DOI: 10.31038/IJNM.2024543

Abstract

Background: The perception and attitude of the general population and health-care workers towards psychiatric disorders have a direct effect on the outcome of these diseases. Negative perceptions and attitudes can lead to worse social facilities (such as employment, and housing), lower self-esteem, help-seeking behavior, as well as complications in receiving health care. Little information is available about the perception and attitude towards schizophrenia in Iran.

Methods: This study was conducted to evaluate the perception and attitude of the general population and medical students toward schizophrenia in Zanjan province, Iran. Several possible factors affecting perception and attitude were also evaluated. A descriptive-analytical cross-sectional study was conducted on 788 medical students and the general population of Zanjan province. A researcher-made questionnaire was used to collect data.

Results: The scores of perception and attitude toward schizophrenia were compared between the two populations. In the comparison of the two general and medical populations, only a significant relationship was found between the attitude of ineffectiveness (significance = 0.001) and stigmatization attitude (significance=0.001), which means that the attitude of the general population is more negative than the medical population.

Conclusion: No correlation was found between gender and level of education with attitude and perception towards schizophrenia. A statistically significant relationship was found between family history and negative attitude towards schizophrenia. A significant relationship was also found between taking a psychology or psychiatry course with a more positive attitude and perception towards schizophrenia.

Keywords

Schizophrenia, Perception, Attitude, Iran

Introduction

Schizophrenia is a mental illness with features such as delusions, hallucinations, disturbed behavior, and negative symptoms that impairs social and occupational functioning and is quite debilitating [1]. According to the World Health Organization’s definition, schizophrenia is a severe disorder that usually begins in late adolescence and early adulthood [2]. A key feature is disordered thinking and perception, often accompanied by inappropriate emotions. The lifetime prevalence of schizophrenia in the United States is around one percent [3]. The prevalence of psychosis especially schizophrenia in Iran is the same as in other countries and is estimated to be around one percent of the general population [4]. Perception and attitude have different definitions in various fields of psychiatry, psychology, and sociology. Social perception refers to how a person is seen by society or other people [5]. Attitude is a state of mental readiness that is acquired through experience and has a direct and dynamic impact on an individual’s response to all attitude-related issues and situations [6]. Perceptions and attitudes toward mental disorders may be positive or negative. Social stigma refers to the negative beliefs and attitudes of the general population towards individuals with mental disorders [7]. A common belief is that people with schizophrenia are unpredictable, dangerous, aggressive, and inadequate. Therefore, many people may have a strong tendency to maintain social distance from these people [8]. Social stigma, apart from the mental illness itself, has serious negative consequences for individuals with mental disorders. It can lead to damaged social facilities (such as employment and housing), lower self-esteem, help-seeking behavior, ruined friendships, and familial relationships, as well as complications in receiving health care. Mental illness stigma can also lead to delays in receiving treatment [9]. In Iran, research has been conducted on stigma towards mental disorders. The global nature of stigma, lack of awareness among mental health professionals and other experts, cultural barriers, policy-making structures, and lack of financial resources are all obstacles to improving stigma [10]. In studies conducted within Iran, even medical students who undergo clinical training may have negative attitudes toward mental disorders [11]. There is limited information about the perception and attitude toward schizophrenia in Iran. Therefore, this study was conducted to evaluate the perception and attitude of residents of Zanjan province and medical students in this province towards schizophrenia.

Methods

Study Type and Population

This study is a descriptive-analytical cross-sectional study conducted in 2023-2024 on two groups of medical students and the general population of Zanjan province. All medical students who were studying at Zanjan University of Medical Sciences in 2023 were used as the source population for the “medical” group. Patients referred to Ayatollah Mousavi Hospital’s clinics were also used as the source population for the “general population” group. The inclusion criteria for the study were medical students at Zanjan University of Medical Sciences or visitors to the Ayatollah Mousavi clinic in Zanjan in 2023 who were able to read and write, willingness to participate in the study, ages between 18 and 70 years old, and negative history of psychiatric illness. The exclusion criteria were illiteracy, unwillingness to participate in the study, ages over 70 or under 18 years old, and a positive history of psychiatric illness in the participant.

Sample Size

Based on similar studies, the G*power software was used to estimate sample size by comparing the means of two independent groups. Since the means of the two groups were estimated to be close to each other, a smaller effect size (0.2) was chosen to obtain a larger sample size. A type alpha error probability of 0.05 was considered. The sample size for the “medical” group was estimated to be 394. The sample size for the “general population” group was also estimated to be 394 and convenience sampling was used to select the general population from visitors of the clinics.

Data Collection Tool, Validity, and Reliability of the Questionnaire

A researcher-made questionnaire was used to evaluate the attitude and perception towards schizophrenia. This questionnaire consisted of 23 questions that were extracted from similar studies [12-30]. The questions were adjusted based on Iranian culture and social conditions. For example, in studies conducted in African countries, factors such as witchcraft, evil eye, and god’s will were identified as causes of schizophrenia [14], but such cases were not included in the researcher-made questionnaire. Instead, factors such as stress, physical and chemical brain disorders, poverty, etc., which are more compatible with the cultural conditions of Iran, were included as possible etiologies of schizophrenia [21]. A three-point Likert scale (1-3) was used to score the questions in the questionnaire. A score of 1=agree, 2=not sure, and 3=disagree was considered, with a lower score indicating a more positive attitude and perception. Demographic factors such as gender, age, and education level were also asked of the participants. A family history of psychiatric disorders was also asked of the participants. Participants were also required to indicate if they had completed a psychology or psychiatry course before. The content validity of the questionnaire was evaluated by psychiatry and Persian literature professors, and corrections were made before sampling. Cronbach’s alpha test was used to assess the reliability of the questionnaire. The internal consistency analysis of the 23-item schizophrenia scale yielded a Cronbach’s alpha of 0.55, which increased to 0.68 after removing items 7-8-9-10-15-16-20-22.

A psychiatrist developed case vignette was used to help the general population what was meant by schizophrenic people.

Variables

The dependent variables include perception and attitude toward schizophrenia. Independent variables include demographic characteristics, family history of psychiatric disorders, and completion of a psychology or psychiatry course.

Data Analysis Method

Incomplete questionnaires were excluded from the study. The data were entered into SPSS version 26 software. The frequency distribution of demographic variables was examined. The frequency distribution of responses to schizophrenia questionnaire items was also examined individually. The reliability of the questionnaire was evaluated using Cronbach’s alpha, which reached 0.68 after removing some items. The remaining items were subjected to exploratory factor analysis with varimax rotation. These items were divided into four factors: perception of the etiology of schizophrenia, attitude toward the inefficacy of schizophrenia, attitude toward the stigmatization of schizophrenia, and attitude toward the destigmatization of schizophrenia. Perception and attitude scores regarding schizophrenia were compared between the two general and medical populations using the t-test. The relationship between completion of a psychology or psychiatry course, family history of psychiatric disorders, gender, education level, and age with perceptions and attitudes toward schizophrenia was also examined using an independent t-test. Finally, independent variables with a significance level less than 0.05 were considered statistically significant.

