PPD_Decision_Making_Proposal

A Mixed-Methods Study of Choice Under Cognitive and Affective Load

Doctoral Research Proposal (Concept Paper)

Non-clinical, non-diagnostic behavioral research

Prepared by: Johnson, R.

This is only a research project.

Version 1.2 (Readability revision, draft for committee review)

Table of Contents

Abstract 3

1. Introduction and Problem Statement 3

2. Purpose Statement 4

3. Research Questions 4

4. Significance of the Study 4

5. Conceptual Framework 5

6. Guiding Propositions 6

7. Research Methodology 6

8. Ethical Considerations 8

9. Validity, Limitations, and Delimitations 11

10. Operational Definitions 11

11. Assumptions, Scope, and Delimitations 12

12. Data Management and Analytical Plan 12

13. Phased Timeline and Milestones 13

14. Expected Contributions 14

15. Anticipated Questions and Responses 14

References 17

Abstract

This proposal outlines a non-clinical, non-diagnostic mixed-methods study of the relationship between postpartum depressive symptom severity and everyday decision-making. The unit of analysis is the decision rather than the person. Perinatal depression is common, affecting an estimated 11.9% of women from conception through twelve months postpartum (Woody et al., 2017), and the postpartum period imposes an unusually high volume of decisions at a time when cognitive resources are already taxed. Depression is associated with measurable changes in executive function (Rock et al., 2014) and in decision behavior, including shifts in risk preference and the systematic reweighting of outcomes (Kahneman & Tversky, 1979; Lerner et al., 2015). Yet the specific link between postpartum symptomatology and the quality of everyday choices remains understudied (Ghadimi & McCormack, 2025). Using an explanatory sequential design, Phase 1 measures the association between symptom severity, captured with a validated screening scale, and decision characteristics in realistic postpartum scenarios. Phase 2 uses semi-structured interviews to explain the quantitative patterns. The study characterizes a relationship; it does not assess the sanity, capacity, or rationality of any individual, and its ethical framework is built around that limit.

1. Introduction and Problem Statement

New mothers make an extraordinary number of decisions in the months following birth, ranging from routine daily choices to consequential, other-directed judgments about the care of an infant. This decision load arrives during a developmental transition, sometimes called matrescence, that involves profound neurobiological, cognitive, and emotional change (Ghadimi & McCormack, 2025). It also coincides with a period of elevated vulnerability to depressive symptoms. Global estimates place the pooled prevalence of perinatal depression near 11.9% (Woody et al., 2017), with anxiety frequently co-occurring (Dennis et al., 2017), and with symptom-based screening instruments identifying still higher rates than diagnostic interviews (Woody et al., 2017).

A substantial literature establishes that depression is associated with impairment in executive functions such as planning, working memory, and inhibitory control, and that these impairments can persist beyond periods of low mood (Rock et al., 2014; Roiser et al., 2012). A parallel literature in decision science shows that emotional and cognitive states shape choice in predictable ways, altering risk preference, the weighting of gains and losses, and tolerance for delay (Kahneman & Tversky, 1979; Lerner et al., 2015; Deck & Jahedi, 2015). These two bodies of work rarely meet. Research specifically examining decision-making in the context of postpartum depressive symptoms remains limited (Ghadimi & McCormack, 2025), and where the topic is addressed it is often framed clinically, in terms of disorder and treatment, rather than behaviorally, in terms of how ordinary choices are made.

The problem this study addresses is therefore both empirical and conceptual. Empirically, we do not yet have a clear description of how postpartum depressive symptom severity relates to the quality of everyday decisions. Conceptually, the field lacks a framing that treats altered decision patterns as behavior to be understood rather than as deficit to be judged. This study is positioned to contribute to both gaps while remaining strictly outside clinical practice.

