Unravelling Complexity in Malaysian Life Insurance Policy Documents: The Questions of Readability and Lexical Density

Unravelling Complexity in Malaysian Life Insurance Policy Documents: The Questions of Readability and Lexical Density

Kamisah Ariffin¹, Khalid Mat Pardi^2*, Noli Maishara Nordin³ & Faiza Rostam Affendi⁴

¹Academy of Language Studies, Universiti Teknologi MARA Pahang, Jengka Campus, 26400 Bandar Tun Abdul Razak, Pahang, Malaysia

^2,3,4Academy of Language Studies, Universiti Teknologi MARA Pahang, Raub Campus, 27600 Raub, Pahang, Malaysia

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2024.8100156

Received: 08 October 2024; Accepted: 11 October 2024; Published: 12 November 2024

ABSTRACT

Studies on knowledge of insurance literacy have shown that people have poor understanding of terms related to disclosures due to the complication of the language of the fine prints. To avoid insurance disputes, certain jurisdictions in the US have incorporated the use of readability formulae, to help assess the reading-level of the policy for the benefits of the policyholders. In Malaysia, it is not known whether such a readability formula is incorporated in the drafting of the insurance policy. Thus, this study aimed to fill the gap by analysing the insurance policy provided by insurance companies in Malaysia in terms of its readability and lexical density. The data were procured from the policy documents obtained from two insurance companies in Malaysia. The policies were analysed using five validated readability formulae of Flesch Reading Ease Index, Flesch-Kincaid Grade Level Index, Gunning Fog Index, Simple Measure of Gobbledygook (SMOG) and Coleman-Liau Index, and Halliday’s lexical density formula. The readability consensus grades the policy documents as ‘difficult to read’. The analysis also reveals ‘average’ and ‘above average’ level of lexical density in both policies. The findings suggest that policyholders with a low level of English language proficiency may find it challenging to understand the legal documentation that elaborate their powers and liabilities to the contract signed. The findings of this study call for the attention of relevant authorities to mandate the incorporation of readability formulae in any policy drafted and the development of readability formula for English as a second or foreign language.

Keywords: Insurance Policy, Readability, Readability Index

INTRODUCTION

Insurance plays a significant role in an individual’s financial wellbeing. One can benefit from having an insurance policy as it is considered as an important risk management tool (Lin, Bruhn, & William, 2019) that helps absorb his/her financial burden caused by unfortunate events, by transferring the losses to an insurance company (Scriven, 2008). However, it is doubtful that insurance policyholders read their policies in detail when they received them apart from the spelling of their names, description of properties, deductions, and the premiums. There is a high possibility that they do not read the lengthy operating manuals and get lost in the complication of the language of the fine prints.

An insurance policy is a legal document between the insurance company and the policyholder. It is a document that entails legal documentation elaborating the powers and liabilities of both parties to the contract. The document is dense as it entails legal implications in case of a dispute. It contains a lot of legalese and specialised terminology, and sentences that run on for paragraphs, making it difficult to read and comprehend by an average policyholder, especially if he/she is not familiar with the English language.

Research on general knowledge of insurance literacy has been scarce. The available research conducted primarily through research and focus groups show a lack of consumer knowledge and decision-making skills (Tennyson, 2011). People have poor understanding of the terms related to disclosures, prices and quality differences between insurance companies (Cude, 2005; Pourkiani, Chegini, Yousefi & Madahian, 2014). When consumers cannot analyse, understand, and distinguish between multiple insurance policies, they usually rely on word-of-mouth to make insurance policy decisions (Berger, 1988; Schwarcz, 2010; Tennyson, 2011). Thus, most policyholders do not understand what is covered and excluded, and are not aware that the policy often includes fine prints that often contain exceptions and exclusions, and sometimes, even exceptions to exceptions, which can cause dispute between the policyholders and the insurance company. Often, the technical legal arguments work in favour of the insurance companies and are used to deny coverage.