Results

Demographic Characteristics

A total of 394 medical students and 394 individuals from the general population were included in the study. 99.2% of the medical students were between the ages of 18 and 30 and the number of medical students over the age of 41 was zero. 57.9% of the general population were between the ages of 18 and 30. 43.4% of the participants in the medical group were male and 56.6% were female. In the general group, 53% were male and 47% were female. Almost half the general population has a university education and half does not (Table 1).

Table 1: Socio-Demographic Characteristics of Respondents

Factor Analysis

Internal consistency of the 23-item schizophrenia scale through Cronbach’s alpha yielded a value of 0.55, which increased to 0.68 after removing items 7-8-9-10-15-16-20-22. The remaining 15 items were subjected to factor analysis with varimax rotation.

Factor one, which makes up 25.69% of the variance includes six questions that are all about the etiology of schizophrenia. This factor was named perception of the etiology of schizophrenia.

Factor two, which makes up 17.74% of the variance includes three questions that are all about the capacity of an individual in their personal and work relationships. This factor was named the attitude of the inefficacy of schizophrenia. Factor three, which makes up 11.01% of the variance includes two questions that are both about destigmatization. This factor was named the attitude of destigmatization of schizophrenia. The scores for this factor were reversed meaning a score of one meant disagree and a score of three meant agree. Factor four, which makes up 7.91% of the variance includes four questions that are all about stigmatizing. This factor was named the attitude of stigmatization of schizophrenia.

As seen in Table 2, item 23 (schizophrenia can be transmitted to others) has a negative loading on Factor 1 and requires reverse scoring in the analysis (Table 3).

Table 2: Component matrix

Table 3: Perception and attitude toward schizophrenia among medical and general population.

Comparison of Perception and Attitude Scores Regarding Schizophrenia in the General and Medical Populations

In the comparison of the scores of perception and attitude towards schizophrenia in both general and medical populations, the variables attitude of inefficacy of schizophrenia (significance = 0.03) and attitude of stigmatization of schizophrenia (significance = 0.001) are significant. Since the lower the mean, the more positive the attitude is, the attitude of the general population (mean = 5.85) in ineffectiveness is more negative than the medical population (mean = 5.01). The attitude of the general population (mean = 8.33) in stigmatizing schizophrenia is more negative than the medical population (mean = 7.61).

Association Between Taking a Psychology or Psychiatry Course with Perception and Attitude Toward Schizophrenia

417 out of 788 participants have completed a psychology or psychiatry course unit. This means that 53% of the population has been trained in the field of psychiatric disorders and 47% has not been trained. The two groups have a significant difference in all variables except for the variable of destigmatization of schizophrenia (significance = 0.07), which means that people who have passed a psychology or psychiatry course (mean = 8.37) have a more positive perception than those who have not received psychiatric training (mean = 8.96). Also, those who passed a psychiatry course have a more positive attitude of inefficacy and stigmatization (mean = 5.10 and 7.67) than those who did not pass such a course (mean = 5.80 and 8.32) (Table 4).

Table 4: Taking a psychiatry or psychology course and its association with perception and attitude toward schizophrenia.

Association Between Family History of Psychiatric Disorders and Perception and Attitude Toward Schizophrenia

Only in the stigmatizing attitude of schizophrenia, there is a significant difference between those who have a family history of psychiatric disorders and those who do not (significance = 0.008). Those who have a family history (mean = 8.16) show a more negative attitude towards stigmatization than those who do not have a family history (mean = 7.86) (Table 5).

Table 5: Family history of psychiatric disorders and its association with perception and attitude toward schizophrenia.

Association Between the Level of Education of the General Population and the Perception and Attitude Towards Schizophrenia

There is no significant difference in the attitude and perception of schizophrenia between university graduates and non-university graduates in the general population (significance>0.05) (Table 6).

Table 6: Educational level of general population and its association with perception and attitude toward schizophrenia.

Association Between Gender and Perception and Attitude Towards Schizophrenia

There is no significant difference in the attitude and perception of schizophrenia between males and females in the general and medical population (significance>0.05) (Table 7).

Table 7: Gender and its association with perception and attitude toward schizophrenia.

Association Between Age and Perception and Attitude Towards Schizophrenia

Due to the heterogeneity of the sample of the medical population, it was not possible to compare the two populations in terms of age. Also, because the number of medical students from the age group of 41 and above becomes zero, it is not possible to compare age groups with each other (Table 8).

Table 8: Responses to the items of the perception and attitude toward schizophrenia questionnaire.

Discussion

The present study was conducted to investigate the perception and attitude toward schizophrenia in both the general population and medical students in 2023. In this research, no significant relationship was found between gender and perception and attitude towards schizophrenia, these results are in line with the study conducted in Oman [31]. According to the findings, a significant relationship was found between the family history of psychiatric disorders and the attitude towards schizophrenia, that is, those who have a positive family history show a more negative attitude. Meanwhile, in the studies of Lebanon and Ethiopia, people who knew a person with mental illness among their acquaintances and family had a more positive attitude towards these patients [13,25]. At the same time, in the Baghdad research, no relationship was found between a positive family history and attitude toward mental disorders [26], this difference in results is justifiable. Since a precise and uniform definition of attitude and perception is not provided in different sources, sometimes the measured factor shows the respondent’s knowledge rather than the attitude and perception. Such questions are also seen in some of the mentioned studies and these questions may have measured the level of knowledge of the person. In this case, it is natural that if you have a positive family history of psychiatric disorders, the level of knowledge about these diseases will be higher than the rest of the people. Cultural and social differences in societies are another reason. In Western societies where there is more social support for these patients, treatments are more available and education about psychiatric disorders starts from a young age, it is natural that the attitude towards these patients is not so negative. However, in Iranian society, where education about psychiatric disorders is not provided, the government does not support such patients, and the high cost of treatment can lead to a more negative attitude towards psychiatric disorders. Sometimes people with stigma and negative attitudes towards these disorders wish to consider themselves exempt from these disorders. However, it seems that the results obtained in Iran are in line with the results seen in practice.

In our study, there was no statistically significant relationship between the level of education and the perception and attitude toward schizophrenia, which is in line with the studies of Oman and Baghdad [26,31]. At the same time, in the Ethiopian study, illiterate people or people who had non-university education showed a more positive attitude towards schizophrenia [14]. In the study of Lebanon, stigma is lower in women, young people, and university graduates than in other groups [25]. In our study, a relationship was found between having taken a psychology or psychiatry course with perception and attitude toward schizophrenia. This means that those who have completed psychology or psychiatry courses show a more positive attitude and perception. These results are in line with the Moroccan study [29]. In our study, a significant relationship was found in the attitude towards schizophrenia in the comparison of two general and medical populations, which means that the general population showed a more negative attitude than medical students. These results are in line with Amini’s study in Iran [30]. In our study, the general population recognized the lack of appropriate social support, drug and alcohol use, and genetics as the main causes of schizophrenia, which is in line with the results of studies in Ethiopia and Saudi Arabia [13,14,24]. Meanwhile, the medical community recognized the lack of appropriate social support, physical and chemical disorders in the brain, and stress as the main causes of schizophrenia, which is closer to the studies of Ghana and China [20,21].