2. Purpose Statement

The purpose of this explanatory sequential mixed-methods study is to describe the relationship between postpartum depressive symptom severity and the characteristics of everyday decision-making among postpartum women. Decision characteristics of interest include decision latency, decision avoidance, choice instability, confidence, and perceived difficulty. A quantitative first phase measures these associations, and a qualitative second phase explains them through the accounts of participants. Depressive symptom severity is measured with a validated screening instrument used as a continuous predictor, never as a diagnosis.

3. Research Questions

The study is organized around five questions that move from measurement to meaning. The quantitative strand asks, first, how postpartum depressive symptom severity relates to decision quality in everyday scenarios, understood as latency, avoidance, instability, and confidence; and second, how that severity relates to perceived cognitive load and perceived decision difficulty. The qualitative strand then turns to lived experience, asking how postpartum women describe their own decision-making during this period, and what they identify as the factors that make everyday decisions feel easy or hard. A final, integrative question ties the two together, asking to what extent participants' accounts converge with, or diverge from, the quantitative associations observed in Phase 1.

4. Significance of the Study

The study offers a descriptive account of a relationship that is frequently assumed but rarely measured. For decision science, it extends work on emotion, cognitive load, and risk (Lerner et al., 2015; Deck & Jahedi, 2015; Weber et al., 2002) into a naturalistic, high-load population. For the perinatal literature, it foregrounds decision behavior as an outcome worth studying alongside mood and child development (Howard et al., 2014; Stein et al., 2014). For practice, a clearer description of where and how everyday decisions become effortful could inform the design of decision-support tools, without the study ever making a clinical claim. Because the aim is descriptive, the contribution is a well-characterized relationship and a set of participant-grounded explanations, not a causal model.

5. Conceptual Framework

The framework bridges two literatures, and the bridge is the study's conceptual contribution.

5.1 The cognitive pathway

Depression is reliably associated with reduced efficiency in the prefrontal systems that support planning, prioritization, working memory, and inhibitory control, alongside heightened reactivity in emotion-processing regions (Rock et al., 2014; Roiser et al., 2012). During the perinatal period these general effects interact with the specific cognitive demands of new motherhood, sometimes experienced as reduced mental sharpness, and with the mental load of coordinating infant care (Ghadimi & McCormack, 2025). Reduced executive resources plausibly translate into slower, more effortful, or avoided decisions.

5.2 The decision-science pathway

Independently, decision research shows that internal states shape choice. Prospect theory establishes that people evaluate outcomes relative to a reference point and respond asymmetrically to framing (Kahneman & Tversky, 1979; Tversky & Kahneman, 1981). Emotions function as pervasive and predictable inputs to judgment and choice (Lerner et al., 2015; Lerner & Keltner, 2001). Higher cognitive load has been associated with more risk-averse and more impatient choices (Deck & Jahedi, 2015), and risk attitudes themselves are domain-specific rather than uniform (Weber et al., 2002; Blais & Weber, 2006). This last point matters: any observed shift may appear in some decision domains and not others, and the design must allow for that.

5.3 The integrated model

The proposed model links these pathways: elevated postpartum depressive symptoms are associated with reduced executive resources and elevated perceived cognitive load, which in turn are associated with altered everyday decision characteristics, including risk shift, longer latency or avoidance, and lower confidence. Perceived cognitive load is positioned as a candidate descriptive correlate that may travel with the relationship, consistent with the study's non-causal aim. Figure 1 summarizes the logic.

Postpartum depressive symptoms → reduced executive resources / elevated cognitive load → altered everyday decision characteristics (risk shift, latency/avoidance, lower confidence)

Figure 1. Proposed descriptive relationship among study constructs.

6. Guiding Propositions

Because the aim is descriptive, the study is guided by propositions to be examined rather than causal hypotheses to be confirmed. It anticipates that higher symptom severity will be associated with greater risk aversion in gain-framed everyday choices (P1), with longer decision latency and more frequent decision avoidance (P2), and with lower decision confidence alongside higher perceived difficulty (P3). It further expects perceived cognitive load to co-vary with each of these relationships (P4), traveling with them rather than standing apart.

