It has been suggested that there is a relationship between the outdoor settings and the recovery of psychiatric patients. Recovery describes an individual process, which can vary from person to person. (2) Methods: This scoping review examined the relationship between the physical environment and the recovery of psychiatric patients. Systematic searches in three online databases, namely Medline, Embase, and PsycINFO, were performed using a selection of psychiatric, environmental, and recovery terms and included both quantitative and qualitative studies. In general, ‘well-being’ serves as an overarching indicator when it comes to research on how outdoor settings can affect mental health. Well-being was expressed in terms of mood, social relations, and autonomy. (3) Results: A total of 8138 records were screened, 85 studies were included for full-text reading, and five articles were included in the final analysis. The review showed in general that outdoor settings, more specifically gardening, contact with nature, and a safe environment can be related to the well-being of patients on psychiatric wards. (4) Conclusions: The five reviews allow us to conclude that outdoor settings can be seen as a comprehensive resource for mental health. The outdoor environment is providing a wide range of benefits for physical and mental health ,2,3. Thepersonal recovery, further elaborated below.A review focusing on Nordic experiences  from 2015 further describes how the green care concept  can provide activities for people with mental health difficulties (among other groups) and strengthen mastery, coping, and meaningfulness . All of Personal recovery involves an individual process and can vary from person to person. In contrast to clinical recovery, personal recovery focuses on the individual’s subjective process of finding a path towards living a meaningful life, rather than focusing on the absence of disease symptoms . The proConsequently, the main focus of personal recovery is not centered around a reduction of symptoms or medicinal intake but on the hope of finding ways to live well despite mental health challenges . Or, as The aim of this scoping review is to provide an overview of the field of research dealing with the relationship between environment in which psychiatric wards are situated and the recovery of psychiatric patients. The scoping review will focus on the outdoor environment as a structural framework that can support the personal recovery of various patient groups, and where better recovery is the goal. The study aims to identify emergent themes that should be considered in the future design of new outdoor areas in psychiatric wards. The scoping review will focus on articles from 1990 and until the present day, since the current focus on personal recovery was first articulated 1990 .Formulating the initial research questionIdentifying relevant studiesSelect relevant studiesCharting the dataCollecting, summarizing, and reporting the results.The methodological procedures that were used to conduct this scoping review were based on Arksey and O’Malley’s five-stage framework for conducting a scoping review . The fivhttps://osf.io/5wy73/ (accessed on 31 December 2021).The review is reported in accordance with the PRISMA guideline for scoping reviews . The proA pilot search in Prospero identified around 20 ongoing review articles dealing with the association between the outdoor settings and recovery. Only a limited number of these focus specifically on the importance of the environment for recovery among psychiatric patients. A few of them focused on children and adolescents  or on spIn the beginning of the process, search terms were identified in cooperation with a research librarian. The search terms were used in pilot studies before the final search to see if the terms were efficient. In January 2022, the final literature searches were carried out at University of Southern Denmark’s library in three online scientific databases: Embase, Medline and Psych-info See . In addiWe used the PEO  question format for qualitative research questions . The PEOWhat is the connection between outdoor settings and recovery on psychiatric wards?In the category population, we use the use the search words psychiatric* and psychiatry*. We are not interested in the diagnosis but in the fact that the patients are placed in a psychiatric ward.In the category exposure, we used common words for outdoor areas, such as garden or more generally outdoor, but therapeutic and healing gardens have also been included since these are common words for outdoor areas focusing on patient well-being.In the category outcomes, we used several synonyms for recovery. The effort of providing support for people undergoing a personal process of recovery is occasionally termed rehabilitation . TherefoWe will include all studies regardless of methodology or design to provide a rich and descriptive overview of the current state of research, while acknowledging that as an emerging field it has yet no research cohesion.We used several restrictions to narrow the search. The articles had to describe empirical studies, and the patients had to be above 18 years old. Otherwise, studies were excluded.In addition, we used the following eligibility criteria: (a) the study only included research studies  published between 1990 and the present day and (b) studies had to be conducted at mental wards and described in the English language.Two reviewers, the first and second author, independently screened titles and abstracts from the databases for eligibility using the software Covidence. We also used Covidence to remove duplicates and manage full text versions of publications included. A total of 8138 references were identified through Medline, Embase, PsycINFO. After we had removed the duplicates, 5826 references remained. We excluded 5741 references as they did not meet the inclusion criteria and read the remaining 85 references in full text. After the full text screening, we excluded 80 references that had a study design, patient group or language that did not conform to our criteria. The final number of eligible references we included in this systematic scoping review was five.The process of reference screening and study eligibility assessment is presented in the PRISMA flow diagram see .A data charting form was created based on the research question and the specific objectives guiding this review. Descriptive information of the studies, including the year and place of publication, population examined  and diagFollowing the data extraction, the first author conducted a content analysis to identify which aspects the study should focus on, so we could identify emergent themes and collect and identify objectives and gaps in our understanding of the current state of research. A spreadsheet was developed to extract data from the five articles. Data extracted included year of publication, study location, study design and method, study population, aim, and variable categories, as well as main results and conclusions . As dataThe review identified 5826 references after duplicate removal see , and a tAll participants from the different studies had a mental disorder, such as mood disorders , PTSD, schizophrenia, and personality disorders, although of varying severity. The studies including information about the age of the participants reported an age span of 20–72 years. In the studies that provided information on the gender of participants, a predominance of female participants was reported  ,30,31.All studies examined different aspects of the relationship ranging from use of the environment to gardening activities as aspects in supporting the process of personal recovery. A common denominator in the studies is the way specific indicators are used to measure recovery. In general, self-reported ‘well-being’ serves as an overarching indicator when it comes to research on how environment and horticultural activities can affect mental health. In the following, similarities between how the different studies approach the concept of well-being will be outlined. Well-being was expressed in terms of mood, social relations, and autonomy. Social aspects as ‘a sense of belonging’ ‘togetherness’, ‘socialization and peer support’ were also found to be linked to increased well-being ,30, and The examination of the participants’ mood in relation to being or working in garden environments was related to increased well-being in four of the five studies ,29,30,31Three studies also stressed that accompanying sensory experiences, such as smells, textures, temperatures, and colors, had a positive effect, allowing a distraction from inner thoughts, stress, and worries. Furthermore, the sensory experiences helped the participants to feel grounded and find focus ,30,31. Tn = 20) also indicated that a lack of clear architectural identity can be perceived as a confusing space [A consistent theme in many of the studies was the importance of a safe and supportive environment. Two of the studies found that such an environment required a clear architectural identity, a simple design with easily identifiable paths and entrances . Anotherng space ,28.The aim of this scoping review was to map the extent of existing empirical research to identify whether there is a connection between outdoor settings and personal recovery on psychiatric wards. At the same time, the scoping review also aimed to identify emergent themes that should be considered in the design of new environments on psychiatric wards.Three common themes were identified during the review study: (1) gardening and well-being, (2) contact with nature, and (3) a safe and supportive environment. These themes address different aspects of design that can influence the recovery of psychiatric patients. The themes have strong connections to an already established theory, namely the stress reduction theory (SRT) proposed by Roger S. Ulrich . Ulrich The articles used in the review were all published within the last seven years (2015–2020), even though we searched back to 1990. This indicates that the research area on recovery is growing, even though the number of publications is still small. The geographical spread across Europe, the United States, and Australia indicates that awareness of the issue is not geographically specific but extends throughout the Western world. Although the linkage between psychiatric wards, outdoor areas, and recovery remains fragile, we identified a large number of articles that described the positive effects of gardening  or time Some argue that scoping reviews can be criticized for a lack of thoroughness, as the approach is often mistakenly compared to systematic reviews . In addiOne strength of this scoping review was that the analysis permitted us to identify the connection between ‘well-being’ and outdoor activities. Furthermore, the literature search method was extensive and systematic, and it has provided a broad insight into the literature in this field. It was a strength that we searched in three scientific databases, which were all found to provide relevant articles relating to the purpose of the review. However, this review also has limitations. Most of the studies included in our scoping review used interviews with psychiatric patients, but the user groups were still rather diverse with different mental health conditions across each study. In addition, some findings were reported based on only few interviews, therefore the results should generally be interpreted with some caution. Finally, the results were based on studies from across the world with only two European studies. Therefore, the results may not be representative for a Danish context.The purpose of the scoping review was to identify existing empirical research on the connection between outdoor settings and recovery processes at psychiatric wards. A total of only five articles was identified, indicating a lack of research within this specific topic. Nevertheless, the articles in general showed that outdoor settings can be related to the well-being of patients on psychiatric wards. The five articles suggest that in the field of health promotion, outdoor settings should be seen as a comprehensive resource for physical, mental, and social health and well-being, offering both contact with nature, varied spaces, and safe and supportive environments. However, further studies will have to be conducted to establish conclusively whether there is a connection between outdoor settings and recovery on psychiatric wards.


Measurement of the quality of abortion services is essential to service improvement. Currently, its measurement is not standardized, and some of the tools which exist are very long, and may deter use. To address this issue, this study describes a process used to create a new, more concise measure of abortion care quality, which was done with the end users in mind. Using a collaborative approach and engaging numerous stakeholders, we developed an approach to defining and selecting a set of indicators, to be tested against abortion outcomes of interest. Indicators were solicited from 12 abortion service provision entities, cataloged, and grouped within a theoretical framework. A resource group of over 40 participants was engaged through surveys, webinars, and one in-person meeting to provide input in prioritizing the indicators. We began with a list of over 1,000 measures, and engaged stakeholders to reduce the list to 72 indicators for testing. These indicators were supplemented with an additional 39 indicators drawn from qualitative research with clients, in order to ensure the client perspective is well represented. The selected indicators can be applied in pharmacies, facilities, or with hotlines, and for clients of surgical or medical abortion services in all countries. To ensure that the final suggested measures are most impactful for service providers, indicators will be tested against outcomes from 2,000 abortion clients in three countries. Those indicators which are well correlated with outcomes will be prioritized. High quality, client centered health services are a human right, and access to the full spectrum of reproductive health options is necessary for all people to achieve that right. A critical component of reproductive health care is safe, high quality abortion services. In settings where abortion is legal, its safety has been well established . Yet, whWhen evaluating the quality of a particular health service, such as abortion care, it is important to be able to compare across geographic areas, providers, or modes of care. Comparison allows providers to evaluate their performance, and clients or policy makers to understand the range of options for services that are possible.Significant strides have been made to measure the quality of abortion services by researchers as well as service delivery organizations in a variety of settings –11. HoweBoth the World Health Organization (WHO) quality of care framework and WHO's vision for maternal and child health emphasize that the experience of care is an essential component of quality , 13, 14.Development of a set of standard measures to assess abortion service quality, irrespective of the service delivery channel  or procedure type  can ensure that a wide array of providers can efficiently and comparably collect data on and strengthen their services. To date, there are no studies which compare the quality of abortion services across different channels, or procedure types. Yet, pregnant people should receive the same level of quality care irrespective of the location and type of their legal abortion. Understanding how that can be measured is a valuable addition to the monitoring and evaluation already being conducted by many large non-profit service providers. Furthermore, it will aid public sector and for-profit private sector care providers, who lack the resources for extensive clinical evaluations.Despite this assertion, the authors' goal in creating a new measurement tool is utilization. To ensure a wide array of possible needs and voices are included, members of the Abortion Service Quality Initiative (ASQ Initiative) have led a collaborative effort with key partners, donors, and Ministries of Health to achieve this goal. This effort is modeled after other consensus driven and stakeholder inclusive methods, including the over 80 articles which have used a Delphi process or modified Delphi