A Library of Logic Models to Explain How Interventions to Reduce Diagnostic Errors Work

Mixed method evaluation of a learning from excellence programme for community health workers in Neno, Malawi

BACKGROUND

Community Health Workers (CHWs) play an essential role in linking communities to facility-based healthcare. However, CHW programmes have often been hampered by low levels of staff motivation, and new tools aimed at improving staff motivation and work environment are needed. One such intervention is the "Learning from Excellence" (LfE) programme. We aimed to assess feasibility, outputs, and impact of a co-designed LfE programme on CHW motivation, in Neno District.

METHODS

We conducted a convergent mixed-method evaluation of the LfE programme. Co-design of the programme and forms took place between October 2019 and January 2020. LfE forms submitted between September and November 2020 were analysed using descriptive statistics and memos summarising answers to the open-ended question. To investigate experiences with LfE we conducted in-depth semi-structured interviews with key stakeholders, CHWs, and site supervisors, which were analysed thematically. A pre-post intervention questionnaire was developed to assess the impact of the co-designed LfE intervention on CHW motivation and perceived supervision. Outcomes were triangulated into a logic model.

RESULTS

In total 555 LfE forms were submitted, with 34.4% of CHWs in Neno District submitting at least one LfE report. Four themes were identified in the interviews: LfE implementation processes, experience, consequences, and recommendations. A total of 50 CHWs participated in the questionnaire in January 2020 and 46 of them completed the questionnaire in December 2020. No statistically significant differences were identified between pre-and post-LfE measurements for both motivation (Site F: p = 0.86; Site G: p = 0.31) and perceived supervision (Site F: p = 0.95; Site G: p = 0.45). A logic model, explaining how the LfE programme could impact CHWs was developed.

CONCLUSIONS

Many CHWs participated in the LfE intervention between September 2020 and November 2020. LfE was welcomed by CHWs and stakeholders as it allowed them to appreciate excellent work in absence of other opportunities to do so. However, no statistically significant differences in CHW motivation and perceived supervision were identified. While the intervention was feasible in Neno District, we identified several barriers and facilitators for implementation. We developed a logic model to explain contextual factors, and mechanisms that could lead to LfE outcomes for CHWs in Neno District. The developed logic model can be used by those designing and implementing interventions like LfE for health workers.

Outcomes, mechanisms and contextual factors of positive psychology interventions for health workers: a systematic review of global evidence

BACKGROUND

Interventions using positive psychology (PP), which build on positive qualities of healthcare personnel and institutions, could potentially enhance organisational performance in healthcare. The aim of this systematic review was to identify if PP interventions have an impact on organisational performance of healthcare personnel, and if so, how this impact can be achieved. We developed a logic model to explain the impact of PP interventions on organisational performance.

METHODS

We searched Web of Science, Medline, Psychinfo, Embase, Scopus and CINAHL (from inception until March 2019) and references of included articles to identify studies that evaluated the impact of a PP intervention for health personnel. Study quality was assessed using the SQUIRE checklist for quality improvement studies. Data were extracted about study details, setting, participants, intervention, method of evaluation and results. Outcomes, mechanisms and contexts were coded in nVivo. Data synthesis was guided by Lewis' theory of the impact of PP interventions on organisational performance and Kneale et al.'s method for logic model development. Collected data were integrated into a logic model explaining initial inputs, processes, and intermediate outcomes of PP interventions that lead to improved organisational performance in healthcare settings.

RESULTS

We retrieved 4638 articles and identified five through references of included articles of which 29 studies (31 articles) met our inclusion criteria. Most articles were of low quality (n = 19) and outcome measures varied widely. We identified 54 different outcomes of PP interventions, including 'improved well-being' and 'improved interaction and support'. Forty-nine mechanisms were identified including 'recognising and reframing negative interpretations'. Twenty four contextual factors were identified of which seven acted as barriers. 'Managerial support' was a facilitator mentioned in eight studies. All identified outcomes, mechanisms and contextual factors were integrated into a logic model explaining how interventions using PP can impact organisational performance in healthcare.

CONCLUSION

Few identified outcomes were statistically significant, however, trends in both quantitative and qualitative outcomes show that PP interventions can increase well-being and interaction and support and thus improve organisational performance in healthcare. The developed logic model can be used in the implementation and evaluation of interventions using PP for health personnel.