Communal Innovations: Inspiring Neighborhoods of Hope and Advocacy

Figures & data

Figure 1. Theoretical model of situation appraisal (innovation attributes, issue importance, storytelling network, and collective efficacy) and advocacy effects on innovation-related hope.

Table 1. Descriptive statistics and global Moran’s I (N = 119)

	M	SD	Global Moran’s I
Neighborhood storytelling	3.42	0.69	−.03
Collective efficacy	3.54	0.62	−.04
Innovation attributes	4.01	0.59	.03
Recent malaria	−.65	0.77	−.01
Innovation advocacy	2.64	1.43	−.14*
Innovation hope	3.75	0.71	.01

Notes. The overall spatial clustering (global Moran’s I) was based on a distance-based spatial weights matrix (using a 60 m threshold). Recent malaria was effect-coded (1 = sick with malaria in the past 2 weeks; −1 = not sick); 17.6% reported being sick with malaria in the past 2 weeks.

*p <.05.

Figure 2. Visual depiction of the community. Participating households are marked with circles; the colors indicate each household’s level of innovation advocacy from light blue (never advocating) to dark blue (advocating all the time). The dark black line indicates a main road that cuts through the community.

Table 2. Regression estimates predicting innovation hope (N = 119)

	OLS Estimation			Spatial Lag Model
	b	SE	t	b	SE	z
Collective efficacy	0.02	0.10	0.24	0.02	0.09	0.20
Innovation attributes	0.62	0.10	6.03*	0.62	0.10	6.26*
Recent malaria illness	−0.14	0.08	−1.82†	−0.13	0.07	−1.78†
Innovation advocacy	0.00	0.04	0.06	0.00	0.04	−0.03
W_Innovation hope	–	–	–	−0.12	0.15	−0.79
Adjusted R^2	.29*			.32*
Akaike info criterion (AIC)	221.64			223.10
Log likelihood	−105.82			−105.55

Notes. “W” identifies the spatial lag term. Model for the OLS estimate was statistically significant, F(5, 114) = 12.95, p <.01, adjusted R² =.29. The spatial lag model was based on a distance-based spatial weights matrix (using a 60 m threshold).

*p <.05, † p <.10.

Table 3. Regression estimates predicting innovation advocacy (N = 119)

	OLS Estimation			Spatial Lag Model
	b	SE	t	b	SE	z
Collective efficacy	0.59	0.20	2.96*	0.57	0.19	2.99*
Innovation attributes	0.68	0.21	3.21*	0.64	0.20	3.19*
Recent malaria illness	0.34	0.16	2.09*	0.32	0.15	2.07*
W_Innovation advocacy				−0.34	0.16	−2.08*
adjusted R^2	.18*			.24*
Akaike info criterion (AIC)	403.02			400.79
Log likelihood	−197.51			−195.40

Notes. “W” identifies the spatial lag term. Model for the OLS estimate was statistically significant, F(4, 115) = 9.54, p <.01, adjusted R² =.18. The spatial lag model was based on a distance matrix.

*p <.05.