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Evidence Informed Decision Making(EIDM)

360 members Created Jun 23, 2023 public

Evidence Informed Decision Making

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Thanks for the prompt @Faith @Henry Magoba\'s pitch on youth unemployment really resonates with me.Drawing on my nutrition background, I would pitch that my 60 seconds go to the double burden of malnutrition among adolescents, a group too often missed…

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My 60-second policy pitch: Invest in young people\'s skills, livelihoods and future.If I had 60 seconds with a policymaker, I would ask them to address youth unemployment by investing in practical skills development, paid internships, mentorship and accessible opportunities for…

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Mwende@APHRC Admin started the topic Your 60-Second Policy Pitch: What Would You Tell a Policymaker? in Evidence Informed Decision Making(EIDM)

Let\'s get talking! 

Imagine you have just 60 seconds with a policymaker who can change ONE thing affecting young people in your community.

What issue would you raise, and what would you say to convince them to act?

Let\'s hear your best pitches! 

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Charles and Fortunate, this is the conversation I have been waiting to see in this group. Let me try to add something on each of your three questions, because I think the hardest one is the second.On proxy indicators, I…

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Fortunate, thank you for this thoughtful and methodologically grounded response — you have captured the core tension perfectly.I agree — we must not confuse linearity in logframes with linearity in healing. Psychosocial recovery is non-linear, yet our accountability systems demand…

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I suggest that the challenge extends beyond establishing measurable endpoints. It also involves deciding whose understanding of success informs those endpoints.For example, in a community-based adolescent mental health programme, researchers may define success through improved psychological assessment scores, while young…

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I particularly appreciate the emphasis on recognising frontline observations as legitimate evidence and developing formal mechanisms through which such observations can inform model governance.I would like to extend the discussion by considering the institutional power relations that determine whose knowledge…

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Thank you, for raising an important issue that speaks directly to how we conceptualise evidence, progress and accountability in mental health programming.I believe one of the challenges is that our monitoring and evaluation systems sometimes assume that meaningful change follows…

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Hello EIDM colleagues,

A challenge we rarely discuss openly:
A challenge we rarely discuss openly:In mental health and psychosocial programs, the most meaningful outcomes — restored functioning, renewed hope, reduced internalized stigma — are often invisible for 3-6 months. They don\'t show up in our quarterly dashboards.
Yet funders and systems ask for \"evidence of impact\" in 30-60 days.
So what do we do in the meantime?
At community level, we see practitioners using proxy evidence: attendance consistency, peer support initiation, family re-engagement, sleep routines returning. These are not in standard logframes, but they predict recovery.
My question to this community:
1. What proxy indicators have you found legitimate to count as early evidence of mental health progress?
2. How do we defend those proxies as rigorous evidence, not just anecdotes, to decision-makers?
3. When should we say \"the evidence is not yet observable\" and still justify continuing?

I believe EIDM in mental health needs a conversation about interim evidence — what we count while we wait for the real change.
Curious to learn how others in this group of 358 members are navigating this.
Looking forward to your thoughts.— Charles
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@Charles Bawate Bawate thank you for this generous synthesis. Your sharpened line is one I\'d sign: A retired model is not failure. A revalidated model answering the wrong question is not success. Failure is keeping a blind algorithm alive because…

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Thank you Rhoda and Nonvicks for this rich pushback — you both moved my thinking forward.Rhoda, thank you for naming the fault line so clearly. I agree: frontline observation becomes evidence the moment we design it to be traceable —…

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@Charles Frontline observations must be treated as formal sentinel data, not mere anecdote. Lived experience legitimately triggers revalidation when field teams see recurring patterns across districts, when workers must rely on operational workarounds, or when structural conditions like cash-transfer policies or…

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@Charles Bawate you\'ve put your finger on the fault line that runs through most evidence systems: frontline observation is treated as anecdote precisely because it arrives informally, not because it\'s weak. My view is that lived experience should count as…

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Colleagues,

Building from a rich discussion in our ABM CoP on model decay and retirement, I want to bring a question to this EIDM group.
We agreed that models can drift — calibration from 2020 does not fit 2026 reality after policy shifts, health campaigns, mobile money expansion etc.
But an important point emerged: drift is often felt by field teams and communities before it shows up in the dashboard.

In our programs, a field officer saying \"this is not what we see anymore\" is often the first signal. Yet in many evidence frameworks, that observation is logged as \"anecdote,\" not evidence. It has no formal route into model governance.
Rhoda\'s challenge was sharp: if field teams are the early-warning system, they need a formal role — a standing agenda item, a named custodian — not an informal conversation.
So my question to this community:
1. When should lived experience and frontline observation count as legitimate evidence to trigger revalidation or retirement of a model/tool?

2. How have you formalized it? Do you have a governance mechanism where community sensing automatically opens an evidence review?

3. What is the minimum documentation needed so another local team can re-run and revalidate without the original modeller?
My working view: A retired model is not failure. Keeping an outdated model alive because we have no mechanism to hear the community is failure.
Would love to learn how others are handling this tension between formal evidence and lived experience.
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Hello, I am Alphoncina Kagaigai, working with Muhimbili University of Health and Allied Sciences, Tanzania. My research interest revolves around health economics, especially in health financing and economic evaluation. 

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