Earthquakes cause a lot of damage and casualties. For various reasons, most households are not prepared for earthquakes. This study aims to identify the challenges and barriers to households' preparedness against earthquakes from the viewpoint of Kerman residents.This qualitative-directed content analysis study was conducted from December 2021 to May 2022 in the city of Kerman in southeast Iran. Data was collected by purposive sampling through in-depth and semi-structured individual face-to-face interviews with 48 households.After multiple rounds of analyzing and summarizing the data based on the social-cognitive theory and taking into consideration similarities and differences, five main categories and 19 subcategories created based on the results of data analysis and including (1) Challenges related to cognitive factors (2) Challenges related to behavioral factors (3) Challenges related to the physical environment (4) Challenges related to the social environment and (5) Challenges related to financial factors.Although the participants listed many challenges and barriers in different fields, in order to overcome the barriers and challenges of preparing households for an earthquake, the support of the authorities and the cooperation of the residents are necessary. Earthquakes cause extensive damage to homes, businesses, and infrastructure, as well as casualties and financial losses . As the Disaster risk reduction management consists of three phases. Prevention, mitigation, and preparation are in the phase before the occurrence of a hazard; response and emergency relief are in the phase during the occurrence of a hazard; and recovery (reconstruction and rehabilitation) is in the phase after the hazard . AcquiriStudies in different parts of the world have shown that perceived challenges and barriers significantly reduce preventive measures and disaster preparedness , 16–19. Considering that the present research is a part of an exploratory sequential study, it was necessary to identify the opinions and beliefs of people about the barriers and challenges of households' preparedness against earthquakes for formulating items and designing tools. From the viewpoint of Kerman residents, since Kerman province is one of the earthquake-prone regions of Iran and most of the people in this region have experienced earthquakes, this study aims to identify the challenges and barriers to households' preparedness against earthquakes.A qualitative study was conducted from December 2021 to May 2022 as part of more extensive research on the design and validation of a tool for determining the factors influencing households' preparedness behaviors for earthquakes based on the social-cognitive theory. This study was conducted using a directed content analysis approach. When there is a theory or research about a phenomenon, but it is not complete and more descriptions should be made about it, the researcher uses a directed content analysis approach . The average age of the participants was 42 years. The average size of the household was about four people. Nine households lived in a rented house. Twenty-four households lived in apartments. Forty-two participants had academic education. There was a vulnerable person in 37 households. Five hundred and six codes were identified without calculating the overlaps. After multiple rounds of analyzing and summarizing the data based on the social-cognitive theory and taking into consideration similarities and differences, five main categories and 19 subcategories created based on the results of data analysis. Main categories including (A) Challenges related to cognitive factors (B) Challenges related to behavioral factors (C) Challenges related to the physical environment (D) Challenges related to the social environment and (E) Challenges related to financial factors shows in The participants stated that acquiring knowledge can effectively improve households' preparedness behavior and reduce losses and casualties, but for various reasons, most people's awareness is not enough or is incorrect. For example, A 34-year-old bachelor's degree woman said:am an employee, and when I come home in the evening, I am busy with housework. I have to take care of my husband and children. I don't have time to participate in Red Crescent classes “(P13).I Participants stated that some people have false beliefs, which lead them to not take preventive and risk reduction measures and feel weak against hazards. A 45-year-old bachelor's degree man who had experienced the Bam earthquake said:Some people think that an earthquake is God's punishment and we can't do anything. Were the children killed in the Bam earthquake because of God's anger? What did they do? The children were innocent. You have to inform the people” (p5).“Some participants mentioned that they thought they could not take preventive measures and prepare and behave efficiently when an earthquake occurs. A 52-year-old master's degree woman said:I get a lot of stress during an earthquake. I'm not sure if one day there will be a strong earthquake in Kerman, I will be able to keep my calm” (P4).“Some people stated that they do not have the necessary skills to prevent secondary hazards and reduce harm.A 43-year-old diploma woman said:I haven't been trained because I don't think I can help the wounded. If I see someone injured, I feel bad. Someone who chooses to do this must be very brave. I really don't have any skills” (P25).The participants commented that they thought preparing for earthquakes and doing drills at home might harm vulnerable groups' physical and psychological health.A 37-year-old woman who had a seminary education said:I have three small children. They may not understand why I am preparing a rescue kit, and it scares them because they think something is going to happen” (P1).“A 34-year-old master's degree man said:My wife is pregnant; I know she can't move fast. If we try to drill at home, she may fall and get more injured, or she may get stressed, and her blood pressure will rise. We prefer not to drill while my wife is in this condition ”(P15).“Some participants mentioned that after the devastating Bam and Zarand earthquakes, they had to search for and save their loved ones themselves in the early hours before the rescuers were present. They mentioned that they had no training and did not know how to save an injured person. A 50-year-old bachelor's degree man said:In the Bam earthquake, the whole city was completely destroyed, and there was not enough relief force. We had to pull the families out from under the rubble. People did not know how to save a wounded person. Later, I heard that many of the wounded were paralyzed because we did not know what to do. Everyone, in my opinion, should learn these skills before the earthquake”(p11).“Participants said that some people's inappropriate behavior causes others to get hurt during an earthquake. A 43-year-old master's degree woman said:When you look at our building, you see that they put flowerpots and other things on the balcony without any protection, so if there is an earthquake, they will fall on people's heads. I wish someone would warn them that this is dangerous” (p33).“Excessive emotional or unthoughtful behavior is one of the challenges during earthquakes that participants mentioned. A 35-year-old master's degree man said:Many people get fearful and confused. For example, my sister is terrified of earthquakes and does things that are not appropriate at all. When she is so afraid, her children get afraid as well ”(P16).“Another challenge that participants said was that some people crowd medical centers for minor injuries that do not require hospital visits.A 41-year-old bachelor's degree woman who worked in a hospital said:During an earthquake, even with minor injuries that do not require immediate treatment, people call the emergency medical center or go to hospitals, which may cause acute cases to receive delayed medical services” (p43).“Participants commented that many secondary hazards and challenges after an earthquake can be prevented by preventing emotional and hasty behaviors and following safety tips. A 39-year-old master's degree man said:After the earthquake, people come to the street by car, and there is a lot of traffic in the city. I think they should be taught in advance not to have these behaviors ”(P18).“A 48-year-old master's degree woman who had experienced the destructive Bam earthquake saidAfter the destruction of Bam city in 2003, many people from far and near cities entered Bam city. Iranians are very altruistic and like to help victims in this situation, but they don't know that this behavior will cause congestion in the city and cause more problems (p14).Participants stated that unsafe and non-resistant buildings are among the most challenging.A 50-year-old diploma man said:In my father's village (Dahuiyeh), although the houses were newly built, after the earthquake, 90% of the houses were destroyed, and a large number of people in the village were killed. Because the houses were not built according to engineering principles and standards” (p20).“Participants commented that equipment inside buildings can result in death or injury if it falls, breaks, or blocks exit routes.A 44-year-old physician woman said:As a tenant, I can't do many things, I can't even hammer a nail into the wall. The owner of the house may not agree that I fix the shelf so that it doesn't fall down during an earthquake (P2).A 43-year-old diploma woman said:Today's houses are very small; we don't have enough space for furniture. We have to put cupboards and shelves in the hall and put many things inside. If an earthquake happens, even if the house is not damaged, these utensils will cause problems for us” (P25).“As some participants commented, appropriate equipment was not available to rescue people. A 50-year-old diploma man, who was severely injured in the Zarand earthquake, said:I was under the rubble for several hours. I could not move. People did not have shovels and picks, and they could not save me. If they had pulled me out from under the rubble earlier. God helped me to survive, but it took me some time to recover” (P20).“The participants who experienced the Bam earthquake also stated that one of the main problems in the early hours after the earthquake was the lack of manual debris removal equipment. They believed this equipment should be prepared in advance.Participants commented that the considerable distance between the houses and the evacuation place, the lack of strength of the buildings in the neighborhood, the density of the buildings, and the insufficient width of the routes could cause many casualties and injuries during an earthquake.A 48-year-old master's degree woman said:Take a look at our neighborhood and you will notice that the houses are old and dilapidated. The alleys are narrow. If a strong earthquake happens, the houses will crash into each other and the alleys will be closed. My friend said that when I went to Bam after the earthquake, I could not find my father's house because the houses were crashing on each other. Several thousand people died in Bam because they could not save people quickly” (P8).“Participants commented that poor infrastructure, lack of access to facilities in some areas, and disruption of communication systems during an earthquake are critical challenges.A 46-year-old bachelor's degree woman said:When there is an earthquake here, sometimes the phones are cut off. My daughter, who is studying at a university in another city, gets very worried about us if she can't talk to me. The authorities should solve the telecommunications problems. If there is an earthquake, the phones will be cut off, and this causes people to worry because they cannot call [their family members] ”(P37).“Many participants said that cold weather and rain are significant barriers to an emergency evacuation.A 41-year-old bachelor's degree woman said:I remember in 2018 or 2019, there were many earthquakes in Kerman, and the weather was cold. Where should we go if we wanted to stay out of our buildings? Has the government considered a place where people could take refuge during an earthquake? We cannot sleep in the park or on the street in winter. Our children get sick ”(P31).“Participants mentioned that one of the most critical issues during an earthquake is people's security.A 51-year-old bachelor's degree man said:During an earthquake, people are afraid of their houses being robbed. That is why they prefer to stay in their dilapidated houses and do not leave the houses to go to a secure place” (P3).“A 60-year-old primary education woman said:My husband is dead and I don't have a son. If there is an earthquake and we want to leave our house, I can't go and sleep in a park with two daughters. I don't dare. We may be persecuted” (P47).