What person attributes influence the comprehension of written health information? A scoping review and critical appraisal

What person attributes influence the comprehension of written health information? A scoping review and critical appraisal

Charlotte Betts

11/09/2023

Increasingly, individuals are required to be actively involved in their healthcare. To do so successfully, individuals need to possess the skills and resources to be able to access, understand, and apply health information. Health communication guidance proposes that health information is not understood due to the mismatch between adults average literacy skills and the literacy skills required to comprehend health information. To tackle this, the use of plain language, such as shortening sentences and removing jargon, is promoted. Policies, however, do not commonly consider the impact of person attributes, such as age, education, and gender, on the comprehension of health information. To understand the nature and scope of current research, and whether person attributes do have an impact, a scoping review was conducted. The search strategy yielded 5,459 articles which were then screened, resulting in a final sample of 99 studies. Quantitative analyses and a critical appraisal revealed three main findings: (1) the research is heterogenous and evolving; (2) person attributes are not commonly used in analyses; and (3) when person attributes are included, the effects on comprehension vary. The findings and implications of this review have the potential to influence how future research is conducted, and crucially inform policies about the importance of person attributes on the comprehension of health information.

health literacy, comprehension, person attributes, health outcomes.

Stage 1: Identify the Research Question
The current research is an updated scoping review, building upon earlier work by Davies et al. (in preparation), which seeks to answer: What person attributes affect or can be predicted to affect the response of individuals to written health information?

Table 2
Form Developer: Rebecca A. James

Search strategy methods
Strategy
Method
Bibliographic
Searched the following: Cumulative Index to Nursing and Allied Health Literature (CINAHL); PsycINFO; PubMed; and Web of Science (WoS).
Journal
Obtained all sources from the following journals between 2018-11-08 and 2023-05-05: Patient Education and Counselling; Health Communication; and Journal of Health Communication.
Author
Obtained sources from the following authors between the dates 2018-11-08 and 2023-05-05: TC Davis; Dan Morrow; Chiung-Ju Liu; Michael Paasche-Orlow; Lisa Soederberg Miller; Rima Rudd; and Michael Wolf.
Reference
Once the full text of the bibliographic, journal, and author searches were complete, the reference lists of the included items were examined to locate new and possibly relevant articles.

Stage 2: Identifying Relevant Studies
Sources were identified using four methods: (1) bibliographic search; (2) journal search; (3) author search; and (4) reference search. Grey literature was not searched due to concerns with the quality of the literature and possible time constraints. Excluding the reference search, all articles were published between 8th November 2018 to 5th May 2023. Details of each of the search methods are outlined in Table 2.

Stage 3: Study Selection
Once articles were imported to Rayyan, a free online software application for conducting reviews (Ouzzani et al., 2016), duplicate articles were identified and removed. Then articles went through a title and abstract screening whereby articles which did not include the following were excluded: (1) a measure of understanding, comprehension, or readability; (2) a quantitative outcome; (3) populations who are typically developed; (4) presentation of health information; (5) present original data (excluding reviews); and (6) presented in English or English was a first language.

The exclusion criteria (Table 3) enabled the final sample of studies to be focussed and relevant to the review. Included articles were then read in full and the same exclusion criteria was applied. Articles which passed the full-text screening were then examined to identify relevant studies from the reference lists, and these references then underwent the same screening process outlined above. Following best practice recommendations (Levac et al., 2010), study selection was conducted by myself and TM (a MSc student) to reduce the chance of bias. Further, regular training and meetings took place (with TM and supervisor RD) to become familiar with the process and to discuss and resolve conflicting decisions between researchers.




Table 3
Exclusion criteria for study selection
Exclusion Criteria
Reasoning
Not a measure(-s) of understanding, comprehension, or readability, metacomprehension, or recall
Articles which do not measure understanding, either directly, or indirectly, and do not measure readability of texts, are not relevant to the current review.
Not quantitative outcomes
Quantitative data is needed to understand average associations between the variation of person attributes and comprehension responses.
Not typical development (excluding participants presenting cognitive or language impairments)
Need to first understand how responses to health information varies within a typical population. Future research should be more inclusive to see how response varies in the whole population.
No presentation of health information.
The present review is concerned with comprehension and response to written health information.
Not original data (rather than reviews).