According to the findings, almost half of the general population believes that schizophrenic patients are not dangerous and violent, which is in line with the study of Saudi Arabia [24], but not in line with the research of Ethiopia [13,14]. In our research, almost three-quarters of the general population and half of the medical population believe that it is necessary to admit schizophrenic patients to medical centers, which is closer to the Indian study [32]. Meanwhile, in the Ethiopian study, only 39.4% of the participants have the same belief [14]. At the same time, in the study of Ghana, 90% of the participants believed that schizophrenic patients should be hospitalized in treatment centers [20]. In our study, 80% of the general population agreed with the equality of human and social rights of people with schizophrenia with the rest of the population, which is not in line with the Ethiopian research [13]. Meanwhile, only 30% believed that these patients could have a favorable career future, which is in line with the studies of India and Saudi Arabia [24,33]. In our study, about 20% of the general population believed that schizophrenic patients can get married, and the same percentage believed that it is impossible to establish a friendship with schizophrenic patients. These results are in line with the study of Ghana and Canada [15,20], but not in line with the studies of southern Ghana and Saudi Arabia [24,34].

About 60% of the general population disagrees that schizophrenic patients have some kind of mental retardation, which is not in line with the study in Ghana [20]. This difference in results can be explained by the cultural differences and the level of education about psychiatric disorders in different societies. Only 16% of the general population believe that anyone may suffer from schizophrenia during their lifetime, which is much lower than studies in Ghana, Saudi Arabia, and southern Ghana [20,24,34]. One of the reasons for the difference in the results could be that by answering this question negatively, people want to rid themselves of this disease. Knowledge of the prevalence of schizophrenia in the general population can also be another influential factor. Since the prevalence of this disease in society is not very high, its estimation by the general population is not high either.

Conclusion

The results of this study showed that there is no significant relationship between gender and education level with perception and attitude toward schizophrenia. Those who have a family history of psychiatric disorders show a more negative attitude towards schizophrenia. A significant relationship between taking a psychology or psychiatry course with positive perception and attitude toward schizophrenia was also found. The general population has a more negative attitude towards schizophrenia than medical students. Lack of proper social support was recognized as the most common cause of schizophrenia.

Conflict of Interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Funding Statement

No financial support was received from any organization or persons.

Acknowledgments

We would like to extend our gratitude to Zanjan University of Medical Sciences for providing the opportunity to conduct the study and issuing the code of ethics.

Ethical Considerations

Zanjan University of Medical Sciences ethics committee provided the ethics code (IR.ZUMS.REC.1402.146) for this project.

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DOI: 10.31038/IJNM.2024542

Abstract

Objective: This study aims to comprehensively understand the actual application of fertility decision support tools in the cancer patient population and their impact on reproductive outcomes. By introducing eight assessment concepts, including acceptability, adoption, appropriateness, feasibility, fidelity, cost, penetration, and sustainability, the tool is comprehensively evaluated. Ultimately, this study aims to provide more comprehensive fertility decision support for cancer patients, offering valuable insights for future research and clinical practice in this domain.

Methods: In August 2023, a comprehensive search was conducted across a total of 14 databases, including MEDLINE, CINAHL, PubMed, PsycINFO, Embase, Scopus, Web of Science, AMED, Cochrane, Google Scholar, CNKI, WanFang Data, VIP, and Sinomed. The included literature underwent methodological quality and bias risk assessment using a mixed-methods appraisal tool.

Results: A total of 11 studies were included for analysis, comprising 5 randomized controlled trials (RCTs), 3 non-randomized controlled studies (N-RCTs), 2 mixed-methods studies, and 1 quantitative cross-sectional study. The findings indicate that research on fertility decision support tools primarily focused on aspects such as fertility-related knowledge, decisional conflict, post-decision regret, satisfaction with information acquisition, the patient’s willingness for reproduction, and the characteristics of the decision support tool. Newly identified themes encompassed decision preparedness, family involvement, informed consent, social support, health literacy, and quality of life. Among the 11 studies included, there was a greater emphasis on the aspects of acceptability, adoption, appropriateness, and feasibility. Other aspects received no attention, including fidelity, cost, penetration, and sustainability.

Conclusion: This study delves into the potential impacts on reproductive outcomes when cancer patients utilize fertility decision-support tools. Through a systematic literature review, new fertility-related themes were identified under the umbrella of fertility decision support tools. However, further research is warranted to comprehensively assess the clinical application of these tools, thereby elucidating their advantages and ultimately enhancing the quality of decision-making for patients facing fertility-related issues.

Keywords

Cancer, Fertility, Decision support, Fertility preservation, Fertility decision-aid tools, Clinical application, Systematic review

Introduction

Fertility is crucial for the continuation of human life, and early adulthood is traditionally regarded as the prime time for individuals to have their own biological children. However, among cancer survivors, reproductive function is often compromised or interrupted due to the destructive nature of cancer itself or the reproductive toxic effects of cancer treatments, particularly in adolescents and young adults (15-39 years old) [1]. With the continuous advancement of comprehensive treatments such as surgery, chemotherapy, radiation therapy, and hormonal therapy, the survival rates of young patients have significantly improved. However, these treatments have both short-term and long-term adverse effects on patients’ fertility, especially in terms of ovarian damage [2]. Studies have shown that, compared to the general population, this gonadal injury may lead to a higher incidence of premature ovarian insufficiency and azoospermia, resulting in early menopause or infertility [3]. With the steady improvement of five-year survival rates among cancer patients [4], over 85% of adolescent and young adult (AYA) cancer survivors express a strong desire for fertility and aspire to become biological parents [5]. Following treatment completion, fertility becomes a focal point of concern for patients, their families, and healthcare providers [6-9]. A comprehensive systematic review concluded that the majority (66%-100%) of cancer patients express a desire to understand the impact of treatment on their fertility [10]. Among young patients without children or with plans for future parenthood, this need and emphasis are even more pronounced, with the proportion of patients seeking relevant information ranging from 0% to 85% [11]. Many guidelines have provided recommendations regarding fertility concerns in patients. International guidelines emphasize that oncologists should inform patients about the potential for treatment-induced infertility and, when necessary, refer them to reproductive medicine specialists before formulating a cancer treatment plan [12]. Clinical practice guidelines from the American Society of Clinical Oncology suggest that healthcare professionals should engage in early discussions with female cancer patients who wish to preserve fertility before treatment in order to offer them more options [13]. Despite an increase in the proportion of fertility counseling initiated by oncologists, less than half of cancer patients are satisfied with the fertility counseling they receive, and the rate of referrals to fertility specialists remains low [14,15]. When receiving reproductive counseling, most patients express an urgent need for more timely, standardized, and written information to address their unmet specific informational needs [16]. However, approximately half of patients (43%-62%) still perceive the information they receive as inadequate and insufficient to meet their needs [17]. A cross-sectional study indicated that less than 10% of adolescent and young adult (AYA) cancer patients received fertility preservation services [18]. In clinical practice, cancer patients face numerous factors that influence their fertility choices. Firstly, they may lack sufficient fertility knowledge [19,20], and their awareness of fertility preservation methods may also be relatively low [21]. Furthermore, there is a severe deficiency in supportive information services related to fertility [22], compounded by the complexity of available fertility preservation options [23], making patients consider many intricate factors in their decision-making. Consequently, the choice of treatment regimen and timing limitations [24], as well as communication issues between patients and healthcare professionals [25], add to the decision-making challenges. Additionally, a range of ethical, legal, and ethical issues need to be considered [26-28]. It should be noted that not all fertility preservation options are suitable for every patient. Depending on factors such as the patient’s age, family status, cancer type, treatment modality, prognosis, and the timing before treatment initiation, some options may be more suitable than others when it comes to preserving fertility. Hence, patients face significant stress and conflicts in making fertility decisions. If patients do not receive comprehensive information about all fertility preservation options or lack support during the decision-making process, the difficulties in decision-making are exacerbated [17,29,30]. Simultaneously, oncology healthcare providers have also reported insufficient knowledge about fertility preservation methods and establishing connections [31,32]. To address these issues, decision support interventions have been developed for both patients and healthcare providers [33,34], aiming to enhance understanding of fertility preservation methods and reduce conflicts in the decision-making process for cancer patients [35].