7. Research Methodology

7.1 Design

The study uses an explanatory sequential mixed-methods design (Creswell & Plano Clark, 2018). Phase 1 (quantitative, dominant) measures the relationship; Phase 2 (qualitative) explains it. The sequence is deliberate: the quantitative findings shape whom to interview and what to ask, and the qualitative findings interpret the quantitative results. This design suits a descriptive relational aim because it pairs measured association with participant-grounded meaning while avoiding causal claims neither strand can support.

7.2 Phase 1: Quantitative

The predictor is depressive symptom severity, measured with the Edinburgh Postnatal Depression Scale (EPDS), a ten-item validated self-report screening instrument (Cox et al., 1987; Murray & Cox, 1990). The scale is used as a continuous score rather than a diagnostic threshold, so no participant is ever labeled depressed on the basis of an answer. Against that predictor the study sets six decision outcomes, all captured across the everyday-scenario battery described in Section 7.5: latency, avoidance, choice instability, confidence, perceived difficulty, and perceived cognitive load. A short set of covariates, including infant age, self-reported sleep, level of practical support, prior history of low mood, education, and income band, is recorded alongside them, not to diagnose anyone but to give the associations context. Analysis proceeds through correlation and descriptive multiple regression, reporting effect sizes and confidence intervals, and the findings are written in associational language, that a factor is associated with or relates to an outcome, rather than the causal language of prediction or cause.

7.3 Phase 2: Qualitative

Phase 2 draws its participants purposively from the Phase 1 sample, deliberately spanning the symptom range so that accounts from both lower and higher scorers can inform interpretation; roughly eight to fifteen interviews are anticipated, continuing until themes stabilize. Each interview is semi-structured, walking the participant through a recent real decision and exploring what made choices feel easy or hard and how energy, mood, and time pressure entered in. The transcripts are then read through reflexive thematic analysis (Braun & Clarke, 2006), coded inductively before the emerging themes are mapped back onto the decision characteristics measured in Phase 1.

7.4 Integration

Findings are integrated in a joint display: a table pairing each Phase 1 result with the interview themes that confirm, expand, or contradict it. This display directly answers the integration research question and is the primary artifact of the mixed-methods contribution.

7.5 Core Instrument: Everyday-Decision Scenarios

The information-gathering engine of the study is a battery of six to ten short, realistic postpartum vignettes, each ending in a choice. Scenarios span three decision types so that the domain-specific nature of risk (Weber et al., 2002) can be observed. Crucially, scenarios are designed without an objectively correct answer: the study profiles how people decide, not whether their choices are right, which also keeps the instrument clear of any implied clinical judgment. Every scenario captures the same dimensions to allow comparison across items.

Table 1. Decision dimensions and their operationalization.

Scenario domains

Routine, low-stakes: for example, what to prepare for a meal given limited time, or which errand to drop today.

Tradeoff, resource-constrained: for example, buying a needed item now or waiting for a sale, or resting versus finishing a task.

Consequential, other-directed: for example, whether to seek advice about a minor infant symptom, or whether to accept offered help.

7.6 Population and Sampling

The target population is postpartum women within approximately twelve months of birth. Recruitment proceeds through parenting communities, online panels, and clinics used strictly as recruitment sites rather than as clinical partners. Non-probability purposive sampling is anticipated and is stated openly as a delimitation. Sample-size planning for Phase 1 will follow power analysis for the planned regression models and will be finalized with committee input.

7.7 Instrument Inventory

Six instruments make up the package. The EPDS provides the symptom measure, used in a permitted, cited version. The everyday-decision scenario battery, original to this study, supplies the behavioral outcomes, and a short block of confidence, difficulty, and cognitive-load items sits alongside it. A demographic and covariate block gathers the contextual variables, a semi-structured interview guide carries Phase 2, and an informed-consent form together with a universal resource card completes the set.

