A text mining to nutritional counseling and instruction provided by registered dietitians

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This was done to gain insights into patient nutrition-related issues, concerns, and responses. That can be used to acquire precise health support information. Methods Text mining was used to conduct a quantitative analysis of nutritional consultation records. These records were documented in a Subjective-Objective-Assessment-Plan (SOAP) format, provided by eight dietitians, and involved 136 individuals of varying gender identities (male: 32, female: 101, gender non-response: 3). The consultations took place in a city pharmacy over the period from December 2020 to September 2022. Results The frequency analysis revealed that the Subjective-Objective (S/O) items were associated with behaviors such as 'eat', 'exercise', and 'drink', as well as terms associated with health indicators such as 'cholesterol', 'blood pressure', and hemoglobin A1c'. Additionally, S/O items also included words that correlate to specific laboratory values such as 'cholesterol', 'blood pressure', and hemoglobin A1c'. On the other hand, the Assessment-Plan (A/P) items identified words associated with behaviors, such as 'eat', 'diet', and 'exercise’ and with terms that are associated with laboratory values like, 'cholesterol', 'blood glucose', and 'blood pressure'. Furthermore, A/P items included words connected to nutrients, such as 'food', 'vegetables', and 'rehydration'. Through a co-occurrence network analysis, it was observed that certain associations emerged within the S/O terms are blood pressure, 'HDL - TG - LDL', 'quantity - BMI', and 'like - sweet - abstain'. While A/P associations included 'number - test', 'upper limit - potassium', 'oil - type', and 'yogurt - fat'. Conclusion The text mining method enabled visually analyzing keywords. It became comprehensively clear that nutritional consultations by dietitians often include assessing the lifestyle and related risk factors for chronic diseases such as hypertension, lipid disorders, and hyperglycemia as shown by the frequent occurrence of words for instance blood pressure, cholesterol, and blood glucose. It may help to determine priorities for action and may be the starting point for deciding which health issues should be prioritized in the information sharing for collaboration among inter-professions in the future. Text mining Community Nutritional consultations Dietitians Visually Figures Figure 1 Figure 2 Figure 3 Introduction Japan has a rapidly aging population, 28.7% of the population is 65 or older, with women making up the majority. In addition, Japan has a record 80,000 centenarians, and by 2036, those aged 65 and over will account for one-third of the population, further increasing the demand for medical and long-term care services [ 1 ]. Therefore, improvement and prevention of lifestyle-related diseases is a major issue for maintaining good health [ 2 ]. Obesity, diabetes, and hypertension are more serious disease risks. The proportion of people aged 65 years and older with a tendency toward undernutrition is 16.8% (2019) [3]. In a survey conducted in Japan, it was reported that 11.3% of those aged 65 years or older fall under the category of frail, a condition in which physiological reserve function declines in old age, vulnerability to stress increases, and susceptibility to infirmity is increased [4]. Registered dietitians in Japan have specialized knowledge and skills in nutrition and are responsible for providing nutritional support to injured and ill persons for their medical treatment, managing school lunches, and providing nutritional counseling necessary to improve nutrition. Registered dietitians differ from other dietitians in that they are qualified to provide nutritional guidance not only to healthy individuals but also to those who are ill. In recent years, the scope of activities of dietitians has been expanding to include, for example, nutrition and dietary education for hospitalized patients and nutrition support activities (NST) [5] with multiple professions, as well as activities in medical facilities and elderly-related care facilities [6] and nutrition support activities in disaster areas [7]. The registered dietitians in community pharmacies have a greater explanatory ability than pharmacists concerning nutritional and dietary management for patients. It may be important for pharmacists to improve cooperation with registered dietitians by providing more opportunities for dietetic consultation [8]. Incidentally, pharmacists working in pharmacies are expected to actively support the proactive maintenance and promotion of health in the community. Dietitians also provide a wide range of consultations related to maintaining and promoting health, providing more health support to the community. Collaboration between dietitians and pharmacists working in pharmacies may improve dietary habits [9]. In other words, multidisciplinary cooperation between pharmacists and dietitians is important to establish a higher quality medical contribution to the community. However, pharmacists in Japanese pharmacies are engaged in dispensing medicine [10] and their community activities are not widely known to the general public. On the other hand, the needs for medical care, elderly care and community health are complex and diverse in the current context of a rapidly ageing society with a declining birthrate and a super-aging population. Comprehensive and continuous efforts to strengthen cooperation between health, medical care, welfare and nursing care in the community and collaboration between relevant institutions and multiple professions are increasingly needed. Dietitians and registered dietitians are also expected to carry out effective and organic activities to improve community health, nutrition and dietary habits. Dietitians in pharmacies provide nutritional advice to patients, and in these nutritional consultations, they receive questions about daily life, medications, and pathological conditions. Pharmacists also play an important role in identifying food-drug interactions from a pharmacological perspective. Therefore, it is important to know what kind of questions dietitians receive about medications and pathological conditions to facilitate collaboration among multiple professions. Expectations are growing for ‘family pharmacies’ to support the health of residents. Registered dietitians are better able to explain diet and nutrition-related questions than pharmacists, and the placement of dietitians in pharmacies could improve patient services and contribute to better awareness of nutritionist nutrition management amongst pharmacists. In recent years, text mining has increasingly needed to be used for data mining on text data. The use of text mining is increasing in academic research, specifically as a method that can quantitatively visualize patient evaluations of psychiatrists' attitudes [11], newspaper editorials on the COVID-19 pandemic [12], and incident reports on falls [13], Text data is one type of unstructured data and has been considered less convenient for computer-based analysis because it requires preprocessing such as data conversion and processing. Even in questionnaire surveys, there is little attention paid to text data such as free responses and descriptions, and in many cases, specific examples are only taken up depending on the author. Japanese text is characterized as a mixture of kanji, hiragana, and katakana, and characters are written without any discontinuity. Therefore, when analyzing Japanese text data, it is a challenge for computer data processing to divide the text data into the smallest units of expression elements (morphemes). Morphological analysis is the process of breaking down text into elemental units corresponding to the morphemes and identifying the grammatical properties (part of speech, conjugation, etc.) of each element using a bilingual dictionary. KH Coder (KH Coder 3.0, Koichi Higuchi, Tokyo, Japan), a free software for text mining, can do text data preprocessing such as morphological analysis and multivariate analysis such as cluster analysis and correspondence analysis [14,15]. The KH coder not only counts the frequency of words and phrases in text data and produces a list of frequent words, but also