Postmenopausal Infertile Women Experience

Material and Methods
This is a qualitative study of postmenopausal infertile women experience. The phenomenological study would assess the experiences of postmenopausal infertile women, understanding their needs and improve their quality of services. Therefore, the present study was performed as phenomenology study. We have conducted 17 semi-structured individual interviews to achieve the experience of the participants. Study participants were postmenopausal infertile women with an age range from 48 to 65 years with mean age of 54.41 ± 4.34 years. Table 1 presents the demographic characteristics of study participants.

Characteristics
Age* 54.41 ± 4.34
Job**

Housewife
Tailor
Marketer
Retired employee
Barber

12(70.6)
1(5.9)
2(11.8)
1(5.9)

The participants met the inclusion criteria, including primary infertility and failure to conceive after at least one year of unprotected sex, identification of self as being infertile; at least one year after the start of menopause and natural menopause (without surgery or drugs or chemotherapy). In the qualitative studies, the sample size of the study is not intended. Therefore, in this study there were no restrictions on sample size and sampling was performed until data saturation. Data saturation in the process of receiving new data to the previous data replication and

Data collection continued until saturation was reached. The interviews were transcribed into text by the interviewer shortly after it was conducted.
Data analysis was carried out for the purpose of research based on the description of the participants in the study in 8 steps, including (17);
1- Prepare the data (type of interviews).
2- The meaning units (specific words, sentences or paragraphs from the speech of participants).
3- Text encoding (converting units of semantic tags, which reflect a summary of selected units).
4- Revision of the text codes (over again, comparing the similarities and differences between the codes and then integrate the same code).
5- Categories based on similarity and proportion of classes.
6- Revision class and compare this data to ensure the reliability of the code.
7- Identification of themes reflecting the