process to select quality indicators –22. SpecThis paper describes the selection of indicators to be tested for a simplified and standard suite of measures for abortion service quality.The process the ASQ Initiative undertook for selecting indicators to pilot test for a simple measure of quality began in 2017 by establishing consensus on a need for a more simple measure. It has advanced through progressive stages of indicator identification, consolidation, reduction, and testing following the Metrics for Management metric development process , along with two LMIC Ministries of Health, shared the quality assessment tools and indicators they use to monitor abortion quality. The development and testing of process indicators of quality is, in itself, a multi-stage endeavor, and having a starting point of tested tools allowed the team to leapfrog a few steps . With thFurther categorization was required before a unique list could be defined. To accomplish this a more granular framework for categorization was inductively created, drawing from the sub-categories outlined in Akachi and Kruk , as wellFinally, as some organizations collected individual data elements, whereas others collected more broadly worded indicators, a final set of unique indicators was created by combining indicators or elements with similar intent together and rewording if needed  dressing gown, b) socks and c) cloth drape. These granular and context specific measures and are grouped and reworded as “Clothing for client privacy and comfort”.The resulting ASQ conceptual framework contained almost 100 categories and over 200 unique indicators. In order to further reduce the list, we fielded two consecutive online surveys to seek input from members of the ASQ RG. In the first survey, in December 2018, the ASQ RG members were given a list of the categories in the framework, placed within the framework hierarchy of domains and sub-domains. They were asked to indicate which categories they believed to be “most critical to measure well, in order to provide high quality abortion services.” Respondents were also asked to provide information about the rationale used in their selection process. Categories selected by at least 25% of respondents to the survey were retained at this stage.The second survey took place in February 2019, and focused on refining indicators within the retained categories. Several of the retained categories contained 10 or more unique indicators; additionally, some indicators contained lengthy checklists of supplies required, or steps in a process; attributes which would make them difficult to collect. The ASQ RG were asked to prioritize a limited number of indicators within these categories, and/or a limited number of items within an indicator checklist. Examples of these reduction requests are shown in Box 2Example 1: For each indicator related to “Integration of SRH services” in the list below, is this necessary to measure in a standardized way, in order to improve abortion service quality? The list included 6 indicators.Example 2: For each item related to “Supplies for exams and procedures” in the list below, is it necessary to measure the presence of this item in the consultation room only, in the operating theater only, in both, or not necessary in either location? This question is administered using a standardized checklist whose length could be reduced. The list included 25 items.in vivo and a priori quality domains and applied the codebook to the interviews. We drafted code summaries for each quality domain and then drafted indicators based on the patterns that emerged in each code summary. These newly drafted indicators were reviewed alongside the list of indicators derived from the 12 service delivery organizations, and duplicates in the existing ASQ database were discarded. Where those concepts were already measured by indicators in the existing ASQ database, but from a different perspective (eg: service provider rather than client) the research team included both measurement methods.Given the limited measures of client experience in existing tools and consensus at the expert meeting in 2017 that client experience is a critical aspect of quality, we conducted formative research with abortion clients at abortion facilities, hotlines, and unlicensed drug sellers in four countries. Through seven focus groups and nearly 100 in-depth interviews of people seeking abortion in Argentina, Bangladesh, Ethiopia and Nigeria, we sought to understand those features of the abortion service experience which mattered most to them . To deveFinally, a subset of the ASQ RG was engaged to define the outcome(s) against which indicators of quality would be assessed. The group worked virtually over a period of weeks to brainstorm, review and define outcomes for assessment. All indicators and outcomes were operationalized for pilot testing, through the design of appropriate study tools, and defining which clients and sites were eligible respondents.Starting with data collection tools and resources from 12 public and private abortion service delivery organizations, we extracted 1,860 items. Of these, 219 were excluded for reasons described above, and 548 were removed as duplicates, yielding 1,093 unique items. These items were consolidated into 243 indicators, organized in the framework seen in Following the consolidation into 243 indicators, reduction was driven by two surveys of ASQ RG members. Responses to the first survey represented approximately 45% of the group. In this survey, we did not capture whether a response was submitted on behalf of several members of the resource group from the same organization. A second survey of the ASQ RG had a response rate of 50%, weighted to account for responses submitted on behalf of an organization. From the 83 remaining, indicators were collapsed or dropped if measuring similar constructs. Seventy-two indicators originating from the data collection tools of the 12 organizations remained.Analysis of the qualitative formative data collected in 2018  led to tThe ASQ RG was also engaged to identify the most important outcomes, against which indicators will be tested. These indicators and outcomes were operationalized for data collection in three countries . Data were collected via client exit interview, provider interview, facility assessment and direct observation, as well as 30-day client follow-up survey to assess abortion outcomes.As indicators were operationalized for data collection, the study team identified which indicators were applicable to which care settings. For example, an indicator on infrastructure for high-level disinfection or sterilization of instruments is applicable only to facilities offering surgical abortion, one about the site being clean and well-maintained is applicable to any physical site, and an indicator asking whether clients received or knew where to get necessary supplies to manage bleeding after abortion is applicable to all abortion clients. Universal indicators to assess healthcare performance have been established in many fields. While the realities of care may differ by location or circumstance, the moral obligation to provide quality care is universal. Our collaborative approach—involving key stakeholders at each stage of the process—demonstrates that in the provision of abortion services, there are myriad quality indicators already in use; that there is significant overlap among the different tools, with many key components of quality addressed in different tools using variations on the same language, and from different perspectives or with different data collection methods. We found that 56% of our shortlisted indicators (62 of 111) were nearly universally applicable to all abortion care settings. This implies that there are other types of indicators which are suited only to certain settings, and that quality assurance processes for abortion must be flexible in their approach. Indicators which are currently being collected across the 12 representative organizations span a wide range of topics, as evidenced by the theoretical framework we developed.Nonetheless, we also identified key gaps in current abortion quality measurement. We were able to identify an additional 