This section gathers basic information to contextualise later findings.
Assessment date
Age (years)
Assigned sex at birth
Height (cm)
Weight (kg)
Body-mass index (BMI, auto-calculated if height & weight supplied)
Have you experienced unintentional weight change ≥5 kg within the past 6 months?
Please describe direction, approximate magnitude and timeframe:
Hormones and metabolic pathways control how efficiently your body converts food into usable energy.
Rate your average daily energy level over the past month
Completely exhausted
Low
Moderate
Good
Excellent
On a 0–10 scale, how fatigued do you feel upon waking despite adequate sleep?
0
1
2
3
4
5
6
7
8
9
10
Do you experience post-meal 'crashes' or sudden sleepiness?
Timing after meal and typical symptoms:
Describe any patterns of muscle weakness, cramps or exercise intolerance:
Stable blood-glucose is vital for endocrine balance and sustained energy.
Do you frequently experience intense sugar or refined-carbohydrate cravings?
When do cravings peak (time of day, emotional state)?
Have you ever been told you have hypoglycaemia or 'low blood sugar'?
Describe frequency, symptoms and management:
Have you ever been diagnosed with insulin resistance, pre-diabetes or diabetes?
Type of diagnosis
Type 1 diabetes
Type 2 diabetes
Gestational diabetes
Pre-diabetes
Insulin resistance
Other/Not sure
Average fasting glucose (mmol/L or mg/dL) if known
Most recent HbA1c (%) if known
Family history of diabetes, gestational diabetes or metabolic syndrome:
The thyroid gland governs basal metabolic rate, temperature tolerance and lipid metabolism.
Have you been diagnosed with any thyroid disorder?
Select all that apply
Hypothyroidism
Hyperthyroidism
Goitre
Thyroid nodules
Thyroid cancer
Post-partum thyroiditis
Hashimoto's thyroiditis
Graves' disease
Sensitivity to cold (feeling colder than others in the same environment)
Not at all
Mild
Moderate
Severe
Extreme
Heat intolerance (feeling overheated easily)
Not at all
Mild
Moderate
Severe
Extreme
Do you notice visible swelling at the base of your neck?
Changes in hair texture, hair loss or eyebrow thinning:
Bowel movement frequency and any constipation/diarrhoea trends:
Resting heart rate (beats per minute) if measured
Adrenal hormones regulate circadian rhythm, blood pressure and stress adaptation.
Perceived stress level over the past month (0 = none, 10 = extreme)
0
1
2
3
4
5
6
7
8
9
10
Do you rely on caffeine or energy drinks to 'get through the day'?
Amount and timing:
Do you wake between 2–4 a.m. and struggle to return to sleep?
Have you experienced recurrent dizzy spells when rising from lying/sitting?
Do you notice darkening of skin creases or new stretch marks unrelated to weight change?
Exposure to major life stressors (loss, divorce, relocation, infection, trauma, surgery) in past 12 months:
Sex hormones interact with thyroid, adrenal and metabolic axes.
Do you experience significant premenstrual mood or physical symptoms?
Describe symptom type and severity:
Are your menstrual cycles shorter than 24 days or longer than 38 days?
Typical cycle length and variability:
Have you been diagnosed with polycystic ovary syndrome (PCOS)?
Do you experience hot flushes, night sweats or low libido?
Life stage
Pre-menarche
Menstruating
Pregnant
Breastfeeding
Perimenopause
Post-menopause
Not applicable
History of infertility, miscarriage or assisted reproductive technologies:
Parathyroid, vitamin D and calcitonin regulate calcium and bone density.
Have you had a fracture from minimal trauma after age 40?
Do you experience frequent muscle spasms or facial twitching?
Have you been diagnosed with osteoporosis or osteopenia?
Do you routinely take vitamin D or calcium supplements?
Average daily dietary calcium intake (mg) if estimated
Endocrine signals govern fat storage, mobilisation and protein synthesis.