“Participants mentioned that more communication between family members, relatives, and neighbors can increase mental preparedness, and knowledge sharing. Insufficient social communication was mentioned by several participants.A 52-year-old master's degree woman said:People are very busy. They have less time to visit each other. I don't see my relatives often because they live in another city. Also, since I am an employee, I rarely see my neighbors. I think that if we have a lot of communication with each other, we will be aware of each other's problems and we can help each other to solve them. We can also learn a lot from each other about earthquake prevention and preparedness” (P4).“The participants mentioned the insufficient collaboration of the neighborhood residents in the fields of preventive measures, reduction of damage, and improvement of preparedness as one of the main challenges for earthquake preparedness.A 50-year-old bachelor's degree man said:We have been living in this neighborhood for a year. We don't know our neighbors, and everyone is busy with their lives. I remember when there was an earthquake in the area around Zarand. We were living there. During the earthquake, the wall of one of the neighbors got many cracks. We talked to the neighbors and repaired the wall. Because it may fall on the street and harm the people passing by” (P29).“One of the barriers most participants mentioned was financial difficulties. A 51-year-old diploma man said:Now, the cost of living in Iran is very high. Our income is also very low. We can't even buy a smartphone for our children so that they can study during this Corona situation. I think we should let's spend our money on more important things, not on an earthquake that might not happen at all” (P23).“A 32-year-old diploma man saidMy house is made of clay and mud. I know how dangerous it is to live in this house. But I have no choice, I have to live in this house. Because building a durable house requires a lot of money, which I don't have” (p24).“One of the barriers most participants mentioned was insurance problems.A 40-year-old bachelor's degree man said:Because people do not have enough income, they do not pay much attention to insuring their houses, and if an earthquake happens, in addition to putting their lives in danger, they also lose a lot financially” (P42).“This research was conducted to identify the challenges and barriers to households' preparedness against earthquakes from the viewpoint of the residents of Kerman. The analysis of the participant's viewpoints showed many challenges and barriers to preventive measures and the preparation of households against earthquakes. Based on socio-cognitive theory, challenges and barriers were categorized into cognitive, behavioral, and environmental  factors.For various reasons, most participants believed that most households lack sufficient knowledge regarding earthquake preparedness measures. In Najafi et al.'s study 2018), which interviewed 132 heads of households living in Tehran, lack of knowledge and insufficient time were identified as the most important barriers to earthquake preparedness , which i. In ApplSome of the participants said that people around them believe that adverse events such as earthquakes are controlled by external factors and that humans have no authority over or ability to overcome them. Some participants did not agree with this. These beliefs are considered barriers to health-related behaviors. In a study by Askarizadeh et al. in Tehran, decision-making about risk reduction behaviors decreased with increasing sources of external control . AccordiOne of the challenges raised by the participants was a lack of belief in their abilities for preventive measures and preparation. According to Bandura, self-efficacy is the most important predictor of behavior change. If people believe they cannot perform a behavior, they are not motivated to act or resist challenges and obstacles . StudiesSome of the participants in this study stated that sometimes taking preparedness measures at home may negatively affect their family members, especially vulnerable groups. Therefore, they prefer not to prepare their family members for an earthquake to avoid physical and mental damage. According to the social-cognitive theory, if people believe that their actions to promote health will have more negative consequences than positive ones, they will stop that behavior . In NajaIn this research, the participants believed that the lack of necessary skills makes households unable to take the necessary and appropriate measures to save their lives or others in the event of an earthquake. In the study of Ning et al. in China, people who had the skill to do drills and did them regularly were more prepared . One impThe interviewees believed that the behavior of most people before, during, and after the earthquake was inappropriate. They were concerned that their emotional behavior during an earthquake would cause more harm to themselves and others. And they stressed that people's behavior should be corrected with proper training before the earthquake.The participants stated that one of the people's behaviors during an earthquake is to go to the earthquake-affected areas, which can cause many problems, including more damage to the injured, disruption of aid delivery, etc. According to the participants, the presence of volunteers that do not have the necessary skills is one of the most critical challenges during an earthquake. In the Sharifi et al. study, many volunteers entered the area spontaneously after the Kermanshah earthquake. Some volunteers had not even received specialized training in rescuing and transporting the injured, which increases the possibility of injuries in the rescue process . VolunteOne of the crucial challenges raised by most of the participants was the building of unsafe and non-resistant buildings. One of the most important basic measures to reduce the vulnerability and preparedness of households against earthquakes, especially in areas with high seismic risk, is the construction of standard and resistant houses. The results of various studies show that residential buildings in Iranian cities are dilapidated. For example, the results of Rezaei and Nouri's study (2017) showed that households in Kerman city are vulnerable to earthquakes in terms of building strength . In the Based on the interviews, some participants believed that other preparation measures are useless when the building is not resistant. In the study of Tekeli-Yeşil et al. in Turkey, households that were sure of the resistance of their building were more prepared, and their information was more about earthquake preparedness measures .Considering that the most essential measure to reduce the vulnerability of households, especially in areas with high seismic risk, is the construction of standard and resistant houses, special attention should be paid to this issue . For exaOne of the barriers mentioned by the households was non-structural factors. Although building features are the most critical factor in earthquake mortality, even in the safest structures, if the furniture, equipment, and appliances inside the building are not safe, death and injury can occur. Some participants stated they faced barriers, including living in rental housing, to non-structural vulnerability reduction measures. Other studies showed that homeowners were more prepared for disasters , 16, 35.The lack of manual and basic debris removal equipment was a significant problem raised by the Bam and Zarand earthquake survivors. Most participants thought that emergency equipment only included the first aid box. Only those who had previously experienced a devastating earthquake considered manuals and tools necessary for removing debris, in addition to other equipment. Therefore, drawing on the experiences of those who experienced destructive earthquakes can be very helpful.Some of the participants believed that the narrowness of the roads in the city center, where most of the buildings are not resistant to earthquakes, is one of the critical challenges that must be solved before an earthquake occurs. In areas where the houses are dilapidated and the roads are narrow, in the event of an earthquake, rescue vehicles can't travel, and rescue forces can only provide services with a delay, which will increase casualties and serious complications among the injured. Studies have shown that cities in most regions of Iran are highly vulnerable to earthquakes. For example, in Mesri Alamdari et al.'s  study, aThe participants believed that one of the most critical issues during an earthquake is providing security by the police and security forces. They believe that if people do not feel secure, they will not evacuate their homes during an earthquake warning. The evacuation order may cause chaos in the city, and there is a possibility of robbery if the house is evacuated. Also, vulnerable groups, including women and young girls, do not have the possibility of staying outside the house due to the possibility of causing harassment. In a study by Newnham et al. in Hong Kong, many participants mentioned fear of home burglary and lack of a suitable place to stay as factors preventing evacuation during a warning . TherefoOne of the challenges expressed by the interviewees about the preparation of households before the earthquake was insufficient interactions between family members, relatives, and community members. They believe that communication between people has decreased compared to the past for various reasons. They believed that the more people communicated with one another, the better they could support one another in various fields and help one another overcome obstacles. According to the study by Kim and Zakur, people who had higher levels of social support and more connections with society and organizations were more prepared for emergency situations related to disasters . A studyThe non-participation of residents in preventive measures and preparations against earthquakes in the neighborhood was one of the other challenges. In the study of Hadafi et al., in Iran (2021), the participation rate of citizens was at a relatively favorable level, and most of the citizens had a lot of participation in voluntary activities to prepare against the risks related to the neighborhood . In the Almost all participants mentioned financial issues as an essential barrier to preparing households against earthquakes. Buying land in safe areas and building a durable and standard house requires a lot of financial resources that most people may not be able to provide. Some of the participants stated that they could not renovate their homes or buy emergency equipment and supplies due to insufficient income and the increase in other living expenses. They preferred to spend their meager income on daily necessities.Studies have shown that people with high income levels are more prepared for disasters , 31. In The interviews were conducted during the COVID-19 pandemic. Some households did not want to participate in the interviews due to the possibility of disease transmission. Some women and most men were working, so the interviews were conducted in the afternoons or on holidays when they were at home.Participants in this study expressed several cognitive, behavioral, social, physical, and financial challenges. Many barriers and challenges can be solved by developing and implementing educational programs. Many of these challenges, however, cannot be overcome by households without the assistance of the government and officials. By removing the challenges and barriers, adopting preventive measures, and improving the level of preparedness, it is possible to decrease the casualties after earthquakes.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.The Ethics Committee of Kerman University of Medical Sciences approved this study. A Qualitative design was employed in 2021. The code of Pajouhan is 400000068 and the ethic approval code is IR.KMU.REC.1400.719. All methods were performed in accordance with the relevant guidelines and regulations; this article does not contain any studies with animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study written informed consent was obtained from individual participants. Confidentiality and anonymity of the participants were ensured by coding of the questioners. Study participants were informed clearly about their freedom to opt out of the study at any point of time without justifying for doing so.The study's concept and design were created by ER. The survey was performed by NK. Data analysis and manuscript writing were handled by HF and MN-M. NK oversaw the research and provided critical feedback on the manuscript. The final manuscript was read and reviewed by all authors.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.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.


