presented below.via the values of adj R2 , as they were derived from the performed regression analysis. Moreover, 2 varies from 0.110 (no. 5) up to 0.740 (no. 14) and the corresponding adj R2 ranges from 0.100 (no. 5) up to 0.732 (no. 14), showing that, in most cases, there is a good fit of the regression models used to express the relation between the items/constructs of the proposed mTAM framework.From a general perspective of the results presented in 2 values are 0.129, 0.193, 0.309, and 0.328, respectively, showing that the plan of healthier meals explains the highest part of the PU variance, compared to the “Recommends me suitable activities,” “Helps me to exercise more,” and “Helps me to improve my health” items. Moreover, the “Easy to organize supermarket shopping list” and “Easy in interaction” items both contribute to the PEoU construct (Cronbach's α= 0.7757) of the mTAM. The corresponding adj R2 values are 0.327 and 0.387, respectively, revealing almost an equal contribution in the explanation of the PEoU variance. In its turn, the “Provides novel meal/activity recording” and “Differs from other related app” items collectively contribute for the PN construct of the mTAM α (Cronbach's α = 0.7674). Clearly, the latter item exhibits much higher adj R2 value (0.719) when compared to the one from the former (0.100). This is anticipated, as the concept of novelty is first conveyed to the users via the comparison of the PROTEIN app with the state - of - the - art and then via the feature of the meal/activity recording. For the PP construct of the mTAM, the “Provides personalized notifications,” “Provides personalized achievements,” and “Provides complete personalized profile” items collectively contribute (Cronbach's α = 0.8071). From these items, the “Provides personalized notifications” item exhibits the highest adj R2 of 0.411, followed by the “Provides complete personalized profile” (adj R2= 0.341) and the “Provides personalized achievements” (adj R2 = 0.313) items. This shows that the sense of personalization is perceived by the users textitvia personalized feedback and the ability to customize the user's profile, taking into consideration the specificity of each user's preferences and sensitivities .Following the paths of 2 values are 0.306, 0.436, 0.224, and 0.424, respectively, showing that the PEoU explains a high part of the variation in the UA, followed by the PP, PU, and PN. There is a strong connection between the UA and UI constructs, as the corresponding adj R2 value is 0.732, revealing that the establishment of a solid usage attitude will effectively lead to an established usage intention. Consequently, this solidification could feed the BC construct (adj R2 = 0.445), explaining a significant part of its variance.Moving on to the hypotheses testing, the results from The aforementioned results showcase the validity of the proposed mTAM framework and related hypotheses to explain the interaction between the items and constructs that are activated during the process of PROTEIN app evaluation and its potential users' acceptance.Here, we present the use of the mTAM framework as a means to model the users' evaluation of the PROTEIN app, a smartphone-based nutrition and activity app developed by a multidisciplinary team to support self-management of dietary intake and physical activity and scaffold any necessary behavior change that would lead to healthier living. In view of this approach, the six hypotheses, i.e., H1–H6, of the proposed mTAM framework provide a fine-grained breakdown of the elements that are gradually built during the user's interaction with the PROTEIN app, explaining the dependencies and power of these constructs to provide a meaningful explanation of the users' perspectives on usefulness, easiness, novelty, personalization, usage attitude, and usage intention toward behavior change.Overall, nutrition and physical activity-related mobile apps show promise as tools to successfully facilitate positive health behavior change. Furthermore, mobile apps that focus on improving motivation, feedback, self-efficacy, attitudes, knowledge, and goal setting may be particularly useful , as in tBased on the Methontology, i.e., a methodology for building ontologies , the PROp < 0.001), is reduced to−0.071 (p = 0.742) when moving to Path No. 2. This is further justified by the difference in the R2 and adj R2 between the Path No. 1 and Path No. 2  does not significantly deviate from the estimated value in the regression Path No. 15 (p < 0.001).The aforementioned design of the PROTEIN app, which combines NAct ontology with LiFR, contributes to the constructs of the adopted mTAM framework. Clearly, the users' evaluation results showcase the various capabilities of the PROTEIN app to facilitate meal and physical activity planning, to reflect about and create appropriate shopping lists, to be aware of the impact of eating healthy food and be more active, to easily interact with and find it as a useful tool, to have valuable personalized feedback and profile, taking into consideration specific nutrition  or physical activity  issues. All these contribute to the users' UA of the PROTEIN app (H1–H4) and support UI to adopt it as a means (H5) that could potentially lead to their behavior change (H6), in terms of clarifying/improving nutritional and physical activity beliefs/habits. To further examine the mediating role of UA and UI in the BC, we performed hierarchical linear regression, examining the prediction of BC from UA and the prediction