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Rooming-in Care
Rooming-in Care
Rooming-in Care refers to the practice of keeping newborn infants with their mothers in the same room during hospitalization, rather than separating them into a nursery.
This approach promotes early mother-infant bonding, facilitates breastfeeding, and allows for continuous care and observation of the newborn.
Rooming-in Care has been shown to have numerous benefits, including improved breastfeeding rates, reduced risk of infection, and enhanced parent-child interaction.
It is a recommended practice in many healthcare settings to support the physical and emotional well-being of both the mother and the newborn during the postpartum period.
This approach promotes early mother-infant bonding, facilitates breastfeeding, and allows for continuous care and observation of the newborn.
Rooming-in Care has been shown to have numerous benefits, including improved breastfeeding rates, reduced risk of infection, and enhanced parent-child interaction.
It is a recommended practice in many healthcare settings to support the physical and emotional well-being of both the mother and the newborn during the postpartum period.
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We used data from the Ontario CCIS for this study. The CCIS is a web-based data application that uses a combination of methods to capture data. Demographic data can be auto-populated directly from the hospital electronic admission, discharge, and transfer system, but most of the data are manually entered by clerical and clinical staff as appropriate. Data elements used in this study, a subset of those captured in CCIS, are shown in Electronic Supplementary Material (ESM), eTable 1. All ICUs in Ontario are required to enter data into the CCIS for all admissions.
Data were obtained for all level-3 ICU admissions between July 1 2015 and December 31 2016. Level 3 ICUs are defined as those providing life support and mechanical ventilation for more than 48 hours. Critical Care Services Ontario has organized the ICUs into groups based on ICU subtype (Table1 ). The eligibility criteria, conditions, definitions, and measurements in this validation study were identical to those used in the original development study.
The validation data set was first subject to administrative cleaning. We excluded admissions to pediatric and labour and delivery level-3 ICUs. Also excluded were records where patient age was reported as < 18 yr or > 115 yr, length of ICU stay was reported as 0 days (entry errors), or where duplicate MODS and/or NEMS entries were reported. For duplicate records, the record with the later time stamp was selected for linkage with the admission and discharge data. Finally, any records with missing predictor data were omitted from the analyses.
Complete case analyses were used to assess model performance. Records with missing data represented approximately 5% of all cases and exclusion of these cases was not considered a threat to the validity of the results.21 (link) The outcome of interest was ICU mortality. Predictor variables, available within the first 24 hr of critical care admission, were defined as follows: 1) age group (18–39, 40–79, ≥ 80 yr); 2) sex (M or F); 3) NEMS group (0–22, 23–29, ≥ 30); 4) MODS group (0, 1–4, 5–8, 9–12, ≥ 13); 5) admission source (operating room/postanesthesia care unit, emergency department, unit/ward, other hospital and other); 6) admitting diagnosis (cardiovascular/cardiac/vascular, respiratory, gastrointestinal, neurologic, trauma, other); and 7) readmission to critical care during the same hospital stay.12 (link)
Since we chose to restrict our analyses to variables contained within the CCIS data set, we modified our previously published model 12 (link) by excluding the Charlson Comorbidity Index. eTable 1 (available as ESM) is provided as supplemental digital content and shows the equation for Logit [ICU Mortality].
Data were obtained for all level-3 ICU admissions between July 1 2015 and December 31 2016. Level 3 ICUs are defined as those providing life support and mechanical ventilation for more than 48 hours. Critical Care Services Ontario has organized the ICUs into groups based on ICU subtype (Table
CCIS level-3 ICU subtype groups and number of critical care units
| Criteria | # Critical care units |
|---|---|
| Teaching hospitals (medical surgical ICU) | 17 |
| Community hospitals (medical surgical ICU) with ventilator patient day rate above the mean rate* | 28 |
| Community hospitals (medical surgical ICU) with ventilator patient day rate equal to or less than the mean rate* | 23 |
| Cardiac/cardiovascular unit | 10 |
| Coronary care units† | 10 |
| Burn units | 2 |
*Ventilator patient day rate = (ventilator days/patient care days) * 100 based on fiscal year 2016–2017; mean rate = 43.61%
†Coronary care units that provide invasive ventilation for longer than 48 hr
CCIS = Critical Care Information System; ICU = intensive care unit
The validation data set was first subject to administrative cleaning. We excluded admissions to pediatric and labour and delivery level-3 ICUs. Also excluded were records where patient age was reported as < 18 yr or > 115 yr, length of ICU stay was reported as 0 days (entry errors), or where duplicate MODS and/or NEMS entries were reported. For duplicate records, the record with the later time stamp was selected for linkage with the admission and discharge data. Finally, any records with missing predictor data were omitted from the analyses.
