Impact of information sources on expectation of cancer treatment side effects: A URCC CCOP study

Hofman, M.; Hickok, Jane T.; Morrow, Gary R.; Moore, D. F.; Wade, James L.; Fitch, Tom R.

doi:10.1200/jco.2004.22.90140.8094

Cited by 1 publication

(5 citation statements)

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“…Scores for journal articles ranged between two and 19 out of 19 (see Table 1). Two conference abstracts had artificially low scores (two and four 52,75 ). Most studies (n = 34) were poor quality; 32 were moderate quality; and six were good quality.…”

Section: Resultsmentioning

confidence: 99%

“…Studies scored particularly poorly for external validity, with only four studies being good quality, 71,74,84,85 and power, with nine studies being adequately powered 57,60,66,74,77,80,84,85 (see Figure 2). Thirty‐one studies scored poorly for reporting, 27,29,30,32,37,38,40–42,47,50,52–56,62–65,69,74,75,78,80,82,83,89 and 31 scored poorly for confounding (selection bias) 28,29,33,34,36,40–44,46,47,52–54,57,58,62–65,70,73–75,78,82,89 . Twelve studies scored poorly for internal validity (bias) 42,52,53,56,62,74,75,78,80,82 …”

Section: Resultsmentioning

confidence: 99%

“…There was no evidence that the number of sources used to gain information about a medical intervention was associated with increased side‐effect expectations, with studies reporting mixed results. One poor quality cross‐sectional study found an association; 52 as this was a conference abstract, the quality rating score was artificially low. This study also found that using the internet, the National Cancer Institute and American Cancer Society as sources of information about cancer were associated with increased side‐effect expectations, whereas consulting newspapers and primary care physicians were associated with decreased side‐effect expectations 52 .…”

Section: Resultsmentioning

confidence: 99%

“…One poor quality cross‐sectional study found an association; 52 as this was a conference abstract, the quality rating score was artificially low. This study also found that using the internet, the National Cancer Institute and American Cancer Society as sources of information about cancer were associated with increased side‐effect expectations, whereas consulting newspapers and primary care physicians were associated with decreased side‐effect expectations 52 . Another cross‐sectional study found no evidence for an association between number of sources used to gain information about the intervention and side‐effect expectations 49 .…”

Section: Resultsmentioning

confidence: 99%

“…Very little research has investigated the role of sources of information on side‐effect expectations, with mixed findings. While other research has focused on the negative role of the media on side‐effect reporting, 104,105 one study included in the review found that consulting newspapers as a source of information was associated with decreased side‐effect expectations 52 . Research has indicated that side‐effect expectations mediate the association between increased suggestion of side‐effects from different sources, and later perception of side‐effects 9 .…”

Section: Discussionmentioning

confidence: 99%

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A systematic review of factors associated with side‐effect expectations from medical interventions

Smith

Webster

Rubin

2020

Health Expectations

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Background Fear of side‐effects can result in non‐adherence to medical interventions, such as medication and chemotherapy. Side‐effect expectations have been identified as strong predictors of later perception of side‐effects. However, research investigating predictors of side‐effect expectations is disparate. Objective To identify factors associated with side‐effect expectations. Search strategy We systematically searched Embase, Ovid MEDLINE, Global Health, PsycARTICLES, PsycINFO, Web of Science and Scopus. Inclusion criteria Studies were included if they investigated associations between any predictive factor and expectations of side‐effects from any medical intervention. Data extraction and synthesis We extracted information about participant characteristics, medication, rates of side‐effects expected and predictors of side‐effect expectations. Data were narratively synthesized. Main results We identified sixty‐four citations, reporting on seventy‐two studies. Predictors fell into five categories: personal characteristics, clinical characteristics, psychological traits and state, presentation format of information, and information sources used. Using verbal risk descriptors (eg ‘common’) compared to numerical descriptors (eg percentages), having lower quality of life or well‐being, and currently experiencing symptoms were associated with increased side‐effect expectations. Discussion and conclusions Decreasing unrealistic side‐effect expectations may lead to decreased experience of side‐effects and increased adherence to medical interventions. Widespread communications about medical interventions should describe the incidence of side‐effects numerically. Evidence suggests that clinicians should take particular care with patients with lower quality of life, who are currently experiencing symptoms and who have previously experienced symptoms from treatment. Further research should investigate different clinical populations and aim to quantify the impact of the media and social media on side‐effect expectations.

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Section: Resultsmentioning

confidence: 99%