Determinant Factors of Participation in Decision Making in Rural Communities: In Perspective of Gender

BACKGROUND Evidence based practice is a key to increase effectiveness and efficiency of quality health services. To achieve this, utilization of health facility data (DHIS2 data) is required which is determined by knowledge and attitudes of health professionals. Thus, this study aimed to assess knowledge and attitudes of health professionals to use DHIS2 data for decision making. OBJECTIVE This study aimed to assess the knowledge, attitudes and its associated factors among health professionals to use DHIS2 data for decision making at South west of Ethiopia 2020 METHODS Cross sectional quantitative study methods was conducted to assess Knowledge and Attitudes of health professionals to use DHIS2 data. A total of 264 participants were approached. SPSS version 22 software was used for data entry and analysis. Descriptive and analytical statistics including Bivariable and Multivariable analyses was done RESULTS Overall 130(49.2%) of the respondents had good knowledge to use DHIS2 data (95% CI: [43, 55.3]), whereas over 149 (56.4%) of the respondents had favorable attitudes towards the use of DHIS2 data for decision making purpose (95% CI: [53.2, 59.8]). Skills [AOR=2.20,95% CI:(1.16, 4.19)], Age [AOR= 1.92, 95% CI: (1.03, 3.59)] ,Resources[AOR=2.56, 95% CI:(1.35,4.86)], Staffing[AOR= 2.85, 95% CI : (1.49, 5.48)] and Experiences[AOR= 4.66, 95% CI: (1.94, 5.78)] were variables associated with knowledge to use DHIS2 data whereas Training [AOR= 5.59, 95% CI: (2.48, 5.42)], Feedback [AOR= 4.08, 95% CI: (1.87, 8.91)], Motivation [AOR=2.87, 95% CI: (1.36, 6.06)] and Health need [AOR=2.32, 95% CI: (1.10-4.92)] were variables associated with attitudes of health professionals to use DHIS2 data CONCLUSIONS In general, about half of the study participants had good knowledge of DHIS2 data utilization whereas more than half of respondents had favorable attitudes. Skills, resources, ages, staffing and experiences were the most determinant factors for the knowledge to use DHIS2 data whereas health need, motivation, feedback and training were determinant factors for attitudes to use DHIS2 data

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Towards a better understanding of the link between participation in decision-making and organizational citizenship behaviour: A multilevel analysis

Journal of Occupational and Organizational Psychology ◽

10.1348/096317999166734 ◽

1999 ◽

Vol 72 (3) ◽

pp. 377-392 ◽

Cited By ~ 98

Author(s):

Nico W. Vanyperen ◽

Agnes E. Berg ◽

Martijn C. Willering

Keyword(s):

Decision Making ◽

Multilevel Analysis ◽

Organizational Citizenship ◽

Participation In Decision Making

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Spending Political Capital*

The Economic Journal ◽

10.1093/ej/ueab040 ◽

2021 ◽

Author(s):

Arthur Campbell

Keyword(s):

Decision Making ◽

Incentive Contracts ◽

Important Task ◽

Political Capital ◽

Alternative Mechanism ◽

Team Size ◽

Current Period ◽

Multi Agent ◽

Participation In Decision Making ◽

Number Of Individuals

Abstract An important task for organizations is establishing truthful communication between parties with differing interests. This task is made particularly challenging when the accuracy of the information is poorly observed or not at all. In these settings, incentive contracts based on the accuracy of information will not be very effective. This paper considers an alternative mechanism that does not require any signal of the accuracy of any information communicated to provide incentives for truthful communication. Rather, an expert sacrifices future participation in decision-making to influence the current period’s decision in favour of their preferred project. This mechanism captures a notion often described as ‘political capital’ whereby an individual is able to achieve their own preferred decision in the current period at the expense of being able to exert influence in future decisions (‘spending political capital’). When the first-best is not possible in this setting, I show that experts hold more influence than under the first-best and that, in a multi-agent extension, a finite team size is optimal. Together these results suggest that a small number of individuals hold excessive influence in organizations.

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