Complete case analyses were used to assess model performance. Records with missing data represented approximately 5% of all cases and exclusion of these cases was not considered a threat to the validity of the results.21 (link) The outcome of interest was ICU mortality. Predictor variables, available within the first 24 hr of critical care admission, were defined as follows: 1) age group (18–39, 40–79, ≥ 80 yr); 2) sex (M or F); 3) NEMS group (0–22, 23–29, ≥ 30); 4) MODS group (0, 1–4, 5–8, 9–12, ≥ 13); 5) admission source (operating room/postanesthesia care unit, emergency department, unit/ward, other hospital and other); 6) admitting diagnosis (cardiovascular/cardiac/vascular, respiratory, gastrointestinal, neurologic, trauma, other); and 7) readmission to critical care during the same hospital stay.12 (link)
Since we chose to restrict our analyses to variables contained within the CCIS data set, we modified our previously published model 12 (link) by excluding the Charlson Comorbidity Index. eTable 1 (available as ESM) is provided as supplemental digital content and shows the equation for Logit [ICU Mortality].
Age Groups
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Clergy
Critical Care
Day Care, Medical
Diagnosis
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Gibbons
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Rooming-in Care
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The TraumaRegister DGU® of the German Trauma Society (Deutsche Gesellschaft für Unfallchirurgie, DGU) was founded in 1993. The aim of this multi-centre database is a pseudonymised and standardised documentation of severely injured patients.
Data are collected prospectively in four consecutive time phases from the site of the accident until discharge from hospital: A) Pre-hospital phase, B) Emergency room and initial surgery, C) Intensive care unit and D) Discharge. The documentation includes detailed information on demographics, injury pattern, comorbidities, pre- and in-hospital management, course on intensive care unit, relevant laboratory findings including data on transfusion and outcome of each individual. The inclusion criterion is admission to hospital via emergency room with subsequent ICU/ICM care or reach the hospital with vital signs and die before admission to ICU.
The infrastructure for documentation, data management, and data analysis is provided by AUC - Academy for Trauma Surgery (AUC - Akademie der Unfallchirurgie GmbH), a company affiliated to the German Trauma Society. The scientific leadership is provided by the Committee on Emergency Medicine, Intensive Care and Trauma Management (Section NIS) of the German Trauma Society. The participating hospitals submit their pseudonymised data into a central database via a web-based application. Scientific data analysis is approved according to a peer review procedure established by Section NIS. The participating hospitals are primarily located in Germany (90%), but a rising number of hospitals of other countries contribute data as well (at the moment from Austria, Belgium, China, Finland, Luxembourg, Slovenia, Switzerland, The Netherlands, and the United Arab Emirates). Currently, approximately 35,000 cases from almost 700 hospitals are entered into the database per year.
Participation in TraumaRegister DGU® is voluntary. For hospitals associated with TraumaNetzwerk DGU® however, the entry of at least a basic data set is obligatory for reasons of quality assurance.
In the present study, we analyzed the registry data from 2002 to 2015. The inclusion criteria were as follows: adult trauma patients with an age of 16 years or above and treated in a European trauma centre with a severe spinal cord injury (AIS 3). In order to avoid double-counting, we excluded patients transferred out within 48 h, as they appear as a transfer in the receiving hospitals.
The definition of cervical spinal cord injury is based on the Abbreviated Injury Scale, version 2005(updated 2008), which is used in the TraumaRegister DGU® (Table1 ). An AIS 6 classifies patients with a cord contusion or laceration at C3 or above with a complete cord syndrome.
