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      Early detection of cervical cancer in western Kenya: determinants of healthcare providers performing a gynaecological examination for abnormal vaginal discharge or bleeding

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          Abstract

          Background

          In western Kenya, women often present with late-stage cervical cancer despite prior contact with the health care system. The aim of this study was to predict primary health care providers’ behaviour in examining women who present with abnormal discharge or bleeding.

          Methods

          This was a cross-sectional survey using the theory of planned behaviour (TPB). A sample of primary health care practitioners in western Kenya completed a 59-item questionnaire. Structural equation modelling was used to identify the determinants of providers’ intention to perform a gynaecological examination. Bivariate analysis was conducted to investigate the relationship between the external variables and intention.

          Results

          Direct measures of subjective norms (DMSN), direct measures of perceived behavioural control (DMPBC), and indirect measures of attitude predicted the intention to examine patients. Negative attitudes toward examining women had a suppressor effect on the prediction of health workers’ intentions. However, the predictors of intention with the highest coefficients were the external variables being a nurse (β = 0.32) as opposed to a clinical officer and workload of attending less than 50 patients per day (β = 0.56).

          In bivariate analysis with intention to perform a gynaecological examination, there was no evidence that working experience, being female, having a lower workload, or being a private practitioner were associated with a higher intention to conduct vaginal examinations. Clinical officers and nurses were equally likely to examine women.

          Conclusions

          The TPB is a suitable theoretical basis to predict the intention to perform a gynaecological examination. Overall, the model predicted 47% of the variation in health care providers’ intention to examine women who present with recurrent vaginal bleeding or discharge. Direct subjective norms (health provider’s conformity with what their colleagues do or expect them to do), PBC (providers need to feel competent and confident in performing examinations in women), and negative attitudes toward conducting vaginal examination accounted for the most variance. External variables in this study also contributed to the overall variance. As the model in this study could not explain 53% of the variance , investigating other external variables that influence the intention to examine women should be undertaken.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12875-021-01395-y.

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          Most cited references39

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          The theory of planned behavior

          Icek Ajzen (1991)
          Organizational Behavior and Human Decision Processes, 50(2), 179-211
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            How Many Subjects Does It Take To Do A Regression Analysis.

            S Green (1991)
            Numerous rules-of-thumb have been suggested for determining the minimum number of subjects required to conduct multiple regression analyses. These rules-of-thumb are evaluated by comparing their results against those based on power analyses for tests of hypotheses of multiple and partial correlations. The results did not support the use of rules-of-thumb that simply specify some constant (e.g., 100 subjects) as the minimum number of subjects or a minimum ratio of number of subjects (N) to number of predictors (m). Some support was obtained for a rule-of-thumb that N ≥ 50 + 8 m for the multiple correlation and N ≥104 + m for the partial correlation. However, the rule-of-thumb for the multiple correlation yields values too large for N when m ≥ 7, and both rules-of-thumb assume all studies have a medium-size relationship between criterion and predictors. Accordingly, a slightly more complex rule-of thumb is introduced that estimates minimum sample size as function of effect size as well as the number of predictors. It is argued that researchers should use methods to determine sample size that incorporate effect size.
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              FIGO classification system (PALM-COEIN) for causes of abnormal uterine bleeding in nongravid women of reproductive age.

              There is general inconsistency in the nomenclature used to describe abnormal uterine bleeding (AUB), in addition to a plethora of potential causes-several of which may coexist in a given individual. It seems clear that the development of consistent and universally accepted nomenclature is a step toward rectifying this unsatisfactory circumstance. Another requirement is the development of a classification system, on several levels, for the causes of AUB, which can be used by clinicians, investigators, and even patients to facilitate communication, clinical care, and research. This manuscript describes an ongoing process designed to achieve these goals, and presents for consideration the PALM-COEIN (polyp; adenomyosis; leiomyoma; malignancy and hyperplasia; coagulopathy; ovulatory dysfunction; endometrial; iatrogenic; and not yet classified) classification system for AUB, which has been approved by the International Federation of Gynecology and Obstetrics (FIGO) Executive Board as a FIGO classification system. Copyright © 2011. Published by Elsevier Ireland Ltd.
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                Author and article information

                Contributors
                waleghwaem@hotmail.com
                guido.vanhal@uantwerpen.be
                hilde.bastiaens@uantwerpen.be
                Stefan.vandongen@uantwerpen.be
                gichangip@yahoo.com , peterbg@tum.ac.ke
                barasaotsyula@yahoo.com
                vnaanyu@mu.ac.ke
                Marleen.Temmerman@UGent.be
                Journal
                BMC Fam Pract
                BMC Fam Pract
                BMC Family Practice
                BioMed Central (London )
                1471-2296
                11 March 2021
                11 March 2021
                2021
                : 22
                : 52
                Affiliations
                [1 ]GRID grid.79730.3a, ISNI 0000 0001 0495 4256, Department of Reproductive Health, School of Medicine, , Moi University, ; Box 4606, Eldoret, 30100 Kenya
                [2 ]GRID grid.5284.b, ISNI 0000 0001 0790 3681, Epidemiology and Social Medicine, Social Epidemiology and Health Policy, , University of Antwerp, ; Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium
                [3 ]GRID grid.5284.b, ISNI 0000 0001 0790 3681, Department of Primary and Interdisciplinary Care, Faculty of Medicine and Health Sciences, , University of Antwerp, ; Gouverneur Kinsbergen Centrum, Doornstraat 331 - 2610 Wilrijk, Antwerp, Belgium
                [4 ]GRID grid.5284.b, ISNI 0000 0001 0790 3681, Department of Biology, Evolutionary Ecology Group, , University of Antwerp, ; Universiteitsplein 1, 2610 Wilrijk, Belgium
                [5 ]GRID grid.449703.d, ISNI 0000 0004 1762 6835, DVC Academic Research & Extension, Technical University of Mombasa, ; Mumbasa, Kenya
                [6 ]GRID grid.5342.0, ISNI 0000 0001 2069 7798, Ghent University, ; Ghent, Belgium
                [7 ]GRID grid.79730.3a, ISNI 0000 0001 0495 4256, Department of Surgery, School of Medicine, , Moi University, ; P.O. Box 4606, Eldoret, 30100 Kenya
                [8 ]GRID grid.79730.3a, ISNI 0000 0001 0495 4256, Department of Sociology Psychology and Anthropology, School of Arts and Social Sciences, , Moi University, ; P.O. Box 3900, Eldoret, 30100 Kenya
                [9 ]GRID grid.5342.0, ISNI 0000 0001 2069 7798, Department of Public Health and Primary Care, Ghent University, ; Ghent, Belgium
                [10 ]GRID grid.470490.e, Department of Obstetrics and Gynaecology, , Aga Khan University, ; P O. Box 00100, Nairobi, Kenya
                Article
                1395
                10.1186/s12875-021-01395-y
                7953728
                33706721
                e90f363c-d1f2-4301-81fa-aed8c41e59ea
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 18 August 2020
                : 9 February 2021
                Funding
                Funded by: VLIR-UOS/MOI UNIVERSITY KENYA PROGRAM
                Award ID: ZIUS2012AP017,ZIUS2013AP017,ZIUS2014AP017,ZIUS2015AP017,ZIUS2016AP017. SERIAL NUMBER:2012-157
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2021

                Medicine
                theory of planned behaviour,health care providers,cervical cancer,early detection,health care seeking delays,primary health care,abnormal uterine bleeding,kenya

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