Decision Aid Tools (PtDAs) are evidence-based tools that assist users in making preference-sensitive decisions by providing information specific to a particular health condition. They emphasize the benefits, risks, probabilities, and uncertainties associated with different choices related to a health condition, allowing patients to clarify their values and consider each option according to their personal preferences before making an informed decision [36]. To address decision-making regarding fertility preservation in female cancer patients, relevant guidelines recommend that healthcare professionals offer decision aids to women considering fertility preservation [12]. Numerous PtDAs for fertility preservation have been developed, and they have demonstrated positive initial application outcomes. These tools significantly enhance patients’ understanding of fertility preservation, reduce decisional conflict, and achieve high overall patient satisfaction. Over 115 randomized controlled trials have indicated that patient decision aids improve decisional conflict by increasing knowledge, fostering realistic expectations, building self-efficacy, and enhancing decision involvement [37]. A previous systematic review has indicated that patient decision aid tools (PtDAs) may play a crucial role in providing information and guiding decisions in this context. Wang et al. (2018) [35] conducted a systematic literature review on cancer patient decision aids to assess their effectiveness in supporting decisions related to fertility preservation. The results showed that decision aids enhanced awareness of fertility preservation, alleviated decisional conflict, and garnered high satisfaction ratings. As research continues to advance, an increasing number of relevant primary studies have emerged. However, in the routine assessment of such studies for clinical application, we have yet to observe systematic, comprehensive, and integrated research outcomes. The purpose of this study is to gain a deeper understanding of the specific impacts of decision-aid tools on reproductive outcomes and to comprehensively and systematically evaluate the actual effects of these tools in cancer patients. Additionally, we aim to identify potential new influencing factors and key determinants of reproductive decision-making that have not been previously mentioned in similar studies. Ultimately, we will utilize the concepts of acceptability, adoption, appropriateness, feasibility,fidelity, cost, penetration, and sustainability to conduct a comprehensive, multidimensional assessment of the application of decision aids, thereby providing a more comprehensive set of research results.

Materials and Methods

Data Sources and Study Selection

The systematic review followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020 guidelines [38]. Inclusion Criteria: 1) fertility decision support tools as an intervention affecting reproductive outcomes in cancer patients; 2) patient involvement must be present in the development, assessment, implementation, and evaluation phases of fertility decision support tools; 3) in cases where multiple reports exist for the same study, the most recent research was included. If the same data was reported with different emphases, the study was still included; 4) forms of intervention included, but were not limited to, printed materials (such as pamphlets), online resources (such as websites), computer-based tools, or video-based resources; 5) both English and Chinese language literature were considered. Exclusion Criteria: 1) Literature reviews, books, unpublished articles, commentaries, protocols, conference abstracts, and research plans; 2) Literature meeting inclusion criteria but with data that could not be extracted.

Search Strategy

The literature search was conducted in August 2023, encompassing a total of 14 databases, including MEDLINE, CINAHL, PubMed, PsycINFO, Embase, Scopus, Web of Science, AMED, Cochrane, Google Scholar, CNKI, WanFang Data, VIP, and Sinomed. Duplicate articles were screened using EndnoteX 9.3.3. Two researchers conducted a joint review, browsing through the titles and abstracts of the literature before proceeding with full-text readings. In the event of any discrepancies, a third expert was consulted for adjudication.2.3 | Data extraction, quality assessment and synthesis

Data Extraction, Quality Assessment and Synthesis

Data extraction was carried out by two scholars. In the event of any discrepancies, a third party was consulted for resolution. The extracted information included general details and specific research outcomes. General details encompassed authorship, country of origin, study type, research phase, participant demographics, sample size source, research methodology, and data collection time points. Specific research outcomes included the type of decision aid tool, primary research objectives, measurement tools, and study results. Data related to implementation outcomes, as described by Proctor et al. (2011) [39], were extracted based on eight conceptually distinct implementation outcomes, which encompassed acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration, and sustainability. It was deemed necessary to track and evaluate these cited references to ensure the report’s completeness. The included studies underwent quality and risk bias assessments using the Mixed Methods Appraisal Tool (MMAT). Each study was subjected to data synthesis based on two screening questions and five assessment criteria. In cases of score discrepancies, reviewers engaged in discussions until consensus was reached. This review strategy has been registered and is available on PROSPERO (ID: CRD42023452239).

Results

Study Selection

We employed a systematic literature search strategy, covering multiple databases and yielding a total of 2660 potentially relevant articles. These included MEDLINE (347 articles), CINAHL (172 articles), PubMed (422 articles), PsycINFO (23 articles), Embase (698 articles), Scopus (85 articles), Web of Science (618 articles), AMED (1 article), Cochrane (71 articles), Google Scholar (17 articles), CNKI (20 articles), WanFang Data (176 articles), VIP (2 articles), and Sinomed (8 articles). Subsequently, we utilized Endnote X9.3.3 software to screen and remove all duplicate records, resulting in the exclusion of repeated literature. Following this, a meticulous initial screening of titles and abstracts was conducted for 1619 articles. At this stage, we ultimately selected 123 articles for full-text reading. Two researchers independently reviewed the literature to ensure its content aligned with the research theme and type. During the process of full-text reading, a total of 112 articles were excluded. The reasons for exclusion included irrelevance to the research theme, unavailability of the full text, inconsistency in study type, and inclusion of research plans and conference abstracts, among others. During the process of including literature, any discrepancies were adjudicated by a third expert to ensure the rigor and accuracy of the research. Ultimately, we included 11 articles that met the objectives and requirements of our study. The specific search strategy can be found in the PRISMA flow diagram.

