The differential item functioning (DIF) testing for the WOCC (Ways of Coping Checklist) instrument based on gender

Abstract

This study examined the Item Response Theory (IRT) method with statistical analysis to determine Differential Item Functioning (DIF) between men and women on the Ways of Coping Checklist (WOCC) Instruments revised by Vitaliano, Russo, Carr, Mauiro, and Becker (1985). Furthermore, it utilized primary data from 722 respondents with educational backgrounds ranging from senior high school, diplomas, and doctorates. The software packages QUEST, BILOG-MG, LISREL, and ITEMAN were used for analysis to address the concerns. Meanwhile, several items on the WOCC instrument indicated the presence of the DIF based on the calculation results using the IRT method with the QUEST and BILOG-MG software. According to the overall calculation for 1 PL and 2 PL using both tools, 8 items containing the DIF are distributed over the dimensions of problem solving, seeking social support, blaming self, and wishful thinking.

1. Introduction

Individuals reach young adulthood when they have completed their development and are prepared to assume a position in society alongside other adults [1]. The division of maturity, according to Hurlock [1], is based on both physical and psychological changes. The individual's physical condition is at its peak at this age. Complexity of cognitive functioning and moral judgments [2]. Together with these alterations, challenges emerge that necessitate adjusting to new pressures and expectations [1]. Individuals will experience stress if they are unable to successfully adapt to pressure. Stress can have various negative clinical effects on individuals, social environments, and organizations, resulting in losses. It is frequently defined in popular parlance as an external element that creates pressure.

According to Atwater [3], stress is any adjustive demand that requires an adaptive response. Another definition comes from Haber and Runyon [4], where stress is conflict, internal and external pressure, and other troublesome conditions in life. Selye [5] reported that the environment contains factors known as stressors. An individual is motivated to take action in adapting to the stressor when confronted. According to Holmes and Rahe [6] numerous factors contribute to stress, and the changes in an individual's life circumstances can result in a crisis. Furthermore, daily reoccurrences can be a source of stress [7] and annoyance originates from various factors, including incompatible relationships, brief unpleasant circumstances, and little but significant effects in life.

Everyone will attempt to adapt in order to escape difficult events and settings. A person is coping if he/she makes adjustments to overcome difficult situations and surroundings. Coping is the process of managing internal demands that are taxing or even overwhelming [7]. Identifying individuals at risk for developing these problems is essential to mitigate the negative effects. A reliable approach is using a psychological assessment instrument to determine stress levels. Specifically, there are few psychological tests designed to measure these levels. The Ways of Coping Checklist (WOCC) is one of the available psychological tests for determining coping strategies. The WOCC is a tool for determining which coping mechanisms an individual employs. The counseling process might employ information about a person's typical coping skills to assist that individual in escaping their stressful environment. The WOCC was originally derived from Lazarus [8,9]. This measuring device was revised by Vitaliano et al. [10]. The WOCC comprises 42 items distributed across five subtests, namely problem-focused, seeking social support, self-blame, wishful thinking, and avoidance, with 15, 6, 3, 8, and 10 items, respectively. The instrument is a popular measurement tool used in study on coping strategies or a clinical context [10].

There are distinctions between men and women regarding coping mechanisms, and this disparity results from differing role expectations. According to Keller [11], women are better at expressing their feelings directly but more readily discouraged. However, men are thought to be more capable of controlling emotions than women, except when angry [12]. Therefore, this study aims to determine the different responses to items in the WOCC instrument when employing the Differential Item Functioning (DIF) technique.

Bias-free and unidimensional goods are desirable and should be recognized that any instrument, including the WOCC, has the potential for bias in its creation. Bias can develop due to inequalities in gender, race, locality, socialization, and educational opportunity. The DIF can assist in explaining reasons the estimated value deviates from the true value. With information about an item's possible bias made available through the DIF technique, errors in drawing inferences and interpreting instrument measurement data can be avoided. Numerous studies already investigated item bias induced by factors such as gender, culture, ethnic origin, religion, and social situation [13]. Wainer et al. [14] also investigated gender-based item prejudice. Bleistein and Wright [15] also Angoff [16] researched item prejudice caused by ethnic characteristics.

According to Osterlind and Everson [17], bias analysis can be performed using the Item Response Theory (IRT) method by comparing the slope and threshold values. Furthermore, the DIF is demonstrated when the item responses of two distinct groups are not identical. A bias is an erroneous inclination to draw conclusions based on incomplete or incorrect information. In another sense, it exhibits a DIF when the minority and majority groups perform differently on the item.