Destination loyalty is a key indicator of the competitiveness of tourist destinations. Rural summer health leisure vacations for urban elderly (RSHLVUE) tourists span a wide range of ages. Destination operators need to understand the loyalty formation mechanisms of different aged tourists. RSHLVUE tourists were divided into a low-aged group (LA) and a high-aged group (HA) to examine and modify the hypothesis of the relationship between perceived value, tourist well-being, place attachment, and destination loyalty based on affect, behavior, and cognition (ABC) theory. The test results of the measurement model indicate that the HA showed stronger responses in terms of cost value, sense of meaning, and place dependency. The formation mechanism of destination loyalty for the LA is tourist well-being → perceived value → place attachment → destination loyalty, and for the HA is perceived value → tourist well-being → place attachment → destination loyalty. The findings deepen the understanding of destination loyalty among elderly leisure vacation tourists and can guide RSHLVUE destination managers to enhance destination competitiveness. The increasingly aging population and the implementation of the rural revitalization strategy have produced a new leisure vacation industry in China, namely, rural summer health leisure vacations for the urban elderly (RSHLVUE). By the end of 2021, China had 267.36 million people aged 60 and above, accounting for 18.9% of the total population . The retRSHLVUE has the characteristics of rural, summer, health, and elderly tourism while developing its own unique characteristics as follows: (1) Tourists are mainly elderly people from nearby cities, (2) the stay length of tourists is usually 1–3 months, (3) the purpose of the vacation is for summer health, (4) the operators of destinations are mainly local villagers, and (5) the destination includes a combination of food and accommodation with a low consumption price. RSHLVUE has been the leading industry in some villages in China.Loyal tourists informally connect potential tourists such as friends and colleagues to the destination . The cosDifferent age groups of tourists perceive the external environment differently , and theAffect, behavior, and cognition (ABC) is a theory of attitudes in consumer behavior . It arguBased on the characteristics of RSHLVUE tourists, this study has two objectives. First, how to measure the four variables of perceived value, tourist well-being, place attachment, and destination loyalty. Second, to construct the hypothesis of influence mechanism for these four variables and to validate/revise the hypothesis of influence mechanism with the questionnaire data from low- and high-aged elderly leisure vacation tourists from Zhongyuan Township, Jing’an County, Jiangxi Province, China.RSHLVUE represents an overlap between rural, summer, health, and elderly tourism. RSHLVUE destinations are usually in high-altitude mountain villages with the characteristics of rural tourism . RSHLVUESome of the villages that are developing RSHLVUE have already formed a certain scale. For example, Guzhu Village in Shuikou Town, Changxing County, Huzhou City, Zhejiang Province receives 2.01 million elderly tourists from cities such as Shanghai and Hangzhou every year ; SanpingSimilar to Dodds et al. , the perWhen tourists’ perceived value of a destination is high, their level of well-being is high as well . TouristH1. Perceived value has a significant positive effect on tourist well-being.The concept of place attachment emphasizes the emotional connection between people and places . ScholarPositive and strong attachments are created by staying in a place for a long period . Lee et H2. Perceived value has a significant positive effect on place attachment.Loyalty is a firm commitment to repurchasing a product or service in the future . DestinaH3. Perceived value has a significant positive effect on destination loyalty.RSHLVUE tourists usually stay in the countryside destination for a month or more. The countryside’s good natural environment, comfortable climate, and fresh air enhance the physical health of elderly leisure vacation tourists. The group living and the richness of activities could also eliminate their loneliness and enhance their well-being . They foH4. Tourist well-being has a significant positive effect on place attachment.Tourist well-being is the most powerful determinant of positive behavioral intentions. For example, Jamaludin et al. found that relatively stable and happy groups were important in ensuring destination loyalty intentions . Vada etH5. Tourist well-being has a significant positive effect on destination loyalty.Place attachment is seen as an important push for tourists to destinations and is an important factor influencing tourists’ behavioral intentions . The higH6. Place attachment has a significant positive effect on destination loyalty.M0 of RSHLVUE destination loyalty is proposed, as shown in The CAB framework in ABC theory considers the consumer decision-making process for a product to be similar to a problem-solving process, with the following steps ,69. (1) The research site for this study was Zhongyuan Township, Jiangxi Province, China. It is about 100 km from Nanchang, the capital of Jiangxi Province. Its average altitude is 655 m, air humidity is 82.5%, forest coverage is more than 86%, and air has a negative oxygen ion content of 100,000 ions per cubic centimeter. Its average summer temperature is 20–22 °C, which is 6–10 °C lower than that of Nanchang City. Zhongyuan Township has been developing RSHLVUE for more than 20 years. By 2020, the destination had more than 640 nongjiales (Farmhouse Joy restaurants), with more than 20,000 beds and 2000 employees. The comprehensive income from summer vacation tourism amounted to 130 million yuan. The main tourists come from Nanchang. Thus, Zhongyuan Township provides a convenient venue for researchers to observe, extract, and analyze the mechanisms of destination loyalty formation among elderly tourists.First, to identify the measurement dimensions of perceived value, tourist well-being, place attachment, and destination loyalty, a systematic literature review and the first semi-structured interviews were conducted. The first semi-structured interview was conducted from 1–4 July 2021 in Zhongyuan Township with 15 elderly tourists. Each participant was interviewed for about 45 min.Second, a questionnaire survey was conducted. The survey was carried out by 14 students trained in research methods. Owing to eyesight problems, most elderly people were interviewed verbally for the survey. The survey was conducted in two phases: (1) A pre-survey was conducted from 22–23 July 2021; (2) a formal survey was conducted from 25 July–5 August 2021.To reduce the effect of common method biases, a questionnaire was designed with three sets of questions in different orders. The Harman one-way test and the error variable control method test were conducted referring to Podsakoff et al.  and MeadFinally, the second semi-structured interviews were conducted from 25–31 August 2021. Twenty tourists were interviewed, ten of whom were in the 45–74 age group and ten in the >75 age group. The average interview time for each interviewee was 45 min.In this study, the measures of the four main constructs—perceived value, tourist well-being, place attachment, and destination loyalty—were drawn from previous research. The items for the five dimensions of perceived value were adapted from the existing literature ,73,74. TFirst, to refine the 52 preliminary items measuring the four constructs from literature and summaries, the expert panel method was applied. The expert panel was composed of three professors of health and wellness tourism research. In this study, the Delphi expert consultation was conducted using back-to-back expert anonymous questionnaires, and a combination of online and offline methods was used to collect data. The investigators explained to each invited expert to ensure that they understood the content of the items and the scoring principles. The experts were asked to rate the importance of each initial dimension on a five-level Likert scale. The initial dimension list with the mean of importance assignment > 3.5, the coefficient of variation < 0.25, and the full score ratio > 20% were selected to form the second version of the initial dimension group. Experts were asked to classify the initial items into the second version of the initial dimension list, and they found that 80% of the items were categorized consistently. Thus, the final initial dimension was determined. In the end, nine items were removed.Second, based on the modification suggestions collected during the pre-survey phase, 16 items were deleted, and 8 items were modified for clarity and comprehensibility. All items were scored using a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5) See . The finA one-to-one pilot survey was conducted with 100 respondents, and 92 valid questionnaires were returned. A total of 700 questionnaires were distributed during the formal survey phase, and 641 valid questionnaires were returned, with a valid return rate of 91.57%. The demographic characteristics of the respondents are shown