This vignette shows the Preregistration Template for Qualitative and Quantitative Ethnographic Studies form (previous versions of this form: v0.93). It can be initialized as follows:

initialized_preregQE_v0_94 <-
  preregr::prereg_initialize(
    "preregQE_v0_94"
  );

After this, content can be specified with preregr::prereg_specify() or preregr::prereg_justify. To check the next field(s) for which content still has to be specified, use preregr::prereg_next_item().

The form is defined as follows (use preregr::form_show() to show the form in the console, instead):

preregr::form_knit(
  "preregQE_v0_94"
);

Preregistration Template for Qualitative and Quantitative Ethnographic Studies

Instructions

Aims

A preregistration is a way to design your research project before you begin and to document your decisions, rationale. A template such as this one can be employed to think about what you want to do and how, and subsequently, if you wish, you can submit the finished preregistration to a registry, such as OSF’s (https://osf.io/registries). This template was developed to aid the preregistration of quantitative ethnographic studies, but due to its modular nature, it can be employed for qualitative studies as well.

Instructions

Download this template from its OSF repository or from this link: https://docs.google.com/document/d/1LsTptfqGQ7rEUGxEB4dM572xcjkXWqxg6O-YY-mzh08/edit?usp=sharing

Fill it out. If any items don’t make sense for your project or you have not made a decision about them at this point, feel free to indicate that in your response.

Submit it. This webpage has detailed instructions on submitting a preregistration to OSF: https://help.osf.io/hc/en-us/articles/360019738834-Create-a-Preregistration

Please note: When you select a registration form, be sure to choose “Open-ended registration” if you are using this particular template.

Brief notes on the template

The expression “coder” and “rater” are used interchangeably in this form. They refer to the person and/or software performing the action of coding (i.e. labelling) qualitative data with constructs relevant to the research question (i.e. codes).

Sections and items

Section: Preparation

Title
title
Tentative title of project
Contributors
contributors
Please list the contributors and their roles. For the latter, you can use CRediT (Contributor Roles Taxonomy), for example.
Research aims
research_aims
Please state the aims of your research. Your aim may be different across different domains (e.g.: knowledge generation, policy development, community resourcing). If so, specify your aim for each domain that is relevant for your study.
Aim type
aim_type
What type of study are you conducting? Exploratory projects, for example, may not have any hypotheses or even specific research questions, their aim is to explore a general topic, community, or practice. Confirmatory studies have specific hypotheses and/or research questions, theories that are either proven or disproven.
Research question
research_question
Please state your research question(s). Research questions are subject to change and/or elaboration. Some beneficial times to review these questions may be at, e.g.: 1) preregistration, 2) after the first instances of data collection, 3) when discussing the first results, 4) when starting write-up of findings
Theoretical framework
theoretical_framework

Please specify the role of theory in your study. You may be using theory to design your methods (including the sampling strategy and coding instructions) or aim to explore the constructs defined in the theory more in-depth. You may aim to closely follow or test a certain theory. Or you may not be basing your design, coding, and other decisions on theory (e.g.: in applied research or in a new area of research with no applicable existing theory). 

Note that this is a good moment to reflect upon your existing expectations and personal preconceptions, and think about whether these derive from theory. If so, indicate that here or in the “Positionality” item (in the Positionality and Credibility section).
Paradigm
paradigm
Please elaborate if your research is conducted from a certain theoretical paradigm (for example, social constructionism, positivism, post-positivism, critical theory, etc.). How will this paradigm influence your research?
Basic data
basic_data
Please describe whether you are working with original or pre-existing data.
Anticipated duration
anticipated_duration
How long do you imagine the study taking, from its preregistration to the final write-up of results?

Section: Sampling

Sampling strategy
sampling_strategy

Please describe your sampling strategy. Please provide a short rationale for why you selected this type of strategy. Describe inclusion and exclusion criteria.