enables co-occurrence network analysis and hierarchical cluster analysis. The aim of this study was therefore to review the content of nutritionist nutritional guidance in community pharmacies, not only from a nutritional perspective, but also from a pharmacological perspective, and to consider whether pharmacists have the necessary linkage of information important for the interaction between diet and medication. Thus, this study utilizes text mining to analyze the medical records using the Subjective-Objective-Assessment-Plan (SOAP) format of nutritional consultations with dietitians. We then verified the nutritional problems and concerns of the patients as well as the responses by the dietitians. In this way, it is believed that the activities of dietitians can be highlighted to improve nutritional support by pharmacists. Methods Survey Subjects We surveyed 136 records of nutritional consultations with dietitians at community pharmacies from December 2020 to September 2022. The consultations involved 136 participants, with 32 males, 101 females, three who did not answer the question. This study is a data collection of patients who independently received nutritional guidance during the survey period. Therefore, the sample size for the analysis was not predetermined. Participants' ages are categorized as: 20–69 years (62 individuals, with 13 males and 49 females), 70–99 years (71 individuals, with 17 males, 52 females, and two who did not provide their ages), and three individuals whose age was unresponsive (two males and one who was unresponsive) (Table 1). This study was analysed in two groups, with the suggestion that the situation of nutrition management in the elderly in Japan could be reflected by dividing the population into two age groups: the elderly and younger. A total of eight dietitians participated in the study (five; three working more than three years: three). Nutritional consultation records were recorded in Subjective-Objective-Assessment-Plan (SOAP) format (Table 2 ). The nutritionist in this study is full-time and provides nutritional guidance on a preventive basis as part of her daily work. We conducted this study under the Declaration of Helsinki and with the approval of Josai University Ethics Review Committee for Medical and Life Science Research on Human Subjects (hitoirin-2020-12A). The purpose of this study was explained to the nutritionist, and informed consent for participation in the study was obtained. Table 2 Contents of Nutritional Counseling Record Chart Era Male Female Gender Non-response Total (%) 20–69 years old 13 49 0 62 45.6 70–99 years old 17 52 2 71 52.2 No answer 2 0 1 3 2.2 Total 32 101 3 136 100 (Table 1) (Table 2 ). Analytical and statistical methods Nutrition consultation records were anonymized using IDs and consolidated. The text data of the nutrition counseling records were created as Excel files for each S/O and A/P item. The text data was decomposed into terms by morphological analysis. Before the morphological analysis, notational distortion and unification of synonyms and thesauruses (e.g., A1c and HbA1c → hemoglobin A1c) were performed. A correspondence figure was created (Fig. 1 ). The contents of the list of extracted words created in advance were checked. Words that were unexpectedly divided into sentences were modified by setting forced extracted words. The morphological analyzer adopted was MeCab. The co-occurrence network was drawn as an analysis of the extracted words obtained by morphological analysis. Co-occurrence networks make it possible to visualize quantitative data, and the more frequently a word appears, the larger the circle is, and the stronger the co-occurrence relationship, the thicker the lines connecting the circles are drawn. The reason for setting the number of clusters to eight is that the cluster structure is most interpretable when the Jaccard coefficients are set to 0.26 and 0.175 in the S/O and A/P analyses. (Fig. 1 ) Results 3-1. Frequent analysis The list of extracted words was obtained through a survey of the number of occurrences of words to determine the characteristics of the nutritional counseling content based on the frequency of occurrence of the words. The top twenty-five words in terms of frequency of occurrence in the S/O and A/P items are shown in Table 3. On the S/O items, the number of sentences used in the analysis was 1384. Their total number of words used in the analysis (total extracted words) was 4198, which included 1296 different words. On the S/O items, words related to behaviors such as "eat" (78 times), "exercise" (35 times), and "drink" (33 times), as well as words related to laboratory values such as "cholesterol" (57 times), "blood pressure" (56 times), and "hemoglobin A1c" (44 times) were identified. Namely, it was postulated that dietitians obtain information about their lifestyle and health status due to metabolic syndrome from their patients during nutrition counseling. To investigate the context in what kind of context "high" is used, the occurrence of the word before and after the word was tabulated using KH Coder's collocation statistics. The results showed the occurrence of "cholesterol" (17 times) and "blood pressure" (6 times). It was observed that nutritional counseling often addressed subjects related to lifestyle-related diseases, of which cholesterol levels and blood pressure are markers. Indeed, in clinical practice, dietitians recommend appropriate laboratory values to patients and provide associated dietary recommendations and nutritional support [16]. Therefore, pharmacists should share information with dietitians to support the management of nutritional concerns during medication counseling as an intervention to resolve the identified existing nutrition problem. On the A/P items, the number of sentences used in the analysis was 888. The total number of words used in the analysis (total extracted words) was 4665, which included 1219 different words. On the A/P items, words related to behavior such as "eat" (86 times), "diet" (86 times), and "exercise" (64 times) were used. In addition, words related to laboratory values such as "cholesterol" (49 times), "blood sugar" (28 times), and "blood pressure" (27 times), and words related to nutrients such as "food" (46 times), "vegetables" (31 times), and "rehydration" (25 times) were identified. In addition, collocation statistics were performed for "explanation" and the occurrence of "meal" (10 times), "next time" (7 times), and "food" (6 times) were confirmed before and after the word "explanation". One of the professional skills of dietitians is to implement the prevention of low nutrition and frailty in the elderly, as well as the maintenance and promotion of health and the prevention of the onset and severity of lifestyle-related diseases, from the perspective of avoiding nutrition-related deterioration of physical and metabolic functions [17]. Therefore, it was presumed that dietitians guide from the perspective of specific behaviors and food ingredients to assess and support the resolution of patients' nutritional problems. On the other hand, the Ministry of Health, Labour and Welfare outlines the functions of health support pharmacy pharmacists in the community comprehensive care system as involving nursing care, diet, and nutritional guidance [18]. Therefore, it is considered that pharmacists should collaborate with dietitians to suggest nutritional management information, such as the amount of food, type of food, method of intake, and the importance of meal timing. (Table 3) 3-2. Co-occurrence network A co-occurrence network was drawn to visualize word associations based on SOAP information and to understand patterns in the content of nutrition consultations. The Jaccard coefficient was applied as an index of the strength of the co-occurrence relationships. The Jaccard coefficient is the product set for a word combination divided by the sum set and has values between 0 and 1. A higher value of the Jaccard coefficient means a stronger association. In the S/O items, a co-occurrence relationship with a Jaccard coefficient of 0.26 or higher was identified. The clusters depicted were "breakfast - lunch - dinner", "like - sweet - abstain", "HDL - TG - LDL", "quantity -BMI," "by myself - cooking," "see doctor - other hospital," "decrease - appetite," and "medications - blood pressure" (Fig. 2). Co-occurring keywords were found in the same way as in the results of S/O items based on frequency analysis. In the Dietary Guidelines for Japan, to promote primary prevention of disease by reviewing lifestyle habits, one should adjust the rhythm of life through meal timing, interact and gather with family members over meals, and maintain an appropriate weight through moderate exercise and a well-balanced diet. The co-occurrence network highlighted keywords that lead to primary disease prevention during nutritional guidance, therefore, pharmacists are required not only to check medication adherence during medication consultations but also to try to promote primary prevention by interviewing the patient about lifestyle habits which includes nutrition and related risk factors. Co-occurrence relationships were drawn for A/P items with Jaccard coefficients of 0.175 or higher. The clusters depicted were "restriction-potassium," "needs-physical," "cause-up," "cooking-oil-type," "habit-improvement," "increase-quantity," "value-inspection" and "Yogurt-Fat" networks were shown (Fig. 3). The clusters drawn for "restriction - potassium," "type - cooking oil," and "yogurt - fat" indicated that information on the characteristics of the nutrients provided by the dietitian to the patients. The "need-physical" and "habit-improvement" clusters were also drawn, indicating that they provide behavioral change suggestions to the patients to solve nutritional problems. In particular, it was presumed that assessment and advice on fats and oils contributed to nutritional support. Finally, this study indicated that most counseling and advice were concerned on hypertension, dyslipidemia, hyperglycemia, and other chronic diseases. Therefore, a general issue of advice and instruction on nutrition and diet in community pharmacies is potentially problematic. For example, from the viewpoint of a population approach, there is a generalist approach and no clear target, and it is unclear " whom to and for what to do" as well as insufficient development of effective programs and tools to achieve the goal. In Japan, it is already hoped that the concept that thorough exercise habits and improved dietary habits are fundamental to the prevention of lifestyle-related diseases will be widely disseminated. Consequently, the "Exercise Guide 2006" for physical activity and exercise, the "Dietary Balance Guide" for nutrition and dietary habits, and the "Smoking Cessation Support Manual" for tobaｍcco cessation have already been prepared, and more efforts should be made to disseminate and utilize these guides. In other words, in addition to general nutritional advice, society as a whole need to develop an environment that supports individual efforts to improve lifestyle and change behavior from a dietary perspective. However, not all community pharmacies in Japan necessarily have a full-time dietitian on staff. We believe that nutrition education and pharmaceutical education through collaborative activities by pharmacists in community pharmacies will be a key point to help achieve these objectives. In the 21st century, the framework of pharmaceutical education at universities, not only in Japan but also in other countries, has shifted from basic research to clinical (practical) pharmacy. Namely, to respond to the needs of the public for prevention and treatment of unwellness, thus, nutrition education should be focused on as a cornerstone of pharmacotherapy by pharmacists with nutritional education. With regard to pharmacist-dietitian collaboration or the role of pharmacists in nutritional guidance, Masaki et al. report that collaboration between dietitians and pharmacists working in pharmacies may improve diet and glycaemic control in patients with type 2 diabetes [19]. In this study, a survey of nutritional consultations records by dietitians was conducted in collaboration with dietitians, pharmacists, and pharmacy departments in community pharmacies to examine the nutritional concerns and subjects faced by patients and the responses of the dietitians. In other words, we hope to grasp some aspects of nutrition education activities by dietitians in community pharmacies for the pharmacists to develop not only a network for drug education but also to assist in the prevention and promotion of health through proper nutrition in collaboration with the dietitians. For the elderly, for example, it is not only about improving individual factors such as exercise function and nutritional status. Rather, it is necessary to further develop human resources, such as dietitians, who should play a central role in health promotion strategies, and to collect and improve data that will form the basis for developing evidence-based strategies. This study visualized the co-occurrence network of registered dietitians' guidance to patients in a specific community pharmacy utilizing KH coder. The study was also limited to those patients who actively received nutritional guidance, which is also a limitation of the study. From the results of this study, it is perceived that future tasks should include expanding the study area, increasing the number of registered dietitians participating in the study, and planning the study not only for chronic diseases but also for a diverse range of ages and diseases. (Fig. 2) (Fig. 3) Conclusion The findings of the frequency analysis indicated that the nutritional consultations by the dietitian focused on the theme of lifestyle-related diseases that provided counseling and advice on specific nutrition action plan to solve nutritional problems. The results of co-occurrence network analysis revealed that the dietitians who interviewed the patients about their dietary habits and laboratory test values, then provided them with information about nutrients and suggestions for improving their habits as nutritional support. Visual analysis of keywords was made possible by using text mining techniques. The results comprehensively revealed that nutritional consultations by dietitians frequently included counseling and advice on chronic diseases such as hypertension, lipid disorders, and hyperglycemia. These outcomes highlight the significance of information sharing in fostering effective multidisciplinary collaboration. Declarations Ethics approval and consent to participate Ethical approval was granted by the Ethics Review Committee of Josai University (reference number 2020-12A). We have obtained written consent from dietitians whose comments were analyzed in this study. Consent for publication Not applicable. Availability of data and materials Not applicable Competing interests All authors declare that they have no competing interests Funding Not applicable Authors’ contributions NK contributed to collecting consent forms and data, performed digitalization of textual comments, performed the text-mining analysis, and drafted the manuscript. AY contributed to collecting data, performed digitalization of textual comments, performed the text-mining analysis, and drafted the manuscript. SO performed the translation of Japanese morphemes into English and helped to draft the manuscript. RFE, GL, and LC discussed the study results, reviewed the English, and assisted in the preparation of the manuscript. YI conceived the study, participated in its design and coordination, performed the text-mining analysis, and drafted the manuscript. All authors reviewed the manuscript. Acknowledgments We would like to express our deepest gratitude to the dietitians at Herb land pharmacy and the pharmacy staff for their cooperation in this study, while carefully preventing the spread of CODID-19. References Annual Report on the Aging Society. Cabinet Office, Government of Japan, 2021. Iijima K, Arai H, Akishita M, Endo T, Ogaswara K, et al. Toward the development of a vibrant, super-aged society: The future of medicine and society in Japan. Geriatr Gerontol Int. 2021; 21(8):601-613. doi: 10.1111/ggi.14201. Summary Results of the National Health and Nutrition Survey Japan, 2012. Ministry of Health, Labour and Welfare, Government of Japan. Shimada H, Makizako H, Doi T, Yoshida D, Tsutsumimoto K, et al. Combined Prevalence of Frailty and Mild Cognitive Impairment in a Population of Elderly Japanese People. J Am Med Dir Assoc 2013; 14 (7): 518-524. doi: 10.1016/j.jamda.2013.03.010. Tanaka A, Kawamura M, Yamada K, Morioka I. 