Table 5 A case study illustrating the codebook development for CLECI [16]

Step

Research question

Data collection

Step

Issue

Action

Example from Stortenbeker et al. (2022)

Selection criteria

Inclusion and exclusion

Define research scope

Language use of patients presenting medically explained or unexplained symptoms to GPs.

Read through training consultations

Patients talk about their past (‘but it was always low’) or current health problems (‘I am unstable’) as well as about potential future health issues (‘I think it could go wrong’).

Redefine selection criteria

Scope was limited to include only utterances relating to current or past condition of patients, not prospective conditions.

Unit of analysis

Turn constructional unit

Define unit of analysis

Grammatical finite clauses served as unit of analysis in earlier stages.

Read through training consultations

A more flexible unit of analysis was needed for subjectivity markers in cases such as ‘[I notice though] [that I’m getting sensitive to it]’.

Redefine unit of analysis

Turn constructional unit was selected as the new unit of analysis.

Deductive categorization

Retain predefined category

Scan literature for relevant linguistic elements

Patients with MUS use more negations when describing (non-) occurrences of symptoms than patients with MES [37, 38].

Formulate code

Negation – a) absent; b) syntactic; c) morphological

Read through training consultations

Plenty of examples were found, such as ‘I am unstable’ and ‘I cannot move comfortably’, so negation was retained in the revised codebook.

Deductive categorization

Exclude predefined category

Scan literature for relevant linguistic elements

Doctors use more ‘illness terms’ (e.g. urination problems) towards MUS patients, whereas MES patients are often described with ‘disease terms’ (e.g. bladder infection) [39].

Formulate code

Terminology – a) illness; b) disease

Read through training consultations

Differentiating between the two was not easy (e.g. ‘I got dizzy’, ‘well then you’re all worn out’) and remained subjective. As an objective definition of the boundaries was not possible, the category was removed from the codebook.

Inductive categorization

Include category based on observations

Read through training consultations

Salient utterances such as ‘that ear keeps on whizzing’ were marked, suggesting ‘that ear’ operating as a separate agent as opposed to ‘I can hear pretty badly’.

Scan literature for relevant studies

Patients can be disconnected from emotional and/or somatic experiences in various degrees [40].

Formulate new code

Grammatical subject – a) first person (the patient, ‘I’); b) third person (patient’s biomedical or psychosocial state, ‘that ear’).

Iterative refinement

Add subcategory after test coding

Define code

Grammatical subject – a) first person; b) third person.

Read through training consultations

Some utterances could not be indicated as having a first- or third-person subject, such as ‘[positive though] [that I do not have any new lesions]’ in which no subject is present in the first TCU.

Redefine code

“empty subject” was included as a subcategory in the revised version of the codebook.

Step

Issue

Action

Example from Stortenbeker et al. (2022)

Double-coding

Refine coding categories

Double code session

Intensity displayed a Kappa of .66.

Explore systematic differences

One coder did not interpret certain time words as intensifiers, whereas the other coder did, e.g. ‘sometimes’, ‘all of a sudden’.

Fine-tune codebook and coders

Remarks were added to the codebook. Words denoting an in- or decrease in time/frequency words are only marked when intensified such that ‘after that it was wrong again’ is not intensified, ‘all the time I think oh I’m getting tired’ is intensified.

Coding

N/A

N/A

Final coding was performed by the main researcher in various separate coding sessions. Cases of doubt were marked and evaluated at a later point in time.

Steps

Analysis

Reporting