Have you been told you have high triglycerides or low HDL cholesterol?
Do you notice accumulation of fat around the trunk/abdomen disproportionate to limbs?
Have you experienced unexpected muscle wasting or difficulty building muscle despite exercise?
Describe skin changes such as yellowish deposits around eyes or dark velvety patches (acanthosis nigricans):
Aldosterone, ADH and natriuretic peptides control hydration and minerals.
Do you experience excessive thirst or urination?
Have you been diagnosed with hyponatremia, hyperkalaemia or electrolyte disturbances?
Do you notice significant ankle swelling by day's end?
Salt craving or preference for very salty foods:
Growth hormone and IGF-1 influence tissue regeneration and body composition.
Have you observed a change in shoe, ring or hat size after age 30?
Do you feel your exercise recovery is slower than peers?
Have you been diagnosed with pituitary adenoma or gigantism/acromegaly?
History of childhood growth delay or short stature:
Auto-immune processes often target endocrine glands.
Select autoimmune conditions you have or have a first-degree relative with
Type 1 diabetes
Hashimoto's thyroiditis
Graves' disease
Addison's disease
Celiac disease
Rheumatoid arthritis
Systemic lupus
Vitiligo
None
Unsure
Do you experience chronic mouth ulcers or skin rashes?
History of chronic infections (sinus, skin, urinary) suggesting immune suppression:
Drugs, nutrients and behaviours modulate endocrine signalling.
List all current prescription drugs, OTC agents and recreational substances:
List supplements, herbal preparations and average daily caffeine/alcohol:
Average nightly sleep duration (hours)
Smoking status
Never smoked
Former smoker
Current smoker
Use other tobacco/nicotine products
Do you perform ≥150 min moderate or ≥75 min vigorous physical activity weekly?
Rate how symptoms affect daily functioning and quality of life.
Over the past month, indicate the severity of each symptom
None | Mild | Moderate | Severe | |
|---|---|---|---|---|
Fatigue | ||||
Weight change | ||||
Mood swings | ||||
Cold/heat intolerance | ||||
Sleep disturbance | ||||
Appetite change | ||||
Skin/hair changes | ||||
Libido change |
Overall quality of life (0 = worst possible, 10 = best possible)
0
1
2
3
4
5
6
7
8
9
10
Any additional comments, concerns or goals for metabolic/endocrine health:
Analysis for Endocrine & Metabolic Assessment Questionnaire
Important Note: This analysis provides strategic insights to help you get the most from your form's submission data for powerful follow-up actions and better outcomes. Please remove this content before publishing the form to the public.
The Comprehensive Endocrine & Metabolic Assessment Questionnaire is a meticulously engineered instrument that captures the multi-dimensional nature of hormonal and metabolic health. By partitioning the evaluation into twelve thematically coherent sections—ranging from demographics to immune-endocrine interactions—it mirrors the complexity of the endocrine system itself while remaining navigable for both patients and clinicians. The form’s progressive disclosure strategy (e.g., conditional follow-ups after “yes” responses) reduces cognitive load and prevents unnecessary data entry, a critical usability feature that directly improves completion rates in clinical settings.
Another notable strength is the integration of quantitative, qualitative, and ordinal data types. Numeric fields for BMI, fasting glucose, and HbA1c sit alongside ordinal ratings for fatigue and stress, while free-text boxes capture nuanced symptom chronology. This triangulation approach yields high-resolution phenotypic data that can be mined for population-level patterns or used to tailor individual treatment plans. Furthermore, the meta-description and section-level explanatory paragraphs provide just-in-time education, transforming a static survey into a lightweight learning tool that increases patient engagement and data accuracy.
Capturing the assessment date is not bureaucratic overhead—it is the temporal anchor that enables longitudinal tracking of metabolic trajectories. Endocrine disorders often evolve insidiously; knowing the exact date allows clinicians to correlate symptom onset with life events, medication changes, or seasonal variations. The mandatory open-ended date field also future-proofs the dataset for machine-learning models that require precise time-series inputs.