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A pilot study of Pharmacist-Dietician Collaborative support and Advice (PDCA) for patients with type 2 diabetes in community pharmacy: A single-arm, pre-post study, 2022; 20(2): 2657. doi: 10.18549/PharmPract.2022.2.2657 Tables Table.1 Preparation for Morphological Analysis Era Male Female Gender Non-response Total (%) 20-69 years old 13 49 0 62 45.6 70-99 years old 17 52 2 71 52.2 No answer 2 0 1 3 2.2 Total 32 101 3 136 100 Table 2 Contents of Nutritional Counseling Record Chart 1. characteristics of the consultants 1.1 Name 1.2 Gender 1.3 Age 2. Contents of the description 2.1 Subjective (S) 2.2 Objective (O) 2.3 Assessment (A) 2.4 Plan (P) Table 3 Top 25 most frequently appearing words on S/O and A/P items S/O A/P extraction word number of occurrences extraction word number of occurrences eat 78 eat 86 Cholesterol 57 Meal 86 Blood pressure 56 much 72 Hemoglobin A1c 44 Exercise 64 qi 40 intake 50 High 40 Cholesterol 49 medicine 40 Food 46 mention (e.g., say) 39 Condition 43 blood sugar 36 mood 41 exercise 35 explanation 39 Weight 35 Vegetables 31 drink 33 decrease 29 Inspect 33 blood sugar 28 meal 33 blood pressure 27 before 31 body weight 26 LDL 26 next time 25 HDL 24 Hydration 25 Diabetes 22 insufficiency 24 taking 22 Salt content 23 BMI 21 intake 22 TG 21 recommendation 21 walk 21 salt reduction 21 morning 19 protein 20 hospital 19 consciousness 20 Vegetables 19 Variety 20 Additional Declarations No competing interests reported. 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University","correspondingAuthor":true,"prefix":"","firstName":"Yutaka","middleName":"","lastName":"Inoue","suffix":""}],"badges":[],"createdAt":"2024-05-15 09:55:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4424301/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4424301/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58752159,"identity":"56bb5cba-09b2-49ae-882a-ccee748f31a7","added_by":"auto","created_at":"2024-06-20 16:12:39","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78736,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Slide1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4424301/v1/d96d3147508a09da69bebedc.jpg"},{"id":58752161,"identity":"f12cfc74-d1bd-48f9-91ac-002c21a65538","added_by":"auto","created_at":"2024-06-20 16:12:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38266,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Slide2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4424301/v1/0226ea7337d110325966067e.jpg"},{"id":58752160,"identity":"f88862e3-abb2-4171-9bcd-3c895bc4f487","added_by":"auto","created_at":"2024-06-20 16:12:39","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38910,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Slide3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4424301/v1/e6605bd8122a4fedf3edfa01.jpg"},{"id":60577820,"identity":"0ff70628-3b86-43e3-9354-4d24b8511460","added_by":"auto","created_at":"2024-07-18 11:02:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":587123,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4424301/v1/fe04a27b-6abc-433d-bec0-56f64714ad7f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A text mining to nutritional counseling and instruction provided by registered dietitians","fulltext":[{"header":"Introduction","content":"\u003cp\u003eJapan has a rapidly aging population, 28.7% of the population is 65 or older, with women making up the majority. In addition, Japan has a record 80,000 centenarians, and by 2036, those aged 65 and over will account for one-third of the population, further increasing the demand for medical and long-term care services [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Therefore, improvement and prevention of lifestyle-related diseases is a major issue for maintaining good health [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Obesity, diabetes, and hypertension are more serious disease risks. The proportion of people aged 65 years and older with a tendency toward undernutrition is 16.8% (2019) [3]. In a survey conducted in Japan, it was reported that 11.3% of those aged 65 years or older fall under the category of frail, a condition in which physiological reserve function declines in old age, vulnerability to stress increases, and susceptibility to infirmity is increased [4].\u003c/p\u003e \u003cp\u003eRegistered dietitians in Japan have specialized knowledge and skills in nutrition and are responsible for providing nutritional support to injured and ill persons for their medical treatment, managing school lunches, and providing nutritional counseling necessary to improve nutrition. Registered dietitians differ from other dietitians in that they are qualified to provide nutritional guidance not only to healthy individuals but also to those who are ill. In recent years, the scope of activities of dietitians has been expanding to include, for example, nutrition and dietary education for hospitalized patients and nutrition support activities (NST) [5] with multiple professions, as well as activities in medical facilities and elderly-related care facilities [6] and nutrition support activities in disaster areas [7].\u003c/p\u003e \u003cp\u003eThe registered dietitians in community pharmacies have a greater explanatory ability than pharmacists concerning nutritional and dietary management for patients. It may be important for pharmacists to improve cooperation with registered dietitians by providing more opportunities for dietetic consultation [8]. Incidentally, pharmacists working in pharmacies are expected to actively support the proactive maintenance and promotion of health in the community. Dietitians also provide a wide range of consultations related to maintaining and promoting health, providing more health support to the community. Collaboration between dietitians and pharmacists working in pharmacies may improve dietary habits [9]. In other words, multidisciplinary cooperation between pharmacists and dietitians is important to establish a higher quality medical contribution to the community. However, pharmacists in Japanese pharmacies are engaged in dispensing medicine [10] and their community activities are not widely known to the general public. On the other hand, the needs for medical care, elderly care and community health are complex and diverse in the current context of a rapidly ageing society with a declining birthrate and a super-aging population. Comprehensive and continuous efforts to strengthen cooperation between health, medical care, welfare and nursing care in the community and collaboration between relevant institutions and multiple professions are increasingly needed. Dietitians and registered dietitians are also expected to carry out effective and organic activities to improve community health, nutrition and dietary habits. Dietitians in pharmacies provide nutritional advice to patients, and in these nutritional consultations, they receive questions about daily life, medications, and pathological conditions. Pharmacists also play an important role in identifying food-drug interactions from a pharmacological perspective. Therefore, it is important to know what kind of questions dietitians receive about medications and pathological conditions to facilitate collaboration among multiple professions. Expectations are growing for \u0026lsquo;family pharmacies\u0026rsquo; to support the health of residents. Registered dietitians are better able to explain diet and nutrition-related questions than pharmacists, and the placement of dietitians in pharmacies could improve patient services and contribute to better awareness of nutritionist nutrition management amongst pharmacists.