Knowledge of cancer symptoms and anxiety affect patient delay in seeking diagnosis in patients with heterogeneous cancer locations

Purpose: This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought to determine the differences between delaying and nondelaying patients with reference to their knowledge of cancer symptoms, sociodemographi...

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Published inCurrent problems in cancer Vol. 41; no. 1; pp. 64 - 70
Main Authors Chojnacka-Szawłowska, Gabriela, Majkowicz, Mikołaj, Basiński, Krzysztof, Zdun-Ryżewska, Agata, Wasilewko, Iwona, Pankiewicz, Piotr
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.01.2017
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Online AccessGet full text
ISSN0147-0272
1535-6345
1535-6345
DOI10.1016/j.currproblcancer.2016.10.001

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Abstract Purpose: This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought to determine the differences between delaying and nondelaying patients with reference to their knowledge of cancer symptoms, sociodemographic variables, and the levels of state anxiety and trait anxiety. The study involved 301 randomly selected patients with suspected cancer disease before their first oncology appointment at a regional oncology center in Poland. Data were collected by means of a semistructured interview conducted by a trained psychologist. To evaluate the knowledge of cancer symptoms, the symptoms mentioned by subjects were compared to the list of symptoms from cancer awareness measure. Anxiety levels were assessed using the State-Trait Anxiety Inventory. In the course of logistic regression analysis a model was developed, in which knowledge of cancer symptoms and state anxiety allowed to predict patient delay. Knowledge of every additional cancer symptom decreased the chance of patient delay by 16.4% point [95% CI: 1.4–29.2]. An increase in state anxiety for every point of the scale decreased the chance of delay by 2.5% points [95% CI: 0.2–4.6]. Trait anxiety and the studied sociodemographic variables proved to be nonsignificant predictors of patient delay. Knowledge of cancer symptoms and the level of state anxiety allowed to predict patient delay in the initiation of treatment. Owing to the heterogeneity of the tumor locations within the sample, the obtained model can be used in large scale prevention programs designed for the whole population.
AbstractList Abstract Purpose: This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought to determine the differences between delaying and nondelaying patients with reference to their knowledge of cancer symptoms, sociodemographic variables, and the levels of state anxiety and trait anxiety. Methods The study involved 301 randomly selected patients with suspected cancer disease before their first oncology appointment at a regional oncology center in Poland. Data were collected by means of a semistructured interview conducted by a trained psychologist. To evaluate the knowledge of cancer symptoms, the symptoms mentioned by subjects were compared to the list of symptoms from cancer awareness measure. Anxiety levels were assessed using the State-Trait Anxiety Inventory. Results In the course of logistic regression analysis a model was developed, in which knowledge of cancer symptoms and state anxiety allowed to predict patient delay. Knowledge of every additional cancer symptom decreased the chance of patient delay by 16.4% point [95% CI: 1.4–29.2]. An increase in state anxiety for every point of the scale decreased the chance of delay by 2.5% points [95% CI: 0.2–4.6]. Trait anxiety and the studied sociodemographic variables proved to be nonsignificant predictors of patient delay. Conclusions Knowledge of cancer symptoms and the level of state anxiety allowed to predict patient delay in the initiation of treatment. Owing to the heterogeneity of the tumor locations within the sample, the obtained model can be used in large scale prevention programs designed for the whole population.
Purpose: This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought to determine the differences between delaying and nondelaying patients with reference to their knowledge of cancer symptoms, sociodemographic variables, and the levels of state anxiety and trait anxiety. The study involved 301 randomly selected patients with suspected cancer disease before their first oncology appointment at a regional oncology center in Poland. Data were collected by means of a semistructured interview conducted by a trained psychologist. To evaluate the knowledge of cancer symptoms, the symptoms mentioned by subjects were compared to the list of symptoms from cancer awareness measure. Anxiety levels were assessed using the State-Trait Anxiety Inventory. In the course of logistic regression analysis a model was developed, in which knowledge of cancer symptoms and state anxiety allowed to predict patient delay. Knowledge of every additional cancer symptom decreased the chance of patient delay by 16.4% point [95% CI: 1.4–29.2]. An increase in state anxiety for every point of the scale decreased the chance of delay by 2.5% points [95% CI: 0.2–4.6]. Trait anxiety and the studied sociodemographic variables proved to be nonsignificant predictors of patient delay. Knowledge of cancer symptoms and the level of state anxiety allowed to predict patient delay in the initiation of treatment. Owing to the heterogeneity of the tumor locations within the sample, the obtained model can be used in large scale prevention programs designed for the whole population.