To avoid insurance disputes, policyholders must understand the insurance policies based on the premiums they are paying for. Excessive use of legal terminologies and complex sentences often demotivate policyholders from reading them. To help policyholders understand their policies, insurance companies should provide readable insurance documents that an average consumer can read and understand. The companies should revise the document by using plain English, using simple words and sentences. The idea of plain language is based on a brief, clear, and direct English document writing style. It refers to not only utilising straightforward terms and simple expression, but also conveying information in a clear and precise manner (Barczuk, 2015). This can help reduce the difficulty of the reading level of the policy.

Insurance companies can simplify their documents by using a readability formula. In the U.S., certain jurisdictions have incorporated the use of readability formula, such as the Flesch Reading Ease Index, Flesch-Kincaid Grade Level Index and Simplified Measure of Gobbledegook (SMOG), to help in assessing the reading-level of the drafted policy. For instance, Massachusetts (Mass. Gen. Laws 2014) mandates that insurance plans and policies have a minimum score of 50 (equal to a reading level for the tenth grade) on the Flesch reading ease test. Likewise, each insurance provider in Michigan must first receive approval from the Insurance Bureau before offering its policy up for sale. Each policy must fulfill its requirement that the readability score for a form requiring endorsement not be less than 45 (Barczuk, 2015). The aim is to improve consumer-friendly legislation so that policyholders are fully aware about every clause and sub-clause of the document. This can ensure that both insurance companies and policyholders understand the subject matter and implications in the same sense.

In Malaysia, it is not known whether such a readability formula is incorporated in the drafting of the insurance policy. Most readability studies found in the literature only focused on business annual reports (Bakar and Ameer, 2011; Courtis and Courtis, 2006; Courtis and Hassan, 2002) and educational texts (Ismail, Yusof  and Yunus, 2016; Gopal, Maniam, Madzlan, Shukor and  Neelamegam, 2021). Thus, this study aims to fill the gap by analysing the insurance policy provided by insurance companies in Malaysia in terms of its readability based on the validated reading formulae, i.e Flesch Reading Ease Index, Flesch-Kincaid Grade Level Index, Gunning Fox Index, SMOG Index and Coleman-Liau Index. In addition, Halliday’s formula of lexical density was also used to find out the lexical density of the policies/ Due to the limitation of the study, it could not examine all types of insurance policy that are offered by all insurance companies in this country. Therefore, the study only focused on life insurance policies provided by two companies in Malaysia. It is hoped that the findings can contribute towards consumer education by facilitating their capacity to understand the content of their insurance policies.

LITERATURE REVIEW

Readability

Readability is defined as all the interactions of every element within a piece of printed material that affect the success the readers have with the material (Dale & Chall, 1949). In addition, the term readability is also described as the extent to which certain texts are comprehensible and understandable by a group of people (Klare, 1963; McLaughlin (1969; Brown, Janssen, Trace, and Kozhevnikova (2012). Richards, Platt & Platt (1992, p.36) simply claimed readability as ‘how easily written materials can be read and understood’. In the same vein, Richards and Schmidt put forward readability as ‘the ease of a text that can be read and understood’ (2010, p.482). This suggests a consensus that readability is not about legibility or literacy but rather on the difficulty of the text perceived by the reader.

Readability of a text is determined by a number of aspects. These include the average length of sentences, the number of new words included, and the complexity of the grammar (of the language) used in the text (Richards and Schmidt, 2002).  Readability problem arises when there is a mismatch between the reader’s reading level and the text. A similar text may be easy for one reader but, on the other hand, may be rather difficult for another reader to comprehend.  Westwood suggested that a reader ‘should at least understand 97% of words on the page so that they can easily understand the text’ (2001, p.64).

Readability Formula

The readability formula is used to measure readability and to predict the difficulty level of texts. There have been many procedures or reading formulae designed to measure readability. The most commonly used is the Flesch Reading Ease Formula (FRE), formulated by Rudolph Flesch in 1948. The formula calculates the readability of a text as:

Where:

FRE is a simple approach to evaluate the readers’ grade-level. FRE evaluation technique measures mainly on the readability of the text from the average syllable number of words in the text and average sentence length. FRE theorises that the more complex the pronunciation of a certain word is, the harder it is to comprehend and the longer the sentence is, the harder it is to read. The readability index rates texts on a 100-point scale where the higher the score, the easier it is to understand the text.