in A common methodological bias test was conducted on the formal survey data. The Harman one-way test showed 11 factors, with the major factor accounting for 29.1%. The results of the error variable control method test showed that the model fit metrics did not become better with the inclusion of the common variance bias latent variable. The common methodological bias was confirmed to not have a significant effect on the results of this study.p < 0.05 was considered statistically significant. A one-way ANOVA test was conducted to understand the differences in the dimensions of the four constructs among elderly leisure vacation tourists of different aged groups; The stronger responses of high-aged elderly leisure vacation tourists in the value of cost can be explained in two ways. On the one hand, the older leisure vacation tourists are, the higher the probability of becoming sick. High-aged leisure vacation tourists consider more expenses for medical care . As a reBased on the above significant differences between low- and high-elderly people, we divided the elderly tourists into a low-aged group (LA) for 45–74 years and a high-aged group (HA) for 75 years and above according to WHO’s age classification criteria.The measurement and structural models of the four constructs of the RSHLVUE destination loyalty formation mechanism were analyzed separately for the low- and high-aged groups.n = 641), the LA (n = 329), and the HA (n = 312). As shown in To validate the measurement models for the four constructs in this study, construct validity, convergent validity, and discriminant validity were assessed using samples from the entire aged group (EA)  The cost value dimension was removed, as the perceived value to cost value significance level  was greater than 0.001 and had a factor loading of 0.18 (<0.3). (2) The sense of meaning dimension was removed because the p-value of the tourist well-being to a sense of meaning was greater than 0.001 and a factor loading of 0.29 (<0.3). (3) The association of EME2 with FUV3 and PLD1 with SEV2 was established because these two groups had the highest residual correction indices. The fit indices of models M1 and M2 were compared  LA: tourist well-being → perceived value → place attachment → destination loyalty. (2) HA: perceived value → tourist well-being → place attachment → destination loyalty.Based on ABC theory, this study is the first to explore the formation mechanism of RSHLVUE destination loyalty by aged grouping of elderly leisure vacation tourists. The results confirm that perceived value, tourist well-being, and place attachment are important antecedents of destination loyalty. However, the role of these antecedents in the formation mechanism of destination loyalty varies across aged groups. The specific findings are as follows. (1) In the RSHLVUE context, significant differences exist in the dimensions of each construct in the destination loyalty formation mechanism of LA and HA, with the most significant differences in the cost value dimension of the perceived value construct and the sense of meaning dimension of the tourist well-being construct. (2) Data from the LA and HA samples confirmed that place attachment directly affects destination loyalty. (3) Data from the HA sample confirmed the effect of tourist well-being and place attachment as continuous mediating variables that transmit perceived value on destination loyalty. (4) Data from a sample of the LA confirmed that tourist well-being indirectly influences place attachment through perceived value.This study makes the following theoretical contributions. First, based on ABC theory, tourist well-being is introduced into the study of the formation mechanism of RSHLVUE destination loyalty, enriching the study of destination loyalty formation mechanism. Existing studies usually consider satisfaction an antecedent of destination loyalty, neglecting the affective factor of tourist well-being. The introduction of tourist well-being in this study allows for a better exploration of the factors influencing the psychological dimension of destination loyalty. In addition to combining the characteristics of RSHLVUE tourists, this study constructs three dimensions of well-being measurement: emotional experience, sense of meaning, and health experience, to provide a scale basis for subsequent research related to the well-being of RSHLVUE tourists.Second, this study further subdivides elderly leisure vacation tourists by age to explore the loyalty formation mechanism, deepening the study of elderly leisure vacation destination loyalty. Existing studies explored the mechanisms of destination loyalty formation mainly from the perspective of tourists in general, without an in-depth understanding of tourist heterogeneity. This study confirms significant differences in the mechanisms of destination loyalty formation between LA and HA. The findings deepen the understanding of destination loyalty among RSHLVUE tourists and enrich the knowledge related to gerontology.The local government of the destination can formulate relevant policies to guide the operators to provide services for LA or HA, which will be more beneficial to improve the satisfaction and loyalty of tourists. More importantly, the results and findings of the study provide the following management insights and guidance to destination operators. First, leisure vacation tourists’ place attachment to the destination should be fostered. The results showed that destination loyalty of LA and HA was directly influenced by place attachment. Their functional needs for leisure vacation destinations can be met by improving medical support facilities and providing humanized care services to enhance their local dependence. Their sense of identification with leisure vacation destinations can be enhanced by conducting more recreational activities.Second, more targeted initiatives can be implemented to enhance the RSHLVUE tourist perceived value. For the LA, more focus should be placed on the environmental and social interaction aspects, such as by designing themed accommodations and adding small ornamental plants to enhance their perception of environmental value. By organizing group activities, a platform for interactive friendships among LA is provided to enhance their perception of social value. For HA, the focus on service quality, functional facilities, and price should be increased, such as by providing more cost-effective packages or group purchase discounts to improve the perception of cost value. The provision of facilities such as free medical testing equipment, fitness facilities, and walking aids enhances the perception of functional value. Regular free medical checkups should be held and services such as free errands for medicine should be provided to enhance the perception of service value.Third, the following differentiated strategies can be used to enhance the well-being of LA and HA. For LA, enhancing their well-being at the initial stage of arrival at the destination is needed. Destination operators focus on enhancing the emotional experience and health experience of the LA. Operators can choose to quickly mobilize the positive emotions and health experience of LA when they first arrive at the destination by organizing small-scale activities or giving them health care gifts. For HA, enhancing the sense of well-being in the middle and later stages of arriving at the destination is necessary, and more attention should be paid to the formation of their sense of meaning. Operators should pay more attention to giving respect to HA in their services and give them regular encouragement to make them feel their own sense of meaning in leisure vacations and promote the formation of loyalty.Finally, different measures can be used to enhance the attractiveness and competitiveness of the destination for the LA and HA. The recommendation willingness of HA is stronger, and RSHLVUE destination operators can be more biased to enhance their word-of-mouth marketing. Operators can give away brochures to them when they leave and ask them to promote the destination. The willingness to revisit is stronger among LA. Destination operators can establish a membership system to enhance their willingness to revisit through membership points and other membership tracking services, such as inviting members to participate in local festivals and events.This study has some limitations, which can be addressed by future research. First, the data source of this study was only from Zhongyuan Township, China, potentially hindering the generalizability of the findings. Leisure vacation tourists from different geographical and cultural backgrounds may understand certain topics differently, and future research should involve different regions as well as different countries. Second, this study only uses age as a segmentation criterion and does not examine the variability of destination loyalty under other segmentation criteria. Factors such as marital status and health status may be considered subdivision criteria in subsequent studies. Finally, subsequent studies could attempt to introduce additional variables into the model to further explore more potential antecedents affecting RSHLVUE leisure vacation destinations’ loyalty.