This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought to determine the differences between delaying and nondelaying patients with reference to their knowledge of cancer symptoms, sociodemographic variables, and the levels of state anxiety and trait anxiety.PURPOSEThis research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought to determine the differences between delaying and nondelaying patients with reference to their knowledge of cancer symptoms, sociodemographic variables, and the levels of state anxiety and trait anxiety.The study involved 301 randomly selected patients with suspected cancer disease before their first oncology appointment at a regional oncology center in Poland. Data were collected by means of a semistructured interview conducted by a trained psychologist. To evaluate the knowledge of cancer symptoms, the symptoms mentioned by subjects were compared to the list of symptoms from cancer awareness measure. Anxiety levels were assessed using the State-Trait Anxiety Inventory.METHODSThe study involved 301 randomly selected patients with suspected cancer disease before their first oncology appointment at a regional oncology center in Poland. Data were collected by means of a semistructured interview conducted by a trained psychologist. To evaluate the knowledge of cancer symptoms, the symptoms mentioned by subjects were compared to the list of symptoms from cancer awareness measure. Anxiety levels were assessed using the State-Trait Anxiety Inventory.In the course of logistic regression analysis a model was developed, in which knowledge of cancer symptoms and state anxiety allowed to predict patient delay. Knowledge of every additional cancer symptom decreased the chance of patient delay by 16.4% point [95% CI: 1.4-29.2]. An increase in state anxiety for every point of the scale decreased the chance of delay by 2.5% points [95% CI: 0.2-4.6]. Trait anxiety and the studied sociodemographic variables proved to be nonsignificant predictors of patient delay.RESULTSIn the course of logistic regression analysis a model was developed, in which knowledge of cancer symptoms and state anxiety allowed to predict patient delay. Knowledge of every additional cancer symptom decreased the chance of patient delay by 16.4% point [95% CI: 1.4-29.2]. An increase in state anxiety for every point of the scale decreased the chance of delay by 2.5% points [95% CI: 0.2-4.6]. Trait anxiety and the studied sociodemographic variables proved to be nonsignificant predictors of patient delay.Knowledge of cancer symptoms and the level of state anxiety allowed to predict patient delay in the initiation of treatment. Owing to the heterogeneity of the tumor locations within the sample, the obtained model can be used in large scale prevention programs designed for the whole population.CONCLUSIONSKnowledge of cancer symptoms and the level of state anxiety allowed to predict patient delay in the initiation of treatment. Owing to the heterogeneity of the tumor locations within the sample, the obtained model can be used in large scale prevention programs designed for the whole population.
This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought to determine the differences between delaying and nondelaying patients with reference to their knowledge of cancer symptoms, sociodemographic variables, and the levels of state anxiety and trait anxiety. The study involved 301 randomly selected patients with suspected cancer disease before their first oncology appointment at a regional oncology center in Poland. Data were collected by means of a semistructured interview conducted by a trained psychologist. To evaluate the knowledge of cancer symptoms, the symptoms mentioned by subjects were compared to the list of symptoms from cancer awareness measure. Anxiety levels were assessed using the State-Trait Anxiety Inventory. In the course of logistic regression analysis a model was developed, in which knowledge of cancer symptoms and state anxiety allowed to predict patient delay. Knowledge of every additional cancer symptom decreased the chance of patient delay by 16.4% point [95% CI: 1.4-29.2]. An increase in state anxiety for every point of the scale decreased the chance of delay by 2.5% points [95% CI: 0.2-4.6]. Trait anxiety and the studied sociodemographic variables proved to be nonsignificant predictors of patient delay. Knowledge of cancer symptoms and the level of state anxiety allowed to predict patient delay in the initiation of treatment. Owing to the heterogeneity of the tumor locations within the sample, the obtained model can be used in large scale prevention programs designed for the whole population.
Author Pankiewicz, Piotr
Basiński, Krzysztof
Zdun-Ryżewska, Agata
Wasilewko, Iwona
Chojnacka-Szawłowska, Gabriela
Majkowicz, Mikołaj
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Issue 1
Keywords Anxiety
Delayed diagnosis
Symptoms
Cancer
Language English
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Snippet Purpose: This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought...
Abstract Purpose: This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease....
This research was aimed at identifying factors that predict patient delay in treatment initiation in patients with suspected cancer disease. We sought to...
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SubjectTerms Adult
Anxiety
Anxiety - epidemiology
Anxiety - etiology
Cancer
Delayed diagnosis
Delayed Diagnosis - psychology
Delayed Diagnosis - statistics & numerical data
Diagnostic Self Evaluation
Early Detection of Cancer - psychology
Female
Health Knowledge, Attitudes, Practice
Hematology, Oncology and Palliative Medicine
Humans
Male
Middle Aged
Neoplasms - diagnosis
Patient Acceptance of Health Care - psychology
Patient Acceptance of Health Care - statistics & numerical data
Socioeconomic Factors
Symptoms
Title Knowledge of cancer symptoms and anxiety affect patient delay in seeking diagnosis in patients with heterogeneous cancer locations
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https://dx.doi.org/10.1016/j.currproblcancer.2016.10.001
https://www.ncbi.nlm.nih.gov/pubmed/28017343
https://www.proquest.com/docview/1853354394
Volume 41
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