Kincaid and his team (1975) later extended this FRE formula by incorporating the grade level evaluation to the scores. This formula, known as Flesch-Kincaid Grade Level (FKG), correlates inversely with FRE. In other words, a text with high score in FRE test should have lower score on the FKG test.  This is shown in Table 1.

Table 1: Flesch Reading Ease and Flesch-Kincaid Grade Level Measurement

With the advance of technology, FRE and FKG softwares have also been incorporated and installed in Microsoft Office Word, and websites such as www.webfx.com, https://goodcalculators.com, and www.textcompare.org, making it a lot easier for research and knowledge. One can utilise the formula just by simply selecting the texts for the readability scores.

Another approach to determine a text readability level is the Simple Measure of Gobbledegook (SMOG). The SMOG formula introduced by McLaughlin (1969) focuses on the length of phrases and words in which they are taken into consideration in the computation (DuBay, 2004). The formula of SMOG comprises a single variable together with the amount of polysyllabic (three or more syllable) words in 30 sentences. The readability of the text is calculated using this formula:

The SMOG approach estimates the level at which the readers have progressed. Technically, if readers read at or above their grade level, they will understand most of the content (Bailin & Grafstein, 2016). Table 2 shows the SMOG score and its conversion to the education level.

Table 2: SMOG Score and Education Level

Like FRE and FKG, SMOG readability calculator is also available online in several websites like https://charactercalculator.com, www.webfx.com, and www.textcompare.org.

As for the Gunning Fog index formula, developed by Robert Gunning, the following calculation is used to determine the readability of a text:

The index approximates the years of education needed to understand the text. It suggests that a text for universal understanding should have an index of less than 8. This is shown in Table 3.

Table 3: Gunning Fog Index and Reading Grade Level

Along the same line, Coleman-Liau Index (CLI) gauges the readability of a text by approximating the output against the US grade level required to understand the text. This is calculated by the following formula:

Where:

As readability affects how a text can be understood by the reader, it is important for writers to aim for high readability as it helps readers to process information easily and be engaged with the content. More importantly, high readability can lessen misunderstanding and increase accessibility to the text. For this reason, some U.S jurisdictions have required legal documents such as insurance policies to be written at no higher than a ninth-grade level of readability as measured by the FKG formula (McClure, 1987). This is because several early works on the readability of laws and legal documents discovered that the comprehension requirements needed to understand the information given to readers are beyond the educational attainment of most people (Arkell & Van Dyck, 1978; Tan & Tower, 1992 as cited in Ruohonen, 2021).

Lexical Density

Ure (1971) introduced the concept of lexical density to describe the proportion of content or lexical words (words with specific meanings, such as nouns, verbs, adjectives, and adverbs) to functional or grammar words (words like articles, prepositions, pronouns, and conjunctions) in a given text. In other words, it quantifies the “content words” relative to the “function words” in a piece of text. He proposed the following formula in computing the lexical density of a text:

Lexical density has been widely studied as a measure of text complexity and readability (Li, 2021; Nasseri & Thompson, 2021, Elgobshawi & Aldawsari, 2022). The concept highlights that texts with higher lexical density possess a greater concentration of information. A high lexical density, thus, indicates that a text is rich in content words, making it denser in meaning and potentially more informative. On the other hand, a low lexical density suggests that a text contains a higher proportion of function words, which can make the text less information-dense and potentially more complex or abstract.

Researchers have applied this concept across diverse fields, including legal and financial communication, recognising its influence on audience understanding and engagement (Kaplan & Saccuzzo, 2019). Studying the lexical density in insurance policy documents holds significant implications for policyholders, offering them a clearer understanding of the terms and conditions outlined in their coverage. The intricate language often employed in insurance policies can create confusion and hinder policyholders from comprehending the extent of their coverage, obligations, and rights (Scott, 2023). Studies indicate that policyholders often struggle to comprehend the intricate language used in insurance policies. In other words, policies with higher lexical density were associated with decreased policyholder comprehension, causing them the difficulties in extracting crucial information from the policies.

