In honour of my Dad.
Dad passed away. Within days, Mum fell ill and was hospitalised. In a period of deep distress, my family was immersed in bureaucratic administration: force-fed forms, questionnaires, and registrations. A long line of encounters with badly designed demographic data capture is burnt to my memory. The image of ‘that’ worn pencil, hovering too long over badly prepared paperwork. Single. Married. Divorced. Mum looked across to me. My stomach flipped. A sickening mix of grief, anger, and confusion. A perception of malintent; to obliterate or dissolve relationship bonds by forcing a selection. A guilt-laden choice. Insensitive, distressing, and from a social scientist perspective, packed with potential to cloud judgement.
The debate of how a ‘widower’ should identify remains an unsettled matter; with views varying from the angry to indifferent. Without delving into the association of grief with the stability of responses  I bore witness to the power of question design, its ability to evoke emotion, and impact response. Across academic fields, there is a convergence on the importance of emotion , that it can influence judgment and decision-making . Yet overlooked in day-to-day form generating practices.
Cognitive psychologists claim “an individual’s temporary mood state, the transient feeling state perceived by the individual influence evaluations made” . In my mind, ‘mood congruency’ , at least that which a badly designed demographic can invoke, should be a priority biasing factor for consideration .
Demographics questions are known to be ‘sensitive’ [7; 8]; often ignoring the complexity of identity . As such they may elicit inaccurate answers . The Institute of Educations’ Research Ethics Guidebook  cautions against questions that offend/upset. The justification of inclusion of ‘sensitive data’ variables, however, can present in 3 key ways:
As means to accurately describe samples for the purposes of clarity, which impacts generalization and replication of findings [12; 13], and identification of sampling error .
Sensitive demographic variables can serve as independent variables [12, 15] i.e. “to determine whether identity is causing an individual to do a specific thing” [13, 14] or entered into multivariate models for controlling and confounding effect .
To ensure inclusion and advancing diversity .
Historically, researchers simply asked if one were single or married. Over time this became confusing and/or offensive [17; 18]. Marital status presents as “less nebulous as questions about racial or sexual identity” [19,] but relationships remain deeply complicated. The National Statistics Office  provide guidance on a wider gamut of relationship possibilities [figure 1].
Figure 1: Marital or Same-sex Civil Partnership Status 
Participants fractured by loss should not need to recalculate identities unfairly . This applies to all “sensitive” demographic variables, in academic or other data generating contexts, to anyone who would feel aggrieved or distressed to be excluded, misrepresented or inappropriately labelled. I pledge to adhere to this promise throughout my research endeavours.
“We know what we are, but not what we may be.”
Disclaimer: Not having scientifically tested the prevalence of a questionnaire design which omits a ‘widow’ option, I am unable to statistically verify my claim, but provide reflections on personal experiences.
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