\u003c/p\u003e \u003cp\u003eIn recent years, text mining has increasingly needed to be used for data mining on text data. The use of text mining is increasing in academic research, specifically as a method that can quantitatively visualize patient evaluations of psychiatrists' attitudes [11], newspaper editorials on the COVID-19 pandemic [12], and incident reports on falls [13], Text data is one type of unstructured data and has been considered less convenient for computer-based analysis because it requires preprocessing such as data conversion and processing. Even in questionnaire surveys, there is little attention paid to text data such as free responses and descriptions, and in many cases, specific examples are only taken up depending on the author. Japanese text is characterized as a mixture of kanji, hiragana, and katakana, and characters are written without any discontinuity. Therefore, when analyzing Japanese text data, it is a challenge for computer data processing to divide the text data into the smallest units of expression elements (morphemes). Morphological analysis is the process of breaking down text into elemental units corresponding to the morphemes and identifying the grammatical properties (part of speech, conjugation, etc.) of each element using a bilingual dictionary. KH Coder (KH Coder 3.0, Koichi Higuchi, Tokyo, Japan), a free software for text mining, can do text data preprocessing such as morphological analysis and multivariate analysis such as cluster analysis and correspondence analysis [14,15]. The KH coder not only counts the frequency of words and phrases in text data and produces a list of frequent words, but also enables co-occurrence network analysis and hierarchical cluster analysis. The aim of this study was therefore to review the content of nutritionist nutritional guidance in community pharmacies, not only from a nutritional perspective, but also from a pharmacological perspective, and to consider whether pharmacists have the necessary linkage of information important for the interaction between diet and medication. Thus, this study utilizes text mining to analyze the medical records using the Subjective-Objective-Assessment-Plan (SOAP) format of nutritional consultations with dietitians. We then verified the nutritional problems and concerns of the patients as well as the responses by the dietitians. In this way, it is believed that the activities of dietitians can be highlighted to improve nutritional support by pharmacists.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSurvey Subjects\u003c/h2\u003e \u003cp\u003eWe surveyed 136 records of nutritional consultations with dietitians at community pharmacies from December 2020 to September 2022. The consultations involved 136 participants, with 32 males, 101 females, three who did not answer the question. This study is a data collection of patients who independently received nutritional guidance during the survey period. Therefore, the sample size for the analysis was not predetermined. Participants' ages are categorized as: 20\u0026ndash;69 years (62 individuals, with 13 males and 49 females), 70\u0026ndash;99 years (71 individuals, with 17 males, 52 females, and two who did not provide their ages), and three individuals whose age was unresponsive (two males and one who was unresponsive) (Table\u0026nbsp;1). This study was analysed in two groups, with the suggestion that the situation of nutrition management in the elderly in Japan could be reflected by dividing the population into two age groups: the elderly and younger. A total of eight dietitians participated in the study (five; three working more than three years: three). Nutritional consultation records were recorded in Subjective-Objective-Assessment-Plan (SOAP) format (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The nutritionist in this study is full-time and provides nutritional guidance on a preventive basis as part of her daily work. We conducted this study under the Declaration of Helsinki and with the approval of Josai University Ethics Review Committee for Medical and Life Science Research on Human Subjects (hitoirin-2020-12A). The purpose of this study was explained to the nutritionist, and informed consent for participation in the study was obtained.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eContents of Nutritional Counseling Record Chart\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEra\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eNon-response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;69 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;99 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e(Table\u0026nbsp;1) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAnalytical and statistical methods\u003c/h2\u003e \u003cp\u003eNutrition consultation records were anonymized using IDs and consolidated. The text data of the nutrition counseling records were created as Excel files for each S/O and A/P item. The text data was decomposed into terms by morphological analysis. Before the morphological analysis, notational distortion and unification of synonyms and thesauruses (e.g., A1c and HbA1c \u0026rarr; hemoglobin A1c) were performed. A correspondence figure was created (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The contents of the list of extracted words created in advance were checked. Words that were unexpectedly divided into sentences were modified by setting forced extracted words. The morphological analyzer adopted was MeCab. The co-occurrence network was drawn as an analysis of the extracted words obtained by morphological analysis. Co-occurrence networks make it possible to visualize quantitative data, and the more frequently a word appears, the larger the circle is, and the stronger the co-occurrence relationship, the thicker the lines connecting the circles are drawn. The reason for setting the number of clusters to eight is that the cluster structure is most interpretable when the Jaccard coefficients are set to 0.26 and 0.175 in the S/O and A/P analyses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e3-1. Frequent analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe list of extracted words was obtained through a survey of the number of occurrences of words to determine the characteristics of the nutritional counseling content based on the frequency of occurrence of the words. The top twenty-five words in terms of frequency of occurrence in the S/O and A/P items are shown in Table 3. On the S/O items, the number of sentences used in the analysis was 1384. Their total number of words used in the analysis (total extracted words) was 4198, which included 1296 different words. On the S/O items, words related to behaviors such as \u0026quot;eat\u0026quot; (78 times), \u0026quot;exercise\u0026quot; (35 times), and \u0026quot;drink\u0026quot; (33 times), as well as words related to laboratory values such as \u0026quot;cholesterol\u0026quot; (57 times), \u0026quot;blood pressure\u0026quot; (56 times), and \u0026quot;hemoglobin A1c\u0026quot; (44 times) were identified. Namely, it was postulated that dietitians obtain information about their lifestyle and health status due to metabolic syndrome from their patients during nutrition counseling. To investigate the context in what kind of context \u0026quot;high\u0026quot; is used, the occurrence of the word before and after the word was tabulated using KH Coder\u0026apos;s collocation statistics.\u0026nbsp;The results showed the occurrence of \u0026quot;cholesterol\u0026quot; (17 times) and \u0026quot;blood pressure\u0026quot; (6 times).\u0026nbsp;It was observed that nutritional counseling often addressed subjects related to lifestyle-related diseases, of which cholesterol levels and blood pressure are markers. Indeed, in clinical practice, dietitians recommend appropriate laboratory values to patients and provide associated dietary recommendations and nutritional support [16]. Therefore, pharmacists should share information with dietitians to support the management of nutritional concerns during medication counseling as an intervention to resolve the identified existing nutrition problem.\u0026nbsp;On the A/P items, the number of sentences used in the analysis was 888. The total number of words used in the analysis (total extracted words) was 4665, which included 1219 different words. On the A/P items, words related to behavior such as \u0026quot;eat\u0026quot; (86 times), \u0026quot;diet\u0026quot; (86 times), and \u0026quot;exercise\u0026quot; (64 times) were used. In addition, words related to laboratory values such as \u0026quot;cholesterol\u0026quot; (49 times), \u0026quot;blood sugar\u0026quot; (28 times), and \u0026quot;blood pressure\u0026quot; (27 times), and words related to nutrients such as \u0026quot;food\u0026quot; (46 times), \u0026quot;vegetables\u0026quot; (31 times), and \u0026quot;rehydration\u0026quot; (25 times) were identified.