39 indicators from formative work centering the client experience, confirming a gap in available measures to achieve a holistic approach to measuring quality as guided by current thinking on what constitutes healthcare quality . StreamlOur approach may be limited in two ways. First, while our starting point yielded 1,093 unique data items, the organizations tools, and the contexts they represent, are not representative of all ways in which pregnant people seek abortions. For example, none of the providers were solely hotline based. Second, the participants of the ASQRG changed over time, although the represented organizations remained the same or expanded. This unavoidable lack of continuity given the length of the project may have impacted the understanding of participants on the project aims, or influenced their enthusiasm for participation. The number of participants in the ASQRG has been larger than found in many other Delphi or modified Delphi approaches.We found the initial consensus building meeting, and initiation of the ASQRG to be an essential part of the project success. Although we did not predict the multiple ways in which the RG would be engaged during the project, establishing that all were working toward a shared goal from the start likely improved their engagement during the project.Following from the work described in this paper, the analysis of the data from 2,000 abortion clients in Bangladesh, Ethiopia and Nigeria, representing first and second trimester care seeking at facilities, pharmacies and via hotline, will identify a reduced set of indicators associated with outcomes . The resThe goal of the ASQ Initiative is to generate a concise minimum list of abortion service quality indicators which are broadly applicable, predictive of one or more outcomes of interest, and able to be collected in across a variety of care settings in low resource environments. We envision that the continued participation of the ASQ RG will facilitate dissemination and use of the metrics and tools. While some of our stakeholders have advanced quality measurement approaches, others are eager to use a pre-identified, minimum set of indicators to improve the quality of their services, and the health outcomes of people seeking abortions.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.NC and EP organized the database. NC, EP, and SB performed the analysis. NC wrote the first draft of the manuscript. All authors contributed to conception, design of the study, interpretation of the analyses, manuscript revision, read, and approved the submitted version. All authors contributed to the article and approved the submitted version.Funding for this research has been provided by grants from the Children's Investment Fund Foundation and the David and Lucile Packard Foundation. Funders have collaborated in study oversight.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.


The lack of specific recommendations on the use of supplements for sport climbers may be the reason for their misuse by athletes of this discipline. This study aimed to evaluate choices of dietary supplementation, the reasons for taking them, and the source of information on supplementation among sport climbers at different levels. In addition, how climbers subjectively evaluated the impact of their diets in supporting selected aspects of climbing training was evaluated. We enrolled 110 regular sport climbers (40 women and 70 men) from Wroclaw, Poland, who completed a validated questionnaire, assessing their use of dietary supplements, attitudes towards the influence of diet on sports performance, and climbing level. Their anthropometric measurements were also collected. Participants regarded diet as an important element of sports performance. Sport climbers indicated the Internet to be the main source of information on supplements. Health maintenance and improvement of recovery were the most frequently chosen reasons for taking dietary supplements. The most common supplements were isolated protein, vitamin C, vitamin D, magnesium, and amino acid blends. However, participants rarely used supplements suggested as beneficial for sport climbing performance. Therefore, developing recommendations for supplementation in sport climbing and promoting this should be an elementary part of the preparation for climbing training. Dietary supplements are commercially available products that are consumed in addition to the regular diet. They include vitamins, minerals, plant extracts, amino acids, and many other substances . DietarySupplements can have a place in an athlete’s diet ,5. Some According to the 2018 International Olympic Committee (IOC) , some diDespite the purported benefits of supplements, they can have a negative impact on health and performance ,9,10. InSport climbing is enjoying growing popularity, with bouldering and lead climbing the most frequently practiced disciplines . BoulderThere are a growing number of studies focusing on supplement use in different populations of athletes ,16,17. AThe aim of the study was to evaluate dietary supplement use and types among sport climbers. We also aimed to assess how climbers subjectively perceived the impact of their diets on supporting selected aspects of climbing training. It was hypothesized that as the climbing level of the athletes increased, their knowledge about nutrition in different aspects of training performance should also increase. As such, climbers from the Elite group should perceive nutrition as more important in their training success than Intermediate and Advanced groups. Indeed, those in the Elite group may have a wider knowledge about discipline-specific supplement use due to the volume and intensity of their training. Based on this, we hypothesized that the frequency of choosing dietary supplements and their type would differ between groups representing different climbing levels. In addition, the study aimed to identify the reasons for taking dietary supplements and the sources of information on supplementation among sport climbers. The study included 110 regular sport climbers  from Wroclaw, Poland. The criterion for inclusion in the study was at least one year of regular sport climbing. The exclusion criterion was recreational climbing with less than once-a-week climbing practice. Information on the study was spread through social media and directly through the trainers of the climbing gyms (5) at the time. All climbers who were willing to take part for the duration of the study  and who fulfilled the criteria were accepted. A survey was carried out in person by the participants during their visit. If they had any doubts, they could consult their answers, which ensured they were as accurate and reliable as possible. Participants gave their informed consent for the study protocol and were informed of the option to withdraw from the study at any time. The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of Wroclaw Medical University (number KB-45/2019).The questionnaire used in the study consisted of questions assessing the use of dietary supplements and had been previously validated in a group of Canadian athletes by Erdman et al. . The queThe first part contained ten questions on supplement use, including sources of knowledge about supplements, reasons for their use, places of purchase, and participants’ subjective assessment of how discontinuing supplements affected their climbing performance. Participants also listed all supplements they had taken in the preceding six months.Another part of the questionnaire consisted of three questions and covered climbers’ dietary behaviors. This included questions on the type of diet they followed, a subjective evaluation of their diet, and an assessment of the importance of nutrition in supporting selected elements of climbing training. The last part of the questionnaire consisted of three questions and focused on participants climbing level and the frequency and duration of their training. Their climbing grade was determined by assessing three different routes established over the preceding six months. Participants were asked to indicate the highest grade, lead, or boulder they had managed to redpoint on three different