Lexical Density Calculation

Lexical density can be quantified either by examining the ratio of lexical items to the total word count or by considering the ratio of lexical items to the number of higher structural elements within sentences, such as clauses. Halliday (1985) modified Ure’s formula by changing the dominator of the ‘total number of words’ to ‘total number of clauses’:

L_d         =              (N_lex / N) x 100

Where:

L_d         =               the density of the analysed text

N_lex    =          the number of lexical items

N       =          the total number of clauses

In Malaysia, studies on readability have mainly focused on students’ text comprehension (Gopal et al., 2021; Ismail, Yusof & Yunus, 2016; Sjahrony, Lubis, & Baharudin, 2018; Uri & Abd Aziz, 2018) and business reports (Bakar & Ameer, 2011; Courtis & Courtis, 2006; Courtis & Hassan, 2002). None has been found on lexical density. Ergo, research on text readability and lexical density on insurance policies in Malaysia has yet to be conducted. There seems to be a need to explore the readability and lexical density level of the policies as information provided in the policies is complex with legal and technical jargons that can pose a challenge to the laymen.

METHODOLOGY

The present study aims to quantify the readability and lexical density level of life insurance policies provided by selected insurance companies in Malaysia. The researchers reached out to several insurance companies, requesting permission to analyse the policies offered to their clients in terms of the readability of the documents. However, only two of the companies consented to the analysis, thus, the data for the study only consisted of two policy documents obtained from these companies. Hence, caution should be taken into making any generalisation as the limited data might not represent all the similar documents available.

This study utilised the readability calculators available online as it would be more convenient in terms of time and accuracy. The five formulae (The Flesch Reading Ease, Flesch-Kincaid Grade Level Measurement, Gunning Fog Index, SMOG Index and Coleman-Liau Index) softwares incorporated in the Readability Formulas website were used to determine the readability index of the policies. The results were automatically calculated and a consensus score was given based on the five formulae.

As for lexical density, textalyser, an online text analysis tool, was used to generate statistics about the insurance policies. The following table is used as a reference to determine the level of lexical density for the policies Scott (2023).

Table 3: Level of Lexical Density

ANALYSIS AND DISCUSSION

The Readability Level of Insurance Policies

The analysis indicates that the overall readability level of the two policy documents is at ‘difficult level’. This is shown by the scores obtained for all sections in the policies. The following section presents the analysis of each policy in detail.

Policy A

Eight sections in this policy were analysed, namely: ‘contribution waiver endorsement’, ‘basic definitions’, ‘fund provision’, ‘ownership provisions’, ‘supplementary contract provisions’, ‘critical illness selection provisions’, ‘claim procedure’, and ‘type of contract’. Table 4a shows the score and the readability level of each of these sections based on the five formulae.

Table 4a: Readability Score and Index

Policy B

Policy B contains less sections compared to Policy A, thus, offers less items to be analysed. Only four sections in this policy were analysed, namely: ‘product disclosure’, ‘product illustration’, ‘investment rate of return’, and ‘death and disability benefi’t. Table 4b shows the score and the readability level of each of these sections based on the five formulae.

Table 4b: Readability Score and Index

The findings indicate that items in Policy A have the readability consensus ranging from ‘difficult to read’ (contribution waiver endorsement, basic definitions, fund provision, ownership provisions) to ‘very difficult to read’ (supplementary contract provisions, critical illness selection provisions, ‘contribution waiver endorsement’, ‘basic definitions’, ‘fund provision’, ‘ownership provisions’, ‘supplementary contract provisions’, ‘critical illness selection provisions’, ‘claim procedure, type of contract) as shown in Table 4a. The grade level analysis also shows the grade level ranging from 11 to 17 (equivalent to Secondary school Form 5 level to post-graduate level, respectively in Malaysia). This disagrees with McCure’s (1987) proposal that legal documents such as insurance policies should be written at a readability level no greater than the ninth grade level as evaluated by the FKG formula. It is very important to note that all the formulae used as the instruments of analysis are meant for native English-speaking policy holders. And even by their standard, the level of readability is considered difficult to read because their level of comprehension is based on a few factors including the strategies used when dealing with the text (Gahari & Basanjideh, 2015). Earlier study by Harding (1967) on the readability of the automobile insurance policy opined that the policies were beyond the reading ability of a significant percentage of American adults. Hence, since this policy is written for Malaysian citizens whose English is mostly their second or foreign language, it can be said that the text readability level for them is more than ‘very difficult to read’. It is doubtful that the policy holders, especially those with low level of English proficiency, are able to comprehend the content of the policy.