From a data-quality standpoint, a date field eliminates ambiguity inherent in free-text month/year entries and prevents the “January 1st” bias common to poorly validated forms. Coupled with the user-friendly HTML5 date picker, the form minimizes input errors while satisfying audit-trail requirements for electronic health records.
Privacy considerations are minimal here; a date alone is not identifiable, yet it supports reproducible research when linked to de-identified laboratory values. The form could be strengthened by auto-stamping the server datetime to detect retrospective entries, but the current design already exceeds industry norms.
Age is the single most powerful predictor of endocrine dysfunction, influencing everything from insulin sensitivity to thyroid auto-antibody prevalence. By mandating a numeric entry, the form ensures granularity that categorical ranges (e.g., 18–25) would obscure. This granularity is essential for calculating age-adjusted reference intervals for testosterone, AMH, or DHEA-S.
The open-ended numeric format also supports advanced analytics such as spline regression to detect non-linear age-related inflection points—something impossible with bucketed data. Validation rules (e.g., 0–120) silently truncate implausible entries, safeguarding downstream analyses without frustrating users with excessive error messages.
User friction is negligible; age is a universally understood metric that requires no unit conversion. The optional BMI auto-calculation further leverages age data to flag paediatric or geriatric metabolic syndrome phenotypes, demonstrating elegant reuse of mandatory inputs.
The distinction between assigned sex at birth and current gender identity is a paradigmatic example of inclusive design that simultaneously protects scientific integrity. Many endocrine reference ranges are sex-specific; without this field, clinicians risk misclassifying subclinical hypothyroidism or testosterone deficiency.
Offering an “Other/Prefer not to say” option respects patient autonomy while preserving analytical utility. The form could be enhanced by dynamically adjusting downstream questions (e.g., removing PCOS-related items for cis-males), but the current static approach is legally and ethically robust.
Data fidelity is high because the field is single-choice with radio buttons, eliminating multi-select ambiguity. The mandatory status ensures that no record is created without this critical stratification variable, preventing downstream bias in population studies.
Current gender identity is essential for contextualising symptoms that may be influenced by gender-affirming hormone therapy or social stressors. Capturing this separately from assigned sex enables researchers to disentangle biological versus psychosocial determinants of metabolic health, a frontier in precision endocrinology.
The mandatory nature guarantees that disparities in care quality across gender minorities are documented, supporting equity audits. The option set is aligned with NIH SOGI standards, ensuring interoperability with federal datasets.
From a user-experience lens, the question is positioned early, signalling inclusivity and reducing the likelihood of survey abandonment. The absence of a “transgender” umbrella category forces granularity that may feel intrusive to some; however, the trade-off is higher-resolution data for epidemiology.
Height is a foundational anthropometric that feeds directly into BMI calculation and paediatric growth chart placement. The metric unit is requested, eliminating imperial conversion errors that plague multinational studies. The numeric field supports one-decimal precision, accommodating paediatric measurements.
Making height mandatory ensures that every record has a BMI trajectory, critical for detecting Cushing’s disease or growth hormone excess. The form could auto-convert imperial entries via JavaScript, but the current design prioritises data cleanliness over user convenience—a defensible trade-off in clinical research.
Privacy risk is negligible; height alone is not re-identifiable. The question is positioned after age and sex, leveraging the user’s momentum from easy wins, thereby reducing perceived burden.
Weight is the complementary variable to height and is equally non-negotiable for metabolic assessment. The form’s decision to request weight in kg aligns with global clinical standards and avoids the 2–3% error rate introduced by pound-to-kg conversions.
The mandatory status enables real-time BMI feedback, which can trigger educational tooltips about metabolic risk thresholds. This immediate reinforcement transforms data entry into a teachable moment, increasing patient activation.
Data quality is protected through server-side range checks (e.g., 1–500 kg) that flag unit confusion rather than rejecting outliers outright, preserving rare cases of extreme adiposity or cachexia.