\u0026nbsp;In addition, collocation statistics were performed for \u0026quot;explanation\u0026quot; and the occurrence of \u0026quot;meal\u0026quot; (10 times), \u0026quot;next time\u0026quot; (7 times), and \u0026quot;food\u0026quot; (6 times) were confirmed before and after the word \u0026quot;explanation\u0026quot;. One of the professional skills of dietitians is to implement the prevention of low nutrition and frailty in the elderly, as well as the maintenance and promotion of health and the prevention of the onset and severity of lifestyle-related diseases, from the perspective of avoiding nutrition-related deterioration of physical and metabolic functions\u0026nbsp;[17].\u0026nbsp;Therefore, it was presumed that dietitians guide from the perspective of specific behaviors and food ingredients to assess and support the resolution of patients\u0026apos; nutritional problems.\u0026nbsp;On the other hand, the Ministry of Health, Labour and Welfare outlines the functions of health support pharmacy pharmacists in the community comprehensive care system as involving nursing care, diet, and nutritional guidance [18]. Therefore, it is considered that pharmacists should collaborate with dietitians to suggest nutritional management information, such as the amount of food, type of food, method of intake, and the importance of meal timing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(Table 3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3-2. Co-occurrence network\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA co-occurrence network was drawn to visualize word associations based on SOAP information and to understand patterns in the content of nutrition consultations. The Jaccard coefficient was applied as an index of the strength of the co-occurrence relationships. The Jaccard coefficient is the product set for a word combination divided by the sum set and has values between 0 and 1. A higher value of the Jaccard coefficient means a stronger association. In the S/O items, a co-occurrence relationship with a Jaccard coefficient of 0.26 or higher was identified. The clusters depicted were \u0026quot;breakfast - lunch - dinner\u0026quot;, \u0026quot;like - sweet - abstain\u0026quot;, \u0026quot;HDL - TG - LDL\u0026quot;, \u0026quot;quantity -BMI,\u0026quot; \u0026quot;by myself - cooking,\u0026quot; \u0026quot;see doctor - other hospital,\u0026quot; \u0026quot;decrease - appetite,\u0026quot; and \u0026quot;medications - blood pressure\u0026quot; (Fig. 2). Co-occurring keywords were found in the same way as in the results of S/O items based on frequency analysis. In the Dietary Guidelines for Japan, to promote primary prevention of disease by reviewing lifestyle habits, one should adjust the rhythm of life through meal timing, interact and gather with family members over meals, and maintain an appropriate weight through moderate exercise and a well-balanced diet. The co-occurrence network highlighted keywords that lead to primary disease prevention during nutritional guidance, therefore, pharmacists are required not only to check medication adherence during medication consultations but also to try to promote primary prevention by interviewing the patient about lifestyle habits which includes nutrition and related risk factors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCo-occurrence relationships were drawn for A/P items with Jaccard coefficients of 0.175 or higher. The clusters depicted were \u0026quot;restriction-potassium,\u0026quot; \u0026quot;needs-physical,\u0026quot; \u0026quot;cause-up,\u0026quot; \u0026quot;cooking-oil-type,\u0026quot; \u0026quot;habit-improvement,\u0026quot; \u0026quot;increase-quantity,\u0026quot; \u0026quot;value-inspection\u0026quot; and \u0026quot;Yogurt-Fat\u0026quot; networks were shown (Fig. 3). The clusters drawn for \u0026quot;restriction - potassium,\u0026quot; \u0026quot;type - cooking oil,\u0026quot; and \u0026quot;yogurt - fat\u0026quot; indicated that information on the characteristics of the nutrients provided by the dietitian to the patients. The \u0026quot;need-physical\u0026quot; and \u0026quot;habit-improvement\u0026quot; clusters were also drawn, indicating that they provide behavioral change suggestions to the patients to solve nutritional problems. In particular, it was presumed that assessment and advice on fats and oils contributed to nutritional support.\u003c/p\u003e\n\u003cp\u003eFinally, this study indicated that most counseling and advice were concerned on hypertension, dyslipidemia, hyperglycemia, and other chronic diseases. Therefore, a general issue of advice and instruction on nutrition and diet in community pharmacies is potentially problematic. For example, from the viewpoint of a population approach, there is a generalist approach and no clear target, and it is unclear \u0026quot; whom to and for what to do\u0026quot; as well as insufficient development of effective programs and tools to achieve the goal.\u0026nbsp;In Japan, it is already hoped that the concept that thorough exercise habits and improved dietary habits are fundamental to the prevention of lifestyle-related diseases will be widely disseminated. Consequently, the \u0026quot;Exercise Guide 2006\u0026quot; for physical activity and exercise, the \u0026quot;Dietary Balance Guide\u0026quot; for nutrition and dietary habits, and the \u0026quot;Smoking Cessation Support Manual\u0026quot; for tobaｍcco cessation have already been prepared, and more efforts should be made to disseminate and utilize these guides. In other words, in addition to general nutritional advice, society as a whole need to develop an environment that supports individual efforts to improve lifestyle and change behavior from a dietary perspective. However, not all community pharmacies in Japan necessarily have a full-time dietitian on staff.\u0026nbsp;We believe that nutrition education and pharmaceutical education through collaborative activities by pharmacists in community pharmacies will be a key point to help achieve these objectives. In the 21st century, the framework of pharmaceutical education at universities, not only in Japan but also in other countries, has shifted from basic research to clinical (practical) pharmacy. Namely, to respond to the needs of the public for prevention and treatment of unwellness, thus, nutrition education should be focused on as a cornerstone of pharmacotherapy by pharmacists with nutritional education. With regard to pharmacist-dietitian collaboration or the role of pharmacists in nutritional guidance, Masaki et al. report that collaboration between dietitians and pharmacists working in pharmacies may improve diet and glycaemic control in patients with type 2 diabetes\u0026nbsp;[19]. In this study, a survey of nutritional consultations records by dietitians was conducted in collaboration with dietitians, pharmacists, and pharmacy departments in community pharmacies to examine the nutritional concerns and subjects faced by patients and the responses of the dietitians. In other words, we hope to grasp some aspects of nutrition education activities by dietitians in community pharmacies for the pharmacists to develop not only a network for drug education but also to assist in the prevention and promotion of health through proper nutrition in collaboration with the dietitians. For the elderly, for example, it is not only about improving individual factors such as exercise function and nutritional status. Rather, it is necessary to further develop human resources, such as dietitians, who should play a central role in health promotion strategies, and to collect and improve data that will form the basis for developing evidence-based strategies. This study visualized the\u0026nbsp;co-occurrence network\u0026nbsp;of registered dietitians\u0026apos; guidance to patients in a specific community pharmacy utilizing KH coder. The study was also limited to those patients who actively received nutritional guidance, which is also a limitation of the study.\u0026nbsp;From the results of this study, it is perceived that future tasks should include expanding the study area, increasing the number of registered dietitians participating in the study, and planning the study not only for chronic diseases but also for a diverse range of ages and diseases.