The main hypothesis is that a digital, biodata-driven, and personalized program would exhibit high user retention and engagement, followed by more effective management of their depressive and anxiety symptoms.This pilot study explores the feasibility, acceptability, engagement, and potential impact on depressive and anxiety and quality of life outcomes of the 16-week Feel Program. Additionally, it examines potential correlations between engagement and impact on mental health outcomes.This single-arm study included 48 adult participants with mild or moderate depressive or anxiety symptoms who joined the 16-week Feel Program, a remote biodata-driven mental health support program created by Feel Therapeutics. The program uses a combination of evidence-based approaches and psychophysiological data. Candidates completed an online demographics and eligibility survey before enrolment. Depressive and anxiety symptoms were measured using the Patient Health Questionnaire and Generalized Anxiety Disorder Scale, respectively. The Satisfaction with Life Scale and the Life Satisfaction Questionnaire were used to assess quality of life. User feedback surveys were employed to evaluate user experience and acceptability.In total, 31 participants completed the program with an overall retention rate of 65%. Completed participants spent 60 min in the app, completed 13 Mental Health Actions, including 5 Mental Health Exercises and 4.9 emotion logs on a weekly basis. On average, 96% of the completed participants were active and 76.8% of them were engaged with the sensor during the week. Sixty five percent of participants reported very or extremely high satisfaction, while 4 out of 5 were very likely to recommend the program to someone. Additionally, 93.5% of participants presented a decrease in at least one of the depressive or anxiety symptoms, with 51.6 and 45% of participants showing clinically significant improvement, respectively. Finally, our findings suggest increased symptom improvement for participants with higher engagement throughout the program.The findings suggest that the Feel Program may be feasible, acceptable, and valuable for adults with mild or moderate depressive and/or anxiety symptoms. However, controlled trials with bigger sample size, inclusion of a control group, and more diverse participant profiles are required in order to provide further evidence of clinical efficacy. Major depressive disorder (MDD) and generalized anxiety disorders (GAD) are very common but serious mental disorders that can lead to considerable deterioration in overall health and daily functioning levels. MDD and GAD are typically manifested by adverse effects on a person's thoughts, behaviors, motivation, feelings, and sense of well-being, as well as a major disruption of a person's day-to-day life. According to the Anxiety and Depression Association of America (ADAA) , 18.1% oApart from the direct implications on overall health and wellbeing of those affected, MDD and GAD also heavily impact the global labor market. The OECD reports  a 15–30%As can be understood, diagnosing, supporting, managing, and treating MDD and GAD is of utmost importance. Numerous reports –14 suggeCurrently, traditional approaches for the management and treatment of depression and anxiety involve pharmacological treatment as well as psychotherapy sessions offered in the form of Cognitive Behavioral Therapy (CBT) or Interpersonal Therapy (IPT). Usually, for the more severe and chronic cases, a combination of both therapy and medication is followed . The effToward alleviating accessibility barriers and inequalities in mental health care, as well as potentially addressing the factors contributing to non-adherence and non-response to management and treatment protocols, digital mental health support tools have spurred during the last years and especially during the COVID-19 pandemic period , 36. TheThese years, we are experiencing an evolution of management and treatment solutions for various physical health disorders toward precise medicine expressed by quantifiable data-driven schemes and continuous monitoring approaches. This established paradigm guides us to a potentially promising alternative for mental health support. Such approaches have been shown to significantly alter current practices and introduce considerable improvements in treatment adherence and effectiveness, with diabetes and cardiovascular diseases being two representative examples. For the former, continuous blood sugar monitoring devices along with insulin pumps are combined in a smart hybrid device that automatically regulates the delivery of insulin based on real-time readings of blood sugar levels. Similarly, for cardiovascular diseases, the pacemakers act by sending electrical signals to increase the heartbeats when their sensors pick up bradycardia conditions. In both cases, it is the introduction of objective data, as reflected by physiological measurements  that has enabled real-time, inexpensive, and unobtrusive interventions. These are usually integrated into closed-loop telehealth solutions which show increased engagement, effectiveness, and improvement of the quality of life of patients in comparison to conventional therapies –46. Thervia the utilization of mobile phones and wearable sensors. This kind of data varies in complexity, ranging from straightforwardly interpreted mobile app-based data such as user interactions, app usage, and activity tracking via the embedded mobile phone sensors , to much more complex data that may require dedicated devices and/or advanced collection and processing techniques such as physiological signals, voice, text, etc. The expectation is that part, or all, of the acquired data, offer a degree of objectivity and ubiquitousness and as such, it enables a greater understanding and a deeper insight into the behavior of individuals, in the context of their respective mental health conditions. At the same time, by incorporating an adaptive UX/UI such as a gamified experience, it is claimed that long-term engagement can be realized, enhancing in this way the effectiveness of the solution  feasibility study has been designed and conducted. In particular, focusing on mild or moderate MDD and/or GAD, Feel Therapeutics has designed and conducted a Proof-of-Concept (PoC), single-arm pilot study, aiming to (i) explore the ecological validity of the Feel emotion detection technology, (ii) validate the engagement with and (iii) evaluate the preliminary efficacy of the FP. The main hypothesis is that a remote, data-driven, and personalized program would exhibit increased levels of user retention and engagement during the 16-weeks, followed by a reduction of their depression and anxiety symptoms that would be captured by a respective decrease in associated clinical measures. In this work, we attempt to validate this hypothesis by presenting the main results of this PoC study, including (i) adoption/conversion rates; (ii) engagement levels with the program, along with the respective drop-out rates; (iii) the impact of the program on health-related quality of life; (iv) preliminary efficacy of the program; (v) validation of the emotion detection capabilities of the Feel technology measured at an in-the-wild environment.The rest of this work is organized as follows: in Section 2, a detailed description of the materials and methods used for the PoC study is provided. Furthermore, in Section 3, we present the results of the study focusing on the feasibility and acceptability of the program (Section 3.1), the ecological validation of the Feel Emotion Detection technology (Section 3.2), the participant retention and engagement in the program (Section 3.3), as well as a preliminary assessment of the program's impact on mental health symptoms (Section 3.4), quality of life measures (Section 3.5) and participant self-assessment metrics (Section 3.6). Then, in Section 4 we continue with a thorough discussion, presenting an interpretation of the results toward supporting our hypothesis (Section 4.1), along with a few further observations  candidate referrals from the undergraduate student mental health support unit of the National and Kapodistrian University of Athens; (ii) social media ads  and (iii) word of mouth.The company developed a dedicated web page that included information about the Feel Program for depression and anxiety for participant recruitment.The target audience for the study was general public, while the study recruitment process was advertised The study's inclusion and exclusion criteria were assessed based on self-reported candidate responses to the eligibility questionnaire, while they were also verified by the Feel Providers during the first introductory session. The main inclusion criteria were: (i) mild to moderate MDD (4 < PHQ-9 < 15) and/or GAD (4 < GAD-7 < 15); (ii) age ≥18 years old; and (iii) smartphone users/owners. On the other hand, the main exclusion criteria were: (i) severe MDD and/or GAD; (ii) personality disorders; (iii) psychotic disorders; (iv) bipolar disorder; (v) eating disorders; (vi) suicidal or self-harm thoughts; (vii) psychotropic medication; (viii) substance abuse.This questionnaire was completed by candidates at the screening stage, in order to assess their eligibility and included demographic information , presence of any of the exclusion criteria, along with wrist measurements, in order to determine the appropriate sensor size, in case of a positive eligibility assessment. The Demographic and Eligibility Questionnaire was embedded at the recruitment web page and completed at baseline.The PHQ-9 is a self-administered questionnaire for assessing the severity of depressive symptoms . The queThe GAD-7 is a self-administered questionnaire that serves as a brief clinical measure for assessing the severity of GAD . The queThe LISAT-11 questionnaire is a self-administered tool for measuring Life Satisfaction . It is cThe SWLS is a self-administered subjective well-being questionnaire that measures global life satisfaction . It consThe self-assessment questionnaire is a custom tool, aiming to capture the participants' perception regarding their accomplishments and progress throughout the 16 weeks of the program. Indicative questions of this survey are: “My concerns that brought me to the program have improved as a result of the services provided” and “I learned to think more clearly/accurately to reduce distressing emotions or behaviors,” among others. A 5-point Likert-type scale was used with participant responses ranging from 1 (strongly disagree) to 5 (strongly agree). The self-assessment questionnaire was completed at week 16 (end-of-program) in the Feel app.A wide range of mobile-app-related metrics was collected during the 16 weeks of the program, including participants' responses to emotion notifications, number of times each component of the FP was accessed, exercises completed, time spent in the Feel app, number of weekly sessions with the Feel provider attended, etc.After the completion of the program , the participants were asked to complete a feedback survey (administered in the Feel app), in order to identify and measure various aspects of their experience throughout the program. The first part of the survey addressed the overall level of satisfaction with the program. Then, a group of questions helped to assess the ease of use of the different program components  and the responsiveness of Customer Support. Next, questions on the importance and value of each program component followed. Finally, the participants were given the option to provide open-ended comments on aspects and features of the FP they particularly liked or considered useful, as well as recommendations for improvements. A 5-point Likert-type scale was used with participant responses ranging from 1  to 5 (extremely).st Department of Psychiatry, Eginition Hospital. The study took place between January 2020 and October 2020. Firstly, individuals interested in participating in the study should complete an online demographic and eligibility questionnaire, as well as the PHQ-9 and GAD-7. The applicants' eligibility was evaluated considering their self-reported survey responses, along with the study's inclusion and exclusion criteria (see Section 2.2). Candidates who fulfilled any of the exclusion criteria were immediately disqualified and received proper communication accordingly. Prior to the start of the program, eligible participants were provided a comprehensive description of the Program and study's scope and components, and scheduled an orientation session with a member of our customer success team that would introduce and onboard them on the program components.The study design was single-arm and was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the National and Kapodistrian University of Athens, 1th session) and at the end of the study . Participant demographics  that were acquired at the completion of the online demographic survey were also verified during the orientation session. A high-level presentation of the experimental process is illustrated in Participants that have accepted the invitation to join the study were provided with a Feel Emotion Sensor, downloaded the Feel app, and attended the orientation session, where they were familiarized with the basic components of the program and the key functionalities of the sensor. As a next step, they had to register to the Feel app and complete the onboarding quests that aim to walk them through the different parts of the program. Among these, participants could check the providers' availability, select their preferred one and book