Begin with the decision the NGO must make
An NGO planning a project in São Tomé and Príncipe needs more than a starting percentage. A baseline must explain whose circumstances are being measured, which services or behaviours are relevant, and how the same indicators can be measured again. São Tomé and Santo António offer two useful fieldwork perspectives: the principal urban centre on São Tomé island and the main town on Príncipe island. The locations can expose differences that a single-city pilot might miss, but they are not, on their own, a national sample.
Start with a decision workshop involving programme management, monitoring staff and implementing partners. Identify the decisions that cannot be made responsibly without new evidence: which groups should be prioritised, whether a service gap is primarily about distance or quality, and what magnitude of change the programme expects. Translate each decision into two or three answerable baseline questions. This process prevents the survey from becoming a catalogue of interesting indicators that nobody will use. Record how the resulting findings will influence location selection, budgeting or programme design.
Understand how research geography works in São Tomé and Príncipe
Fieldwork should follow the administrative vocabulary used in São Tomé and Príncipe: districts and the autonomous region of Príncipe. These structures help researchers identify the correct boundaries, local gatekeepers and likely sources of population lists, but they do not automatically supply a complete probability sampling frame. First establish which boundaries apply to the actual programme area, then verify maps and household or facility counts. Administrative labels should be used only after checking their exact local meaning and relationship to the study population. Where islands and separated population centres shape coverage, sampling and transport budgets must treat each catchment as distinct rather than assuming a single urban team can reach all groups.
Define the target population and sampling frame
Sampling quality depends on how people can enter the study, not simply how many questionnaires are completed. Construct a frame with clearly defined geographic and eligibility boundaries. If households are selected through multiple stages, track selected clusters and household selection rules; if facilities are sampled, separate a facility census from interviews with its users. Anticipate nonresponse and predefine replacement procedures. A two-city study can estimate outcomes for well-defined urban populations when designed for that purpose, but it cannot automatically claim to represent every region.
Baseline research in São Tomé: designing the first city sample
In São Tomé, where the city functions as the principal urban centre on São Tomé island, a baseline might start with an inventory of programme catchments and service points. If the intervention concerns climate adaptation and agricultural resilience, the field team should test measures of exposure to shocks, land-use practices, access to inputs and livelihood recovery. Interviewer routes should deliberately cover selected neighbourhoods rather than concentrating around accessible offices and major roads. Compare the register of intended participants with people who actually use services; discrepancies may expose targeting or access problems. Whether the unit is a household, young person, facility or beneficiary must remain consistent through analysis.
Baseline research in Santo António: testing a contrasting city context
Santo António deserves an independent field plan because it is the main town on Príncipe island. Before importing the São Tomé questionnaire unchanged, conduct a short cognitive pilot and verify where the target population resides, travels and receives services. The sample allocation should reflect the stated comparison question, not an arbitrary equal split made for convenience. If the NGO needs a comparison between the two cities, agree the minimum precision and subgroup coverage needed. Findings should describe the observed difference without attributing it automatically to geography or programme performance.
Build indicators that can be measured again
Programme dashboards often group together activity counts, outputs and outcomes, but a baseline primarily needs interpretable starting values for the intended results. Define what counts as a person reached, a household with access, a user satisfied or a facility functioning. For sensitive measures, confirm privacy before selecting a mode. Set out missing-value rules and calculation conventions in advance. This protects the study from retrospective threshold-setting once the team has seen the data.
Choose appropriate survey and qualitative methods
Selecting CAPI, CATI or CAWI is a coverage decision before it is a technology decision. CAPI helps where interviewers must locate households or verify assets. CATI can be efficient when phone numbers form a credible frame, but shared phones and unreachable numbers may affect who responds. CAWI works for digitally reachable populations, not automatically for everyone. Add observation and interviews with service providers when respondent accounts need contextual interpretation. Document any mixed-mode effects before combining the results.
Translate and pilot instruments for local respondents
Tools and consent scripts should be tested in Portuguese, Forro and other locally relevant creoles. A language that works for a formal meeting may not be the clearest language for a household interview, and bilingual respondents may switch vocabulary when describing sensitive experiences. Prepare a glossary for core constructs, reconcile translations with the source questionnaire and role-play difficult questions. Recruit interviewers for language competence and cultural familiarity, not only device skills. Translation changes need recorded approval so that future midline and endline rounds can preserve conceptual equivalence.