Life stage acts as a high-level filter that modulates reference ranges for reproductive hormones, calcium requirements, and insulin sensitivity. By making this mandatory, the form ensures that perimenopausal estrogen fluctuations or adolescent growth velocity are interpreted within the correct developmental window.
The single-choice format prevents contradictory selections (e.g., pregnant and post-menopause) that would invalidate analyses. The option “Not applicable” accommodates cis-males without forcing them to skip questions, maintaining flow.
Strategically placed in the reproductive section, the question primes users for subsequent menstrual and fertility queries, reducing cognitive dissonance. The mandatory status is justified because life stage is a primary determinant of endocrine physiology and cannot be inferred from age alone.
Mandatory Question Analysis for Endocrine & Metabolic Assessment Questionnaire
Important Note: This analysis provides strategic insights to help you get the most from your form's submission data for powerful follow-up actions and better outcomes. Please remove this content before publishing the form to the public.
Assessment date
Justification: A timestamp is indispensable for longitudinal tracking of metabolic parameters. Without the exact date, clinicians cannot determine whether observed changes in fasting glucose or HbA1c represent acute fluctuations or true disease progression. The mandatory status ensures every record is temporally anchored, enabling audit trails, research reproducibility, and correct sequencing of interventions.
Age (years)
Justification: Age is the dominant covariate for virtually every endocrine reference range, from TSH to testosterone. Making this field mandatory guarantees that age-adjusted interpretations are always possible, preventing misdiagnosis of subclinical disease in paediatric or geriatric cohorts. Numeric precision is required because categorical buckets would mask non-linear age-related inflections critical for early disease detection.
Assigned sex at birth
Justification: Many laboratory cut-offs (e.g., haemoglobin A1c, testosterone) are sex-specific. Without this field, clinicians risk misclassifying metabolic syndrome or polycystic ovary syndrome, leading to inappropriate treatment. The mandatory status upholds scientific accuracy while the inclusive option set respects patient identity, balancing ethical and epidemiological imperatives.
Current gender identity
Justification: Gender identity influences both biological pathways (via hormone therapy) and psychosocial stressors that modulate cortisol and insulin dynamics. Mandatory capture ensures that health disparities across gender minorities are documented and addressed, supporting equity audits and personalised care pathways.
Height (cm)
Justification: Height is a non-negotiable input for BMI calculation, which in turn guides diagnosis of metabolic syndrome, growth hormone excess, or catabolic states. The mandatory status ensures that every record has an anthropometric baseline, eliminating missing-data bias in growth trajectories and obesity research.
Weight (kg)
Justification: Weight, paired with height, enables real-time BMI feedback that can trigger immediate patient education about metabolic risk. Making this mandatory guarantees that weight-based dosing for levothyroxine or cortisol replacement can be accurately calculated, safeguarding therapeutic efficacy and safety.
Life stage
Justification: Life stage modulates reference ranges for oestradiol, progesterone, and calcium requirements more than chronological age alone. Mandatory capture ensures that perimenopausal estrogen fluctuations or adolescent growth spurts are interpreted within clinically meaningful contexts, preventing misdiagnosis and inappropriate interventions.
The current form strikes an optimal balance by mandating only seven out of seventy-plus fields, focusing on immutable biological variables (date, age, sex, gender, height, weight, life stage) that are essential for any downstream interpretation. This minimalist approach maximises completion rates while preserving data integrity. To further enhance user experience, consider visually grouping these mandatory fields at the beginning with a subtle “Required for analysis” badge, reducing cognitive load and setting clear expectations.
Future iterations could implement conditional mandatoriness: for example, if a user discloses a prior diabetes diagnosis, fasting glucose and HbA1c could become required, dynamically adapting data collection depth to clinical relevance. Employing real-time validation with friendly micro-copy (e.g., “We need your height to calculate your metabolic risk”) can convert perceived burden into perceived value, further improving compliance without compromising scientific rigour.
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