routes/problems, on either an artificial wall or on a rock. The grade was then standardized according to the International Rock Climbing Research Association (IRCRA) scale. Participants were then stratified into a specific climbing level group, Intermediate, Advanced, or Elite, based on IRCRA scale score and gender . For femClimbers’ weight and body composition was measured using an X-Contact bio impedance balance . Height was measured using a TANITA HR-001 stadiometer . Participants were asked to come in the morning after an overnight fast. They were also asked not to perform intensive training in the evening before measurements. Based on the height and weight measured, the body mass index (BMI) of the participants was calculated.2. The Cochran–Mantel–Haenszel test was used to assess the impact of belonging to a given level of climbers on gender differences. The effect of climbing level on the perceived importance of nutrition for supporting climbing performance was assessed using the Kruskal–Wallis test and differences between genders here were assessed using Mann–Whitney U test. Differences were recognized as statistically significant when p < 0.05. For statistically significant differences, a post hoc test was performed to assess differences between the study groups. Descriptive statistics were generated according to the anthropometric measurements of the study group (Patterns (frequencies) of the reasons for taking dietary supplements and the source of information on supplementation were recognized in the whole group. Differences in the frequency of using given supplements between the three defined climber groups  and between genders were analyzed with the use of Fisher’s exact test (when the expected size of a group was less than five) or Pearson’s χdy group . Data ann = 110), filled out the questionnaire and underwent anthropometric measurements. All of the participants who were willing to take part and who fulfilled the inclusion criteria  and iron  when the whole groups of climbers were analyzed, and the Cochran–Mantel–Haenszel test indicates that belonging to a given level of climbers does not influenced these differences—the smallest p was greater than 0.05.The most common supplements were isolated protein supplements , vitamin C, vitamin D, magnesium, and amino acid blends (BCAAs or EAAs). Regarding supplements not included in the table, individual athletes declared taking supplements for joint regeneration (collagen and glutamine), plant extracts , probiotics, L-carnitine, beet juice, maca extract, and carbohydrate gels. The most frequent use of protein isolates, amino acids, vitamin C, creatine, magnesium, and multivitamin preparations was reported among elite climbers. However, there were no statistical differences between the caliber of athletes and the types of dietary supplements reported. The influence of gender on the use of supplements was borderline significant for creatine , are in the same category as sports food  and are According to the AIS, vitamin C belongs to Group B supplements , which aThe AIS-classified BCAAs and magnesium as Group C supplements , which mClimbers may benefit from supplementing with beta-alanine ,14, nitrOur study participants declared supplementation with maca extract, which, according to the AIS, belongs to Group D supplements. The extract itself is not prohibited for use in sports; however, it may be contaminated with banned substances, and taking it as a dietary supplement is not recommended .In summary, the choice of supplements used by the climbers studied was rather random. They were not only unrelated to the specific sports training they were undertaking, but it is also doubtful if they could prevent nutritional deficiency, which was the main reason declared for supplementing. Similar results were observed in a study on Spanish athletes, in whom the most prevalent group of substances chosen were those supported by little scientific evidence. It was suggested that this effect was produced by the availability of a high number of supplements on the market that contain minimal evidence for their effectiveness .In studies conducted among different populations of athletes, authors have reported the frequent use of multivitamin preparations . In our A properly balanced diet should provide all essential nutrients, vitamins, and minerals at optimal levels to meet the requirements of the body . RespectThere are little data on the prevalence of vitamin and mineral deficiencies among athletes. Furthermore, estimates generated for the general population are of little relevance to the population of professional athletes. Most nutritional surveys of athletes are based on dietary records or prospective data and are often compared with reference nutrient intakes (RNIs). This is of little value because the RNI is a population estimate, and, by definition, we expect that most of the population (98%) would have a nutrient requirement that is less than the RNI of the athletes. Deficiencies in an individual athlete are identified by measuring appropriate biomarkers .Participants in the current study reported nutrition to be an important part of climbing training, which may be evidence of their high nutrition education and awareness of the impact of pre-and post-workout nutrition on selected aspects of training. The mean value on a scale of 1 to 5 (where 1 means not significant and 5 means very significant) was higher across all groups compared to the values declared by climbers in the study by Peoples et al. In our study, climbers declared nutrition was most important for “recovery”, followed by “body weight” and “hydration”. In contrast, in the study by Peoples et al., participants reported that nutrition was most important for “hydration” and least important for preventing DOMS . In the current study, health maintenance and improved recovery were the main reasons for supplement use. One of the least popular reasons was medical indications, such as nutrient deficiency. Heikkinen et al. reported similar reasons for dietary supplementation among Finnish athletes . The maiIn our study, the most popular sources of information about supplements were online sources, followed by other climbers and family members. In a meta-analysis by Halabchi et al. , which eNo statistically significant differences were found in the use of supplements between the groups of climbers at different levels. Our study participants most commonly chose supplements with little scientific evidence for use in climbing. Additionally, they declared little or no use of supplements with proven effects, such as beta-alanine, nitrates, and sodium bicarbonate.The representatives of female and male climbers indicated selected sources of knowledge about supplements, as well as reasons for using supplements with different frequency. The choice of non-climbing specific supplements that do not have scientific backing is probably influenced by the source of information most frequently chosen by both genders, the Internet. Therefore, proper education on where to source trusted information on the Internet would be an excellent move forward. This would allow climbers to make informed decisions and would encourage them to make responsible supplementation choices. Developing recommendations for supplementation in sport climbing and promoting this knowledge through appropriate nutrition education should be an elementary part of the preparation for climbing training.A limitation of the study is that data were collected from the population of sport climbers in only one city, Wrocław. It would be necessary to repeat the study protocol in other Polish cities to see if the observed tendencies represent the bigger scale of the issue. Comparing results to similar research led by representatives of sport climbers from other countries would also enrich the state of knowledge on the topic.It would be interesting to evaluate the effectiveness of education on proper nutrition and responsible supplement use, as well as on the smart use of social media and the Internet as a source of information. This would allow for the identification of the most adequate ways of improving the knowledge of sport climbers, in relation to wise supplement choices.