As for items in Policy B, the readability consensus ranges from ‘standard/average’ (investment of return) to ‘very difficult to read’ (product illustration) with grade level 5 to 17 (equivalent to Primary school Standard 5 level to post-graduate level, respectively in Malaysia). The analysis shows that the ‘investment rate of return’ item has the ‘standard/ average’ level of readability, promising a relatively easier understanding of the text compared to the other items. However, as mentioned earlier, it is important to note that the level of standard or average here is meant for the native speaker of English. Thence, the local policy holders, with English most probably being their second or foreign language may still not find it easy to comprehend what is being written in the policy. As put forward by Robert Hunter, an insurance director at the Consumer Federation of America, even policies “written in plain English are above the average person’s grade level. There are so many twists and turns in the language that you can read through the whole policy and not understand it” (in Scott, 2023).

The Lexical Density of the Insurance Policies

The analysis indicates that the overall lexical density of the two policy documents is between ‘average density’ and ‘above average density’ levels. This suggests that the policies contain more or less the same amount of content words and function words. The following section presents the analysis of each policy in detail.

Policy A

The same data from the eight sections used in the readability analysis were scrutinized for their lexical density measurement, that is, ‘contribution waiver endorsement’, ‘basic definitions’, ‘fund provision’, ‘ownership provisions’, ‘supplementary contract provisions’, ‘critical illness selection provisions’, ‘claim procedure’, and ‘type of contract’. Table 5a reports the lexical density of each section.

Table 5a: Lexical Density of Policy Document A

Policy B

Data from the four sections used in the readability analysis were examined for their lexical density measurement, namely, ‘product disclosure’, ‘product illustration’, ‘investment rate of return’, and ‘death and disability benefit’. Table 5b reports the lexical density of each section.

Table 5b: Lexical Density of Policy Document B

The analysis shows that Policy A has five items with ‘average’ lexical density level and three items with ‘above average’ lexical density level (refer to Table 5a). All the four items in Policy B, on the other hand, have ‘above average’ lexical density level (refer to Table 5b). These ‘average’ and ‘above average’ levels of lexical density suggest that the policies represent a balance between accessibility and details of their contents. This is because the policies contain a balance number of content words that can provide greater concentration of information with function words that can contribute to the meaning of the texts.

However, such contention can be wide off the mark. The policies can still be challenging to read and comprehend as the content may become obscure by the abundance of words that may be unfamiliar to laymen readers. Content words like ‘lapse’, ‘exclusion, ‘return’, ‘maturity’, ‘pure’, and ‘provision’, though familiar would carry different meaning when used as legal terms in the policies. Similarly, unfamiliar function words used in the policies instead of their simple equivalence can make the texts incomprehensible. Function words like ‘notwithstanding’ for ‘however’, or  ‘in lieu’ for ‘instead of’ can also contribute to the challenge of understanding the text. Rosemblat, Logan, Tse and Graham (2006) in their study on the influence of linguistic and stylistic features on the readability of health texts found that vocabulary is one of the features that attest the texts as readable for general audiences.

Having looked at both the readability and lexical density levels of the life insurance policy documents in Malaysia, it can be concluded that they may be incomprehensible to the policyholders; especially those whole English proficiency is not up to the level of English used in the documents. Content and functions words that are unfamiliar and less encountered in their daily life can contribute towards the incomprehensibility of the texts.

CONCLUSION

This study, although limited in its data, has shown that people’s understanding of the content of their insurance policy documents may be questionable. This is because the policy holders’ language background and reading skills may impact the readability of the documents. As attested by Scott (2023), the texts, sometimes, just presume that the readers have foundation knowledge of the topic, and this often leads to gaps in understanding.