Although reviews themselves are not targets for review, they will be identified as potentially informative.
Not English or second language speakers of English.
There is limited information regarding how comprehension responses to text may be different or similar in different language, further, text properties may differ.

Stage 4: Data Charting
Articles were classified as being either an experimental, readability, or review article and as this paper focusses on research investigating the effects of person attributes, only experimental articles are analysed and reported. TM analysed and reported readability studies. Data extraction was completed so that information about the nature and characteristics of the study could be recorded. Data extraction was achieved by entering information (Table 4) into an online Qualtrics form which was developed and used by Davies et al. (in preparation) in their scoping review, which allowed for systematic extraction of information regarding the characteristics, methods, and findings of each study. To ensure that data extraction was reliable, a sample of studies were charted in parallel by myself and TM and were checked by RD for consistency.

Table 4
Characteristics that will be extracted from experimental studies for data charting.
Form Developer: Rebecca A. James

the article title
the article DOI, if available
the article authors
the article year of publication
the location of data collection (location may be inferred by author affiliation, or reported in article text concerning the regional or national source of health texts, or the locality of participant recruitment)
information about the composition of the participant sample (e.g., healthy adults, patients, etc.)
the number of participants
individual differences measures, if reported (e.g., gender, age, etc.)
text type (the type of the health information text sampled, e.g., website, medicine information, etc.)
text topic (the topic of the health texts sampled)
text sample size (the number of texts sampled)
if the study involved the manipulation of text properties, information on what linguistic or other features were manipulated, or what intervention was implemented (e.g., variation in organization or structure, in the inclusion of pictures, in readability, format, or other)
what test of comprehension was conducted (e.g., verbal or written summary, true/false question, open-ended questions, multiple-choice questions, cloze, recall, etc.)
what outcome measure was analysed (accuracy, or other)

Stage 5: Collating, summarising and reporting the results
Data charting resulted in the creation of a database of detailed information about the nature and scope of each article. To effectively make sense of such information, the original database of information was organised using thematic labels (Table 5). For example, the thematic label leaflet would be applied to articles which referenced handouts of medical information as pamphlets, leaflets, and brochures. This process enabled greater ease and clarity to conduct quantitative analyses and to provide a textual commentary of the findings. Quantitative analyses include frequencies and distributions of study characteristics observed in the sample, in addition to evidencing what direction of effect person attributes had on responses to health information. Directionality of the results, as opposed to reporting significance is deemed appropriate as the reporting of significance in reviews is misleading (McKenzie & Brennan, 2019). Following the synthesis and quantitative analyses, a critical appraisal of the evidence was conducted. Although this stage is optional for scoping reviews (Tricco et al., 2018; Levac et al., 2010), it was considered necessary to provide a sense-making of the conclusions we can reach given the synthesis of evidence. The appraisal followed guidance from the Synthesis Without Meta-Narrative (SWiM) guidance (Campbell et al., 2020) and Realist And Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) publication standards (Wong et al., 2013). Such guidance provides a framework
Form Developer: Rebecca A. James

for the critical appraisal to comprehensively answer the research question, and discuss the traditions, trends, and value of research. Unlike other reviews such as systematic reviews, formal assessment tools such as the Cochrane Risk of Bias tools will not be used as this review does not focus on examining randomised control trials and the research is too heterogenous to appropriately apply such tools (Levac et al., 2010).

Table 5
Thematic labels for experimental studies
location
text type (e.g., consent form, decision aid)
topic or health area (e.g., arthritis, cancer)
intervention (e.g., counselling, drug)
[study] design (e.g., illustration type, text readability)
[study] implementation (e.g., different data visualizations, different organisation)
outcome (e.g., comprehension, knowledge)
[outcome] measure (e.g., multiple choice question, self-rated)
individual differences (e.g., age, gender)

Lancaster University

Data.csv and Text.doc

Betts2023

Oliver Powell

Unsure. Contact Dr. Rob Davies.

In part, in collaboration with TM. Supervised by Dr. Rob Davies

English

Scoping Review

LA1 4YW

Dr. Rob Davies

MSC

Scoping Review - Health Communication

99 Studies

Density plot and dot plot with critical appraisal