This is a sequential exploratory mixed-method study, with the qualitative-quantitative sequencing design (Fig. 1). In the qualitative phase, the concept of infertility stigma will be explored based on infertile female experiences and literature review and then, the primary items of F-ISQ would be developed. In the second phase (the quantitative phase), the psychometric properties of the questionnaire would be assessed.
The qualitative phase
This phase of the present study will be carried out using a qualitative content analysis method. This study is designed to answer the following question “What is the concept of infertility stigma in infertile women?”
Data will be collected through in-depth semi-structured interviews with infertile women and taking field notes. women who are eligible for participating in the study will be selected using purposeful sampling method with maximum variation in terms of age, education, occupation and infertility duration. While collecting the data, the interviews will be analyzed using a conventional qualitative content analysis method(25). In qualitative studies, sample size is unpredictable and sampling will be continued until data saturation occurs(26).
Characteristic of the participants
Study population consists of women with known primary female infertility who had experienced infertility whithout any psychological disorder. Women who refer to Isfahan fertility and infertility centre, Isfahan, Iran, will be enroled in the study voluntarily and with informed consents.
The interviews will be conducted individually at selected time and location by the participants; also a private room in Isfahan fertility and infertility centre will be considered for the interviews due to its accessiblity, comfort and ease of use for the participant.
Content analysis with conventional approach will be utilized along with data collection through the Graneheim and Lundman approach (2004)(27). Transcription, analysis and coding of each interview will be performed before the beginning of the next interview. Codes, sub- categories, categories and themes will be derived from the transcripted data. The combinations of related initial codes will be labeled to form sub-categories and categories. Finally, the latent meaning of the text and the main themes will be extracted by consensus between researchers, until the concept of stigma in infertile women will be obtained. The extracted themes and main categories, besides the existing literature and instruments, will be used to generate the primary item pool for F-ISQ.
The quantitative phase
This phase of the study will evaluate the psychometric criteria of F-ISQ including content, face and construct validity, as well as reliability (internal consistency and stability).
Content validation plays a primary role in the development of any new instrument.The qualitative and quantitative methods will be used to determine the content validity of F-ISQ.
In the qualitative content validity method, the opinions of ten experts in the field of qualitative research, instrument development, Psychology, midwifery and reproductive health will be used to assess the proper grammar, appropriate and correct words and items’ scoring. Quantitative content validity will be evaluated by the content validity ratio (CVR) and content validity index (CVI)(28).
For CVR calculation, experts will be invited to assess item essentiality. The score of each item would be considered within a three-degree range of “not essential, useful but not essential, essential” from 1 to 3 points. CVR varies between 1 and − 1. Higher scores indicate further agreement of the experts on the essentiality of an item in a tool. The formula is:
CVR= (Ne - N/2)/ (N/2).
Ne = the number of experts indicating "essential"
N = the total number of experts
The total score of CVR is determined by Lawshe table (1975) and based on the number of the expert(29). In this study 10 experts will be attended, so any item with a CVR of more than 0.62 will be accepted.
CVI is the most widely reported index for quantitative content validity in tool development (30). CVI can be computed using the Item-CVI (I-CVI) and the Scale level-CVI (S-CVI). Experts are asked to rate the relevancy of each item on a 4-point scale from 1 to 4 respectively (not relevant, somewhat relevant, quite relevant, highly relevant). I-CVI will be computed by dividing the number of experts giving a rating score of either 3 or 4 by the total number of experts. Values of CVI more than 0.79 would show the item is relevant (31). Average of the I-CVIs for all items on the scale will be assessed by S-CVI via mean scores for content validity index. S-CVI values of greater than 0.9 indicating that have excellent content validity(32).
The face validity of this study will be assessed by quantitative and qualitative method.
In the qualitative approach, 10 face-to-face interviews would be conducted with the target group and the difficulty level, proportion and ambiguity of the items would be examined. After correction, the quantitative approach will be perfromed. Quantitative face validity assessment will be done via the item impact measurement technique. 10 infertile women will score the importance of each item with a 5-point Likert scale, from slightly important (score1) to very important (score 5). The item impact score is calculated by the following formula:
Impact Score = Frequency(%) × Importance
Importance = Patients who will check the options 4 and 5
The impact score of more than 1.5 will show that the item is acceptable and will be chosen for further analysis(33).
Exploratory factor analysis (EFA) will be used to evaluate the construct validity and extract the latent constructs of F-ISQ(34).
Sampling and Sample size
Study population will consist of the women who referred to Isfahan Fertility and Infertility Center with known primary female infertility, had experienced infertility whithout any psychological disorder.
The sample sieze would be based on the number of items extracted at the first phase of the study. The number of samples is relevent to the number of items and the proportion of N/K should not be less than 5/1 (26). Therefore, the number of samples would be calculated based on the extracted items and to the maximum. At this phase, sampling would be conducted using convinient sampling method.
Statistical data analysis
In order to evaluate the adequacy of sampling to perform exploratory factor analysis, sample size is important, so KMO test and Bartlett's sphericity test will be used to confirm the adequacy of sampling in EFA. The KMO index ranges from 0 to 1. KMO more than 0.7 is interpreted as acceptable and large sample size that is suitable for EFA(28, 34).The Bartlett's Test of Sphericity should have significant results (p < 0.05). To determine the best structure, the eigenvalue greater than one and with factor loading equal to or greater than 0.4 will be applied(35).
Moreover, statistical analyses will be performed by running exploratory factor analysis, Pearson correlation analysis, Cronbach’s alpha model, intraclass correlation coefficient and standard error measurement (34). All the statistical calculations would be performed using SPSS software and for all the tests a maximum error of 5% will be accepted.
Internal consistency and stability will be used to verify the reliability of F-ISQ.
Internal consistency would be estimated by computing Cronbach’s alpha coefficient for F-ISQ and its subscales. The alpha values of 0.70 or above would be considered acceptable.
Test-retest reliability of F-ISQ and its subscale for two-week interval will be estimated by intraclass correlation coefficient (ICC). ICC values of 0.7–0.8 will be considered as having suitable stability(28, 34). Items that do not have good reliability will not be included in factor analysis to check the construct validity. The psychometric properties described in the COSMIN (consensus-based standards for the selection of the health status measurement instrument) (36)checklist will be utilized for designing the instrument.