According to Hambleton et al. [18], a question demonstrates the DIF when the subject possesses the same capacity across groups but does not possess the same likelihood of successfully answering the items, which is a significant concern in a test. Items considered good are free of bias, have a single function, or are unidimensional [18].

There will be disparities in respondents' results in all test activities between groups and individuals. Differences in results across respondents may suggest that they have varying talents in the areas disclosed by the test. Exam score disparities between respondents can be explained by various variables other than variations in talents. According to Camili and Sephard [19], bias is a systematic inaccuracy that works against the best performance of one group. Although certain irrelevant sources of variation in test scores are unavoidable, respondents' test scores may be systematically influenced by group differences. For example, respondents from some groups consistently score worse on tests than others. Test bias occurs when this disparity is driven by variables unrelated to the tested ability. Furthermore, test bias refers to the disproportionate advantage that one group enjoys over another.

According to Embretson and Reise [20], an IRT model can also be seen based on assumptions, and the distribution used is the logistic and the ogive model. For the logistic model, there are three parameters to detect the DIF. It is recommended to use these models, namely models 1, 2, and 3 PL look at the index of difficulty, differential power and difficulty, and multiple choice questions to determine the guessing index [20]. In the WOCC instrument, the parameters used to identify the DIF will be 1 and 2 models. This is because responses on a Likert scale are not assigned true or false weights, and the potential of guessing is nearly non-existent, hence, testing with a three-parameter model is deemed excessive.

Concerning validity research, the word and analysis of the DIF are fairly popular. This study aims to compare the relative performance of vocal groups of interest namely gender bias on WOCC. Numerous studies on this bias have been conducted as stated before, and it is frequently shown that culture, gender, ethnic origin, and socioeconomic status have a role. The IRT approach combined with the DIF detection analysis can determine the bias indicating differences in men's and women's responses to items in the WOCC instrument. DIF will be detected using QUEST and BILOG-MG software. QUEST offers three estimation methods for item difficulty: delta, tau, and threshold [21]. In this study, the delta estimation will be utilized. The delta item parameter belongs to the delta category. One delta is provided for each step and represents the conditional probability of a change in one step given the skipped preceding step. In accordance with model (1), the category delta for step j is δ_i + τ_ij. The DIF detection technique using BILOG-MG can be seen from the adjusted threshold values, which state the differences in the threshold values of each group for each item, and the group threshold differences values, which express the differences in the threshold values of each group for each item [22]. DIF can be detected through chi-square (χ²) statistics and t-test statistics. Due to the constraints of the software, this study will convert polytomous data to dichotomous data used to detect the DIF [22]. This subject is considered given the scarcity of the DIF study on polytomy data and tools that measure stress in Indonesia. However, when testing polytomy data using software designed for dichotomous, there is a danger of analytical error. The reduction technique is predicted to lower the likelihood of analysis error. Additionally, this study can serve as a springboard for other Indonesian scholars interested in conducting additional investigations on the DIF theme for polytomous data. QUEST, BILOGMG, LISREL, and ITEMAN will be employed for analysis purposes to address this challenge.

2. Study method

The sample consisted of men and women in their early to middle adulthood, specifically between the ages of 24 and 53, with educational levels ranging from High School to Doctorate Degree, as can be observed in Table 1's distribution of data on level of education by gender. The above age range was selected because young adulthood is the group most likely to encounter stressful events. At this age, new role expectations arise, and creates pressure, leading to stress when incomplete. As a result, extra effort is required at this age to adjust to coping mechanisms. This study is limited to middle adulthood with a minimum high school education level to collect more accurate data. With these features, respondents should be able to comprehend the questionnaire meaning better and respond correctly. All procedures involving human participants in this study complied with the institutional and/or national research committee’s ethical standards (the Code of Professional Ethics for Psychologist and Psychology scientist, Indonesian Psychological Association [HIMPSI]), as well as the 1964 Helsinki declaration and its subsequent amendments or comparable ethical standards. Furthermore, informed consent was obtained from all participants for this study. The following Table 1 details the sample used in this investigation.

Table 1.

Respondents’ demographics.

