Development of the Person-Centered Contraceptive Counseling scale (PCCC), a short form of the Interpersonal Quality of Family Planning care scale.

OBJECTIVE: Person-centeredness is a critical component of quality in family planning. We previously validated an 11-item Interpersonal Quality of Family Planning (IQFP) scale. We sought to create a parsimonious version of the scale in preparation for testing its appropriateness as a patient-reported outcome performance measure. STUDY DESIGN: To explore clarity and importance of each of the 11 items, we conducted English and Spanish cognitive interviews with patients who received contraceptive counseling (n = 33) at 3 publicly funded California clinics. We triangulated these results with psychometric analysis of previously collected IQFP data (n = 1097) to assess validity and reliability of selected item combinations. RESULTS: The 11-item IQFP scale was reduced to a 4-item scale (the Person-Centered Contraceptive Counseling scale, or PCCC) that includes items evaluating provider performance regarding respect for patients, information provision, and eliciting and honoring patient preferences for birth control. Interview participants deemed the items included in the 4-item PCCC important and clear in both English and Spanish versions of the instrument. The 4-item PCCC retained the 11-item IQFP's psychometric properties, including internal consistency (Cronbach's alpha = 0.92 vs 0.97 for the PCCC and IQFP, respectively) and a consistent single factor analysis solution (factor loadings = 0.86-0.92 and 0.81-0.91). The 4-item PCCC additionally retained the construct and predictive validity of the IQFP. CONCLUSIONS: The 4-item PCCC is a valid and reliable as a measure of person-centered contraceptive counseling that reflects patients' perspectives on contraceptive counseling. IMPLICATIONS: Person-centered measures such as the 4-item PCCC can help inform efforts to improve health care quality. Future work will investigate the validity and reliability of the 4-item PCCC as a performance measure to determine the appropriateness of its use in the quality improvement context.

Analysis of climate signals in the crop yield record of sub-Saharan Africa.

Food security and agriculture productivity assessments in sub-Saharan Africa (SSA) require a better understanding of how climate and other drivers influence regional crop yields. In this paper, our objective was to identify the climate signal in the realized yields of maize, sorghum, and groundnut in SSA. We explored the relation between crop yields and scale-compatible climate data for the 1962-2014 period using Random Forest, a diagnostic machine learning technique. We found that improved agricultural technology and country fixed effects are three times more important than climate variables for explaining changes in crop yields in SSA. We also found that increasing temperatures reduced yields for all three crops in the temperature range observed in SSA, while precipitation increased yields up to a level roughly matching crop evapotranspiration. Crop yields exhibited both linear and nonlinear responses to temperature and precipitation, respectively. For maize, technology steadily increased yields by about 1% (13 kg/ha) per year while increasing temperatures decreased yields by 0.8% (10 kg/ha) per °C. This study demonstrates that although we should expect increases in future crop yields due to improving technology, the potential yields could be progressively reduced due to warmer and drier climates.