In addition, the formulae used to evaluate the readability of the documents, which are based on the native English standard, still find that the documents as difficult to read. Since English is only a second or even a foreign language for most people in Malaysia, it is doubtful that the documents are comprehensible for many policyholders. They may only rely on what is explained by the insurance agents and may not understand what is covered and excluded in the policy. This indicates that policyholders with a low level of English language proficiency may find it difficult to understand the legal documentation that elaborate their powers and liabilities to the contract signed.

To avoid legal disputes between the insurance company and policyholders, it is imperative that the latter understand the content of their insurance policy. If English is to be maintained as the language of the documents, one step towards policyholders’ comprehension of their policy document is to mandate the incorporation of the use of readability formulae to assess the readability of any drafted policy. However, to use the available formulae might not help as they are based on the native-English standard. It is also imperative, therefore, for a readability formula or index for English as a second or foreign language to be developed.

Authors Declaration

The authors have declared that there is no conflict of interest in this article.

ACKNOWLEDGEMENT

This study is supported by Universiti Teknologi MARA Pahang, Malaysia, under the Internal Grant Scheme (Dana Khazanah Alam), Project No. 600-TNCPI 5/3/DDN (06) (/2022)

REFERENCES

1. Arkell, R.N & van Dyck, H.C. (1978). Readability of Human Rights Material. Canadian Community Law Journal–Revue Canadiennede Droit, 2, 12–14.
2. Bakar, A. S & Ameer, R. (2011). Readability of corporate social responsibility communication in Malaysia. Corporate Social Responsibility and Environmental Management, 18, (1), 50–60.
3. Bailin, A., & Grafstein, A. (2016). Readability: Text and content. Macmillan: Hofstra University.
4. Barczuk-Grędzińska, K. (2015). The Usefulness of Readability Formulas in the Insurance Industry. Olsztyn Economic Journal. 10. 339-351. 10.31648/oej.3157.
5. Berger, L. A. (1988). Word-of-mouth reputations in auto insurance markets. Journal of Economic Behavior and Organization, 10(2), 225-234.
6. Brown, J. D., Janssen, G., Trace, J., & Kozhevnikova, L. (2012). A Preliminary Study of Cloze Procedure as a Tool for Estimating English Readability for Russian Students. Second Language Studies, 1-22.
7. Courtis, J. K, & Courtis, J. K. (2006). Readability of annual reports: Western versus Asian evidence. Accountability Journal, 8, (2), 4–17.
8. Courtis, J.K & Hassan, S. (2002). Reading ease of bilingual annual reports. The Journal of Business Communication, 394–413.
9. Cude, B. (2005). Insurance disclosures: An effective mechanism to increase consumers’ market power? Journal of Insurance Regulation, 24(2), 57-80.
10. Dale, E. & Chall, J. S. (1949). The concept of readability. Elementary English, XXVI (1), 19-26.
11. DuBay, W. H. (2004). The principles of readability. Impact Information: Costa Mesa.
12. Elgobshawi, A. E. & Aldawsari, M. (2022). Lexical density as improvement indicator in the Written Performance of EFL majors. International Journal of English Language and Literature Studies, 11. 4, 181-190.  DOI: 10.55493/5019.v11i4.4668
13. Fitzsimmons, P., Michael, B., Hulley, J. & Scott, G. (2010). A readability assessment of online Parkinson’s disease information. J R Coll Physicians Edinb. 40 (4): 292–6.
14. Flesch, R. (1948). A new readability yardstick. Journal of Applied Psychology, 32, 221-233.
15. Ghahari, S., & Basanjideh, M. (2015). Dynamics of Strategies-Based Language Instruction: A Study of Reading Comprehension and Problem-Solving Abilities via Structural Equation Modeling. RELC Journal: A Journal of Language Teaching and Research, 46 (3), 237-253. http://dx.doi.org.proxy.mau.se/10.1177/0033688215595713
