Health-related quality of life, often abbreviated HRQOL, has become a central endpoint in modern medicine. Survival is no longer the only yardstick; researchers and clinicians want to know whether treatments restore the ability to walk to the market, sleep through the night, or take a shower without exhaustion. Instruments such as the Minnesota Living with Heart Failure Questionnaire, known as the MLHFQ, convert these lived experiences into scores that can be tracked over time and compared across trials. The MLHFQ asks patients to rate how much their heart failure has prevented them from engaging in activities ranging from working around the house to enjoying hobbies, and it also probes physical, emotional, and social dimensions of the illness. But a questionnaire is only as valid as the words it uses, and those words carry cultural freight that a literal translation can easily crush.

The research team set out to close a well-recognized gap. Although many tools exist to measure quality of life in chronic illness, the evidence on how they are adapted across cultures remains thin, and adaptation processes are often reported so sketchily that other researchers cannot judge their quality. An Urdu version of the MLHFQ exists, but it was developed for Indian Urdu speakers, and the team judged that it could not simply be assumed to work in Pakistan, where vocabulary, idiom, register, and everyday phrasing differ in ways that matter to patients answering sensitive questions about their bodies and emotions. Rather than starting from scratch, the researchers designed a structured methodological study that combined the MAPI Research Trust’s established five-step linguistic validation process with an added layer of scrutiny: a modified Delphi panel.

The process began with translation. Two forward translators worked independently to adapt the Indian Urdu version of the MLHFQ for Pakistani use, and their versions were then reconciled into a single draft, labeled Pakistani Urdu version 1.0. This reconciliation step is where much of the quiet science of questionnaire adaptation happens, because two skilled translators frequently disagree, and each disagreement signals a word or phrase that is ambiguous, culturally loaded, or simply absent from the target language. The draft then went to the Delphi panel, a small structured group consisting of three heart failure patients and one cardiologist. Unlike a casual review, the Delphi approach asks panelists to systematically evaluate the translation for linguistic accuracy, cultural relevance, and comprehensiveness, to identify specific problems, and to provide feedback that fed directly into revisions. Involving patients in this step is notable, because the people who ultimately fill out the questionnaire are best placed to say whether a phrase sounds natural or clinical, respectful or strange.

Version 1.0 then traveled in the opposite direction. Two independent back translators, who had not seen the original English questionnaire, translated the Urdu draft back into English. Back translation is a classic quality-control technique in instrument adaptation: if the back-translated English diverges from the source English, the divergence flags an item that may have shifted meaning. The principal investigator and the back translators reconciled the back translations and proposed changes, which were then approved by the forward translators, creating a closed loop of checks in which every modification had to survive review from multiple independent perspectives. Translations, reconciliation reports, and the Delphi panel’s feedback were all analyzed using inductive qualitative content analysis, a method that lets themes emerge from the data rather than imposing predefined categories on it.

That analysis produced four themes that together form a practical map of the methodological challenges in cross-cultural adaptation. The first theme was the direct transferring of compatible words from the Indian Urdu version to the Pakistani Urdu version. Not everything needed to change; a substantial portion of the vocabulary worked in both countries, and recognizing what could be carried over unchanged saved effort while preserving continuity with the existing instrument. The second theme concerned indirect substitutes for words that lack direct Urdu equivalents. This is a familiar headache in translation science: English terms for emotional states, bodily sensations, or social functioning often have no one-word counterpart in another language, forcing translators to choose a phrase that approximates the concept without distorting it.

The third theme was balancing the tone of written and spoken Urdu. Urdu, like many languages with long literary traditions, exists on a spectrum from formal written registers to everyday spoken forms, and a questionnaire must thread a needle. Language that is too formal can feel alienating or obscure to patients with limited literacy, while language that is too colloquial can seem inappropriate in a clinical context or lose the precision the instrument requires. The fourth theme was incorporating contextual nuances within each element of the tool, ensuring that individual items made sense in the daily reality of Pakistani patients, whose living arrangements, family roles, and expectations about illness and care may differ from those of the populations in which the questionnaire was originally validated.

The significance of this work becomes clear when one considers what happens when patient-reported outcome measures are used without proper adaptation. A mistranslated item does not merely produce noise; it can systematically bias scores, making patients appear healthier or sicker than they are, undermining clinical decisions, clinical trials, and health policy built on the data. Pakistan carries a substantial burden of cardiovascular disease, and heart failure services there are expanding, yet without a validated Urdu instrument, researchers and clinicians have lacked a trustworthy way to capture how Pakistani patients experience their illness. The adapted MLHFQ now offers a quality-assured option, and the detailed documentation of the adaptation process provides a template that other teams adapting HRQOL tools can follow, whether their target language is Urdu or something else entirely.

The study also contributes to a broader conversation in measurement science about transparency. By publishing the themes from their qualitative analysis, the researchers have turned what is usually an invisible, behind-the-scenes craft into an auditable record. Other investigators can see exactly which strategies were used, why words were substituted, and how patients on the Delphi panel shaped the final version. This kind of methodological honesty is increasingly demanded by journals and regulators, particularly as patient-reported outcomes become key endpoints in drug trials and value-based care. The team’s conclusion is straightforward: the MLHFQ has been successfully adapted for Urdu-speaking patients with heart failure in Pakistan, with the linguistic, cultural, and contextual challenges systematically documented along the way. For the patients who will eventually fill out the questionnaire in clinics across Pakistan, the payoff is more intimate than any trial statistic: their answers will finally mean what they intend them to mean.

Subject of Research: Cross-cultural adaptation and linguistic validation of the Minnesota Living with Heart Failure Questionnaire for Urdu-speaking heart failure patients in Pakistan

Article Title: Translation and cultural adaptation of the Minnesota Living with Heart Failure Questionnaire for use in Pakistan

Article References: Gowani, A., Norris, C., Low, G., Ajani, K., Noor, A., & Hoben, M. (2026). Translation and cultural adaptation of the Minnesota Living with Heart Failure Questionnaire for use in Pakistan. PLOS One, 21(10), e0360245. https://doi.org/10.1371/journal.pone.0360245

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360245

Keywords: heart failure, quality of life, MLHFQ, Urdu translation, cross-cultural adaptation, Pakistan, patient-reported outcomes, linguistic validation, Delphi panel, HRQOL, translation science, PLOS One