of BC from UA considering as mediator the UI. The results of this analysis are tabulated in th No. 2 , which ah No. 15 , i.e., 0kg/m2), revealed that users with a personal digital assistant (PDA) to input a description of their daily meals and self-regulate their energy intake via a “goal feedback thermometer” updated with their current caloric intake, achieved greater weight loss than their control group counterparts. In another 24-month RCT, namely, Self-Monitoring and Recording Using Technology (SMART)  , involvi (SMART) , highlig (SMART) , includiR2 = 0.718), showing adequate acceptance and intention to be used in self-managing and supporting healthy eating and physical activity.The aforementioned works highlight the efficiency of the related apps to be incorporated in clinical settings and act as the mediators for scaffolding the users' efforts toward healthier living. Actually, incorporation of mobile apps in the design of health promotion programs is growing, following the profound mobile app market exponential growth . Neverthvia the identified interdependencies between the mTAM items/constructs  clear understanding of the users' health needs and introduction of apps with high degree of novelty, compared to the ones currently in the market, personalization, adaptation capabilities, and scalability within the growing market to meet different users' needs; the use of AI (as in the PROTEIN app) can contribute toward such need; b) easy-to-use apps, since the individual's decision to actually perform a health behavior has to be acted on in efficient and quick way . Consequn = 85) may not be considered adequate for generalization of the findings to larger populations. However, as the average age of the participants is around 50 years, coming from eight European countries, we could argue that the sample is representative enough to ground the proposed mTAM model, assuming that, as adults with living experience, their understanding of the PROTEIN app use and the related survey may be adequate. Extending the sampling to larger and more diverse populations could further justify the validity of the current findings. The PROTEIN consortium has already scheduled the testing of the proposed mTAM framework in a second round of pilot studies that will involve a higher number of participants, an updated version of the PROTEIN app to include also iOS smartphone users, and populations, apart from the healthy ones, with specific characteristics, e.g., patients with diabetes, patients with cardiovascular disease, patients with obesity/overweight, and vulnerable population. The users' time period of the PROTEIN app use (2 months) sets also another limitation. In general, meeting the expectation for the healthier lifestyle goal requires long-term effort, and immediate rewards usually do not appear as substantial positive outcomes. However, the proposed mTAM framework provides the opportunity for a dynamic perception of its constructs, using it in a time-scale manner. In fact, mTAM outcomes could be evaluated upon meeting intermediate (short/mid-term) goals, providing output for the constructs that strongly participate in the sustainability of the users' positive perspective of the app, hence keeping them using the app. In this context, time-scaled versions of the mTAM could be combined to provide an explanation of the time-based dynamics of users' continuance intention (CI) for health apps (R2 = 0.397) showed its capabilities to support healthy online food ecosystem.Despite the promising results, some limitations of this work should be highlighted. Clearly, the number of participants . Online informed consent was obtained from every participant prior to enrolment in the online PROTEIN survey. The patients/participants provided their written informed consent to participate in this study.SD: conceptualization, study design, organization, and writing the manuscript. YO: online PROTEIN survey realization in the SurveyMonkey platform. LH: conceptualization, study design, organization, statistical analysis, manuscript review, and update. All authors contributed to the conceptual design and development of the PROTEIN mobile application and online PROTEIN survey, discussed the results and reviewed the manuscript, have read, and agreed to the published version of this manuscript.The research leading to these results has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no. 817732 .CV was employed by Fluviale SRL. YO and AB were employed by the company Intrasoft International SA. SG was employed by the company Datawizard. GT was employed by the company PLUX. JB was employed by the company Grupo CMC. DR and JK were employed by the company OCADO. SM was employed by the company AgriFood Capital BV. PB was employed by the company Healthium/Nutrium. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The relationship between multiple indicators of women and postoperative recurrence of pelvic organ prolapse was analyzed to establish a model for predicting postoperative recurrence of female pelvic organ prolapse.  Three hundred patients with pelvic organ prolapse who underwent pelvic organ prolapse surgery at our hospital were monitored for 1-2 years to determine their prognosis. Whether there was a postoperative recurrence, they were divided into two groups. We collected the relevant data from the two groups of patients before and after surgery. Through single factor and logistic multivariate analysis, we selected the risk factors that may affect the recurrence of patients to construct a prediction model. We verified the identification ability, proofreading ability, and clinical applicability of the model. U = −0.007, Brief = 0.087). The Hosmer-Lemeshow goodness-of-fit test demonstrated that the model had good calibration , and the decision curve showed that the threshold probability was in the range of ~12% to 100%, having a high net benefit value.  