8. Ethical Considerations

This study involves a population that is both important to study and deserving of particular care, together with a variable that sits adjacent to mental health. Institutional Review Board (IRB) approval is required before any data collection, and the design follows the principles of respect for persons, beneficence, and justice (National Commission, 1979). Beyond standard protections, the study's central ethical work concerns the language of the research itself.

8.1 On “sanity,” “rationality,” and the limits of what this study may claim

A predictable and loaded question hangs over any study in this area: how can a researcher determine whether a woman who experiences hormonal change, including significant fluctuation, is thinking sanely or rationally? The most defensible answer is that this study deliberately refuses to make that determination, and its refusal is the ethical spine of the entire design. The framing must be interrogated rather than inherited.

The first move is to be honest about definitions. Sanity is a lay and legal category with no operational meaning in behavioral science and no place among this study's variables. Rationality, in decision science, is a technical term for the internal coherence of preferences, their consistency and transitivity, and it says nothing about whether an observer approves of a choice or its outcome. The study measures decision characteristics; it does not adjudicate whether any woman is sane, competent, or fit. Three constructs therefore have to be kept strictly apart, because collapsing them is where harm occurs. Decisional capacity is a functional, decision-specific, time-specific clinical and legal determination, and nothing in these instruments measures it. Rationality is coherence of preference. Sanity is a folk and legal category outside the study's scope entirely. What remains, and all that this study occupies, is the descriptive space around decision behavior.

Within that space, rationality means coherence, not correctness. A woman with elevated symptoms who becomes more risk-averse, or who reweights outcomes because an internal reference point has shifted (Kahneman & Tversky, 1979), is not thereby behaving irrationally; she is making coherent choices given an altered internal state, and prospect theory already describes reference-dependent, framing-sensitive choice as ordinary. An altered decision pattern is treated here as an adaptation to be understood, not a defect, and the reporting language follows suit: an observed effect is described as decision behavior varying with symptom state, never as decisions becoming irrational. This also means naming and refusing the hormonal-determinism trap, the inference that because a woman experiences hormonal fluctuation her rationality is in doubt. That inference is a fallacy with a long history of dismissing women's judgment, and it bundles two errors: that biological influence equals biological determination, when everyone's cognition is modulated by physiology without their choices being void, and that any difference from a non-postpartum baseline equals impairment. Symptom severity is treated as a continuous variable to be correlated with behavior, not a switch that toggles a woman between rational and not.

The risks of getting this wrong are real and asymmetric. Findings could be lifted out of context and used in custody disputes, benefit determinations, or paternalistic arguments, and the people harmed would not be the researcher, so the study reports only at the group level, warns explicitly against individual inference, pre-commits in its analysis plan to non-deficit framing, and carries a limitation clause, in both the consent form and the final report, stating that it cannot be used to assess any individual's capacity, competence, or fitness. Autonomy is handled with the same care, presumed and supported rather than revoked on suspicion. The tempting inference that symptom-related cognitive change might undermine a participant's ability to consent would itself be a serious breach, defaulting to paternalism and excluding a population from research that concerns it; capacity is instead presumed and scaffolded through plain-language consent, comprehension checks, the right to pause or withdraw at any time without penalty, and the option to re-consent.

These commitments are backed by concrete safeguards written into the protocol: an interpretive-guardrails statement in the methods that specifies what the study can and cannot conclude about sanity, capacity, and rationality; deficit-free language rules applied to instrument wording, coding, and reporting, with the researcher auditing scenario text for implied judgment; group-level reporting only, carrying an explicit no-individual-inference caveat; a universal resource card shown to every participant regardless of score, so that support is never framed as a verdict; a reflexivity statement acknowledging the historical pathologizing of women's decision-making and how the design counters it; and a misuse-limitation clause carried in both the consent form and the final write-up.

The one-line statement for a committee: this study characterizes how decision behavior varies with postpartum symptom severity; it does not, and ethically must not, adjudicate any woman's rationality, capacity, or sanity.

