Examining the normality assumption of a design-comparable effect size in single-case designs.

What Works Clearinghouse (WWC, 2022) recommends a design-comparable effect size (D-CES; i.e., gAB) to gauge an intervention in single-case experimental design (SCED) studies, or to synthesize findings in meta-analysis. So far, no research has examined gAB's performance under non-normal distributions. This study expanded Pustejovsky et al. (2014) to investigate the impact of data distributions, number of cases (m), number of measurements (N), within-case reliability or intra-class correlation (ρ), ratio of variance components (λ), and autocorrelation (ϕ) on gAB in multiple-baseline (MB) design. The performance of gAB was assessed by relative bias (RB), relative bias of variance (RBV), MSE, and coverage rate of 95% CIs (CR). Findings revealed that gAB was unbiased even under non-normal distributions. gAB's variance was generally overestimated, and its 95% CI was over-covered, especially when distributions were normal or nearly normal combined with small m and N. Large imprecision of gAB occurred when m was small and ρ was large. According to the ANOVA results, data distributions contributed to approximately 49% of variance in RB and 25% of variance in both RBV and CR. m and ρ each contributed to 34% of variance in MSE. We recommend gAB for MB studies and meta-analysis with N ≥ 16 and when either (1) data distributions are normal or nearly normal, m = 6, and ρ = 0.6 or 0.8, or (2) data distributions are mildly or moderately non-normal, m ≥ 4, and ρ = 0.2, 0.4, or 0.6. The paper concludes with a discussion of gAB's applicability and design-comparability, and sound reporting practices of ES indices.

Dealing with missing data by EM in single-case studies.

Single-case experimental design (SCED) research plays an important role in establishing and confirming evidence-based practices. Due to multiple measures of a target behavior in such studies, missing information is common in their data. The expectation-maximization (EM) algorithm has been successfully applied to deal with missing data in between-subjects designs, but only in a handful of SCED studies. The present study extends the findings from Smith, Borckardt, and Nash (2012) and Velicer and Colby (2005b, Study 2) by systematically examining the performance of EM in a baseline-intervention (or AB) design under various missing rates, autocorrelations, intervention phase lengths, and magnitudes of effects, as well as two fitted models. Three indicators of an intervention effect (baseline slope, level shift, and slope change) were estimated. The estimates' relative bias, root-mean squared error, and relative bias of the estimated standard error were used to assess EM's performance. The findings revealed that autocorrelation impacted the estimates' qualities most profoundly. Autocorrelation interacted with missing rate in impacting the relative bias of the estimates, impacted the root-mean squared error nonlinearly, and interacted with the fitted model in impacting the relative bias of the estimated standard errors. A simpler model without autocorrelation can be used to estimate baseline slope and slope change in time-series data. EM is recommended as a principled method to handle missing data in SCED studies. Two decision trees are presented to assist researchers and practitioners in applying EM. Emerging research directions are identified for treating missing data in SCED studies.

Beliefs about Supporting Mothers to Exclusively Breastfeed for 6 Months: An Elicitation Study of Health Professionals Working in Maternal-Child Health Clinics in Nairobi, Kenya.

BACKGROUND: Exclusive breastfeeding rates remain low in Kenya and determinants influencing mothers' practice are documented. Little is known about factors underlying health professionals' intention to support mothers to continue exclusive breastfeeding. Effective behavior modification requires designing interventions at multiple levels of influence, informed by theory-based research to identify relevant determinants. OBJECTIVES: To identify salient beliefs held by health professionals about support of mothers to exclusively breastfeed for 6 months and to explore definitions of the term support. METHODS: This qualitative study was conducted in 6 public health facilities in Nairobi, Kenya. We used open-ended questions based on the reasoned action approach to elicit salient consequences, referents, and circumstances perceived by 15 health professionals about support for mothers to exclusively breastfeed for 6 months. RESULTS: The most frequently mentioned consequences were healthier babies (87%) and reduced childhood ailments (67%). The main disadvantage was human immunodeficiency virus transmission through breast milk (33%). Colleagues (80%) and managers (67%) were perceived as approving referents, whereas some mothers/couples (40%) and the breast milk substitute industry (20%) were perceived as disapproving. Facilitating circumstances included lighter workload, better training, and more time. Definitions of support were varied and included giving information and demonstrating positioning and attachment techniques. CONCLUSIONS: Overall, health professionals perceived positive consequences toward supporting exclusive breastfeeding continuation and identified a number of approving referents. However, they reported challenging circumstances in the work environment, which managers need to address to help health professionals provide the support needed by Kenyan mothers to continue exclusive breastfeeding.

Computing tools for implementing standards for single-case designs.

In the single-case design (SCD) literature, five sets of standards have been formulated and distinguished: design standards, assessment standards, analysis standards, reporting standards, and research synthesis standards. This article reviews computing tools that can assist researchers and practitioners in meeting the analysis standards recommended by the What Works Clearinghouse: Procedures and Standards Handbook-the WWC standards. These tools consist of specialized web-based calculators or downloadable software for SCD data, and algorithms or programs written in Excel, SAS procedures, SPSS commands/Macros, or the R programming language. We aligned these tools with the WWC standards and evaluated them for accuracy and treatment of missing data, using two published data sets. All tools were tested to be accurate. When missing data were present, most tools either gave an error message or conducted analysis based on the available data. Only one program used a single imputation method. This article concludes with suggestions for an inclusive computing tool or environment, additional research on the treatment of missing data, and reasonable and flexible interpretations of the WWC standards.

