Background: Recruitment of health research participants through social media is becoming more common. In the United States, 80% of adults use at least one social media platform. Social media platforms may allow researchers to reach potential participants efficiently. However, online research methods may be associated with unique threats to sample validity and data integrity. Limited research has described issues of data quality and authenticity associated with the recruitment of health research participants through social media, and sources of low-quality and fraudulent data in this context are poorly understood. Objective: The goal of the research was to describe and explain threats to sample validity and data integrity following recruitment of health research participants through social media and summarize recommended strategies to mitigate these threats. Our experience designing and implementing a research study using social media recruitment and online data collection serves as a case study. Methods: Using published strategies to preserve data integrity, we recruited participants to complete an online survey through the social media platforms Twitter and Facebook. Participants were to receive $15 upon survey completion. Prior to manually issuing remuneration, we reviewed completed surveys for indicators of fraudulent or low-quality data. Indicators attributable to respondent error were labeled suspicious, while those suggesting misrepresentation were labeled fraudulent. We planned to remove cases with 1 fraudulent indicator or at least 3 suspicious indicators. Results: Within 7 hours of survey activation, we received 271 completed surveys. We classified 94.5% (256/271) of cases as fraudulent and 5.5% (15/271) as suspicious. In total, 86.7% (235/271) provided inconsistent responses to verifiable items and 16.2% (44/271) exhibited evidence of bot automation. Of the fraudulent cases, 53.9% (138/256) provided a duplicate or unusual response to one or more open-ended items and 52.0% (133/256) exhibited evidence of inattention. Conclusions: Research findings from several disciplines suggest studies in which research participants are recruited through social media are susceptible to data quality issues. Opportunistic individuals who use virtual private servers to fraudulently complete research surveys for profit may contribute to low-quality data. Strategies to preserve data integrity following research participant recruitment through social media are limited. Development and testing of novel strategies to prevent and detect fraud is a research priority.
Purpose: Although patient-reported cancer symptoms and quality-of-life issues (SQLIs) have been promoted as essential to a comprehensive assessment, efficient and efficacious methods have not been widely tested in clinical settings. The purpose of this trial was to determine the effect of the Electronic Self-Report Assessment–Cancer (ESRA-C) on the likelihood of SQLIs discussed between clinicians and patients with cancer in ambulatory clinic visits. Secondary objectives included comparison of visit duration between groups and usefulness of the ESRA-C as reported by clinicians. Patients and Methods: This randomized controlled trial was conducted in 660 patients with various cancer diagnoses and stages at two institutions of a comprehensive cancer center. Patient-reported SQLIs were automatically displayed on a graphical summary and provided to the clinical team before an on-treatment visit (n = 327); in the control group, no summary was provided (n = 333). SQLIs were scored for level of severity or distress. One on-treatment clinic visit was audio recorded for each participant and then scored for discussion of each SQLI. We hypothesized that problematic SQLIs would be discussed more often when the intervention was delivered to the clinicians. Results: The likelihood of SQLIs being discussed differed by randomized group and depended on whether an SQLI was first reported as problematic (P = .032). Clinic visits were similar with regard to duration between groups, and clinicians reported the summary as useful. Conclusion: The ESRA-C is the first electronic self-report application to increase discussion of SQLIs in a US randomized clinical trial.
Purpose: The purpose of this trial was to evaluate the effect of a Web-based, self-report assessment and educational intervention on symptom distress during cancer therapy. Patients and Methods: A total of 752 ambulatory adult participants were randomly assigned to symptom/quality-of-life (SxQOL) screening at four time points (control) versus screening, targeted education, communication coaching, and the opportunity to track/graph SxQOL over time (intervention). A summary of the participant-reported data was delivered to clinicians at each time point in both groups. All participants used the assessment before a new therapeutic regimen, at 3 to 6 weeks and 6 to 8 weeks later, completing the final assessment at the end of therapy. Change in Symptom Distress Scale–15 (SDS-15) score from pretreatment to end of study was compared using analysis of covariance and regression analysis adjusting for selected variables. Results: We detected a significant difference between study groups in mean SDS-15 score change from baseline to end of study: 1.27 (standard deviation [SD], 6.7) in the control group (higher distress) versus −0.04 (SD, 5.8) in the intervention group (lower distress). SDS-15 score was reduced by an estimated 1.21 (95% CI, 0.23 to 2.20; P = .02) in the intervention group. Baseline SDS-15 score (P < .001) and clinical service (P = .01) were predictive. Multivariable analyses suggested an interaction between age and study group (P = .06); in subset analysis, the benefit of intervention was strongest in those age > 50 years (P = .002). Conclusion: Web-based self-care support and communication coaching added to SxQOL screening reduced symptom distress in a multicenter sample of participants with various diagnoses during and after active cancer treatment. Participants age > 50 years, in particular, may have benefited from the intervention.
1 October 2013 in Urologic Oncology: Seminars and Original Investigations
Background: Therapeutic cancer chemotherapy is most successful when complete dosing is achieved. Because many newer therapeutic agents are oral and self-administered by the patient, adherence is a concern. The purpose of our analysis was to explore relationships between adherence, patient characteristics, and barriers to adherence. Methods: This secondary analysis utilized self-reported data from a randomized trial of self-care management conducted at two cancer centers in the US. Symptom distress was measured using the 15-item Symptom Distress Scale (SDS-15) and depression with the Patient Health Questionnaire-9 (PHQ-9). Adherence to oral medication was self-reported using the 8-item Morisky Medication Adherence Scale (MMAS-8). Measures were collected via Web-based, study-specific software ~8 weeks after treatment start date. Odds of low/medium adherence (score <8) were explored using univariate logistic regression. Given the number of factors and possible relationships among factors, a classification tree was built in lieu of a multivariable logistic regression model. Results: Of the eligible participants enrolled, 77 were on oral therapy and 70 had an MMAS score. Forty-nine (70%) reported a high adherence score (=8). Higher odds of low/medium adherence were associated with greater symptom distress (P=0.09), more depression (P=0.05), chemotherapy vs hormonal oral medication (P=0.03), being female (P=0.02), and being randomized to the control group in the parent trial (P=0.09). Conversely, high adherence was associated with working (P=0.08), being married/partnered (P=0.004), and being older (P=0.02). Factors identified as significantly related to low/medium adherence from the univariate logistic regression analyses were supported by the classification tree results. Conclusion: Nonadherence to therapeutic oral medications in patients with cancer was associated with being unmarried/unpartnered, symptom distress, younger age, not working, and female sex. These findings may help to identify patients at risk for nonadherence and for whom supportive interventions to enhance adherence may be needed.