The task of ore transportation is performed in all mines, regardless of their type (open pit/underground) or mining process. A substantial number of enterprises utilize wheeled machines to perform ore haulage, especially haul trucks and loaders. These machines’ work consists of repeating cycles, and each cycle can be divided into 4 operations: loading, driving with full box/bucket, unloading and driving with empty box/bucket. Monitoring this process is essential to create analytical tools that support foremen and other management crew in achieving effective and optimal production and planning activities. Unfortunately, information gathered regarding the process is frequently based on operators’ oral testimony. This process not only allows for abuse but is also a repetitive and tedious task that must be performed by foremen. The time and attention of foremen is valuable as they are responsible for managing practically everything in their current mine section . Therefore, the automatization of the described process of information gathering should be performed. In this article, we present two neural network models (one for haul trucks and one for loaders) build for detecting work cycles of the ore haulage process. Both models were built utilizing a 2-stage approach. In the first stage, the models’ structures were optimized, while the second was focused on optimizing hyperparameters for the structure with best performance. Both of the proposed models were trained using data collected from on-board monitoring systems over hundreds of the machines’ work hours and utilized the same input features: vehicle speed, fuel consumption, selected gear and engine rotational speed. Models have been subjected to comprehensive testing during which the efficiency and stability of the model responsible for haul trucks was proven. Results for loaders were not as high quality for haul trucks; however, some interesting facts were discovered that indicate possible directions for future development. Nowadays, new technologies are being introduced to various environments as Industry 4.0 progresses, and the mining enterprises are no exception . A largeThe work cycles for each machine type can be divided into 4 components: driving with empty cargo box/bucket, loading, driving with full cargo box/bucket and unloading. The problem of automated monitoring of ore haulage work cycles  for wheeled machines is not new, and some approaches can be found in the literature. These methods can be divided based on two criteria: by monitoring the vehicle and by the time series used for the algorithms. The easiest way to detect the haulage cycles is to monitor the hydraulic pressure measured at the hydraulic cylinder (bucket/cargo box), where the cycles components are clearly visible. Such an approach was presented by the authors of , where aSome methods can also be found to estimate work cycles without the use of hydraulic pressure signals; those are mostly (if not fully) dedicated to haul trucks. Authors of  presenteThe literature review uncovers some trends. There are only a few methods of work cycle detection for loaders, and they are all based on the hydraulic pressure signal. One possible reason for this could be that the process itself is especially complicated when considering loaders . On the Although literature for the assumed task is limited , the task of operational regimes detection is not. Expert systems are being constantly created that work based on standard linear programming and logic rules, such as the one presented in . Anotherboth of the models used the hydraulic pressure signal as a reference, but did not use it as input feature (one of the first such approaches for loaders);both of the models were fully validated on large scale samples in terms of efficiency and stability;results acquired for haul trucks are currently the best available, indicating that the model can be implemented into the information-gathering process;results acquired for the loaders, despite being weak for most of the machines, are very good for one (with considerable contribution to sample size). This machine case may pave the way for further research.In our research, we wish to present the methodology used to build two neural network models that can be used for work cycles detection. What distinguishes the approach presented in this article and brings some novelty to the already researched topic is as follows:The structure of this article is as follows. In The ore haulage process can be performed in several ways, and one of them (used for longer haulage routes) is completed using two types of wheeled vehicles: haul trucks and loaders . For thiThe ore transportation process is the second most important operation in numerous mining enterprises (after ore extraction). This process can be performed using four means of transportation: wheeled vehicles, trains, conveyors  and shafts . Each mode of transport has different characteristics that correspond to its efficiency, effort of initial implementation, cost of use, etc.  In this When there is not much material to transport, or when the transportation path is short, the loader can be allocated to complete this task alone. However, most cases require the second configuration, where a single loader is assigned to the mining face along with several haul trucks. In such situations, the loader is responsible for filling up the haul trucks. The overall process is similar to the first configuration, but it is more time efficient. The loader drives to the ore pile, then uses its bucket to raise some of the material. It then drives to the haul truck, where the unloading takes place (bucket is tilted down and then lowered). This whole process represents one work cycle. Three LHD unloadings are usually needed to fill the entire cargo box of the haul truck. Similar operations can be determined for haul trucks. Their work cycle begins with driving (cargo box empty) to the loading site, where the cargo box will be filled by the designated loader. Once full, the haul truck will drive to the site where it will perform unloading (either by tilting the cargo box or by pushing the spoil out of it).Because the number of performed work cycles and other important KPIs are being calculated based on oral testimony, risk of abuse is introduced to the system that can potentially disturb the reports. Furthermore, requesting the information manually means that companies are unable to adequately estimate some KPIs that are important to the process, such as cycle time  or energNowadays, it is common for the machines that are used in the mining industry to have some form of monitoring system. Depending on the machine and the company, such systems can measure a variety of signals, which provide more or less information. Data in this research comes from an on-board monitoring system which measures over a dozen variables, where most of them are consistent between loaders and trucks. Each of the signals is first measured with frequency of 100 Hz; later, the archiving system automatically calculating the mean value aggregated to 1 Hz. Access to larger sampling in this case