(e.g.: convenience, purposive, snowball, theoretical, maximum variation, proportional quota, non-proportional quota, random, mixed)
Recruitment
recruitment
Please describe from where you are recruiting the participants for your study and how you will be getting in touch with them.
Sample size
sample_size
Planned number of participants (or providers of data or “cases”) and your justification or rationale for this number or range

Section: Data collection

Data collection method
data_collection_method

Please indicate the data collection procedure(s) you will use.

(e.g.: semi-structured interview, structured interview, focus group, enabling technique, self-report, field notes, diary, participant observation, observation, archival research, log file, survey)
Type of raw data
raw_data_type

In what form will you be collecting data for your study?

(e.g.: audio, video, audio-video, text, numerical)
Data providers
data_providers

Your study may be conducted with individuals but data is recorded from a dyad or a group; individuals may not be considered separately. Thus, please indicate who/what you consider data providers in your study.

(e.g.: individual, dyad, group (≥3), individual and group, other)
Data collection tools
data_collection_tools

Please describe or upload the tools, instruments, or plans you will use in collecting or generating your data.

(e.g.: topic guide, interview structure, questionnaire, focus group guide, observation scheme, standardized prompts, protocol, archival search interfaces and queries)
Stopping criteria
stopping_criteria

Please describe the criteria or rationale for stopping data generation or collection. These can differ for various aspects of the project.

(e.g.: data saturation (please elaborate), when inclusion criteria are satisfied, resource constraints (e.g. time/funding), when the analysis has produced an enriching answer to the research question(s))
Metadata or Attributes
metadata_or_attributes

Please specify what constitutes metadata and/or attributes in your study.

Metadata = data about the data collection process or the data itself (interviewer, date of interview, timestamp, etc.)

Attributes = characteristics of data providers (e.g., age, sex, education of cases)

Section: Coding

Type of coding
type_of_coding
Please indicate whether you will be developing your own codes (inductively) or adopting codes from a previous study or theoretical framework (deductive). You may be using a combination of these, e.g., inductively developing codes through test coding and then deductively applying the final code structure.
Process of coding
process_of_coding
If there is more than one rater, are they coding with the same or a different set of codes? For example, all raters may employ different codes, all raters can employ the same codes, or it can be a mix.
Application of codes
code_application
Are you using manual coding (each instance of a code is applied intentionally by the researcher with or without the help of a machine/software) or automated coding (machine performs coding based on an algorithm with or without parameterization by the researcher) a combination of both?
Code development
code_development
Please describe in detail the stages of code development. If applicable, you may upload different code structures developed before triangulation, as well as anything in the process of creating the final version.
Code structure
code_structure
Describe the final code structure, if you have it at the time of preregistration: If you are applying your codes deductively, how many levels of abstraction do you have? How many codes are at the lowest level? (If possible, please upload your final codebook with your preregistration or to your repository)
Classifiers
classifiers
Are you using classifiers (e.g. regular expressions) for automated coding? If so, please elaborate your considerations in developing your classifiers. Provided you have them at the time of preregistration, please list your classifiers, upload them, or indicate that you will have them in your repository.
Types of raters
types_of_raters
Who or what is performing the coding? For example, human only, computer only, or human and computer.
Number of raters
number_of_raters
How many raters are performing coding? If automated coding is (also) being used, please include the computer as a “rater”.
Coding tools
coding_tools
Are you planning on using any specific tools for performing coding? (e.g.: interface for the Reproducible Open Coding Kit (iROCK), nCoder, NVivo, Atlas.ti)
Inter-coder agreement
inter_coder_agreement
Are you planning to examine agreement between coders in any way? If so, how? If you are not planning to do this, you can explain your rationale here.
Intra-coder agreement
intra_coder_agreement
Are you planning to examine the degree to which the application of codes changes over time within the work of the same coder? If so, how? If you are not planning to do this, you can explain your rationale here.
Training for coders
coder_training
Will you be providing any training for raters? If so, please describe this process below. If coders received any previous relevant training, you may indicate that here as well. If you are not planning to provide training, you can explain your rationale here.