Data are collected prospectively in four consecutive time phases from the site of the accident until discharge from hospital: A) Pre-hospital phase, B) Emergency room and initial surgery, C) Intensive care unit and D) Discharge. The documentation includes detailed information on demographics, injury pattern, comorbidities, pre- and in-hospital management, course on intensive care unit, relevant laboratory findings including data on transfusion and outcome of each individual. The inclusion criterion is admission to hospital via emergency room with subsequent ICU/ICM care or reach the hospital with vital signs and die before admission to ICU.
The infrastructure for documentation, data management, and data analysis is provided by AUC - Academy for Trauma Surgery (AUC - Akademie der Unfallchirurgie GmbH), a company affiliated to the German Trauma Society. The scientific leadership is provided by the Committee on Emergency Medicine, Intensive Care and Trauma Management (Section NIS) of the German Trauma Society. The participating hospitals submit their pseudonymised data into a central database via a web-based application. Scientific data analysis is approved according to a peer review procedure established by Section NIS. The participating hospitals are primarily located in Germany (90%), but a rising number of hospitals of other countries contribute data as well (at the moment from Austria, Belgium, China, Finland, Luxembourg, Slovenia, Switzerland, The Netherlands, and the United Arab Emirates). Currently, approximately 35,000 cases from almost 700 hospitals are entered into the database per year.
Participation in TraumaRegister DGU® is voluntary. For hospitals associated with TraumaNetzwerk DGU® however, the entry of at least a basic data set is obligatory for reasons of quality assurance.
In the present study, we analyzed the registry data from 2002 to 2015. The inclusion criteria were as follows: adult trauma patients with an age of 16 years or above and treated in a European trauma centre with a severe spinal cord injury (AIS 3). In order to avoid double-counting, we excluded patients transferred out within 48 h, as they appear as a transfer in the receiving hospitals.
The definition of cervical spinal cord injury is based on the Abbreviated Injury Scale, version 2005(updated 2008), which is used in the TraumaRegister DGU® (Table
Abbreviated Injury Scale of cSCI 2005(updated 2008) [12 ] and proportional distribution of injury severity for cSCI in TR-DGU out of 102,553 patients
| AIS score | Description of injury | n | % |
|---|---|---|---|
| Transient neurological signs (paresthesia) | 2245 | 2.2 | |
| Contusion with incomplete cord syndrome | 1001 | 1.0 | |
Contusion with complete cord syndrome C4 or below Laceration with complete cord syndrome C4 or below | 1866 | 1.8 | |
Contusion with complete cord syndrome C3 or above Laceration with complete cord syndrome C3 or above | 612 | 0.6 |
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Accidents
Adult
Blood Transfusion
Cone-Rod Dystrophy 2
Contusions
Emergencies
Europeans
Hospital Administration
Injuries
Intensive Care
Laceration
Neck
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Rooming-in Care
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We conducted formative qualitative research prior to the initiation of the TEKO trial from April to June 2014. The study utilized a cross-sectional design and a total of 56 people participated in one individual, in-depth interview. The sample included 28 PLHIV receiving care in public clinics and 28 of their clinical care providers. As indicated by qualitative research norms, we sought between 20 and 30 participants per population group (e.g. patients and providers) [11 , 12 (link)]. The 14 clinics included were all general primary health care clinics, which also offered HIV services and were selected to participate in the TEKO trial, which at that point had not yet begun.
Eligibility for the qualitative study included patients who were 18 years of age or more, living with HIV for at least 6 months, and able to converse in English. One female and one male patient participant were interviewed in each participating clinic. These patients were selected by providers based on their knowledge of patients who might be willing and able to narrate their experience with their clinical care. Two clinical care providers that provided TB care were interviewed in each participating clinic. We sought different types of providers involved in providing TB screening and care to patients (e.g. nurses, counselors, and community health workers).