16. Gopal, R., Maniam, M., Madzlan, N. A., Shukor, S. S., & Neelamegam, K. (2021). Readability formulas: An analysis into the reading index of prose forms. Studies in English Language and Education, 8(3), 972-985.
17. Halliday, M. A. K. (1985). Introduction to functional grammar. London: Edward Arnold.
18. Harding, F. E. (1967). The Standard Automobile Insurance Policy: A Study of Its Readability. The Journal of Risk and Insurance, 34(1), 39–45. https://doi.org/10.2307/251015
19. Ismail, A., Yusof, N. & Yunus, K. (2016). The Readability of Malaysian English Children Books: A Multilevel Analysis. International Journal of Applied Linguistics and English Literature. 5(6), 214-220.
20. Kincaid, J. P., Fishburne, R.P., Rogers, R.L. & Chissom, B. S. (1975). Derivation Of New Readability Formulas (Automated Readability Index, Fog Count and Flesch Reading Ease Formula) For Navy Enlisted Personnel. Research Branch Report: Institute for Simulation and Training.
21. Klare, G. R. (1963). The measurement of readability. Iowa State University Press: Ames.
22. Li, X., & Zhang, H. (2021). Developmental features of lexical richness in English writings by Chinese L3 beginner learners. Frontiers in Psychology, 12, 752950. https://doi.org/10.3389/fpsyg.2021.752950.
23. Lin, X., Bruhn, A., & William, J. (2019). Extending financial literacy to insurance literacy: A survey approach. Accounting & Finance, 59, 685-713. Mass. Gen. Laws ch. 175 sec. 2B. 2014.
24. McClure G (1987). Readability formulas: Useful or useless. (an interview with J. Peter Kincaid.). IEEE Transactions on Professional Communication. 30, 12–15.
25. McLaughlin, G. H. (1969). SMOG grading: A new readability formula. Journal of Reading, 22, 639-664.
26. Nasseri, M. & Thompson, P. (2021). Lexical density and diversity in dissertation abstracts: Revisiting English L1 vs. L2 text differences. Assessing writing, 47, 100511, https://doi.org/10.1016/j.asw.2020.100511.
27. Pourkiani, M., Chegini, G. M., Yousefi, S., & Madahian, S. (2014). Service quality effect on satisfaction and word of mouth in the insurance industry. Management Science Letters, 4, 1773-1780.
28. Richards, J. C., Platt, J., & Platt, H. (1992). Longman dictionary of language teaching and applied linguistics. London: Longman.
29. Richards, J.C. and Schmidt, R. (2002) Longman Dictionary of Language Teaching & Applied Linguistics (3rd edition). Essex: Pearson Education Limited.
30. Richards, Jack C., & Schmidt, Richard W. (2010). Longman Dictionary of Language Teaching and Applied Linguistics (4th ed.). Harlow: Longman.
31. Rosemblat G, Logan R, Tse T, Graham L. (2006). Text Features and Readability: Expert Evaluation of Consumer Health Text. Mednet. October 14-16. https://lhncbc.nlm.nih.gov/LHC-publications/PDF/pub2006029.pdf
32. Ruohonen, J. (2021, July). Assessing the Readability of Policy Documents on the Digital Single Market of the European Union. In 2021 Eighth International Conference on eDemocracy & eGovernment (ICEDEG). IEEE, 205-209.
33. Scott, B. (2023).  Why Should the Insurance Industry Use Readability Formulas? Retrieved from https://readabilityformulas.com/why-should-the-insurance-industry-use-readability-formulas/
34. Scriven, D. (2008). Guide to life protection and planning (2nd ed.). Sydney, Australia: CCH Australia Limited.
35. Schwarcz, D. (2010). Regulating insurance sales or selling insurance regulations? Against regulatory competition in insurance. Minnesota Law Review, 94, 1707-1788.
36. Sjahrony. A., Lubis, M.A & Baharudin, H. (2018). The Readability of Arabic Textbooks Among University Students in Malaysia Based on the Cloze Test. Journal of Computational and Theoretical Nanoscience, 24(1),443-446.
37. Tennyson, S. (2011). Consumers’ insurance literacy: Evidence from survey data. Financial Service Review, 20, 165-179.
38. Ure, J. (1971) Lexical Density and Register Differentiation. Contemporary Educational Psychology, 5, 96-104.
39. Uri, N. F. M., & Abd Aziz, M. S. (2018). Assessing readability of a national exam reading texts in Malaysia. European Journal of English Language Teaching.
40. Westwood, P. (2001). Reading and learning difficulties approaches to teaching and assessment. Victoria: Polar Design Pty Ltd.