Gender	Educational Level					Total
	High School	Diploma	Bachelor	Master	Doctorate
			Undergraduate	Graduate	Post Grad
Men	95	72	240	42	1	450
Women	43	48	155	26	0	272
Total	138	120	395	68	1	722

Respondents were given questionnaires based on the WOCC and then asked to indicate their response to polytomy data at five Likert points, namely: 1 = Not relevant to be conducted in overcoming the situation, 2 = Relevant, but I do not do it in dealing with the situation, 3 = I rarely do in dealing with the situation, 4 = I frequently do in dealing with situations; and 5 = I always do in dealing with situations. As stated in the background, the response to polytomy was restricted to a dichotomy due to the software's constraints. The first, second, and third responses were recorded as 0, while the fourth and fifth were recorded as 1. Furthermore, the analysis was conducted in the following steps.

• 1.Psychometric characteristic tests were performed by comparing questionnaire data from men and women while continuing to use the polytomy scale. This test was conducted on each dimension of the WOCC instrument with the assistance of the ITEMAN software.
• 2.Additionally, it was continued with a unidimensionality using CFA for each dimension and, as a whole, allowing for the observation of interactions between latent variables of both first and second order using a polytomy scale.
• 3.Finally, this study obtained the DIF between men and women by converting polytomy data to dichotomous (0 & 1) using QUEST (Rasch Model) and BILOG-MG (model 1 and 2 PL). Individual responses to the WOCC instrument were classified into five categories (Vitaliano, Russo, Carr, Mauiro, & Becker, 1985). Respondents were instructed to cross out the number 1, 2, 3, 4, or 5 next to each item that corresponded to one of the potential answers, namely 1. Not relevant to dealing with the problem, 2. Relevant, but I do not do it when dealing with the situation, 3. I seldom do when dealing with situations, 4. I frequently do when dealing with situations, and 5. I always do when dealing with situations. Answer choices 1, 2, and 3 on a frequency continuum were options in which individuals do not employ exposure to overcome circumstances. Therefore, they were included in a response group coded 0, and the answers 4 and 5 combined. The frequency continuum was a decision in which individuals frequently employ exposure to goods to overcome obstacles and be included in a response group recorded to 1. According to Creswell and Creswell [23] positive responses to items can be given a larger weight than negative responses, such as disagree, never, etc.

3. Findings and discussion

The following Table 2 summarizes the general psychometric properties of the polytomy data (original data) on the WOCC instrument using a statistical scale developed from the ITEMAN.

Table 2.

Psychometrics characteristics of the WOCC between men and women.

Parameters	Men					Women
	Problem Focused	Seeks Social Support	Blamed Self	Wishful Thinking	Avoidance	Problem Focused	Seeks Social Support	Blamed Self	Wishful Thinking	Avoidance
N of Items	15	6	3	8	10	15	6	3	8	10
N of Examinees	450	450	450	450	450	272	272	272	272	272
Mean	3.838	3.597	2.361	3.003	2.560	3.845	3.675	2.286	3.136	2.585
Variance	0.203	0.388	0.991	0.486	0.401	0.316	0.459	0.954	0.661	0.468
Std. Dev.	0.450	0.623	0.996	0.697	0.633	0.562	0.678	0.977	0.813	0.684
Skew	−0.536	−0.348	0.428	−0.153	0.120	−0.943	−0.809	0.238	−0.433	0.189
Kurtosis	2.038	0.813	−0.432	0.002	−0.079	2.209	1.368	−0.977	−0.001	−0.302
Minimum	1.786	1.000	1.000	1.000	1.000	1.400	1.000	1.000	1.000	1.000
Maximum	5.000	5.000	5.000	5.000	4.700	5.000	5.000	5.000	5.000	4.600
Median	3.867	3.667	2.333	3.000	2.500	3.867	3.833	2.333	3.250	2.500
Alpha	0.774	0.750	0.801	0.761	0.753	0.857	0.807	0.825	0.837	0.782
SEM	0.214	0.312	0.444	0.340	0.315	0.213	0.298	0.409	0.328	0.319
Mean Item-Tot.	0.513	0.672	0.846	0.610	0.556	0.595	0.719	0.861	0.682	0.576

Table 2 shows that the minimum, maximum, mean, and median values do not differ significantly between the men and women groups or are almost identical. This demonstrates that men and women respond almost equally to items in the WOCC. From the mean and median values, which are close to a score of 4, respondents tend to respond positively to the dimensions of problem-solving, seeking social support, and wishful thinking. The dimensions of blamed self and avoidance indicate that the responses to specific items tend to be negative, as indicated by the mean and median values found in score 2.