8.2 Contemporary legal context, and why the guardrails matter

The concern that motivates this chapter is not hypothetical. Courts and legislatures are actively grappling with how postpartum mental states bear on responsibility and capacity, and the language they use maps directly onto the constructs this study refuses to adjudicate. A necessary caveat comes first: the cases noted below involve rare, severe postpartum psychosis and grave criminal charges, which are categorically different from the everyday, non-clinical decisions this study examines. They are relevant here not as analogues to the study population, but as vivid evidence of how rationality and capacity get contested in postpartum women, and therefore of how findings in this area can be misread.

Several recent developments illustrate the point. In Massachusetts, the trial of Lindsay Clancy, arising from a 2023 offense, reached court in 2026 and ended in a mistrial after the jury deadlocked on criminal responsibility; it turned on whether postpartum psychosis negated that responsibility, with prosecutors arguing she had acted “intentionally, rationally and swiftly” and retained the capacity to appreciate wrongfulness while the defense argued she did not, making the proceeding in effect a courtroom contest over rationality and capacity. In West Virginia, Krista Brunecz was found not guilty by reason of insanity in 2024 on the basis of postpartum psychosis and later sought restoration of parental rights, which shows how such determinations reach into family law. Both cases echo the long-standing Texas case of Andrea Yates, found not guilty by reason of insanity in 2006, which continues to shape public and legal understanding. On the legislative side, Illinois has become the first and only U.S. state to make postpartum depression or psychosis a statutory mitigating factor at sentencing (Public Act 100-0574, 2018, codified at 730 ILCS 5/5-5-3.1(a)(17)), with related post-conviction relief (735 ILCS 5/2-1401(b-10), added by Public Act 101-0411, 2019) and a 2025 amendment (SB0019) directing the Prisoner Review Board to weigh these conditions in parole and medical-release decisions.

Two implications follow for this study. First, these developments confirm that rationality and capacity in postpartum women are live, consequential legal questions, which is precisely why this study reports only at the group level and carries an explicit clause barring individual inference. A descriptive behavioral finding about everyday choices must never be imported into a courtroom as evidence about any individual's mind. Second, the legislative recognition that postpartum states can bear on behavior, paired with expert cautions that the severe cases are rare (postpartum psychosis affects roughly one to two births per thousand), models the balance this study also seeks: taking postpartum experience seriously without pathologizing the ordinary decisions of the vast majority of mothers. This study's contribution sits at the ordinary end of that spectrum, and its guardrails are designed to keep it there.

Note: legal authorities and case details above reflect reporting current as of September 2026 and are provided for research context, not as legal advice; citations should be verified and formalized (for example, to Bluebook) before formal use.

9. Validity, Limitations, and Delimitations

Several limitations shape what the study can claim, and each is met by a design choice rather than left implicit. Symptom severity, confidence, and load are self-reported, so they are triangulated against behavioral measures, latency, avoidance, and instability, that do not depend on introspection. Risk attitudes stated in scenarios may diverge from real behavior and may be domain-specific (Weber et al., 2002), which is exactly why the battery spans several decision domains rather than one, surfacing that variation instead of hiding it. Recruitment is purposive and largely voluntary, which limits generalizability and is declared openly as a delimitation. Sleep and support are plausible confounders and are therefore measured as covariates. Finally, screening is not diagnosis; that boundary protects the study's non-clinical framing even as it limits the strength of any clinical claim, which the study in any case does not make.

10. Operational Definitions

Terms are defined as they are used in this study, to keep interpretation consistent and to prevent drift toward clinical meanings the study does not intend.

The postpartum period is taken as the window up to roughly twelve months after birth, which bounds eligibility, and matrescence names the developmental transition to motherhood across neurobiological, cognitive, and emotional change (Ghadimi & McCormack, 2025). Depressive symptom severity is a continuous score on the Edinburgh Postnatal Depression Scale (Cox et al., 1987), indexing intensity for analysis and never treated as a diagnosis or a cut-off label. Where the proposal speaks of rationality in the technical sense, it means the internal coherence of preferences, their consistency and transitivity, not an observer's approval of a choice or its outcome.