their 16 weekly sessions. All participants who completed these steps finally joined the study. Their progress was monitored at the middle  or Play Store (Android). For the present study, the FP focuses on people suffering from depression and/or anxiety and expands over 16 weeks and consists of the following components:The Feel Program (FP) is a fully-remote mental health support program created by Feel Therapeutics, in an effort to bring objective data and precise therapeutics in the management and treatment of mental health conditions and address the ever-increasing need of people to enhance emotional awareness and self-regulating skills. The program uses a combination of emotion journaling and evidence-based approaches, such as cognitive behavioral therapy (CBT), mindfulness and Positive Psychology (PP) techniques. Furthermore, it is augmented by physiological data that reflect the activation of the individual's Autonomic Nervous System and capture mental health and emotion-related information. The program is available as a patient support system in the USA and Europe and is available for download Feel Emotion Sensor: The Feel Emotion Sensor (FES) is a wrist-worn electronic device designed and manufactured by Feel Therapeutics  health use cases. In the context of this study, the Feel Emotion Detection (FED) has been the main functionality that has been deployed. The FED is the backbone of the Feel Program and is based on affective computing technology principles, translating physiological signals  to emotional events. The platform brings together many different data processing and insights extraction components, including data curation, artifact detection, signal processing and denoising, dynamic segmentation, feature extraction, personalization, and decision models.The FED infrastructure was developed and extensively tested by Feel Therapeutics, is proprietary and protected by U.S. patent , augmented by the data provided by the Feel Emotion Sensor and the Feel app. There are a total of 16 sessions with weekly educational material and exercises. The first 3 weeks of the program are foundational and build upon the participants' knowledge. The following 5 weeks focus on CBT, biopsychology and positive psychology and the final weeks build upon the Thoughts, Feelings, Behavior cycle with developing skills and resiliency. The Feel Provider utilizes the Feel Dashboard to access the data to identify themes, key words and behavior patterns to prepare for the session in order to connect-the-dots with the weekly material and exercises. During the session, the provider is able to target feedback and personalize interventions based on each participant's data. The provider also discusses the participant's next steps after graduation and how they can continue applying what they learned to their daily lives.Mental health resource center: This component is directly integrated into the Feel mobile app and compiles tutorials, exercises, and tips that focus on the challenges present when dealing with depression and anxiety. The information is designed to engage the participant on their journey and provide the scientific basis for the program interventions and tools. The exercises compliment the material and are customized by the provider based on the participant's data. The participant establishes motivation to engage in the program, set program goals and enhance the knowledge with theoretical frameworks and evidenced-based practices. The educational material and exercises assigned promote mind-body awareness and self-management to further improve the quality of life according to the goals of the participant. The goal is to help participants develop mental health coping skills. All of the material in the mental health resource center has been created by Feel Therapeutics utilizing evidence-based techniques, including CBT, Mindfulness, Biopsychology and Positive Psychology, and is available to the participants anytime via the Feel mobile app.via the Feel app anytime throughout the program.The emotion journaling aspect constitutes one of the core components of the data-driven nature of the FP. Thus, an engaging and intuitive journaling user experience has been designed and implemented in the Feel app. This journaling process integrates all the information required both for personalized interventions and for empowering the providers with emotion-related insights and patterns that could be leveraged during the weekly sessions. Additionally, it is used for algorithmic validation purposes, as well as improvements and enhancements of the Feel Biomarkers platform. The emotion journaling process can be either triggered by an emotion notification received by the FES  or be manually logged by the participant. For each emotional event detected by the platform, the participant receives a notification in the Feel app to register their response to the detected event. The participant is presented with two high-confidence answers, “accept” or “reject” and with two low-confidence ones, “skip” and “not sure.” In case of an accurate detection , the participant is also asked to specify the perceived intensity of the emotional event, ranging from 1 to 10, in the next mandatory step. Furthermore, participants are encouraged to input the triggers, thoughts, behaviors, and physical sensations associated with the specific emotional event in free-form text or voice recording in the following non-mandatory steps. It should be noted that for the emotional events manually registered by the participants , the journaling procedure is exactly the same, except for the first step requiring the response to a detected event. The complete structure for the accurately detected events involving all user input (both mandatory and not) is referred to as an emotion journal, while the sole completion of the mandatory steps constitutes an emotion log. All emotion logs can be accessed th week of the program, participants were asked to complete a set of questionnaires assessing their depressive and anxiety symptoms, as well as their life satisfaction levels, via the Feel app. Finally, at the end of the program participants responded to the same questionnaires, along with the self-assessment and the user feedback survey. No monetary incentive was provided to the participants.Upon the completion of the 8Regarding the FP feasibility assessment, the overall onboarding process is summarized and presented, followed by the participant responses to the eligibility survey. Considering that this is a PoC single-arm study that serves as a preliminary evaluation of the participant engagement with the intervention, followed by a preliminary assessment of the efficacy of the intervention, we have followed a per-protocol analysis approach. As stated by the FDA “the use of the per protocol set may maximize the opportunity for a new treatment to show additional efficacy in the analysis, and most closely reflects the scientific model underlying the protocol” . TherefoFor the evaluation of engagement metrics, the average values and percentages of participants engaging with the different program components are presented to evaluate engagement aspects. For such metrics, we present the aggregate values over a specified period of time , averaged over the number of participants. As previously discussed, for this analysis only the participants that completed the study have been considered. Finally, aggregate values of the participant responses to the user feedback survey have been employed to assess program acceptability.r) for the effect sizes. Minimal clinically important differences (MCID) are defined as at least five points for the PHQ-9 scores , with almost 70% of them being 18–40 years old, while their gender distribution was 62.5% females-37.5% males . The combination of the above supports the capability of FED to correctly identify the participants' emotional events in the wild.As previously discussed, among the primary aims of this study was to validate in-the-wild the performance of the FED that focuses on the identification of the significant emotional moments participants have been experiencing. In this context, an analysis of the FES-triggered emotion logs follows, considering the participants' responses (positive or negative) on the notifications sent, as well as the perceived intensity input by the participants during the emotion logging flow. Overall, the average precision levels, that reflect the ratio of total accepted notifications of the study to the sum of the accepted and rejected, were 87%. On an individual level, the mean precision among the participants was 88% with a standard deviation of 0.2. Moreover, when weighing each participant's precision with the total number of notifications, the obtained (weighted) average precision was 86%. Furthermore, it should be noted that 75% of the participants had a precision of at least 85%  indicating minimum bias toward the detection of emotions of a particular valence. More specifically, when referring to the positive valence emotions, study participants logged 32% “content” and 22% “joyous” emotions, while for the negative valence ones, they logged 18% “sad” and 28% “distressed” . Meanwhin = 31, 65% of the total participants).In order to measure and extract meaningful insights associated with the participant retention levels in the FP, we divide the FP into four parts (modules), each one consisting of four personalized weekly sessions spread across a time period of 1 month. The monthly retention rate is illustrated in SD = 10.3) in the Feel Mobile app and accessed it on average for 16.5 times throughout the week which translates to roughly 2.5 times per day. Moreover, regarding the weekly data-driven sessions, we observed that the session compliance ratio was 96.9%, while on average, the participants completed 5 mental health exercises/educational material provided via the mental health resource center of the mobile app per week. Aiming to capture the overall participant engagement and their progress/efforts toward improving their mental health, an aggregate engagement metric, the weekly Mental Health Actions (MHA), is introduced. This metric includes the number of emotion logs, completed mental health exercises/educational material, sessions with the Provider attended, as well as whether the participant has engaged with the sensor or not and is calculated on a weekly basis. During this study, participants' MHA reached an average of 13 actions per week.Regarding participant engagement, we gauge it by metrics that capture all the different aspects of the FP. We define as “active,” a completed participant that shows engagement with one or more of the study components . With respect to the overall activity in the FP during the study, it was observed that participants engaged with any component of the FP on average for 3.1 days per week, with an average of 96% of them being active on a weekly basis. The participants spent close to 60 min per week  registered by the participants. More specifically, in SD = 3.44), while for the mid-program evaluation the obtained mean reduces to 6.23 (SD = 3.15), and reaches an average of 3.76 (SD = 2.48) at the end of the program. Similarly, for the GAD-7 questionnaire, at baseline the mean score was 7.30 (SD = 3.68), reducing to an average of 4.26 (SD = 2.08) at the mid-program assessment, before reaching a mean value of 3.3 (SD = 2.18) at the end of the program. These results suggest that the overall average mental health symptom reduction throughout the FP was 54.3 % for the depressive symptoms and 54.8% for the anxiety ones. The reduction was statistically significant in both cases . More specifically, 87% of participants exhibited a reduction in depressive symptoms, while 83.8% had a reduction in anxiety symptoms. Additionally, 93.5% of participants presented a decrease in at least one the two symptom categories , while 77.4% of them showed a decrease in both of them. Referring to participants exhibiting clinically significant symptom improvement . More specifically, at the baseline evaluation, the mean SWLS score was 19.9 (SD = 5.42), at mid-program it increased to 23.8 (SD = 5.76) while at the end-of-program evaluation, it reached 24.7 (SD = 4.71). At the same time, the corresponding scores for the LISAT-11 questionnaire were at baseline 3.86 (SD = 0.59), at mid-program 4.24 (SD = 0.68) and at the end-of-program evaluation 4.45 (SD = 0.54). Finally, 80.7% of participants demonstrated an increase at the SWLS scores throughout the program, while 71.4% showed an increase at the LISAT-11 scores.In An additional tool used to assess the impact participants perceive that the FP has had, along with their accomplishments during the program, was the participant self-assessment questionnaire. Participant responses, following a Likert-type scale, are presented in In this study, we have presented the results of a RWD feasibility study that serves as a PoC for a digital data-driven mental health program  for people suffering from MDD and/or GAD. In this context, an experimental protocol involving the deployment of the 16-week Feel Program at a population with mild or moderate MDD/GAD, has been designed and executed. Our first aim was to explore the feasibility of such a program, as captured by the responses of potential participants' to the recruitment campaign. We, therefore, implemented a relatively broad campaign, with the aim of exploring the various personas, mental health conditions and demographic profiles of individuals that were more interested in the program and, therefore, in joining the study. At the same time, the study