is possible but very limited, as it requires a worker to manually download the data. Therefore, the 1 Hz data were used as they allow for complete automation.SPEED—Instantaneous machine speed [km/h];SELGEAR—Selected gear of 9 possible , where positive value means driving forward and negative means driving backwards;FUELUS—Instantaneous fuel consumption [l/h];ENGRPM—Engine rotational speed [rpm];HYDOILP—Hydraulic oil pressure of working system [kPa] (reference);As mentioned earlier, the indirect variable used as a reference for training the models is the hydraulic oil pressure signal from the working system . Authors of  analyzedThe above-mentioned list of variables was chosen not only because their impact and correlation with HYDOILP has been proven. They are also all of very good quality, and they are the highest of all signals measured in terms of missing values, sensors MTBF (Mean Time Between Failures) and availability. In addition, almost all mining machines utilize some form of sensory network which usually covers the presented list.The method of input data processing, their normalization and structure are crucial for the neural network model effectiveness and stability . Each inThe described preprocessing method that was used to create the input samples was the same for both haul trucks and bucket loaders (with the exception of the moving average). The differences appeared later  in form The hydraulic oil pressure signal allows for estimation of work cycles in case of both haul trucks and bucket loaders. However, the variable itself along with the estimation process is drastically different depending on the machine type. In case of haul trucks, the only information that can be extracted is the moment of unloading that appears as a large peak in the pressure signal (matching the cargo box operation). Therefore, the algorithm for their detection is quite simple and involves using a threshold to divide the signal into two values: unloading and other. This is shown in For bucket loaders, the HYDOILP variable is more informative and allows for detection of each of the work cycle components. This estimation can be performed using the algorithm presented in , but we Initial trials showed that the categorization approach is much more effective than the regression. As each of the input samples consists of several work cycles, it was decided to split it further using a windowing operation. Window length differed depending on the machine type (mainly because of the operation schema): 30 s for loaders and 120 s for haul trucks. Therefore, for each input sample of shape 30x4 for loaders and 12 × 4 for trucks, the model returned the category vector of length 2 for trucks and 3 for loaders .Neural network structure is determined by the order and appearance of layers inside the model. Usually, frameworks that are used for the construction of neural networks have some pre-defined layers that are used as building blocks. This is essentially the most important factor that needs to be faced when constructing NN models ,30. Alth1.Create a space of all possible structures, within the assumed parameters;2.Remove from that space all of the structures that are incorrect or incompatible with two general architectures;3.Pre-train all structures with default hyperparameters and evaluate their performance;4.Return one best structure.Choosing the right network structure for the model significantly increases the results achieved with it. From all the possible layer combinations, manually constructing the network structure is a tremendous task that will most likely fail to achieve the most optimal arrangement. Therefore, the following algorithm, which is rather simple but effective, was implemented to automate this process:The structures space was initially created with two main boundaries: 1—all structures need to be built from the combination of 3 layers: convolutional, dense and dropout, and 2—there was a maximum number of layers set that the structures can achieve. The space then was crafted by iteratively taking Cartesian product of two sets of layers combinations as it is showed in below formulas (1) and (2).All of the convolutional layers in the network must form a consistent block in the beginning of the structure, and can be only intertwined by dropout layers;The Structure has to possess at least one dense layer;There cannot be two sequential dropout layers in a structure.When the structures space was created, some of the combinations had to be removed, mainly because of their incorrectness or incompatibility. Structures that did not meet the following criteria were removed:After cleaning of the space, the structures were ready to be trained. The default hyperparameters used in this process were: 360 neurons and ‘relu’ activation function for dense layers, 16 filters and  filter size for convolutional layers, 30% probability for dropout layers, categorical cross-entropy loss function and Adam optimizer with default settings. The training process of the networks was handled by using the EarlyStopping callback, set on parameters that ensured faster but less accurate training (pretraining). Finally, all the trained networks were evaluated, and the best network was chosen.Hyperparameters of neural network model layers are the second most important factor, after the model’s structure. The task of their optimization is usually performed in a similar way to the process presented for structure optimization. The key difference is that the optimization algorithm operates in param space instead of a structure space. The Talos library  was usedThe optimization of hyperparameters with the Talos library began with declaration in the form of a dictionary. The keys of that dictionary corresponded to hyperparameters, and the possible parameter values were stated for each key. Using this dictionary, the param space was created (again with by using the Cartesian product). For this optimization task, the hyperparameter keys used along with their description are presented in After creation of param space, the Talos library performed the optimization by iteration through all param space elements. Each of the possible combinations were created using the dictionary keys, then trained and finally evaluated.64,288 2-min samples for haul trucks, 31,113 per class (2 classes), resulting in a total of 2143 h of work;102,042 30-s samples for loaders, 34,014 per class (3 classes), resulting in a total of 850 h of work.The main result of the research presented in this article was the development of two neural network models with proven efficiency and stability. To achieve this task, methods presented in This data was then used in the optimization process for both structure and hyperparameters , and finBecause the task of cycles detection is more difficult for loaders (3 classes and different work schema), it was assumed that the model should be larger for them. Therefore, in optimization for structure, the only optimization criterium (maximum number of layers) was set to 10 for loaders and 8 for haul trucks. Both parameters are assumed to be without input and output layer.The total