From the skew value, it can be seen that there is a negative slope in the dimensions of problem solving, seeking social support, and wishful thinking which shows the score is at the top of the distribution of scores in both men and women groups. This supports the analysis conducted on the mean and median values in the previous group of men and women that men's and women's responses to these three dimensions tend to be positive. In contrast, the skew values on the blame self and avoidance dimensions show positive values in both the male and female data groups which indicate the score is at the bottom of the score distribution. This fact also supports the previous analysis of the mean and median in men and women that men's and women's responses to both dimensions tend to be negative.

Considering the kurtosis value, which shows the scores' sloping distribution, in a men group shows a positive kurtosis, with a peak more taper of the dimension of problem-solving, seeking social support, and wishful thinking. The blamed self and avoidance dimensions show negative values, which are equally sloping. Furthermore, the kurtosis value for the men group similarly indicates mean, media, and skewness. The value in the women group is positive, more taper or peak for dimensions of problem solution and seeking social support. Negative kurtosis value that is more evenly sloping for blamed self and wishful thinking dimension. Therefore, the kurtosis value in the wishful thinking dimension for the women group indicates a different value from mean, median, and skewness.

This instrument measures homogeneity by gender, with a greater level (>0.80) for women than men (>0.70). This alpha value suggests that the measurement error in the men group was higher than the women group.

4. Unidimensionality testing

Items considered good are free of bias, have a single function, or are stated to be unidimensional (Swaminathan, Hambleton, & Rogers, 1991). The following Table 3 exhibit the results of the unidimensionality test using the CFA approach for each dimension of the WOCC.

Table 3.

WOCC unidimensionality test results.

No	Item	1	2	3	4	5	6
	Problem Focused	-	0,05714	0.020	0.98	0.97	0.99
1	Bargained or compromised to get something positive from the situation.	0.29	–	–	–	–	–
2	Concentrate on something good that could come out of the whole thing.	0.51	–	–	–	–	–
3	Tried not to burn my bridges behind me, but left things open somewhat.	0.51	–	–	–	–	–
4	Changed or grew as a person in a good way.	0.49	–	–	–	–	–
5	Made a plan of action and followed lt.	0.73	–	–	–	–	–
6	Accepted the next best thing to what I wanted.	0.59	–	–	–	–	–
7	Came out of the experience better than when I went in.	0.61	–	–	–	–	–
8	Tried not to act too hastily or follow my own hunch.	0.06	–	–	–	–	–
9	Changed something so things would turn out all right.	0.44	–	–	–	–	–
10	Just took things one step at a time.	0.54	–	–	–	–	–
11	I know what had to be done, so I doubled my efforts and tried harder to make things work.	0.65	–	–	–	–	–
12	Came up with a couple of different solutions to the problem.	0.65	–	–	–	–	–
13	Accepted my strong feelings, but didn't let them interfere with other things too much.	0.54	–	–	–	–	–
14	Changed something about myself so I could deal with the situation better.	0.50	–	–	–	–	–
15	Stood my ground and fought for what I wanted.	0.18
	Seeks Social Support		0.09368	0.035	1.00	0.98	1.00
16	Talked to someone to find out about the situation.	0.57	–	–	–	–	–
17	Accepted sympathy and understanding from someone.	0.66	–	–	–	–	–
18	Got professional help and did what they recommended	0.56	–	–	–	–	–
19	Talked to someone who could do something about the problem.	0.66	–	–	–	–	–
20	Asked someone I respected for advice and followed it	0.57	–	–	–	–	–
21	Talked to someone about how I was feeling.	0.52	–	–	–	–	–
	Blamed Self	-	1.00	0.00	1.00	1.00	1.00
22	Blamed yourself	0.83	–	–	–	–	–
23	Criticized or lectured yourself.	0.90	–	–	–	–	–
24	Realized you brought the problem on yourself.	0.59	–	–	–	–	–
	Wishful Thinking	–	0.0851	0.030	0.99	0.98	1.00
25	Hoped a miracle would happen.	0.56	–	–	–	–	–
26	Wished I was a stronger person - more optimistic and forceful.	0.44	–	–	–	–	–
27	Wished that I could change what had happened.	0.54	–	–	–	–	–
28	Wished I could change the way that I felt.	0.58	–	–	–	–	–
29	Daydreamed or imagined a better time or place than the one I was in.	0.64	–	–	–	–	–
30	Bad fantasies or wishes about how things might turn out.	0.63	–	–	–	–	–
31	Thought about fantastic or unreal things (like perfect revenge or finding a million dollars) that made me feel better.	0.66	–	–	–	–	–
32	Wished the situation would go away or somehow be finished.	0.38	–	–	–	–	–
	Avoidance	–	0.0717	0.024	0.99	0.98	0.99
33	Went on as if nothing had happened.	0.12	–	–	–	–	–
34	Felt bad that I couldn't avoid the problem.	0.49	–	–	–	–	–
35	Kept my feelings to myself.	0.45	–	–	–	–	–
36	Slept more than usual.	0.54	–	–	–	–	–
37	Cot is mad at the people or things that caused the problem.	0.60	–	–	–	–	–
38	Tried to forget the whole thing.	0.42	–	–	–	–	–
39	Tried to make myself feel better by eating, drinking, smoking, and taking medications.	0.46	–	–	–	–	–
40	Avoid being with people in general.	0.55	–	–	–	–	–
41	Kept others from knowing how bad things were.	0.68	–	–	–	–	–
42	Refused to believe it had happened,	0.57	–	–	–	–	–