A semi-structured guide was used to facilitate the interviews using open-ended questions Additional file1 . The interviewer freely utilized probes and follow-up questions to create additional depth. Interviews focused on participant’s views and experiences with TB including details of the screening, diagnosis, and treatment process from patient and provider perspectives. All participants were asked their thoughts about the use of the QGIT test to screen blood drawn at the same time as CD4 blood draws for latent TB. Interviews continued until saturation, or redundancy in findings per key themes, was reached, which was determined by readings of individual transcripts as they came in. These readings also helped ensure the quality of the data collection and transcription.
Clinical care providers were approached directly by study staff, while patients were recruited with the assistance of clinic staff. All interviews took place at the clinic where the participant worked or received care in a private room. Written informed consent was obtained from all participants. The interviews took place in English and lasted approximately one hour. Institutional Review Boards of the Johns Hopkins School of Medicine and the University of Witwatersrand in South Africa approved the study.
All interviews were audio recorded and transcribed. Thematic content analysis [13 ] was conducted coding and synthesizing provider and patient participants’ views and experiences on the key domains outlined above, as well as those that emerged through the course of the interview through the use of case summaries of each interview. Both the first and second author coded the data in parallel and worked together to generate the case summaries. Three salient themes were documented and are presented below on the clinic environment, TB management practices, and perspectives on the use of the QGIT.
Eligibility for the qualitative study included patients who were 18 years of age or more, living with HIV for at least 6 months, and able to converse in English. One female and one male patient participant were interviewed in each participating clinic. These patients were selected by providers based on their knowledge of patients who might be willing and able to narrate their experience with their clinical care. Two clinical care providers that provided TB care were interviewed in each participating clinic. We sought different types of providers involved in providing TB screening and care to patients (e.g. nurses, counselors, and community health workers).
A semi-structured guide was used to facilitate the interviews using open-ended questions Additional file
Clinical care providers were approached directly by study staff, while patients were recruited with the assistance of clinic staff. All interviews took place at the clinic where the participant worked or received care in a private room. Written informed consent was obtained from all participants. The interviews took place in English and lasted approximately one hour. Institutional Review Boards of the Johns Hopkins School of Medicine and the University of Witwatersrand in South Africa approved the study.
All interviews were audio recorded and transcribed. Thematic content analysis [13 ] was conducted coding and synthesizing provider and patient participants’ views and experiences on the key domains outlined above, as well as those that emerged through the course of the interview through the use of case summaries of each interview. Both the first and second author coded the data in parallel and worked together to generate the case summaries. Three salient themes were documented and are presented below on the clinic environment, TB management practices, and perspectives on the use of the QGIT.
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BLOOD
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The TraumaRegister DGU® of the German Trauma Society (Deutsche Gesellschaft für Unfallchirurgie, DGU) was founded in 1993. The aim of this multicenter database is a pseudonymized and standardized documentation of severely injured patients.
Data are collected prospectively in four consecutive time phases from the site of the accident until discharge from hospital: (A) pre-hospital phase, (B) emergency room and initial surgery, (C) intensive care unit and (D) discharge.
The documentation includes detailed information on demographics, injury pattern, comorbidities, pre- and in-hospital management, course on intensive care unit, relevant laboratory findings including data on transfusion and outcome of each individual. The inclusion criterion is admission to hospital via emergency room with subsequent ICU/ICM care or reach the hospital with vital signs and die before admission to ICU.
The infrastructure for documentation, data management, and data analysis is provided by AUC—Academy for Trauma Surgery (AUC—Akademie der Unfallchirurgie GmbH), a company affiliated to the German Trauma Society. The scientific leadership is provided by the Committee on Emergency Medicine, Intensive Care and Trauma Management (Sektion NIS) of the German Trauma Society. The participating hospitals submit their data pseudonymized into a central database via a web-based application. Scientific data analysis is approved according to a peer review procedure laid down in the publication guideline of TraumaRegister DGU®.
The participating hospitals are primarily located in Germany (90%), but a rising number of hospitals in other countries contribute data as well (at the moment from Austria, Belgium, China, Finland, Luxembourg, Slovenia, Switzerland, The Netherlands, and the United Arab Emirates). Currently, almost 30,000 cases from almost 700 hospitals are entered into the database per year.
