Cancer awareness in the general population varies with sex, age and media coverage: A population-based survey with focus on gynecologic cancers

A Multilabel Text Classifier of Cancer Literature at the Publication Level: Methods Study of Medical Text Classification

BACKGROUND

Given the threat posed by cancer to human health, there is a rapid growth in the volume of data in the cancer field and interdisciplinary and collaborative research is becoming increasingly important for fine-grained classification. The low-resolution classifier of reported studies at the journal level fails to satisfy advanced searching demands, and a single label does not adequately characterize the literature originated from interdisciplinary research results. There is thus a need to establish a multilabel classifier with higher resolution to support literature retrieval for cancer research and reduce the burden of screening papers for clinical relevance.

OBJECTIVE

The primary objective of this research was to address the low-resolution issue of cancer literature classification due to the ambiguity of the existing journal-level classifier in order to support gaining high-relevance evidence for clinical consideration and all-sided results for literature retrieval.

METHODS

We trained a multilabel classifier with scalability for classifying the literature on cancer research directly at the publication level to assign proper content-derived labels based on the "Bidirectional Encoder Representation from Transformers (BERT) + X" model and obtain the best option for X. First, a corpus of 70,599 cancer publications retrieved from the Dimensions database was divided into a training and a testing set in a ratio of 7:3. Second, using the classification terminology of International Cancer Research Partnership cancer types, we compared the performance of classifiers developed using BERT and 5 classical deep learning models, such as the text recurrent neural network (TextRNN) and FastText, followed by metrics analysis.

RESULTS

After comparing various combined deep learning models, we obtained a classifier based on the optimal combination "BERT + TextRNN," with a precision of 93.09%, a recall of 87.75%, and an F1-score of 90.34%. Moreover, we quantified the distinctive characteristics in the text structure and multilabel distribution in order to generalize the model to other fields with similar characteristics.

CONCLUSIONS

The "BERT + TextRNN" model was trained for high-resolution classification of cancer literature at the publication level to support accurate retrieval and academic statistics. The model automatically assigns 1 or more labels to each cancer paper, as required. Quantitative comparison verified that the "BERT + TextRNN" model is the best fit for multilabel classification of cancer literature compared to other models. More data from diverse fields will be collected to testify the scalability and extensibility of the proposed model in the future.

Determination of the Relationship Between Gynecological Cancer Awareness and Fear of Cancer in Women Using Social Media and the Affecting Factors

BACKGROUND

Understanding the relationship between fear of gynecological cancer and awareness of cancer in women may help oncology nurses increase women's participation in gynecological cancer screening.

OBJECTIVE

To examine the relationship between women's gynecological cancer awareness and cancer fear using social media and the affecting factors.

METHODS

In a descriptive and cross-sectional study design, online data were collected from 1231 women aged 20 to 69 years through social media using the Descriptive Information Form, the Gynecological Cancer Awareness Scale (GCAS), and the Cancer Worry Scale (CWS). Analytic tests included paired t tests, analysis of variance, and post hoc correlations and structural equation modeling.

RESULTS

The women's total mean GCAS score was above moderate (152 ± 17), and their mean CWS score was high (19 ± 5). There was no relationship between the GCAS and CWS mean scores. Characteristics of participants with high awareness of gynecological cancer were being young, having a high educational level, having children, living in a province, having a history of cancer or family history of cancer, and having regular gynecological examinations, Papanicolaou smear tests, breast self-examination, and vulva examinations (P < .05). The fear of cancer was higher in women with children, a family history of cancer, and regular gynecological examination behaviors (P < .05).

CONCLUSION

Awareness of gynecological cancer was not significantly statistically associated with fear of cancer. Certain sociodemographic and gynecological characteristics are associated with awareness of gynecological cancer and/or fear of cancer.

IMPLICATIONS FOR PRACTICE

Oncology nurses may plan individualized or large-scale educational events that may make use of social media to enhance accurate awareness of gynecological cancer and related examinations in women.

The Relationship between Gynecological Cancer Awareness and Self-Care Agency in Married Women

Nursel Alp DalObjective  This study was conducted to determine the relationship between gynecological cancer awareness and self-care agency among married women. Materials and Methods  This descriptive and cross-sectional study was performed with 819 women who presented to the obstetrics polyclinic of a hospital located in the west of Turkey between December 15, 2020 and April 15, 2021. The data of the study were collected by using the Exercise of Self-Care Agency Scale (ESCA) and the Gynecological Cancers Awareness Scale (GCAS). Results  The mean age of the participants was 37.62 ± 9.181 years. The mean ESCA score of the women who participated in this study was 95.89 ± 25.060, which indicated moderate levels of self-care agency. The mean total GCAS score of the participants of this study was 156.57 ± 32.930, which indicated high levels of gynecological cancer awareness among the women. As the self-care agency of the women increased, their awareness of gynecological cancers also increased. Conclusion  Midwives and nurses who provide preventive and supportive healthcare services may affect the self-care agency of women positively by gynecological cancer awareness they will raise in these women.