Note: 1 = λ (loading factors >0.05); 2 = P-Value ≥0.05; 3 = RMSEA ≤0.08; 4 = GFI ≥0.90; 5 = AGFI ≥0.90; 6 = CFI ≥0.95.

Chi-square analysis should be used in conjunction with other test techniques when big samples (n > 200) are used. RMSEA, GFI, AGFI, and CFI are other test tools that can be used in place of the chi-square value. As observed from the overall dimensions in Table 3, the model results derived for RMSEA, GFI, AGFI, and CFI are deemed FIT with the data. Meanwhile, the results, particularly for the blamed self dimension, are saturated because the expected number of indexes exceeds the number of items. This index, as stated in Table 3 with each dimension's P-Value ≥0.05, RMSEA ≤0.08, GFI and AGFI ≥0.90, also CFI ≥0.95, can prove that the hypothesis of the WOCC instrument's unidimensionality in its five dimensions is valid and unidimensional.

5. The differential item functioning (DIF) detection

The DIF results obtained using the QUEST and BILOG MG program showed the presence of multiple items, with p-value <0.05 (Ho rejected, b1 # b2), as reported in the following Table 4.

Table 4.

Items with the DIF indication.

Item Number	Item	QUEST				BILOG-MG
		δ		χ2	P-Value	1 PL	2 PL
		Men	Women
	Problem Solving
5	Made a plan of actlon and followed lt.	−2.02	−1.52	4.81	.03	2.208
12	Came up with a couple of different solutions to the problem.	−2.18	−1.70	4.11	.04
14	Changed something about myself so I could deal wlth the situation better.	−1.45	−1.03	4.51	.03	2.091
	Seeks Social Support
21	Talked to someone about how I was feeling.	.53	−.31	24.06	.00	−4.813	−4.448
	Blamed Self
23	Criticized or lectured yourself.					2.022
	Wihsful Thinking
25	Hoped a miracle would happen.	1.91	1.24	11.65	.00	−3.421
26	Wished I was a stronqer person - more optimistic and forceful.	−.42	−.84	5.43	.02	−2.286
30	Bad fantasies or wishes about how things might turn out.	.92	.52	5.41	.02	−2.313	−1.988

Note: δ = b = the difficulty index; χ2 = chi-square; P-Value <0.05 (Item with the DIF).

As a consequence of the analysis performed with the QUEST software, it is clear that seven components as illustrated in Table 4 describe the DIF value. Within the problem solving dimension, items 5, 12, and 14 have a negative value, indicating that the difficulty level appears larger for women respondents. This demonstrates that these items are frequently associated with ‘disadvantage’ for women respondents. In item 5, the line “made a plan” is most likely to have women responders have difficulty comprehending the sentence's meaning. Similarly, the sentences ”came up with a couple of different solutions” (item 12) and “changed something about myself” (item 14) can be interpreted differently by women respondents.

The most intriguing aspect is the distinction between positive and negative signs on item 21, where the chi-square has the highest index. Item 21 is a component of the social support dimension, with a higher index for men respondents. Therefore, a preliminary conclusion can be formed that it is likely to cause a ‘disadvantage’ for men. The keyword indicating a DIF is the term ‘feeling’, which is typically perceived differently by men. The term may be problematic, as the notion of ‘feeling’ varies significantly. Additionally, items 25, 26, and 30 exhibit the DIF and fall under the wishful thinking category. The difficulty index (δ) is larger for the men group on these three questions, indicating a greater difficulty or problem reading the item. The phrase “hoped for a miracle” (item 25) appears vague, and groups of men frequently struggle with this interpretation. Similarly, for items 26 and 30, the phrases “wished I was a stronger person - more optimistic and forceful” and “bad fantasies or wishes” allow men to perceive differently following their various gender roles.