Participation in TR-DGU is voluntary. For hospitals associated with TraumaNetzwerk DGU®, however, the entry of at least a basic data set is obligatory for reasons of quality assurance.
The present study is in accordance with the publication guidelines of the TraumaRegister DGU® and registered as TR-DGU project ID 2021–014.
Data are collected prospectively in four consecutive time phases from the site of the accident until discharge from hospital: (A) pre-hospital phase, (B) emergency room and initial surgery, (C) intensive care unit and (D) discharge.
The documentation includes detailed information on demographics, injury pattern, comorbidities, pre- and in-hospital management, course on intensive care unit, relevant laboratory findings including data on transfusion and outcome of each individual. The inclusion criterion is admission to hospital via emergency room with subsequent ICU/ICM care or reach the hospital with vital signs and die before admission to ICU.
The infrastructure for documentation, data management, and data analysis is provided by AUC—Academy for Trauma Surgery (AUC—Akademie der Unfallchirurgie GmbH), a company affiliated to the German Trauma Society. The scientific leadership is provided by the Committee on Emergency Medicine, Intensive Care and Trauma Management (Sektion NIS) of the German Trauma Society. The participating hospitals submit their data pseudonymized into a central database via a web-based application. Scientific data analysis is approved according to a peer review procedure laid down in the publication guideline of TraumaRegister DGU®.
The participating hospitals are primarily located in Germany (90%), but a rising number of hospitals in other countries contribute data as well (at the moment from Austria, Belgium, China, Finland, Luxembourg, Slovenia, Switzerland, The Netherlands, and the United Arab Emirates). Currently, almost 30,000 cases from almost 700 hospitals are entered into the database per year.
Participation in TR-DGU is voluntary. For hospitals associated with TraumaNetzwerk DGU®, however, the entry of at least a basic data set is obligatory for reasons of quality assurance.
The present study is in accordance with the publication guidelines of the TraumaRegister DGU® and registered as TR-DGU project ID 2021–014.
Accidents
Blood Transfusion
Emergencies
Hospital Administration
Injuries
Intensive Care
Operative Surgical Procedures
Patient Discharge
Patients
Peer Review
Rooming-in Care
Signs, Vital
Wounds and Injuries
A total of 76 mother-child pairs volunteered to participate in this study. According to the inclusion/exclusion criteria, 6 pairs were excluded due to premature birth (before 37 weeks of pregnancy); 4 mothers were excluded due to interruption of breastfeeding (the cause being the mother) within the first 48 h after birth; 6 other pairs were excluded (the newborns who required care in the neonatal intensive care unit (NICU)).
Following the secondary selection according to the inclusion/exclusion criteria, a convenience sample group of 60 pairs of new-born mothers, aged over 16, who expressed their desire for exclusive natural nutrition and accepted inclusion in the study, healthy (without cardiovascular or renal comorbidities) who declare that they choose to breastfeed immediately after birth, from which written consent was obtained. The medical data of patients and newborns were taken from the clinic’s electronic system and then stored in a database and identification. The post hoc analysis indicated this sample size yielded a power of 89.6% with the probability of type I error of 0.05.
Patients hospitalized and included in the study group align the ten steps of the Baby Friendly Hospital initiatives, especially step 3 (inform all pregnant women about the benefits and management of breastfeeding), step 5 (show mothers how to breastfeed and how to breastfeed to maintain lactation) and step 7 (rooming practice—in postnatal care allows mothers and babies to stay together 24 h a day).
Inclusion criteria:
To evaluate the success of natural nutrition after birth [36 (link)], the LATCH score was evaluated 24 and 48 h after birth, by a single nurse with experience in conducting clinical and research studies, with the aim of minimizing interpretation errors.
The HADS scale has 14 items of which 7 are for anxiety, and 7 are for depression. Each item is evaluated on a Likert scale with 4 anchors, from 0 = never, to 3 = always. The items for anxiety are represented by odd questions (1,3,5,7,9,11,13) and indicate a level of depression rated on a Likert scale. The items for depression are represented by even questions (2,4,6,8,10,12,14) and indicate a level of depression rated on a Likert scale. To rate the answers, the score is calculated for each scale: anxiety, respectively, depression, taking into account the grid, summing up the scores obtained for the items of the scales separately (Table 1 ).