Study Quality

We conducted quality assessments for each included publication using the Mixed Methods Appraisal Tool (MMAT) standard. MMAT assesses the quality of qualitative or quantitative studies, with scores ranging from 25% (meeting one criterion) to 100% (meeting all criteria). In this study, the overall quality of the included research was relatively high. Specifically, seven studies achieved a quality score of 100%, while the remaining studies scored 80%. The lower scores were primarily attributed to poor reporting of methods in RCT studies, particularly in the aspects of randomization and allocation concealment.

Study Characteristics

Table 1 and Table 2 summarize the general characteristics and specific content of the included studies. The 11 selected articles span the years from 2012 to 2022 and were conducted in various countries or regions, including one from the United Kingdom [40], two from China [41,42], two from Australia [34,43], three from Switzerland [14,44,45], one from Germany [46], and two from the Netherlands [47,48]. These studies encompass a diverse range of types, consisting of five randomized controlled trials (RCTs) [14,42-44,47], three non-randomized controlled studies (N-RCTs) [45,46,48], two mixed-method studies [40,41], and one quantitative cross-sectional study [34]. The primary phases of the studies predominantly focus on the implementation of effects, with a total of 10 articles addressing this aspect [14,34,40-42,44-48], followed by tool development (2 articles) [41,45], feasibility (2 articles) [40,47], and acceptability (1 article) [43]. In total, 1300 subjects were involved in these studies, covering various types of cancer with a primary focus on breast cancer.

Table 1: General characteristics of 17 trials of patient decision-aids for cancer patient.

Table 2: Overview of Included Decision Aids, Treatment Coverage, Outcome Measures, and Key Findings.

Decision‐Aid Characteristics

Decision aid tools were incorporated in the studies in various formats: four studies utilized paper-based tools [34,40,43,46], three studies employed online-based tools [14,45,48], three studies were based on web platforms [41,44,47], and one study did not specify the type of decision aid tool used [42].

Effect of Decision‐Aids on Decisional Outcomes

Fertility-related Knowledge

Six studies investigated the impact of fertility decision support systems on patients’ fertility-related knowledge. This includes two randomized controlled trials (RCTs) [44,47], two non-randomized controlled trials [45,46], one cross-sectional study [34], and one quasi-experimental study [48]. These studies employed researcher-developed questionnaires for measurement. In these studies, Peate et al.’s research [34] found no significant difference in knowledge scores between the intervention and control groups at one month, but at 12 months, the DA group had lower knowledge scores compared to the routine care group. Ehrbar et al.’s study [45] indicated that after fertility preservation knowledge counseling (T1), there was no significant difference in knowledge between the two groups. However, in the aspect of “egg freezing,” the intervention group showed significantly higher knowledge and confidence. Conversely, a recent study [44] discovered no significant difference in patients’ knowledge about existing fertility preservation methods between the two groups. On the other hand, Borgmann-Staudt et al.’s study [46] demonstrated that in terms of impaired fertility and preservation knowledge, patients in the intervention group had higher average knowledge scores than the control group at both 3 months post-diagnosis (T0) and 6 months post-diagnosis (T1), but these differences were not significant at both time points. Garvelink et al.’s study [47] found significant differences in knowledge between baseline and 6 weeks post-baseline (T1), as well as between baseline and 6 months post-baseline (T2). However, there were no significant knowledge differences between the intervention group and the control group. Additionally, Garvelink et al.’s study [48] pointed out that different types of decision support tools did not significantly affect the time spent using the tool and the number of pages viewed. However, regardless of the type of tool used, they significantly elevated the level of knowledge, resulting in an 81% relative increase. Furthermore, there was a positive correlation between the time spent using the tool and the level of knowledge.

Decision Conflict

Among the 7 studies evaluating the impact of fertility decision support tools on decision conflict, the study designs included 3 randomized controlled trials (RCTs) [14,42,47], 1 non-randomized controlled trial [45], 1 mixed-methods study [40], 1 quasi-experimental study [48], and 1 cross-sectional study [34]. These studies employed the Decisional Conflict Scale for assessment. Jones et al.’s study [40] showed that that the level of decision conflict in the control group was generally below the average level. Huang et al. [42] assessed the impact of oncology fertility education for breast cancer nurses and patients on decision-conflict. The results indicated that, with similar scores on the Fertility Intention Scale (FIS) among patients, the experimental group had significantly lower decision conflict scores than the control group. Peate et al. [34] used the Decisional Conflict Scale for decision conflict measurement and found that participants receiving the DA experienced a significantly greater reduction in decision conflict over 12 months compared to participants receiving standard care. At 1 month, the average difference in DCS between the two groups was negligible, but at 12 months, the DA group had lower Decisional Conflict Scale scores than the routine care group. Additionally, Ehrbar et al.’s study in 2019 [14] found that participants who had already made a decision about fertility preservation after consultation (T1) had significantly lower decision conflict scores. The intervention group had significantly lower decision conflict scores compared to the control group. At 1 month after consultation (T2), the intervention group also had significantly lower decision conflict scores in total and on both sub-scales compared to the control group. However, 12 months after consultation (T3), the decision conflict difference between the two groups was no longer significant. Furthermore, Ehrbar et al.’s 2018 study [45] found that the intervention group had slightly higher overall decision conflict scores than the control group, but these differences were not significant. In another study, Garvelink et al.’s results [47] showed that women who received the booklet scored significantly lower on the “effective decision” sub-scale compared to women who received the decision aid (DA). Finally, Garvelink et al.’s study [48] found that women who used the values clarification exercise had a significantly different tool use time compared to those who did not use it, but there was no difference compared to those who were unable to use the exercise. Women who used the exercise performed better in decision conflict, value clarification, decision support, and informed decision.

Decision Regret

In the included literature, a total of four studies addressed decision regret, including three randomized controlled trials (RCTs) [14,44,47] and one cross-sectional study [34]. These studies all employed the Decisional Regret Scale (DRS) for measurement. The study by Peate et al. [34] observed that at one month, there were no significant differences in DRS scores regarding fertility-related decisions between groups. However, at twelve months, after adjusting for educational levels, participants who received Decision Aid (DA) exhibited significantly lower levels of decision regret. On the other hand, findings from the studies by Ehrbar et al. in 2019 and 2021 [14,44] indicated that patients in both intervention and control groups reported overall low levels of decision regret, with the intervention group consistently lower than the control group. However, these differences did not reach statistical significance. It is noteworthy that at one month post-consultation (T2), no significant correlation was found between decision conflict and decision regret. However, at twelve months post-consultation (T3), a strong correlation emerged. Contrastingly, the study by Garvelink et al. [47] found no statistically significant differences in anticipated regret between measurement time points or between groups. It is worth noting that both groups exhibited a slight trend of increased regret between baseline assessments after six weeks (T1) and six months (T2), although this increase was not significant.

