Table 4 MORECare Statement— checklist of components that require consideration when designing and conducting EoLC intervention studies

Introduction/background

1. Present theoretical framework for the intervention and levels of need established

2. Present objectives appropriate to the level of intervention development

Study design

3. Indicate and justify stage in MRC guidance for development and evaluation of complex interventions, for example, feasibility, preliminary evaluation, efficacy/cost effectiveness and wider effectiveness

4. Feasibility stages should test both feasibility of the intervention and of methods of evaluation, including outcome measurement

5. Justify methods, considering appropriate use of existing data sets and secondary analysis as these may produce rapid information

6. Justify methods of empirical studies considering mixed methods, observational studies and randomised trials

Study team

7. Ensure involvement from: (i) consumers, patients and caregivers; (ii) relevant clinicians; (iii) relevant methodologists to develop study questions, questionnaires and procedures; and (iv) researchers familiar with the challenges in EoLC studies

8. Ideally, involvement should be well established and continuing, beyond a specific study, with joint meetings or rotations between clinical and research staff

Ethics

9. Note in ethics committee application MORECare recommendations that it is ethically desirable for patients and families in EoLC to be offered involvement in research and MORECare evidence of patient willingness to be approached

10. Work within legal frameworks on mental capacity, consent and so on, to ensure that those who may benefit from interventions are offered an opportunity to participate if they wish

11. Collaborate with patients and caregivers in the design of the study, vocabulary used in explaining the study, consent procedures and any ethical aspects

12. Attend the ethics committee meeting with a caregiver or patient, as a means to help the committee better understand the patient perspective

13. Ensure proportionality in patient and caregiver information sheets, appropriate to the study design and level of risk, as excessive information in itself can be tiring/distressing for very ill individuals

Participants

14. Adjust eligibility criteria to recruit those patients who may benefit most from intervention, ensuring equipoise

Procedures

15. Minimise burden for existing clinical staff for participation in the study

16. Clearly distinguish between service received and research activity interviews in study arms when multiple interviews with patients are undertaken in trials, for example, using a graphical system [25]

Outcome measures

17. Choose outcome measures that meet the following criteria:

 • established validity and reliability in relevant population

 • responsive to change over time

 • capture clinically important data

 • easy to administer and interpret (for example, short and with low level of complexity)

 • applicable across care settings to capture change in outcomes by location (for example, patients’ home, hospital, hospice)

 • able to be integrated into clinical care

 • minimise problems of response shift (see below)

18. Consider including patients’ experience of care, as this is central to many interventions

19. Select time points of outcome measurement to balance the value of early recording, to reduce attrition, but to allow enough time for the intervention to have had an effect

20. Consider the potential effect of response shift (that is, a change in a person’s internal conceptualisation or calibration of the aspects measured). Questionnaires that include anchor points or descriptions of each response category may be less problematic in this regard

Missing data and attrition considerations

21. Estimate in advance levels of, and reasons for, attrition and missing data, integrating these into sample size estimates and planned collection of data from proxies

22. Monitor during the study and report all levels of, and reasons for, attrition and other missing data

23. Assume missing quantitative data NOT to be at random unless proven otherwise

24. Test results from different methods of imputation – noting that ‘using only complete cases’ is a form of imputation

25. Use the MORECARE classification of attrition to describe causes of attrition: that is,

 • ADD – attrition due to death;

 • ADI - attrition due to illness;

 • AaR - attrition at random.

26. Consider reasons for missing data which are not due to attrition, for example missed questionnaire, or missed data item in questionnaire. Consider these in analysis and the potential imputations

Mixed method studies

27. Mixed methods can be appropriate in all phases of development and evaluation

28. Ensure appropriate multi-disciplinary skills mix or training of team

29. Define the theoretical paradigm and method of integrating results and safeguards to ensure rigour at the outset

30. Plan investigation to avoid undue burden of qualitative and quantitative questionnaires – perhaps dividing data collection or selecting questions and/or sampling appropriately

31. Take into account any potential therapeutic effect of qualitative interviews where participants can express their feelings, if these are similar to components of the intervention

32. Ensure that those collecting data are appropriately trained in qualitative data collection

Implementation

33. Consider implementation implications, including workforce and training needs, in all phases of the study

Cost-effectiveness

34. Integrate into preliminary evaluations and test feasibility of methods

35. Collect data on use of services including health, voluntary, social and informal care, to take societal approach to care costs

36. Justify appropriate outcome measures to generate cost effectiveness