Following the secondary selection according to the inclusion/exclusion criteria, a convenience sample group of 60 pairs of new-born mothers, aged over 16, who expressed their desire for exclusive natural nutrition and accepted inclusion in the study, healthy (without cardiovascular or renal comorbidities) who declare that they choose to breastfeed immediately after birth, from which written consent was obtained. The medical data of patients and newborns were taken from the clinic’s electronic system and then stored in a database and identification. The post hoc analysis indicated this sample size yielded a power of 89.6% with the probability of type I error of 0.05.
Patients hospitalized and included in the study group align the ten steps of the Baby Friendly Hospital initiatives, especially step 3 (inform all pregnant women about the benefits and management of breastfeeding), step 5 (show mothers how to breastfeed and how to breastfeed to maintain lactation) and step 7 (rooming practice—in postnatal care allows mothers and babies to stay together 24 h a day).
Inclusion criteria:
Pregnant women who declare that they want to breastfeed immediately after birth;
Pregnant women over the age of 16, with secondary education;
The signed consent of the mother for the inclusion of the newborn in the study;
Only term newborns and without comorbidities are eligible.
Pregnant with preterm delivery;
Pregnant women with cardiovascular and renal comorbidities, mental illnesses in the antecedents;
Newborns who required maneuvers and intensive therapy treatments at birth.
To evaluate the success of natural nutrition after birth [36 (link)], the LATCH score was evaluated 24 and 48 h after birth, by a single nurse with experience in conducting clinical and research studies, with the aim of minimizing interpretation errors.
The HADS scale has 14 items of which 7 are for anxiety, and 7 are for depression. Each item is evaluated on a Likert scale with 4 anchors, from 0 = never, to 3 = always. The items for anxiety are represented by odd questions (1,3,5,7,9,11,13) and indicate a level of depression rated on a Likert scale. The items for depression are represented by even questions (2,4,6,8,10,12,14) and indicate a level of depression rated on a Likert scale. To rate the answers, the score is calculated for each scale: anxiety, respectively, depression, taking into account the grid, summing up the scores obtained for the items of the scales separately (
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Rooming-in Care
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The LTCF was an integrated care center with 154 single rooms for the elderly with widely differing needs regarding care, ranging from residents with little need for assistance to people with dementia and those who required extensive care. All residents and staff members (including external workers) during the period of outbreak were included in the analysis. Cases included in the study were defined as those having received a positive PCR result for SARS-CoV-2 either from oro- or naso-pharyngeal swabs between 17 February 2021 and 23 March 2021. Subjects were tested either on the basis of having symptoms or in the context of monthly or reactive screening campaigns. Cases with a documented positive PCR result dating more than 60 days ago were considered to be reinfected. Additional data on residents and staff members were provided by the LTCF management.
The first cases were tested after developing symptoms and being present at the LTCF at the time of their pre-symptomatic infectious episode. Therefore, in addition to testing every symptomatic person and their contacts with a high risk of infection, a comprehensive testing of all staff members and residents was also organized on 23 February. In total, four comprehensive molecular screenings were performed during the outbreak. Two screenings were organized by the LTCF management on 23 February and 10 March, and two screenings were organized by the national LST program and took place on 1 March and 15 March 2021.
The first cases were tested after developing symptoms and being present at the LTCF at the time of their pre-symptomatic infectious episode. Therefore, in addition to testing every symptomatic person and their contacts with a high risk of infection, a comprehensive testing of all staff members and residents was also organized on 23 February. In total, four comprehensive molecular screenings were performed during the outbreak. Two screenings were organized by the LTCF management on 23 February and 10 March, and two screenings were organized by the national LST program and took place on 1 March and 15 March 2021.