Eighty-four patients with pelvic organ prolapse who had postoperative recurrence were assigned to the recurrence group, and 216 patients were included in the nonrecurrence group. Based on the logistic multivariate analysis results, we constructed a nomogram model containing 5 dimensions of age, BMI, degree of prolapse, pubic fissure, and serum calcium to predict postoperative recurrence. The tests revealed that the model had an excellent identification ability (AUC = 0.910), and the expected recurrence rate was significantly in agreement with the actual recurrence rate ( Based on the present study findings, we concluded that the constructed nomogram model has suitable identification, calibration, and clinical applicability. Pelvic organ prolapse (POP) is an abnormal position and function of the anterior vaginal wall, posterior vaginal wall, uterus, or vagina due to the weakness of pelvic floor support tissue. The main symptoms of POP are external vaginal prolapse, mainly manifested as urination, defecation, and sexual dysfunction . AlthougCurrently, there is no safe and satisfactory treatment for POP. Vaginal hysterectomy and pelvic floor mesh reconstruction (TVM) via the vagina are POP's most widely used surgical treatments. TVM is still controversial due to its long operation time, high bleeding, and high exposure rate of mesh erosion . The anaIn this study, 300 patients who received surgical treatment in the Department of Gynecology of Suzhou No. 9 Hospital (Affiliated with Suzhou University) were selected as the research subjects from January 2015 to June 2021. The Suzhou University ethical committee approved the present study, and informed consent forms were obtained from all participants. In addition, all patients' clinical and follow-up data were retrospectively analyzed. The inclusion criteria were (1) no history of cachexia before surgery, (2) surgeries were successful, (3) conditional postoperative review and follow-up, and (4) meeting POP recurrence criteria. The exclusion criteria were set as follows: (1) patients with incomplete data and unmatched follow-up and (2) patients with mental illness or language disorder history.A physical examination was performed on these patients from 1 to 2 years after the operation to determine their POP-Q staging. During the follow-up period, we collected patients' follow-up data by telephone and evaluated the review results to determine the recurrence cases. POP recurrence criteria were as follows: (1) POP-Q staging indicator points exceed virgin membrane, (2) symptoms of vaginal bulge affecting life, and (3) retreatment for prolapse . AccordiAll patients received detailed medical history, symptoms, and follow-up surveys before and after surgery. We collected general information about age, body mass index (BMI), number of deliveries, history of chronic constipation, history of hysterectomy, degree of pelvic organ prolapse, preoperative genital hiatus (GH), surgical approach, recurrence, and total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), thrombin time (TT), prothrombin time (PT), blood calcium (Ca), and follow-up time. GH was defined as the distance between the posterior margins of the tunica vaginalis.The degree of the cervical lowest point below the sciatic spine plane did not reach the virgin membrane edge; II degree cervical out of the vagina, but the uterus is still in the vagina; III degree cervical and uterine body all out of the vagina.t-test, and ANOVA was used among multiple groups. Count data are expressed as rate or constituent ratio and compared by the chi-square test. Single factor analysis and multivariate analysis were used to screen out the statistically significant factors affecting the postoperative recurrence of POP. Based on multivariate analysis, the nomogram model for predicting POP's postoperative recurrence was constructed using “rms” in R3.5.1. The model's identification ability, proofreading ability, and clinical applicability were verified by the receiver operating characteristic (ROC) curve, calibration curve, and decision analysis curve, and α = 0.05; P < 0.05 was used as the criterion for judging the statistical significance.SPSS 23.0 software was used for data analysis in the study. The measurement data were expressed as mean ± SD. The results of homogeneity of visual variance between groups were evaluated by P < 0.001), and the proportion of patients with preoperative prolapse degree III was also higher than that in the nonrecurrence group (P < 0.001). There was no significant difference in other indicators between the two groups , and the independent factors were the corresponding characteristics of 2, II degree prolapse, GH = 5 cm, and Ca = 2.5 mmol/L, the total score of predicting recurrence was 35.8 + 47.8 + 19.5 + 45 + 32.5 = 180.6, and the corresponding probability of recurrence was 28% , Brief score (0.087), and Hosmer-Lemeshow goodness-of-fit tests revealed that the model had an excellent calibration value , as shown in ROC analysis showed that the AUC of the nomogram model for predicting the postoperative recurrence risk of POP patients was 0.910 (95% CI: 0.874–0.953), and