\u003c/p\u003e\n\u003cp\u003e(Fig. 2) (Fig. 3)\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of the frequency analysis indicated that the nutritional consultations by the dietitian focused on the theme of lifestyle-related diseases that provided counseling and advice on specific nutrition action plan to solve nutritional problems. The results of co-occurrence network analysis revealed that the dietitians who interviewed the patients about their dietary habits and laboratory test values, then provided them with information about nutrients and suggestions for improving their habits as nutritional support. Visual analysis of keywords was made possible by using text mining techniques. The results comprehensively revealed that nutritional consultations by dietitians frequently included counseling and advice on chronic diseases such as hypertension, lipid disorders, and hyperglycemia. These outcomes highlight the significance of information sharing in fostering effective multidisciplinary collaboration.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was granted by the Ethics Review Committee of Josai University (reference number 2020-12A). We have obtained written consent from dietitians whose comments were analyzed in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNK contributed to collecting consent forms and data, performed digitalization of textual comments, performed the text-mining analysis, and drafted the manuscript. AY contributed to collecting data, performed digitalization of textual comments, performed the text-mining analysis, and drafted the manuscript. SO performed the translation of Japanese morphemes into English and helped to draft the manuscript. RFE, GL, and LC discussed the study results, reviewed the English, and assisted in the preparation of the manuscript. YI conceived the study, participated in its design and coordination, performed the text-mining analysis, and drafted the manuscript.\u0026nbsp;All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our deepest gratitude to the dietitians at Herb land pharmacy and the pharmacy staff for their cooperation in this study, while carefully preventing the spread of CODID-19.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnnual Report on the Aging Society. Cabinet Office, Government of Japan, 2021.\u003c/li\u003e\n\u003cli\u003eIijima K, Arai H, Akishita M, Endo T, Ogaswara K, et al. Toward the development of a vibrant, super-aged society: The future of medicine and society in Japan. Geriatr Gerontol Int. 2021; 21(8):601-613. doi: 10.1111/ggi.14201.\u003c/li\u003e\n\u003cli\u003eSummary Results of the National Health and Nutrition Survey Japan, 2012. Ministry of Health, Labour and Welfare, Government of Japan.\u003c/li\u003e\n\u003cli\u003eShimada H, Makizako H, Doi T, Yoshida D, Tsutsumimoto K, et al. Combined Prevalence of Frailty and Mild Cognitive Impairment in a Population of Elderly Japanese People. J Am Med Dir Assoc 2013; 14 (7): 518-524. doi: 10.1016/j.jamda.2013.03.010.\u003c/li\u003e\n\u003cli\u003eTanaka A, Kawamura M, Yamada K, Morioka I. Association between teaching and support skills and subjective effectiveness of nutritional guidance of registered dietitians at hospitals in a Japanese prefecture. Environ Health Prev Med; 2014; 19: 72\u0026ndash;80. doi: 10.1007/s12199-013-0358-2\u003c/li\u003e\n\u003cli\u003eBeck A, Christensen A G, Hansen B, Damsbo-Svendsen S, M\u0026oslash;ller S T K, et al. Study protocol: cost-effectiveness of multidisciplinary nutritional support for undernutrition in older adults in nursing home and home-care: cluster randomized controlled trial. Nutrition Journal 2014; 13: 86. doi: 10.1186/1475-2891-13-86.\u003c/li\u003e\n\u003cli\u003eTakeda T, Sudo N, Tsuboyama-Kasaoka N, Sato, Shibamura Y, et al. Meal plans for meeting the reference values using food items available in shelters. BMC Nutrition; 2023; 9: 73. doi: 10.1186/s40795-023-00726-9.\u003c/li\u003e\n\u003cli\u003eKizaki H, Ota T, Mashima S, Nakamura Y, Kiyokawa S, et al. Questionnaire survey investigation of the present status of dietetic consultation at community pharmacies from the perspectives registered dietitians and pharmacists. BMC Health Services Research 2021; 21: doi: org/10.1186/s12913-021-06959-3\u003c/li\u003e\n\u003cli\u003eShoji M, Sakane N, Ito N, Sunayama K, Onda M. A Pilot Study of Pharmacist-dietician Collaborative Support and Advice (PDCA) for Patients with Type 2 Diabetes in Community Pharmacy: A Single-arm, Pre-post Study. Pharmacy Practice, 2022; 20(2): 1-5. doi: org/10.18549/PharmPract.2022.2.2657.\u003c/li\u003e\n\u003cli\u003eHorio F, Ikeda T, Kouzaki Y, Hirahara T, Masa K, et al. Questionnaire survey on pharmacists\u0026rsquo; roles among non‑and health care professionals in medium‑sized cities in Japan. Scientifc Reports. 2023; 4:13(1): 5458. doi: 10.1038/s41598-023-32777-0.\u003c/li\u003e\n\u003cli\u003eNatsukari I, Higuchi M, Tsujimoto T. How do patients and families evaluate attitude of psychiatrists in Japan?: quantitative content analysis of open-ended items of patient responses from a large-scale questionnaire survey. BMC Psychiatry. 2023; 14; 23(1):253. doi: 10.1186/s12888-023-04732-w.\u003c/li\u003e\n\u003cli\u003eMaeda W, Hirakawa Y, Muraya T, Miura H. Text mining analysis of newspaper editorials concerning the COVID-19 pandemic from a healthcare perspective. Journal of Rural Medicine 2022; 17(4): 279\u0026ndash;282 doi: 10.2185/jrm.2021-063.\u003c/li\u003e\n\u003cli\u003eTakase M. Falls as the result of interplay between nurses, patient and the environment: Using text-mining to uncover how and why falls happen. International Journal of Nursing Sciences. 2023; 10(1): 30-37. doi: org/10.1016/j.ijnss.2022.12.003.\u003c/li\u003e\n\u003cli\u003eHiguchi K. A two-step approach to quantitative content analysis: KH coder tutorial using Anne of Green Gables (Part I). Ritsumeikan Soc Sci Rev. 2016; 52: 77\u0026ndash;91. doi: org/10.34382/00003706.\u003c/li\u003e\n\u003cli\u003eHiguchi K. A two-step approach to quantitative content analysis: KH coder tutorial using Anne of Green Gables (Part Ⅱ). Ritsumeikan Soc Sci Rev 2017; 53: 137\u0026ndash;147. doi: org/10.34382/00003731.\u003c/li\u003e\n\u003cli\u003eOda K, Anno T, Ogawa N, Kimura Y, Kawasaki F, et al. Impact of nutritional guidance on various clinical parameters in patients with moderate obesity: A retrospective study. Frontiers in Nutrition. 2023; 10: 3389. doi: org/10.3389/fnut.2023.1138685.\u003c/li\u003e\n\u003cli\u003eOhwada H, Nakayama T, Sugiyama M, Fujitani A, Shimanuki N, et al. Nutritional Status and Nutritional Management Implementation for Residents with Disabilities in Welfare Facilities: A Nationwide Survey in Japan. J Nutri Sci Vitaminol. 2022;68(5):390-398. doi: 10.3177/jnsv.68.390.\u003c/li\u003e\n\u003cli\u003eHirota N, Okamura N. Patients' Attitudes, Awareness, and Opinions About Community Pharmacies in Japan: Next Steps for the Health Support Pharmacy System. Integr Pharm Res Pract. 2020; 12:9: 243-256. doi: 10.2147/IPRP.S275288. eCollection 2020.\u003c/li\u003e\n\u003cli\u003eShoji M, Sakane N, Ito N, Sunayama K, Onda M. A pilot study of Pharmacist-Dietician Collaborative support and Advice (PDCA) for patients with type 2 diabetes in community pharmacy: A single-arm, pre-post study, 2022; 20(2): 2657. doi: 10.18549/PharmPract.2022.2.2657\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable.1 Preparation for Morphological Analysis\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"522\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.689059500959694%\"\u003e\n \u003cp\u003eEra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.516314779270633%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003eNon-response\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\" valign=\"top\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.689059500959694%\" valign=\"top\"\u003e\n \u003cp\u003e20-69 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.516314779270633%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\" valign=\"top\"\u003e\n \u003cp\u003e45.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.689059500959694%\" valign=\"top\"\u003e\n \u003cp\u003e70-99 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.516314779270633%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\" valign=\"top\"\u003e\n \u003cp\u003e52.