The sensitivity of three methods to nonnormality and unequal variances in interval estimation of effect sizes.

Confidence interval (CI) estimation for an effect size (ES) provides a range of possible population ESs supported by data. In this article, we investigated the noncentral t method, Bonett's method, and the bias-corrected and accelerated (BCa) bootstrap method for constructing CIs when a standardized linear contrast of means is defined as an ES. The noncentral t method assumes normality and equal variances, Bonett's method assumes only normality, and the BCa bootstrap method makes no assumptions. We simulated data for three and four groups from a variety of populations (one normal and five nonnormals) with varied variance ratios (1, 2.25, 4, 8), population ESs (0, 0.2, 0.5, 0.8), and sample size patterns (one equal and two unequal). Results showed that the noncentral method performed the best among the three methods under the joint condition of ES = 0 and equal variances. Performance of the noncentral method was comparable to that of the other two methods under (1) equal sample size, unequal weight for each group, and the last group sampled from a leptokurtic distribution, or (2) equal sample size and equal weight for all groups, when all are sampled from a normal population, or only the last group sampled from a nonnormal distribution. In the remaining conditions, Bonett's and the BCa bootstrap methods performed better than the noncentral method. The BCa bootstrap method is the method of choice when the sample size per group is 30 or more. Findings from this study have implications for simultaneous comparisons of means and of ranked means in between- and within-subjects designs.

Physician communication behaviors from the perspective of adult HIV patients in Kenya.

OBJECTIVE: We describe perceived physician communication behaviors and its association with adherence to care, among HIV patients in Kenya. DESIGN: This cross-sectional study was conducted between July and August 2011. SETTING: The study was conducted in three adult HIV clinics within the Academic Model Providing Healthcare program in western Kenya. PARTICIPANTS: HIV adult patients. MAIN OUTCOME MEASURES: Patient's predisposition to attend clinic, missed appointment and missed combined antiretroviral therapy (cART) medication. RESULTS: A total of 400 patients were enrolled and participated in the study; the median age was 38 years (IQR = 33-44) and 56.5% were female. Patients perceived physicians engaged in a high number of communication behaviors (mean = 3.80, range 1-5). A higher perceived general health status (P = 0.01), shorter distance to the health facility (P = 0.03) and lesser time spent at the health facility (P = 0.02) were associated with a higher number of perceived physician communication behaviors. Physician-patient relationship factors were not associated with physician communication behaviors. In addition, a higher number of perceived physician communication behaviors was associated with a very high likelihood of patients' attending the next HIV clinic [adjusted odds ratio (AOR): 1.89, 95% confidence interval (CI): 1.49-2.40], a lower likelihood of patients' missing an appointment (AOR: 0.75, 95% CI: 0.61-0.92) and missing cART medication (AOR: 0.68, 95% CI: 0.52-0.87). CONCLUSION: Patients' perception of physician communication behaviors was found to be associated with their adherence to HIV care.

Principled missing data methods for researchers.

The impact of missing data on quantitative research can be serious, leading to biased estimates of parameters, loss of information, decreased statistical power, increased standard errors, and weakened generalizability of findings. In this paper, we discussed and demonstrated three principled missing data methods: multiple imputation, full information maximum likelihood, and expectation-maximization algorithm, applied to a real-world data set. Results were contrasted with those obtained from the complete data set and from the listwise deletion method. The relative merits of each method are noted, along with common features they share. The paper concludes with an emphasis on the importance of statistical assumptions, and recommendations for researchers. Quality of research will be enhanced if (a) researchers explicitly acknowledge missing data problems and the conditions under which they occurred, (b) principled methods are employed to handle missing data, and (c) the appropriate treatment of missing data is incorporated into review standards of manuscripts submitted for publication.

Psychometric Assessment of a Physician-Patient Communication Behaviors Scale: The Perspective of Adult HIV Patients in Kenya.

Introduction. There have been no scales specifically developed to assess physician-patient communication behaviors (PPCB) in the sub-Saharan population. Aim. We revised an existing PPCB scale and tested its psychometric properties for HIV patients in Kenya. Methods. 17 items (five-point scale) measuring PPCB were initially adopted from the Matched Pair Instrument (MPI). Between July and August 2011, we surveyed a convenient sample of 400 HIV adult patients, attending three Academic Model Providing Healthcare program (AMPATH) clinics in Eldoret, Kenya. Of these 400, eight also participated in cognitive interviews, and 200 were invited to return after one week for follow-up interviews; 134 (67%) returned and were interviewed. Construct and content validity were established using an exploratory factor analysis, bivariate analyses, internal consistency, test-retest reliability and cognitive interviews. Results. Construct and content validity supported a one-dimensional measure of 13 PPCB items. Items assessed physicians' effort to promote a favorable atmosphere for interaction with HIV patients. Biases associated with encoding and comprehension of specific terms, such as "discussion, involvement or concerns," were noted. Internal consistency (Cronbach's alpha = .81) and one-week retest reliability scores (.82) supported the reliability of the 13-item scale. Discussion. The revised PPCB scale showed acceptable validity and reliability in Kenya.