The behavioral terms follow from the instrument. Decision quality, as used here, is a descriptive profile of a decision across latency, avoidance, instability, confidence, and difficulty, and is explicitly not a judgment of whether a choice was correct. Decision latency is the time between a scenario prompt and the response; decision avoidance is the selection of a genuine defer or cannot-decide option; and choice instability is the reversal of an earlier choice when a scenario is re-presented later in the session. Confidence and perceived difficulty are self-rated certainty and effort, each on a 0 to 10 scale recorded immediately after a choice, while perceived cognitive load is the subjective mental workload for a block of scenarios, captured with NASA-TLX-style items (Hart & Staveland, 1988). An everyday-decision scenario, finally, is a short, realistic vignette ending in a choice, deliberately written without an objectively correct answer.

11. Assumptions, Scope, and Delimitations

11.1 Assumptions

The design rests on a few stated assumptions: that participants can report their experience and symptoms with reasonable accuracy; that the EPDS validly indexes symptom severity along a continuum for a community sample (Cox et al., 1987; Murray & Cox, 1990); that the everyday-decision scenarios approximate real decisions closely enough to elicit representative behavior; and that participants have the capacity to give informed consent, a capacity the study actively supports rather than presumes absent.

11.2 Scope

The study is bounded to women within approximately twelve months of birth, treats the topic behaviorally rather than clinically, and pursues a descriptive rather than causal aim. The dominant quantitative phase is cross-sectional.

11.3 Delimitations

By design, the study does not measure clinical diagnosis, decisional capacity, or child outcomes; it is not an intervention or treatment study; and it does not attempt causal inference. These boundaries are chosen deliberately to keep the work inside behavioral research and to protect participants.

12. Data Management and Analytical Plan

12.1 Data management

Data collection follows the principle of minimization: only what the analysis requires is collected. Contact information used for Phase 2 recruitment is stored separately from response data, responses are de-identified, and all files are encrypted at rest and in transit. A retention and destruction schedule is set in advance and approved by the Institutional Review Board. Because this is a behavioral study and not a clinical record, no protected health information is created, held, or shared.

12.2 Quantitative analysis

Phase 1 begins with descriptive statistics and distribution checks, proceeds to correlations among symptom severity and the decision characteristics, and then to multiple-regression models that include the planned covariates (infant age, sleep, support, prior history, education, income band). Results are reported with standardized effect sizes and confidence intervals rather than significance alone, and sensitivity analyses probe the influence of covariates and of any outliers. Missing data are handled with a pre-specified strategy documented in the analysis plan. Throughout, findings are described in associational language consistent with the descriptive aim.

12.3 Qualitative analysis

Phase 2 follows the six recursive movements of reflexive thematic analysis: familiarization with the data, generation of initial codes, construction of candidate themes, review of themes against the data, definition and naming of themes, and reporting (Braun & Clarke, 2006). An audit trail and a reflexive journal document interpretive decisions, and the analyst's own standpoint is treated as part of the analysis rather than a contaminant to be removed.

12.4 Integration

The strands are combined in a joint display that sets each Phase 1 finding beside the interview themes that confirm, expand, or contradict it. The display is read three ways: where accounts and numbers converge, where they diverge, and where interviews expand on a pattern the numbers could only outline. This structured comparison is the primary evidence for the integration research question.

13. Phased Timeline and Milestones

Durations are indicative and relative rather than fixed calendar dates, and they assume sequential dependency between phases.

Table 2. Indicative phased timeline.