protocol did include a set of strict inclusion and exclusion criteria , ensuring that only participant profiles aligned with the study scope were finally enrolled. Therefore, the recruitment campaign attracted a high number of respondents to the demographics and eligibility questionnaire, indicating that there is a great need for mental health support resources for numerous conditions. The combination of the high number of responses to the broad recruitment campaign and the presented exclusion and inclusion criteria led to an eligibility ratio of 8.5%. In particular, a high prevalence of the exclusion disorders  was observed, with 3 out of 4 applicants reporting the existence of at least one of the above. Additionally, we noticed that the vast majority of respondents were females (76.2%), frequently low-to-mid income level  and often with a basic level of education (32% high-school graduates or no schooling completed). This is in line with findings from previous studies , 65 thatThe second aim of the present study, after its feasibility was established, was to explore the main hypothesis which revolved around the fact that a remote, data-driven and personalized program would boost the participant engagement, while a significant improvement of their depressive and anxiety symptoms would be observed. In order to support our hypothesis, our analysis focuses on three main sections: (i) in-the-wild Feel technology validation; (ii) acceptability and participant engagement and (iii) preliminary assessment of impact on depressive and anxiety symptoms, as well as on quality of life aspects. In the following, we discuss in more detail the key findings of our investigation with regards to these aspects. In the context of technology validation, we aimed to demonstrate that the enabler of the data-driven nature of the FP, the Feel Emotion Detection technology, can be deployed in real-world settings maintaining similar performance levels compared to our testing environments. Successful deployment of technology is dependent on; (i) system-design-specific factors impacting performance , and (ii) successfully withstanding challenges associated with real-world applications, such as unknown emotional stimuli, noise signal artifacts and stochastic participant behavior. The results of this study show a very high average precision level (87%) in identifying emotional events for this group of individuals suffering from MDD and/or GAD. Moreover, positive and negative emotional events were detected in a balanced (54 and 46% respectively), suggesting that there was a minimal bias toward either valence category. Finally, we have shown that, for the majority of the participants (> 70%), their FES-triggered events were registered on average as high-intensity . These findings indicate that the Feel Emotion Detection technology performs well enough to capture significant emotional events from any participant.The next step toward validating our initial hypothesis includes assessing the acceptability of and participant engagement with the FP. Regarding the former, participant responses to the user feedback survey collected after the completion of the 16-week study suggest that participant satisfaction levels were considerably high with over 65% (20 participants) reporting very or extremely high satisfaction levels. Additionally, 4 out of 5 participants were at least very likely to recommend the program to someone. These findings imply that the FP sufficiently addressed their needs and met their expectations. Furthermore, the data-driven nature of the program—in the form of the data-driven weekly sessions with the provider and the FES—was recognized in the survey responses as one of the most important features of the program. Specifically, more than 90% of participants identified the weekly data-driven sessions as the most important feature of the program, while 70% selected the FES. Participants also reported particularly liking the data integration to the program and the in-the-moment interventions, powered by the FES-triggered emotion logs.Regarding participant engagement, we focused on participant retention levels throughout the program, as well as the degree of engagement with the different components. An overall 65% retention rate was observed with most discontinuations from the program occurring during its 1st month while no participants dropped out after the midpoint of the program. This could be related to the initial introductory period required for participants to acquaint themselves with the various program components, and the level of commitment, effort, and time resources required. Equally, this could possibly be attributed to the structure of the FP and its use of the theoretical framework of the Stages of Change  . During via the mental health resource center per week, followed by the emotion journaling feature, with completed participants registering an average of 4.92 emotional events, either FES-triggered or manually input, per week. Finally, a very high rate of attendance to the weekly sessions with the provider (96.9%) was also observed.Turning our attention toward participant engagement, a wide range of extracted metrics referring to all program components indicate high engagement levels. Overall, completed participants spent on average 60 min per week in the Feel app, accessing it on average 2.5 times per day. This equated to an interaction with at least one of the FP components on average for approximately 3.1 days per week. Additionally, the term weekly Mental Health Actions was introduced as a metric to capture participants' weekly activity during the week which reached an average of 13 actions per week for the completed ones. The highest amount of activity was the on average 5 mental health exercises accessed With respect to the main data-driver in the FP, the FES, completed participants engaged with it for 74.5% of the time while they were on the program, with an average of 76.8% of them using the sensor on a weekly basis. An interesting observation was that increased engagement with the FES boosted overall completed participant engagement in terms of both increased FES-triggered emotion logs, and also increased manually registered emotional events. The former seems quite intuitive, as the more physiological data are available, the more events can be detected. However, what is particularly interesting is that increased FES engagement was also highly associated with a higher number of the manual logs. More specifically, we observed that on the days that completed participants engaged with the FES, the number of manual emotion logs more than doubled, compared to the days without any FES engagement. The contribution of the FES to emotion journaling can be quantified by an approximate 5.5-fold increase in the probability of an emotion log occurring on days with FES engagement. The FES is considered a driving factor for overall participant engagement with the program, since it is strongly associated with the majority of the emotion logs, which are in turn linked with the various other components of the FP .Having discussed the in-the-wild performance of the technology and the fact that the data-driven nature of the program significantly enhances engagement, we lastly focused on depressive and anxiety symptoms, as well as on quality of life levels. For both MDD and GAD symptoms—reflected by PHQ-9 and GAD-7 scores, respectively—a continuing decrease in average scores was observed from baseline to mid-program, and all the way to the end-of-program evaluations, with 9 out of 10 participants reporting symptom reduction for at least one symptom category. Overall, the average reduction in both scales during the 16-week program was over 50%. For almost 3 out of 4 participants the severity of their symptoms decreased by at least one severity level, while a clinically significant improvement was characterized for almost half of the participants. This symptom improvement was followed by a subsequent increase of 24% on average in quality of life metrics. It should be noted that this study did not include participants with severe depression or anxiety symptoms, in order to exclude the effect of pharmacotherapy on symptom improvement. We anticipate that the inclusion of more severe cases will significantly enhance the total average reduction of mental health symptoms in a 16-week program like FP .In summary, the study results support that very high levels of participant engagement with a 16-week personalized data-driven digital mental health program, with its data-driven nature—coming from the use of a wearable sensor—being a key engagement factor. Moreover, the increased participant engagement levels and the data enhancement of the provided mental health support, may be linked to a significant reduction of depressive and anxiety symptoms, as well as an improvement in quality of life. Having discussed our initial hypothesis which evolved around the feasibility, acceptability, engagement and potential impact on mental health symptoms of the FP, a few interesting observations are presented. Considering that the emotion journaling aspect constitutes a core component of the program, we introduced an additional metric—the mood index—to capture the progression of participants' emotional patterns throughout the program. This new metric is derived from a combination of the different positive and negative emotions logged by the participants, where each emotion valence category is mapped accordingly to a positive (+1) or negative (−1) value, accordingly. The daily value is then derived from the average value of all emotions logged during each particular day. As an additional step toward exploring the importance of the data-driven component of the FP, we explored the level of engagement of different participant cohorts based on their baseline symptom severity. In this context, the average number of emotion logs per day was selected as a measure of engagement, as it constitutes one of the most important engagement metrics. In Finally, we explored the effects of differing engagement levels  on the program's impact on symptom severity. By utilizing the aforementioned index of engagement, we assigned participants to the high (or low) engagement group, if they had more (or less) than 1 emotion log every two days. This threshold was selected based on the average weekly rate of emotion logs for all participants. In When interpreting the results presented in such a paper, study limitations should always be considered. The most important among these is the lack of a control group, which could provide further evidence as to whether the overall symptom and quality of life improvement can be attributed to the intervention or not. Secondly, the sample size of the study was relatively small with 31 participants actually completing the program. Additionally, the different cohorts include a small number of participants, so the respective insights should be treated with caution. Thirdly, a more diverse demographic group  of participants could be included in future studies, in order to generalize the findings to a general demographic audience. Additionally, the study includes only participants with mild and moderate depressive and anxiety symptoms severity. Examining the impact of the program on severe cases in a follow-up study would be valuable. Finally, the level of mobile device proficiency was not monitored and its impact on participants' engagement was not assessed.In summary, this study aimed to explore the hypothesis that a digital, biodata-driven mental health program, the Feel Program, would introduce multiple benefits for people suffering from mild or moderate MDD and/or GAD. Therefore, we first focused on providing evidence supporting the feasibility of this program. Feedback from the participants revealed very high satisfaction scores across the different components of the program, and highlighted the significance of their data-driven nature. Moreover, overall completed participant engagement remained at high levels throughout the program and was significantly boosted by the use of the sensor. Additionally, we have shown that the key differentiating program component—the Feel Emotion Sensor and the Feel Emotion Detection—can be successfully deployed in-the-wild and can accurately detect significant emotional events. Overall, participants exhibited significant improvement on depressive and anxiety symptoms, with almost all of them showing symptom reduction at the end of the study. However, a controlled trial will be required to demonstrate further evidence of the clinical efficacy of the program. Finally, our indicators regarding the value of using personalized data - mainly collected by the FES—suggest enhanced engagement for groups with more severe depressive symptoms, as well as greater symptom improvement in participants with higher engagement throughout the program.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.The studies involving human participants were reviewed and approved by the Ethics Committee of the National Kapodistrian University of Athens, First Department of Psychiatry, Eginition Hospital. The patients/participants provided their written informed consent to participate in this study.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.Authors CT and GE are employed by Feel Therapeutics Inc., receive a salary and own a large share of the company stocks. DA and PF are employed by Feel Therapeutics Inc., receive a salary and own options of the company. JA is an advisor to and holds options of the company. 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.