the discrimination of the model was good, as shown in So far, most reports on pelvic organ prolapse have focused on the progress of surgical treatment of primary prolapse. A few researchers have studied the postoperative recurrence of patients, finding that the probability of postoperative recurrence can reach as high as 37% in the long term. Factors affecting recurrence have also been reported in recent years. Still, the results are not uniform, mainly focused on age, BMI, preoperative POP-Q stage, neonatal birth weight, parity, chronic diseases, levator injury, estrogen, surgical methods, and family history of these indicators .However, few studies have constructed reliable and efficient models that can be used to predict postoperative recurrence based on these indicators. For this purpose, we screened five indicators that can be used for model construction from the 15 related factors of postoperative recurrence through logistic regression analysis. Compared with previous studies, this study successfully constructed a model for postoperative recurrence of POP patients based on multidimensional indicators. Through AUC, calibration curve and decision curve analysis found that the model showed satisfactory performance. It can be considered that this model can be used in clinical practice to evaluate the postoperative recovery of each patient individually, which will significantly improve the life and health of patients, especially elderly patients.With the aging population, POP has become a common disease that seriously affects the quality of life of older women. It has been reported that 1.5–1.8 women suffer from POP every 1000 women each year. It is expected that by 2050, the number of patients with POP will increase by about 50%, and the postoperative rehabilitation of patients is often satisfactory, of which 1/6 patients will be hospitalized due to the recurrence of POP . This isWe also applied this standard to determine our research objects in this study. In this study, five independent risk factors, age, BMI, GH, Ca, and prolapse degree, were selected from the 15 variables affecting the recurrence of patients. The nomogram model based on these indicators can accurately predict patients' postoperative recurrence incidence. Nomogram contains three parts: the variables of the prediction model, the scores corresponding to the variables, and the incidence of predicted events. It is essential to predict the probability of clinical events using individual variables. It is also a standard tool for evaluating the prognosis of certain tumor diseases . Fu et aIn this study, we first proposed to apply the line graph model to predict the recurrence of POP. Each line segment in the model corresponds to a risk factor, and the length of the line segment represents the contribution value of each risk factor to the outcome. After testing, the model also showed solid predictive ability. The AUC of the ROC curve was 0.910 (95% CI: 0.874–0.953), and the predicted value of the calibration curve was consistent with the measured value. In addition, the decision curve analysis shows that the clinical net benefit value of POP patients is very high, up to 100%, indicating that the model has strong identification ability, proofreading ability, and clinical applicability. Medical staff can predict patients according to the model and identify high-risk patients in time.Notably, only five indicators are included in the nomogram model, with age and BMI widely considered one of the most critical risk factors for recurrence in POP patients. With the increase of age, the estrogen level in patients decreases, and there are reproductive tract support tissue decomposition, local blood supply, poor mental nutrition, easily leading to pelvic floor support tissue thinning, loss of elasticity, and POP. Garshasbi et al.  found thThe above results are consistent with our research. In addition, the effect of BMI on postoperative recurrence is also apparent. BMI is a standard indicator to measure obesity. Some studies have found that high BMI is a high-risk factor for postoperative recurrence of POP , which iThis study did not count the postoperative GH of patients. Still, it can be found that patients with more significant preoperative GH have a greater risk of postoperative recurrence, similar to the existing research. The muscle contraction intensity is closely related to the concentration of calcium ions within a specific range. A slight decrease in blood calcium can enhance osteoclast activity, limit osteoblasts' function, and further affect pelvic floor skeletal muscle strength, making the muscle relax. This results in decreased pelvic floor support's posture stability and increased risk of POP recurrence . In addiIn addition, there are still shortcomings in the study. Firstly, we only included 15 indicators in the previous studies, which may ignore the impact of other factors on the prediction results. Secondly, our research sample size is relatively small, and the obtained model lacks external verification. In the later stage, a large external verification queue is needed to improve the credibility and effectiveness of our model.In summary, this study constructed a nomogram model containing age, BMI, GH, Ca, and prolapse degree and used it to predict the postoperative recurrence rate of POP patients. The model has good identification ability, proofreading ability, and clinical applicability. It is expected to be applied to the risk stratification management of postoperative patients.