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Aged
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Rooming-in Care
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Before conducting the interview, a face sheet was used to enquire about the participants’ age, current use of ADC, and history of using ADC. Subsequently, a semi-structured individual interview was conducted using an interview guide. Each interview lasted approximately 60 minutes. Since the interviews were conducted slowly to ensure participants’ comfort, they were conducted twice (if possible), with an interval of at least 1 week.
The following questions were included in the interview guide: (1) how the interviewee spent their day at the day-care center; (2) what they thought of the others (users and staff) at the center; (3) what kind of relationships they had with the others.
The data were collected from October 2020 to August 2022. The interviews were recorded, and transcripts were verbatim for analysis. The interviewees’ tone of voice and facial expressions were also referenced as data. Two researchers were present during the interviews. The first author conducted the interview and the second one observed the first, ensured proper ventilation, set up panels for infection control, and monitored the participants’ physical condition. To ensure the quality of the interview data, we employed the following strategies. Interviews were conducted in a room where privacy is protected. After informing them that they would not be seen by anyone other than the researcher, the audio was recorded and transcribed verbatim. Interviews were conducted according to an interview guide. When possible, we interviewed twice in order to get them to reveal their true feelings about their interactions with others. Prior to the interviews, we arranged a casual chat time with the participants to make them feeling safe and comfortable. Soon after each interview, the voice data were reviewed for recording error check.
Besides the interviews, the first and second authors observed the day care rooms of each participating agency for an hour with the administrator’s permission. The purpose was to observe the participants and the people around them. However, they were careful not to record personal information other than those associated with the study participants. The observations were recorded as field notes and used for analysis. Observers stayed at ADCs and participated in ADC practices, taking a few unstructured notes. Observers noted participants’ behavior as they interacted with other people. Furthermore, ADC staff were interviewed about the participants’ usual behavior and how they distinguished between clients. All comments were included in the field notes.
Each older adult was considered one unit for data collection and analysis. We interviewed and observed the participants’ experiences within the ADC at the time of the interview and did not include longitudinal changes within the research period.
The following questions were included in the interview guide: (1) how the interviewee spent their day at the day-care center; (2) what they thought of the others (users and staff) at the center; (3) what kind of relationships they had with the others.
The data were collected from October 2020 to August 2022. The interviews were recorded, and transcripts were verbatim for analysis. The interviewees’ tone of voice and facial expressions were also referenced as data. Two researchers were present during the interviews. The first author conducted the interview and the second one observed the first, ensured proper ventilation, set up panels for infection control, and monitored the participants’ physical condition. To ensure the quality of the interview data, we employed the following strategies. Interviews were conducted in a room where privacy is protected. After informing them that they would not be seen by anyone other than the researcher, the audio was recorded and transcribed verbatim. Interviews were conducted according to an interview guide. When possible, we interviewed twice in order to get them to reveal their true feelings about their interactions with others. Prior to the interviews, we arranged a casual chat time with the participants to make them feeling safe and comfortable. Soon after each interview, the voice data were reviewed for recording error check.
Besides the interviews, the first and second authors observed the day care rooms of each participating agency for an hour with the administrator’s permission. The purpose was to observe the participants and the people around them. However, they were careful not to record personal information other than those associated with the study participants. The observations were recorded as field notes and used for analysis. Observers stayed at ADCs and participated in ADC practices, taking a few unstructured notes. Observers noted participants’ behavior as they interacted with other people. Furthermore, ADC staff were interviewed about the participants’ usual behavior and how they distinguished between clients. All comments were included in the field notes.
Each older adult was considered one unit for data collection and analysis. We interviewed and observed the participants’ experiences within the ADC at the time of the interview and did not include longitudinal changes within the research period.
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Cefotaxime is a third-generation cephalosporin antibiotic used for the treatment of bacterial infections. It functions as a broad-spectrum antibiotic effective against a wide range of gram-positive and gram-negative bacteria.
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The MALDI-TOF VITEK MS IVD v2.3.3 is a laboratory equipment product offered by bioMérieux. It is a mass spectrometry-based system for the identification of microorganisms.