Numerous items containing DIF were discovered in the QUEST and BILOG-MG calculation outputs for 1 PL and 2 PL. Items 21 (social support) and 30 (wishful thinking) strongly indicate the presence of the DIF, with this indication appearing in three different modes of computation, namely QUEST, BILOG-MG 1 PL, and 2 PL. Furthermore, items 25 and 26 are in the wishful thinking dimension. Although the computation using BILOG-MG for 2 PL is not reflected in the table, the index shows a value close to 1.96 (item 25; t-test = - 1864 and item 26; t-test = −1.941). Additionally, items 5 and 14 exhibit the DIF in two different calculation methodologies, namely QUEST and BILOG-MG for 1 PL. Distinct elements are observed in various calculating procedures, indicating the DIF. In the QUEST and BILOG-MG calculation, item 12 indicates the presence of the DIF. According to the overall calculation for 1 PL and 2 PL using both tools, 8 items containing the DIF are distributed over the dimensions of problem solving, seeking social support, blaming self, and wishful thinking.

6. Conclusion

The results using the IRT method with the QUEST and BILOG-MG software showed numerous items such as 5-12-14-21-23-25-26-30 in the WOCC instrument, indicating the DIF. The 8 items fall into four categories, namely problem solving, seeking social support, blamed self, and wishful thinking. The dimensions that contain the most DIF sequentially are problem-solving, wishful thinking, seeking social support, and blaming self.

The disparities in answers between men and women on each aspect are almost certainly due to the gender roles expected. According to the findings of Keller [11] and Pleck [12], women are more emotional than men when confronted with challenges. Additionally, Keller [11] found that they can express their feelings directly but are more readily discouraged. Men are thought to be more capable of controlling their emotions unless they become angry [12]. Based on these distinctions, views of coping techniques, including issue-solving, social support, or wishful thinking, may differ.

A more emotional woman capable of expressing her feelings directly is more likely to receive social support from the environment. Men are more energetic, autonomous, and aggressive than women [11,12]. Therefore, coping tactics involving problem-solving and social support systems vary based on the perspective and perception of each gender. This is evidenced by the rise of the DIF indications on WOCC instrument items 5, 12, and 14 for the problem-solving component and 21 for the social support dimension.

The predisposition of men to be more reasonable can influence their interpretation of difficulties. This can impact the understanding of items, resulting in distinct responses between men and women to wishful thinking coping techniques. The perceptual difference is most likely to result in the DIF signals on items 25, 26, and 30. Differences in self-concept between men and women [24] allow the reflection on self-blame coping methods. Therefore, there is a probability that they will answer differently, indicating a DIF on item 23 of the self-blame dimension.

Meanwhile, there is no indication of the DIF on any of the avoidance dimension's items. This demonstrates that men and women use the same avoidance coping mechanisms. From the basic psychometric description of the ITEMAN calculation, they respond differently to the avoidance dimension, with a mean value of +2. Therefore, avoidance coping methods are rarely used to solve difficulties.

7. Limitations and further study

In a further study on a similar issue, it is preferable to use specialized software designed for polytomy data to ensure that the calculation results to determine the indications of the DIF on items are precise. Additionally, users of the WOCC instrument exercise greater caution when scoring and interpreting items that exhibit the DIF. There is a chance that the interpretation of coping techniques based on the results of scoring men and women will be misleading, as certain items do not have an equal probability of reaction. To avoid misinterpretation, the instrument should be revised first, particularly in terms of content, and then subjected to psychometric tests, such as unidimensionality, item analysis, validity, reliability, and the DIF, to further improve the reliability and trustworthiness. In addition, future studies must pay attention to the number equality samples and demographic similarities, such as education level and occupation, between women and men, to ensure that the bias seen is indeed due to gender [25] difference and not other factors.

Author contribution statement

Arbania Fitriani: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Dominikus David Biondi Situmorang: Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement

Data will be made available on request.

Declaration of interest's statement

Dominikus David Biondi Situmorang has a position to declare and he is one of the members of the journal's Editorial Teams or Associate Editor, however this article is handled by another unknown Associate Editor and reviewed by the Reviewers objectively and double-blind, based on applicable regulations from Elsevier, Heliyon, and Cell Press.

Appendix A. Supplementary data

The following is the Supplementary data to this article.