Section: Segmentation

Smallest unit of segmentation
smallest_unit_of_segmentation
Define the smallest meaningful unit of segmentation (one sentence, one log entry, one second, etc.)
Other levels of segmentation
other_levels_of_segmentation
Define any other level(s) of segmentation (intermediate, highest), for example: a topic, psychological proximity, recent temporal context, utterances from one participant during one session, an interview transcript, a focus group session transcript, log entries within the duration of 24 hours, observations from one group performing one task, etc.
Type of segmentation
type_of_segmentation
Please indicate whether you will be performing segmentation manually or automating it or a combination of both. This answer may differ depending on level of segmentation; please indicate separately for each level of segmentation you plan to perform. (e.g. “automated”, “manual”, “automated and manual”, “not applicable”, etc)
Coding and segmentation level
coding_and_segmentation_level
Please indicate on which level(s) of segmentation you will be performing coding. You may want to distinguish between coding a narrative and designating attributes or metadata.
Operationalization of source (codable or coded file)
operationalization_of_source
What data will your files contain? (e.g.: one interview, a series of interviews, all think-aloud entries from a participant)

Section: Threading

Indication of threading
indication_of_threading
How are you planning to indicate the depth of threading (nesting) in your data?
Levels of threading
levels_of_threading
If you are using threaded data, are you planning to limit the number of levels you are working with? If so, what is the depth you are planning to work with? What is your rationale for this decision?

Section: Analysis

Approach
approach
Please specify what type of analysis you are planning on conducting. (e.g.: Narrative analysis, Interpretative phenomenological analysis, Grounded theory, Thematic analysis, Content analysis, Process tracing, Comparative analysis, Discourse analysis)
Process
process
Please describe the process that your analysis approach requires and how you see this process manifesting in your study.
Data transformation
data_transformation
If you intend to do so, describe how you will change the grouping or representation of your data in order to perform analysis (e.g.: a higher order grouping of sources, cases, or attributes).
Analytical tools
analytical_tools
Are you planning on using any tools to perform analysis? If so, please specify them here. (e.g.: the Reproducible Open Coding Kit (ROCK), Epistemic Network Analysis (ENA), nCoder, Rho, Topic modelling)

Section: Epistemic Network Analysis (ENA)-Specific

ENA unit
ENA_unit
What will constitute “units”, i.e., for what will you be generating networks? If you know this ahead of time, please indicate it here.
ENA conversation
ENA_conversation
What will constitute “conversation”, i.e., how do you plan to aggregate (bounded sets of) utterances? If you know this ahead of time, please indicate it here.
ENA stanza window
ENA_stanza_window
How will code co-occurrences be accumulated? If you know this ahead of time, please indicate it here. For example, “moving window”, “whole conversation”, or “infinite stanza”.
ENA moving stanza window
ENA_moving_stanza_window
If you will be using a moving stanza window, what will be its length? If you know this ahead of time, please indicate it here along with a justification or rationale. If you don’t know, how do you plan on deciding its size?
Edge weights
edge_weights
What will the edge weight threshold be set to? Will there be any changes in the analytical process or among various networks? If you know this ahead of time, please indicate it here.
Means rotation
means_rotation
Will means rotation be performed? If you know this ahead of time, please indicate it here.
Assessing connections
assessing_connections
What constitutes a strong or weak connection? How will this be determined? If you know this ahead of time, please indicate it here.

Section: Positionality and Credibility

Positionality
positionality
Feel free to reflect on your relation to or association with the studied phenomenon and your position in the research setting/field, including your academic/personal standpoints, assumptions and values. In addition, if there is a potential conflict of interest that can arise, you may want to report that here.
Credibility strategies
credibility_strategies
Please indicate any strategies you will be employing to ensure better credibility of analyses and conclusions. (e.g.: member checking / respondent validation, triangulation with other data sources, asking different researchers to analyze the data, inter-rater reliability, negative case analysis, peer debriefing, cross-checks for rivalling explanations, bringing in an ‘auditor’, reflexivity)

Section: Open Science

Repository
repository
Do you currently have or are you planning to create a repository for making any aspects of your research process open (preregistration, data, code development, codebook, analysis, etc.)? If so, please indicate it here.