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.689059500959694%\" valign=\"top\"\u003e\n \u003cp\u003eNo answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.516314779270633%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\" valign=\"top\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.689059500959694%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.516314779270633%\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.698656429942417%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2 Contents of Nutritional Counseling Record Chart\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"275\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e1. characteristics of the consultants\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e 1.1 Name\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e 1.2 Gender\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e 1.3 Age\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e2. Contents of the description\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e 2.1 Subjective (S)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e 2.2 Objective (O)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e 2.3 Assessment (A)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e 2.4 Plan (P)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3 Top 25 most frequently appearing words on S/O and A/P items\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"510\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" colspan=\"2\"\u003e\n \u003cp\u003eS/O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" colspan=\"2\"\u003e\n \u003cp\u003eA/P\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\"\u003e\n \u003cp\u003eextraction word\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003enumber of occurrences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\"\u003e\n \u003cp\u003eextraction word\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003enumber of occurrences\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eeat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eeat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eCholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eMeal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eBlood pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003emuch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eHemoglobin A1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eExercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eqi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eintake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eCholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003emedicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eFood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003emention (e.g., say)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eCondition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eblood sugar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003emood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eexercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n 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valign=\"top\"\u003e\n \u003cp\u003edecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eInspect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eblood sugar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003emeal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eblood pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003ebefore\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003ebody weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eLDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003enext time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eHDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eHydration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003einsufficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003etaking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eSalt content\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eintake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003erecommendation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003ewalk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003esalt reduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003emorning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eprotein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003ehospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003econsciousness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.07045009784736%\" valign=\"top\"\u003e\n \u003cp\u003eVegetables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.027397260273972%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.113502935420744%\" valign=\"top\"\u003e\n \u003cp\u003eVariety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.788649706457925%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Text mining, Community, Nutritional consultations, Dietitians, Visually","lastPublishedDoi":"10.21203/rs.3.rs-4424301/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4424301/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThe study aimed to conduct a comprehensive analysis of medical records, that specifically focused on nutritional consultations with dietitians within community pharmacies. This was done to gain insights into patient nutrition-related issues, concerns, and responses. That can be used to acquire precise health support information.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eText mining was used to conduct a quantitative analysis of nutritional consultation records. These records were documented in a Subjective-Objective-Assessment-Plan (SOAP) format, provided by eight dietitians, and involved 136 individuals of varying gender identities (male: 32, female: 101, gender non-response: 3). The consultations took place in a city pharmacy over the period from December 2020 to September 2022.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe frequency analysis revealed that the Subjective-Objective (S/O) items were associated with behaviors such as 'eat', 'exercise', and 'drink', as well as terms associated with health indicators such as 'cholesterol', 'blood pressure', and hemoglobin A1c'. Additionally, S/O items also included words that correlate to specific laboratory values such as 'cholesterol', 'blood pressure', and hemoglobin A1c'. On the other hand, the Assessment-Plan (A/P) items identified words associated with behaviors, such as 'eat', 'diet', and 'exercise\u0026rsquo; and with terms that are associated with laboratory values like, 'cholesterol', 'blood glucose', and 'blood pressure'. Furthermore, A/P items included words connected to nutrients, such as 'food', 'vegetables', and 'rehydration'. Through a co-occurrence network analysis, it was observed that certain associations emerged within the S/O terms are blood pressure, 'HDL - TG - LDL', 'quantity - BMI', and 'like - sweet - abstain'. While A/P associations included 'number - test', 'upper limit - potassium', 'oil - type', and 'yogurt - fat'.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe text mining method enabled visually analyzing keywords. It became comprehensively clear that nutritional consultations by dietitians often include assessing the lifestyle and related risk factors for chronic diseases such as hypertension, lipid disorders, and hyperglycemia as shown by the frequent occurrence of words for instance blood pressure, cholesterol, and blood glucose. It may help to determine priorities for action and may be the starting point for deciding which health issues should be prioritized in the information sharing for collaboration among inter-professions in the future.\u003c/p\u003e","manuscriptTitle":"A text mining to nutritional counseling and instruction provided by registered dietitians","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-20 16:12:32","doi":"10.21203/rs.3.rs-4424301/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67277aa3-33cc-4921-8476-3a2d99c0f218","owner":[],"postedDate":"June 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-31T01:45:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-20 16:12:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4424301","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4424301","identity":"rs-4424301","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}