Introduction and Hypothesis
Despite growing interest in a mobile-app bowel diary to assess fecal incontinence (FI) symptoms, data are limited regarding the correlation between mobile-app diary and ...questionnaire-based outcomes. The primary aim is to determine whether percentage reduction in FI episodes (FIEs)/week recorded on a mobile-app diary correlates with changes in scores of validated FI-symptom measures from baseline to 12 weeks in women with FI undergoing percutaneous tibial nerve stimulation (PTNS) versus sham.
Methods
This is a planned secondary analysis of a multicenter randomized trial in which women with FI underwent PTNS or sham. FIEs were collected using a mobile-app diary at baseline and after 12 weekly sessions. FI-symptom-validated measures included St. Mark’s, Accidental Bowel Leakage Evaluation, FI Severity Index (FISI), Colorectal Anal Distress Inventory, Colorectal Anal Impact Questionnaire, FI Quality of Life, Patient Global Impression of Improvement (PGI-I), and Patient Global Symptom Control (PGSC) rating. Spearman’s correlation coefficient (ρ) was computed between %-reduction in FIEs/week and change in questionnaire scores from baseline to 12 weeks. Significance was set at 0.005 to account for multiple comparisons.
Results
Baseline characteristics of 163 women (109 PTNS, 54 sham) include mean age 63.4±11.6, 81% white, body mass index 29.4±6.6 kg/m
2
, 4% previous FI surgeries, 6.6±5.5 FIEs/week, and St. Mark’s score 17.4±2.6. A significant correlation was demonstrated between %-reduction in FIEs/week and all questionnaires (
p
<0.005). A moderate-strength correlation (|ρ|>0.4) was observed for St. Mark’s (ρ=0.48), FISI (ρ=0.46), PGI-I (ρ=0.51), and PGSC (ρ=−0.43).
Conclusions
In women with FI randomized to PTNS versus sham, a moderate correlation was noted between FIEs measured via mobile-app diary and FI-symptom-validated questionnaire scores.
This article concerns how to estimate reliability (defined as the internal consistency of responses to a scale) in designs that are commonly used in studies of within-person variability. I present ...relevant issues, describe common errors, make recommendations for best practice, and discuss unresolved issues and future directions. I describe how to estimate the reliability of scales administered in studies in which observations are nested within persons, such as daily diary and “beeper” studies and studies of social interaction. Multilevel modeling analyses that include a measurement level can estimate the occasionlevel (e.g., days or beeps or interactions) reliability of scales. In such models, items on a scale are nested within occasions of measurement and occasions of measurement are nested within persons.
Objective: The timeline follow-back interview is a common method of collecting daily cigarette consumption (cigarettes per day CPD) in smoking research. However, it may be subject to recall bias due ...to its reliance on retrospective reports. The increasing ownership of smartphones allows researchers to administer app-based digital diaries (DD) to collect CPD, which is expected to have less recall bias. Several studies have compared these two methods and found a noticeable discrepancy between them. However, these studies have mainly focused on the time window when smokers were smoking ad libitum. In this study, we wanted to determine the comparability of these two methods when treatment-seeking smokers are attempting to quit smoking. Method: In a cessation trial, treatment-seeking smokers (n = 251) reported their CPD using the timeline follow-back and DD methods over a 12-week treatment period. To evaluate the comparability, we used the Bland-Altman comparison approach for agreement, correlational analysis between CPD and biochemical measures, digit bias, and logistic regression for predicting abstinence. Results: We found that the two methods exhibited good agreement, and the agreement did not vary as a function of consumption levels. Consistent with this agreement, CPD data from both methods showed similar correlations with biochemical measures of smoking and predicted 6-month abstinence in a comparable fashion. Despite the agreement, the DD method appeared to be more precise by having a lower digit bias than the timeline follow-back method. Conclusions: Capturing smoking behavior using either TLFB or DD approaches yields similar data while smokers are attempting to quit smoking.
Public Health Significance Statement
Our study provides evidence to support that the timeline follow-back interview and app-based digital diary methods to record daily cigarette consumption in smoking cessation studies are both valid. The validity of these methods allows researchers to use either method to accurately evaluate smoking cessation outcomes.
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