Design field operations around actual access conditions
Operationally, the two-island design needs distinct transport and translation assumptions. Plan interviewer assignments, transport, safe operating hours, supervision and escalation around this reality. An initial reconnaissance visit can check listing feasibility, accessibility, the actual duration of an interview and any mismatch between administrative maps and lived settlement boundaries. A rigorous pilot should include sample-selection rehearsal, consent practice, skip-logic tests and mock data submission. Budget for replacements that comply with the original selection procedure rather than allowing opportunistic substitution when a respondent is absent.
Protect consent, privacy and vulnerable participants
Informed consent should explain the study purpose, voluntary participation, the expected length of contact and the treatment of personal information. Beneficiaries must not assume that declining an interview will affect their assistance. Collect only identifiers needed for follow-up, store contact lists separately from analytical data, and restrict access according to role. Sensitive subjects may require private interview spaces, interviewer matching or referral procedures. Review applicable permissions and data-protection obligations locally before fieldwork rather than relying on a generic pan-African consent script.
Check quality while fieldwork is still active
Digital collection can enforce range checks, but the research still needs people and procedures. Supervisors should observe interviews, audit respondent selection, review suspicious patterns and ensure that genuine refusals are recorded. Training must address leading probes, substitution of selected households and pressure to meet numerical targets. A short feedback cycle allows correction before weaknesses contaminate the full sample. At closure, reconcile accepted interviews, exclusions, weights, field incidents and outstanding quality flags.
Analyse change without overstating causal claims
Turn the baseline into a measurement asset rather than a one-off report. The analyst should supply a transparent dataset, a codebook, stable indicator definitions and enough documentation to recreate every major result. Report confidence and precision where the design allows, and avoid making small subgroup differences sound definitive. The programme team should agree how baseline findings change implementation and schedule any follow-up measurements at periods that preserve comparability.
Turn baseline evidence into action in São Tomé and Príncipe
For a hypothetical NGO programme focused on climate adaptation and agricultural resilience, the useful deliverable is not simply a table showing exposure to shocks, land-use practices, access to inputs and livelihood recovery. It is an explanation of which barriers can be addressed through the intervention and which reflect factors outside programme control. If participants know a service exists but rarely use it, explore cost, location, opening time, quality, trust and social norms. Recommend a response only when the evidence distinguishes among those explanations. The baseline should also register external shocks and programme exposure dates to protect later interpretation.
At the end of the exercise, the NGO should be able to say what the baseline means for São Tomé and Príncipe, what it means specifically for São Tomé and Santo António, and what it does not mean. Set a schedule for repeating core indicators, preferably at comparable seasonal periods. Keep the sample frame, contact protocol, questionnaire versions, interview-date records and calculation syntax. Use a short management session to decide whether targeting, staffing, communication or referral practices should change. Record those decisions so the endline can examine both outcomes and the adaptation process.
What a useful baseline report should deliver
A strong São Tomé and Príncipe baseline report should provide a clearly defined study population, an honest sampling account, accepted-interview totals, response outcomes, reproducible indicators and accessible recommendations. City comparisons should carry their own denominators and limitations. The report can be supported by a clean dataset, fieldwork memo, codebook and monitoring matrix, for internal analysis and subsequent measurement rounds. Any gaps in coverage should be visible so implementers can decide whether further listing or targeted qualitative inquiry is needed before expanding activities.
How Surveysphere Africa can support
Surveysphere Africa helps NGOs and development organisations design baseline studies, define indicators, plan samples, manage fieldwork, verify data quality and turn findings into actionable programme decisions. For work involving São Tomé, Santo António or wider coverage in São Tomé and Príncipe, the research design should begin with the intended decision and the population it needs to represent, then adapt responsibly to the local context.
Related guidance
For the continent-wide view, read our guide to baseline, midline and endline studies.
Our services for research in São Tomé and Príncipe
We run research across African markets. Start with these services for work in São Tomé and Príncipe:
- Monitoring, evaluation and learning in São Tomé and Príncipe: Baseline, midline, endline and programme evaluation.
- Social and development research in São Tomé and Príncipe: Qualitative and quantitative studies for social and development programmes.
We also offer: Outsourced fieldwork, Market and consumer research, Public health research, Policy, economic and institutional research, Data analytics and insights visualisation.