Information Satisfaction

Incorporated into the research are three studies that delve into information satisfaction. These include one randomized controlled study [14], one non-randomized controlled study [45], and one cross-sectional study [34]. The assessment tools utilized in these studies were custom-designed questionnaires by the researchers. Peate et al.’s study [34] found that participants who underwent decision aid (DA) were more satisfied with information regarding the impact of breast cancer treatment on fertility and different fertility options. Ehrbar et al.’s 2018 research [45] demonstrated that decision support tools were considered helpful in the decision-making process, with the majority of participants expressing willingness to recommend them to other women. Their 2019 study likewise affirmed [14] that DA participants reported higher satisfaction levels and perceived the use of DAs as beneficial.

Fertility Intentions

In addressing the influence of decision support tools on fertility intentions, we included a total of three randomized controlled trials [14,42,44]. One study utilized the Fertility Intentions Scale (FIS) for measurement [42], while the remaining two employed patient-designed questionnaires. Huang et al.’s study assessed changes in patients’ fertility intentions using the FIS scale after employing decision support tools. The results revealed that, with similar scores on the Fertility Intentions Scale (FIS), the experimental group exhibited significantly lower decisional conflict scores compared to the control group. This indicates the effectiveness of decision-support tools in reducing decisional conflict. Ehrbar et al.’s study [14] found a notably higher positive attitude towards fertility preservation compared to a negative attitude, with no significant differences between the two groups. Additionally, attitudes and willingness to undergo fertility preservation remained stable over time, demonstrating consistency and stability in patients’ attitudes towards fertility preservation. Furthermore, Ehrbar et al.’s 2021 research [44] arrived at similar conclusions. They observed significantly higher positive attitudes in both groups compared to negative attitudes. The control and intervention groups showed comparable scores in positive attitudes, negative attitudes, and willingness to utilize fertility preservation methods. Participants’ attitudes and intentions towards fertility preservation remained stable from post-consultation (T1) to 12 months post-consultation (T3), indicating that the impact of decision support tools on fertility attitudes and intentions remains consistent over a period of time.

Characteristics of Decision Support Tools

In the evaluation of fertility decision support tools, we included a total of four studies, comprising two randomized controlled trials [43, 44] and two mixed-method studies [40,41]. Jones et al. [40] assessed the utility of the decision tool using the QQ-10 scale and ultimately concluded that the CFM tool is acceptable and highly beneficial for women making decisions regarding fertility preservation treatment. Additionally, Huang et al. [41] developed an electronic system for tumor fertility protection and examined its comprehensibility, feasibility, and usability. The study found high usability ratings from both patients and healthcare providers. Furthermore, the social support questionnaire assessment indicated effectiveness of the tool in providing information and practical support, particularly for breast cancer patients. Ussher et al. [43] evaluated the perceived acceptability and impact of the intervention. The results showed that the majority of participants gave positive feedback on the educational resources, considering them easy to understand, user-friendly, containing relevant information, and addressing fertility concerns more effectively than other sources of information. Moreover, Ehrbar et al.’s [44] study reached similar conclusions. They found significantly higher positive attitudes in both groups compared to negative attitudes. The control and intervention groups showed comparable scores in positive attitudes, negative attitudes, and willingness to use fertility preservation methods. Participants’ attitudes and intentions towards fertility preservation remained stable from post-consultation (T1) to 12 months post-consultation (T3), with no significant changes observed.

Others

Fertility decision support tools play a positive role in decision readiness [40,41], family involvement [34,46], informed consent [34,48], social support [41], and health literacy [43], providing robust support and guidance for patients facing decisions about fertility preservation treatment. However, we encountered different results in terms of quality of life. Within the context of fertility decision-making, we observed relatively limited coverage of various aspects under this theme. Nevertheless, despite the relatively small number of studies involved, we were able to identify some intriguing patterns and draw some conclusions based on existing data. Therefore, we conducted a comprehensive review based on logical grouping, highlighting the following key themes: decision readiness, family involvement, informed consent, social support, health literacy, and quality of life. First and foremost, decision readiness emerged as a crucial topic. Research indicates that decision support tools play a positive role in enhancing patients’ level of decision readiness. By employing these tools, patients gain a more comprehensive understanding of information related to fertility preservation treatment, providing a solid foundation for their decision-making process. Jones et al.’s study [40] found that fertility decision support tools were considered acceptable and highly beneficial for women preparing to make decisions about fertility preservation treatment. Additionally, Huang et al.’s 2022 study [41] emphasized the importance of providing ample knowledge about breast cancer and related treatments, addressing participants’ concerns about fertility and fertility preservation choices. Furthermore, family involvement and support also play an indispensable role in the decision-making process. Studies suggest that the active participation of partners or family members can alleviate patient anxiety and have a positive impact on decision outcomes. Obtaining support from family members during the decision-making process provides patients with additional confidence and peace of mind, enabling them to make decisions that align with their own wishes. Borgmann-Staudt et al.’s study also confirmed that specially designed educational materials about fertility preservation improved the knowledge and autonomy of both patients and parents [46]. However, Peate et al.’s study found no significant difference in partner involvement between the two groups [34]. Additionally, having a comprehensive understanding of relevant information is crucial for making informed decisions. By thoroughly comprehending various pieces of information during the decision-making process, patients can better grasp the implications and consequences of various choices, allowing them to make fertility preservation decisions that align with their individual circumstances. Garvelink et al.’s study also emphasized the importance of information, with women using value clarification exercises performing better in decision conflict, value clarification, decision support, and informed decision-making [48]. The effectiveness of social support networks also plays a crucial role in the decision-making process. When facing decisions about fertility preservation treatment, receiving assistance from social support networks helps patients better understand and address various issues, providing strong support for the decision-making process. Huang et al.’s study found that providing ample knowledge about breast cancer and related treatments was crucial for participants in making decisions about fertility and fertility protection [41]. Lastly, having good health literacy is an essential component of the decision-making process. It helps patients better understand and participate in the decision-making process, enhancing their capacity for making informed health decisions. The study found that after the intervention, patients’ health literacy significantly improved, including functional, interactive, and critical health literacy [43]. It’s worth noting that in the included studies, intervention had different expected outcomes on participants’ quality of life, with no change or varying degrees of decline observed. Jones et al. [40] assessed the quality of life of women facing decisions about preserving fertility after receiving a cancer diagnosis using the EQ-5D-3L scale. The baseline EQ-5D-3L average scores indicated lower levels of problems in five quality of life domains. Apart from daily activities (p = 0.018), there were no other significant differences in quality of life scores based on EQ-5D data before and after receiving CFM. Ussher et al.’s study noted that at the baseline stage, the Health Promotion (HP) group, through self-intervention with educational resources, had significantly higher quality of life scores than the Standard Health (SH) group, showing a statistical difference. However, after the intervention, both groups experienced a decline in quality of life, with the SH group’s average quality of life score significantly lower than that of the HP group.

