For quantitative study, the data were checked for completeness, cleaned and entered in EPI INFO version 7 and exported to SPSS version 23 for data cleaning and analysis. Tables and pie charts were used to present results. The goodness-of-fit model (Hosmer and Lemshow) was used for the fitness of the model. Bivariate and multivariate logistic regression analysis was performed to see the association between MHM and independent variables. Variables with a p-value < 0.25 at bivariate logistic regression were entered into multivariate logistic regression. Finally, AOR with 95% CI and p-value < 0.05 were used to declare a statistically significant association. The qualitative study data were first transcribed verbatim. The next step was to translate the transcript from the local languages (Afan Oromo and Amharic) into the English language. The transcript was copied to ATLAS.ti version 7 for analysis. Then ATLAS.ti version 7 was used for developing categories and themes. The researchers conducted qualitative data analysis using inductive thematic analysis, which aimed to identify a set of main themes that captured the diverse views and feelings expressed by participants. Direct quotations were presented with a thick description of the findings to triangulate the quantitative results.
Version 7
Manufactured by ATLAS.ti
Sourced in Germany
Atlas.ti version 7 is a qualitative data analysis software that supports researchers in organizing, analyzing, and interpreting complex non-numerical data. It provides a range of tools for coding, annotating, and visualizing data from various sources, including interviews, documents, and multimedia files.
Automatically generated - may contain errors
Lab products found in correlation
Spss statistics version 25, by IBM (2 mentions)
Spss version 23, by IBM (1 mentions)
Epi info version 7, by IBM (1 mentions)
Statistical package for the social sciences version 22, by IBM (1 mentions)
Stata version 12, by StataCorp (1 mentions)
Atlas ti 7, by ATLAS.ti (1 mentions)
Stata se, by StataCorp (1 mentions)
Stata version 11, by StataCorp (1 mentions)
Spss version 22, by IBM (1 mentions)
Spss version 20, by IBM (1 mentions)
Stata version 15, by StataCorp (1 mentions)
46 protocols using version 7
1
Menstrual Hygiene Management Research Protocol
2
Qualitative Data Analysis Methodology
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Written transcripts of the interviews, which compounded the unit of analysis, were classified and then codified according to the study objectives and the dimensions addressed, constituting a single corpus of information.
The written transcripts were entered into ATLAS.ti version 7 (ATLAS.ti Scientific Software Development GmbH) software combined with the manual technique of information coding. Analytical dimensions were identified as constructs for the description of findings.
Finally, data were abstracted and interpreted through content analysis [29 (link)]. As part of the analysis, direct quotations representative of the participants’ opinions were selected and included in this manuscript to illustrate our findings. In order to protect the identity of the informants we only provide information on age and gender.
The written transcripts were entered into ATLAS.ti version 7 (ATLAS.ti Scientific Software Development GmbH) software combined with the manual technique of information coding. Analytical dimensions were identified as constructs for the description of findings.
Finally, data were abstracted and interpreted through content analysis [29 (link)]. As part of the analysis, direct quotations representative of the participants’ opinions were selected and included in this manuscript to illustrate our findings. In order to protect the identity of the informants we only provide information on age and gender.
3
Quantitative and Qualitative Analysis of Student Learning Plans
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Descriptive statistics were used to summarize the student population and academic performance. The learning plans were analyzed using quantitative and qualitative analysis. Likert scales were characterized as ordinal scales and summarized using descriptive statistics. Students answering “don’t know” to any question were excluded from calculations of the mean and standard deviation. Qualitative data of free text comments within the learning plans were analyzed using content analysis. ATLAS.ti version 7 (Berlin, Germany) was used to assist content analysis. Codes for common themes were generated, and through a series of iterations, common themes were identified. A paired samples t-test was used to compare academic goals, that is, target scores, typical scores, and actual scores. Statistical Package for the Social Sciences version 22 (SPSS Inc., IBM Corporation, Armonk, NY, USA) was used for statistical analysis.
4
Young Adults' COVID-19 Lockdown Experiences
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One of the authors checked and/or back-translated all transcripts for accuracy. To enhance trustworthiness, three authors read through two of the emerging adults' transcripts, and applied deductive and inductive codes to the text. A coding frame was generated which enabled codes to be applied to all other emerging adults' transcripts while additional new codes were also noted in the coding frame. For this paper, only codes related to their COVID-19 lockdown experiences were analysed and reported. We analysed the transcripts using the principles of codebook thematic analysis (Braun & Clarke, 2022 ), aided by the qualitative data analysis software, Atlas.ti version 7. Codes were grouped into sub-themes under deductively proffered major themes (relationship quality, sexual activity and contraceptive use and reproductive health outcomes). The two family planning providers' transcripts were read by one of the authors and findings relating to young people's access to contraception, and supply and cost of commodities during the lockdown were elicited to complement the study findings. These are discussed in the ensuing sections.