Sourced in Japan
Sprague-Dawley rats are a commonly used laboratory animal model. They are a breed of albino rats developed for use in scientific research. Sprague-Dawley rats are known for their calm temperament and reliable breeding characteristics, making them a widely accepted choice for various experimental studies.
Sourced in Finland
The Polar RS800CX is a heart rate monitor designed to track and record heart rate data. It features wireless transmission and data storage capabilities.
Sourced in Germany, United States, France
Dunkin-Hartley guinea pigs are a breed of guinea pig used in laboratory research. They are a common and well-established animal model in biomedical research.
Sourced in United States, France, Germany
The Direct-Q system is a water purification device designed to produce high-quality, ultrapure water for laboratory applications. It utilizes a combination of filtration and purification technologies to provide reliable and consistent water purity.
More about "Rooming-in Care"
Rooming-in Care, also known as mother-infant cohabitation or in-room care, is a healthcare practice that involves keeping newborn infants with their mothers during hospitalization, rather than separating them into a nursery.
This approach, which is recommended in many healthcare settings, promotes early mother-infant bonding, facilitates breastfeeding, and allows for continuous care and observation of the newborn.
Numerous studies have demonstrated the benefits of Rooming-in Care, including improved breastfeeding rates, reduced risk of infection, and enhanced parent-child interaction.
The practice has been shown to support the physical and emotional well-being of both the mother and the newborn during the postpartum period.
In addition to the insights gained from the MeSH term description, other related topics and terms can be explored to further enrich the understanding of Rooming-in Care.
For example, research conducted on Sprague-Dawley rats, C57BL/6J (B6) mice, and Female C57BL/6 mice may provide additional insights into the biological and physiological aspects of mother-infant bonding and early-life development.
Similarly, the use of Tryptic soy broth, Cefotaxime, and MALDI-TOF VITEK MS IVD v2.3.3 may be relevant in the context of infection prevention and control measures associated with Rooming-in Care.
The Polar RS800CX heart rate monitor may be useful in monitoring the physiological responses of both the mother and the newborn during the rooming-in process.
Dunkin-Hartley guinea pigs, another animal model, could also be studied to understand the behavioral and developmental aspects of mother-infant interactions.
Additionally, the Direct-Q system may be employed to ensure the quality of the water used in the healthcare setting, which can be an important factor in maintaining a safe and hygienic environment for the mother and newborn.
By incorporating these related terms and concepts, the content on Rooming-in Care can be expanded and enriched, providing a more comprehensive understanding of this important healthcare practice.
The final text should be informative, clear, and easy to read, with a natural feel that includes a single human-like typo.
This approach, which is recommended in many healthcare settings, promotes early mother-infant bonding, facilitates breastfeeding, and allows for continuous care and observation of the newborn.
Numerous studies have demonstrated the benefits of Rooming-in Care, including improved breastfeeding rates, reduced risk of infection, and enhanced parent-child interaction.
The practice has been shown to support the physical and emotional well-being of both the mother and the newborn during the postpartum period.
In addition to the insights gained from the MeSH term description, other related topics and terms can be explored to further enrich the understanding of Rooming-in Care.
For example, research conducted on Sprague-Dawley rats, C57BL/6J (B6) mice, and Female C57BL/6 mice may provide additional insights into the biological and physiological aspects of mother-infant bonding and early-life development.
Similarly, the use of Tryptic soy broth, Cefotaxime, and MALDI-TOF VITEK MS IVD v2.3.3 may be relevant in the context of infection prevention and control measures associated with Rooming-in Care.
The Polar RS800CX heart rate monitor may be useful in monitoring the physiological responses of both the mother and the newborn during the rooming-in process.
Dunkin-Hartley guinea pigs, another animal model, could also be studied to understand the behavioral and developmental aspects of mother-infant interactions.
Additionally, the Direct-Q system may be employed to ensure the quality of the water used in the healthcare setting, which can be an important factor in maintaining a safe and hygienic environment for the mother and newborn.
By incorporating these related terms and concepts, the content on Rooming-in Care can be expanded and enriched, providing a more comprehensive understanding of this important healthcare practice.
The final text should be informative, clear, and easy to read, with a natural feel that includes a single human-like typo.