amount of tested structures for haul trucks was 477, and their results (on the plane of accuracy and loss function) are showed in The total number of tested structures for loader was 1585, almost 3 times higher than for haul trucks. However, the results obtained  were sigFor haul trucks: Input Layer, Convolutional, Dropout, Flatten, Dense, Dense, Dropout, Dense, Output Layer;For loaders: Input Layer, Convolutional, Convolutional, Convolutional, Convolutional, Dropout, Flatten, Dense, Dropout, Dense, Dense, Output Layer.The following two structures were obtained in the process of structure optimization:Structure for haul trucks scored the accuracy of 92.02448% and loss value of 0.232505, while the structure for loaders scored respectively 56.9949% and 0.953545.Similar to the task of structure optimization and based on its results, the possible parameter space for loaders was extended. Parameters used in this optimization for each machines type are presented in The total number of tested combinations for models hyperparameters was 2592 for haul trucks, and its results are shown in The total number of tested combinations for model hyperparameters was 10,368 for loaders, and its results are shown in Optimization of hyperparameters was the second and last step of model’s creation. During this process, the final structures presented in Exemplary detection performed by final models can be seen on To summarize, the process of hyperparameters optimization showed that the selection of initial networks parameter was optimal, and that the emphasis should be put on the network structure (in this particular task). Regardless of the amount, some improvements were achieved in this process. The network for haul trucks scored about 1.3% higher accuracy while the network for loaders improved by about 0.3%.k parts and performs k learning processes, during which each of the k-1 parts are used for training and the remaining part is used for validation. The one validation part is changed during each training process until none of the k parts are used for that purpose. In the modified version used for this research, each of the k learnings is repeated n times (with the same data division), to focus on the randomly initiated networks parameters such as weights and kernel filters. For both models, values of k = 10 and n = 10 were used, and the results from that procedure are shown in To establish the stability of models, the modified k-fold cross-validation algorithm was used. In its original form, this algorithm divides all data into The model for haul trucks showed high stability, efficiency and accuracy with mean values in the range of 93.0%–93.4%, with the highest score being 94.0239% and 92.5135% as the lowest score. Unfortunately, the model for loaders showed none of the predecessor’s quality, with mean values in the range of 57.75%–58.25%, with the highest accuracy being 59.4672% and lowest one being 57.4876%.To assess the overall results of the models, two methods of analysis were selected: confusion matrix and accuracy analysis relative to the machines measurements proportion in general sample size. The model for the haul truck was built to detect two states, and its confusion matrix is showed in The confusion matrix for loaders is presented in For the second analysis, all data were grouped in datasets based on unique machines (1 dataset—1 machine). Accuracy achieved for these datasets, along with their size in relation to all possessed data, is showed in Finally, to summarize the achieved results, we decided to perform a comparison between effectiveness of models created in this research and results declared by other authors  and optimization of structure hyperparameters.Constructed models were fueled using data from on-board monitoring system of vehicles (which is consistent between machine types). Both models used the same set of input features: instantaneous vehicles speed, fuel consumption, engine rotational speed and selected gear. A hydraulic pressure signal was used as a reference in training and validation, processed by different algorithms depending on machines type. The models were trained to perform a task of classification, and therefore the model for haul trucks is able to distinguish between two operations: unloading and other. The model for loaders supports one more cycle stage: unloading, loading, other.The data initially provided for this research consisted of 17,341 h of work for 8 haul trucks along with 16,812 h of work for 8 loaders. Since most of the hours did not contain a proper reference variable, and later because of large class imbalance, we decided to downsize the samples created to match the least occurring class. Therefore, the final data consisted of 2143 workhours for haul trucks and 850 workhours for loaders. These data were used for training, validation and testing.The final results were assessed by the k by n fold cross validation  algorithm. The model for haul tracks scored a mean accuracy of 93% and was proven stable in multiple assessment tasks. The score for this model along with the size of its sample is currently among the best described in related literature. Unfortunately, the model for loaders did not share the same results; it scored only 58% of accuracy. Despite poor global results for loaders, one machine scored 90% accuracy, which is promising. However, it should be stated that the task of work cycle estimation is much more difficult when it comes to loaders, and the attempt presented in the article was one of the first.The model for haul trucks acquired the highest accuracy and was trained and validated based on the largest (and possibly the most various) data sample.The model for loaders is the first described approach of work cycle estimation based on signals other than hydraulic oil pressure. It was trained and validated based on largest sample. Its accuracy is generally lower in comparison with the rest of approaches, except for the machine 8, for which it is higher than mean general accuracies.By comparing the results acquired by presented models with those found in the literature, some fundamental facts were established:Implementation of the haul trucks model will result in noticeable reduction of foremen workload. Assuming that the enterprise is large, each foreman needs to manually request information about machines’ work cycles from up to 20 operators, and then use it to complete the corresponding forms. Automation of this process can save as much as 30 min of work time. Therefore, assuming that large mines employ over a dozen foremen on each work shift, the savings can be measured as several hours per shift. In addition, cycle detection performed using the presented model can be used as data preprocessing stage for predictive maintenance algorithms. One of such approach is presented in , where cIt is also worth mentioning that, apart from the overall bad results, the model for loaders scored accuracy close to 90% for one machine while having a not small share of the sample. Investigating this outlier along with an attempt of transfer its success to other loaders is a future direction of research.