5
Mixed-Methods Analysis of Study Outcomes
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For the quantitative analysis, we used descriptive statistics such as means, median and proportions to describe the general characteristics of the study population, study outcomes, process indicators and satisfaction level in participants using the RE-AIM framework [38 (link)]. Statistical analyses were performed using STATA version 12.0 (Stata Corp., College Station, TX, USA). For the qualitative analysis, written transcripts of the interviews were classified and then codified according to the study objectives. The written transcripts were entered into ATLAS.ti version 7 software (ATLAS.ti Scientific Software Development GmbH) combined with the manual technique of information coding. Analytical dimensions were identified as constructs for the description of findings. Finally, data were abstracted and interpreted through content analysis [39 , 40 (link)].
6
Barriers and Facilitators of Team-Based Integration
7
Qualitative and Quantitative Analysis
8
Qualitative Analysis of Participant Interviews
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All IDIs were transcribed verbatim after a minimum of three-repeat listening. The transcribed documents were imported into Atlas.ti™ version 7 for coding and analysis. The investigators then coded the respondent's words, phrases, sentences, and memos relevant to the area of the study. They systematically coded raw data openly and categorized the subthemes under their respective themes. Then, they created nonrepetitive central themes that were constructed based on the formed categories. Finally, investigators also cross-checked the themes that emerged after analysis with the raw data and respective quotes in each category of the themes. Direct quotes of the participants were included in the write-up of the findings.
9
Thematic Analysis of Qualitative Interviews
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After transcribing, a research team with expertise in social sciences, public health, and clinical care was established comprising three members (AKT, DBN, RN), who conducted thematic content analysis. The team coded transcripts using the deductive (guided by CFIR as a coding framework) approach. The coding process was guided by the consensual qualitative research (CQR) procedure [23 (link)].
First, each research team member reads three transcripts independently and identified preliminary codes. Through a series of meetings, discussing coding differences, an initial codebook was agreed upon. To organize and manage the large amount of data, all transcripts were then coded utilizing the Atlas.ti (version 7) software while applying the codebook and giving an allowance for new codes. An external researcher independently coded six of the transcripts to establish inter coder reliability (Kappa 0.80). A final codebook and subthemes were resolved by the researchers through more meetings, and these were mapped to the CFIR domains and constructs (Table3 ).
First, each research team member reads three transcripts independently and identified preliminary codes. Through a series of meetings, discussing coding differences, an initial codebook was agreed upon. To organize and manage the large amount of data, all transcripts were then coded utilizing the Atlas.ti (version 7) software while applying the codebook and giving an allowance for new codes. An external researcher independently coded six of the transcripts to establish inter coder reliability (Kappa 0.80). A final codebook and subthemes were resolved by the researchers through more meetings, and these were mapped to the CFIR domains and constructs (Table
10
Communication Patterns in Medical Encounters
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The number and duration of the selected scenes were evaluated. Communication pattern frequencies and performance judgement outcomes were counted, as well as cue-usage frequencies. A chi-square test was used to check for differences between doctors and non-doctors, and standardized residuals were used to describe the inclination to prefer rating scenes positively or negatively for both communication patterns. Effects were labelled small, medium, and large according to conventions (d = 0.2/ = 0.1: small, d = 0.5/w=0.3: medium, d = 0.8/w=0.5: large) [29 ]. To further describe differences in cue usage we used the c-index (ATLAS.ti GmbH 1993–2014) that normalizes the co-occurrence of using cues together with communication patterns and positive/negative judgements. The c-index varies between 0 and 1, where 0 indicates that the two variables never co-occur and 1 that they do co-occur in all instances. The degree of co-occurrence was labelled as follows: low degree (c < 0.25; meaning both codes are used in <25% of the cases), medium degree (c > 0.25 and c < 0.75), and high degree (c > 0.75). Atlas.ti, Version 7 (Atlas.ti GmbH, Berlin/Germany) was used for content coding and counting frequencies of code occurrence.
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