Chronic wasting disease (CWD) is a disease affecting cervids and is caused by prions accumulating as pathogenic fibrils in lymphoid tissue and the central nervous system. Approaches for detecting CWD prions historically relied on antibody-based assays. However, recent advancements in protein amplification technology provided the foundation for a new class of CWD diagnostic tools. In particular, real-time quaking-induced conversion (RT-QuIC) has rapidly become a feasible option for CWD diagnosis. Despite its increased usage for CWD-focused research, there lacks a consensus regarding the interpretation of RT-QuIC data for diagnostic purposes. It is imperative then to identify a standardized and replicable method for determining CWD status from RT-QuIC data. Here, we assessed variables that could impact RT-QuIC results and explored the use of maxpoint ratios (maximumRFU/backgroundRFU) to improve the consistency of RT-QuIC analysis. We examined a variety of statistical analyses to retrospectively analyze CWD status based on RT-QuIC and ELISA results from 668 white-tailed deer lymph nodes. Our results revealed an MPR threshold of 2.0 for determining the rate of amyloid formation, and MPR analysis showed excellent agreement with independent ELISA results. These findings suggest that the use of MPR is a statistically viable option for normalizing between RT-QuIC experiments and defining CWD status. The diagnosis of prion diseases has historically relied on immunoassays such as enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC) . However disease ,11. The  disease ,13,14. B disease ,16. MoreDespite the growing interest in RT-QuIC-based diagnostics, there is currently no consensus regarding the interpretation of the assay’s output. Most authors determine CWD positivity by setting a predefined number of standard deviations  above the average background ThT fluorescence per plate and defining that fluorescent value as a positivity threshold  . This men = 30), (2) comparison to a negative control using a statistical test (n = 11), or (3) the average RFU of a sample’s replicates was above Tn = 5). The analytical approach used for CWD diagnosis was highly variable, without any clear agreement in RT-QuIC analysis regardless of tissue type.The literature review conducted in PubMed identified 46 peer-reviewed publications fitting our search criteria see   and RAF values (Rp: 0.1136) were both well supported by their lognormal regression models , which indicate the best tradeoff between sensitivity and specificity. The two highest indices were obtained with MPR values of 1.957 and 2.523. These support the TA conservative threshold , submandibular , and tonsil lymph node  distributions were all still very well explained by the normal regression model  suggests that they are mostly independent of each other. The weak correlation resulted in a poor fit of the linear regression as well (RRAFs were plotted against their corresponding MPRs to determine any relationship between the two . Spearmap: <0.0001–0.0129), except for one comparison  and 3 vs. 4  and 2 vs. 3  except 1 vs. 2 (p: 0.9612) and 3 vs. 4  batches to understand their potential effects on the assay. We detected no significant differences in negative-control MPRs between the batches A. HoweveBecause ELISA is used as the standard screening process for CWD diagnosis, a comparison was necessary to determine the agreement between MPR results and ELISA results. Out of the 420 RT-QuIC replicates produced from 64 lymph node samples (with one sample tested twice due to a conflicting result) for which tissue-matched ELISA data were available, 402 replicates agreed with the ELISA results, whereas 18 replicates disagreed  also shows that the dataset does not need to be exceedingly large for researchers to obtain an accurate distribution estimate of a negative control. It should be noted that this study focused only on lymphoid tissue, so MPR distributions for other tissue types should be independently determined.Using MPRs instead solves the statistical issues associated with interpreting RT-QuIC data with RAF values alone. Of 2974 negative sample replicates from over 500 individuals, MPR values were distributed normally see . FurtherInterestingly, there is seemingly no correlation between individual replicates’ MPR and RAF values, indicating that the two measurements are mostly independent of each other . This man = 20) for that batch  for articles that performed RT-QuIC between 2012 and 2021. Studies were selected if the researchers both performed RT-QuIC and implemented a rubric for determining TSE status. Studies were not vetted for any particular prion disease or proteopathy.In accordance with the culling efforts of the Minnesota Department of Natural Resources (DNR), 668 lymph node samples from 533 wild white-tailed deer (WTD) were sampled from CWD endemic areas in southwestern Minnesota . Followin = 515), CWD-positive medial retropharyngeal , submandibular , and palatine tonsil  lymph nodes were collected and stored at −20 °C. For controls, PLNs from known CWD+ and CWD− WTD were used. Approximately 100 mg of lymph node tissue were homogenized in 1X PBS to a concentration of 10% (w:v) using a BeadBug™ homogenizer  and 1.5 mm zirconium beads  for 90 s at the maximum setting. Homogenates were stored at −80 °C until tested, at which point they were diluted 100-fold  in dilution buffer  sodium dodecyl sulfate, 1X NAdditionally, parotid  [ [1], a sw:v). Reactions were performed in quadruplicate for all the samples (n = 668), and six replicates per plate for positive and negative controls. All the experiments were run using four BMG FluoStar® plate readers . Assays were performed at 42 °C, and readings were taken every 45 min with one-minute cycles of double-orbital shaking and resting. The gain was set to 1600. Four different batches of recPrP substrate were used in the span of this study and were produced at The University of Minnesota Biotechnology Resource Center.The expression and purification of recombinant prion protein  and RT-QuIC assays were performed following Schwabenlander et al. [J = sensitivity + specificity − 1). RAFs were computed retrospectively by taking the reciprocal of the time in seconds needed to cross TMPRs and their associated RAF values were adapted from the algorithm of Cheng, et al. . MPRs we results . Cutoff zero see .n = 3560) and control (n = 601) samples. For those replicates which crossed Tn = 524) and control (n = 316) replicates. Rp-values were calculated to diagnose the regressions . A low p-value indicates that the distribution is skewed, and an Rn = 2594), SMLN (n = 217), or TLN (n = 427). Due to insufficient data points, RPLN (n = 17), PPLN (n = 30), and PSLN (n = 16) replicates were excluded from this analysis. The differences in tissue-specific MPR distributions were compared using a Brown–Forsythe and Welch ANOVA, and a Dunnett’s T3 multiple-comparison test.Data curation and management were performed in the R software v4.1.0 (R Core Team 2021), and GraphPad Prism version 9.0.1  was used for all statistical analyses. The relative frequency distributions and density plots for MPR values were constructed for both unknown  were plotted against their corresponding MPR values to determine the relationship between conversion efficiency and ThT fluorescent intensity. Spearman’s rank correlation test was performed to determine the correlation between the individual replicate measurements.RAF values greater than zero (p < 0.05.CWD diagnosis using the MPR method was performed by comparing four MPR replicates to six replicates of each experiment’s corresponding negative control using a one-way ANOVA and a Dunnett’s multiple-comparison test . A samplRT-QuIC results from the MPR method were compared with ELISA results when available. In total, 420 replicates from 64 samples were analyzed using Cohen’s kappa test to determine the reliability between ELISA and RT-QuIC results using the MPR method.