Implementation Results

Among the studies included, at least seven provided data on implementation results (see Table 3 Additional file 6). A total of five studies discussed acceptability [14,34,40,43,45], three discussed adoption [14,41,45], one discussed appropriateness [43], and two discussed feasibility [41,47]. Other aspects were not addressed, including fidelity, cost, penetration, and sustainability. The measurement method primarily involved surveying patients. In terms of acceptability, our main focus was focused on the perspectives of patients, healthcare providers, or other stakeholders to determine whether there was widespread acceptance and satisfaction. In the five included studies, researchers assessed participants’ satisfaction with fertility decision support tools through self-made questionnaires [14,34,40,43,45]. In terms of adoption, the attention was on the extent of implementation strategy dissemination across different organizations or regions. In the three studies included, one study measured this through the System Usability Scale (SUS) Scores questionnaire [41], and all three results indicated willingness to propagate and use this tool [14,41,45]. Appropriateness considered contextual factors, such as patient characteristics and healthcare environments, to assess the suitability of the strategy. Only one study measured results in this aspect, showing that clinical healthcare providers had confidence in recommending the tool’s use to patients [43]. Feasibility focused on resource feasibility and implementation feasibility assessments, including potential obstacles and challenges. Two studies addressed this theme, and the research results both showed that the tool is feasible and effective, with potential for further validation through large-scale studies in the future [41,47].

Discussion

In this study, we conducted a systematic review of the impact of fertility decision support on fertility outcomes in cancer patients. The outcome indicators primarily covered fertility knowledge, decisional conflict, decision regret, information satisfaction, fertility intentions, and tool characteristics. Additionally, we discovered a range of new research findings, including the effects on patient decision-making preparedness, family involvement, patient informedness, social support, patient health literacy, and quality of life. Upon comprehensively analyzing the application of decision support tools in clinical practice, we observed that the majority of studies primarily focused on assessing the acceptability, adoption, appropriateness, and feasibility of the tools. The fertility decision support system has shown a certain impact on patients’ knowledge related to fertility preservation. However, this impact is influenced by multiple factors and requires continuous optimization and improvement in practice. Additionally, specific support for fertility preservation and its long-term effects need further research and attention. From the research results, there is considerable heterogeneity, and the impact on fertility knowledge is time-dependent, yielding different results at different times. Peate et al.’s study [34] found that the fertility decision support system did not have a significant impact on knowledge scores in the short term, but in the long term, the DA group’s knowledge scores were significantly lower than than those of the standard care group. Future research should pay more attention to and optimize the long-term effects of fertility decision support systems. Furthermore, Garvelink et al.’s study [48] indicates that different types of decision-support tools do not significantly affect the time spent using the tool or the number of pages viewed. However, regardless of the type of tool used, they significantly increase knowledge levels, with a relative increase of 81%. This underscores that the design of decision support tools may be more important than specific types, as their primary function is to enhance patients’ knowledge levels.

Decision conflict is an issue that cancer patients need to pay attention to when facing the decision of fertility preservation. Decision support tools can reduce the level of decision conflict in patients to some extent. However, there are certain differences in results under different research conditions, so the application of decision support tools needs to be considered comprehensively according to specific situations in practice. At the same time, long-term tracking and evaluation are also necessary to understand the persistence and stability of the decision. Huang et al.’s study shows that after receiving cancer fertility education, the decision conflict scores of the experimental group were significantly lower than those of the control group, indicating that an improved education level can make patients more clear about their choices when making decisions [42]. The results of Peate et al.’s study present an interesting trend. In the short term, the difference in decision conflict between the two groups is not significant [34]. However, with long-term observation, patients receiving decision support were significantly lower than those receiving routine care, indicating that fertility decision support tools play a positive role in the long-term decision-making process. On the other hand, Ehrbar et al.’s study also found that after consultation, participants who had already made the decision to preserve fertility had significantly lower decision conflict scores, and the decision conflict scores of the intervention group were also significantly lower than those of the control group. However, after long-term follow-up, the difference in decision conflict between the two groups was no longer significant, which may be because the stability of the decision gradually tended to be consistent over time. The analysis of multiple studies shows that the overall level of decision conflict is relatively low, indicating that fertility decision support tools can provide effective support, reducing the contradictions and confusion in the decision-making process. Decision regret is a complex and multidimensional psychological state in the process of fertility preservation treatment decision-making. Different research results may be influenced by various factors, including individual characteristics, education level, and the timing of using decision support tools. In future research, it may be considered to further explore these influencing factors in order to provide more targeted decision support and intervention measures to alleviate the potential decision-regret emotions that patients may face. Decision support tools have achieved significant effectiveness in providing fertility-related information, enabling patients to have a clearer understanding of reproductive knowledge. The discussion of information satisfaction in the study focuses on evaluating the effectiveness of decision support tools in helping patients obtain fertility-related information and the satisfaction of patients with this information. At the same time, patients’ satisfaction with the use of decision support tools is also high, and they are willing to recommend them to other women. This provides strong support for the further promotion and application of decision support tools. Peate et al.’s research results show that participants who received decision support were more satisfied with information regarding the impact of breast cancer treatment on fertility and different reproductive choices [34]. This indicates that decision support tools play a positive role in providing information, enabling patients to have a more comprehensive understanding of reproductive knowledge. The multiple studies by Ehrbar et al. [14,45] also indicate that patients participating in decision support are satisfied with the use of the tool and believe that it has a positive impact on their decision-making process. However, it is worth noting that there are certain differences in results under different research conditions, so the application of decision support tools needs to be comprehensively considered according to specific situations in practice to ensure that patients can obtain the maximum level of information satisfaction. The decision support tool has achieved positive results in influencing the willingness for fertility preservation, reducing the patients’ decision conflict, and maintaining a positive attitude towards fertility preservation. This provides strong support for the application of decision support tools in clinical practice. It also reminds us that in the design and implementation of decision support tools, it is important to provide patients with comprehensive and clear information about fertility preservation to better assist them in making decisions that align with their own intentions. The results of Huang et al.’s study [42] indicate that the experimental group had significantly lower decision conflict scores compared to the control group. This suggests that the decision support tool has achieved significant effectiveness in reducing patients’ decision conflict. It is evident that the decision support tool provides patients with more comprehensive and clear information about fertility preservation, enabling them to have a clearer understanding of their choices. Additionally, the studies by Ehrbar et al. in 2019 and 2021 [14,44] show that participants’ attitudes towards fertility preservation were significantly more positive than negative, and this attitude remained stable over time. This indicates that patients’ attitudes towards fertility preservation are relatively stable and consistent. The decision support tool did not change the patients’ attitudes but rather provided additional information based on their existing attitudes.