14. Expected Contributions

14.1 To theory

The study joins two literatures that rarely meet: the cognitive account of depression and executive function (Rock et al., 2014; Roiser et al., 2012) and the decision-science account of how internal states shape choice (Kahneman & Tversky, 1979; Lerner et al., 2015; Weber et al., 2002). Applying that combined lens to the high-load naturalistic setting of matrescence (Ghadimi & McCormack, 2025) offers a characterized relationship where the field currently has mostly assumption.

14.2 To method

The study contributes a reusable, non-deficit everyday-scenario instrument and a worked example of using a screening scale as a continuous behavioral predictor without diagnostic labeling. The instrument's deliberate absence of correct answers is itself a methodological stance, keeping measurement clear of implied clinical judgment.

14.3 To practice

Decision-making under cognitive and affective load is central to the design of decision-support systems and information environments. A clearer description of where everyday decisions become effortful for a high-load population can inform how supportive tools, interfaces, and information are structured for people deciding under strain. This applied, information-design contribution is where the work speaks to practice, and it makes no clinical claim in doing so.

15. Anticipated Questions and Responses

These short exchanges anticipate the questions a committee or reviewer is most likely to raise, and state the study's position on each.

Q. If you use a depression screening scale, are you not effectively diagnosing participants?

A. No. The EPDS score is used only as a continuous predictor. No cut-off is applied to label anyone as depressed, and the study makes no clinical or diagnostic claim at any point.

Q. Why a mixed-methods design rather than a single clean quantitative study?

A. The aim is descriptive and relational. The quantitative strand shows the pattern; the qualitative strand explains it in participants' own terms. The joint display that integrates them is the study's central contribution, and neither strand alone would produce it.

Q. Why everyday scenarios instead of established laboratory tasks such as gambles or the Balloon Analog Risk Task?

A. Ecological validity for this population. Everyday choices are the phenomenon of interest, not an abstract proxy for it. The multi-domain scenario battery still captures risk, latency, avoidance, and instability while staying realistic and, importantly, free of any correct answer that could imply judgment.

Q. How does the design avoid the historical trap of pathologizing women's decisions through hormones?

A. Symptom severity is modeled as a continuous variable, never a switch that toggles a woman between rational and not. Altered patterns are framed as adaptation to be understood rather than deficit to be judged, and explicit non-deficit language rules plus a reflexivity statement hold that framing across instruments, coding, and reporting.

Q. Could these findings be misused, for example in custody or benefit determinations?

A. That risk is real and asymmetric, so it is pre-empted. The study reports only at the group level, states an explicit no-individual-inference caveat, and carries a misuse-limitation clause in both the consent form and the final report affirming that it cannot assess any individual's capacity, competence, or fitness.

Q. If symptoms can affect cognition, can participants truly give informed consent?

A. Capacity is presumed and actively supported through plain-language consent, comprehension checks, the right to pause or withdraw without penalty, and the option to re-consent. Defaulting to an assumption of incapacity would itself be an ethical breach and would wrongly exclude a population from research that concerns it.

Q. This is a doctoral project in information technology. Where is the business and technology relevance?

A. Decision-making under cognitive and affective load is foundational to decision-support systems and information design. The study's applied contribution is a clearer picture of where everyday decisions become effortful for high-load users, which informs how supportive tools and information environments should be structured. The contribution is to applied decision science and information design, not to clinical care.

Q. Is self-report not unreliable?

A. Self-report is triangulated with behavioral measures captured in the same session, including latency, avoidance, and instability, and then further contextualized by the Phase 2 interviews. The limitation is acknowledged openly rather than assumed away.

Q. Why restrict yourself to a descriptive aim rather than pursuing causation?

A. The cross-sectional, non-clinical design does not support causal claims, and overclaiming would be unsound both statistically and ethically. A well-characterized relationship, honestly bounded, is the appropriate and defensible contribution here.

Q. What is the concrete deliverable at the end of the study?

A. Three things: a characterized relationship between postpartum symptom severity and everyday decision characteristics, a participant-grounded explanation of that relationship via the joint display, and a reusable non-deficit scenario instrument that other researchers can adapt.

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