The decision support tool has demonstrated significant effectiveness in providing fertility preservation information and support, offering strong assistance for patients to make decisions in line with their own preferences. This underscores the importance of considering patients’ needs and providing easily understandable, user-friendly, and comprehensive information when designing and implementing decision support tools, in order to better assist patients in their decision-making process. The study by Jones et al. [40], which utilized the QQ-10 to assess the usability of the CFM tool, yielded results indicating that the tool is acceptable and highly useful for women preparing to make decisions about fertility preservation treatment. This indicates the tool’s effectiveness in providing information and support. Additionally, the electronic system for tumor fertility protection developed by Huang et al. [41] received positive evaluations in terms of comprehensibility, feasibility, and usability. Both patients and healthcare providers considered it highly usable. Furthermore, the tool demonstrated effectiveness in providing information and practical support, particularly for breast cancer patients. In the research on fertility preservation decision support tools, we have made intriguing new findings that play a positive role in decision preparedness, family involvement, informed consent, social support, health literacy, and quality of life. Firstly, decision preparedness has been confirmed as a crucial issue. Decision support tools actively contribute to enhancing patients’ level of decision preparedness. By utilizing these tools, patients can gain a more comprehensive understanding of information related to fertility preservation treatment, providing a solid foundation for decision-making. Particularly, in the study by Jones et al. [40], fertility preservation decision support tools were deemed acceptable and highly useful for women preparing to make decisions about fertility preservation treatment. Secondly, family involvement and support play an indispensable role in the decision-making process. The active participation of partners or family members can alleviate patient anxiety, positively influence decision outcomes, and garnering support from family members can provide patients with added confidence and reassurance, enabling them to make decisions that align with their preferences more resolutely. Furthermore, having a thorough understanding of relevant information is crucial for making informed decisions. By comprehensively understanding various pieces of information during the decision-making process, patients can better grasp the impacts and consequences of various choices, thereby making fertility preservation selections that align with their individual circumstances. The effectiveness of a social support network also plays a vital role in the decision-making process. Receiving assistance from a social support network can help patients better comprehend and address various issues, providing robust support for decision-making. Finally, having good health literacy is an essential component of the decision-making process. It aids patients in better understanding and participating in the decision-making process, elevating their capacity for making health-related decisions. The research found that after intervention, patients’ health literacy significantly improved, including functional, interactive, and critical health literacy [43]. Regarding quality of life, the reasons behind changes in quality of life after fertility preservation decision support will also need to be further explored in the future. In summary, though research on these aspects is relatively limited, we have uncovered numerous intriguing patterns and conclusions from existing data. Decision preparedness, family involvement, informed consent, social support, health literacy, and quality of life are all crucial topics worthy of attention in the fertility preservation treatment decision-making process. The positive impacts of these aspects provide robust support and guidance for patients when facing decisions about fertility preservation treatment, further promoting the rationality and personalization of medical decisions. These new findings offer valuable references for future research and clinical practice.

Clinical Limitations

While we have made comprehensive efforts to discuss the application of fertility preservation decision support tools in clinical settings in this study, it is important to acknowledge that there are still some limitations in certain aspects. Firstly, in terms of factors such as credibility, cost, penetration, and sustainability, there may be insufficient data or the ability to provide a comprehensive summary in the current research. However, we can propose some potential improvement suggestions from the perspective of future research and practice. It is recommended to consider tool reliability as a crucial assessment criterion in future studies and explore how to ensure the stability and credibility of the tool in practice. Additionally, from the standpoint of technological progress and development trends, discussing how to reduce the cost of the tool to promote its widespread clinical application is worthwhile. Furthermore, strengthening the promotion and training of this tool is also an important initiative to increase its prevalence in clinical practice. It is essential to think about how to ensure the tool remains effective in long-term use, such as through regular updates and enhancements. For other aspects of the discussion, it should be noted that not all possible scenarios have been covered in the current research. In future studies, further exploration of these aspects will be necessary to gain a comprehensive understanding of the effectiveness of fertility preservation decision-support tools in clinical practice. Despite our best efforts to address these limitations in this study, it is crucial to exercise caution when generalizing these results to other contexts.

The limitations of this study include the potential for significant bias and contradictory results due to inconsistent assessment criteria in the measurement methods employed. This limitation could impact the accurate understanding and assessment of the psychological state in the decision-making process regarding fertility preservation treatments. Furthermore, factors such as sample selection and study design may introduce selection bias and extrapolation constraints, thereby restricting the generalizability and applicability of the study’s findings to a certain extent. Therefore, the inconsistency in measurement methods within the study may lead to contradictions among research outcomes. This underscores the need for future research to carefully and meticulously select appropriate measurement tools while taking into full consideration various potential influencing factors in order to enhance the reliability and robustness of research results. This study, based on existing data and our inclusion methodology, has made every effort to ensure comprehensiveness. However, given the breadth of the research field and the nature of database searches, we acknowledge the possibility that some studies, especially those conducted under specific conditions, may not have been included. Nevertheless, we believe that this does not diminish the uniqueness and importance of our study. Given the current limitations of this research, we encourage future researchers to continue exploring this field. We believe that such efforts will contribute to enriching and refining the knowledge base in this area, providing more comprehensive and effective support for future clinical practices.

Clinical Implications

Firstly, through a comprehensive analysis of the latest research findings, we can provide clinical practitioners with an up-to-date and authoritative body of scientific evidence to support the development and application of fertility decision-making tools. Secondly, it can facilitate patient involvement in decision-making. Fertility decisions are highly personalized and sensitive topics, making patient involvement crucial. By furnishing patients with scientific foundations, we empower them with more agency and confidence, enabling active participation in the decision-making process. This not only ensures that patients feel heard but also enhances their trust in treatment options, thereby improving the overall efficacy of the treatment process. Additionally, we can assist patients in better comprehending the various influencing factors of fertility decisions through information and education, enabling them to make more informed choices. Lastly, our research provides practical guidance and decision support. Clinical healthcare providers can tailor the most appropriate fertility decision plans for each patient based on this scientific evidence, thus maximizing patients’ fertility aspirations. Simultaneously, patients can, with this evidence, participate more confidently in the treatment process, thereby collectively achieving the most desirable treatment objectives.

Conclusion

The primary objective of this study is to explore the tangible impact of fertility preservation decision aid tools (PtDAs) among cancer patients. Through a comprehensive assessment encompassing various aspects such as fertility-related knowledge, decision conflicts, post-decision regret, information satisfaction, fertility intentions, and tool characteristics, this research furnishes robust evidence for a deeper understanding of the practical implications of PtDAs within the cancer patient population. It offers valuable insights for clinical nursing practices, potentially serving as a valuable complement to current fertility care practices. Beyond clinical counseling, this research aims to ensure the fulfillment of the demand for high-quality information and support.

Declarations

Ethical Approval and Consent to Participate

Not applicable

Funding

No funding

Availability of Data and Materials

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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